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| IAA IAA if( (vect = 'q' and nq >= k) or (vect <> 'q' and nq > k) ), IAA=ia; jaa=ja; mi=m; ni=n; icc=ic; jcc=jc iaa=ia+1; jaa=ja; mi=m-1; ni=n; icc=ic+1; jcc=jc; IAA = ia + ilo; jaa = ja+ilo-1 mi = ihi-ilo; ni = n; icc = ic + ilo; jcc = jc; if uplo = 'u', IAA = ia, jaa = ja+1, icc = ic, jcc = jc iaa = ia+1, jaa = ja; if( (vect = 'q' and nq >= k) or (vect <> 'q' and nq > k) ), IAA=ia; jaa=ja; mi=m; ni=n; icc=ic; jcc=jc iaa=ia+1; jaa=ja; mi=m-1; ni=n; icc=ic+1; jcc=jc; IAA = ia + ilo; jaa = ja+ilo-1 mi = ihi-ilo; ni = n; icc = ic + ilo; jcc = jc; if uplo = 'u', IAA = ia, jaa = ja+1, icc = ic, jcc = jc iaa = ia+1, jaa = ja; if( (vect = 'q' and nq >= k) or (vect <> 'q' and nq > k) ), IAA=ia; jaa=ja; mi=m; ni=n; icc=ic; jcc=jc iaa=ia+1; jaa=ja; mi=m-1; ni=n; icc=ic+1; jcc=jc; IAA = ia + ilo; jaa = ja+ilo-1 mi = ihi-ilo; ni = n; icc = ic + ilo; jcc = jc; if uplo = 'u', IAA = ia, jaa = ja+1, icc = ic, jcc = jc iaa = ia+1, jaa = ja; if( (vect = 'q' and nq >= k) or (vect <> 'q' and nq > k) ), IAA=ia; jaa=ja; mi=m; ni=n; icc=ic; jcc=jc iaa=ia+1; jaa=ja; mi=m-1; ni=n; icc=ic+1; jcc=jc; IAA = ia + ilo; jaa = ja+ilo-1 mi = ihi-ilo; ni = n; icc = ic + ilo; jcc = jc; if uplo = 'u', IAA = ia, jaa = ja+1, icc = ic, jcc = jc iaa = ia+1, jaa = ja; |
| IACOL IACOL iarow = indxg2p( ia, nb, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb, mycol, csrc_a, npcol ) nqa0 = numroc( n+iroffa, nb, mycol, iacol, npcol ). iarow = indxg2p( ia, nb, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb, mycol, csrc_a, npcol ) nqa0 = numroc( n+icoffa, nb, mycol, iacol, npcol ). iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nq0 = numroc( n+icoff, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nq0 = numroc( n+icoff, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nqa0 = numroc( n+icoffa, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nq0 = numroc( n+icoff, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nq0 = numroc( n+icoff, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nq0 = numroc( n+icoff, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nq0 = numroc( n+icoff, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nq0 = numroc( n+icoff, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nq0 = numroc( n+icoff, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nq0 = numroc( n+icoff, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) mqa0 = numroc( m+icoffa, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nqa0 = numroc( n+icoffa, nb_a, mycol, iacol, npcol ), np = numroc( n, nb, myrow, iarow, nprow ) nq = numroc( n, nb, mycol, IACOL, npcol iwork (local workspace/output) integer array, dimension (liwork) nq = numroc( n+mod( ia-1, nb_y ), nb_y, mycol, IACOL, npcol iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nq0 = numroc( n+icoffa, nb_a, mycol, iacol, npcol ), gather the result on process (iarow,IACOL) gather the result on process (iarow,IACOL) iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nq0 = numroc( n+icoff, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nq0 = numroc( n+icoff, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nqa0 = numroc( n+icoffa, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nqa0 = numroc( n+icoffa, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nqa0 = numroc( n+icoffa, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nqa0 = numroc( n+icoffa, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nqa0 = numroc( n+icoffa, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nqa0 = numroc( n+icoffa, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nqa0 = numroc( n+icoffa, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nqa0 = numroc( n+icoffa, nb_a, mycol, iacol, npcol ), iarow = indxg2p( iaa, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( jaa, nb_a, mycol, csrc_a, npcol ) npa0 = numroc( ni+iroffa, mb_a, myrow, iarow, nprow ), if side = 'r', ( nb_a.eq.nb_c .and. icoffa.eq.icoffc .and. IACOL.eq.iccol ===================================================================== iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) if side = 'r', ( nb_a.eq.nb_c .and. icoffa.eq.icoffc .and. IACOL.eq.iccol ===================================================================== if side = 'r', ( nb_a.eq.nb_c .and. icoffa.eq.icoffc .and. IACOL.eq.iccol ===================================================================== iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) iarow = indxg2p( ia, nb, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb, mycol, csrc_a, npcol ) nqa0 = numroc( n+iroffa, nb, mycol, iacol, npcol ). iarow = indxg2p( ia, nb, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb, mycol, csrc_a, npcol ) nqa0 = numroc( n+icoffa, nb, mycol, iacol, npcol ). iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nq0 = numroc( n+icoff, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nq0 = numroc( n+icoff, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nqa0 = numroc( n+icoffa, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nq0 = numroc( n+icoff, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nq0 = numroc( n+icoff, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nq0 = numroc( n+icoff, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nq0 = numroc( n+icoff, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nq0 = numroc( n+icoff, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nq0 = numroc( n+icoff, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nq0 = numroc( n+icoff, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) mqa0 = numroc( m+icoffa, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nqa0 = numroc( n+icoffa, nb_a, mycol, iacol, npcol ), nq = numroc( n+mod( ia-1, nb_y ), nb_y, mycol, IACOL, npcol iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nq0 = numroc( n+icoffa, nb_a, mycol, iacol, npcol ), gather the result on process (iarow,IACOL) iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nq0 = numroc( n+icoff, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nqa0 = numroc( n+icoffa, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nqa0 = numroc( n+icoffa, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nqa0 = numroc( n+icoffa, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nqa0 = numroc( n+icoffa, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nqa0 = numroc( n+icoffa, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nqa0 = numroc( n+icoffa, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nqa0 = numroc( n+icoffa, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nqa0 = numroc( n+icoffa, nb_a, mycol, iacol, npcol ), iarow = indxg2p( iaa, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( jaa, nb_a, mycol, csrc_a, npcol ) npa0 = numroc( ni+iroffa, mb_a, myrow, iarow, nprow ), if side = 'r', ( nb_a.eq.nb_c .and. icoffa.eq.icoffc .and. IACOL.eq.iccol ===================================================================== iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) if side = 'r', ( nb_a.eq.nb_c .and. icoffa.eq.icoffc .and. IACOL.eq.iccol ===================================================================== if side = 'r', ( nb_a.eq.nb_c .and. icoffa.eq.icoffc .and. IACOL.eq.iccol ===================================================================== iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) np = numroc( n, nb, myrow, iarow, nprow ) nq = numroc( n, nb, mycol, IACOL, npcol if lwork = -1, the lwork is global input and a workspace iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nq0 = numroc( n+icoff, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, nb, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb, mycol, csrc_a, npcol ) nqa0 = numroc( n+iroffa, nb, mycol, iacol, npcol ). iarow = indxg2p( ia, nb, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb, mycol, csrc_a, npcol ) nqa0 = numroc( n+icoffa, nb, mycol, iacol, npcol ). iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nq0 = numroc( n+icoff, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nq0 = numroc( n+icoff, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nqa0 = numroc( n+icoffa, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nq0 = numroc( n+icoff, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nq0 = numroc( n+icoff, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nq0 = numroc( n+icoff, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nq0 = numroc( n+icoff, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nq0 = numroc( n+icoff, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nq0 = numroc( n+icoff, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nq0 = numroc( n+icoff, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) mqa0 = numroc( m+icoffa, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nqa0 = numroc( n+icoffa, nb_a, mycol, iacol, npcol ), nq = numroc( n+mod( ia-1, nb_y ), nb_y, mycol, IACOL, npcol iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nq0 = numroc( n+icoffa, nb_a, mycol, iacol, npcol ), gather the result on process (iarow,IACOL) iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nq0 = numroc( n+icoff, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nqa0 = numroc( n+icoffa, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nqa0 = numroc( n+icoffa, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nqa0 = numroc( n+icoffa, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nqa0 = numroc( n+icoffa, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nqa0 = numroc( n+icoffa, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nqa0 = numroc( n+icoffa, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nqa0 = numroc( n+icoffa, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nqa0 = numroc( n+icoffa, nb_a, mycol, iacol, npcol ), iarow = indxg2p( iaa, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( jaa, nb_a, mycol, csrc_a, npcol ) npa0 = numroc( ni+iroffa, mb_a, myrow, iarow, nprow ), if side = 'r', ( nb_a.eq.nb_c .and. icoffa.eq.icoffc .and. IACOL.eq.iccol ===================================================================== iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) if side = 'r', ( nb_a.eq.nb_c .and. icoffa.eq.icoffc .and. IACOL.eq.iccol ===================================================================== if side = 'r', ( nb_a.eq.nb_c .and. icoffa.eq.icoffc .and. IACOL.eq.iccol ===================================================================== iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) np = numroc( n, nb, myrow, iarow, nprow ) nq = numroc( n, nb, mycol, IACOL, npcol if lwork = -1, the lwork is global input and a workspace iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nq0 = numroc( n+icoff, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, nb, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb, mycol, csrc_a, npcol ) nqa0 = numroc( n+iroffa, nb, mycol, iacol, npcol ). iarow = indxg2p( ia, nb, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb, mycol, csrc_a, npcol ) nqa0 = numroc( n+icoffa, nb, mycol, iacol, npcol ). iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nq0 = numroc( n+icoff, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nq0 = numroc( n+icoff, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nqa0 = numroc( n+icoffa, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nq0 = numroc( n+icoff, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nq0 = numroc( n+icoff, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nq0 = numroc( n+icoff, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nq0 = numroc( n+icoff, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nq0 = numroc( n+icoff, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nq0 = numroc( n+icoff, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nq0 = numroc( n+icoff, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) mqa0 = numroc( m+icoffa, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nqa0 = numroc( n+icoffa, nb_a, mycol, iacol, npcol ), np = numroc( n, nb, myrow, iarow, nprow ) nq = numroc( n, nb, mycol, IACOL, npcol iwork (local workspace/output) integer array, dimension (liwork) nq = numroc( n+mod( ia-1, nb_y ), nb_y, mycol, IACOL, npcol iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nq0 = numroc( n+icoffa, nb_a, mycol, iacol, npcol ), gather the result on process (iarow,IACOL) gather the result on process (iarow,IACOL) iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nq0 = numroc( n+icoff, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nq0 = numroc( n+icoff, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nqa0 = numroc( n+icoffa, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nqa0 = numroc( n+icoffa, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nqa0 = numroc( n+icoffa, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nqa0 = numroc( n+icoffa, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nqa0 = numroc( n+icoffa, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nqa0 = numroc( n+icoffa, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nqa0 = numroc( n+icoffa, nb_a, mycol, iacol, npcol ), iarow = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) nqa0 = numroc( n+icoffa, nb_a, mycol, iacol, npcol ), iarow = indxg2p( iaa, mb_a, myrow, rsrc_a, nprow ), IACOL = indxg2p( jaa, nb_a, mycol, csrc_a, npcol ) npa0 = numroc( ni+iroffa, mb_a, myrow, iarow, nprow ), if side = 'r', ( nb_a.eq.nb_c .and. icoffa.eq.icoffc .and. IACOL.eq.iccol ===================================================================== iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) if side = 'r', ( nb_a.eq.nb_c .and. icoffa.eq.icoffc .and. IACOL.eq.iccol ===================================================================== if side = 'r', ( nb_a.eq.nb_c .and. icoffa.eq.icoffc .and. IACOL.eq.iccol ===================================================================== iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), IACOL = indxg2p( ja, nb_a, mycol, csrc_a, npcol ) |
| IAF IAF IAF (global input) intege row of sub( af ). equilibrated before it is factored. = 'f': on entry, af(IAF:iaf+n-1,jaf:jaf+n-1) and ipiv con if equed is not 'n', the matrix IAF (global input) intege row of sub( af ). IAF (global input) intege row of sub( af ). IAF (global input) intege row of sub( af ). equilibrated before it is factored. = 'f': on entry, af(IAF:iaf+n-1,jaf:jaf+n-1) and ipiv con if equed is not 'n', the matrix IAF (global input) intege row of sub( af ). IAF (global input) intege row of sub( af ). IAF (global input) intege row of sub( af ). equilibrated before it is factored. = 'f': on entry, af(IAF:iaf+n-1,jaf:jaf+n-1) and ipiv con if equed is not 'n', the matrix IAF (global input) intege row of sub( af ). IAF (global input) intege row of sub( af ). IAF (global input) intege row of sub( af ). equilibrated before it is factored. = 'f': on entry, af(IAF:iaf+n-1,jaf:jaf+n-1) and ipiv con if equed is not 'n', the matrix IAF (global input) intege row of sub( af ). IAF (global input) intege row of sub( af ). |
| IAFIRST IAFIRST node (IAFIRST,jafirst) owns a(1,1 node (IAFIRST,jafirst) owns a(1,1 node (IAFIRST,jafirst) owns a(1,1 node (IAFIRST,jafirst) owns a(1,1 |
| iam iam zin (local input) real array, dimension ( ldzi, nvs(iam) in one process. each process holds a contiguous set of zin (local input) double precision array, dimension ( ldzi, nvs(iam) in one process. each process holds a contiguous set of zin (local input) real array, dimension ( ldzi, nvs(iam) in one process. each process holds a contiguous set of zin (local input) double precision array, dimension ( ldzi, nvs(iam) in one process. each process holds a contiguous set of |
| IAROW IAROW where nb = mb_a = nb_a, iroffa = mod( ia-1, nb ) IAROW = indxg2p( ia, nb, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, nb, myrow, iarow, nprow ), iroffa = mod( ia-1, nb ), icoffa = mod( ja-1, nb ), IAROW = indxg2p( ia, nb, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, nb, myrow, iarow, nprow ), where nb = mb_a = nb_a, iroffa = mod( ia-1, nb ), IAROW = indxg2p( ia, nb, myrow, rsrc_a, nprow ) icoffa = mod( ja-1, nb ), ioff = mod( ia+ilo-2, nb ), IAROW = indxg2p( ia, nb, myrow, rsrc_a, nprow ) ilrow = indxg2p( ia+ilo-1, nb, myrow, rsrc_a, nprow ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) npa0 = numroc( n+iroffa, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), ( mb_a.eq.nb_a.eq.mb_z .and. iroffa.eq.iroffz .and. iroffa.eq.0 .and. IAROW.eq.izrow iroffa = mod( ia-1, mb_a ) and icoffa = mod( ja-1, nb_a ). lrwork >= 1 + 9*n + 3*np*nq, np = numroc( n, nb, myrow, IAROW, nprow ( mb_a.eq.nb_a.eq.mb_z .and. iroffa.eq.iroffz .and. iroffa.eq.0 .and. IAROW.eq.izrow iroffa = mod( ia-1, mb_a ) and icoffa = mod( ja-1, nb_a ). where nb = mb_a = nb_a, np = numroc( n, nb, myrow, IAROW, nprow ) iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), gather the result on process (IAROW,iacol) gather the result on process (IAROW,iacol) iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), if side = 'l', ( mb_a.eq.mb_c .and. iroffa.eq.iroffc .and. IAROW.eq.icrow ( mb_a.eq.nb_c .and. iroffa.eq.icoffc ) if side = 'l', ( mb_a.eq.mb_c .and. iroffa.eq.iroffc .and. IAROW.eq.icrow ( mb_a.eq.nb_c .and. iroffa.eq.icoffc ) iroffa = mod( iaa-1, mb_a ), icoffa = mod( jaa-1, nb_a ), IAROW = indxg2p( iaa, mb_a, myrow, rsrc_a, nprow ) mqa0 = numroc( mi+icoffa, nb_a, mycol, iacol, npcol ), iroffa = mod( iaa-1, mb_a ), icoffa = mod( jaa-1, nb_a ), IAROW = indxg2p( iaa, mb_a, myrow, rsrc_a, nprow ) iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) iroffa = mod( iaa-1, mb_a ), icoffa = mod( jaa-1, nb_a ), IAROW = indxg2p( iaa, mb_a, myrow, rsrc_a, nprow ) where nb = mb_a = nb_a, iroffa = mod( ia-1, nb ) IAROW = indxg2p( ia, nb, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, nb, myrow, iarow, nprow ), iroffa = mod( ia-1, nb ), icoffa = mod( ja-1, nb ), IAROW = indxg2p( ia, nb, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, nb, myrow, iarow, nprow ), where nb = mb_a = nb_a, iroffa = mod( ia-1, nb ), IAROW = indxg2p( ia, nb, myrow, rsrc_a, nprow ) icoffa = mod( ja-1, nb ), ioff = mod( ia+ilo-2, nb ), IAROW = indxg2p( ia, nb, myrow, rsrc_a, nprow ) ilrow = indxg2p( ia+ilo-1, nb, myrow, rsrc_a, nprow ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) npa0 = numroc( n+iroffa, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), gather the result on process (IAROW,iacol) where np = numroc( n, nb, myrow, IAROW, nprow ) iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), if side = 'l', ( mb_a.eq.mb_c .and. iroffa.eq.iroffc .and. IAROW.eq.icrow ( mb_a.eq.nb_c .and. iroffa.eq.icoffc ) if side = 'l', ( mb_a.eq.mb_c .and. iroffa.eq.iroffc .and. IAROW.eq.icrow ( mb_a.eq.nb_c .and. iroffa.eq.icoffc ) iroffa = mod( iaa-1, mb_a ), icoffa = mod( jaa-1, nb_a ), IAROW = indxg2p( iaa, mb_a, myrow, rsrc_a, nprow ) mqa0 = numroc( mi+icoffa, nb_a, mycol, iacol, npcol ), iroffa = mod( iaa-1, mb_a ), icoffa = mod( jaa-1, nb_a ), IAROW = indxg2p( iaa, mb_a, myrow, rsrc_a, nprow ) iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) iroffa = mod( iaa-1, mb_a ), icoffa = mod( jaa-1, nb_a ), IAROW = indxg2p( iaa, mb_a, myrow, rsrc_a, nprow ) ( mb_a.eq.nb_a.eq.mb_z .and. iroffa.eq.iroffz .and. iroffa.eq.0 .and. IAROW.eq.izrow iroffa = mod( ia-1, mb_a ) and icoffa = mod( ja-1, nb_a ). trilwmin = 3*n + max( nb*( np+1 ), 3*nb ) np = numroc( n, nb, myrow, IAROW, nprow ( mb_a.eq.nb_a.eq.mb_z .and. iroffa.eq.iroffz .and. iroffa.eq.0 .and. IAROW.eq.izrow iroffa = mod( ia-1, mb_a ) and icoffa = mod( ja-1, nb_a ). where nb = mb_a = nb_a, np = numroc( n, nb, myrow, IAROW, nprow ) iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), where nb = mb_a = nb_a, iroffa = mod( ia-1, nb ) IAROW = indxg2p( ia, nb, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, nb, myrow, iarow, nprow ), iroffa = mod( ia-1, nb ), icoffa = mod( ja-1, nb ), IAROW = indxg2p( ia, nb, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, nb, myrow, iarow, nprow ), where nb = mb_a = nb_a, iroffa = mod( ia-1, nb ), IAROW = indxg2p( ia, nb, myrow, rsrc_a, nprow ) icoffa = mod( ja-1, nb ), ioff = mod( ia+ilo-2, nb ), IAROW = indxg2p( ia, nb, myrow, rsrc_a, nprow ) ilrow = indxg2p( ia+ilo-1, nb, myrow, rsrc_a, nprow ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) npa0 = numroc( n+iroffa, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), gather the result on process (IAROW,iacol) where np = numroc( n, nb, myrow, IAROW, nprow ) iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), if side = 'l', ( mb_a.eq.mb_c .and. iroffa.eq.iroffc .and. IAROW.eq.icrow ( mb_a.eq.nb_c .and. iroffa.eq.icoffc ) if side = 'l', ( mb_a.eq.mb_c .and. iroffa.eq.iroffc .and. IAROW.eq.icrow ( mb_a.eq.nb_c .and. iroffa.eq.icoffc ) iroffa = mod( iaa-1, mb_a ), icoffa = mod( jaa-1, nb_a ), IAROW = indxg2p( iaa, mb_a, myrow, rsrc_a, nprow ) mqa0 = numroc( mi+icoffa, nb_a, mycol, iacol, npcol ), iroffa = mod( iaa-1, mb_a ), icoffa = mod( jaa-1, nb_a ), IAROW = indxg2p( iaa, mb_a, myrow, rsrc_a, nprow ) iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) iroffa = mod( iaa-1, mb_a ), icoffa = mod( jaa-1, nb_a ), IAROW = indxg2p( iaa, mb_a, myrow, rsrc_a, nprow ) ( mb_a.eq.nb_a.eq.mb_z .and. iroffa.eq.iroffz .and. iroffa.eq.0 .and. IAROW.eq.izrow iroffa = mod( ia-1, mb_a ) and icoffa = mod( ja-1, nb_a ). trilwmin = 3*n + max( nb*( np+1 ), 3*nb ) np = numroc( n, nb, myrow, IAROW, nprow ( mb_a.eq.nb_a.eq.mb_z .and. iroffa.eq.iroffz .and. iroffa.eq.0 .and. IAROW.eq.izrow iroffa = mod( ia-1, mb_a ) and icoffa = mod( ja-1, nb_a ). where nb = mb_a = nb_a, np = numroc( n, nb, myrow, IAROW, nprow ) iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), where nb = mb_a = nb_a, iroffa = mod( ia-1, nb ) IAROW = indxg2p( ia, nb, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, nb, myrow, iarow, nprow ), iroffa = mod( ia-1, nb ), icoffa = mod( ja-1, nb ), IAROW = indxg2p( ia, nb, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, nb, myrow, iarow, nprow ), where nb = mb_a = nb_a, iroffa = mod( ia-1, nb ), IAROW = indxg2p( ia, nb, myrow, rsrc_a, nprow ) icoffa = mod( ja-1, nb ), ioff = mod( ia+ilo-2, nb ), IAROW = indxg2p( ia, nb, myrow, rsrc_a, nprow ) ilrow = indxg2p( ia+ilo-1, nb, myrow, rsrc_a, nprow ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) npa0 = numroc( n+iroffa, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), ( mb_a.eq.nb_a.eq.mb_z .and. iroffa.eq.iroffz .and. iroffa.eq.0 .and. IAROW.eq.izrow iroffa = mod( ia-1, mb_a ) and icoffa = mod( ja-1, nb_a ). lrwork >= 1 + 9*n + 3*np*nq, np = numroc( n, nb, myrow, IAROW, nprow ( mb_a.eq.nb_a.eq.mb_z .and. iroffa.eq.iroffz .and. iroffa.eq.0 .and. IAROW.eq.izrow iroffa = mod( ia-1, mb_a ) and icoffa = mod( ja-1, nb_a ). where nb = mb_a = nb_a, np = numroc( n, nb, myrow, IAROW, nprow ) iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), gather the result on process (IAROW,iacol) gather the result on process (IAROW,iacol) iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), if side = 'l', ( mb_a.eq.mb_c .and. iroffa.eq.iroffc .and. IAROW.eq.icrow ( mb_a.eq.nb_c .and. iroffa.eq.icoffc ) if side = 'l', ( mb_a.eq.mb_c .and. iroffa.eq.iroffc .and. IAROW.eq.icrow ( mb_a.eq.nb_c .and. iroffa.eq.icoffc ) iroffa = mod( iaa-1, mb_a ), icoffa = mod( jaa-1, nb_a ), IAROW = indxg2p( iaa, mb_a, myrow, rsrc_a, nprow ) mqa0 = numroc( mi+icoffa, nb_a, mycol, iacol, npcol ), iroffa = mod( iaa-1, mb_a ), icoffa = mod( jaa-1, nb_a ), IAROW = indxg2p( iaa, mb_a, myrow, rsrc_a, nprow ) iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), IAROW = indxg2p( ia, mb_a, myrow, rsrc_a, nprow ) iroffa = mod( iaa-1, mb_a ), icoffa = mod( jaa-1, nb_a ), IAROW = indxg2p( iaa, mb_a, myrow, rsrc_a, nprow ) |
| iax iax h * sub( x ) = h * ( x(iax,jax) ) = ( alpha ), h' * h = i h * sub( x ) = h * ( x(iax,jax) ) = ( alpha ), h' * h = i h * sub( x ) = h * ( x(iax,jax) ) = ( alpha ), h' * h = i h * sub( x ) = h * ( x(iax,jax) ) = ( alpha ), h' * h = i |
| IB1 IB1 nn2 (global output) integer, the order of matrix q2, (pdlaed1). IB1 (global output) integer, pointeur on q1, (pdlaed1) nn2 (global output) integer, the order of matrix q2, (pslaed1). IB1 (global output) integer, pointeur on q1, (pslaed1) |
| IB2 IB2 ib1 (global output) integer, pointeur on q1, (pdlaed1). IB2 (global output) integer, pointeur on q2, (pdlaed1) ===================================================================== ib1 (global output) integer, pointeur on q1, (pslaed1). IB2 (global output) integer, pointeur on q2, (pslaed1) ===================================================================== |
| IBCOL IBCOL ibrow = indxg2p( ib, mb_b, myrow, rsrc_b, nprow ), IBCOL = indxg2p( jb, nb_b, mycol, csrc_b, npcol ) npb0 = numroc( n+iroffb, mb_b, myrow, ibrow, nprow ), ibrow = indxg2p( ib, mb_b, myrow, rsrc_b, nprow ), IBCOL = indxg2p( jb, nb_b, mycol, csrc_b, npcol ) pqb0 = numroc( p+icoffb, nb_b, mycol, ibcol, npcol ), ibrow = indxg2p( ib, mb_b, myrow, rsrc_b, nprow ), IBCOL = indxg2p( jb, nb_b, mycol, csrc_b, npcol ) nqb0 = numroc( n+icoffb, nb_b, mycol, ibcol, npcol ), ibrow = indxg2p( ib, mb_b, myrow, rsrc_b, nprow ), IBCOL = indxg2p( jb, nb_b, mycol, csrc_b, npcol ) npb0 = numroc( n+iroffb, mb_b, myrow, ibrow, nprow ), ibrow = indxg2p( ib, mb_b, myrow, rsrc_b, nprow ), IBCOL = indxg2p( jb, nb_b, mycol, csrc_b, npcol ) pqb0 = numroc( p+icoffb, nb_b, mycol, ibcol, npcol ), ibrow = indxg2p( ib, mb_b, myrow, rsrc_b, nprow ), IBCOL = indxg2p( jb, nb_b, mycol, csrc_b, npcol ) nqb0 = numroc( n+icoffb, nb_b, mycol, ibcol, npcol ), ibrow = indxg2p( ib, mb_b, myrow, rsrc_b, nprow ), IBCOL = indxg2p( jb, nb_b, mycol, csrc_b, npcol ) npb0 = numroc( n+iroffb, mb_b, myrow, ibrow, nprow ), ibrow = indxg2p( ib, mb_b, myrow, rsrc_b, nprow ), IBCOL = indxg2p( jb, nb_b, mycol, csrc_b, npcol ) pqb0 = numroc( p+icoffb, nb_b, mycol, ibcol, npcol ), ibrow = indxg2p( ib, mb_b, myrow, rsrc_b, nprow ), IBCOL = indxg2p( jb, nb_b, mycol, csrc_b, npcol ) nqb0 = numroc( n+icoffb, nb_b, mycol, ibcol, npcol ), ibrow = indxg2p( ib, mb_b, myrow, rsrc_b, nprow ), IBCOL = indxg2p( jb, nb_b, mycol, csrc_b, npcol ) npb0 = numroc( n+iroffb, mb_b, myrow, ibrow, nprow ), ibrow = indxg2p( ib, mb_b, myrow, rsrc_b, nprow ), IBCOL = indxg2p( jb, nb_b, mycol, csrc_b, npcol ) pqb0 = numroc( p+icoffb, nb_b, mycol, ibcol, npcol ), ibrow = indxg2p( ib, mb_b, myrow, rsrc_b, nprow ), IBCOL = indxg2p( jb, nb_b, mycol, csrc_b, npcol ) nqb0 = numroc( n+icoffb, nb_b, mycol, ibcol, npcol ), |
| IBLK IBLK the main loop begins here. i is the loop index and decreases from ihi to ilo in steps of our schur block size (<=2*IBLK). eac and columns l to i. eigenvalues i+1 to ihi have already the main loop begins here. i is the loop index and decreases from ihi to ilo in steps of our schur block size (<=2*IBLK). eac and columns l to i. eigenvalues i+1 to ihi have already the main loop begins here. i is the loop index and decreases from ihi to ilo in steps of our schur block size (<=2*IBLK). eac and columns l to i. eigenvalues i+1 to ihi have already the main loop begins here. i is the loop index and decreases from ihi to ilo in steps of our schur block size (<=2*IBLK). eac and columns l to i. eigenvalues i+1 to ihi have already |
| IBLOCK IBLOCK IBLOCK (global input) integer array, dimension (n eigenvalues in w -- 1 for eigenvalues belonging to the specifies the order in which the eigenvalues and their block numbers are stored in w and IBLOCK split-off block (see iblock, isplit) and IBLOCK (global input) integer array, dimension (n eigenvalues in w -- 1 for eigenvalues belonging to the specifies the order in which the eigenvalues and their block numbers are stored in w and IBLOCK split-off block (see iblock, isplit) and IBLOCK (global input) integer array, dimension (n eigenvalues in w -- 1 for eigenvalues belonging to the IBLOCK (global input) integer array, dimension (n eigenvalues in w -- 1 for eigenvalues belonging to the |
| IBROW IBROW iroffb = mod( ib-1, mb_b ), icoffb = mod( jb-1, nb_b ), IBROW = indxg2p( ib, mb_b, myrow, rsrc_b, nprow ) mpb0 = numroc( m+iroffb, mb_b, myrow, ibrow, nprow ), iroffb = mod( ib-1, mb_b ), icoffb = mod( jb-1, nb_b ), IBROW = indxg2p( ib, mb_b, myrow, rsrc_b, nprow ) npb0 = numroc( n+iroffb, mb_b, myrow, ibrow, nprow ), iroffb = mod( ib-1, mb_b ), icoffb = mod( jb-1, nb_b ), IBROW = indxg2p( ib, mb_b, myrow, rsrc_b, nprow ) ppb0 = numroc( p+iroffb, mb_b, myrow, ibrow, nprow ), iroffb = mod( ib-1, mb_b ), icoffb = mod( jb-1, nb_b ), IBROW = indxg2p( ib, mb_b, myrow, rsrc_b, nprow ) mpb0 = numroc( m+iroffb, mb_b, myrow, ibrow, nprow ), iroffb = mod( ib-1, mb_b ), icoffb = mod( jb-1, nb_b ), IBROW = indxg2p( ib, mb_b, myrow, rsrc_b, nprow ) npb0 = numroc( n+iroffb, mb_b, myrow, ibrow, nprow ), iroffb = mod( ib-1, mb_b ), icoffb = mod( jb-1, nb_b ), IBROW = indxg2p( ib, mb_b, myrow, rsrc_b, nprow ) ppb0 = numroc( p+iroffb, mb_b, myrow, ibrow, nprow ), iroffb = mod( ib-1, mb_b ), icoffb = mod( jb-1, nb_b ), IBROW = indxg2p( ib, mb_b, myrow, rsrc_b, nprow ) mpb0 = numroc( m+iroffb, mb_b, myrow, ibrow, nprow ), iroffb = mod( ib-1, mb_b ), icoffb = mod( jb-1, nb_b ), IBROW = indxg2p( ib, mb_b, myrow, rsrc_b, nprow ) npb0 = numroc( n+iroffb, mb_b, myrow, ibrow, nprow ), iroffb = mod( ib-1, mb_b ), icoffb = mod( jb-1, nb_b ), IBROW = indxg2p( ib, mb_b, myrow, rsrc_b, nprow ) ppb0 = numroc( p+iroffb, mb_b, myrow, ibrow, nprow ), iroffb = mod( ib-1, mb_b ), icoffb = mod( jb-1, nb_b ), IBROW = indxg2p( ib, mb_b, myrow, rsrc_b, nprow ) mpb0 = numroc( m+iroffb, mb_b, myrow, ibrow, nprow ), iroffb = mod( ib-1, mb_b ), icoffb = mod( jb-1, nb_b ), IBROW = indxg2p( ib, mb_b, myrow, rsrc_b, nprow ) npb0 = numroc( n+iroffb, mb_b, myrow, ibrow, nprow ), iroffb = mod( ib-1, mb_b ), icoffb = mod( jb-1, nb_b ), IBROW = indxg2p( ib, mb_b, myrow, rsrc_b, nprow ) ppb0 = numroc( p+iroffb, mb_b, myrow, ibrow, nprow ), |
| IBTYPE IBTYPE if IBTYPE = 1, the problem is sub( a )*x = lambda*sub( b )*x inv(l)*sub( a )*inv(l**h) if IBTYPE = 1, the problem is sub( a )*x = lambda*sub( b )*x inv(l)*sub( a )*inv(l**h) IBTYPE (global input) intege = 1: sub( a )*x = (lambda)*sub( b )*x pchengst calls pchegst when uplo='u', hence pchengst provides improved performance only when uplo='l', IBTYPE=1 pchengst also calls pchegst when insufficient workspace is if IBTYPE = 1, the problem is sub( a )*x = lambda*sub( b )*x inv(l)*sub( a )*inv(l**t) if IBTYPE = 1, the problem is sub( a )*x = lambda*sub( b )*x inv(l)*sub( a )*inv(l**t) IBTYPE (global input) intege = 1: sub( a )*x = (lambda)*sub( b )*x pdsyngst calls pdhegst when uplo='u', hence pdhengst provides improved performance only when uplo='l', IBTYPE=1 pdsyngst also calls pdhegst when insufficient workspace is if IBTYPE = 1, the problem is sub( a )*x = lambda*sub( b )*x inv(l)*sub( a )*inv(l**t) if IBTYPE = 1, the problem is sub( a )*x = lambda*sub( b )*x inv(l)*sub( a )*inv(l**t) IBTYPE (global input) intege = 1: sub( a )*x = (lambda)*sub( b )*x pssyngst calls pshegst when uplo='u', hence pshengst provides improved performance only when uplo='l', IBTYPE=1 pssyngst also calls pshegst when insufficient workspace is if IBTYPE = 1, the problem is sub( a )*x = lambda*sub( b )*x inv(l)*sub( a )*inv(l**h) if IBTYPE = 1, the problem is sub( a )*x = lambda*sub( b )*x inv(l)*sub( a )*inv(l**h) IBTYPE (global input) intege = 1: sub( a )*x = (lambda)*sub( b )*x pzhengst calls pzhegst when uplo='u', hence pzhengst provides improved performance only when uplo='l', IBTYPE=1 pzhengst also calls pzhegst when insufficient workspace is |
| IBULGE IBULGE IBULGE is the number of bulges going so fa IBULGE is the number of bulges going so fa IBULGE is the number of bulges going so fa IBULGE is the number of bulges going so fa |
| ICC ICC if( (vect = 'q' and nq >= k) or (vect <> 'q' and nq > k) ), iaa=ia; jaa=ja; mi=m; ni=n; ICC=ic; jcc=jc iaa=ia+1; jaa=ja; mi=m-1; ni=n; icc=ic+1; jcc=jc; if side = 'l', mi = ihi-ilo; ni = n; ICC = ic + ilo; jcc = jc nb_a * nb_a if uplo = 'u', iaa = ia, jaa = ja+1, ICC = ic, jcc = jc iaa = ia+1, jaa = ja; if( (vect = 'q' and nq >= k) or (vect <> 'q' and nq > k) ), iaa=ia; jaa=ja; mi=m; ni=n; ICC=ic; jcc=jc iaa=ia+1; jaa=ja; mi=m-1; ni=n; icc=ic+1; jcc=jc; if side = 'l', mi = ihi-ilo; ni = n; ICC = ic + ilo; jcc = jc nb_a * nb_a if uplo = 'u', iaa = ia, jaa = ja+1, ICC = ic, jcc = jc iaa = ia+1, jaa = ja; if( (vect = 'q' and nq >= k) or (vect <> 'q' and nq > k) ), iaa=ia; jaa=ja; mi=m; ni=n; ICC=ic; jcc=jc iaa=ia+1; jaa=ja; mi=m-1; ni=n; icc=ic+1; jcc=jc; if side = 'l', mi = ihi-ilo; ni = n; ICC = ic + ilo; jcc = jc nb_a * nb_a if uplo = 'u', iaa = ia, jaa = ja+1, ICC = ic, jcc = jc iaa = ia+1, jaa = ja; if( (vect = 'q' and nq >= k) or (vect <> 'q' and nq > k) ), iaa=ia; jaa=ja; mi=m; ni=n; ICC=ic; jcc=jc iaa=ia+1; jaa=ja; mi=m-1; ni=n; icc=ic+1; jcc=jc; if side = 'l', mi = ihi-ilo; ni = n; ICC = ic + ilo; jcc = jc nb_a * nb_a if uplo = 'u', iaa = ia, jaa = ja+1, ICC = ic, jcc = jc iaa = ia+1, jaa = ja; |
| ICCOL ICCOL send v and tau to the process column ICCOL icrow = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ), ICCOL = indxg2p( jc, nb_c, mycol, csrc_c, npcol ) npc0 = numroc( n+icoffc, mb_c, myrow, icrow, nprow ), send v and tau to the process column ICCOL icrow = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ), ICCOL = indxg2p( jc, nb_c, mycol, csrc_c, npcol ) npc0 = numroc( n+icoffc, mb_c, myrow, icrow, nprow ), icrow = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ), ICCOL = indxg2p( jc, nb_c, mycol, csrc_c, npcol ) nqc0 = numroc( n+icoffc, nb_c, mycol, iccol, npcol ), icrow = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ), ICCOL = indxg2p( jc, nb_c, mycol, csrc_c, npcol ) nqc0 = numroc( n+icoffc, nb_c, mycol, iccol, npcol ), icrow = indxg2p( icc, mb_c, myrow, rsrc_c, nprow ), ICCOL = indxg2p( jcc, nb_c, mycol, csrc_c, npcol ) nqc0 = numroc( ni+icoffc, nb_c, mycol, iccol, npcol ), icrow = indxg2p( icc, mb_c, myrow, rsrc_c, nprow ), ICCOL = indxg2p( jcc, nb_c, mycol, csrc_c, npcol ) nqc0 = numroc( ni+icoffc, nb_c, mycol, iccol, npcol ), icrow = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ), ICCOL = indxg2p( jc, nb_c, mycol, csrc_c, npcol ) nqc0 = numroc( n+icoffc, nb_c, mycol, iccol, npcol ), icrow = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ), ICCOL = indxg2p( jc, nb_c, mycol, csrc_c, npcol ) nqc0 = numroc( n+icoffc, nb_c, mycol, iccol, npcol ), icrow = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ), ICCOL = indxg2p( jc, nb_c, mycol, csrc_c, npcol ) nqc0 = numroc( n+icoffc, nb_c, mycol, iccol, npcol ), icrow = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ), ICCOL = indxg2p( jc, nb_c, mycol, csrc_c, npcol ) nqc0 = numroc( n+icoffc, nb_c, mycol, iccol, npcol ), icrow = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ), ICCOL = indxg2p( jc, nb_c, mycol, csrc_c, npcol ) nqc0 = numroc( n+icoffc, nb_c, mycol, iccol, npcol ), icrow = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ), ICCOL = indxg2p( jc, nb_c, mycol, csrc_c, npcol ) nqc0 = numroc( n+icoffc, nb_c, mycol, iccol, npcol ), icrow = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ), ICCOL = indxg2p( jc, nb_c, mycol, csrc_c, npcol ) nqc0 = numroc( n+icoffc, nb_c, mycol, iccol, npcol ), icrow = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ), ICCOL = indxg2p( jc, nb_c, mycol, csrc_c, npcol ) nqc0 = numroc( n+icoffc, nb_c, mycol, iccol, npcol ), icrow = indxg2p( icc, mb_c, myrow, rsrc_c, nprow ), ICCOL = indxg2p( jcc, nb_c, mycol, csrc_c, npcol ) nqc0 = numroc( ni+icoffc, nb_c, mycol, iccol, npcol ), send v and tau to the process column ICCOL icrow = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ), ICCOL = indxg2p( jc, nb_c, mycol, csrc_c, npcol ) npc0 = numroc( n+icoffc, mb_c, myrow, icrow, nprow ), icrow = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ), ICCOL = indxg2p( jc, nb_c, mycol, csrc_c, npcol ) npc0 = numroc( n+icoffc, mb_c, myrow, icrow, nprow ), icrow = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ), ICCOL = indxg2p( jc, nb_c, mycol, csrc_c, npcol ) nqc0 = numroc( n+icoffc, nb_c, mycol, iccol, npcol ), icrow = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ), ICCOL = indxg2p( jc, nb_c, mycol, csrc_c, npcol ) nqc0 = numroc( n+icoffc, nb_c, mycol, iccol, npcol ), icrow = indxg2p( icc, mb_c, myrow, rsrc_c, nprow ), ICCOL = indxg2p( jcc, nb_c, mycol, csrc_c, npcol ) nqc0 = numroc( ni+icoffc, nb_c, mycol, iccol, npcol ), icrow = indxg2p( icc, mb_c, myrow, rsrc_c, nprow ), ICCOL = indxg2p( jcc, nb_c, mycol, csrc_c, npcol ) nqc0 = numroc( ni+icoffc, nb_c, mycol, iccol, npcol ), icrow = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ), ICCOL = indxg2p( jc, nb_c, mycol, csrc_c, npcol ) nqc0 = numroc( n+icoffc, nb_c, mycol, iccol, npcol ), icrow = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ), ICCOL = indxg2p( jc, nb_c, mycol, csrc_c, npcol ) nqc0 = numroc( n+icoffc, nb_c, mycol, iccol, npcol ), icrow = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ), ICCOL = indxg2p( jc, nb_c, mycol, csrc_c, npcol ) nqc0 = numroc( n+icoffc, nb_c, mycol, iccol, npcol ), icrow = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ), ICCOL = indxg2p( jc, nb_c, mycol, csrc_c, npcol ) nqc0 = numroc( n+icoffc, nb_c, mycol, iccol, npcol ), icrow = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ), ICCOL = indxg2p( jc, nb_c, mycol, csrc_c, npcol ) nqc0 = numroc( n+icoffc, nb_c, mycol, iccol, npcol ), icrow = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ), ICCOL = indxg2p( jc, nb_c, mycol, csrc_c, npcol ) nqc0 = numroc( n+icoffc, nb_c, mycol, iccol, npcol ), icrow = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ), ICCOL = indxg2p( jc, nb_c, mycol, csrc_c, npcol ) nqc0 = numroc( n+icoffc, nb_c, mycol, iccol, npcol ), icrow = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ), ICCOL = indxg2p( jc, nb_c, mycol, csrc_c, npcol ) nqc0 = numroc( n+icoffc, nb_c, mycol, iccol, npcol ), icrow = indxg2p( icc, mb_c, myrow, rsrc_c, nprow ), ICCOL = indxg2p( jcc, nb_c, mycol, csrc_c, npcol ) nqc0 = numroc( ni+icoffc, nb_c, mycol, iccol, npcol ), send v and tau to the process column ICCOL icrow = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ), ICCOL = indxg2p( jc, nb_c, mycol, csrc_c, npcol ) npc0 = numroc( n+icoffc, mb_c, myrow, icrow, nprow ), icrow = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ), ICCOL = indxg2p( jc, nb_c, mycol, csrc_c, npcol ) npc0 = numroc( n+icoffc, mb_c, myrow, icrow, nprow ), icrow = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ), ICCOL = indxg2p( jc, nb_c, mycol, csrc_c, npcol ) nqc0 = numroc( n+icoffc, nb_c, mycol, iccol, npcol ), icrow = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ), ICCOL = indxg2p( jc, nb_c, mycol, csrc_c, npcol ) nqc0 = numroc( n+icoffc, nb_c, mycol, iccol, npcol ), icrow = indxg2p( icc, mb_c, myrow, rsrc_c, nprow ), ICCOL = indxg2p( jcc, nb_c, mycol, csrc_c, npcol ) nqc0 = numroc( ni+icoffc, nb_c, mycol, iccol, npcol ), icrow = indxg2p( icc, mb_c, myrow, rsrc_c, nprow ), ICCOL = indxg2p( jcc, nb_c, mycol, csrc_c, npcol ) nqc0 = numroc( ni+icoffc, nb_c, mycol, iccol, npcol ), icrow = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ), ICCOL = indxg2p( jc, nb_c, mycol, csrc_c, npcol ) nqc0 = numroc( n+icoffc, nb_c, mycol, iccol, npcol ), icrow = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ), ICCOL = indxg2p( jc, nb_c, mycol, csrc_c, npcol ) nqc0 = numroc( n+icoffc, nb_c, mycol, iccol, npcol ), icrow = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ), ICCOL = indxg2p( jc, nb_c, mycol, csrc_c, npcol ) nqc0 = numroc( n+icoffc, nb_c, mycol, iccol, npcol ), icrow = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ), ICCOL = indxg2p( jc, nb_c, mycol, csrc_c, npcol ) nqc0 = numroc( n+icoffc, nb_c, mycol, iccol, npcol ), icrow = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ), ICCOL = indxg2p( jc, nb_c, mycol, csrc_c, npcol ) nqc0 = numroc( n+icoffc, nb_c, mycol, iccol, npcol ), icrow = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ), ICCOL = indxg2p( jc, nb_c, mycol, csrc_c, npcol ) nqc0 = numroc( n+icoffc, nb_c, mycol, iccol, npcol ), icrow = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ), ICCOL = indxg2p( jc, nb_c, mycol, csrc_c, npcol ) nqc0 = numroc( n+icoffc, nb_c, mycol, iccol, npcol ), icrow = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ), ICCOL = indxg2p( jc, nb_c, mycol, csrc_c, npcol ) nqc0 = numroc( n+icoffc, nb_c, mycol, iccol, npcol ), icrow = indxg2p( icc, mb_c, myrow, rsrc_c, nprow ), ICCOL = indxg2p( jcc, nb_c, mycol, csrc_c, npcol ) nqc0 = numroc( ni+icoffc, nb_c, mycol, iccol, npcol ), send v and tau to the process column ICCOL icrow = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ), ICCOL = indxg2p( jc, nb_c, mycol, csrc_c, npcol ) npc0 = numroc( n+icoffc, mb_c, myrow, icrow, nprow ), send v and tau to the process column ICCOL icrow = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ), ICCOL = indxg2p( jc, nb_c, mycol, csrc_c, npcol ) npc0 = numroc( n+icoffc, mb_c, myrow, icrow, nprow ), icrow = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ), ICCOL = indxg2p( jc, nb_c, mycol, csrc_c, npcol ) nqc0 = numroc( n+icoffc, nb_c, mycol, iccol, npcol ), icrow = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ), ICCOL = indxg2p( jc, nb_c, mycol, csrc_c, npcol ) nqc0 = numroc( n+icoffc, nb_c, mycol, iccol, npcol ), icrow = indxg2p( icc, mb_c, myrow, rsrc_c, nprow ), ICCOL = indxg2p( jcc, nb_c, mycol, csrc_c, npcol ) nqc0 = numroc( ni+icoffc, nb_c, mycol, iccol, npcol ), icrow = indxg2p( icc, mb_c, myrow, rsrc_c, nprow ), ICCOL = indxg2p( jcc, nb_c, mycol, csrc_c, npcol ) nqc0 = numroc( ni+icoffc, nb_c, mycol, iccol, npcol ), icrow = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ), ICCOL = indxg2p( jc, nb_c, mycol, csrc_c, npcol ) nqc0 = numroc( n+icoffc, nb_c, mycol, iccol, npcol ), icrow = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ), ICCOL = indxg2p( jc, nb_c, mycol, csrc_c, npcol ) nqc0 = numroc( n+icoffc, nb_c, mycol, iccol, npcol ), icrow = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ), ICCOL = indxg2p( jc, nb_c, mycol, csrc_c, npcol ) nqc0 = numroc( n+icoffc, nb_c, mycol, iccol, npcol ), icrow = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ), ICCOL = indxg2p( jc, nb_c, mycol, csrc_c, npcol ) nqc0 = numroc( n+icoffc, nb_c, mycol, iccol, npcol ), icrow = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ), ICCOL = indxg2p( jc, nb_c, mycol, csrc_c, npcol ) nqc0 = numroc( n+icoffc, nb_c, mycol, iccol, npcol ), icrow = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ), ICCOL = indxg2p( jc, nb_c, mycol, csrc_c, npcol ) nqc0 = numroc( n+icoffc, nb_c, mycol, iccol, npcol ), icrow = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ), ICCOL = indxg2p( jc, nb_c, mycol, csrc_c, npcol ) nqc0 = numroc( n+icoffc, nb_c, mycol, iccol, npcol ), icrow = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ), ICCOL = indxg2p( jc, nb_c, mycol, csrc_c, npcol ) nqc0 = numroc( n+icoffc, nb_c, mycol, iccol, npcol ), icrow = indxg2p( icc, mb_c, myrow, rsrc_c, nprow ), ICCOL = indxg2p( jcc, nb_c, mycol, csrc_c, npcol ) nqc0 = numroc( ni+icoffc, nb_c, mycol, iccol, npcol ), |
| ICCOL2 ICCOL2 send v and tau to the process column ICCOL2 send v and tau to the process column ICCOL2 send v and tau to the process column ICCOL2 send v and tau to the process column ICCOL2 send v and tau to the process column ICCOL2 send v and tau to the process column ICCOL2 |
| ICEIL ICEIL lrwork >= 4*n + max( 5*nn, np0 * mq0 ) + ICEIL( neig, nprow*npcol)*n the computed eigenvectors may not be orthogonal if the lrwork >= 4*n + max( 5*nn, np0 * mq0 ) + ICEIL( neig, nprow*npcol)*n the computed eigenvectors may not be orthogonal if the lwork >= 5*n + max( 5*nn, np0 * mq0 + 2 * nb * nb ) + ICEIL( neig, nprow*npcol)*n the computed eigenvectors may not be orthogonal if the lwork >= 5 * n + max( 5*nn, np0 * mq0 + 2 * nb * nb ) + ICEIL( neig, nprow*npcol)*n the computed eigenvectors may not be orthogonal if the lwork >= 5*n + max( 5*nn, np0 * mq0 + 2 * nb * nb ) + ICEIL( neig, nprow*npcol)*n the computed eigenvectors may not be orthogonal if the lwork >= 5 * n + max( 5*nn, np0 * mq0 + 2 * nb * nb ) + ICEIL( neig, nprow*npcol)*n the computed eigenvectors may not be orthogonal if the lrwork >= 4*n + max( 5*nn, np0 * mq0 ) + ICEIL( neig, nprow*npcol)*n the computed eigenvectors may not be orthogonal if the lrwork >= 4*n + max( 5*nn, np0 * mq0 ) + ICEIL( neig, nprow*npcol)*n the computed eigenvectors may not be orthogonal if the |
| ICLM ICLM where lcmq = lcm / npcol with lcm = ICLM( nprow, npcol ) iroffv = mod( iv-1, mb_v ), icoffv = mod( jv-1, nb_v ), where lcmq = lcm / npcol with lcm = ICLM( nprow, npcol ) iroffv = mod( iv-1, mb_v ), icoffv = mod( jv-1, nb_v ), where lcmq = lcm / npcol with lcm = ICLM( nprow, npcol ) iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), where lcmq = lcm / npcol with lcm = ICLM( nprow, npcol ) iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), where lcmp = lcm / nprow, lcmq = lcm / npcol, with lcm = ICLM( nprow, npcol ) iroffa = mod( iaa-1, mb_a ), icoffa = mod( jaa-1, nb_a ), where lcmq = lcm / npcol with lcm = ICLM( nprow, npcol ) iroffa = mod( iaa-1, mb_a ), icoffa = mod( jaa-1, nb_a ), where lcmp = lcm / nprow with lcm = ICLM( nprow, npcol ) iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), where lcmp = lcm / nprow with lcm = ICLM( nprow, npcol ) iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), where lcmq = lcm / npcol with lcm = ICLM( nprow, npcol ) iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), where lcmq = lcm / npcol with lcm = ICLM( nprow, npcol ) iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), where lcmp = lcm / nprow with lcm = ICLM( nprow, npcol ) iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), where lcmp = lcm / nprow with lcm = ICLM( nprow, npcol ) iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), where lcmp = lcm / nprow with lcm = ICLM( nprow, npcol ) iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), where lcmp = lcm / nprow with lcm = ICLM( nprow, npcol ) iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), where lcmq = lcm / npcol with lcm = ICLM( nprow, npcol ) iroffa = mod( iaa-1, mb_a ), icoffa = mod( jaa-1, nb_a ), where lcmq = lcm / npcol with lcm = ICLM( nprow, npcol ) iroffv = mod( iv-1, mb_v ), icoffv = mod( jv-1, nb_v ), where lcmq = lcm / npcol with lcm = ICLM( nprow, npcol ) iroffv = mod( iv-1, mb_v ), icoffv = mod( jv-1, nb_v ), where lcmq = lcm / npcol with lcm = ICLM( nprow, npcol ) iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), where lcmq = lcm / npcol with lcm = ICLM( nprow, npcol ) iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), where lcmp = lcm / nprow, lcmq = lcm / npcol, with lcm = ICLM( nprow, npcol ) iroffa = mod( iaa-1, mb_a ), icoffa = mod( jaa-1, nb_a ), where lcmq = lcm / npcol with lcm = ICLM( nprow, npcol ) iroffa = mod( iaa-1, mb_a ), icoffa = mod( jaa-1, nb_a ), where lcmp = lcm / nprow with lcm = ICLM( nprow, npcol ) iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), where lcmp = lcm / nprow with lcm = ICLM( nprow, npcol ) iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), where lcmq = lcm / npcol with lcm = ICLM( nprow, npcol ) iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), where lcmq = lcm / npcol with lcm = ICLM( nprow, npcol ) iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), where lcmp = lcm / nprow with lcm = ICLM( nprow, npcol ) iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), where lcmp = lcm / nprow with lcm = ICLM( nprow, npcol ) iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), where lcmp = lcm / nprow with lcm = ICLM( nprow, npcol ) iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), where lcmp = lcm / nprow with lcm = ICLM( nprow, npcol ) iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), where lcmq = lcm / npcol with lcm = ICLM( nprow, npcol ) iroffa = mod( iaa-1, mb_a ), icoffa = mod( jaa-1, nb_a ), where lcmq = lcm / npcol with lcm = ICLM( nprow, npcol ) iroffv = mod( iv-1, mb_v ), icoffv = mod( jv-1, nb_v ), where lcmq = lcm / npcol with lcm = ICLM( nprow, npcol ) iroffv = mod( iv-1, mb_v ), icoffv = mod( jv-1, nb_v ), where lcmq = lcm / npcol with lcm = ICLM( nprow, npcol ) iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), where lcmq = lcm / npcol with lcm = ICLM( nprow, npcol ) iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), where lcmp = lcm / nprow, lcmq = lcm / npcol, with lcm = ICLM( nprow, npcol ) iroffa = mod( iaa-1, mb_a ), icoffa = mod( jaa-1, nb_a ), where lcmq = lcm / npcol with lcm = ICLM( nprow, npcol ) iroffa = mod( iaa-1, mb_a ), icoffa = mod( jaa-1, nb_a ), where lcmp = lcm / nprow with lcm = ICLM( nprow, npcol ) iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), where lcmp = lcm / nprow with lcm = ICLM( nprow, npcol ) iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), where lcmq = lcm / npcol with lcm = ICLM( nprow, npcol ) iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), where lcmq = lcm / npcol with lcm = ICLM( nprow, npcol ) iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), where lcmp = lcm / nprow with lcm = ICLM( nprow, npcol ) iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), where lcmp = lcm / nprow with lcm = ICLM( nprow, npcol ) iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), where lcmp = lcm / nprow with lcm = ICLM( nprow, npcol ) iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), where lcmp = lcm / nprow with lcm = ICLM( nprow, npcol ) iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), where lcmq = lcm / npcol with lcm = ICLM( nprow, npcol ) iroffa = mod( iaa-1, mb_a ), icoffa = mod( jaa-1, nb_a ), where lcmq = lcm / npcol with lcm = ICLM( nprow, npcol ) iroffv = mod( iv-1, mb_v ), icoffv = mod( jv-1, nb_v ), where lcmq = lcm / npcol with lcm = ICLM( nprow, npcol ) iroffv = mod( iv-1, mb_v ), icoffv = mod( jv-1, nb_v ), where lcmq = lcm / npcol with lcm = ICLM( nprow, npcol ) iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), where lcmq = lcm / npcol with lcm = ICLM( nprow, npcol ) iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), where lcmp = lcm / nprow, lcmq = lcm / npcol, with lcm = ICLM( nprow, npcol ) iroffa = mod( iaa-1, mb_a ), icoffa = mod( jaa-1, nb_a ), where lcmq = lcm / npcol with lcm = ICLM( nprow, npcol ) iroffa = mod( iaa-1, mb_a ), icoffa = mod( jaa-1, nb_a ), where lcmp = lcm / nprow with lcm = ICLM( nprow, npcol ) iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), where lcmp = lcm / nprow with lcm = ICLM( nprow, npcol ) iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), where lcmq = lcm / npcol with lcm = ICLM( nprow, npcol ) iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), where lcmq = lcm / npcol with lcm = ICLM( nprow, npcol ) iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), where lcmp = lcm / nprow with lcm = ICLM( nprow, npcol ) iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), where lcmp = lcm / nprow with lcm = ICLM( nprow, npcol ) iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), where lcmp = lcm / nprow with lcm = ICLM( nprow, npcol ) iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), where lcmp = lcm / nprow with lcm = ICLM( nprow, npcol ) iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), where lcmq = lcm / npcol with lcm = ICLM( nprow, npcol ) iroffa = mod( iaa-1, mb_a ), icoffa = mod( jaa-1, nb_a ), |
| ICLUSTER ICLUSTER orfac, ICLUSTER() and gap() parameters adde orfac, ICLUSTER() and gap() parameters adde orfac, ICLUSTER() and gap() parameters adde orfac, ICLUSTER() and gap() parameters adde |
| ICLUSTR ICLUSTR ICLUSTR (global output) integer array, dimension (2*nprow*npcol a cluster of eigenvalues that could not be reorthogonalized ICLUSTR (global output) integer array, dimension (2*nprow*npcol a cluster of eigenvalues that could not be reorthogonalized ICLUSTR (global output) integer array, dimension (2*p corresponding to a cluster of eigenvalues that could not be ICLUSTR (global output) integer array, dimension (2*p corresponding to a cluster of eigenvalues that could not be ICLUSTR (global output) integer array, dimension (2*nprow*npcol a cluster of eigenvalues that could not be reorthogonalized ICLUSTR (global output) integer array, dimension (2*nprow*npcol a cluster of eigenvalues that could not be reorthogonalized ICLUSTR (global output) integer array, dimension (2*p corresponding to a cluster of eigenvalues that could not be ICLUSTR (global output) integer array, dimension (2*nprow*npcol a cluster of eigenvalues that could not be reorthogonalized ICLUSTR (global output) integer array, dimension (2*nprow*npcol a cluster of eigenvalues that could not be reorthogonalized ICLUSTR (global output) integer array, dimension (2*nprow*npcol a cluster of eigenvalues that could not be reorthogonalized ICLUSTR (global output) integer array, dimension (2*nprow*npcol a cluster of eigenvalues that could not be reorthogonalized ICLUSTR (global output) integer array, dimension (2*p corresponding to a cluster of eigenvalues that could not be |
| ICOFF ICOFF iroff = mod( ia-1, mb_a ), ICOFF = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroff = mod( ia-1, mb_a ), ICOFF = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroff = mod( ia-1, mb_a ), ICOFF = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroff = mod( ia-1, mb_a ), ICOFF = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroff = mod( ia-1, mb_a ), ICOFF = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroff = mod( ia-1, mb_a ), ICOFF = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroff = mod( ia-1, mb_a ), ICOFF = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroff = mod( ia-1, mb_a ), ICOFF = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroff = mod( ia-1, mb_a ), ICOFF = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroff = mod( ia-1, mb_a ), ICOFF = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroff = mod( ia-1, mb_a ), ICOFF = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroff = mod( ia-1, mb_a ), ICOFF = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroff = mod( ia-1, mb_a ), ICOFF = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroff = mod( ia-1, mb_a ), ICOFF = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroff = mod( ia-1, mb_a ), ICOFF = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroff = mod( ia-1, mb_a ), ICOFF = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroff = mod( ia-1, mb_a ), ICOFF = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroff = mod( ia-1, mb_a ), ICOFF = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroff = mod( ia-1, mb_a ), ICOFF = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroff = mod( ia-1, mb_a ), ICOFF = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroff = mod( ia-1, mb_a ), ICOFF = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroff = mod( ia-1, mb_a ), ICOFF = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroff = mod( ia-1, mb_a ), ICOFF = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroff = mod( ia-1, mb_a ), ICOFF = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroff = mod( ia-1, mb_a ), ICOFF = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroff = mod( ia-1, mb_a ), ICOFF = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroff = mod( ia-1, mb_a ), ICOFF = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroff = mod( ia-1, mb_a ), ICOFF = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroff = mod( ia-1, mb_a ), ICOFF = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroff = mod( ia-1, mb_a ), ICOFF = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroff = mod( ia-1, mb_a ), ICOFF = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroff = mod( ia-1, mb_a ), ICOFF = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroff = mod( ia-1, mb_a ), ICOFF = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroff = mod( ia-1, mb_a ), ICOFF = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroff = mod( ia-1, mb_a ), ICOFF = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroff = mod( ia-1, mb_a ), ICOFF = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroff = mod( ia-1, mb_a ), ICOFF = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroff = mod( ia-1, mb_a ), ICOFF = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroff = mod( ia-1, mb_a ), ICOFF = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroff = mod( ia-1, mb_a ), ICOFF = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroff = mod( ia-1, mb_a ), ICOFF = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroff = mod( ia-1, mb_a ), ICOFF = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroff = mod( ia-1, mb_a ), ICOFF = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroff = mod( ia-1, mb_a ), ICOFF = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), |
| ICOFFA ICOFFA ties, namely the following expressions should be true: ( mb_a.eq.nb_a .and. iroffa.eq.ICOFFA ===================================================================== where nb = mb_a = nb_a, iroffa = mod( ia-1, nb ), ICOFFA = mod( ja-1, nb ) iacol = indxg2p( ja, nb, mycol, csrc_a, npcol ), ties, namely the following expression should be true: ( mb_a.eq.nb_a .and. iroffa.eq.ICOFFA ===================================================================== where nb = mb_a = nb_a, iroffa = mod( ia-1, nb ), ICOFFA = mod( ja-1, nb ), ioff = mod( ia+ilo-2, nb ) ihip = numroc( ihi+iroffa, nb, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), ICOFFA = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroffa = mod( ia-1, mb_a ), ICOFFA = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroffa = mod( ia-1, mb_a ), ICOFFA = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), where iroffa = mod( ia-1, mb_a ) and ICOFFA = mod( ja-1, nb_a ) ===================================================================== should be true: ( mb_a.eq.nb_a.eq.mb_z.eq.nb_z .and. iroffa.eq.ICOFFA .and with iroffa = mod( ia-1, mb_a ) where iroffa = mod( ia-1, mb_a ) and ICOFFA = mod( ja-1, nb_a ) ===================================================================== ties, namely the following expression should be true: ( mb_a.eq.nb_a .and. iroffa.eq.ICOFFA .and. iroffa.eq.0 ) wit ties, namely the following expression should be true: ( mb_a.eq.nb_a .and. iroffa.eq.ICOFFA ) wit ties, namely the following expression should be true: ( mb_a.eq.nb_a .and. iroffa.eq.ICOFFA .and. iroffa.eq.0 ) wit iroffa = mod( ia-1, mb_a ), ICOFFA = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroffa = mod( ia-1, mb_a ), ICOFFA = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroffa = mod( ia-1, mb_a ), ICOFFA = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroffa = mod( ia-1, mb_a ), ICOFFA = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroffa = mod( ia-1, mb_a ), ICOFFA = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroffa = mod( ia-1, mb_a ), ICOFFA = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroffa = mod( ia-1, mb_a ), ICOFFA = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroffa = mod( ia-1, mb_a ), ICOFFA = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroffa = mod( ia-1, mb_a ), ICOFFA = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroffa = mod( iaa-1, mb_a ), ICOFFA = mod( jaa-1, nb_a ) iacol = indxg2p( jaa, nb_a, mycol, csrc_a, npcol ), iroffa = mod( iaa-1, mb_a ), ICOFFA = mod( jaa-1, nb_a ) npa0 = numroc( ni+iroffa, mb_a, myrow, iarow, nprow ), if side = 'l', ( nb_a.eq.mb_c .and. ICOFFA.eq.iroffc ( nb_a.eq.nb_c .and. icoffa.eq.icoffc .and. iacol.eq.iccol ) iroffa = mod( ia-1, mb_a ), ICOFFA = mod( ja-1, nb_a ) mqa0 = numroc( m+icoffa, nb_a, mycol, iacol, npcol ), iroffa = mod( ia-1, mb_a ), ICOFFA = mod( ja-1, nb_a ) npa0 = numroc( n+iroffa, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), ICOFFA = mod( ja-1, nb_a ) npa0 = numroc( n+iroffa, mb_a, myrow, iarow, nprow ), if side = 'l', ( nb_a.eq.mb_c .and. ICOFFA.eq.iroffc ( nb_a.eq.nb_c .and. icoffa.eq.icoffc .and. iacol.eq.iccol ) if side = 'l', ( nb_a.eq.mb_c .and. ICOFFA.eq.iroffc ( nb_a.eq.nb_c .and. icoffa.eq.icoffc .and. iacol.eq.iccol ) iroffa = mod( ia-1, mb_a ), ICOFFA = mod( ja-1, nb_a ) mqa0 = numroc( m+icoffa, nb_a, mycol, iacol, npcol ), iroffa = mod( ia-1, mb_a ), ICOFFA = mod( ja-1, nb_a ) mqa0 = numroc( m+icoffa, nb_a, mycol, iacol, npcol ), iroffa = mod( iaa-1, mb_a ), ICOFFA = mod( jaa-1, nb_a ) npa0 = numroc( ni+iroffa, mb_a, myrow, iarow, nprow ), ties, namely the following expressions should be true: ( mb_a.eq.nb_a .and. iroffa.eq.ICOFFA ===================================================================== where nb = mb_a = nb_a, iroffa = mod( ia-1, nb ), ICOFFA = mod( ja-1, nb ) iacol = indxg2p( ja, nb, mycol, csrc_a, npcol ), ties, namely the following expression should be true: ( mb_a.eq.nb_a .and. iroffa.eq.ICOFFA ===================================================================== where nb = mb_a = nb_a, iroffa = mod( ia-1, nb ), ICOFFA = mod( ja-1, nb ), ioff = mod( ia+ilo-2, nb ) ihip = numroc( ihi+iroffa, nb, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), ICOFFA = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroffa = mod( ia-1, mb_a ), ICOFFA = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroffa = mod( ia-1, mb_a ), ICOFFA = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroffa = mod( ia-1, mb_a ), ICOFFA = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroffa = mod( ia-1, mb_a ), ICOFFA = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroffa = mod( ia-1, mb_a ), ICOFFA = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroffa = mod( ia-1, mb_a ), ICOFFA = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroffa = mod( ia-1, mb_a ), ICOFFA = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroffa = mod( ia-1, mb_a ), ICOFFA = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroffa = mod( ia-1, mb_a ), ICOFFA = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroffa = mod( ia-1, mb_a ), ICOFFA = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroffa = mod( ia-1, mb_a ), ICOFFA = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroffa = mod( iaa-1, mb_a ), ICOFFA = mod( jaa-1, nb_a ) iacol = indxg2p( jaa, nb_a, mycol, csrc_a, npcol ), iroffa = mod( iaa-1, mb_a ), ICOFFA = mod( jaa-1, nb_a ) npa0 = numroc( ni+iroffa, mb_a, myrow, iarow, nprow ), if side = 'l', ( nb_a.eq.mb_c .and. ICOFFA.eq.iroffc ( nb_a.eq.nb_c .and. icoffa.eq.icoffc .and. iacol.eq.iccol ) iroffa = mod( ia-1, mb_a ), ICOFFA = mod( ja-1, nb_a ) mqa0 = numroc( m+icoffa, nb_a, mycol, iacol, npcol ), iroffa = mod( ia-1, mb_a ), ICOFFA = mod( ja-1, nb_a ) npa0 = numroc( n+iroffa, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), ICOFFA = mod( ja-1, nb_a ) npa0 = numroc( n+iroffa, mb_a, myrow, iarow, nprow ), if side = 'l', ( nb_a.eq.mb_c .and. ICOFFA.eq.iroffc ( nb_a.eq.nb_c .and. icoffa.eq.icoffc .and. iacol.eq.iccol ) if side = 'l', ( nb_a.eq.mb_c .and. ICOFFA.eq.iroffc ( nb_a.eq.nb_c .and. icoffa.eq.icoffc .and. iacol.eq.iccol ) iroffa = mod( ia-1, mb_a ), ICOFFA = mod( ja-1, nb_a ) mqa0 = numroc( m+icoffa, nb_a, mycol, iacol, npcol ), iroffa = mod( ia-1, mb_a ), ICOFFA = mod( ja-1, nb_a ) mqa0 = numroc( m+icoffa, nb_a, mycol, iacol, npcol ), iroffa = mod( iaa-1, mb_a ), ICOFFA = mod( jaa-1, nb_a ) npa0 = numroc( ni+iroffa, mb_a, myrow, iarow, nprow ), where iroffa = mod( ia-1, mb_a ) and ICOFFA = mod( ja-1, nb_a ) ===================================================================== should be true: ( mb_a.eq.nb_a.eq.mb_z.eq.nb_z .and. iroffa.eq.ICOFFA .and with iroffa = mod( ia-1, mb_a ) where iroffa = mod( ia-1, mb_a ) and ICOFFA = mod( ja-1, nb_a ) ===================================================================== ties, namely the following expression should be true: ( mb_a.eq.nb_a .and. iroffa.eq.ICOFFA .and. iroffa.eq.0 ) wit ties, namely the following expression should be true: ( mb_a.eq.nb_a .and. iroffa.eq.ICOFFA ) wit ties, namely the following expression should be true: ( mb_a.eq.nb_a .and. iroffa.eq.ICOFFA .and. iroffa.eq.0 ) wit ties, namely the following expressions should be true: ( mb_a.eq.nb_a .and. iroffa.eq.ICOFFA ===================================================================== where nb = mb_a = nb_a, iroffa = mod( ia-1, nb ), ICOFFA = mod( ja-1, nb ) iacol = indxg2p( ja, nb, mycol, csrc_a, npcol ), ties, namely the following expression should be true: ( mb_a.eq.nb_a .and. iroffa.eq.ICOFFA ===================================================================== where nb = mb_a = nb_a, iroffa = mod( ia-1, nb ), ICOFFA = mod( ja-1, nb ), ioff = mod( ia+ilo-2, nb ) ihip = numroc( ihi+iroffa, nb, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), ICOFFA = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroffa = mod( ia-1, mb_a ), ICOFFA = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroffa = mod( ia-1, mb_a ), ICOFFA = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroffa = mod( ia-1, mb_a ), ICOFFA = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroffa = mod( ia-1, mb_a ), ICOFFA = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroffa = mod( ia-1, mb_a ), ICOFFA = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroffa = mod( ia-1, mb_a ), ICOFFA = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroffa = mod( ia-1, mb_a ), ICOFFA = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroffa = mod( ia-1, mb_a ), ICOFFA = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroffa = mod( ia-1, mb_a ), ICOFFA = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroffa = mod( ia-1, mb_a ), ICOFFA = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroffa = mod( ia-1, mb_a ), ICOFFA = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroffa = mod( iaa-1, mb_a ), ICOFFA = mod( jaa-1, nb_a ) iacol = indxg2p( jaa, nb_a, mycol, csrc_a, npcol ), iroffa = mod( iaa-1, mb_a ), ICOFFA = mod( jaa-1, nb_a ) npa0 = numroc( ni+iroffa, mb_a, myrow, iarow, nprow ), if side = 'l', ( nb_a.eq.mb_c .and. ICOFFA.eq.iroffc ( nb_a.eq.nb_c .and. icoffa.eq.icoffc .and. iacol.eq.iccol ) iroffa = mod( ia-1, mb_a ), ICOFFA = mod( ja-1, nb_a ) mqa0 = numroc( m+icoffa, nb_a, mycol, iacol, npcol ), iroffa = mod( ia-1, mb_a ), ICOFFA = mod( ja-1, nb_a ) npa0 = numroc( n+iroffa, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), ICOFFA = mod( ja-1, nb_a ) npa0 = numroc( n+iroffa, mb_a, myrow, iarow, nprow ), if side = 'l', ( nb_a.eq.mb_c .and. ICOFFA.eq.iroffc ( nb_a.eq.nb_c .and. icoffa.eq.icoffc .and. iacol.eq.iccol ) if side = 'l', ( nb_a.eq.mb_c .and. ICOFFA.eq.iroffc ( nb_a.eq.nb_c .and. icoffa.eq.icoffc .and. iacol.eq.iccol ) iroffa = mod( ia-1, mb_a ), ICOFFA = mod( ja-1, nb_a ) mqa0 = numroc( m+icoffa, nb_a, mycol, iacol, npcol ), iroffa = mod( ia-1, mb_a ), ICOFFA = mod( ja-1, nb_a ) mqa0 = numroc( m+icoffa, nb_a, mycol, iacol, npcol ), iroffa = mod( iaa-1, mb_a ), ICOFFA = mod( jaa-1, nb_a ) npa0 = numroc( ni+iroffa, mb_a, myrow, iarow, nprow ), where iroffa = mod( ia-1, mb_a ) and ICOFFA = mod( ja-1, nb_a ) ===================================================================== should be true: ( mb_a.eq.nb_a.eq.mb_z.eq.nb_z .and. iroffa.eq.ICOFFA .and with iroffa = mod( ia-1, mb_a ) where iroffa = mod( ia-1, mb_a ) and ICOFFA = mod( ja-1, nb_a ) ===================================================================== ties, namely the following expression should be true: ( mb_a.eq.nb_a .and. iroffa.eq.ICOFFA .and. iroffa.eq.0 ) wit ties, namely the following expression should be true: ( mb_a.eq.nb_a .and. iroffa.eq.ICOFFA ) wit ties, namely the following expression should be true: ( mb_a.eq.nb_a .and. iroffa.eq.ICOFFA .and. iroffa.eq.0 ) wit ties, namely the following expressions should be true: ( mb_a.eq.nb_a .and. iroffa.eq.ICOFFA ===================================================================== where nb = mb_a = nb_a, iroffa = mod( ia-1, nb ), ICOFFA = mod( ja-1, nb ) iacol = indxg2p( ja, nb, mycol, csrc_a, npcol ), ties, namely the following expression should be true: ( mb_a.eq.nb_a .and. iroffa.eq.ICOFFA ===================================================================== where nb = mb_a = nb_a, iroffa = mod( ia-1, nb ), ICOFFA = mod( ja-1, nb ), ioff = mod( ia+ilo-2, nb ) ihip = numroc( ihi+iroffa, nb, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), ICOFFA = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroffa = mod( ia-1, mb_a ), ICOFFA = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroffa = mod( ia-1, mb_a ), ICOFFA = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), where iroffa = mod( ia-1, mb_a ) and ICOFFA = mod( ja-1, nb_a ) ===================================================================== should be true: ( mb_a.eq.nb_a.eq.mb_z.eq.nb_z .and. iroffa.eq.ICOFFA .and with iroffa = mod( ia-1, mb_a ) where iroffa = mod( ia-1, mb_a ) and ICOFFA = mod( ja-1, nb_a ) ===================================================================== ties, namely the following expression should be true: ( mb_a.eq.nb_a .and. iroffa.eq.ICOFFA .and. iroffa.eq.0 ) wit ties, namely the following expression should be true: ( mb_a.eq.nb_a .and. iroffa.eq.ICOFFA ) wit ties, namely the following expression should be true: ( mb_a.eq.nb_a .and. iroffa.eq.ICOFFA .and. iroffa.eq.0 ) wit iroffa = mod( ia-1, mb_a ), ICOFFA = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroffa = mod( ia-1, mb_a ), ICOFFA = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroffa = mod( ia-1, mb_a ), ICOFFA = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroffa = mod( ia-1, mb_a ), ICOFFA = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroffa = mod( ia-1, mb_a ), ICOFFA = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroffa = mod( ia-1, mb_a ), ICOFFA = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroffa = mod( ia-1, mb_a ), ICOFFA = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroffa = mod( ia-1, mb_a ), ICOFFA = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroffa = mod( ia-1, mb_a ), ICOFFA = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), iroffa = mod( iaa-1, mb_a ), ICOFFA = mod( jaa-1, nb_a ) iacol = indxg2p( jaa, nb_a, mycol, csrc_a, npcol ), iroffa = mod( iaa-1, mb_a ), ICOFFA = mod( jaa-1, nb_a ) npa0 = numroc( ni+iroffa, mb_a, myrow, iarow, nprow ), if side = 'l', ( nb_a.eq.mb_c .and. ICOFFA.eq.iroffc ( nb_a.eq.nb_c .and. icoffa.eq.icoffc .and. iacol.eq.iccol ) iroffa = mod( ia-1, mb_a ), ICOFFA = mod( ja-1, nb_a ) mqa0 = numroc( m+icoffa, nb_a, mycol, iacol, npcol ), iroffa = mod( ia-1, mb_a ), ICOFFA = mod( ja-1, nb_a ) npa0 = numroc( n+iroffa, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), ICOFFA = mod( ja-1, nb_a ) npa0 = numroc( n+iroffa, mb_a, myrow, iarow, nprow ), if side = 'l', ( nb_a.eq.mb_c .and. ICOFFA.eq.iroffc ( nb_a.eq.nb_c .and. icoffa.eq.icoffc .and. iacol.eq.iccol ) if side = 'l', ( nb_a.eq.mb_c .and. ICOFFA.eq.iroffc ( nb_a.eq.nb_c .and. icoffa.eq.icoffc .and. iacol.eq.iccol ) iroffa = mod( ia-1, mb_a ), ICOFFA = mod( ja-1, nb_a ) mqa0 = numroc( m+icoffa, nb_a, mycol, iacol, npcol ), iroffa = mod( ia-1, mb_a ), ICOFFA = mod( ja-1, nb_a ) mqa0 = numroc( m+icoffa, nb_a, mycol, iacol, npcol ), iroffa = mod( iaa-1, mb_a ), ICOFFA = mod( jaa-1, nb_a ) npa0 = numroc( ni+iroffa, mb_a, myrow, iarow, nprow ), |
| ICOFFB ICOFFB iroffb = mod( ib-1, mb_b ), ICOFFB = mod( jb-1, nb_b ) ibcol = indxg2p( jb, nb_b, mycol, csrc_b, npcol ), iroffb = mod( ib-1, mb_b ), ICOFFB = mod( jb-1, nb_b ) ibcol = indxg2p( jb, nb_b, mycol, csrc_b, npcol ), iroffb = mod( ib-1, mb_b ), ICOFFB = mod( jb-1, nb_b ) ibcol = indxg2p( jb, nb_b, mycol, csrc_b, npcol ), iroffb = mod( ib-1, mb_b ), ICOFFB = mod( jb-1, nb_b ) ibcol = indxg2p( jb, nb_b, mycol, csrc_b, npcol ), iroffb = mod( ib-1, mb_b ), ICOFFB = mod( jb-1, nb_b ) ibcol = indxg2p( jb, nb_b, mycol, csrc_b, npcol ), iroffb = mod( ib-1, mb_b ), ICOFFB = mod( jb-1, nb_b ) ibcol = indxg2p( jb, nb_b, mycol, csrc_b, npcol ), iroffb = mod( ib-1, mb_b ), ICOFFB = mod( jb-1, nb_b ) ibcol = indxg2p( jb, nb_b, mycol, csrc_b, npcol ), iroffb = mod( ib-1, mb_b ), ICOFFB = mod( jb-1, nb_b ) ibcol = indxg2p( jb, nb_b, mycol, csrc_b, npcol ), iroffb = mod( ib-1, mb_b ), ICOFFB = mod( jb-1, nb_b ) ibcol = indxg2p( jb, nb_b, mycol, csrc_b, npcol ), iroffb = mod( ib-1, mb_b ), ICOFFB = mod( jb-1, nb_b ) ibcol = indxg2p( jb, nb_b, mycol, csrc_b, npcol ), iroffb = mod( ib-1, mb_b ), ICOFFB = mod( jb-1, nb_b ) ibcol = indxg2p( jb, nb_b, mycol, csrc_b, npcol ), iroffb = mod( ib-1, mb_b ), ICOFFB = mod( jb-1, nb_b ) ibcol = indxg2p( jb, nb_b, mycol, csrc_b, npcol ), |
| ICOFFC ICOFFC else if side = 'r', lwork >= ( nqc0 + max( npv0 + numroc( numroc( n+ICOFFC mpc0 ) ) * k else if side = 'r', lwork >= ( nqc0 + max( npv0 + numroc( numroc( n+ICOFFC mpc0 ) ) * k if side = 'r', lwork >= nqc0 + max( max( 1, mpc0 ), numroc( numroc( n+ICOFFC,nb_a,0,0,npcol ),nb_a,0,0,lcmq ) ) where lcmq = lcm / npcol with lcm = iclm( nprow, npcol ), if side = 'r', lwork >= nqc0 + max( max( 1, mpc0 ), numroc( numroc( n+ICOFFC,nb_a,0,0,npcol ),nb_a,0,0,lcmq ) ) where lcmq = lcm / npcol with lcm = iclm( nprow, npcol ), lwork >= max( (nb_a*(nb_a-1))/2, ( nqc0 + max( npa0 + numroc( numroc( ni+ICOFFC, nb_a, 0, 0, npcol ) nb_a * nb_a lwork >= max( (nb_a*(nb_a-1))/2, ( nqc0 + max( npa0 + numroc( numroc( ni+ICOFFC, nb_a, 0, 0, npcol ) nb_a * nb_a iroffc = mod( ic-1, mb_c ), ICOFFC = mod( jc-1, nb_c ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), iroffc = mod( ic-1, mb_c ), ICOFFC = mod( jc-1, nb_c ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), lwork >= max( (nb_a*(nb_a-1))/2, ( nqc0 + max( npa0 + numroc( numroc( n+ICOFFC, nb_a, 0, 0, npcol ) nb_a * nb_a lwork >= max( (nb_a*(nb_a-1))/2, ( nqc0 + max( npa0 + numroc( numroc( n+ICOFFC, nb_a, 0, 0, npcol ) nb_a * nb_a iroffc = mod( ic-1, mb_c ), ICOFFC = mod( jc-1, nb_c ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), iroffc = mod( ic-1, mb_c ), ICOFFC = mod( jc-1, nb_c ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), iroffc = mod( ic-1, mb_c ), ICOFFC = mod( jc-1, nb_c ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), iroffc = mod( ic-1, mb_c ), ICOFFC = mod( jc-1, nb_c ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), lwork >= max( (nb_a*(nb_a-1))/2, ( nqc0 + max( npa0 + numroc( numroc( ni+ICOFFC, nb_a, 0, 0, npcol ) nb_a * nb_a else if side = 'r', lwork >= ( nqc0 + max( npv0 + numroc( numroc( n+ICOFFC mpc0 ) ) * k else if side = 'r', lwork >= ( nqc0 + max( npv0 + numroc( numroc( n+ICOFFC mpc0 ) ) * k if side = 'r', lwork >= nqc0 + max( max( 1, mpc0 ), numroc( numroc( n+ICOFFC,nb_a,0,0,npcol ),nb_a,0,0,lcmq ) ) where lcmq = lcm / npcol with lcm = iclm( nprow, npcol ), if side = 'r', lwork >= nqc0 + max( max( 1, mpc0 ), numroc( numroc( n+ICOFFC,nb_a,0,0,npcol ),nb_a,0,0,lcmq ) ) where lcmq = lcm / npcol with lcm = iclm( nprow, npcol ), lwork >= max( (nb_a*(nb_a-1))/2, ( nqc0 + max( npa0 + numroc( numroc( ni+ICOFFC, nb_a, 0, 0, npcol ) nb_a * nb_a lwork >= max( (nb_a*(nb_a-1))/2, ( nqc0 + max( npa0 + numroc( numroc( ni+ICOFFC, nb_a, 0, 0, npcol ) nb_a * nb_a iroffc = mod( ic-1, mb_c ), ICOFFC = mod( jc-1, nb_c ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), iroffc = mod( ic-1, mb_c ), ICOFFC = mod( jc-1, nb_c ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), lwork >= max( (nb_a*(nb_a-1))/2, ( nqc0 + max( npa0 + numroc( numroc( n+ICOFFC, nb_a, 0, 0, npcol ) nb_a * nb_a lwork >= max( (nb_a*(nb_a-1))/2, ( nqc0 + max( npa0 + numroc( numroc( n+ICOFFC, nb_a, 0, 0, npcol ) nb_a * nb_a iroffc = mod( ic-1, mb_c ), ICOFFC = mod( jc-1, nb_c ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), iroffc = mod( ic-1, mb_c ), ICOFFC = mod( jc-1, nb_c ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), iroffc = mod( ic-1, mb_c ), ICOFFC = mod( jc-1, nb_c ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), iroffc = mod( ic-1, mb_c ), ICOFFC = mod( jc-1, nb_c ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), lwork >= max( (nb_a*(nb_a-1))/2, ( nqc0 + max( npa0 + numroc( numroc( ni+ICOFFC, nb_a, 0, 0, npcol ) nb_a * nb_a else if side = 'r', lwork >= ( nqc0 + max( npv0 + numroc( numroc( n+ICOFFC mpc0 ) ) * k else if side = 'r', lwork >= ( nqc0 + max( npv0 + numroc( numroc( n+ICOFFC mpc0 ) ) * k if side = 'r', lwork >= nqc0 + max( max( 1, mpc0 ), numroc( numroc( n+ICOFFC,nb_a,0,0,npcol ),nb_a,0,0,lcmq ) ) where lcmq = lcm / npcol with lcm = iclm( nprow, npcol ), if side = 'r', lwork >= nqc0 + max( max( 1, mpc0 ), numroc( numroc( n+ICOFFC,nb_a,0,0,npcol ),nb_a,0,0,lcmq ) ) where lcmq = lcm / npcol with lcm = iclm( nprow, npcol ), lwork >= max( (nb_a*(nb_a-1))/2, ( nqc0 + max( npa0 + numroc( numroc( ni+ICOFFC, nb_a, 0, 0, npcol ) nb_a * nb_a lwork >= max( (nb_a*(nb_a-1))/2, ( nqc0 + max( npa0 + numroc( numroc( ni+ICOFFC, nb_a, 0, 0, npcol ) nb_a * nb_a iroffc = mod( ic-1, mb_c ), ICOFFC = mod( jc-1, nb_c ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), iroffc = mod( ic-1, mb_c ), ICOFFC = mod( jc-1, nb_c ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), lwork >= max( (nb_a*(nb_a-1))/2, ( nqc0 + max( npa0 + numroc( numroc( n+ICOFFC, nb_a, 0, 0, npcol ) nb_a * nb_a lwork >= max( (nb_a*(nb_a-1))/2, ( nqc0 + max( npa0 + numroc( numroc( n+ICOFFC, nb_a, 0, 0, npcol ) nb_a * nb_a iroffc = mod( ic-1, mb_c ), ICOFFC = mod( jc-1, nb_c ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), iroffc = mod( ic-1, mb_c ), ICOFFC = mod( jc-1, nb_c ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), iroffc = mod( ic-1, mb_c ), ICOFFC = mod( jc-1, nb_c ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), iroffc = mod( ic-1, mb_c ), ICOFFC = mod( jc-1, nb_c ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), lwork >= max( (nb_a*(nb_a-1))/2, ( nqc0 + max( npa0 + numroc( numroc( ni+ICOFFC, nb_a, 0, 0, npcol ) nb_a * nb_a else if side = 'r', lwork >= ( nqc0 + max( npv0 + numroc( numroc( n+ICOFFC mpc0 ) ) * k else if side = 'r', lwork >= ( nqc0 + max( npv0 + numroc( numroc( n+ICOFFC mpc0 ) ) * k if side = 'r', lwork >= nqc0 + max( max( 1, mpc0 ), numroc( numroc( n+ICOFFC,nb_a,0,0,npcol ),nb_a,0,0,lcmq ) ) where lcmq = lcm / npcol with lcm = iclm( nprow, npcol ), if side = 'r', lwork >= nqc0 + max( max( 1, mpc0 ), numroc( numroc( n+ICOFFC,nb_a,0,0,npcol ),nb_a,0,0,lcmq ) ) where lcmq = lcm / npcol with lcm = iclm( nprow, npcol ), lwork >= max( (nb_a*(nb_a-1))/2, ( nqc0 + max( npa0 + numroc( numroc( ni+ICOFFC, nb_a, 0, 0, npcol ) nb_a * nb_a lwork >= max( (nb_a*(nb_a-1))/2, ( nqc0 + max( npa0 + numroc( numroc( ni+ICOFFC, nb_a, 0, 0, npcol ) nb_a * nb_a iroffc = mod( ic-1, mb_c ), ICOFFC = mod( jc-1, nb_c ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), iroffc = mod( ic-1, mb_c ), ICOFFC = mod( jc-1, nb_c ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), lwork >= max( (nb_a*(nb_a-1))/2, ( nqc0 + max( npa0 + numroc( numroc( n+ICOFFC, nb_a, 0, 0, npcol ) nb_a * nb_a lwork >= max( (nb_a*(nb_a-1))/2, ( nqc0 + max( npa0 + numroc( numroc( n+ICOFFC, nb_a, 0, 0, npcol ) nb_a * nb_a iroffc = mod( ic-1, mb_c ), ICOFFC = mod( jc-1, nb_c ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), iroffc = mod( ic-1, mb_c ), ICOFFC = mod( jc-1, nb_c ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), iroffc = mod( ic-1, mb_c ), ICOFFC = mod( jc-1, nb_c ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), iroffc = mod( ic-1, mb_c ), ICOFFC = mod( jc-1, nb_c ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), lwork >= max( (nb_a*(nb_a-1))/2, ( nqc0 + max( npa0 + numroc( numroc( ni+ICOFFC, nb_a, 0, 0, npcol ) nb_a * nb_a |
| ICOFFC2 ICOFFC2 transpose column vector v (iroffv = ICOFFC2 transpose column vector v (iroffv = ICOFFC2 transpose column vector v (iroffv = ICOFFC2 transpose column vector v (iroffv = ICOFFC2 transpose column vector v (iroffv = ICOFFC2 transpose column vector v (iroffv = ICOFFC2 |
| ICOFFV ICOFFV iroffv = mod( iv-1, mb_v ), ICOFFV = mod( jv-1, nb_v ) ivcol = indxg2p( jv, nb_v, mycol, csrc_v, npcol ), transpose row vector v (ICOFFV = iroffc2 iroffv = mod( iv-1, mb_v ), ICOFFV = mod( jv-1, nb_v ) ivcol = indxg2p( jv, nb_v, mycol, csrc_v, npcol ), transpose row vector v (ICOFFV = iroffc2 iroffv = mod( iv-1, mb_v ), ICOFFV = mod( jv-1, nb_v ) ivcol = indxg2p( jv, nb_v, mycol, csrc_v, npcol ), transpose row vector v (ICOFFV = iroffc2 iroffv = mod( iv-1, mb_v ), ICOFFV = mod( jv-1, nb_v ) ivcol = indxg2p( jv, nb_v, mycol, csrc_v, npcol ), iroffv = mod( iv-1, mb_v ), ICOFFV = mod( jv-1, nb_v ) ivcol = indxg2p( jv, nb_v, mycol, csrc_v, npcol ), transpose row vector v (ICOFFV = iroffc2 iroffv = mod( iv-1, mb_v ), ICOFFV = mod( jv-1, nb_v ) ivcol = indxg2p( jv, nb_v, mycol, csrc_v, npcol ), iroffv = mod( iv-1, mb_v ), ICOFFV = mod( jv-1, nb_v ) ivcol = indxg2p( jv, nb_v, mycol, csrc_v, npcol ), transpose row vector v (ICOFFV = iroffc2 iroffv = mod( iv-1, mb_v ), ICOFFV = mod( jv-1, nb_v ) ivcol = indxg2p( jv, nb_v, mycol, csrc_v, npcol ), transpose row vector v (ICOFFV = iroffc2 |
| ICOL1 ICOL1 ICOL1 (local input/output) intege undefined on output. ICOL1 (local input/output) intege undefined on output. (irow1,ICOL1) is (i,j)-coordinates of h(istart,istart (irow1,ICOL1) is (i,j)-coordinates of h(istart,istart (irow1,ICOL1) is (i,j)-coordinates of h(istart,istart (irow1,ICOL1) is (i,j)-coordinates of h(istart,istart ICOL1 (local input/output) intege undefined on output. ICOL1 (local input/output) intege undefined on output. |
| ICROW ICROW send v and tau to the process row ICROW iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), ICROW = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( m+iroffc, mb_c, myrow, icrow, nprow ), send v and tau to the process row ICROW iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), ICROW = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( m+iroffc, mb_c, myrow, icrow, nprow ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), ICROW = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( m+iroffc, mb_c, myrow, icrow, nprow ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), ICROW = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( m+iroffc, mb_c, myrow, icrow, nprow ), iroffc = mod( icc-1, mb_c ), icoffc = mod( jcc-1, nb_c ), ICROW = indxg2p( icc, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( mi+iroffc, mb_c, myrow, icrow, nprow ), iroffc = mod( icc-1, mb_c ), icoffc = mod( jcc-1, nb_c ), ICROW = indxg2p( icc, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( mi+iroffc, mb_c, myrow, icrow, nprow ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), ICROW = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( m+iroffc, mb_c, myrow, icrow, nprow ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), ICROW = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( m+iroffc, mb_c, myrow, icrow, nprow ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), ICROW = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( m+iroffc, mb_c, myrow, icrow, nprow ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), ICROW = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( m+iroffc, mb_c, myrow, icrow, nprow ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), ICROW = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( m+iroffc, mb_c, myrow, icrow, nprow ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), ICROW = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( m+iroffc, mb_c, myrow, icrow, nprow ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), ICROW = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( m+iroffc, mb_c, myrow, icrow, nprow ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), ICROW = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( m+iroffc, mb_c, myrow, icrow, nprow ), iroffc = mod( icc-1, mb_c ), icoffc = mod( jcc-1, nb_c ), ICROW = indxg2p( icc, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( mi+iroffc, mb_c, myrow, icrow, nprow ), send v and tau to the process row ICROW iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), ICROW = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( m+iroffc, mb_c, myrow, icrow, nprow ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), ICROW = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( m+iroffc, mb_c, myrow, icrow, nprow ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), ICROW = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( m+iroffc, mb_c, myrow, icrow, nprow ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), ICROW = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( m+iroffc, mb_c, myrow, icrow, nprow ), iroffc = mod( icc-1, mb_c ), icoffc = mod( jcc-1, nb_c ), ICROW = indxg2p( icc, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( mi+iroffc, mb_c, myrow, icrow, nprow ), iroffc = mod( icc-1, mb_c ), icoffc = mod( jcc-1, nb_c ), ICROW = indxg2p( icc, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( mi+iroffc, mb_c, myrow, icrow, nprow ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), ICROW = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( m+iroffc, mb_c, myrow, icrow, nprow ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), ICROW = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( m+iroffc, mb_c, myrow, icrow, nprow ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), ICROW = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( m+iroffc, mb_c, myrow, icrow, nprow ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), ICROW = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( m+iroffc, mb_c, myrow, icrow, nprow ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), ICROW = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( m+iroffc, mb_c, myrow, icrow, nprow ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), ICROW = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( m+iroffc, mb_c, myrow, icrow, nprow ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), ICROW = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( m+iroffc, mb_c, myrow, icrow, nprow ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), ICROW = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( m+iroffc, mb_c, myrow, icrow, nprow ), iroffc = mod( icc-1, mb_c ), icoffc = mod( jcc-1, nb_c ), ICROW = indxg2p( icc, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( mi+iroffc, mb_c, myrow, icrow, nprow ), send v and tau to the process row ICROW iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), ICROW = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( m+iroffc, mb_c, myrow, icrow, nprow ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), ICROW = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( m+iroffc, mb_c, myrow, icrow, nprow ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), ICROW = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( m+iroffc, mb_c, myrow, icrow, nprow ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), ICROW = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( m+iroffc, mb_c, myrow, icrow, nprow ), iroffc = mod( icc-1, mb_c ), icoffc = mod( jcc-1, nb_c ), ICROW = indxg2p( icc, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( mi+iroffc, mb_c, myrow, icrow, nprow ), iroffc = mod( icc-1, mb_c ), icoffc = mod( jcc-1, nb_c ), ICROW = indxg2p( icc, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( mi+iroffc, mb_c, myrow, icrow, nprow ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), ICROW = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( m+iroffc, mb_c, myrow, icrow, nprow ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), ICROW = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( m+iroffc, mb_c, myrow, icrow, nprow ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), ICROW = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( m+iroffc, mb_c, myrow, icrow, nprow ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), ICROW = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( m+iroffc, mb_c, myrow, icrow, nprow ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), ICROW = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( m+iroffc, mb_c, myrow, icrow, nprow ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), ICROW = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( m+iroffc, mb_c, myrow, icrow, nprow ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), ICROW = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( m+iroffc, mb_c, myrow, icrow, nprow ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), ICROW = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( m+iroffc, mb_c, myrow, icrow, nprow ), iroffc = mod( icc-1, mb_c ), icoffc = mod( jcc-1, nb_c ), ICROW = indxg2p( icc, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( mi+iroffc, mb_c, myrow, icrow, nprow ), send v and tau to the process row ICROW iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), ICROW = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( m+iroffc, mb_c, myrow, icrow, nprow ), send v and tau to the process row ICROW iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), ICROW = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( m+iroffc, mb_c, myrow, icrow, nprow ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), ICROW = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( m+iroffc, mb_c, myrow, icrow, nprow ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), ICROW = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( m+iroffc, mb_c, myrow, icrow, nprow ), iroffc = mod( icc-1, mb_c ), icoffc = mod( jcc-1, nb_c ), ICROW = indxg2p( icc, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( mi+iroffc, mb_c, myrow, icrow, nprow ), iroffc = mod( icc-1, mb_c ), icoffc = mod( jcc-1, nb_c ), ICROW = indxg2p( icc, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( mi+iroffc, mb_c, myrow, icrow, nprow ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), ICROW = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( m+iroffc, mb_c, myrow, icrow, nprow ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), ICROW = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( m+iroffc, mb_c, myrow, icrow, nprow ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), ICROW = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( m+iroffc, mb_c, myrow, icrow, nprow ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), ICROW = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( m+iroffc, mb_c, myrow, icrow, nprow ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), ICROW = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( m+iroffc, mb_c, myrow, icrow, nprow ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), ICROW = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( m+iroffc, mb_c, myrow, icrow, nprow ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), ICROW = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( m+iroffc, mb_c, myrow, icrow, nprow ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), ICROW = indxg2p( ic, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( m+iroffc, mb_c, myrow, icrow, nprow ), iroffc = mod( icc-1, mb_c ), icoffc = mod( jcc-1, nb_c ), ICROW = indxg2p( icc, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( mi+iroffc, mb_c, myrow, icrow, nprow ), |
| ICROW2 ICROW2 send v and tau to the process row ICROW2 send v and tau to the process row ICROW2 send v and tau to the process row ICROW2 send v and tau to the process row ICROW2 send v and tau to the process row ICROW2 send v and tau to the process row ICROW2 |
| ICTXT ICTXT ICTXT = desca( ctxt_ sqnpc = sqrt( dble( nprow * npcol ) ) nq0 = numroc( n, nb, 0, 0, npcol ) ICTXT = desca( ctxt_ sqnpc = sqrt( dble( nprow * npcol ) ) lwork >= 2*( anb+1 )*( 4*nps+2 ) + ( nps + 4 ) * nps ICTXT = desca( ctxt_ sqnpc = int( sqrt( real( nprow * npcol ) ) ) ICTXT (global input) intege place. ICTXT (global input) intege the operation on the matrix. the context itself is global. ICTXT (global input) intege the operation on the matrix. the context itself is global. ICTXT (global input) intege place. ICTXT (global input) intege lwork >= 2*( anb+1 )*( 4*nps+2 ) + ( nps + 4 ) * nps ICTXT = desca( ctxt_ sqnpc = int( sqrt( dble( nprow * npcol ) ) ) ICTXT (global input) intege place. ICTXT (global input) intege the operation on the matrix. the context itself is global. ICTXT (global input) intege the operation on the matrix. the context itself is global. ICTXT (global input) intege place. ICTXT (global input) intege lwork >= 2*( anb+1 )*( 4*nps+2 ) + ( nps + 4 ) * nps ICTXT = desca( ctxt_ sqnpc = int( sqrt( real( nprow * npcol ) ) ) ICTXT = desca( ctxt_ sqnpc = sqrt( dble( nprow * npcol ) ) nq0 = numroc( n, nb, 0, 0, npcol ) ICTXT = desca( ctxt_ sqnpc = sqrt( dble( nprow * npcol ) ) lwork >= 2*( anb+1 )*( 4*nps+2 ) + ( nps + 4 ) * nps ICTXT = desca( ctxt_ sqnpc = int( sqrt( dble( nprow * npcol ) ) ) |
| ICURCOL ICURCOL icurrow : process row containing diagonal block ICURCOL : process column containing diagonal bloc they are stored along a process column icurrow : process row containing diagonal block ICURCOL : process column containing diagonal bloc they are stored along a process column icurrow : process row containing diagonal block ICURCOL : process column containing diagonal bloc they are stored along a process column icurrow : process row containing diagonal block ICURCOL : process column containing diagonal bloc they are stored along a process column icurrow : process row containing diagonal block ICURCOL : process column containing diagonal bloc they are stored along a process column icurrow : process row containing diagonal block ICURCOL : process column containing diagonal bloc they are stored along a process column |
| ICURROW ICURROW ii, jj : local indices into array a ICURROW : process row containing diagonal bloc irsc0 : pointer to part of work used to store the rowsums while ii, jj : local indices into array a ICURROW : process row containing diagonal bloc irsc0 : pointer to part of work used to store the rowsums while ii, jj : local indices into array a ICURROW : process row containing diagonal bloc irsc0 : pointer to part of work used to store the rowsums while ii, jj : local indices into array a ICURROW : process row containing diagonal bloc irsc0 : pointer to part of work used to store the rowsums while ii, jj : local indices into array a ICURROW : process row containing diagonal bloc irsc0 : pointer to part of work used to store the rowsums while ii, jj : local indices into array a ICURROW : process row containing diagonal bloc irsc0 : pointer to part of work used to store the rowsums while |
| Ideally Ideally fudge double precision, default = 2.0 a "fudge factor" to widen the gershgorin intervals. Ideally arithmetic, this needs to be larger. the default for fudge real, default = 2.0 a "fudge factor" to widen the gershgorin intervals. Ideally arithmetic, this needs to be larger. the default for |
| identical identical is required to make the odd and even frontal matrices look identical if info = n+1, then pcheev has detected heterogeneity by finding that eigenvalues were not identical acros the results from pcheev cannot be guaranteed. a default value of 10^-3 is used if orfac is negative. orfac should be identical on all processes z (local output) complex array, a default value of 10^-3 is used if orfac is negative. orfac should be identical on all processes z (local output) complex array, a default value of 10^-3 is used if orfac is negative. orfac should be identical on all processes z (local output) complex array, is required to make the odd and even frontal matrices look identical reltol times the larger (in magnitude) endpoint, or if the counts at the endpoints are identical to the count considered to have "converged". rows and that all process columns contain the same copy of bycol. the output array, byall, will be identical on all processe columns and that all process rows contain the same copy of byrow. the output array, byall, will be identical on all processe a default value of 10^-3 is used if orfac is negative. orfac should be identical on all processes z (local output) double precision array, if info = n+1, then pdsyev has detected heterogeneity by finding that eigenvalues were not identical acros the results from pdsyev cannot be guaranteed. a default value of 10^-3 is used if orfac is negative. orfac should be identical on all processes z (local output) double precision array, a default value of 10^-3 is used if orfac is negative. orfac should be identical on all processes z (local output) double precision array, most parameters set via a call to pjlaenv must be identical value to all procesors (i.e. global output). however some, is required to make the odd and even frontal matrices look identical reltol times the larger (in magnitude) endpoint, or if the counts at the endpoints are identical to the count considered to have "converged". rows and that all process columns contain the same copy of bycol. the output array, byall, will be identical on all processe columns and that all process rows contain the same copy of byrow. the output array, byall, will be identical on all processe a default value of 10^-3 is used if orfac is negative. orfac should be identical on all processes z (local output) real array, if info = n+1, then pssyev has detected heterogeneity by finding that eigenvalues were not identical acros the results from pssyev cannot be guaranteed. a default value of 10^-3 is used if orfac is negative. orfac should be identical on all processes z (local output) real array, a default value of 10^-3 is used if orfac is negative. orfac should be identical on all processes z (local output) real array, is required to make the odd and even frontal matrices look identical if info = n+1, then pzheev has detected heterogeneity by finding that eigenvalues were not identical acros the results from pzheev cannot be guaranteed. a default value of 10^-3 is used if orfac is negative. orfac should be identical on all processes z (local output) complex*16 array, a default value of 10^-3 is used if orfac is negative. orfac should be identical on all processes z (local output) complex*16 array, a default value of 10^-3 is used if orfac is negative. orfac should be identical on all processes z (local output) complex*16 array, |
| identified identified does not converge for some or all eigenvalues, info is set to 1 and the ones for which it did not are identified by does not converge for some or all eigenvalues, info is set to 1 and the ones for which it did not are identified by |
| identify identify the log of large is sufficiently large. this subroutine is intended to identify machines with a large exponent range, such as the crays of the values computed by pdlamch. this subroutine is needed because the log of large is sufficiently large. this subroutine is intended to identify machines with a large exponent range, such as the crays of the values computed by pslamch. this subroutine is needed because |
| IEEE IEEE pcheevx assumes IEEE 754 standard compliant arithmetic. to por the appropriate slmake.inc file to include the compiler switch a flag which indicates whether n(w) should be speeded up by exploiting IEEE arithmetic info (output) integer note : it is assumed that the user is on an IEEE machine. if the use to 1 (in slmake.inc). the features of ieee arithmetic that pdsyevx assumes IEEE 754 standard compliant arithmetic. to por the appropriate slmake.inc file to include the compiler switch a flag which indicates whether n(w) should be speeded up by exploiting IEEE arithmetic info (output) integer note : it is assumed that the user is on an IEEE machine. if the use to 1 (in slmake.inc). the features of ieee arithmetic that pssyevx assumes IEEE 754 standard compliant arithmetic. to por the appropriate slmake.inc file to include the compiler switch pzheevx assumes IEEE 754 standard compliant arithmetic. to por the appropriate slmake.inc file to include the compiler switch |
| IEFLAG IEFLAG IEFLAG (input) intege exploiting ieee arithmetic. IEFLAG (input) intege exploiting ieee arithmetic. |
| IFAIL IFAIL if stopping criterion was not satisfied, update info and store eigenvector number in array IFAIL approximation to the eigenvector, and the index of the eigenvector is returned in IFAIL approximation to the eigenvector, and the index of the eigenvector is returned in IFAIL IFAIL (global output) integer array, dimension (m if one or more eigenvectors fail to converge after maxits IFAIL (global output) integer array, dimension (m if one or more eigenvectors fail to converge after maxits approximation to the eigenvector, and the index of the eigenvector is returned in IFAIL approximation to the eigenvector, and the index of the eigenvector is returned in IFAIL IFAIL (global output) integer array, dimension (m if one or more eigenvectors fail to converge after maxits approximation to the eigenvector, and the index of the eigenvector is returned in IFAIL approximation to the eigenvector, and the index of the eigenvector is returned in IFAIL approximation to the eigenvector, and the index of the eigenvector is returned in IFAIL approximation to the eigenvector, and the index of the eigenvector is returned in IFAIL IFAIL (global output) integer array, dimension (m if one or more eigenvectors fail to converge after maxits if stopping criterion was not satisfied, update info and store eigenvector number in array IFAIL |
| Ignored Ignored used as an index into vecs if block is set. istart is Ignored if block is .false. istop (global input) integer used as an index into vecs if block is set. istart is Ignored if block is .false. istop (global input) integer is distributed. Ignored desca( 6 ) ignored for tridiagonal matrices is distributed. Ignored desca( 6 ) ignored for tridiagonal matrices i am not sure that this works correctly when ib and jb are not equal to 1. indeed, i suspect that ib should always be set to 1 or Ignored is distributed. Ignored desca( 6 ) ignored for tridiagonal matrices is distributed. Ignored desca( 6 ) ignored for tridiagonal matrices is distributed. Ignored desca( 6 ) ignored for tridiagonal matrices is distributed. Ignored desca( 6 ) ignored for tridiagonal matrices i am not sure that this works correctly when ib and jb are not equal to 1. indeed, i suspect that ib should always be set to 1 or Ignored is distributed. Ignored desca( 6 ) ignored for tridiagonal matrices is distributed. Ignored desca( 6 ) ignored for tridiagonal matrices is distributed. Ignored desca( 6 ) ignored for tridiagonal matrices is distributed. Ignored desca( 6 ) ignored for tridiagonal matrices i am not sure that this works correctly when ib and jb are not equal to 1. indeed, i suspect that ib should always be set to 1 or Ignored is distributed. Ignored desca( 6 ) ignored for tridiagonal matrices is distributed. Ignored desca( 6 ) ignored for tridiagonal matrices is distributed. Ignored desca( 6 ) ignored for tridiagonal matrices is distributed. Ignored desca( 6 ) ignored for tridiagonal matrices i am not sure that this works correctly when ib and jb are not equal to 1. indeed, i suspect that ib should always be set to 1 or Ignored is distributed. Ignored desca( 6 ) ignored for tridiagonal matrices is distributed. Ignored desca( 6 ) ignored for tridiagonal matrices used as an index into vecs if block is set. istart is Ignored if block is .false. istop (global input) integer used as an index into vecs if block is set. istart is Ignored if block is .false. istop (global input) integer |
| IHI IHI the main loop begins here. i is the loop index and decreases from IHI to ilo in steps of 1 or 2. each iteration of the loop work eigenvalues i+1 to ihi have already converged. either l = ilo, or ilo (global input) integer IHI (global input) intege rows ia:ia+ilo-2 and ia+ihi:ia+n-1 and columns ja:ja+jlo-2 ilo (global input) integer IHI (global input) intege rows ia:ia+ilo-2 and ia+ihi:ia+n-1 and columns ja:ja+ilo-2 the main loop begins here. i is the loop index and decreases from IHI to ilo in steps of our schur block size (<=2*iblk). eac and columns l to i. eigenvalues i+1 to ihi have already nq = m if side = 'l' and nq = n if side = 'r'. q is defined as the product of IHI-ilo elementary reflectors, as returned by pcgehrd q = h(ilo) h(ilo+1) . . . h(ihi-1). ilo (global input) integer IHI (global input) intege rows ia:ia+ilo-2 and ia+ihi:ia+n-1 and columns ja:ja+jlo-2 ilo (global input) integer IHI (global input) intege rows ia:ia+ilo-2 and ia+ihi:ia+n-1 and columns ja:ja+ilo-2 the main loop begins here. i is the loop index and decreases from IHI to ilo in steps of our schur block size (<=2*iblk). eac and columns l to i. eigenvalues i+1 to ihi have already nq = m if side = 'l' and nq = n if side = 'r'. q is defined as the product of IHI-ilo elementary reflectors, as returned by pdgehrd q = h(ilo) h(ilo+1) . . . h(ihi-1). ilo (global input) integer IHI (global input) intege rows ia:ia+ilo-2 and ia+ihi:ia+n-1 and columns ja:ja+jlo-2 ilo (global input) integer IHI (global input) intege rows ia:ia+ilo-2 and ia+ihi:ia+n-1 and columns ja:ja+ilo-2 the main loop begins here. i is the loop index and decreases from IHI to ilo in steps of our schur block size (<=2*iblk). eac and columns l to i. eigenvalues i+1 to ihi have already nq = m if side = 'l' and nq = n if side = 'r'. q is defined as the product of IHI-ilo elementary reflectors, as returned by psgehrd q = h(ilo) h(ilo+1) . . . h(ihi-1). ilo (global input) integer IHI (global input) intege rows ia:ia+ilo-2 and ia+ihi:ia+n-1 and columns ja:ja+jlo-2 ilo (global input) integer IHI (global input) intege rows ia:ia+ilo-2 and ia+ihi:ia+n-1 and columns ja:ja+ilo-2 the main loop begins here. i is the loop index and decreases from IHI to ilo in steps of our schur block size (<=2*iblk). eac and columns l to i. eigenvalues i+1 to ihi have already nq = m if side = 'l' and nq = n if side = 'r'. q is defined as the product of IHI-ilo elementary reflectors, as returned by pzgehrd q = h(ilo) h(ilo+1) . . . h(ihi-1). the main loop begins here. i is the loop index and decreases from IHI to ilo in steps of 1 or 2. each iteration of the loop work eigenvalues i+1 to ihi have already converged. either l = ilo, or |
| IHIP IHIP lwork is local input and must be at least lwork >= nb*nb + nb*max( IHIP+1, ihlp+inlq where nb = mb_a = nb_a, iroffa = mod( ia-1, nb ), lwork is local input and must be at least lwork >= nb*nb + nb*max( IHIP+1, ihlp+inlq where nb = mb_a = nb_a, iroffa = mod( ia-1, nb ), lwork is local input and must be at least lwork >= nb*nb + nb*max( IHIP+1, ihlp+inlq where nb = mb_a = nb_a, iroffa = mod( ia-1, nb ), lwork is local input and must be at least lwork >= nb*nb + nb*max( IHIP+1, ihlp+inlq where nb = mb_a = nb_a, iroffa = mod( ia-1, nb ), |
| IHLP IHLP lwork is local input and must be at least lwork >= nb*nb + nb*max( ihip+1, IHLP+inlq where nb = mb_a = nb_a, iroffa = mod( ia-1, nb ), lwork is local input and must be at least lwork >= nb*nb + nb*max( ihip+1, IHLP+inlq where nb = mb_a = nb_a, iroffa = mod( ia-1, nb ), lwork is local input and must be at least lwork >= nb*nb + nb*max( ihip+1, IHLP+inlq where nb = mb_a = nb_a, iroffa = mod( ia-1, nb ), lwork is local input and must be at least lwork >= nb*nb + nb*max( ihip+1, IHLP+inlq where nb = mb_a = nb_a, iroffa = mod( ia-1, nb ), |
| IJOB IJOB IJOB (input) intege = 0 : find an interval with desired values of n(w) at the IJOB (input) intege = 0 : when an interval is narrower than abstol, or than IJOB (input) intege = 0 : find an interval with desired values of n(w) at the IJOB (input) intege = 0 : when an interval is narrower than abstol, or than |
| ILAENV ILAENV pjlaenv is patterned after ILAENV and keeps the same interface i used at present in scalapack. most scalapack codes use the input |
| ILCM ILCM where lcmp = lcm / nprow with lcm = ILCM( nprow, npcol ) iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), ILCM, indxg2p and numroc are scalapack tool functions the subroutine blacs_gridinfo. ILCM, indxg2p and numroc are scalapack tool functions the subroutine blacs_gridinfo. ILCM, indxg2p and numroc are scalapack tool functions the subroutine blacs_gridinfo. ILCM, indxg2p and numroc are scalapack tool functions the subroutine blacs_gridinfo. ILCM, indxg2p and numroc are scalapack tool functions the subroutine blacs_gridinfo. ILCM, indxg2p and numroc are scalapack tool functions the subroutine blacs_gridinfo. ILCM, indxg2p and numroc are scalapack tool functions the subroutine blacs_gridinfo. ILCM, indxg2p and numroc are scalapack tool functions the subroutine blacs_gridinfo. ILCM, indxg2p and numroc are scalapack tool functions the subroutine blacs_gridinfo. ILCM, indxg2p and numroc are scalapack tool functions the subroutine blacs_gridinfo. ILCM, indxg2p and numroc are scalapack tool functions the subroutine blacs_gridinfo. ILCM, indxg2p and numroc are scalapack tool functions the subroutine blacs_gridinfo. ILCM, indxg2p and numroc are scalapack tool functions the subroutine blacs_gridinfo. ILCM, indxg2p and numroc are scalapack tool functions the subroutine blacs_gridinfo. where lcmp = lcm / nprow with lcm = ILCM( nprow, npcol ) iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), ILCM, indxg2p and numroc are scalapack tool functions the subroutine blacs_gridinfo. ILCM, indxg2p and numroc are scalapack tool functions the subroutine blacs_gridinfo. ILCM, indxg2p and numroc are scalapack tool functions the subroutine blacs_gridinfo. ILCM, indxg2p and numroc are scalapack tool functions the subroutine blacs_gridinfo. ILCM, indxg2p and numroc are scalapack tool functions the subroutine blacs_gridinfo. ILCM, indxg2p and numroc are scalapack tool functions the subroutine blacs_gridinfo. ILCM, indxg2p and numroc are scalapack tool functions the subroutine blacs_gridinfo. ILCM, indxg2p and numroc are scalapack tool functions the subroutine blacs_gridinfo. ILCM, indxg2p and numroc are scalapack tool functions the subroutine blacs_gridinfo. ILCM, indxg2p and numroc are scalapack tool functions the subroutine blacs_gridinfo. ILCM, indxg2p and numroc are scalapack tool functions the subroutine blacs_gridinfo. ILCM, indxg2p and numroc are scalapack tool functions the subroutine blacs_gridinfo. ILCM, indxg2p and numroc are scalapack tool functions the subroutine blacs_gridinfo. ILCM, indxg2p and numroc are scalapack tool functions the subroutine blacs_gridinfo. where lcmp = lcm / nprow with lcm = ILCM( nprow, npcol ) iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), ILCM, indxg2p and numroc are scalapack tool functions the subroutine blacs_gridinfo. ILCM, indxg2p and numroc are scalapack tool functions the subroutine blacs_gridinfo. ILCM, indxg2p and numroc are scalapack tool functions the subroutine blacs_gridinfo. ILCM, indxg2p and numroc are scalapack tool functions the subroutine blacs_gridinfo. ILCM, indxg2p and numroc are scalapack tool functions the subroutine blacs_gridinfo. ILCM, indxg2p and numroc are scalapack tool functions the subroutine blacs_gridinfo. ILCM, indxg2p and numroc are scalapack tool functions the subroutine blacs_gridinfo. ILCM, indxg2p and numroc are scalapack tool functions the subroutine blacs_gridinfo. ILCM, indxg2p and numroc are scalapack tool functions the subroutine blacs_gridinfo. ILCM, indxg2p and numroc are scalapack tool functions the subroutine blacs_gridinfo. ILCM, indxg2p and numroc are scalapack tool functions the subroutine blacs_gridinfo. ILCM, indxg2p and numroc are scalapack tool functions the subroutine blacs_gridinfo. ILCM, indxg2p and numroc are scalapack tool functions the subroutine blacs_gridinfo. ILCM, indxg2p and numroc are scalapack tool functions the subroutine blacs_gridinfo. where lcmp = lcm / nprow with lcm = ILCM( nprow, npcol ) iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), ILCM, indxg2p and numroc are scalapack tool functions the subroutine blacs_gridinfo. ILCM, indxg2p and numroc are scalapack tool functions the subroutine blacs_gridinfo. ILCM, indxg2p and numroc are scalapack tool functions the subroutine blacs_gridinfo. ILCM, indxg2p and numroc are scalapack tool functions the subroutine blacs_gridinfo. ILCM, indxg2p and numroc are scalapack tool functions the subroutine blacs_gridinfo. ILCM, indxg2p and numroc are scalapack tool functions the subroutine blacs_gridinfo. ILCM, indxg2p and numroc are scalapack tool functions the subroutine blacs_gridinfo. ILCM, indxg2p and numroc are scalapack tool functions the subroutine blacs_gridinfo. ILCM, indxg2p and numroc are scalapack tool functions the subroutine blacs_gridinfo. ILCM, indxg2p and numroc are scalapack tool functions the subroutine blacs_gridinfo. ILCM, indxg2p and numroc are scalapack tool functions the subroutine blacs_gridinfo. ILCM, indxg2p and numroc are scalapack tool functions the subroutine blacs_gridinfo. ILCM, indxg2p and numroc are scalapack tool functions the subroutine blacs_gridinfo. ILCM, indxg2p and numroc are scalapack tool functions the subroutine blacs_gridinfo. |
| ILCOL ILCOL ihlp = numroc( ihi-ilo+ioff+1, nb, myrow, ilrow, nprow ), ILCOL = indxg2p( ja+ilo-1, nb, mycol, csrc_a, npcol ) ihlp = numroc( ihi-ilo+ioff+1, nb, myrow, ilrow, nprow ), ILCOL = indxg2p( ja+ilo-1, nb, mycol, csrc_a, npcol ) ihlp = numroc( ihi-ilo+ioff+1, nb, myrow, ilrow, nprow ), ILCOL = indxg2p( ja+ilo-1, nb, mycol, csrc_a, npcol ) ihlp = numroc( ihi-ilo+ioff+1, nb, myrow, ilrow, nprow ), ILCOL = indxg2p( ja+ilo-1, nb, mycol, csrc_a, npcol ) |
| illegal illegal = 0: successful exit < 0: if info = -i, the i-th argument had an illegal valu has been completed, but the factor u is exactly = 0: successful exit < 0: if info = -i, the i-th argument had an illegal valu has been completed, but the factor u is exactly = 0: successful exit < 0: if info = -i, the i-th argument had an illegal valu ===================================================================== = 0: successful exit < 0: if info = -i, the i-th argument had an illegal valu ===================================================================== = 0: successful exit < 0: if info = -i, the i-th argument had an illegal valu has been completed, but the factor u is exactly = 0: successful exit < 0: if info = -i, the i-th argument had an illegal valu has been completed, but the factor u is exactly = 0: successful exit < 0: if info = -i, the i-th argument had an illegal valu ===================================================================== = 0: successful exit < 0: if info = -i, the i-th argument had an illegal valu ===================================================================== < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. = 0: successful exit < 0: if info = -i, the i-th argument had an illegal valu = 0: successful exit < 0: if info = -i, the i-th argument had an illegal valu <= n: u(ia+i-1,ia+i-1) is exactly zero. the < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. = 0: successful exit < 0: if info = -i, the i-th argument had an illegal valu <= n: if info = i, the leading minor of order i of a < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. = 0: successful exit < 0: if info = -i, the i-th argument had an illegal valu further details < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. = 0: successful exit < 0: if info = -i, the i-th argument had an illegal valu = 0: successful exit < 0: if info = -i, the i-th argument had an illegal valu <= n: u(ia+i-1,ia+i-1) is exactly zero. the < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. = 0: successful exit. < 0: if info = -i, the i-th argument had an illegal value < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. = 0: successful exit < 0: if info = -i, the i-th argument had an illegal valu <= n: if info = i, the leading minor of order i of a < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. = 0 : successful exit < 0 : if info = -i, the i-th argument had an illegal valu were not computed: < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. >= 0: the value of the parameter specified by ispec < 0: if pjlaenv = -k, the k-th argument had an illegal < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. = 0: successful exit < 0: if info = -i, the i-th argument had an illegal valu = 0: successful exit < 0: if info = -i, the i-th argument had an illegal valu <= n: u(ia+i-1,ia+i-1) is exactly zero. the < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. = 0: successful exit. < 0: if info = -i, the i-th argument had an illegal value < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. = 0: successful exit < 0: if info = -i, the i-th argument had an illegal valu <= n: if info = i, the leading minor of order i of a < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. = 0 : successful exit < 0 : if info = -i, the i-th argument had an illegal valu were not computed: < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. = 0: successful exit < 0: if info = -i, the i-th argument had an illegal valu = 0: successful exit < 0: if info = -i, the i-th argument had an illegal valu <= n: u(ia+i-1,ia+i-1) is exactly zero. the < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. = 0: successful exit < 0: if info = -i, the i-th argument had an illegal valu <= n: if info = i, the leading minor of order i of a < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. = 0: successful exit < 0: if info = -i, the i-th argument had an illegal valu further details < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. < 0: if the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j), if the i-t info = -i. = 0: successful exit < 0: if info = -i, the i-th argument had an illegal valu has been completed, but the factor u is exactly = 0: successful exit < 0: if info = -i, the i-th argument had an illegal valu has been completed, but the factor u is exactly = 0: successful exit < 0: if info = -i, the i-th argument had an illegal valu ===================================================================== = 0: successful exit < 0: if info = -i, the i-th argument had an illegal valu ===================================================================== = 0: successful exit < 0: if info = -i, the i-th argument had an illegal valu has been completed, but the factor u is exactly = 0: successful exit < 0: if info = -i, the i-th argument had an illegal valu has been completed, but the factor u is exactly = 0: successful exit < 0: if info = -i, the i-th argument had an illegal valu ===================================================================== = 0: successful exit < 0: if info = -i, the i-th argument had an illegal valu ===================================================================== |
| illustrated illustrated the band storage scheme is illustrated by the following example, whe the band storage scheme is illustrated by the following example, whe the contents of sub( a ) on exit are illustrated by the followin the contents of sub( a ) on exit are illustrated by the followin the contents of a(ia:ia+n-1,ja:ja+n-1) are illustrated by the follo the contents of a(ia:ia+n-1,ja:ja+n-1) are illustrated by the follow the contents of sub( a ) on exit are illustrated by the followin the contents of sub( a ) on exit are illustrated by the followin the contents of sub( a ) on exit are illustrated by the followin the contents of sub( a ) on exit are illustrated by the followin the contents of sub( a ) on exit are illustrated by the followin the contents of a(ia:ia+n-1,ja:ja+n-k) on exit are illustrated by th the shape of the matrix v and the storage of the vectors which define the h(i) is best illustrated by the following example with n = 5 an array elements are modified but restored on exit. the rest of the the shape of the matrix v and the storage of the vectors which define the h(i) is best illustrated by the following example with n = 5 an array elements are modified but restored on exit. the rest of the the contents of a on exit are illustrated by the following example the contents of sub( a ) on exit are illustrated by the followin the contents of sub( a ) on exit are illustrated by the followin the contents of a(ia:ia+n-1,ja:ja+n-1) are illustrated by the follo the contents of a(ia:ia+n-1,ja:ja+n-1) are illustrated by the follow the contents of sub( a ) on exit are illustrated by the followin the contents of a(ia:ia+n-1,ja:ja+n-k) on exit are illustrated by th the shape of the matrix v and the storage of the vectors which define the h(i) is best illustrated by the following example with n = 5 an array elements are modified but restored on exit. the rest of the the shape of the matrix v and the storage of the vectors which define the h(i) is best illustrated by the following example with n = 5 an array elements are modified but restored on exit. the rest of the the contents of a on exit are illustrated by the following example the contents of sub( a ) on exit are illustrated by the followin the contents of sub( a ) on exit are illustrated by the followin the contents of sub( a ) on exit are illustrated by the followin the contents of sub( a ) on exit are illustrated by the followin the contents of sub( a ) on exit are illustrated by the followin the contents of sub( a ) on exit are illustrated by the followin the contents of a(ia:ia+n-1,ja:ja+n-1) are illustrated by the follo the contents of a(ia:ia+n-1,ja:ja+n-1) are illustrated by the follow the contents of sub( a ) on exit are illustrated by the followin the contents of a(ia:ia+n-1,ja:ja+n-k) on exit are illustrated by th the shape of the matrix v and the storage of the vectors which define the h(i) is best illustrated by the following example with n = 5 an array elements are modified but restored on exit. the rest of the the shape of the matrix v and the storage of the vectors which define the h(i) is best illustrated by the following example with n = 5 an array elements are modified but restored on exit. the rest of the the contents of a on exit are illustrated by the following example the contents of sub( a ) on exit are illustrated by the followin the contents of sub( a ) on exit are illustrated by the followin the contents of sub( a ) on exit are illustrated by the followin the contents of sub( a ) on exit are illustrated by the followin the contents of sub( a ) on exit are illustrated by the followin the contents of sub( a ) on exit are illustrated by the followin the contents of a(ia:ia+n-1,ja:ja+n-1) are illustrated by the follo the contents of a(ia:ia+n-1,ja:ja+n-1) are illustrated by the follow the contents of sub( a ) on exit are illustrated by the followin the contents of sub( a ) on exit are illustrated by the followin the contents of sub( a ) on exit are illustrated by the followin the contents of sub( a ) on exit are illustrated by the followin the contents of sub( a ) on exit are illustrated by the followin the contents of a(ia:ia+n-1,ja:ja+n-k) on exit are illustrated by th the shape of the matrix v and the storage of the vectors which define the h(i) is best illustrated by the following example with n = 5 an array elements are modified but restored on exit. the rest of the the shape of the matrix v and the storage of the vectors which define the h(i) is best illustrated by the following example with n = 5 an array elements are modified but restored on exit. the rest of the the contents of a on exit are illustrated by the following example the band storage scheme is illustrated by the following example, whe the band storage scheme is illustrated by the following example, whe |
| ILO ILO the main loop begins here. i is the loop index and decreases from ihi to ILO in steps of 1 or 2. each iteration of the loop work eigenvalues i+1 to ihi have already converged. either l = ilo, or ILO (global input) intege it is assumed that sub( a ) is already upper triangular in ILO (global input) intege it is assumed that sub( a ) is already upper triangular in the main loop begins here. i is the loop index and decreases from ihi to ILO in steps of our schur block size (<=2*iblk). eac and columns l to i. eigenvalues i+1 to ihi have already nq = m if side = 'l' and nq = n if side = 'r'. q is defined as the product of ihi-ILO elementary reflectors, as returned by pcgehrd q = h(ilo) h(ilo+1) . . . h(ihi-1). ILO (global input) intege it is assumed that sub( a ) is already upper triangular in ILO (global input) intege it is assumed that sub( a ) is already upper triangular in the main loop begins here. i is the loop index and decreases from ihi to ILO in steps of our schur block size (<=2*iblk). eac and columns l to i. eigenvalues i+1 to ihi have already nq = m if side = 'l' and nq = n if side = 'r'. q is defined as the product of ihi-ILO elementary reflectors, as returned by pdgehrd q = h(ilo) h(ilo+1) . . . h(ihi-1). ILO (global input) intege it is assumed that sub( a ) is already upper triangular in ILO (global input) intege it is assumed that sub( a ) is already upper triangular in the main loop begins here. i is the loop index and decreases from ihi to ILO in steps of our schur block size (<=2*iblk). eac and columns l to i. eigenvalues i+1 to ihi have already nq = m if side = 'l' and nq = n if side = 'r'. q is defined as the product of ihi-ILO elementary reflectors, as returned by psgehrd q = h(ilo) h(ilo+1) . . . h(ihi-1). ILO (global input) intege it is assumed that sub( a ) is already upper triangular in ILO (global input) intege it is assumed that sub( a ) is already upper triangular in the main loop begins here. i is the loop index and decreases from ihi to ILO in steps of our schur block size (<=2*iblk). eac and columns l to i. eigenvalues i+1 to ihi have already nq = m if side = 'l' and nq = n if side = 'r'. q is defined as the product of ihi-ILO elementary reflectors, as returned by pzgehrd q = h(ilo) h(ilo+1) . . . h(ihi-1). the main loop begins here. i is the loop index and decreases from ihi to ILO in steps of 1 or 2. each iteration of the loop work eigenvalues i+1 to ihi have already converged. either l = ilo, or |
| ILROW ILROW ihip = numroc( ihi+iroffa, nb, myrow, iarow, nprow ), ILROW = indxg2p( ia+ilo-1, nb, myrow, rsrc_a, nprow ) ilcol = indxg2p( ja+ilo-1, nb, mycol, csrc_a, npcol ), ihip = numroc( ihi+iroffa, nb, myrow, iarow, nprow ), ILROW = indxg2p( ia+ilo-1, nb, myrow, rsrc_a, nprow ) ilcol = indxg2p( ja+ilo-1, nb, mycol, csrc_a, npcol ), ihip = numroc( ihi+iroffa, nb, myrow, iarow, nprow ), ILROW = indxg2p( ia+ilo-1, nb, myrow, rsrc_a, nprow ) ilcol = indxg2p( ja+ilo-1, nb, mycol, csrc_a, npcol ), ihip = numroc( ihi+iroffa, nb, myrow, iarow, nprow ), ILROW = indxg2p( ia+ilo-1, nb, myrow, rsrc_a, nprow ) ilcol = indxg2p( ja+ilo-1, nb, mycol, csrc_a, npcol ), |
| implementation implementation the minimum absolute of a "pivot" in the "paranoid" implementation of the sturm sequence loop. this must be a safe_min is at least the smallest number that can divide 1.0 pdlapdct counts the number of negative eigenvalues of (t - sigma i). this implementation of the sturm sequence loop has conditionals i floating point number. pdlapdct will be referred to as the "paranoid" the minimum absolute of a "pivot" in the "paranoid" implementation of the sturm sequence loop. this must be a safe_min is at least the smallest number that can divide 1.0 pslapdct counts the number of negative eigenvalues of (t - sigma i). this implementation of the sturm sequence loop has conditionals i floating point number. pslapdct will be referred to as the "paranoid" |
| IMPLEMENTED IMPLEMENTED IMPLEMENTED by: m. fahey, may 28, 199 ===================================================================== IMPLEMENTED by mark r. fahey, may 28, 199 ===================================================================== IMPLEMENTED by: m. fahey, may 28, 199 ===================================================================== IMPLEMENTED by: g. henry, may 1, 199 ===================================================================== IMPLEMENTED by: g. henry, november 17, 199 ===================================================================== IMPLEMENTED by: g. henry, november 17, 199 ===================================================================== currently, only algorithms designed for the case n/p >> bw are IMPLEMENTED. these go by many names, including divide and conquer currently, only algorithms designed for the case n/p >> bw are IMPLEMENTED. these go by many names, including divide and conquer currently, only algorithms designed for the case n/p >> bw are IMPLEMENTED. these go by many names, including divide and conquer for tridiagonal matrices, it is obvious: n/p >> bw(=1), and so d&c currently, only algorithms designed for the case n/p >> bw are IMPLEMENTED. these go by many names, including divide and conquer for tridiagonal matrices, it is obvious: n/p >> bw(=1), and so d&c currently, only algorithms designed for the case n/p >> bw are IMPLEMENTED. these go by many names, including divide and conquer currently, only algorithms designed for the case n/p >> bw are IMPLEMENTED. these go by many names, including divide and conquer jobz (input) character*1 = 'n': compute eigenvalues only; (not IMPLEMENTED yet IMPLEMENTED by: m. fahey, may 28, 199 ===================================================================== IMPLEMENTED by: m. fahey, may 28, 199 ===================================================================== IMPLEMENTED by: m. fahey, may 28, 199 ===================================================================== IMPLEMENTED by: m. fahey, may 28, 199 ===================================================================== currently, only algorithms designed for the case n/p >> bw are IMPLEMENTED. these go by many names, including divide and conquer currently, only algorithms designed for the case n/p >> bw are IMPLEMENTED. these go by many names, including divide and conquer currently, only algorithms designed for the case n/p >> bw are IMPLEMENTED. these go by many names, including divide and conquer for tridiagonal matrices, it is obvious: n/p >> bw(=1), and so d&c currently, only algorithms designed for the case n/p >> bw are IMPLEMENTED. these go by many names, including divide and conquer for tridiagonal matrices, it is obvious: n/p >> bw(=1), and so d&c the code robust against possible overflow. but scaling has not yet been IMPLEMENTED in pclattrs which is called by this routine to solv currently, only algorithms designed for the case n/p >> bw are IMPLEMENTED. these go by many names, including divide and conquer currently, only algorithms designed for the case n/p >> bw are IMPLEMENTED. these go by many names, including divide and conquer currently, only algorithms designed for the case n/p >> bw are IMPLEMENTED. these go by many names, including divide and conquer for tridiagonal matrices, it is obvious: n/p >> bw(=1), and so d&c currently, only algorithms designed for the case n/p >> bw are IMPLEMENTED. these go by many names, including divide and conquer for tridiagonal matrices, it is obvious: n/p >> bw(=1), and so d&c currently, only algorithms designed for the case n/p >> bw are IMPLEMENTED. these go by many names, including divide and conquer currently, only algorithms designed for the case n/p >> bw are IMPLEMENTED. these go by many names, including divide and conquer IMPLEMENTED by: g. henry, november 17, 199 ===================================================================== IMPLEMENTED by: g. henry, may 1, 199 ===================================================================== IMPLEMENTED by: g. henry, november 17, 199 ===================================================================== = 'i': sort d in increasing order; = 'd': sort d in decreasing order. (not IMPLEMENTED yet n (global input) integer IMPLEMENTED by: g. henry, november 17, 199 ===================================================================== currently, only algorithms designed for the case n/p >> bw are IMPLEMENTED. these go by many names, including divide and conquer currently, only algorithms designed for the case n/p >> bw are IMPLEMENTED. these go by many names, including divide and conquer currently, only algorithms designed for the case n/p >> bw are IMPLEMENTED. these go by many names, including divide and conquer for tridiagonal matrices, it is obvious: n/p >> bw(=1), and so d&c currently, only algorithms designed for the case n/p >> bw are IMPLEMENTED. these go by many names, including divide and conquer for tridiagonal matrices, it is obvious: n/p >> bw(=1), and so d&c compz (input) character*1 = 'n': compute eigenvalues only. (not IMPLEMENTED yet = 'v': compute eigenvectors of original dense symmetric jobz (input) character*1 = 'n': compute eigenvalues only; (not IMPLEMENTED yet currently, only algorithms designed for the case n/p >> bw are IMPLEMENTED. these go by many names, including divide and conquer currently, only algorithms designed for the case n/p >> bw are IMPLEMENTED. these go by many names, including divide and conquer currently, only algorithms designed for the case n/p >> bw are IMPLEMENTED. these go by many names, including divide and conquer for tridiagonal matrices, it is obvious: n/p >> bw(=1), and so d&c currently, only algorithms designed for the case n/p >> bw are IMPLEMENTED. these go by many names, including divide and conquer for tridiagonal matrices, it is obvious: n/p >> bw(=1), and so d&c currently, only algorithms designed for the case n/p >> bw are IMPLEMENTED. these go by many names, including divide and conquer currently, only algorithms designed for the case n/p >> bw are IMPLEMENTED. these go by many names, including divide and conquer IMPLEMENTED by: g. henry, november 17, 199 ===================================================================== IMPLEMENTED by: g. henry, may 1, 199 ===================================================================== IMPLEMENTED by: g. henry, november 17, 199 ===================================================================== = 'i': sort d in increasing order; = 'd': sort d in decreasing order. (not IMPLEMENTED yet n (global input) integer IMPLEMENTED by: g. henry, november 17, 199 ===================================================================== currently, only algorithms designed for the case n/p >> bw are IMPLEMENTED. these go by many names, including divide and conquer currently, only algorithms designed for the case n/p >> bw are IMPLEMENTED. these go by many names, including divide and conquer currently, only algorithms designed for the case n/p >> bw are IMPLEMENTED. these go by many names, including divide and conquer for tridiagonal matrices, it is obvious: n/p >> bw(=1), and so d&c currently, only algorithms designed for the case n/p >> bw are IMPLEMENTED. these go by many names, including divide and conquer for tridiagonal matrices, it is obvious: n/p >> bw(=1), and so d&c compz (input) character*1 = 'n': compute eigenvalues only. (not IMPLEMENTED yet = 'v': compute eigenvectors of original dense symmetric jobz (input) character*1 = 'n': compute eigenvalues only; (not IMPLEMENTED yet currently, only algorithms designed for the case n/p >> bw are IMPLEMENTED. these go by many names, including divide and conquer currently, only algorithms designed for the case n/p >> bw are IMPLEMENTED. these go by many names, including divide and conquer currently, only algorithms designed for the case n/p >> bw are IMPLEMENTED. these go by many names, including divide and conquer for tridiagonal matrices, it is obvious: n/p >> bw(=1), and so d&c currently, only algorithms designed for the case n/p >> bw are IMPLEMENTED. these go by many names, including divide and conquer for tridiagonal matrices, it is obvious: n/p >> bw(=1), and so d&c currently, only algorithms designed for the case n/p >> bw are IMPLEMENTED. these go by many names, including divide and conquer currently, only algorithms designed for the case n/p >> bw are IMPLEMENTED. these go by many names, including divide and conquer jobz (input) character*1 = 'n': compute eigenvalues only; (not IMPLEMENTED yet IMPLEMENTED by: m. fahey, may 28, 199 ===================================================================== IMPLEMENTED by: m. fahey, may 28, 199 ===================================================================== IMPLEMENTED by: m. fahey, may 28, 199 ===================================================================== IMPLEMENTED by: m. fahey, may 28, 199 ===================================================================== currently, only algorithms designed for the case n/p >> bw are IMPLEMENTED. these go by many names, including divide and conquer currently, only algorithms designed for the case n/p >> bw are IMPLEMENTED. these go by many names, including divide and conquer currently, only algorithms designed for the case n/p >> bw are IMPLEMENTED. these go by many names, including divide and conquer for tridiagonal matrices, it is obvious: n/p >> bw(=1), and so d&c currently, only algorithms designed for the case n/p >> bw are IMPLEMENTED. these go by many names, including divide and conquer for tridiagonal matrices, it is obvious: n/p >> bw(=1), and so d&c the code robust against possible overflow. but scaling has not yet been IMPLEMENTED in pzlattrs which is called by this routine to solv IMPLEMENTED by: g. henry, may 1, 199 ===================================================================== IMPLEMENTED by: g. henry, november 17, 199 ===================================================================== IMPLEMENTED by: g. henry, november 17, 199 ===================================================================== IMPLEMENTED by: m. fahey, may 28, 199 ===================================================================== IMPLEMENTED by mark r. fahey, may 28, 199 ===================================================================== IMPLEMENTED by: m. fahey, may 28, 199 ===================================================================== |
| implicit implicit the main implicit shift francis loops over the bulges start the main implicit shift francis loops over the bulges start |
| implicitly implicitly in particular, if sub( b ) is square and nonsingular, the gqr factorization of sub( a ) and sub( b ) implicitly gives the q in particular, if sub( b ) is square and nonsingular, the grq factorization of sub( a ) and sub( b ) implicitly gives the r products. x and v are aligned with the distributed matrix a, this information is implicitly contained within iv, ix, descv, and descx notes in particular, if sub( b ) is square and nonsingular, the gqr factorization of sub( a ) and sub( b ) implicitly gives the q in particular, if sub( b ) is square and nonsingular, the grq factorization of sub( a ) and sub( b ) implicitly gives the r x and v are aligned with the distributed matrix a, this information is implicitly contained within iv, ix, descv, and descx notes in particular, if sub( b ) is square and nonsingular, the gqr factorization of sub( a ) and sub( b ) implicitly gives the q in particular, if sub( b ) is square and nonsingular, the grq factorization of sub( a ) and sub( b ) implicitly gives the r x and v are aligned with the distributed matrix a, this information is implicitly contained within iv, ix, descv, and descx notes in particular, if sub( b ) is square and nonsingular, the gqr factorization of sub( a ) and sub( b ) implicitly gives the q in particular, if sub( b ) is square and nonsingular, the grq factorization of sub( a ) and sub( b ) implicitly gives the r products. x and v are aligned with the distributed matrix a, this information is implicitly contained within iv, ix, descv, and descx notes |
| implies implies row pivoting and locc(n_a)+nb_a for column pivoting. this array is tied to the matrix a, ipiv(k) = l implies row row pivoting and locc(n_a)+nb_a for column pivoting. this array is tied to the matrix a, ipiv(k) = l implies row row pivoting and locc(n_a)+nb_a for column pivoting. this array is tied to the matrix a, ipiv(k) = l implies row row pivoting and locc(n_a)+nb_a for column pivoting. this array is tied to the matrix a, ipiv(k) = l implies row |
| IMPORTANT IMPORTANT non-cyclic restriction: very IMPORTANT the mapping for matrices must be blocked, reflecting the nature non-cyclic restriction: very IMPORTANT the mapping for matrices must be blocked, reflecting the nature non-cyclic restriction: very IMPORTANT the mapping for matrices must be blocked, reflecting the nature non-cyclic restriction: very IMPORTANT the mapping for matrices must be blocked, reflecting the nature non-cyclic restriction: very IMPORTANT the mapping for matrices must be blocked, reflecting the nature non-cyclic restriction: very IMPORTANT the mapping for matrices must be blocked, reflecting the nature non-cyclic restriction: very IMPORTANT the mapping for matrices must be blocked, reflecting the nature non-cyclic restriction: very IMPORTANT the mapping for matrices must be blocked, reflecting the nature non-cyclic restriction: very IMPORTANT the mapping for matrices must be blocked, reflecting the nature all of b or a submatrix of b). IMPORTANT note: the current version of this code support non-cyclic restriction: very IMPORTANT the mapping for matrices must be blocked, reflecting the nature non-cyclic restriction: very IMPORTANT the mapping for matrices must be blocked, reflecting the nature non-cyclic restriction: very IMPORTANT the mapping for matrices must be blocked, reflecting the nature non-cyclic restriction: very IMPORTANT the mapping for matrices must be blocked, reflecting the nature non-cyclic restriction: very IMPORTANT the mapping for matrices must be blocked, reflecting the nature non-cyclic restriction: very IMPORTANT the mapping for matrices must be blocked, reflecting the nature non-cyclic restriction: very IMPORTANT the mapping for matrices must be blocked, reflecting the nature non-cyclic restriction: very IMPORTANT the mapping for matrices must be blocked, reflecting the nature non-cyclic restriction: very IMPORTANT the mapping for matrices must be blocked, reflecting the nature all of b or a submatrix of b). IMPORTANT note: the current version of this code support non-cyclic restriction: very IMPORTANT the mapping for matrices must be blocked, reflecting the nature non-cyclic restriction: very IMPORTANT the mapping for matrices must be blocked, reflecting the nature non-cyclic restriction: very IMPORTANT the mapping for matrices must be blocked, reflecting the nature non-cyclic restriction: very IMPORTANT the mapping for matrices must be blocked, reflecting the nature non-cyclic restriction: very IMPORTANT the mapping for matrices must be blocked, reflecting the nature non-cyclic restriction: very IMPORTANT the mapping for matrices must be blocked, reflecting the nature non-cyclic restriction: very IMPORTANT the mapping for matrices must be blocked, reflecting the nature non-cyclic restriction: very IMPORTANT the mapping for matrices must be blocked, reflecting the nature non-cyclic restriction: very IMPORTANT the mapping for matrices must be blocked, reflecting the nature all of b or a submatrix of b). IMPORTANT note: the current version of this code support non-cyclic restriction: very IMPORTANT the mapping for matrices must be blocked, reflecting the nature non-cyclic restriction: very IMPORTANT the mapping for matrices must be blocked, reflecting the nature non-cyclic restriction: very IMPORTANT the mapping for matrices must be blocked, reflecting the nature non-cyclic restriction: very IMPORTANT the mapping for matrices must be blocked, reflecting the nature non-cyclic restriction: very IMPORTANT the mapping for matrices must be blocked, reflecting the nature non-cyclic restriction: very IMPORTANT the mapping for matrices must be blocked, reflecting the nature non-cyclic restriction: very IMPORTANT the mapping for matrices must be blocked, reflecting the nature non-cyclic restriction: very IMPORTANT the mapping for matrices must be blocked, reflecting the nature non-cyclic restriction: very IMPORTANT the mapping for matrices must be blocked, reflecting the nature all of b or a submatrix of b). IMPORTANT note: the current version of this code support |
| impossible impossible to the number of blocks) the eigenvalue w(i) belongs to. note: in the (theoretically impossible) event that bisectio to 1 and the ones for which it did not are identified by a to the number of blocks) the eigenvalue w(i) belongs to. note: in the (theoretically impossible) event that bisectio to 1 and the ones for which it did not are identified by a |
| improve improve 5. iterative refinement is applied to improve the computed solutio for it. 5. iterative refinement is applied to improve the computed solutio for it. means before entering this routine. pctrrfs does not do iterative refinement because doing so cannot improve the backward error notes 5. iterative refinement is applied to improve the computed solutio for it. 5. iterative refinement is applied to improve the computed solutio for it. means before entering this routine. pdtrrfs does not do iterative refinement because doing so cannot improve the backward error notes 5. iterative refinement is applied to improve the computed solutio for it. 5. iterative refinement is applied to improve the computed solutio for it. means before entering this routine. pstrrfs does not do iterative refinement because doing so cannot improve the backward error notes 5. iterative refinement is applied to improve the computed solutio for it. 5. iterative refinement is applied to improve the computed solutio for it. means before entering this routine. pztrrfs does not do iterative refinement because doing so cannot improve the backward error notes |
| improved improved the local pieces of the distributed matrix solution sub( x ). on exit, the improved solution vectors ix (global input) integer pchengst calls pchegst when uplo='u', hence pchengst provides improved performance only when uplo='l', ibtype=1 pchengst also calls pchegst when insufficient workspace is solution vectors sub( x ). on exit, it contains the improved solution vectors ix (global input) integer the local pieces of the distributed matrix solution sub( x ). on exit, the improved solution vectors ix (global input) integer solution vectors sub( x ). on exit, it contains the improved solution vectors ix (global input) integer pdsyngst calls pdhegst when uplo='u', hence pdhengst provides improved performance only when uplo='l', ibtype=1 pdsyngst also calls pdhegst when insufficient workspace is the local pieces of the distributed matrix solution sub( x ). on exit, the improved solution vectors ix (global input) integer solution vectors sub( x ). on exit, it contains the improved solution vectors ix (global input) integer pssyngst calls pshegst when uplo='u', hence pshengst provides improved performance only when uplo='l', ibtype=1 pssyngst also calls pshegst when insufficient workspace is the local pieces of the distributed matrix solution sub( x ). on exit, the improved solution vectors ix (global input) integer pzhengst calls pzhegst when uplo='u', hence pzhengst provides improved performance only when uplo='l', ibtype=1 pzhengst also calls pzhegst when insufficient workspace is solution vectors sub( x ). on exit, it contains the improved solution vectors ix (global input) integer |
| improves improves pcgerfs improves the computed solution to a system of linea the solutions. pcporfs improves the computed solution to a system of linea and provides error bounds and backward error estimates for the pdgerfs improves the computed solution to a system of linea the solutions. pdporfs improves the computed solution to a system of linea and provides error bounds and backward error estimates for the psgerfs improves the computed solution to a system of linea the solutions. psporfs improves the computed solution to a system of linea and provides error bounds and backward error estimates for the pzgerfs improves the computed solution to a system of linea the solutions. pzporfs improves the computed solution to a system of linea and provides error bounds and backward error estimates for the |
| inc inc to a system which does not have ieee 754 arithmetic, modify the appropriate slmake.inc file to include the compiler switc is not on an ieee mchine, set the compile time flag no_ieee to 1 (in slmake.inc). the features of ieee arithmetic tha arithmetic (b) the sign bit of a single precision floating to a system which does not have ieee 754 arithmetic, modify the appropriate slmake.inc file to include the compiler switc is not on an ieee mchine, set the compile time flag no_ieee to 1 (in slmake.inc). the features of ieee arithmetic tha arithmetic (b) the sign bit of a double precision floating to a system which does not have ieee 754 arithmetic, modify the appropriate slmake.inc file to include the compiler switc to a system which does not have ieee 754 arithmetic, modify the appropriate slmake.inc file to include the compiler switc |
| include include to a system which does not have ieee 754 arithmetic, modify the appropriate slmake.inc file to include the compiler switc to a system which does not have ieee 754 arithmetic, modify the appropriate slmake.inc file to include the compiler switc to a system which does not have ieee 754 arithmetic, modify the appropriate slmake.inc file to include the compiler switc to a system which does not have ieee 754 arithmetic, modify the appropriate slmake.inc file to include the compiler switc |
| including including currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer for tridiagonal matrices, it is obvious: n/p >> bw(=1), and so d&c currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer for tridiagonal matrices, it is obvious: n/p >> bw(=1), and so d&c currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer on exit, the lower triangle (if uplo='l') or the upper triangle (if uplo='u') of a, including the diagonal, i on exit, the lower triangle (if uplo='l') or the upper triangle (if uplo='u') of a, including the diagonal, i on exit, the lower triangle (if uplo='l') or the upper triangle (if uplo='u') of a, including the diagonal, i if jobz = 'n', then on exit the upper triangle (if uplo='u') or the lower triangle (if uplo='l') of sub( a ), including compute the 1-norm of each column, not including the diagonal currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer for tridiagonal matrices, it is obvious: n/p >> bw(=1), and so d&c currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer for tridiagonal matrices, it is obvious: n/p >> bw(=1), and so d&c currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer for tridiagonal matrices, it is obvious: n/p >> bw(=1), and so d&c currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer for tridiagonal matrices, it is obvious: n/p >> bw(=1), and so d&c currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer for tridiagonal matrices, it is obvious: n/p >> bw(=1), and so d&c currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer for tridiagonal matrices, it is obvious: n/p >> bw(=1), and so d&c on exit, the lower triangle (if uplo='l') or the upper triangle (if uplo='u') of a, including the diagonal, i on exit, the lower triangle (if uplo='l') or the upper triangle (if uplo='u') of a, including the diagonal, i on exit, the lower triangle (if uplo='l') or the upper triangle (if uplo='u') of a, including the diagonal, i if jobz = 'n', then on exit the upper triangle (if uplo='u') or the lower triangle (if uplo='l') of sub( a ), including currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer for tridiagonal matrices, it is obvious: n/p >> bw(=1), and so d&c currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer for tridiagonal matrices, it is obvious: n/p >> bw(=1), and so d&c currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer for tridiagonal matrices, it is obvious: n/p >> bw(=1), and so d&c currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer for tridiagonal matrices, it is obvious: n/p >> bw(=1), and so d&c on exit, the lower triangle (if uplo='l') or the upper triangle (if uplo='u') of a, including the diagonal, i on exit, the lower triangle (if uplo='l') or the upper triangle (if uplo='u') of a, including the diagonal, i on exit, the lower triangle (if uplo='l') or the upper triangle (if uplo='u') of a, including the diagonal, i if jobz = 'n', then on exit the upper triangle (if uplo='u') or the lower triangle (if uplo='l') of sub( a ), including currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer for tridiagonal matrices, it is obvious: n/p >> bw(=1), and so d&c currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer for tridiagonal matrices, it is obvious: n/p >> bw(=1), and so d&c currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer on exit, the lower triangle (if uplo='l') or the upper triangle (if uplo='u') of a, including the diagonal, i on exit, the lower triangle (if uplo='l') or the upper triangle (if uplo='u') of a, including the diagonal, i on exit, the lower triangle (if uplo='l') or the upper triangle (if uplo='u') of a, including the diagonal, i if jobz = 'n', then on exit the upper triangle (if uplo='u') or the lower triangle (if uplo='l') of sub( a ), including compute the 1-norm of each column, not including the diagonal currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer for tridiagonal matrices, it is obvious: n/p >> bw(=1), and so d&c currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer for tridiagonal matrices, it is obvious: n/p >> bw(=1), and so d&c |
| incorrect incorrect different processes. because of this, it is possible that a heterogeneous system may return incorrect results without any erro the array descriptor for the distributed matrix a. if desca( ctxt_ ) is incorrect, pcheevd cannot guarante the array descriptor for the distributed matrix a. if desca( ctxt_ ) is incorrect, pcheevx cannot guarante the array descriptor for the distributed matrix a. if desca( ctxt_ ) is incorrect, pchegvx cannot guarante = 3 : range='i', and the gershgorin interval initially used was incorrect. no eigenvalues were computed point arithmetic. the different processes. because of this, it is possible that a heterogeneous system may return incorrect results without any erro the different processes. because of this, it is possible that a heterogeneous system may return incorrect results without any erro the array descriptor for the distributed matrix a. if desca( ctxt_ ) is incorrect, pdsyevx cannot guarante the array descriptor for the distributed matrix a. if desca( ctxt_ ) is incorrect, pdsygvx cannot guarante = 3 : range='i', and the gershgorin interval initially used was incorrect. no eigenvalues were computed point arithmetic. the different processes. because of this, it is possible that a heterogeneous system may return incorrect results without any erro the different processes. because of this, it is possible that a heterogeneous system may return incorrect results without any erro the array descriptor for the distributed matrix a. if desca( ctxt_ ) is incorrect, pssyevx cannot guarante the array descriptor for the distributed matrix a. if desca( ctxt_ ) is incorrect, pssygvx cannot guarante different processes. because of this, it is possible that a heterogeneous system may return incorrect results without any erro the array descriptor for the distributed matrix a. if desca( ctxt_ ) is incorrect, pzheev cannot guarante the array descriptor for the distributed matrix a. if desca( ctxt_ ) is incorrect, pzheevx cannot guarante the array descriptor for the distributed matrix a. if desca( ctxt_ ) is incorrect, pzhegvx cannot guarante |
| increase increase for clustersize = n/sqrt(nprow*npcol) reorthogonalizing all eigenvectors will increase the total execution tim for clustersize > n/sqrt(nprow*npcol) execution time will for clustersize = n/sqrt(nprow*npcol) reorthogonalizing all eigenvectors will increase the total execution tim for clustersize > n/sqrt(nprow*npcol) execution time will note : if the eigenvectors obtained are not orthogonal, increase point arithmetic. cure: increase the parameter "fudge", recompile note : if the eigenvectors obtained are not orthogonal, increase performance can decrease as the workspace provided increases above the workspace amount shown below for optimal performance, greater workspace may be performance can decrease as the workspace provided increases above the workspace amount shown below for optimal performance, greater workspace may be point arithmetic. cure: increase the parameter "fudge", recompile note : if the eigenvectors obtained are not orthogonal, increase performance can decrease as the workspace provided increases above the workspace amount shown below for optimal performance, greater workspace may be performance can decrease as the workspace provided increases above the workspace amount shown below for optimal performance, greater workspace may be for clustersize = n/sqrt(nprow*npcol) reorthogonalizing all eigenvectors will increase the total execution tim for clustersize > n/sqrt(nprow*npcol) execution time will for clustersize = n/sqrt(nprow*npcol) reorthogonalizing all eigenvectors will increase the total execution tim for clustersize > n/sqrt(nprow*npcol) execution time will note : if the eigenvectors obtained are not orthogonal, increase |
| increases increases performance can decrease as the workspace provided increases above the workspace amount shown below for optimal performance, greater workspace may be performance can decrease as the workspace provided increases above the workspace amount shown below for optimal performance, greater workspace may be performance can decrease as the workspace provided increases above the workspace amount shown below for optimal performance, greater workspace may be performance can decrease as the workspace provided increases above the workspace amount shown below for optimal performance, greater workspace may be |
| increasing increasing sort into increasing orde sort into increasing orde on exit, d contains the trailing (n-k) updated eigenvalues (those which were deflated) sorted into increasing order drow (global input) integer on exit, d contains the trailing (n-k) updated eigenvalues (those which were deflated) sorted into increasing order drow (global input) integer pdlasrt sort the numbers in d in increasing order and th on exit, d contains the trailing (n-k) updated eigenvalues (those which were deflated) sorted into increasing order drow (global input) integer on exit, d contains the trailing (n-k) updated eigenvalues (those which were deflated) sorted into increasing order drow (global input) integer pslasrt sort the numbers in d in increasing order and th sort into increasing orde sort into increasing orde |
| increment increment incx - integer. on entry, incx specifies the increment for the elements o unchanged on exit. incx - integer. on entry, incx specifies the increment for the elements o unchanged on exit. incx (global input) integer the global increment for the elements of x. only two value incx must not be zero. contains the local pieces of the distributed vector sub( x ). before entry, the incremented array sub( x ) must contai incx (global input) integer the global increment for the elements of x. only two value incx must not be zero. incx (global input) integer the global increment for the elements of x. only two value incx must not be zero. incx (global input) pointer to integer the global increment for the elements of x. only two value contains the local pieces of the distributed vector sub( x ). before entry, the incremented array sub( x ) must contai incx (global input) integer the global increment for the elements of x. only two value incx must not be zero. incx (global input) pointer to integer the global increment for the elements of x. only two value incx (global input) pointer to integer the global increment for the elements of x. only two value incx (global input) pointer to integer the global increment for the elements of x. only two value contains the local pieces of the distributed vector sub( x ). before entry, the incremented array sub( x ) must contai incx (global input) integer the global increment for the elements of x. only two value incx must not be zero. incx (global input) pointer to integer the global increment for the elements of x. only two value incx (global input) pointer to integer the global increment for the elements of x. only two value incx (global input) integer the global increment for the elements of x. only two value incx must not be zero. contains the local pieces of the distributed vector sub( x ). before entry, the incremented array sub( x ) must contai incx (global input) integer the global increment for the elements of x. only two value incx must not be zero. incx (global input) integer the global increment for the elements of x. only two value incx must not be zero. incx - integer. on entry, incx specifies the increment for the elements o unchanged on exit. incx - integer. on entry, incx specifies the increment for the elements o unchanged on exit. |
| incremented incremented ( 1 + ( n - 1 )*abs( incy ) ). before entry, the incremented array y must contain the ( 1 + ( n - 1 )*abs( incy ) ). before entry, the incremented array y must contain the at the top of the loop, bindex gets incremented, hence where h = h( maxindex:n, 1:bindex-1 ) and contains the local pieces of the distributed vector sub( x ). before entry, the incremented array sub( x ) must contai contains the local pieces of the distributed vector sub( x ). before entry, the incremented array sub( x ) must contai at the top of the loop, bindex gets incremented, hence where h = h( maxindex:n, 1:bindex-1 ) and contains the local pieces of the distributed vector sub( x ). before entry, the incremented array sub( x ) must contai at the top of the loop, bindex gets incremented, hence where h = h( maxindex:n, 1:bindex-1 ) and at the top of the loop, bindex gets incremented, hence where h = h( maxindex:n, 1:bindex-1 ) and contains the local pieces of the distributed vector sub( x ). before entry, the incremented array sub( x ) must contai ( 1 + ( n - 1 )*abs( incy ) ). before entry, the incremented array y must contain the ( 1 + ( n - 1 )*abs( incy ) ). before entry, the incremented array y must contain the |
| INCV INCV tau (local input) complex, array, dimension locr(iv+k-1) if INCV = m_v, and locc(jv+k-1) otherwise. this arra vectors. tau is tied to the distributed matrix v. tau (local input) complex, array, dimension locr(iv+k-1) if INCV = m_v, and locc(jv+k-1) otherwise. this arra vectors. tau is tied to the distributed matrix v. tau (local input) double precision array, dimension locr(iv+k-1) if INCV = m_v, and locc(jv+k-1) otherwise. this arra vectors. tau is tied to the distributed matrix v. tau (local input) double precision array, dimension locr(iv+k-1) if INCV = m_v, and locc(jv+k-1) otherwise. this arra vectors. tau is tied to the distributed matrix v. tau (local input) real, array, dimension locr(iv+k-1) if INCV = m_v, and locc(jv+k-1) otherwise. this arra vectors. tau is tied to the distributed matrix v. tau (local input) real, array, dimension locr(iv+k-1) if INCV = m_v, and locc(jv+k-1) otherwise. this arra vectors. tau is tied to the distributed matrix v. tau (local input) complex*16, array, dimension locr(iv+k-1) if INCV = m_v, and locc(jv+k-1) otherwise. this arra vectors. tau is tied to the distributed matrix v. tau (local input) complex*16, array, dimension locr(iv+k-1) if INCV = m_v, and locc(jv+k-1) otherwise. this arra vectors. tau is tied to the distributed matrix v. |
| INCW INCW w - complex array of dimension at least ( 1 + ( n - 1 )*abs( INCW ) ) w - double precision array of dimension at least ( 1 + ( n - 1 )*abs( INCW ) ) w - real array of dimension at least ( 1 + ( n - 1 )*abs( INCW ) ) w - complex*16 array of dimension at least ( 1 + ( n - 1 )*abs( INCW ) ) |
| INCX INCX x - complex array of dimension at least ( 1 + ( n - 1 )*abs( INCX ) ) x - double precision array of dimension at least ( 1 + ( n - 1 )*abs( INCX ) ) pclacgv conjugates a complex vector of length n, sub( x ), where sub( x ) denotes x(ix,jx:jx+n-1) if INCX = descx( m_ ) an where alpha is a real scalar, and sub( x ) is an (n-1)-element complex distributed vector x(ix:ix+n-2,jx) if INCX = 1 an where x( i ) = sub( x ) = abs( x( ix+(jx-1)*descx(m_)+(i-1)*INCX ) ) ssq will then satisfy where sub( x ) denotes x(ix:ix+n-1,jx) if INCX = 1 where sub( x ) denotes x(ix:ix+n-1,jx:jx), if INCX = 1 where alpha is a scalar, and sub( x ) is an (n-1)-element real distributed vector x(ix:ix+n-2,jx) if INCX = 1 and x(ix,jx:jx+n-2) i where x( i ) = sub( x ) = x( ix+(jx-1)*descx(m_)+(i-1)*INCX ) value where sub( x ) denotes x(ix:ix+n-1,jx:jx), if INCX = 1 where sub( x ) denotes x(ix:ix+n-1,jx:jx), if INCX = 1 where sub( x ) denotes x(ix:ix+n-1,jx:jx), if INCX = 1 where alpha is a scalar, and sub( x ) is an (n-1)-element real distributed vector x(ix:ix+n-2,jx) if INCX = 1 and x(ix,jx:jx+n-2) i where x( i ) = sub( x ) = x( ix+(jx-1)*descx(m_)+(i-1)*INCX ) value where sub( x ) denotes x(ix:ix+n-1,jx:jx), if INCX = 1 where sub( x ) denotes x(ix:ix+n-1,jx:jx), if INCX = 1 pzlacgv conjugates a complex vector of length n, sub( x ), where sub( x ) denotes x(ix,jx:jx+n-1) if INCX = descx( m_ ) an where alpha is a real scalar, and sub( x ) is an (n-1)-element complex distributed vector x(ix:ix+n-2,jx) if INCX = 1 an where x( i ) = sub( x ) = abs( x( ix+(jx-1)*descx(m_)+(i-1)*INCX ) ) ssq will then satisfy where sub( x ) denotes x(ix:ix+n-1,jx) if INCX = 1 x - real array of dimension at least ( 1 + ( n - 1 )*abs( INCX ) ) x - complex*16 array of dimension at least ( 1 + ( n - 1 )*abs( INCX ) ) |
| INCY INCY y - complex array of dimension at least ( 1 + ( n - 1 )*abs( INCY ) ) element vector y. unchanged on exit. y - double precision array of dimension at least ( 1 + ( n - 1 )*abs( INCY ) ) element vector y. unchanged on exit. y - real array of dimension at least ( 1 + ( n - 1 )*abs( INCY ) ) element vector y. unchanged on exit. y - complex*16 array of dimension at least ( 1 + ( n - 1 )*abs( INCY ) ) element vector y. unchanged on exit. |
| INCZ INCZ z - complex array of dimension at least ( 1 + ( n - 1 )*abs( INCZ ) ) element vector z. unchanged on exit. z - double precision array of dimension at least ( 1 + ( n - 1 )*abs( INCZ ) ) element vector z. unchanged on exit. z - real array of dimension at least ( 1 + ( n - 1 )*abs( INCZ ) ) element vector z. unchanged on exit. z - complex*16 array of dimension at least ( 1 + ( n - 1 )*abs( INCZ ) ) element vector z. unchanged on exit. |
| INDCOL INDCOL INDCOL (workspace) integer array, dimension (n coltyp (workspace/output) integer array, dimension (n) INDCOL (workspace) integer array, dimension (n INDCOL (workspace) integer array, dimension (n coltyp (workspace/output) integer array, dimension (n) INDCOL (workspace) integer array, dimension (n |
| Indeed Indeed h = h( liip1:n, bindex ) and bindex = 0 Indeed, the previous loop invariant as stated above for th are null matrices. i am not sure that this works correctly when ib and jb are not equal to 1. Indeed, i suspect that ib should always be set to 1 or ignore i am not sure that this works correctly when ib and jb are not equal to 1. Indeed, i suspect that ib should always be set to 1 or ignore h = h( liip1:n, bindex ) and bindex = 0 Indeed, the previous loop invariant as stated above for th are null matrices. i am not sure that this works correctly when ib and jb are not equal to 1. Indeed, i suspect that ib should always be set to 1 or ignore h = h( liip1:n, bindex ) and bindex = 0 Indeed, the previous loop invariant as stated above for th are null matrices. h = h( liip1:n, bindex ) and bindex = 0 Indeed, the previous loop invariant as stated above for th are null matrices. i am not sure that this works correctly when ib and jb are not equal to 1. Indeed, i suspect that ib should always be set to 1 or ignore |
| independent independent the tailored codes provide performance that is essentially independent of the input data layout the tailored codes place no restrictions on ia, ja, mb or nb. the tailored codes provide performance that is essentially independent of the input data layout the tailored codes place no restrictions on ia, ja, mb or nb. the tailored codes provide performance that is essentially independent of the input data layout the tailored codes place no restrictions on ia, ja, mb or nb. the tailored codes provide performance that is essentially independent of the input data layout the tailored codes place no restrictions on ia, ja, mb or nb. |
| independently independently 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary |
| index index ccombamax1 finds the element having maximum real part absolute value as well as its corresponding globl index arguments ju is the index of the last column affected by the curren the main loop begins here. i is the loop index and decreases fro with the active submatrix in rows and columns l to i. specifies the "number" of the first reflector. this is used as an index into vecs if block is set ju is the index of the last column affected by the curren specifies the "number" of the first reflector. this is used as an index into vecs if block is set ja (global input) integer the index in the global array a that points to the start o or a submatrix of a). ja (global input) integer the index in the global array a that points to the start o or a submatrix of a). ja (global input) integer the index in the global array a that points to the start o or a submatrix of a). ja (global input) integer the index in the global array a that points to the start o or a submatrix of a). ja (global input) integer the index in the global array a that points to the start o or a submatrix of a). ja (global input) integer the index in the global array a that points to the start o or a submatrix of a). ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer a's global row index, which points to the beginning of th ia (global input) integer a's global row index, which points to the beginning of th ia (global input) integer a's global row index, which points to the beginning of th ia (global input) integer a's global row index, which points to the beginning of th ia (global input) integer a's global row index, which points to the beginning of th ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer a's global row index, which points to the beginning of th ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ix (global input) integer the row index in the global array x indicating the firs iv (global input) integer the row index in the global array v indicating the firs ia (global input) integer the row index in the global array a indicating the firs by using rev 0 & 1, data can be sent out and returned again. if rev=0, then ii is destination row index for the node(s if ii>=0,jj>=0, then node (ii,jj) receives the data ia (global input) integer the row index in the global array a indicating the firs iz (global input) integer z's global row index, which points to the beginning of th the main loop begins here. i is the loop index and decreases fro iteration of the loop works with the active submatrix in rows ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer a's global row index, which points to the beginning o ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs iv (global input) integer the row index in the global array v indicating the firs iax (global input) integer the global row index in x of x(iax,jax) jax (global input) integer iv (global input) integer the row index in the global array v indicating the firs iv (global input) integer the row index in the global array v indicating the firs iv (global input) integer the row index in the global array v indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ix (global input) integer the row index in the global array x indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs pcmax1 computes the global index of the maximum element in absolut in indx and the value is returned in amax, ja (global input) integer the index in the global array a that points to the start o or a submatrix of a). ja (global input) integer the index in the global array a that points to the start o or a submatrix of a). ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ja (global input) integer the index in the global array a that points to the start o or a submatrix of a). ja (global input) integer the index in the global array a that points to the start o or a submatrix of a). ix (global input) pointer to integer the global row index of the submatrix of the distribute iz (global input) integer z's global row index, which points to the beginning of th ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs if side = 'r', 1 <= ilo <= ihi <= max(1,n); ilo and ihi are relative indexes a (local input) complex pointer into the local memory ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ja (global input) integer the index in the global array a that points to the start o or a submatrix of a). ja (global input) integer the index in the global array a that points to the start o or a submatrix of a). ja (global input) integer the index in the global array a that points to the start o or a submatrix of a). ja (global input) integer the index in the global array a that points to the start o or a submatrix of a). ja (global input) integer the index in the global array a that points to the start o or a submatrix of a). ja (global input) integer the index in the global array a that points to the start o or a submatrix of a). ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs iv (global input) integer the row index in the global array v indicating the firs ia (global input) integer the row index in the global array a indicating the firs by using rev 0 & 1, data can be sent out and returned again. if rev=0, then ii is destination row index for the node(s if ii>=0,jj>=0, then node (ii,jj) receives the data ia (global input) integer the row index in the global array a indicating the firs i = kf, ... , kl-1, have "converged". pdlaecv modifies kf to be the index of the last converged interval have converged. note that the input intervals may be reordered by iq (global input) integer q's global row index, which points to the beginning of th id (global input) integer q's global row/col index, which points to the beginnin iz (global input) integer z's global row index, which points to the beginning of th the main loop begins here. i is the loop index and decreases fro iteration of the loop works with the active submatrix in rows ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer a's global row index, which points to the beginning o ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs iv (global input) integer the row index in the global array v indicating the firs iax (global input) integer the global row index in x of x(iax,jax) jax (global input) integer iv (global input) integer the row index in the global array v indicating the firs iv (global input) integer the row index in the global array v indicating the firs iv (global input) integer the row index in the global array v indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs iq (global input) integer the row index in the global array a indicating the firs ix (global input) integer the row index in the global array x indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs if side = 'r', 1 <= ilo <= ihi <= max(1,n); ilo and ihi are relative indexes a (local input) double precision pointer into the local memory ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ja (global input) integer the index in the global array a that points to the start o or a submatrix of a). ja (global input) integer the index in the global array a that points to the start o or a submatrix of a). ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ja (global input) integer the index in the global array a that points to the start o or a submatrix of a). ja (global input) integer the index in the global array a that points to the start o or a submatrix of a). ix (global input) pointer to integer the global row index of the submatrix of the distribute parallel. the user may ask for all eigenvalues, all eigenvalues in the interval [vl, vu], or the eigenvalues indexed il through iu. results in all processes finding an (almost) equal number of iq (global input) integer q's global row index, which points to the beginning of th iz (global input) integer z's global row index, which points to the beginning of th ia (global input) integer a's global row index, which points to the beginning of th ia (global input) integer a's global row index, which points to the beginning of th ia (global input) integer a's global row index, which points to the beginning of th ia (global input) integer a's global row index, which points to the beginning of th ia (global input) integer a's global row index, which points to the beginning of th ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer a's global row index, which points to the beginning of th ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ix (global input) pointer to integer the global row index of the submatrix of the distribute ix (global input) pointer to integer the global row index of the submatrix of the distribute ja (global input) integer the index in the global array a that points to the start o or a submatrix of a). ja (global input) integer the index in the global array a that points to the start o or a submatrix of a). ja (global input) integer the index in the global array a that points to the start o or a submatrix of a). ja (global input) integer the index in the global array a that points to the start o or a submatrix of a). ja (global input) integer the index in the global array a that points to the start o or a submatrix of a). ja (global input) integer the index in the global array a that points to the start o or a submatrix of a). ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs iv (global input) integer the row index in the global array v indicating the firs ia (global input) integer the row index in the global array a indicating the firs by using rev 0 & 1, data can be sent out and returned again. if rev=0, then ii is destination row index for the node(s if ii>=0,jj>=0, then node (ii,jj) receives the data ia (global input) integer the row index in the global array a indicating the firs i = kf, ... , kl-1, have "converged". pslaecv modifies kf to be the index of the last converged interval have converged. note that the input intervals may be reordered by iq (global input) integer q's global row index, which points to the beginning of th id (global input) integer q's global row/col index, which points to the beginnin iz (global input) integer z's global row index, which points to the beginning of th the main loop begins here. i is the loop index and decreases fro iteration of the loop works with the active submatrix in rows ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer a's global row index, which points to the beginning o ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs iv (global input) integer the row index in the global array v indicating the firs iax (global input) integer the global row index in x of x(iax,jax) jax (global input) integer iv (global input) integer the row index in the global array v indicating the firs iv (global input) integer the row index in the global array v indicating the firs iv (global input) integer the row index in the global array v indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs iq (global input) integer the row index in the global array a indicating the firs ix (global input) integer the row index in the global array x indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs if side = 'r', 1 <= ilo <= ihi <= max(1,n); ilo and ihi are relative indexes a (local input) real pointer into the local memory ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ja (global input) integer the index in the global array a that points to the start o or a submatrix of a). ja (global input) integer the index in the global array a that points to the start o or a submatrix of a). ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ja (global input) integer the index in the global array a that points to the start o or a submatrix of a). ja (global input) integer the index in the global array a that points to the start o or a submatrix of a). ix (global input) pointer to integer the global row index of the submatrix of the distribute parallel. the user may ask for all eigenvalues, all eigenvalues in the interval [vl, vu], or the eigenvalues indexed il through iu. results in all processes finding an (almost) equal number of iq (global input) integer q's global row index, which points to the beginning of th iz (global input) integer z's global row index, which points to the beginning of th ia (global input) integer a's global row index, which points to the beginning of th ia (global input) integer a's global row index, which points to the beginning of th ia (global input) integer a's global row index, which points to the beginning of th ia (global input) integer a's global row index, which points to the beginning of th ia (global input) integer a's global row index, which points to the beginning of th ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer a's global row index, which points to the beginning of th ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ja (global input) integer the index in the global array a that points to the start o or a submatrix of a). ja (global input) integer the index in the global array a that points to the start o or a submatrix of a). ix (global input) pointer to integer the global row index of the submatrix of the distribute ja (global input) integer the index in the global array a that points to the start o or a submatrix of a). ja (global input) integer the index in the global array a that points to the start o or a submatrix of a). ja (global input) integer the index in the global array a that points to the start o or a submatrix of a). ja (global input) integer the index in the global array a that points to the start o or a submatrix of a). ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer a's global row index, which points to the beginning of th ia (global input) integer a's global row index, which points to the beginning of th ia (global input) integer a's global row index, which points to the beginning of th ia (global input) integer a's global row index, which points to the beginning of th ia (global input) integer a's global row index, which points to the beginning of th ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer a's global row index, which points to the beginning of th ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ix (global input) integer the row index in the global array x indicating the firs iv (global input) integer the row index in the global array v indicating the firs ia (global input) integer the row index in the global array a indicating the firs by using rev 0 & 1, data can be sent out and returned again. if rev=0, then ii is destination row index for the node(s if ii>=0,jj>=0, then node (ii,jj) receives the data ia (global input) integer the row index in the global array a indicating the firs iz (global input) integer z's global row index, which points to the beginning of th the main loop begins here. i is the loop index and decreases fro iteration of the loop works with the active submatrix in rows ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer a's global row index, which points to the beginning o ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs iv (global input) integer the row index in the global array v indicating the firs iax (global input) integer the global row index in x of x(iax,jax) jax (global input) integer iv (global input) integer the row index in the global array v indicating the firs iv (global input) integer the row index in the global array v indicating the firs iv (global input) integer the row index in the global array v indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ix (global input) integer the row index in the global array x indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs pzmax1 computes the global index of the maximum element in absolut in indx and the value is returned in amax, ja (global input) integer the index in the global array a that points to the start o or a submatrix of a). ja (global input) integer the index in the global array a that points to the start o or a submatrix of a). ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ja (global input) integer the index in the global array a that points to the start o or a submatrix of a). ja (global input) integer the index in the global array a that points to the start o or a submatrix of a). iz (global input) integer z's global row index, which points to the beginning of th ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs if side = 'r', 1 <= ilo <= ihi <= max(1,n); ilo and ihi are relative indexes a (local input) complex*16 pointer into the local memory ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ia (global input) integer the row index in the global array a indicating the firs ju is the index of the last column affected by the curren specifies the "number" of the first reflector. this is used as an index into vecs if block is set zcombamax1 finds the element having maximum real part absolute value as well as its corresponding globl index arguments ju is the index of the last column affected by the curren the main loop begins here. i is the loop index and decreases fro with the active submatrix in rows and columns l to i. specifies the "number" of the first reflector. this is used as an index into vecs if block is set |
| indexed indexed due to insufficient workspace (see lwork, orfac and info). eigenvectors corresponding to clusters of eigenvalues indexed reorthogonalized due to lack of workspace. hence the due to insufficient workspace (see lwork, orfac and info). eigenvectors corresponding to clusters of eigenvalues indexed reorthogonalized due to lack of workspace. hence the the eigenvectors computed by each process. process i computes eigenvectors indexed iwork(i+2)+1 thru' iwork(i+3) liwork (local input) integer parallel. the user may ask for all eigenvalues, all eigenvalues in the interval [vl, vu], or the eigenvalues indexed il through iu. results in all processes finding an (almost) equal number of the eigenvectors computed by each process. process i computes eigenvectors indexed iwork(i+2)+1 thru' iwork(i+3) liwork (local input) integer due to insufficient workspace (see lwork, orfac and info). eigenvectors corresponding to clusters of eigenvalues indexed reorthogonalized due to lack of workspace. hence the due to insufficient workspace (see lwork, orfac and info). eigenvectors corresponding to clusters of eigenvalues indexed reorthogonalized due to lack of workspace. hence the parallel. the user may ask for all eigenvalues, all eigenvalues in the interval [vl, vu], or the eigenvalues indexed il through iu. results in all processes finding an (almost) equal number of the eigenvectors computed by each process. process i computes eigenvectors indexed iwork(i+2)+1 thru' iwork(i+3) liwork (local input) integer due to insufficient workspace (see lwork, orfac and info). eigenvectors corresponding to clusters of eigenvalues indexed reorthogonalized due to lack of workspace. hence the due to insufficient workspace (see lwork, orfac and info). eigenvectors corresponding to clusters of eigenvalues indexed reorthogonalized due to lack of workspace. hence the due to insufficient workspace (see lwork, orfac and info). eigenvectors corresponding to clusters of eigenvalues indexed reorthogonalized due to lack of workspace. hence the due to insufficient workspace (see lwork, orfac and info). eigenvectors corresponding to clusters of eigenvalues indexed reorthogonalized due to lack of workspace. hence the the eigenvectors computed by each process. process i computes eigenvectors indexed iwork(i+2)+1 thru' iwork(i+3) liwork (local input) integer |
| indexes indexes get grid parameters and local indexes get grid parameters and local indexes figure local indexes figure local indexes figure local indexes figure local indexes if side = 'r', 1 <= ilo <= ihi <= max(1,n); ilo and ihi are relative indexes a (local input) complex pointer into the local memory get grid parameters and local indexes figure local indexes figure local indexes if side = 'r', 1 <= ilo <= ihi <= max(1,n); ilo and ihi are relative indexes a (local input) double precision pointer into the local memory get grid parameters and local indexes figure local indexes figure local indexes if side = 'r', 1 <= ilo <= ihi <= max(1,n); ilo and ihi are relative indexes a (local input) real pointer into the local memory get grid parameters and local indexes get grid parameters and local indexes figure local indexes figure local indexes figure local indexes figure local indexes if side = 'r', 1 <= ilo <= ihi <= max(1,n); ilo and ihi are relative indexes a (local input) complex*16 pointer into the local memory |
| indicate indicate required. on return, the iwork(2) through iwork(p+2) indicate eigenvectors indexed iwork(i+2)+1 thru' iwork(i+3). coltyp (workspace/output) integer array, dimension (n) during execution, a label which will indicate which of th 1 : non-zero in the upper half only; required. on return, the iwork(2) through iwork(p+2) indicate eigenvectors indexed iwork(i+2)+1 thru' iwork(i+3). coltyp (workspace/output) integer array, dimension (n) during execution, a label which will indicate which of th 1 : non-zero in the upper half only; required. on return, the iwork(2) through iwork(p+2) indicate eigenvectors indexed iwork(i+2)+1 thru' iwork(i+3). required. on return, the iwork(2) through iwork(p+2) indicate eigenvectors indexed iwork(i+2)+1 thru' iwork(i+3). |
| indicated indicated 2nd dimension (as if the grid were 1-by-p). this choice is indicated by the descriptor type (501 or 502 2nd dimension (as if the grid were 1-by-p). this choice is indicated by the descriptor type (501 or 502 2nd dimension (as if the grid were 1-by-p). this choice is indicated by the descriptor type (501 or 502 however, for tridiagonal matrices, since the objects being 2nd dimension (as if the grid were 1-by-p). this choice is indicated by the descriptor type (501 or 502 however, for tridiagonal matrices, since the objects being 2nd dimension (as if the grid were 1-by-p). this choice is indicated by the descriptor type (501 or 502 2nd dimension (as if the grid were 1-by-p). this choice is indicated by the descriptor type (501 or 502 rcond = 0), the matrix is singular to working precision. this condition is indicated by a return code of info > 0 ferr (local output) real array, dimension locc(n_b) eigenvectors could not be reorthogonalized. the output values in this array correspond to the clusters indicated eigenvectors correspoding to the i^th cluster may be as high eigenvectors could not be reorthogonalized. the output values in this array correspond to the clusters indicated eigenvectors correspoding to the i^th cluster may be as high pclapiv applies either p (permutation matrix indicated by ipiv sub( a ) = a(ia:ia+m-1,ja:ja+n-1), resulting in row or column pclapv2 applies either p (permutation matrix indicated by ipiv a(ia:ia+m-1,ja:ja+n-1), resulting in row or column pivoting. the 2nd dimension (as if the grid were 1-by-p). this choice is indicated by the descriptor type (501 or 502 2nd dimension (as if the grid were 1-by-p). this choice is indicated by the descriptor type (501 or 502 is singular to working precision. this condition is indicated by a return code of info > 0, and the solution an 2nd dimension (as if the grid were 1-by-p). this choice is indicated by the descriptor type (501 or 502 however, for tridiagonal matrices, since the objects being 2nd dimension (as if the grid were 1-by-p). this choice is indicated by the descriptor type (501 or 502 however, for tridiagonal matrices, since the objects being values in this array correspond to the info/(m+1) clusters indicated by the array iclustr. as a result, the dot produc as high as ( o(n)*macheps ) / gap(i). 2nd dimension (as if the grid were 1-by-p). this choice is indicated by the descriptor type (501 or 502 2nd dimension (as if the grid were 1-by-p). this choice is indicated by the descriptor type (501 or 502 2nd dimension (as if the grid were 1-by-p). this choice is indicated by the descriptor type (501 or 502 however, for tridiagonal matrices, since the objects being 2nd dimension (as if the grid were 1-by-p). this choice is indicated by the descriptor type (501 or 502 however, for tridiagonal matrices, since the objects being 2nd dimension (as if the grid were 1-by-p). this choice is indicated by the descriptor type (501 or 502 2nd dimension (as if the grid were 1-by-p). this choice is indicated by the descriptor type (501 or 502 rcond = 0), the matrix is singular to working precision. this condition is indicated by a return code of info > 0 ferr (local output) double precision array, dimension locc(n_b) pdlapiv applies either p (permutation matrix indicated by ipiv sub( a ) = a(ia:ia+m-1,ja:ja+n-1), resulting in row or column pdlapv2 applies either p (permutation matrix indicated by ipiv a(ia:ia+m-1,ja:ja+n-1), resulting in row or column pivoting. the 2nd dimension (as if the grid were 1-by-p). this choice is indicated by the descriptor type (501 or 502 2nd dimension (as if the grid were 1-by-p). this choice is indicated by the descriptor type (501 or 502 is singular to working precision. this condition is indicated by a return code of info > 0, and the solution an 2nd dimension (as if the grid were 1-by-p). this choice is indicated by the descriptor type (501 or 502 however, for tridiagonal matrices, since the objects being 2nd dimension (as if the grid were 1-by-p). this choice is indicated by the descriptor type (501 or 502 however, for tridiagonal matrices, since the objects being values in this array correspond to the info/(m+1) clusters indicated by the array iclustr. as a result, the dot produc as high as ( o(n)*macheps ) / gap(i). eigenvectors could not be reorthogonalized. the output values in this array correspond to the clusters indicated eigenvectors correspoding to the i^th cluster may be as high eigenvectors could not be reorthogonalized. the output values in this array correspond to the clusters indicated eigenvectors correspoding to the i^th cluster may be as high 2nd dimension (as if the grid were 1-by-p). this choice is indicated by the descriptor type (501 or 502 2nd dimension (as if the grid were 1-by-p). this choice is indicated by the descriptor type (501 or 502 2nd dimension (as if the grid were 1-by-p). this choice is indicated by the descriptor type (501 or 502 however, for tridiagonal matrices, since the objects being 2nd dimension (as if the grid were 1-by-p). this choice is indicated by the descriptor type (501 or 502 however, for tridiagonal matrices, since the objects being 2nd dimension (as if the grid were 1-by-p). this choice is indicated by the descriptor type (501 or 502 2nd dimension (as if the grid were 1-by-p). this choice is indicated by the descriptor type (501 or 502 rcond = 0), the matrix is singular to working precision. this condition is indicated by a return code of info > 0 ferr (local output) real array, dimension locc(n_b) pslapiv applies either p (permutation matrix indicated by ipiv sub( a ) = a(ia:ia+m-1,ja:ja+n-1), resulting in row or column pslapv2 applies either p (permutation matrix indicated by ipiv a(ia:ia+m-1,ja:ja+n-1), resulting in row or column pivoting. the 2nd dimension (as if the grid were 1-by-p). this choice is indicated by the descriptor type (501 or 502 2nd dimension (as if the grid were 1-by-p). this choice is indicated by the descriptor type (501 or 502 is singular to working precision. this condition is indicated by a return code of info > 0, and the solution an 2nd dimension (as if the grid were 1-by-p). this choice is indicated by the descriptor type (501 or 502 however, for tridiagonal matrices, since the objects being 2nd dimension (as if the grid were 1-by-p). this choice is indicated by the descriptor type (501 or 502 however, for tridiagonal matrices, since the objects being values in this array correspond to the info/(m+1) clusters indicated by the array iclustr. as a result, the dot produc as high as ( o(n)*macheps ) / gap(i). eigenvectors could not be reorthogonalized. the output values in this array correspond to the clusters indicated eigenvectors correspoding to the i^th cluster may be as high eigenvectors could not be reorthogonalized. the output values in this array correspond to the clusters indicated eigenvectors correspoding to the i^th cluster may be as high 2nd dimension (as if the grid were 1-by-p). this choice is indicated by the descriptor type (501 or 502 2nd dimension (as if the grid were 1-by-p). this choice is indicated by the descriptor type (501 or 502 2nd dimension (as if the grid were 1-by-p). this choice is indicated by the descriptor type (501 or 502 however, for tridiagonal matrices, since the objects being 2nd dimension (as if the grid were 1-by-p). this choice is indicated by the descriptor type (501 or 502 however, for tridiagonal matrices, since the objects being 2nd dimension (as if the grid were 1-by-p). this choice is indicated by the descriptor type (501 or 502 2nd dimension (as if the grid were 1-by-p). this choice is indicated by the descriptor type (501 or 502 rcond = 0), the matrix is singular to working precision. this condition is indicated by a return code of info > 0 ferr (local output) double precision array, dimension locc(n_b) eigenvectors could not be reorthogonalized. the output values in this array correspond to the clusters indicated eigenvectors correspoding to the i^th cluster may be as high eigenvectors could not be reorthogonalized. the output values in this array correspond to the clusters indicated eigenvectors correspoding to the i^th cluster may be as high pzlapiv applies either p (permutation matrix indicated by ipiv sub( a ) = a(ia:ia+m-1,ja:ja+n-1), resulting in row or column pzlapv2 applies either p (permutation matrix indicated by ipiv a(ia:ia+m-1,ja:ja+n-1), resulting in row or column pivoting. the 2nd dimension (as if the grid were 1-by-p). this choice is indicated by the descriptor type (501 or 502 2nd dimension (as if the grid were 1-by-p). this choice is indicated by the descriptor type (501 or 502 is singular to working precision. this condition is indicated by a return code of info > 0, and the solution an 2nd dimension (as if the grid were 1-by-p). this choice is indicated by the descriptor type (501 or 502 however, for tridiagonal matrices, since the objects being 2nd dimension (as if the grid were 1-by-p). this choice is indicated by the descriptor type (501 or 502 however, for tridiagonal matrices, since the objects being values in this array correspond to the info/(m+1) clusters indicated by the array iclustr. as a result, the dot produc as high as ( o(n)*macheps ) / gap(i). |
| indicates indicates matrix s was not originally in schur form. 0 indicates successful completion implemented by: g. henry, november 17, 1996 ifail provides additional information when info .ne. 0 if (mod(info/16,2).ne.0) then ifail(1) indicates the order o if (mod(info,2).ne.0) on exit, then ifail contains the in the following overview of the steps performed, m in the margin indicates message traffic and c indicates o(n^2 nb/sqrt(p) key (global input) integer array, dimension( n ) indicates the actual index (after sorting) for each of th direct (global input) character indicates how q is formed from a product of elementar = 'f': q = h(1) h(2) . . . h(k) (forward) direct (global input) character indicates how h is formed from a product of elementar = 'f': h = h(1) h(2) . . . h(k) (forward, not supported yet) ieflag (input) integer a flag which indicates whether n(w) should be speeded up b key (global input) integer array, dimension( n ) indicates the actual index (after sorting) for each of th direct (global input) character indicates how q is formed from a product of elementar = 'f': q = h(1) h(2) . . . h(k) (forward) direct (global input) character indicates how h is formed from a product of elementar = 'f': h = h(1) h(2) . . . h(k) (forward, not supported yet) ifail provides additional information when info .ne. 0 if (mod(info/16,2).ne.0) then ifail(1) indicates the order o if (mod(info,2).ne.0) on exit, then ifail contains the in the following overview of the steps performed, m in the margin indicates message traffic and c indicates o(n^2 nb/sqrt(p) ieflag (input) integer a flag which indicates whether n(w) should be speeded up b key (global input) integer array, dimension( n ) indicates the actual index (after sorting) for each of th direct (global input) character indicates how q is formed from a product of elementar = 'f': q = h(1) h(2) . . . h(k) (forward) direct (global input) character indicates how h is formed from a product of elementar = 'f': h = h(1) h(2) . . . h(k) (forward, not supported yet) ifail provides additional information when info .ne. 0 if (mod(info/16,2).ne.0) then ifail(1) indicates the order o if (mod(info,2).ne.0) on exit, then ifail contains the in the following overview of the steps performed, m in the margin indicates message traffic and c indicates o(n^2 nb/sqrt(p) ifail provides additional information when info .ne. 0 if (mod(info/16,2).ne.0) then ifail(1) indicates the order o if (mod(info,2).ne.0) on exit, then ifail contains the in the following overview of the steps performed, m in the margin indicates message traffic and c indicates o(n^2 nb/sqrt(p) key (global input) integer array, dimension( n ) indicates the actual index (after sorting) for each of th direct (global input) character indicates how q is formed from a product of elementar = 'f': q = h(1) h(2) . . . h(k) (forward) direct (global input) character indicates how h is formed from a product of elementar = 'f': h = h(1) h(2) . . . h(k) (forward, not supported yet) matrix s was not originally in schur form. 0 indicates successful completion implemented by: g. henry, november 17, 1996 |
| indicating indicating dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a(global) desca( dtype_) the descriptor type. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating the blacs process grid a is distribu bal, but the handle (the integer dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- ia (global input) integer the row index in the global array a indicating the firs dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dt_a = 1. ctxt_a (global) desca[ ctxt_ ] the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- ictxt (global input) integer the blacs context handle, indicating the global context o ictxt (global input) integer the blacs context handle, indicating the global context o dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- ia (global input) integer the row index in the global array a indicating the firs dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- iq (global input) integer the row index in the global array a indicating the firs dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dt_a = 1. ctxt_a (global) desca[ ctxt_ ] the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a(global) desca( dtype_) the descriptor type. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating the blacs process grid a is distribu bal, but the handle (the integer dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- ictxt (global input) integer the blacs context handle, indicating the global context o ictxt (global input) integer the blacs context handle, indicating the global context o dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- ia (global input) integer the row index in the global array a indicating the firs dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- iq (global input) integer the row index in the global array a indicating the firs dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dt_a = 1. ctxt_a (global) desca[ ctxt_ ] the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a(global) desca( dtype_) the descriptor type. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating the blacs process grid a is distribu bal, but the handle (the integer dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dt_a = 1. ctxt_a (global) desca[ ctxt_ ] the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a(global) desca( dtype_) the descriptor type. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating the blacs process grid a is distribu bal, but the handle (the integer dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- ia (global input) integer the row index in the global array a indicating the firs dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- dtype_a = 1. ctxt_a (global) desca( ctxt_ ) the blacs context handle, indicating ted over. the context itself is glo- |
| indices indices i1 and i2 are the indices of the first row and last column of being computed, i1 and i2 are set inside the main loop. find starting and ending indices of block nblk ipiv (local output) integer array, dimension >= desca( nb ). pivot indices for local factorizations factorization and solve. ipiv (local output) integer array, dimension >= desca( nb ). pivot indices for local factorizations factorization and solve. locr(m_a)+mb_a. if fact = 'f', then ipiv is an input argu- ment and on entry contains the pivot indices from the fac pcgetrf; ipiv(i) -> the global row local row i was of scalapack routines. eigenvalues/vectors can be selected by specifying a range of values or a range of indices for the desire if (mod(info,2).ne.0) on exit, then ifail contains the indices of the eigenvectors that failed to converge if neither of the above error conditions hold and jobz = 'v', the following variables are global indices into a maxindex: the global row and column for the first row and set work array indices ii, jj : local indices into array icurcol : process column containing diagonal block ii, jj : local indices into array icurcol : process column containing diagonal block type (global input) character type indices the storage type of the input distribute = 'g': sub( a ) is a full matrix, iblock (global input) integer array, dimension (n) the submatrix indices associated with the correspondin first submatrix from the top, 2 for those belonging to ipiv (local output) integer array, dimension >= desca( nb ). pivot indices for local factorizations factorization and solve. ipiv (local output) integer array, dimension >= desca( nb ). pivot indices for local factorizations factorization and solve. locr(m_a)+mb_a. if fact = 'f', then ipiv is an input argu- ment and on entry contains the pivot indices from the fac pdgetrf; ipiv(i) -> the global row local row i was set work array indices ii, jj : local indices into array icurcol : process column containing diagonal block type (global input) character type indices the storage type of the input distribute = 'g': sub( a ) is a full matrix, iblock (global input) integer array, dimension (n) the submatrix indices associated with the correspondin first submatrix from the top, 2 for those belonging to of scalapack routines. eigenvalues/vectors can be selected by specifying a range of values or a range of indices for the desire if (mod(info,2).ne.0) on exit, then ifail contains the indices of the eigenvectors that failed to converge if neither of the above error conditions hold and jobz = 'v', the following variables are global indices into a maxindex: the global row and column for the first row and ipiv (local output) integer array, dimension >= desca( nb ). pivot indices for local factorizations factorization and solve. ipiv (local output) integer array, dimension >= desca( nb ). pivot indices for local factorizations factorization and solve. locr(m_a)+mb_a. if fact = 'f', then ipiv is an input argu- ment and on entry contains the pivot indices from the fac psgetrf; ipiv(i) -> the global row local row i was set work array indices ii, jj : local indices into array icurcol : process column containing diagonal block type (global input) character type indices the storage type of the input distribute = 'g': sub( a ) is a full matrix, iblock (global input) integer array, dimension (n) the submatrix indices associated with the correspondin first submatrix from the top, 2 for those belonging to of scalapack routines. eigenvalues/vectors can be selected by specifying a range of values or a range of indices for the desire if (mod(info,2).ne.0) on exit, then ifail contains the indices of the eigenvectors that failed to converge if neither of the above error conditions hold and jobz = 'v', the following variables are global indices into a maxindex: the global row and column for the first row and ipiv (local output) integer array, dimension >= desca( nb ). pivot indices for local factorizations factorization and solve. ipiv (local output) integer array, dimension >= desca( nb ). pivot indices for local factorizations factorization and solve. locr(m_a)+mb_a. if fact = 'f', then ipiv is an input argu- ment and on entry contains the pivot indices from the fac pzgetrf; ipiv(i) -> the global row local row i was of scalapack routines. eigenvalues/vectors can be selected by specifying a range of values or a range of indices for the desire if (mod(info,2).ne.0) on exit, then ifail contains the indices of the eigenvectors that failed to converge if neither of the above error conditions hold and jobz = 'v', the following variables are global indices into a maxindex: the global row and column for the first row and set work array indices ii, jj : local indices into array icurcol : process column containing diagonal block ii, jj : local indices into array icurcol : process column containing diagonal block type (global input) character type indices the storage type of the input distribute = 'g': sub( a ) is a full matrix, iblock (global input) integer array, dimension (n) the submatrix indices associated with the correspondin first submatrix from the top, 2 for those belonging to find starting and ending indices of block nblk i1 and i2 are the indices of the first row and last column of being computed, i1 and i2 are set inside the main loop. |
| individual individual 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary processes and then calls sstein2 (modified lapack routine) on each individual process. if insufficient workspace is allocated, th 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary processes and then calls dstein2 (modified lapack routine) on each individual process. if insufficient workspace is allocated, th 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary processes and then calls sstein2 (modified lapack routine) on each individual process. if insufficient workspace is allocated, th 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary 1) local phase: the individual pieces are factored independently and i fillin, which is stored in a non-inspectable way in auxiliary processes and then calls dstein2 (modified lapack routine) on each individual process. if insufficient workspace is allocated, th |
| INDROW INDROW INDROW (workspace) integer array, dimension (n INDROW (workspace) integer array, dimension (n |
| INDX INDX dimension 2. the first maximum absolute value element and its global index. v1(1) = amax, v1(2) = INDX v2 (local input) complex array of dimension 2. value of a distributed vector sub( x ). the global index is returned in INDX and the value is returned in amax where sub( x ) denotes x(ix:ix+n-1,jx) if incx = 1, INDX (workspace) integer array, dimension (n ascending order. INDX (workspace) integer array, dimension (n ascending order. INDX (workspace) integer array, dimension (n ascending order. INDX (workspace) integer array, dimension (n ascending order. value of a distributed vector sub( x ). the global index is returned in INDX and the value is returned in amax where sub( x ) denotes x(ix:ix+n-1,jx) if incx = 1, dimension 2. the first maximum absolute value element and its global index. v1(1) = amax, v1(2) = INDX v2 (local input) complex*16 array of dimension 2. |
| INDXC INDXC INDXC (output) integer array, dimension (n q matrix into three groups: the first group contains non-zero INDXC (workspace) integer array, dimension (n ctot (workspace) integer array, dimension( npcol, 4) INDXC (output) integer array, dimension (n q matrix into three groups: the first group contains non-zero INDXC (workspace) integer array, dimension (n ctot (workspace) integer array, dimension( npcol, 4) |
| INDXG2P INDXG2P where nb = mb_a = nb_a, iroffa = mod( ia-1, nb ) iarow = INDXG2P( ia, nb, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, nb, myrow, iarow, nprow ), iroffa = mod( ia-1, nb ), icoffa = mod( ja-1, nb ), iarow = INDXG2P( ia, nb, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, nb, myrow, iarow, nprow ), where nb = mb_a = nb_a, iroffa = mod( ia-1, nb ), iarow = INDXG2P( ia, nb, myrow, rsrc_a, nprow ) icoffa = mod( ja-1, nb ), ioff = mod( ia+ilo-2, nb ), iarow = INDXG2P( ia, nb, myrow, rsrc_a, nprow ) ilrow = indxg2p( ia+ilo-1, nb, myrow, rsrc_a, nprow ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) npa0 = numroc( n+iroffa, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), np = numroc( n, nb, myrow, iarow, nprow ), iarow = INDXG2P( ia, nb, myrow, rsrc_a, nprow ) indxg2p and numroc are scalapack tool functions; nq = numroc( n+mod( ia-1, nb_y ), nb_y, mycol, iacol, npcol ) iacol = INDXG2P( ja, nb_a, mycol, csrc_a, npcol indxg2p and numroc are scalapack tool functions; iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), iroffv = mod( iv-1, mb_v ), icoffv = mod( jv-1, nb_v ), ivrow = INDXG2P( iv, mb_v, myrow, rsrc_v, nprow ) mqv0 = numroc( m+icoffv, nb_v, mycol, ivcol, npcol ), iroffv = mod( iv-1, mb_v ), icoffv = mod( jv-1, nb_v ), ivrow = INDXG2P( iv, mb_v, myrow, rsrc_v, nprow ) mqv0 = numroc( m+icoffv, nb_v, mycol, ivcol, npcol ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), icrow = INDXG2P( ic, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( m+iroffc, mb_c, myrow, icrow, nprow ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), icrow = INDXG2P( ic, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( m+iroffc, mb_c, myrow, icrow, nprow ), iroffa = mod( iaa-1, mb_a ), icoffa = mod( jaa-1, nb_a ), iarow = INDXG2P( iaa, mb_a, myrow, rsrc_a, nprow ) mqa0 = numroc( mi+icoffa, nb_a, mycol, iacol, npcol ), iroffa = mod( iaa-1, mb_a ), icoffa = mod( jaa-1, nb_a ), iarow = INDXG2P( iaa, mb_a, myrow, rsrc_a, nprow ) iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), icrow = INDXG2P( ic, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( m+iroffc, mb_c, myrow, icrow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), iacol = INDXG2P( ja, nb_a, mycol, csrc_a, npcol ) iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), icrow = INDXG2P( ic, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( m+iroffc, mb_c, myrow, icrow, nprow ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), icrow = INDXG2P( ic, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( m+iroffc, mb_c, myrow, icrow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), iacol = INDXG2P( ja, nb_a, mycol, csrc_a, npcol ) iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), iacol = INDXG2P( ja, nb_a, mycol, csrc_a, npcol ) iroffa = mod( iaa-1, mb_a ), icoffa = mod( jaa-1, nb_a ), iarow = INDXG2P( iaa, mb_a, myrow, rsrc_a, nprow ) where nb = mb_a = nb_a, iroffa = mod( ia-1, nb ) iarow = INDXG2P( ia, nb, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, nb, myrow, iarow, nprow ), iroffa = mod( ia-1, nb ), icoffa = mod( ja-1, nb ), iarow = INDXG2P( ia, nb, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, nb, myrow, iarow, nprow ), where nb = mb_a = nb_a, iroffa = mod( ia-1, nb ), iarow = INDXG2P( ia, nb, myrow, rsrc_a, nprow ) icoffa = mod( ja-1, nb ), ioff = mod( ia+ilo-2, nb ), iarow = INDXG2P( ia, nb, myrow, rsrc_a, nprow ) ilrow = indxg2p( ia+ilo-1, nb, myrow, rsrc_a, nprow ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) npa0 = numroc( n+iroffa, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), nq = numroc( n+mod( ia-1, nb_y ), nb_y, mycol, iacol, npcol ) iacol = INDXG2P( ja, nb_a, mycol, csrc_a, npcol indxg2p and numroc are scalapack tool functions; nq = numroc( n, nb_q, mycol, iqcol, npcol ) iqrow = INDXG2P( iq, nb_q, myrow, rsrc_q, nprow iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), iroffv = mod( iv-1, mb_v ), icoffv = mod( jv-1, nb_v ), ivrow = INDXG2P( iv, mb_v, myrow, rsrc_v, nprow ) mqv0 = numroc( m+icoffv, nb_v, mycol, ivcol, npcol ), iroffv = mod( iv-1, mb_v ), icoffv = mod( jv-1, nb_v ), ivrow = INDXG2P( iv, mb_v, myrow, rsrc_v, nprow ) mqv0 = numroc( m+icoffv, nb_v, mycol, ivcol, npcol ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), icrow = INDXG2P( ic, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( m+iroffc, mb_c, myrow, icrow, nprow ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), icrow = INDXG2P( ic, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( m+iroffc, mb_c, myrow, icrow, nprow ), iroffa = mod( iaa-1, mb_a ), icoffa = mod( jaa-1, nb_a ), iarow = INDXG2P( iaa, mb_a, myrow, rsrc_a, nprow ) mqa0 = numroc( mi+icoffa, nb_a, mycol, iacol, npcol ), iroffa = mod( iaa-1, mb_a ), icoffa = mod( jaa-1, nb_a ), iarow = INDXG2P( iaa, mb_a, myrow, rsrc_a, nprow ) iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), icrow = INDXG2P( ic, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( m+iroffc, mb_c, myrow, icrow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), iacol = INDXG2P( ja, nb_a, mycol, csrc_a, npcol ) iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), icrow = INDXG2P( ic, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( m+iroffc, mb_c, myrow, icrow, nprow ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), icrow = INDXG2P( ic, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( m+iroffc, mb_c, myrow, icrow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), iacol = INDXG2P( ja, nb_a, mycol, csrc_a, npcol ) iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), iacol = INDXG2P( ja, nb_a, mycol, csrc_a, npcol ) iroffa = mod( iaa-1, mb_a ), icoffa = mod( jaa-1, nb_a ), iarow = INDXG2P( iaa, mb_a, myrow, rsrc_a, nprow ) np = numroc( n, nb, myrow, iarow, nprow ), iarow = INDXG2P( ia, nb, myrow, rsrc_a, nprow ) indxg2p and numroc are scalapack tool functions; iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), where nb = mb_a = nb_a, iroffa = mod( ia-1, nb ) iarow = INDXG2P( ia, nb, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, nb, myrow, iarow, nprow ), iroffa = mod( ia-1, nb ), icoffa = mod( ja-1, nb ), iarow = INDXG2P( ia, nb, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, nb, myrow, iarow, nprow ), where nb = mb_a = nb_a, iroffa = mod( ia-1, nb ), iarow = INDXG2P( ia, nb, myrow, rsrc_a, nprow ) icoffa = mod( ja-1, nb ), ioff = mod( ia+ilo-2, nb ), iarow = INDXG2P( ia, nb, myrow, rsrc_a, nprow ) ilrow = indxg2p( ia+ilo-1, nb, myrow, rsrc_a, nprow ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) npa0 = numroc( n+iroffa, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), nq = numroc( n+mod( ia-1, nb_y ), nb_y, mycol, iacol, npcol ) iacol = INDXG2P( ja, nb_a, mycol, csrc_a, npcol indxg2p and numroc are scalapack tool functions; nq = numroc( n, nb_q, mycol, iqcol, npcol ) iqrow = INDXG2P( iq, nb_q, myrow, rsrc_q, nprow iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), iroffv = mod( iv-1, mb_v ), icoffv = mod( jv-1, nb_v ), ivrow = INDXG2P( iv, mb_v, myrow, rsrc_v, nprow ) mqv0 = numroc( m+icoffv, nb_v, mycol, ivcol, npcol ), iroffv = mod( iv-1, mb_v ), icoffv = mod( jv-1, nb_v ), ivrow = INDXG2P( iv, mb_v, myrow, rsrc_v, nprow ) mqv0 = numroc( m+icoffv, nb_v, mycol, ivcol, npcol ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), icrow = INDXG2P( ic, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( m+iroffc, mb_c, myrow, icrow, nprow ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), icrow = INDXG2P( ic, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( m+iroffc, mb_c, myrow, icrow, nprow ), iroffa = mod( iaa-1, mb_a ), icoffa = mod( jaa-1, nb_a ), iarow = INDXG2P( iaa, mb_a, myrow, rsrc_a, nprow ) mqa0 = numroc( mi+icoffa, nb_a, mycol, iacol, npcol ), iroffa = mod( iaa-1, mb_a ), icoffa = mod( jaa-1, nb_a ), iarow = INDXG2P( iaa, mb_a, myrow, rsrc_a, nprow ) iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), icrow = INDXG2P( ic, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( m+iroffc, mb_c, myrow, icrow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), iacol = INDXG2P( ja, nb_a, mycol, csrc_a, npcol ) iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), icrow = INDXG2P( ic, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( m+iroffc, mb_c, myrow, icrow, nprow ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), icrow = INDXG2P( ic, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( m+iroffc, mb_c, myrow, icrow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), iacol = INDXG2P( ja, nb_a, mycol, csrc_a, npcol ) iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), iacol = INDXG2P( ja, nb_a, mycol, csrc_a, npcol ) iroffa = mod( iaa-1, mb_a ), icoffa = mod( jaa-1, nb_a ), iarow = INDXG2P( iaa, mb_a, myrow, rsrc_a, nprow ) np = numroc( n, nb, myrow, iarow, nprow ), iarow = INDXG2P( ia, nb, myrow, rsrc_a, nprow ) indxg2p and numroc are scalapack tool functions; iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), where nb = mb_a = nb_a, iroffa = mod( ia-1, nb ) iarow = INDXG2P( ia, nb, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, nb, myrow, iarow, nprow ), iroffa = mod( ia-1, nb ), icoffa = mod( ja-1, nb ), iarow = INDXG2P( ia, nb, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, nb, myrow, iarow, nprow ), where nb = mb_a = nb_a, iroffa = mod( ia-1, nb ), iarow = INDXG2P( ia, nb, myrow, rsrc_a, nprow ) icoffa = mod( ja-1, nb ), ioff = mod( ia+ilo-2, nb ), iarow = INDXG2P( ia, nb, myrow, rsrc_a, nprow ) ilrow = indxg2p( ia+ilo-1, nb, myrow, rsrc_a, nprow ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) npa0 = numroc( n+iroffa, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), np = numroc( n, nb, myrow, iarow, nprow ), iarow = INDXG2P( ia, nb, myrow, rsrc_a, nprow ) indxg2p and numroc are scalapack tool functions; nq = numroc( n+mod( ia-1, nb_y ), nb_y, mycol, iacol, npcol ) iacol = INDXG2P( ja, nb_a, mycol, csrc_a, npcol indxg2p and numroc are scalapack tool functions; iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), iroffv = mod( iv-1, mb_v ), icoffv = mod( jv-1, nb_v ), ivrow = INDXG2P( iv, mb_v, myrow, rsrc_v, nprow ) mqv0 = numroc( m+icoffv, nb_v, mycol, ivcol, npcol ), iroffv = mod( iv-1, mb_v ), icoffv = mod( jv-1, nb_v ), ivrow = INDXG2P( iv, mb_v, myrow, rsrc_v, nprow ) mqv0 = numroc( m+icoffv, nb_v, mycol, ivcol, npcol ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mp0 = numroc( m+iroff, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) mpa0 = numroc( m+iroffa, mb_a, myrow, iarow, nprow ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), icrow = INDXG2P( ic, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( m+iroffc, mb_c, myrow, icrow, nprow ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), icrow = INDXG2P( ic, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( m+iroffc, mb_c, myrow, icrow, nprow ), iroffa = mod( iaa-1, mb_a ), icoffa = mod( jaa-1, nb_a ), iarow = INDXG2P( iaa, mb_a, myrow, rsrc_a, nprow ) mqa0 = numroc( mi+icoffa, nb_a, mycol, iacol, npcol ), iroffa = mod( iaa-1, mb_a ), icoffa = mod( jaa-1, nb_a ), iarow = INDXG2P( iaa, mb_a, myrow, rsrc_a, nprow ) iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), icrow = INDXG2P( ic, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( m+iroffc, mb_c, myrow, icrow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), iacol = INDXG2P( ja, nb_a, mycol, csrc_a, npcol ) iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), iarow = INDXG2P( ia, mb_a, myrow, rsrc_a, nprow ) iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), icrow = INDXG2P( ic, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( m+iroffc, mb_c, myrow, icrow, nprow ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ), icrow = INDXG2P( ic, mb_c, myrow, rsrc_c, nprow ) mpc0 = numroc( m+iroffc, mb_c, myrow, icrow, nprow ), iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), iacol = INDXG2P( ja, nb_a, mycol, csrc_a, npcol ) iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), iacol = INDXG2P( ja, nb_a, mycol, csrc_a, npcol ) iroffa = mod( iaa-1, mb_a ), icoffa = mod( jaa-1, nb_a ), iarow = INDXG2P( iaa, mb_a, myrow, rsrc_a, nprow ) |
| INDXP INDXP INDXP (workspace) integer array, dimension (n of the array. indxp(1:k) points to the nondeflated d-values INDXP (workspace) integer array, dimension (n of the array. indxp(1:k) points to the nondeflated d-values |
| INDXR INDXR INDXR (workspace) integer array, dimension (n INDXR (workspace) integer array, dimension (n |
| infinity infinity check the infinity norm of the iterate distributed complex matrix a(ia:ia+n-1,ja:ja+n-1), in either the 1-norm or the infinity-norm, using the lu factorization computed b pclange returns the value of the one norm, or the frobenius norm, or the infinity norm, or the element of largest absolute value of refered to as rowsums, and the column sums shown by | are refered to as colsums. infinity-norm = 1-norm = rowsums+colsums uplo = 'u' uplo = 'l' find maximum sum of rows for infinity-nor refered to as rowsums, and the column sums shown by | are refered to as colsums. infinity-norm = 1-norm = rowsums+colsums uplo = 'u' uplo = 'l' find maximum sum of rows for infinity-nor anorm (global input) real the 1-norm (or infinity-norm) of the hermitian distribute triangular distributed matrix a(ia:ia+n-1,ja:ja+n-1), in either the 1-norm or the infinity-norm the norm of a(ia:ia+n-1,ja:ja+n-1) is computed and an estimate is distributed real matrix a(ia:ia+n-1,ja:ja+n-1), in either the 1-norm or the infinity-norm, using the lu factorization computed by pdgetrf an estimate is obtained for norm(inv(a(ia:ia+n-1,ja:ja+n-1))), and pdlange returns the value of the one norm, or the frobenius norm, or the infinity norm, or the element of largest absolute value of find maximum sum of rows for infinity-nor refered to as rowsums, and the column sums shown by | are refered to as colsums. infinity-norm = 1-norm = rowsums+colsums uplo = 'u' uplo = 'l' find maximum sum of rows for infinity-nor anorm (global input) double precision the 1-norm (or infinity-norm) of the symmetric distribute to 1 (in slmake.inc). the features of ieee arithmetic that are needed for the "fast" sturm count are : (a) infinity point number is assumed be in the 32nd bit position triangular distributed matrix a(ia:ia+n-1,ja:ja+n-1), in either the 1-norm or the infinity-norm the norm of a(ia:ia+n-1,ja:ja+n-1) is computed and an estimate is distributed real matrix a(ia:ia+n-1,ja:ja+n-1), in either the 1-norm or the infinity-norm, using the lu factorization computed by psgetrf an estimate is obtained for norm(inv(a(ia:ia+n-1,ja:ja+n-1))), and pslange returns the value of the one norm, or the frobenius norm, or the infinity norm, or the element of largest absolute value of find maximum sum of rows for infinity-nor refered to as rowsums, and the column sums shown by | are refered to as colsums. infinity-norm = 1-norm = rowsums+colsums uplo = 'u' uplo = 'l' find maximum sum of rows for infinity-nor anorm (global input) real the 1-norm (or infinity-norm) of the symmetric distribute to 1 (in slmake.inc). the features of ieee arithmetic that are needed for the "fast" sturm count are : (a) infinity point number is assumed be in the 32nd or 64th bit position triangular distributed matrix a(ia:ia+n-1,ja:ja+n-1), in either the 1-norm or the infinity-norm the norm of a(ia:ia+n-1,ja:ja+n-1) is computed and an estimate is distributed complex matrix a(ia:ia+n-1,ja:ja+n-1), in either the 1-norm or the infinity-norm, using the lu factorization computed b pzlange returns the value of the one norm, or the frobenius norm, or the infinity norm, or the element of largest absolute value of refered to as rowsums, and the column sums shown by | are refered to as colsums. infinity-norm = 1-norm = rowsums+colsums uplo = 'u' uplo = 'l' find maximum sum of rows for infinity-nor refered to as rowsums, and the column sums shown by | are refered to as colsums. infinity-norm = 1-norm = rowsums+colsums uplo = 'u' uplo = 'l' find maximum sum of rows for infinity-nor anorm (global input) double precision the 1-norm (or infinity-norm) of the hermitian distribute triangular distributed matrix a(ia:ia+n-1,ja:ja+n-1), in either the 1-norm or the infinity-norm the norm of a(ia:ia+n-1,ja:ja+n-1) is computed and an estimate is check the infinity norm of the iterate |
| info info info (output) intege < 0: if info = -i, the i-th argument had an illegal value info (output) intege < 0: if info = -i, the i-th argument had an illegal value info (output) intege < 0: if info = -i, the i-th argument had an illegal value info (output) intege < 0: if info = -i, the i-th argument had an illegal value skip the current step: the subdiagonal info is just noise info (output) intege < 0: if info = -i, the i-th argument had an illegal value info (output) intege < 0: if info = -i, the i-th argument had an illegal value info (output) intege < 0: if info = -i, the i-th argument had an illegal value info (local input) intege eigenvalues and things couldn't be paired or if the input info (output) intege < 0: if info = -i, the i-th argument had an illegal value if stopping criterion was not satisfied, update info an distributed matrices. on exit, this array contains information containing detail note that permutations are performed on the matrix, so that prepare output: set info = 0 if no error, and divide by descmul the array descriptor for the distributed matrix a. contains information of mapping of a to memory. pleas prepare output: set info = 0 if no error, and divide by descmul must be of size >= desca( nb_ ). on exit, this array contains information containing th prepare output: set info = 0 if no error, and divide by descmul must be of size >= desca( nb_ ). on exit, this array contains information containing th prepare output: set info = 0 if no error, and divide by descmul distributed matrices. on exit, this array contains information containing detail note that permutations are performed on the matrix, so that prepare output: set info = 0 if no error, and divide by descmul the array descriptor for the distributed matrix a. contains information of mapping of a to memory. pleas each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. a description vector is associated with each 2d block-cyclicly dis- tributed matrix. this vector stores the information required t process and memory location. w (global output) real array, dimension (n) if info=0, the eigenvalues in ascending order z (local output) complex array, each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis process and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. distributed matrices. on exit, this array contains information containing detail note that permutations are performed on the matrix, so that prepare output: set info = 0 if no error, and divide by descmul the array descriptor for the distributed matrix a. contains information of mapping of a to memory. pleas prepare output: set info = 0 if no error, and divide by descmul each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. the scaling factor are stored along process rows in sr and along process columns in sc. the duplication of information simplifie each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. matrix. on exit, this array contains information containing th must be of size >= desca( nb_ ). prepare output: set info = 0 if no error, and divide by descmul matrix. on exit, this array contains information containing th must be of size >= desca( nb_ ). prepare output: set info = 0 if no error, and divide by descmul each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. distributed matrices. on exit, this array contains information containing detail note that permutations are performed on the matrix, so that prepare output: set info = 0 if no error, and divide by descmul the array descriptor for the distributed matrix a. contains information of mapping of a to memory. pleas prepare output: set info = 0 if no error, and divide by descmul must be of size >= desca( nb_ ). on exit, this array contains information containing th prepare output: set info = 0 if no error, and divide by descmul must be of size >= desca( nb_ ). on exit, this array contains information containing th prepare output: set info = 0 if no error, and divide by descmul distributed matrices. on exit, this array contains information containing detail note that permutations are performed on the matrix, so that prepare output: set info = 0 if no error, and divide by descmul the array descriptor for the distributed matrix a. contains information of mapping of a to memory. pleas each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. more than mmax intervals are generated, then pdlaebz will quit with info = mmax+1 minp (input) integer on entry, the diagonal elements of the tridiagonal matrix. on exit, if info = 0, the eigenvalues in descending order e (global input/output) double precision array, dimension (n-1) info (global output) intege < 0: if the i-th argument is an array and the j-entry had info (output) intege < 0: if info = -i, the i-th argument had an illegal value. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. info (global output) intege < 0: if the i-th argument is an array and the j-entry had each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. distributed matrices. on exit, this array contains information containing detail note that permutations are performed on the matrix, so that prepare output: set info = 0 if no error, and divide by descmul the array descriptor for the distributed matrix a. contains information of mapping of a to memory. pleas prepare output: set info = 0 if no error, and divide by descmul each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. the scaling factor are stored along process rows in sr and along process columns in sc. the duplication of information simplifie each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. matrix. on exit, this array contains information containing th must be of size >= desca( nb_ ). prepare output: set info = 0 if no error, and divide by descmul matrix. on exit, this array contains information containing th must be of size >= desca( nb_ ). prepare output: set info = 0 if no error, and divide by descmul the actual number of eigenvalues found. 0 <= m <= n. (see also the description of info=2 nsplit (global output) integer on entry, the diagonal elements of the tridiagonal matrix. on exit, if info = 0, the eigenvalues in descending order e (global input/output) double precision array, dimension (n-1) each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. a description vector is associated with each 2d block-cyclicly dis- tributed matrix. this vector stores the information required t process and memory location. w (global output) double precision array, dimension (n) if info=0, the eigenvalues in ascending order z (local output) double precision array, each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis process and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. distributed matrices. on exit, this array contains information containing detail note that permutations are performed on the matrix, so that prepare output: set info = 0 if no error, and divide by descmul the array descriptor for the distributed matrix a. contains information of mapping of a to memory. pleas prepare output: set info = 0 if no error, and divide by descmul must be of size >= desca( nb_ ). on exit, this array contains information containing th prepare output: set info = 0 if no error, and divide by descmul must be of size >= desca( nb_ ). on exit, this array contains information containing th prepare output: set info = 0 if no error, and divide by descmul distributed matrices. on exit, this array contains information containing detail note that permutations are performed on the matrix, so that prepare output: set info = 0 if no error, and divide by descmul the array descriptor for the distributed matrix a. contains information of mapping of a to memory. pleas each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. more than mmax intervals are generated, then pslaebz will quit with info = mmax+1 minp (input) integer on entry, the diagonal elements of the tridiagonal matrix. on exit, if info = 0, the eigenvalues in descending order e (global input/output) real array, dimension (n-1) info (global output) intege < 0: if the i-th argument is an array and the j-entry had info (output) intege < 0: if info = -i, the i-th argument had an illegal value. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. info (global output) intege < 0: if the i-th argument is an array and the j-entry had each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. distributed matrices. on exit, this array contains information containing detail note that permutations are performed on the matrix, so that prepare output: set info = 0 if no error, and divide by descmul the array descriptor for the distributed matrix a. contains information of mapping of a to memory. pleas prepare output: set info = 0 if no error, and divide by descmul each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. the scaling factor are stored along process rows in sr and along process columns in sc. the duplication of information simplifie each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. matrix. on exit, this array contains information containing th must be of size >= desca( nb_ ). prepare output: set info = 0 if no error, and divide by descmul matrix. on exit, this array contains information containing th must be of size >= desca( nb_ ). prepare output: set info = 0 if no error, and divide by descmul the actual number of eigenvalues found. 0 <= m <= n. (see also the description of info=2 nsplit (global output) integer on entry, the diagonal elements of the tridiagonal matrix. on exit, if info = 0, the eigenvalues in descending order e (global input/output) real array, dimension (n-1) each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. a description vector is associated with each 2d block-cyclicly dis- tributed matrix. this vector stores the information required t process and memory location. w (global output) real array, dimension (n) if info=0, the eigenvalues in ascending order z (local output) real array, each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis process and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. distributed matrices. on exit, this array contains information containing detail note that permutations are performed on the matrix, so that prepare output: set info = 0 if no error, and divide by descmul the array descriptor for the distributed matrix a. contains information of mapping of a to memory. pleas prepare output: set info = 0 if no error, and divide by descmul must be of size >= desca( nb_ ). on exit, this array contains information containing th prepare output: set info = 0 if no error, and divide by descmul must be of size >= desca( nb_ ). on exit, this array contains information containing th prepare output: set info = 0 if no error, and divide by descmul distributed matrices. on exit, this array contains information containing detail note that permutations are performed on the matrix, so that prepare output: set info = 0 if no error, and divide by descmul the array descriptor for the distributed matrix a. contains information of mapping of a to memory. pleas each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. a description vector is associated with each 2d block-cyclicly dis- tributed matrix. this vector stores the information required t process and memory location. w (global output) double precision array, dimension (n) if info=0, the eigenvalues in ascending order z (local output) complex*16 array, each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis process and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. distributed matrices. on exit, this array contains information containing detail note that permutations are performed on the matrix, so that prepare output: set info = 0 if no error, and divide by descmul the array descriptor for the distributed matrix a. contains information of mapping of a to memory. pleas prepare output: set info = 0 if no error, and divide by descmul each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. the scaling factor are stored along process rows in sr and along process columns in sc. the duplication of information simplifie each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. matrix. on exit, this array contains information containing th must be of size >= desca( nb_ ). prepare output: set info = 0 if no error, and divide by descmul matrix. on exit, this array contains information containing th must be of size >= desca( nb_ ). prepare output: set info = 0 if no error, and divide by descmul each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. info (output) intege < 0: if info = -i, the i-th argument had an illegal value info (output) intege < 0: if info = -i, the i-th argument had an illegal value info (output) intege < 0: if info = -i, the i-th argument had an illegal value info (local input) intege eigenvalues and things couldn't be paired or if the input info (output) intege < 0: if info = -i, the i-th argument had an illegal value if stopping criterion was not satisfied, update info an info (output) intege < 0: if info = -i, the i-th argument had an illegal value info (output) intege < 0: if info = -i, the i-th argument had an illegal value info (output) intege < 0: if info = -i, the i-th argument had an illegal value info (output) intege < 0: if info = -i, the i-th argument had an illegal value skip the current step: the subdiagonal info is just noise |
| information information t3 (global input/output) complex this holds information on a single size 3 householde overwritten when block is .true. t3 (global input/output) double precision this holds information on a single size 3 householde overwritten when block is .true. distributed matrices. on exit, this array contains information containing detail note that permutations are performed on the matrix, so that get information about new grid the array descriptor for the distributed matrix a. contains information of mapping of a to memory. pleas get information about new grid must be of size >= desca( nb_ ). on exit, this array contains information containing th get information about new grid must be of size >= desca( nb_ ). on exit, this array contains information containing th get information about new grid distributed matrices. on exit, this array contains information containing detail note that permutations are performed on the matrix, so that get information about new grid the array descriptor for the distributed matrix a. contains information of mapping of a to memory. pleas each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. a description vector is associated with each 2d block-cyclicly dis- tributed matrix. this vector stores the information required t process and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis process and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. products. x and v are aligned with the distributed matrix a, this information is implicitly contained within iv, ix, descv, and descx notes each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. interchange is initiated for each of rows or columns k1 trough k2 of sub( a ). this routine assumes that the pivoting information ha also note that this routine will only work for k1-k2 being in the each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. distributed matrices. on exit, this array contains information containing detail note that permutations are performed on the matrix, so that get information about new grid the array descriptor for the distributed matrix a. contains information of mapping of a to memory. pleas get information about new grid each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. the scaling factor are stored along process rows in sr and along process columns in sc. the duplication of information simplifie each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. matrix. on exit, this array contains information containing th must be of size >= desca( nb_ ). get information about new grid matrix. on exit, this array contains information containing th must be of size >= desca( nb_ ). get information about new grid each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. distributed matrices. on exit, this array contains information containing detail note that permutations are performed on the matrix, so that get information about new grid the array descriptor for the distributed matrix a. contains information of mapping of a to memory. pleas get information about new grid must be of size >= desca( nb_ ). on exit, this array contains information containing th get information about new grid must be of size >= desca( nb_ ). on exit, this array contains information containing th get information about new grid distributed matrices. on exit, this array contains information containing detail note that permutations are performed on the matrix, so that get information about new grid the array descriptor for the distributed matrix a. contains information of mapping of a to memory. pleas each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. reverse communication is used for evaluating matrix-vector products. x and v are aligned with the distributed matrix a, this information each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. interchange is initiated for each of rows or columns k1 trough k2 of sub( a ). this routine assumes that the pivoting information ha also note that this routine will only work for k1-k2 being in the each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. distributed matrices. on exit, this array contains information containing detail note that permutations are performed on the matrix, so that get information about new grid the array descriptor for the distributed matrix a. contains information of mapping of a to memory. pleas get information about new grid each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. the scaling factor are stored along process rows in sr and along process columns in sc. the duplication of information simplifie each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. matrix. on exit, this array contains information containing th must be of size >= desca( nb_ ). get information about new grid matrix. on exit, this array contains information containing th must be of size >= desca( nb_ ). get information about new grid each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. a description vector is associated with each 2d block-cyclicly dis- tributed matrix. this vector stores the information required t process and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis process and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. the tuning parameters for their particular machine using the option and problem size information in the arguments this routine will not function correctly if it is converted to all each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. distributed matrices. on exit, this array contains information containing detail note that permutations are performed on the matrix, so that get information about new grid the array descriptor for the distributed matrix a. contains information of mapping of a to memory. pleas get information about new grid must be of size >= desca( nb_ ). on exit, this array contains information containing th get information about new grid must be of size >= desca( nb_ ). on exit, this array contains information containing th get information about new grid distributed matrices. on exit, this array contains information containing detail note that permutations are performed on the matrix, so that get information about new grid the array descriptor for the distributed matrix a. contains information of mapping of a to memory. pleas each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. reverse communication is used for evaluating matrix-vector products. x and v are aligned with the distributed matrix a, this information each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. interchange is initiated for each of rows or columns k1 trough k2 of sub( a ). this routine assumes that the pivoting information ha also note that this routine will only work for k1-k2 being in the each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. distributed matrices. on exit, this array contains information containing detail note that permutations are performed on the matrix, so that get information about new grid the array descriptor for the distributed matrix a. contains information of mapping of a to memory. pleas get information about new grid each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. the scaling factor are stored along process rows in sr and along process columns in sc. the duplication of information simplifie each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. matrix. on exit, this array contains information containing th must be of size >= desca( nb_ ). get information about new grid matrix. on exit, this array contains information containing th must be of size >= desca( nb_ ). get information about new grid each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. a description vector is associated with each 2d block-cyclicly dis- tributed matrix. this vector stores the information required t process and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis process and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. distributed matrices. on exit, this array contains information containing detail note that permutations are performed on the matrix, so that get information about new grid the array descriptor for the distributed matrix a. contains information of mapping of a to memory. pleas get information about new grid each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. must be of size >= desca( nb_ ). on exit, this array contains information containing th get information about new grid must be of size >= desca( nb_ ). on exit, this array contains information containing th get information about new grid distributed matrices. on exit, this array contains information containing detail note that permutations are performed on the matrix, so that get information about new grid the array descriptor for the distributed matrix a. contains information of mapping of a to memory. pleas each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. a description vector is associated with each 2d block-cyclicly dis- tributed matrix. this vector stores the information required t process and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis process and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. products. x and v are aligned with the distributed matrix a, this information is implicitly contained within iv, ix, descv, and descx notes each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. interchange is initiated for each of rows or columns k1 trough k2 of sub( a ). this routine assumes that the pivoting information ha also note that this routine will only work for k1-k2 being in the each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. distributed matrices. on exit, this array contains information containing detail note that permutations are performed on the matrix, so that get information about new grid the array descriptor for the distributed matrix a. contains information of mapping of a to memory. pleas get information about new grid each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. the scaling factor are stored along process rows in sr and along process columns in sc. the duplication of information simplifie each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. matrix. on exit, this array contains information containing th must be of size >= desca( nb_ ). get information about new grid matrix. on exit, this array contains information containing th must be of size >= desca( nb_ ). get information about new grid each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. each global data object is described by an associated description vector. this vector stores the information required to establis and memory location. t3 (global input/output) real this holds information on a single size 3 householde overwritten when block is .true. t3 (global input/output) complex*16 this holds information on a single size 3 householde overwritten when block is .true. |
| ing ing vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces |
| InH InH work ( inv ) dimension ( np, anb+1): array v work ( InH ) dimension ( np, anb+1): array work ( inht ) dimension ( nq, anb+1): transpose of the array h work ( inv ) dimension ( np, anb+1): array v work ( InH ) dimension ( np, anb+1): array work ( inht ) dimension ( nq, anb+1): transpose of the array h work ( inv ) dimension ( np, anb+1): array v work ( InH ) dimension ( np, anb+1): array work ( inht ) dimension ( nq, anb+1): transpose of the array h work ( inv ) dimension ( np, anb+1): array v work ( InH ) dimension ( np, anb+1): array work ( inht ) dimension ( nq, anb+1): transpose of the array h |
| InHT InHT work ( invt ) dimension ( nq, anb+1): transpose of the array v work ( InHT ) dimension ( nq, anb+1): transpose of the array work ( invt ) dimension ( nq, anb+1): transpose of the array v work ( InHT ) dimension ( nq, anb+1): transpose of the array work ( invt ) dimension ( nq, anb+1): transpose of the array v work ( InHT ) dimension ( nq, anb+1): transpose of the array work ( invt ) dimension ( nq, anb+1): transpose of the array v work ( InHT ) dimension ( nq, anb+1): transpose of the array |
| initial initial define the initial dimensions of the diagonal block kase (local input/local output) integer on the initial call to pclacon, kase should be 0 whether x should be overwritten by a * x or a' * x. define the initial dimensions of the diagonal block kase (local input/local output) integer on the initial call to pdlacon, kase should be 0 whether x should be overwritten by a * x or a' * x. endpoints of the interval. = 1 : find a floating point number contained in the initial = 2 : perform bisection iteration to find eigenvalues of t. define the initial dimensions of the diagonal block kase (local input/local output) integer on the initial call to pslacon, kase should be 0 whether x should be overwritten by a * x or a' * x. endpoints of the interval. = 1 : find a floating point number contained in the initial = 2 : perform bisection iteration to find eigenvalues of t. define the initial dimensions of the diagonal block kase (local input/local output) integer on the initial call to pzlacon, kase should be 0 whether x should be overwritten by a * x or a' * x. |
| Initialize Initialize Initialize seed for random number generator dlarnv Initialize seed for random number generator slarnv |
| initializes initializes pclase2 initializes an m-by-n distributed matrix sub( a ) denotin offdiagonals. pclase2 requires that only dimension of the matrix pclaset initializes an m-by-n distributed matrix sub( a ) denotin offdiagonals. pdlase2 initializes an m-by-n distributed matrix sub( a ) denotin offdiagonals. pdlase2 requires that only dimension of the matrix pdlaset initializes an m-by-n distributed matrix sub( a ) denotin offdiagonals. pslase2 initializes an m-by-n distributed matrix sub( a ) denotin offdiagonals. pslase2 requires that only dimension of the matrix pslaset initializes an m-by-n distributed matrix sub( a ) denotin offdiagonals. pzlase2 initializes an m-by-n distributed matrix sub( a ) denotin offdiagonals. pzlase2 requires that only dimension of the matrix pzlaset initializes an m-by-n distributed matrix sub( a ) denotin offdiagonals. |
| Initially Initially compute grow = 1/g(j) and xbnd = 1/m(j).
Initially, g(0) = max{x(i), i=1,...,n}
eigenvalues output and the number desired. = 3 : range='i', and the gershgorin interval Initially probable cause: your machine has sloppy floating eigenvalues output and the number desired. = 3 : range='i', and the gershgorin interval Initially probable cause: your machine has sloppy floating compute grow = 1/g(j) and xbnd = 1/m(j).
Initially, g(0) = max{x(i), i=1,...,n}
|
| Initiate Initiate Initiate send of e_i to previous processor to overla Initiate send of e_i to previous processor to overla Initiate send of e_i to previous processor to overla Initiate send of e_i to previous processor to overla Initiate send of e_i to previous processor to overla Initiate send of e_i to previous processor to overla Initiate send of e_i to previous processor to overla Initiate send of e_i to previous processor to overla Initiate send of e_i to previous processor to overla Initiate send of e_i to previous processor to overla Initiate send of e_i to previous processor to overla Initiate send of e_i to previous processor to overla Initiate send of e_i to previous processor to overla Initiate send of e_i to previous processor to overla Initiate send of e_i to previous processor to overla Initiate send of e_i to previous processor to overla |
| initiated initiated the distributed matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1). one interchange is initiated for each of rows or columns k1 trough k2 o already been broadcast along the process row or column. the distributed matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1). one interchange is initiated for each of rows or columns k1 trough k2 o already been broadcast along the process row or column. the distributed matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1). one interchange is initiated for each of rows or columns k1 trough k2 o already been broadcast along the process row or column. the distributed matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1). one interchange is initiated for each of rows or columns k1 trough k2 o already been broadcast along the process row or column. |
| INLQ INLQ lwork is local input and must be at least lwork >= nb*nb + nb*max( ihip+1, ihlp+INLQ where nb = mb_a = nb_a, iroffa = mod( ia-1, nb ), lwork is local input and must be at least lwork >= nb*nb + nb*max( ihip+1, ihlp+INLQ where nb = mb_a = nb_a, iroffa = mod( ia-1, nb ), lwork is local input and must be at least lwork >= nb*nb + nb*max( ihip+1, ihlp+INLQ where nb = mb_a = nb_a, iroffa = mod( ia-1, nb ), lwork is local input and must be at least lwork >= nb*nb + nb*max( ihip+1, ihlp+INLQ where nb = mb_a = nb_a, iroffa = mod( ia-1, nb ), |
| inner inner inner loo inner loo at the bottom of the inner loop where h = h( maxindex:n, 1:bindex ) and at the bottom of the inner loop where h = h( maxindex:n, 1:bindex ) and at the bottom of the inner loop where h = h( maxindex:n, 1:bindex ) and at the bottom of the inner loop where h = h( maxindex:n, 1:bindex ) and inner loo inner loo |
| innermost innermost this implementation of the sturm sequence loop has conditionals in the innermost loop to avoid overflow and determine the sign of implementation of the sturm sequence loop. this implementation of the sturm sequence loop has conditionals in the innermost loop to avoid overflow and determine the sign of implementation of the sturm sequence loop. |
| input input v1 (local input/local output) complex array o its global index. v1(1) = amax, v1(2) = indx. m (input) intege test the input parameters n (input) intege uplo (input) character* s (local input/output) complex array, ( lds,* is referenced. it is assumed that s has jblk double shifts a (input/output) comple c (input/output) complex type (global input) character* (apply from left) uplo (input) character* of the tridiagonal matrix a is stored and the form of the m (input) intege test the input parameters n (input) intege uplo (input) character* s (local input/output) double precision array, (lds,* referenced. it is assumed that s has jblk double shifts test the input paramters type (global input) character* (apply from left) s (local input/output) double precision array, dimension ld on exit, the diagonal blocks of s have been rewritten to pair test the input paramters trans (input) characte = 'n': l * x = b (no transpose) test the input parameters test the input parameters n (global input) intege order of the distributed submatrix a(1:n, ja:ja+n-1). n >= 0. test the input parameter trans (global input) characte = 'c': solve with conjugate_transpose( a(1:n, ja:ja+n-1) ); test the input parameter n (global input) intege order of the distributed submatrix a(1:n, ja:ja+n-1). n >= 0. test the input parameter trans (global input) characte = 'c': solve with conjugate_transpose( a(1:n, ja:ja+n-1) ); test the input parameter n (global input) intege order of the distributed submatrix a(1:n, ja:ja+n-1). n >= 0. test the input parameter trans (global input) characte = 'c': solve with conjugate_transpose( a(1:n, ja:ja+n-1) ); m (global input) intege of the distributed submatrix sub( a ). m >= 0. m (global input) intege of the distributed submatrix sub( a ). m >= 0. norm (global input) characte infinity-norm condition number is required: m (global input) intege of the distributed submatrix sub( a ). m >= 0. n (global input) intege order of the distributed submatrix sub( a ). n >= 0. n (global input) intege order of the distributed submatrix sub( a ). n >= 0. m (global input) intege of the distributed submatrix sub( a ). m >= 0. m (global input) intege of the distributed submatrix sub( a ). m >= 0. trans (global input) characte = 'c': the linear system involves sub( a )**h. m (global input) intege of the distributed submatrix sub( a ). m >= 0. m (global input) intege of the distributed submatrix sub( a ). m >= 0. m (global input) intege of the distributed submatrix sub( a ). m >= 0. m (global input) intege of the distributed submatrix sub( a ). m >= 0. m (global input) intege of the distributed submatrix sub( a ). m >= 0. trans (global input) character* = 'n': sub( a ) * sub( x ) = sub( b ) (no transpose) m (global input) intege of the distributed submatrix sub( a ). m >= 0. m (global input) intege of the distributed submatrix sub( a ). m >= 0. n (global input) intege order of the distributed submatrix sub( a ). n >= 0. jobu (global input) character* = 'v': the first size columns of u (the left singular fact (global input) characte a(ia:ia+n-1,ja:ja+n-1) is supplied on entry, and if not, m (global input) intege of the distributed submatrix sub( a ). m >= 0. m (global input) intege of the distributed submatrix sub( a ). m >= 0. n (global input) intege order of the distributed submatrix sub( a ). n >= 0. trans (global input) characte = 'n': sub( a ) * x = sub( b ) (no transpose) n (global input) intege of the distributed submatrices sub( a ) and sub( b ). n >= 0. m (global input) intege rows of the distributed submatrix sub( a ). m >= 0. jobz (global input) character* = 'n': compute eigenvalues only. jobz (input) character* = 'v': compute eigenvalues and eigenvectors. jobz (global input) character* = 'n': compute eigenvalues only. ibtype (global input) intege inv(l)*sub( a )*inv(l**h); ibtype (global input) intege inv(l)*sub( a )*inv(l**h); ibtype (global input) intege = 1: sub( a )*x = (lambda)*sub( b )*x ibtype (global input) intege inv(l)*sub( a )*inv(l**h); the tailored codes provide performance that is essentially independent of the input data layout the tailored codes place no restrictions on ia, ja, mb or nb. uplo (global input) characte hermitian matrix sub( a ) is stored: uplo (global input) characte hermitian matrix sub( a ) is stored: uplo (global input) characte hermitian matrix sub( a ) is stored: m (global input) intege of the distributed submatrix sub( a ). m >= 0. n (global input) intege n (global input) intege a (global input) complex array, dimensio on entry, the hessenberg matrix whose tridiagonal part is uplo (global input) characte copied: m (global input) intege m >= 0. uplo (global input) characte copied: n (global input) intege n (global input) intege order of the distributed submatrix sub( a ). n (global input) intege norm (global input) characte above. direc (global input) character* = 'f' (forward) applies pivots forward from top of matrix. direc (global input) characte = 'f' (forward) applies pivots forward from top of matrix. m (global input) intege of the distributed submatrix sub( a ). m >= 0. uplo (global input) characte symmetric distributed matrix sub( a ) is to be referenced: side (global input) characte = 'r': apply q or q**h from the right. n (global input) intege direct (global input) character* multiplied to form the block reflector: side (global input) characte = 'r': apply q or q**h from the right. direct (global input) characte multiplied to form the block reflector: type (global input) characte matrix. uplo (global input) characte set: uplo (global input) characte set: a (global input) complex array, dimension (desca(lld_),* being scanned. n (global input) intege direc (global input) characte = 'f' (forward) n (global input) intege order of the distributed submatrix sub( a ). n >= 0. uplo (global input) characte hermitian matrix sub( a ) is stored: m (global input) intege of the distributed submatrix sub( a ). m >= 0. test the input parameters uplo (global input) character* sub( a ) is upper or lower triangular: uplo (global input) character* distributed matrix sub( a ) is upper or lower triangular: ii (global input) intege be made available only within the scope which owns the vector(s) being operated on. let x be a generic term for the input vector(s) an operation involves more than one vector, the processes which re- uplo (global input) characte = 'l': lower triangle of a(1:n, ja:ja+n-1) is stored. test the input parameter uplo (global input) characte = 'l': lower triangle of a(1:n, ja:ja+n-1) is stored. test the input parameter uplo (global input) characte a(ia:ia+n-1,ja:ja+n-1) is upper or lower triangular. n (global input) intege order of the distributed submatrix sub( a ). n >= 0. uplo (global input) character* hermitian matrix sub( a ) is stored. uplo (global input) characte = 'l': lower triangle of sub( a ) is stored. fact (global input) characte supplied on entry, and if not, whether the matrix a should be uplo (global input) characte = 'l': lower triangle of sub( a ) is stored. uplo (global input) characte = 'l': lower triangle of sub( a ) is stored. uplo (global input) character* = 'l': lower triangle of sub( a ) is stored. uplo (global input) characte = 'l': lower triangle of sub( a ) is stored. uplo (global input) characte = 'l': lower triangle of a(1:n, ja:ja+n-1) is stored. test the input parameter uplo (global input) characte = 'l': lower triangle of a(1:n, ja:ja+n-1) is stored. test the input parameter n (global input) pointer to intege n >= 0. orthogonalize vectors that are on different processes. the extent of orthogonalization is controlled by the input parameter lwork process. pcstein decides on the allocation of work among the norm (global input) characte infinity-norm condition number is required: matrices x and/or y of right or left eigenvectors of t, or the products q*x and/or q*y, where q is an input unitar original matrix a = q*t*q', then q*x and q*y are the matrices of uplo (global input) character* = 'l': sub( a ) is lower triangular. uplo (global input) character* = 'l': sub( a ) is lower triangular. uplo (global input) characte or lower triangular: uplo (global input) characte = 'l': sub( a ) is lower triangular. m (global input) intege of the distributed submatrix sub( a ). m >= 0. m (global input) intege of the distributed submatrix q. m >= 0. m (global input) intege of the distributed submatrix q. m >= 0. m (global input) intege of the distributed submatrix q. m >= 0. m (global input) intege of the distributed submatrix q. m >= 0. m (global input) intege of the distributed submatrix q. m >= 0. m (global input) intege of the distributed submatrix q. m >= 0. m (global input) intege of the distributed submatrix q. m >= 0. m (global input) intege of the distributed submatrix q. m >= 0. side (global input) characte = 'r': apply q or q**h from the right. side (global input) characte = 'r': apply q or q**h from the right. vect (global input) characte = 'p': apply p or p**h. side (global input) characte = 'r': apply q or q**h from the right. side (global input) characte = 'r': apply q or q**h from the right. side (global input) characte = 'r': apply q or q**h from the right. side (global input) characte = 'r': apply q or q**h from the right. side (global input) characte = 'r': apply q or q**h from the right. side (global input) characte = 'r': apply q or q**h from the right. side (global input) characte = 'r': apply q or q**h from the right. side (global input) characte = 'r': apply q or q**h from the right. side (global input) characte = 'r': apply q or q**h from the right. side (global input) characte = 'r': apply q or q**h from the right. n (global input) intege order of the distributed submatrix a(1:n, ja:ja+n-1). n >= 0. test the input parameter trans (global input) characte = 't' or 'c': solve with a(1:n, ja:ja+n-1)^t; test the input parameter n (global input) intege order of the distributed submatrix a(1:n, ja:ja+n-1). n >= 0. test the input parameter trans (global input) characte = 't' or 'c': solve with a(1:n, ja:ja+n-1)^t; test the input parameter n (global input) intege order of the distributed submatrix a(1:n, ja:ja+n-1). n >= 0. test the input parameter trans (global input) characte = 't' or 'c': solve with a(1:n, ja:ja+n-1)^t; m (global input) intege of the distributed submatrix sub( a ). m >= 0. m (global input) intege of the distributed submatrix sub( a ). m >= 0. norm (global input) characte infinity-norm condition number is required: m (global input) intege of the distributed submatrix sub( a ). m >= 0. n (global input) intege order of the distributed submatrix sub( a ). n >= 0. n (global input) intege order of the distributed submatrix sub( a ). n >= 0. m (global input) intege of the distributed submatrix sub( a ). m >= 0. m (global input) intege of the distributed submatrix sub( a ). m >= 0. trans (global input) characte = 't': the linear system involves sub( a )**t. m (global input) intege of the distributed submatrix sub( a ). m >= 0. m (global input) intege of the distributed submatrix sub( a ). m >= 0. m (global input) intege of the distributed submatrix sub( a ). m >= 0. m (global input) intege of the distributed submatrix sub( a ). m >= 0. m (global input) intege of the distributed submatrix sub( a ). m >= 0. trans (global input) character* = 'n': sub( a ) * sub( x ) = sub( b ) (no transpose) m (global input) intege of the distributed submatrix sub( a ). m >= 0. m (global input) intege of the distributed submatrix sub( a ). m >= 0. n (global input) intege order of the distributed submatrix sub( a ). n >= 0. jobu (global input) character* = 'v': the first size columns of u (the left singular fact (global input) characte a(ia:ia+n-1,ja:ja+n-1) is supplied on entry, and if not, m (global input) intege of the distributed submatrix sub( a ). m >= 0. m (global input) intege of the distributed submatrix sub( a ). m >= 0. n (global input) intege order of the distributed submatrix sub( a ). n >= 0. trans (global input) characte = 'n': sub( a ) * x = sub( b ) (no transpose) n (global input) intege of the distributed submatrices sub( a ) and sub( b ). n >= 0. m (global input) intege rows of the distributed submatrix sub( a ). m >= 0. pdlabad takes as input the values computed by pdlamch for underflo the log of large is sufficiently large. this subroutine is intended m (global input) intege of the distributed submatrix sub( a ). m >= 0. n (global input) intege a (global input) double precision array, dimensio on entry, the hessenberg matrix whose tridiagonal part is uplo (global input) characte copied: m (global input) intege m >= 0. uplo (global input) characte copied: pdlaebz contains the iteration loop which computes the eigenvalues contained in the input intervals [ intvl(2*j-1), intvl(2*j) ] wher the count of eigenvalues of a symmetric tridiagonal matrix less than pdlaecv checks if the input intervals [ intvl(2*i-1), intvl(2*i) ] pdlaecv modifies kf to be the index of the last converged interval, n (global input) intege n (global input) intege ictxt (global input) intege the operation on the matrix. the context itself is global. ictxt (global input) intege the operation on the matrix. the context itself is global. n (global input) intege n (global input) intege order of the distributed submatrix sub( a ). ictxt (global input) intege place. n (global input) intege norm (global input) characte above. sigma (input) double precisio than or equal to sigma. direc (global input) character* = 'f' (forward) applies pivots forward from top of matrix. direc (global input) characte = 'f' (forward) applies pivots forward from top of matrix. m (global input) intege of the distributed submatrix sub( a ). m >= 0. uplo (global input) characte symmetric distributed matrix sub( a ) is to be referenced: it assumes that the input array, bycol, is distributed acros bycol. the output array, byall, will be identical on all processes it assumes that the input array, byrow, is distributed acros byrow. the output array, byall, will be identical on all processes side (global input) characte = 'r': apply q or q**t from the right. n (global input) intege direct (global input) character* multiplied to form the block reflector: side (global input) characte = 'r': apply q or q**t from the right. direct (global input) characte multiplied to form the block reflector: type (global input) characte matrix. uplo (global input) characte set: uplo (global input) characte set: a (global input) double precision array, dimensio on entry, the hessenberg matrix whose tridiagonal part is id (global input) character* = 'd': sort d in decreasing order. (not implemented yet) n (global input) intege direc (global input) characte = 'f' (forward) n (global input) intege order of the distributed submatrix sub( a ). n >= 0. uplo (global input) characte symmetric matrix sub( a ) is stored: m (global input) intege of the distributed submatrix sub( a ). m >= 0. uplo (global input) character* sub( a ) is upper or lower triangular: uplo (global input) character* distributed matrix sub( a ) is upper or lower triangular: ii (global input) intege m (global input) intege of the distributed submatrix q. m >= 0. m (global input) intege of the distributed submatrix q. m >= 0. m (global input) intege of the distributed submatrix q. m >= 0. m (global input) intege of the distributed submatrix q. m >= 0. m (global input) intege of the distributed submatrix q. m >= 0. m (global input) intege of the distributed submatrix q. m >= 0. m (global input) intege of the distributed submatrix q. m >= 0. m (global input) intege of the distributed submatrix q. m >= 0. side (global input) characte = 'r': apply q or q**t from the right. side (global input) characte = 'r': apply q or q**t from the right. vect (global input) characte = 'p': apply p or p**t. side (global input) characte = 'r': apply q or q**t from the right. side (global input) characte = 'r': apply q or q**t from the right. side (global input) characte = 'r': apply q or q**t from the right. side (global input) characte = 'r': apply q or q**t from the right. side (global input) characte = 'r': apply q or q**t from the right. side (global input) characte = 'r': apply q or q**t from the right. side (global input) characte = 'r': apply q or q**t from the right. side (global input) characte = 'r': apply q or q**t from the right. side (global input) characte = 'r': apply q or q**t from the right. side (global input) characte = 'r': apply q or q**t from the right. uplo (global input) characte = 'l': lower triangle of a(1:n, ja:ja+n-1) is stored. test the input parameter uplo (global input) characte = 'l': lower triangle of a(1:n, ja:ja+n-1) is stored. test the input parameter uplo (global input) characte a(ia:ia+n-1,ja:ja+n-1) is upper or lower triangular. n (global input) intege order of the distributed submatrix sub( a ). n >= 0. uplo (global input) character* symmetric matrix sub( a ) is stored. uplo (global input) characte = 'l': lower triangle of sub( a ) is stored. fact (global input) characte supplied on entry, and if not, whether the matrix a should be uplo (global input) characte = 'l': lower triangle of sub( a ) is stored. uplo (global input) characte = 'l': lower triangle of sub( a ) is stored. uplo (global input) character* = 'l': lower triangle of sub( a ) is stored. uplo (global input) characte = 'l': lower triangle of sub( a ) is stored. n (global input) intege order of the distributed submatrix a(1:n, ja:ja+n-1). n >= 0. test the input parameter n (global input) intege order of the distributed submatrix a(1:n, ja:ja+n-1). n >= 0. test the input parameter n (global input) pointer to intege n >= 0. ictxt (global input) intege compz (input) character* = 'i': compute eigenvectors of tridiagonal matrix also. orthogonalize vectors that are on different processes. the extent of orthogonalization is controlled by the input parameter lwork process. pdstein decides on the allocation of work among the jobz (global input) character* = 'n': compute eigenvalues only. jobz (input) character* = 'v': compute eigenvalues and eigenvectors. jobz (global input) character* = 'n': compute eigenvalues only. ibtype (global input) intege inv(l)*sub( a )*inv(l**t); ibtype (global input) intege inv(l)*sub( a )*inv(l**t); ibtype (global input) intege = 1: sub( a )*x = (lambda)*sub( b )*x ibtype (global input) intege inv(l)*sub( a )*inv(l**h); the tailored codes provide performance that is essentially independent of the input data layout the tailored codes place no restrictions on ia, ja, mb or nb. uplo (global input) characte symmetric matrix sub( a ) is stored: uplo (global input) characte symmetric matrix sub( a ) is stored: uplo (global input) characte hermitian matrix sub( a ) is stored: norm (global input) characte infinity-norm condition number is required: uplo (global input) character* = 'l': sub( a ) is lower triangular. uplo (global input) character* = 'l': sub( a ) is lower triangular. uplo (global input) characte or lower triangular: uplo (global input) characte = 'l': sub( a ) is lower triangular. m (global input) intege of the distributed submatrix sub( a ). m >= 0. be made available only within the scope which owns the vector(s) being operated on. let x be a generic term for the input vector(s) an operation involves more than one vector, the processes which re- ispec (global input) intege pjlaenv. be made available only within the scope which owns the vector(s) being operated on. let x be a generic term for the input vector(s) an operation involves more than one vector, the processes which re- n (global input) intege order of the distributed submatrix a(1:n, ja:ja+n-1). n >= 0. test the input parameter trans (global input) characte = 't' or 'c': solve with a(1:n, ja:ja+n-1)^t; test the input parameter n (global input) intege order of the distributed submatrix a(1:n, ja:ja+n-1). n >= 0. test the input parameter trans (global input) characte = 't' or 'c': solve with a(1:n, ja:ja+n-1)^t; test the input parameter n (global input) intege order of the distributed submatrix a(1:n, ja:ja+n-1). n >= 0. test the input parameter trans (global input) characte = 't' or 'c': solve with a(1:n, ja:ja+n-1)^t; m (global input) intege of the distributed submatrix sub( a ). m >= 0. m (global input) intege of the distributed submatrix sub( a ). m >= 0. norm (global input) characte infinity-norm condition number is required: m (global input) intege of the distributed submatrix sub( a ). m >= 0. n (global input) intege order of the distributed submatrix sub( a ). n >= 0. n (global input) intege order of the distributed submatrix sub( a ). n >= 0. m (global input) intege of the distributed submatrix sub( a ). m >= 0. m (global input) intege of the distributed submatrix sub( a ). m >= 0. trans (global input) characte = 't': the linear system involves sub( a )**t. m (global input) intege of the distributed submatrix sub( a ). m >= 0. m (global input) intege of the distributed submatrix sub( a ). m >= 0. m (global input) intege of the distributed submatrix sub( a ). m >= 0. m (global input) intege of the distributed submatrix sub( a ). m >= 0. m (global input) intege of the distributed submatrix sub( a ). m >= 0. trans (global input) character* = 'n': sub( a ) * sub( x ) = sub( b ) (no transpose) m (global input) intege of the distributed submatrix sub( a ). m >= 0. m (global input) intege of the distributed submatrix sub( a ). m >= 0. n (global input) intege order of the distributed submatrix sub( a ). n >= 0. jobu (global input) character* = 'v': the first size columns of u (the left singular fact (global input) characte a(ia:ia+n-1,ja:ja+n-1) is supplied on entry, and if not, m (global input) intege of the distributed submatrix sub( a ). m >= 0. m (global input) intege of the distributed submatrix sub( a ). m >= 0. n (global input) intege order of the distributed submatrix sub( a ). n >= 0. trans (global input) characte = 'n': sub( a ) * x = sub( b ) (no transpose) n (global input) intege of the distributed submatrices sub( a ) and sub( b ). n >= 0. m (global input) intege rows of the distributed submatrix sub( a ). m >= 0. pslabad takes as input the values computed by pslamch for underflo the log of large is sufficiently large. this subroutine is intended m (global input) intege of the distributed submatrix sub( a ). m >= 0. n (global input) intege a (global input) real array, dimensio on entry, the hessenberg matrix whose tridiagonal part is uplo (global input) characte copied: m (global input) intege m >= 0. uplo (global input) characte copied: pslaebz contains the iteration loop which computes the eigenvalues contained in the input intervals [ intvl(2*j-1), intvl(2*j) ] wher the count of eigenvalues of a symmetric tridiagonal matrix less than pslaecv checks if the input intervals [ intvl(2*i-1), intvl(2*i) ] pslaecv modifies kf to be the index of the last converged interval, n (global input) intege n (global input) intege ictxt (global input) intege the operation on the matrix. the context itself is global. ictxt (global input) intege the operation on the matrix. the context itself is global. n (global input) intege n (global input) intege order of the distributed submatrix sub( a ). ictxt (global input) intege place. n (global input) intege norm (global input) characte above. sigma (input) rea than or equal to sigma. direc (global input) character* = 'f' (forward) applies pivots forward from top of matrix. direc (global input) characte = 'f' (forward) applies pivots forward from top of matrix. m (global input) intege of the distributed submatrix sub( a ). m >= 0. uplo (global input) characte symmetric distributed matrix sub( a ) is to be referenced: it assumes that the input array, bycol, is distributed acros bycol. the output array, byall, will be identical on all processes it assumes that the input array, byrow, is distributed acros byrow. the output array, byall, will be identical on all processes side (global input) characte = 'r': apply q or q**t from the right. n (global input) intege direct (global input) character* multiplied to form the block reflector: side (global input) characte = 'r': apply q or q**t from the right. direct (global input) characte multiplied to form the block reflector: type (global input) characte matrix. uplo (global input) characte set: uplo (global input) characte set: a (global input) real array, dimensio on entry, the hessenberg matrix whose tridiagonal part is id (global input) character* = 'd': sort d in decreasing order. (not implemented yet) n (global input) intege direc (global input) characte = 'f' (forward) n (global input) intege order of the distributed submatrix sub( a ). n >= 0. uplo (global input) characte symmetric matrix sub( a ) is stored: m (global input) intege of the distributed submatrix sub( a ). m >= 0. uplo (global input) character* sub( a ) is upper or lower triangular: uplo (global input) character* distributed matrix sub( a ) is upper or lower triangular: ii (global input) intege m (global input) intege of the distributed submatrix q. m >= 0. m (global input) intege of the distributed submatrix q. m >= 0. m (global input) intege of the distributed submatrix q. m >= 0. m (global input) intege of the distributed submatrix q. m >= 0. m (global input) intege of the distributed submatrix q. m >= 0. m (global input) intege of the distributed submatrix q. m >= 0. m (global input) intege of the distributed submatrix q. m >= 0. m (global input) intege of the distributed submatrix q. m >= 0. side (global input) characte = 'r': apply q or q**t from the right. side (global input) characte = 'r': apply q or q**t from the right. vect (global input) characte = 'p': apply p or p**t. side (global input) characte = 'r': apply q or q**t from the right. side (global input) characte = 'r': apply q or q**t from the right. side (global input) characte = 'r': apply q or q**t from the right. side (global input) characte = 'r': apply q or q**t from the right. side (global input) characte = 'r': apply q or q**t from the right. side (global input) characte = 'r': apply q or q**t from the right. side (global input) characte = 'r': apply q or q**t from the right. side (global input) characte = 'r': apply q or q**t from the right. side (global input) characte = 'r': apply q or q**t from the right. side (global input) characte = 'r': apply q or q**t from the right. uplo (global input) characte = 'l': lower triangle of a(1:n, ja:ja+n-1) is stored. test the input parameter uplo (global input) characte = 'l': lower triangle of a(1:n, ja:ja+n-1) is stored. test the input parameter uplo (global input) characte a(ia:ia+n-1,ja:ja+n-1) is upper or lower triangular. n (global input) intege order of the distributed submatrix sub( a ). n >= 0. uplo (global input) character* symmetric matrix sub( a ) is stored. uplo (global input) characte = 'l': lower triangle of sub( a ) is stored. fact (global input) characte supplied on entry, and if not, whether the matrix a should be uplo (global input) characte = 'l': lower triangle of sub( a ) is stored. uplo (global input) characte = 'l': lower triangle of sub( a ) is stored. uplo (global input) character* = 'l': lower triangle of sub( a ) is stored. uplo (global input) characte = 'l': lower triangle of sub( a ) is stored. n (global input) intege order of the distributed submatrix a(1:n, ja:ja+n-1). n >= 0. test the input parameter n (global input) intege order of the distributed submatrix a(1:n, ja:ja+n-1). n >= 0. test the input parameter n (global input) pointer to intege n >= 0. ictxt (global input) intege compz (input) character* = 'i': compute eigenvectors of tridiagonal matrix also. orthogonalize vectors that are on different processes. the extent of orthogonalization is controlled by the input parameter lwork process. psstein decides on the allocation of work among the jobz (global input) character* = 'n': compute eigenvalues only. jobz (input) character* = 'v': compute eigenvalues and eigenvectors. jobz (global input) character* = 'n': compute eigenvalues only. ibtype (global input) intege inv(l)*sub( a )*inv(l**t); ibtype (global input) intege inv(l)*sub( a )*inv(l**t); ibtype (global input) intege = 1: sub( a )*x = (lambda)*sub( b )*x ibtype (global input) intege inv(l)*sub( a )*inv(l**h); the tailored codes provide performance that is essentially independent of the input data layout the tailored codes place no restrictions on ia, ja, mb or nb. uplo (global input) characte symmetric matrix sub( a ) is stored: uplo (global input) characte symmetric matrix sub( a ) is stored: uplo (global input) characte hermitian matrix sub( a ) is stored: norm (global input) characte infinity-norm condition number is required: uplo (global input) character* = 'l': sub( a ) is lower triangular. uplo (global input) character* = 'l': sub( a ) is lower triangular. uplo (global input) characte or lower triangular: uplo (global input) characte = 'l': sub( a ) is lower triangular. m (global input) intege of the distributed submatrix sub( a ). m >= 0. n (global input) intege order of the distributed submatrix a(1:n, ja:ja+n-1). n >= 0. test the input parameter trans (global input) characte = 'c': solve with conjugate_transpose( a(1:n, ja:ja+n-1) ); test the input parameter n (global input) pointer to intege n >= 0. n (global input) intege order of the distributed submatrix a(1:n, ja:ja+n-1). n >= 0. test the input parameter trans (global input) characte = 'c': solve with conjugate_transpose( a(1:n, ja:ja+n-1) ); test the input parameter n (global input) intege order of the distributed submatrix a(1:n, ja:ja+n-1). n >= 0. test the input parameter trans (global input) characte = 'c': solve with conjugate_transpose( a(1:n, ja:ja+n-1) ); m (global input) intege of the distributed submatrix sub( a ). m >= 0. m (global input) intege of the distributed submatrix sub( a ). m >= 0. norm (global input) characte infinity-norm condition number is required: m (global input) intege of the distributed submatrix sub( a ). m >= 0. n (global input) intege order of the distributed submatrix sub( a ). n >= 0. n (global input) intege order of the distributed submatrix sub( a ). n >= 0. m (global input) intege of the distributed submatrix sub( a ). m >= 0. m (global input) intege of the distributed submatrix sub( a ). m >= 0. trans (global input) characte = 'c': the linear system involves sub( a )**h. m (global input) intege of the distributed submatrix sub( a ). m >= 0. m (global input) intege of the distributed submatrix sub( a ). m >= 0. m (global input) intege of the distributed submatrix sub( a ). m >= 0. m (global input) intege of the distributed submatrix sub( a ). m >= 0. m (global input) intege of the distributed submatrix sub( a ). m >= 0. trans (global input) character* = 'n': sub( a ) * sub( x ) = sub( b ) (no transpose) m (global input) intege of the distributed submatrix sub( a ). m >= 0. m (global input) intege of the distributed submatrix sub( a ). m >= 0. n (global input) intege order of the distributed submatrix sub( a ). n >= 0. jobu (global input) character* = 'v': the first size columns of u (the left singular fact (global input) characte a(ia:ia+n-1,ja:ja+n-1) is supplied on entry, and if not, m (global input) intege of the distributed submatrix sub( a ). m >= 0. m (global input) intege of the distributed submatrix sub( a ). m >= 0. n (global input) intege order of the distributed submatrix sub( a ). n >= 0. trans (global input) characte = 'n': sub( a ) * x = sub( b ) (no transpose) n (global input) intege of the distributed submatrices sub( a ) and sub( b ). n >= 0. m (global input) intege rows of the distributed submatrix sub( a ). m >= 0. jobz (global input) character* = 'n': compute eigenvalues only. jobz (input) character* = 'v': compute eigenvalues and eigenvectors. jobz (global input) character* = 'n': compute eigenvalues only. ibtype (global input) intege inv(l)*sub( a )*inv(l**h); ibtype (global input) intege inv(l)*sub( a )*inv(l**h); ibtype (global input) intege = 1: sub( a )*x = (lambda)*sub( b )*x ibtype (global input) intege inv(l)*sub( a )*inv(l**h); the tailored codes provide performance that is essentially independent of the input data layout the tailored codes place no restrictions on ia, ja, mb or nb. uplo (global input) characte hermitian matrix sub( a ) is stored: uplo (global input) characte hermitian matrix sub( a ) is stored: uplo (global input) characte hermitian matrix sub( a ) is stored: m (global input) intege of the distributed submatrix sub( a ). m >= 0. n (global input) intege n (global input) intege a (global input) complex*16 array, dimensio on entry, the hessenberg matrix whose tridiagonal part is uplo (global input) characte copied: m (global input) intege m >= 0. uplo (global input) characte copied: n (global input) intege n (global input) intege order of the distributed submatrix sub( a ). n (global input) intege norm (global input) characte above. direc (global input) character* = 'f' (forward) applies pivots forward from top of matrix. direc (global input) characte = 'f' (forward) applies pivots forward from top of matrix. m (global input) intege of the distributed submatrix sub( a ). m >= 0. uplo (global input) characte symmetric distributed matrix sub( a ) is to be referenced: side (global input) characte = 'r': apply q or q**h from the right. n (global input) intege direct (global input) character* multiplied to form the block reflector: side (global input) characte = 'r': apply q or q**h from the right. direct (global input) characte multiplied to form the block reflector: type (global input) characte matrix. uplo (global input) characte set: uplo (global input) characte set: a (global input) complex*16 array, dimension (desca(lld_),* being scanned. n (global input) intege direc (global input) characte = 'f' (forward) n (global input) intege order of the distributed submatrix sub( a ). n >= 0. uplo (global input) characte hermitian matrix sub( a ) is stored: m (global input) intege of the distributed submatrix sub( a ). m >= 0. test the input parameters uplo (global input) character* sub( a ) is upper or lower triangular: uplo (global input) character* distributed matrix sub( a ) is upper or lower triangular: ii (global input) intege be made available only within the scope which owns the vector(s) being operated on. let x be a generic term for the input vector(s) an operation involves more than one vector, the processes which re- uplo (global input) characte = 'l': lower triangle of a(1:n, ja:ja+n-1) is stored. test the input parameter uplo (global input) characte = 'l': lower triangle of a(1:n, ja:ja+n-1) is stored. test the input parameter uplo (global input) characte a(ia:ia+n-1,ja:ja+n-1) is upper or lower triangular. n (global input) intege order of the distributed submatrix sub( a ). n >= 0. uplo (global input) character* hermitian matrix sub( a ) is stored. uplo (global input) characte = 'l': lower triangle of sub( a ) is stored. fact (global input) characte supplied on entry, and if not, whether the matrix a should be uplo (global input) characte = 'l': lower triangle of sub( a ) is stored. uplo (global input) characte = 'l': lower triangle of sub( a ) is stored. uplo (global input) character* = 'l': lower triangle of sub( a ) is stored. uplo (global input) characte = 'l': lower triangle of sub( a ) is stored. uplo (global input) characte = 'l': lower triangle of a(1:n, ja:ja+n-1) is stored. test the input parameter uplo (global input) characte = 'l': lower triangle of a(1:n, ja:ja+n-1) is stored. test the input parameter orthogonalize vectors that are on different processes. the extent of orthogonalization is controlled by the input parameter lwork process. pzstein decides on the allocation of work among the norm (global input) characte infinity-norm condition number is required: matrices x and/or y of right or left eigenvectors of t, or the products q*x and/or q*y, where q is an input unitar original matrix a = q*t*q', then q*x and q*y are the matrices of uplo (global input) character* = 'l': sub( a ) is lower triangular. uplo (global input) character* = 'l': sub( a ) is lower triangular. uplo (global input) characte or lower triangular: uplo (global input) characte = 'l': sub( a ) is lower triangular. m (global input) intege of the distributed submatrix sub( a ). m >= 0. m (global input) intege of the distributed submatrix q. m >= 0. m (global input) intege of the distributed submatrix q. m >= 0. m (global input) intege of the distributed submatrix q. m >= 0. m (global input) intege of the distributed submatrix q. m >= 0. m (global input) intege of the distributed submatrix q. m >= 0. m (global input) intege of the distributed submatrix q. m >= 0. m (global input) intege of the distributed submatrix q. m >= 0. m (global input) intege of the distributed submatrix q. m >= 0. side (global input) characte = 'r': apply q or q**h from the right. side (global input) characte = 'r': apply q or q**h from the right. vect (global input) characte = 'p': apply p or p**h. side (global input) characte = 'r': apply q or q**h from the right. side (global input) characte = 'r': apply q or q**h from the right. side (global input) characte = 'r': apply q or q**h from the right. side (global input) characte = 'r': apply q or q**h from the right. side (global input) characte = 'r': apply q or q**h from the right. side (global input) characte = 'r': apply q or q**h from the right. side (global input) characte = 'r': apply q or q**h from the right. side (global input) characte = 'r': apply q or q**h from the right. side (global input) characte = 'r': apply q or q**h from the right. side (global input) characte = 'r': apply q or q**h from the right. m (input) intege test the input parameters n (input) intege uplo (input) character* s (local input/output) real array, (lds,* referenced. it is assumed that s has jblk double shifts test the input paramters type (global input) character* (apply from left) s (local input/output) real array, dimension ld on exit, the diagonal blocks of s have been rewritten to pair test the input paramters trans (input) characte = 'n': l * x = b (no transpose) test the input parameters test the input parameters v1 (local input/local output) complex*16 array o its global index. v1(1) = amax, v1(2) = indx. m (input) intege test the input parameters n (input) intege uplo (input) character* s (local input/output) complex*16 array, ( lds,* is referenced. it is assumed that s has jblk double shifts a (input/output) complex*1 c (input/output) complex*16 type (global input) character* (apply from left) uplo (input) character* of the tridiagonal matrix a is stored and the form of the |
| inquiry inquiry numroc is a scalapack tool functions; pjlaenv is a scalapack envionmental inquiry functio the subroutine blacs_gridinfo. numroc is a scalapack tool functions; pjlaenv is a scalapack envionmental inquiry functio the subroutine blacs_gridinfo. numroc is a scalapack tool functions; pjlaenv is a scalapack envionmental inquiry functio the subroutine blacs_gridinfo. numroc is a scalapack tool function; pjlaenv is a scalapack envionmental inquiry functio the subroutine blacs_gridinfo. numroc is a scalapack tool functions; pjlaenv is a scalapack envionmental inquiry functio calling the subroutine blacs_gridinfo. numroc is a scalapack tool functions; pjlaenv is a scalapack envionmental inquiry functio calling the subroutine blacs_gridinfo. numroc is a scalapack tool functions; pjlaenv is a scalapack envionmental inquiry functio the subroutine blacs_gridinfo. numroc is a scalapack tool function; pjlaenv is a scalapack envionmental inquiry functio the subroutine blacs_gridinfo. numroc is a scalapack tool functions; pjlaenv is a scalapack envionmental inquiry functio calling the subroutine blacs_gridinfo. numroc is a scalapack tool functions; pjlaenv is a scalapack envionmental inquiry functio calling the subroutine blacs_gridinfo. numroc is a scalapack tool functions; pjlaenv is a scalapack envionmental inquiry functio the subroutine blacs_gridinfo. numroc is a scalapack tool function; pjlaenv is a scalapack envionmental inquiry functio the subroutine blacs_gridinfo. numroc is a scalapack tool functions; pjlaenv is a scalapack envionmental inquiry functio the subroutine blacs_gridinfo. numroc is a scalapack tool functions; pjlaenv is a scalapack envionmental inquiry functio the subroutine blacs_gridinfo. numroc is a scalapack tool functions; pjlaenv is a scalapack envionmental inquiry functio the subroutine blacs_gridinfo. numroc is a scalapack tool function; pjlaenv is a scalapack envionmental inquiry functio the subroutine blacs_gridinfo. |
| Insertion Insertion do Insertion sort on d( start:endd do Insertion sort on d( start:endd do Insertion sort on d( start:endd do Insertion sort on d( start:endd |
| inside inside to which transformations must be applied. if eigenvalues only are being computed, i1 and i2 are set inside the main loop to which transformations must be applied. if eigenvalues only are being computed, i1 and i2 are set inside the main loop to which transformations must be applied. if eigenvalues only are being computed, i1 and i2 are set inside the main loop to which transformations must be applied. if eigenvalues only are being computed, i1 and i2 are set inside the main loop to which transformations must be applied. if eigenvalues only are being computed, i1 and i2 are set inside the main loop to which transformations must be applied. if eigenvalues only are being computed, i1 and i2 are set inside the main loop |
| inspectable inspectable parallel. these factors are applied to the matrix creating fillin, which is stored in a non-inspectable way in auxiliar the matrix a as p a p^t and then factoring the principal parallel. these factors are applied to the matrix creating fillin, which is stored in a non-inspectable way in auxiliar the matrix a as p a p^t and then factoring the principal parallel. these factors are applied to the matrix creating fillin, which is stored in a non-inspectable way in auxiliar the matrix a as p a p^t and then factoring the principal parallel. these factors are applied to the matrix creating fillin, which is stored in a non-inspectable way in auxiliar the matrix a as p a p^t and then factoring the principal parallel. these factors are applied to the matrix creating fillin, which is stored in a non-inspectable way in auxiliar the matrix a as p a p^t and then factoring the principal parallel. these factors are applied to the matrix creating fillin, which is stored in a non-inspectable way in auxiliar the matrix a as p a p^t and then factoring the principal parallel. these factors are applied to the matrix creating fillin, which is stored in a non-inspectable way in auxiliar the matrix a as p a p^t and then factoring the principal parallel. these factors are applied to the matrix creating fillin, which is stored in a non-inspectable way in auxiliar the matrix a as p a p^t and then factoring the principal parallel. these factors are applied to the matrix creating fillin, which is stored in a non-inspectable way in auxiliar the matrix a as p a p^t and then factoring the principal parallel. these factors are applied to the matrix creating fillin, which is stored in a non-inspectable way in auxiliar the matrix a as p a p^t and then factoring the principal parallel. these factors are applied to the matrix creating fillin, which is stored in a non-inspectable way in auxiliar the matrix a as p a p^t and then factoring the principal parallel. these factors are applied to the matrix creating fillin, which is stored in a non-inspectable way in auxiliar the matrix a as p a p^t and then factoring the principal parallel. these factors are applied to the matrix creating fillin, which is stored in a non-inspectable way in auxiliar the matrix a as p a p^t and then factoring the principal parallel. these factors are applied to the matrix creating fillin, which is stored in a non-inspectable way in auxiliar the matrix a as p a p^t and then factoring the principal parallel. these factors are applied to the matrix creating fillin, which is stored in a non-inspectable way in auxiliar the matrix a as p a p^t and then factoring the principal parallel. these factors are applied to the matrix creating fillin, which is stored in a non-inspectable way in auxiliar the matrix a as p a p^t and then factoring the principal parallel. these factors are applied to the matrix creating fillin, which is stored in a non-inspectable way in auxiliar the matrix a as p a p^t and then factoring the principal parallel. these factors are applied to the matrix creating fillin, which is stored in a non-inspectable way in auxiliar the matrix a as p a p^t and then factoring the principal parallel. these factors are applied to the matrix creating fillin, which is stored in a non-inspectable way in auxiliar the matrix a as p a p^t and then factoring the principal parallel. these factors are applied to the matrix creating fillin, which is stored in a non-inspectable way in auxiliar the matrix a as p a p^t and then factoring the principal parallel. these factors are applied to the matrix creating fillin, which is stored in a non-inspectable way in auxiliar the matrix a as p a p^t and then factoring the principal parallel. these factors are applied to the matrix creating fillin, which is stored in a non-inspectable way in auxiliar the matrix a as p a p^t and then factoring the principal parallel. these factors are applied to the matrix creating fillin, which is stored in a non-inspectable way in auxiliar the matrix a as p a p^t and then factoring the principal parallel. these factors are applied to the matrix creating fillin, which is stored in a non-inspectable way in auxiliar the matrix a as p a p^t and then factoring the principal parallel. these factors are applied to the matrix creating fillin, which is stored in a non-inspectable way in auxiliar the matrix a as p a p^t and then factoring the principal parallel. these factors are applied to the matrix creating fillin, which is stored in a non-inspectable way in auxiliar the matrix a as p a p^t and then factoring the principal parallel. these factors are applied to the matrix creating fillin, which is stored in a non-inspectable way in auxiliar the matrix a as p a p^t and then factoring the principal parallel. these factors are applied to the matrix creating fillin, which is stored in a non-inspectable way in auxiliar the matrix a as p a p^t and then factoring the principal parallel. these factors are applied to the matrix creating fillin, which is stored in a non-inspectable way in auxiliar the matrix a as p a p^t and then factoring the principal parallel. these factors are applied to the matrix creating fillin, which is stored in a non-inspectable way in auxiliar the matrix a as p a p^t and then factoring the principal parallel. these factors are applied to the matrix creating fillin, which is stored in a non-inspectable way in auxiliar the matrix a as p a p^t and then factoring the principal parallel. these factors are applied to the matrix creating fillin, which is stored in a non-inspectable way in auxiliar the matrix a as p a p^t and then factoring the principal parallel. these factors are applied to the matrix creating fillin, which is stored in a non-inspectable way in auxiliar the matrix a as p a p^t and then factoring the principal parallel. these factors are applied to the matrix creating fillin, which is stored in a non-inspectable way in auxiliar the matrix a as p a p^t and then factoring the principal parallel. these factors are applied to the matrix creating fillin, which is stored in a non-inspectable way in auxiliar the matrix a as p a p^t and then factoring the principal parallel. these factors are applied to the matrix creating fillin, which is stored in a non-inspectable way in auxiliar the matrix a as p a p^t and then factoring the principal parallel. these factors are applied to the matrix creating fillin, which is stored in a non-inspectable way in auxiliar the matrix a as p a p^t and then factoring the principal parallel. these factors are applied to the matrix creating fillin, which is stored in a non-inspectable way in auxiliar the matrix a as p a p^t and then factoring the principal parallel. these factors are applied to the matrix creating fillin, which is stored in a non-inspectable way in auxiliar the matrix a as p a p^t and then factoring the principal parallel. these factors are applied to the matrix creating fillin, which is stored in a non-inspectable way in auxiliar the matrix a as p a p^t and then factoring the principal |
| instead instead v = tau * v) and then a sum-to-all is required (to compute v' * h ). we use the following formula instead v = tau * ( v - c * tau' * h / 2 ) v = tau * v) and then a sum-to-all is required (to compute v' * h ). we use the following formula instead v = tau * ( v - c * tau' * h / 2 ) v = tau * v) and then a sum-to-all is required (to compute v' * h ). we use the following formula instead v = tau * ( v - c * tau' * h / 2 ) v = tau * v) and then a sum-to-all is required (to compute v' * h ). we use the following formula instead v = tau * ( v - c * tau' * h / 2 ) |
| Institute Institute based on code written by : peter arbenz, eth zurich, 1996. last modified by: peter arbenz, Institute of scientific computing based on code written by : peter arbenz, eth zurich, 1996. last modified by: peter arbenz, Institute of scientific computing |
| insufficient insufficient if jobz .eq. 'v', nz = m unless the user supplies insufficient space and pcheevx is not able to detect thi requested, the user must supply both sufficient if jobz .eq. 'v', nz = m unless the user supplies insufficient space and pchegvx is not able to detect thi requested, the user must supply both sufficient pchengst also calls pchegst when insufficient workspace i performance only when lwork >= 2 * np0 * nb + nq0 * nb + nb * nb processes and then calls sstein2 (modified lapack routine) on each individual process. if insufficient workspace is allocated, th processes and then calls dstein2 (modified lapack routine) on each individual process. if insufficient workspace is allocated, th if jobz .eq. 'v', nz = m unless the user supplies insufficient space and pdsyevx is not able to detect thi requested, the user must supply both sufficient if jobz .eq. 'v', nz = m unless the user supplies insufficient space and pdsygvx is not able to detect thi requested, the user must supply both sufficient pdsyngst also calls pdhegst when insufficient workspace i performance only when lwork >= 2 * np0 * nb + nq0 * nb + nb * nb processes and then calls sstein2 (modified lapack routine) on each individual process. if insufficient workspace is allocated, th if jobz .eq. 'v', nz = m unless the user supplies insufficient space and pssyevx is not able to detect thi requested, the user must supply both sufficient if jobz .eq. 'v', nz = m unless the user supplies insufficient space and pssygvx is not able to detect thi requested, the user must supply both sufficient pssyngst also calls pshegst when insufficient workspace i performance only when lwork >= 2 * np0 * nb + nq0 * nb + nb * nb if jobz .eq. 'v', nz = m unless the user supplies insufficient space and pzheevx is not able to detect thi requested, the user must supply both sufficient if jobz .eq. 'v', nz = m unless the user supplies insufficient space and pzhegvx is not able to detect thi requested, the user must supply both sufficient pzhengst also calls pzhegst when insufficient workspace i performance only when lwork >= 2 * np0 * nb + nq0 * nb + nb * nb processes and then calls dstein2 (modified lapack routine) on each individual process. if insufficient workspace is allocated, th |
| INT INT at present, ia, ja, mb and nb are restricted to those values allowed by pchetrd to keep the INTerface simple. these restrictions ar ted over. the context itself is glo- bal, but the handle (the INTege m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTege m_a (global) desca( m_ ) the number of rows in the global at present, ia, ja, mb and nb are restricted to those values allowed by pdsytrd to keep the INTerface simple. these restrictions ar ted over. the context itself is glo- bal, but the handle (the INTege m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTege m_a (global) desca( m_ ) the number of rows in the global at present, ia, ja, mb and nb are restricted to those values allowed by pssytrd to keep the INTerface simple. these restrictions ar at present, ia, ja, mb and nb are restricted to those values allowed by pzhetrd to keep the INTerface simple. these restrictions ar |
| INTEGER INTEGER m (input) INTEGER n (input) INTEGER n (input) INTEGER lds (local input) INTEGER 1 < nbulge <= jblk <= lds/2 lda (local input) INTEGER n (input) INTEGER n - INTEGER n must be at least zero. m (input) INTEGER n (input) INTEGER n (input) INTEGER lds (local input) INTEGER 1 < nbulge <= jblk <= lds/2 lda (local input) INTEGER lds (local input) INTEGER unchanged on exit. n (input) INTEGER n - INTEGER n must be at least zero. n (global input) INTEGER order of the distributed submatrix a(1:n, ja:ja+n-1). n >= 0. n (global input) INTEGER order of the distributed submatrix a(1:n, ja:ja+n-1). n >= 0. n (global input) INTEGER order of the distributed submatrix a(1:n, ja:ja+n-1). n >= 0. n (global input) INTEGER order of the distributed submatrix a(1:n, ja:ja+n-1). n >= 0. n (global input) INTEGER order of the distributed submatrix a(1:n, ja:ja+n-1). n >= 0. n (global input) INTEGER order of the distributed submatrix a(1:n, ja:ja+n-1). n >= 0. ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the distributed n (global input) INTEGER ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global n (global input) INTEGER order of the distributed submatrix sub( a ). n (global input) INTEGER ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global n (global input) INTEGER order of the distributed submatrix a(1:n, ja:ja+n-1). n >= 0. n (global input) INTEGER order of the distributed submatrix a(1:n, ja:ja+n-1). n >= 0. ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global n (global input) INTEGER order of the distributed submatrix a(1:n, ja:ja+n-1). n >= 0. n (global input) INTEGER order of the distributed submatrix a(1:n, ja:ja+n-1). n >= 0. ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca[ m_ ] the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global n (global input) INTEGER order of the distributed submatrix a(1:n, ja:ja+n-1). n >= 0. n (global input) INTEGER order of the distributed submatrix a(1:n, ja:ja+n-1). n >= 0. n (global input) INTEGER order of the distributed submatrix a(1:n, ja:ja+n-1). n >= 0. n (global input) INTEGER order of the distributed submatrix a(1:n, ja:ja+n-1). n >= 0. n (global input) INTEGER order of the distributed submatrix a(1:n, ja:ja+n-1). n >= 0. n (global input) INTEGER order of the distributed submatrix a(1:n, ja:ja+n-1). n >= 0. ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ictxt (global input) INTEGER place. ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ijob (input) INTEGER = 0 : find an interval with desired values of n(w) at the ijob (input) INTEGER = 0 : when an interval is narrower than abstol, or than n (global input) INTEGER n (global input) INTEGER ictxt (global input) INTEGER the operation on the matrix. the context itself is global. ictxt (global input) INTEGER the operation on the matrix. the context itself is global. ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global n (global input) INTEGER order of the distributed submatrix sub( a ). ictxt (global input) INTEGER place. n (global input) INTEGER ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global n (input) INTEGER ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global n (global input) INTEGER columns of the distributed submatrix sub( q ). n >= 0. ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global n (global input) INTEGER order of the distributed submatrix a(1:n, ja:ja+n-1). n >= 0. n (global input) INTEGER order of the distributed submatrix a(1:n, ja:ja+n-1). n >= 0. ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global n (global input) INTEGER order of the distributed submatrix a(1:n, ja:ja+n-1). n >= 0. n (global input) INTEGER order of the distributed submatrix a(1:n, ja:ja+n-1). n >= 0. ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca[ m_ ] the number of rows in the global ictxt (global input) INTEGER n (global input) INTEGER ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the distributed n (global input) INTEGER order of the distributed submatrix sub( a ). n >= 0. ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ispec (global input) INTEGER pjlaenv. ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global n (global input) INTEGER order of the distributed submatrix a(1:n, ja:ja+n-1). n >= 0. n (global input) INTEGER order of the distributed submatrix a(1:n, ja:ja+n-1). n >= 0. n (global input) INTEGER order of the distributed submatrix a(1:n, ja:ja+n-1). n >= 0. n (global input) INTEGER order of the distributed submatrix a(1:n, ja:ja+n-1). n >= 0. n (global input) INTEGER order of the distributed submatrix a(1:n, ja:ja+n-1). n >= 0. n (global input) INTEGER order of the distributed submatrix a(1:n, ja:ja+n-1). n >= 0. ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ictxt (global input) INTEGER place. ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ijob (input) INTEGER = 0 : find an interval with desired values of n(w) at the ijob (input) INTEGER = 0 : when an interval is narrower than abstol, or than n (global input) INTEGER n (global input) INTEGER ictxt (global input) INTEGER the operation on the matrix. the context itself is global. ictxt (global input) INTEGER the operation on the matrix. the context itself is global. ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global n (global input) INTEGER order of the distributed submatrix sub( a ). ictxt (global input) INTEGER place. n (global input) INTEGER ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global n (input) INTEGER ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global n (global input) INTEGER columns of the distributed submatrix sub( q ). n >= 0. ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global n (global input) INTEGER order of the distributed submatrix a(1:n, ja:ja+n-1). n >= 0. n (global input) INTEGER order of the distributed submatrix a(1:n, ja:ja+n-1). n >= 0. ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global n (global input) INTEGER order of the distributed submatrix a(1:n, ja:ja+n-1). n >= 0. n (global input) INTEGER order of the distributed submatrix a(1:n, ja:ja+n-1). n >= 0. ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca[ m_ ] the number of rows in the global ictxt (global input) INTEGER n (global input) INTEGER ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the distributed n (global input) INTEGER order of the distributed submatrix sub( a ). n >= 0. ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global n (global input) INTEGER order of the distributed submatrix a(1:n, ja:ja+n-1). n >= 0. n (global input) INTEGER order of the distributed submatrix a(1:n, ja:ja+n-1). n >= 0. ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca[ m_ ] the number of rows in the global n (global input) INTEGER order of the distributed submatrix a(1:n, ja:ja+n-1). n >= 0. n (global input) INTEGER order of the distributed submatrix a(1:n, ja:ja+n-1). n >= 0. n (global input) INTEGER order of the distributed submatrix a(1:n, ja:ja+n-1). n >= 0. n (global input) INTEGER order of the distributed submatrix a(1:n, ja:ja+n-1). n >= 0. ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the distributed n (global input) INTEGER ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global n (global input) INTEGER order of the distributed submatrix sub( a ). n (global input) INTEGER ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global n (global input) INTEGER order of the distributed submatrix a(1:n, ja:ja+n-1). n >= 0. n (global input) INTEGER order of the distributed submatrix a(1:n, ja:ja+n-1). n >= 0. ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global n (global input) INTEGER order of the distributed submatrix a(1:n, ja:ja+n-1). n >= 0. n (global input) INTEGER order of the distributed submatrix a(1:n, ja:ja+n-1). n >= 0. ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global ted over. the context itself is glo- bal, but the handle (the INTEGER m_a (global) desca( m_ ) the number of rows in the global m (input) INTEGER n (input) INTEGER n (input) INTEGER lds (local input) INTEGER 1 < nbulge <= jblk <= lds/2 lda (local input) INTEGER lds (local input) INTEGER unchanged on exit. n (input) INTEGER n - INTEGER n must be at least zero. m (input) INTEGER n (input) INTEGER n (input) INTEGER lds (local input) INTEGER 1 < nbulge <= jblk <= lds/2 lda (local input) INTEGER n (input) INTEGER n - INTEGER n must be at least zero. |
| integers integers the two integers npact (nu. of active processors) and npst loop. the two integers npact (nu. of active processors) and npst loop. the two integers npact (nu. of active processors) and npst loop. the two integers npact (nu. of active processors) and npst loop. |
| intended intended pcgeequ computes row and column scalings intended to equilibrate a reduce its condition number. r returns the row scale factors and c pchettrd is not intended to be called directly. all users ar appropriate. a must be in cyclic format (i.e. mb = nb = 1), pcpoequ computes row and column scalings intended t sub( a ) = a(ia:ia+n-1,ja:ja+n-1) and reduce its condition number pdgeequ computes row and column scalings intended to equilibrate a reduce its condition number. r returns the row scale factors and c and overflow, and returns the square root of each of these values if the log of large is sufficiently large. this subroutine is intended and redefine the underflow and overflow limits to be the square roots pdpoequ computes row and column scalings intended t sub( a ) = a(ia:ia+n-1,ja:ja+n-1) and reduce its condition number pdsyttrd is not intended to be called directly. all users ar appropriate. a must be in cyclic format (i.e. mb = nb = 1), psgeequ computes row and column scalings intended to equilibrate a reduce its condition number. r returns the row scale factors and c and overflow, and returns the square root of each of these values if the log of large is sufficiently large. this subroutine is intended and redefine the underflow and overflow limits to be the square roots pspoequ computes row and column scalings intended t sub( a ) = a(ia:ia+n-1,ja:ja+n-1) and reduce its condition number pssyttrd is not intended to be called directly. all users ar appropriate. a must be in cyclic format (i.e. mb = nb = 1), pzgeequ computes row and column scalings intended to equilibrate a reduce its condition number. r returns the row scale factors and c pzhettrd is not intended to be called directly. all users ar appropriate. a must be in cyclic format (i.e. mb = nb = 1), pzpoequ computes row and column scalings intended t sub( a ) = a(ia:ia+n-1,ja:ja+n-1) and reduce its condition number |
| inter inter pclaswp performs a series of row or column interchanges o interchange is initiated for each of rows or columns k1 trough k2 of pdlaswp performs a series of row or column interchanges o interchange is initiated for each of rows or columns k1 trough k2 of pslaswp performs a series of row or column interchanges o interchange is initiated for each of rows or columns k1 trough k2 of pzlaswp performs a series of row or column interchanges o interchange is initiated for each of rows or columns k1 trough k2 of |
| interaction interaction if info = k>nprocs, the submatrix stored on processor info-nprocs representing interactions with othe stably factorable wo/interchanges, a small (max(bwl,bwu)* (p-1)) system is formed representing interaction of the larger blocks, and is stored (as are it algorithm is used. for a linear system, a parallel front solve if info = k>nprocs, the submatrix stored on processor info-nprocs representing interactions with othe stably factorable wo/interchanges, a small ((p-1)) system is formed representing interaction of the larger blocks, and is stored (as are it algorithm is used. for a linear system, a parallel front solve if info = k>nprocs, the submatrix stored on processor info-nprocs representing interactions with othe nonsingular, a small (max(bwl,bwu)* (p-1)) system is formed representing interaction of the larger blocks, and is stored (as are it algorithm is used. for a linear system, a parallel front solve if info = k>nprocs, the submatrix stored on processor info-nprocs representing interactions with othe positive definite, a small (bw* (p-1)) system is formed representing interaction of the larger blocks, and is stored (as are it algorithm is used. for a linear system, a parallel front solve if info = k>nprocs, the submatrix stored on processor info-nprocs representing interactions with othe positive definite, a small ((p-1)) system is formed representing interaction of the larger blocks, and is stored (as are it algorithm is used. for a linear system, a parallel front solve if info = k>nprocs, the submatrix stored on processor info-nprocs representing interactions with othe stably factorable wo/interchanges, a small (max(bwl,bwu)* (p-1)) system is formed representing interaction of the larger blocks, and is stored (as are it algorithm is used. for a linear system, a parallel front solve if info = k>nprocs, the submatrix stored on processor info-nprocs representing interactions with othe stably factorable wo/interchanges, a small ((p-1)) system is formed representing interaction of the larger blocks, and is stored (as are it algorithm is used. for a linear system, a parallel front solve if info = k>nprocs, the submatrix stored on processor info-nprocs representing interactions with othe nonsingular, a small (max(bwl,bwu)* (p-1)) system is formed representing interaction of the larger blocks, and is stored (as are it algorithm is used. for a linear system, a parallel front solve if info = k>nprocs, the submatrix stored on processor info-nprocs representing interactions with othe positive definite, a small (bw* (p-1)) system is formed representing interaction of the larger blocks, and is stored (as are it algorithm is used. for a linear system, a parallel front solve if info = k>nprocs, the submatrix stored on processor info-nprocs representing interactions with othe positive definite, a small ((p-1)) system is formed representing interaction of the larger blocks, and is stored (as are it algorithm is used. for a linear system, a parallel front solve if info = k>nprocs, the submatrix stored on processor info-nprocs representing interactions with othe stably factorable wo/interchanges, a small (max(bwl,bwu)* (p-1)) system is formed representing interaction of the larger blocks, and is stored (as are it algorithm is used. for a linear system, a parallel front solve if info = k>nprocs, the submatrix stored on processor info-nprocs representing interactions with othe stably factorable wo/interchanges, a small ((p-1)) system is formed representing interaction of the larger blocks, and is stored (as are it algorithm is used. for a linear system, a parallel front solve if info = k>nprocs, the submatrix stored on processor info-nprocs representing interactions with othe nonsingular, a small (max(bwl,bwu)* (p-1)) system is formed representing interaction of the larger blocks, and is stored (as are it algorithm is used. for a linear system, a parallel front solve if info = k>nprocs, the submatrix stored on processor info-nprocs representing interactions with othe positive definite, a small (bw* (p-1)) system is formed representing interaction of the larger blocks, and is stored (as are it algorithm is used. for a linear system, a parallel front solve if info = k>nprocs, the submatrix stored on processor info-nprocs representing interactions with othe positive definite, a small ((p-1)) system is formed representing interaction of the larger blocks, and is stored (as are it algorithm is used. for a linear system, a parallel front solve if info = k>nprocs, the submatrix stored on processor info-nprocs representing interactions with othe stably factorable wo/interchanges, a small (max(bwl,bwu)* (p-1)) system is formed representing interaction of the larger blocks, and is stored (as are it algorithm is used. for a linear system, a parallel front solve if info = k>nprocs, the submatrix stored on processor info-nprocs representing interactions with othe stably factorable wo/interchanges, a small ((p-1)) system is formed representing interaction of the larger blocks, and is stored (as are it algorithm is used. for a linear system, a parallel front solve if info = k>nprocs, the submatrix stored on processor info-nprocs representing interactions with othe nonsingular, a small (max(bwl,bwu)* (p-1)) system is formed representing interaction of the larger blocks, and is stored (as are it algorithm is used. for a linear system, a parallel front solve if info = k>nprocs, the submatrix stored on processor info-nprocs representing interactions with othe positive definite, a small (bw* (p-1)) system is formed representing interaction of the larger blocks, and is stored (as are it algorithm is used. for a linear system, a parallel front solve if info = k>nprocs, the submatrix stored on processor info-nprocs representing interactions with othe positive definite, a small ((p-1)) system is formed representing interaction of the larger blocks, and is stored (as are it algorithm is used. for a linear system, a parallel front solve |
| interactions interactions if info = k>nprocs, the submatrix stored on processor info-nprocs representing interactions with othe stably factorable wo/interchanges, if info = k>nprocs, the submatrix stored on processor info-nprocs representing interactions with othe stably factorable wo/interchanges, if info = k>nprocs, the submatrix stored on processor info-nprocs representing interactions with othe nonsingular, if info = k>nprocs, the submatrix stored on processor info-nprocs representing interactions with othe positive definite, if info = k>nprocs, the submatrix stored on processor info-nprocs representing interactions with othe positive definite, if info = k>nprocs, the submatrix stored on processor info-nprocs representing interactions with othe stably factorable wo/interchanges, if info = k>nprocs, the submatrix stored on processor info-nprocs representing interactions with othe stably factorable wo/interchanges, if info = k>nprocs, the submatrix stored on processor info-nprocs representing interactions with othe nonsingular, if info = k>nprocs, the submatrix stored on processor info-nprocs representing interactions with othe positive definite, if info = k>nprocs, the submatrix stored on processor info-nprocs representing interactions with othe positive definite, if info = k>nprocs, the submatrix stored on processor info-nprocs representing interactions with othe stably factorable wo/interchanges, if info = k>nprocs, the submatrix stored on processor info-nprocs representing interactions with othe stably factorable wo/interchanges, if info = k>nprocs, the submatrix stored on processor info-nprocs representing interactions with othe nonsingular, if info = k>nprocs, the submatrix stored on processor info-nprocs representing interactions with othe positive definite, if info = k>nprocs, the submatrix stored on processor info-nprocs representing interactions with othe positive definite, if info = k>nprocs, the submatrix stored on processor info-nprocs representing interactions with othe stably factorable wo/interchanges, if info = k>nprocs, the submatrix stored on processor info-nprocs representing interactions with othe stably factorable wo/interchanges, if info = k>nprocs, the submatrix stored on processor info-nprocs representing interactions with othe nonsingular, if info = k>nprocs, the submatrix stored on processor info-nprocs representing interactions with othe positive definite, if info = k>nprocs, the submatrix stored on processor info-nprocs representing interactions with othe positive definite, |
| interchange interchange pclaswp performs a series of row or column interchanges o interchange is initiated for each of rows or columns k1 trough k2 of pdlaswp performs a series of row or column interchanges o interchange is initiated for each of rows or columns k1 trough k2 of pslaswp performs a series of row or column interchanges o interchange is initiated for each of rows or columns k1 trough k2 of pzlaswp performs a series of row or column interchanges o interchange is initiated for each of rows or columns k1 trough k2 of |
| interchangeably interchangeably tridiagonal matrices. thus, for tridiagonal matrices, dtype_a = 501 or 502 can be used interchangeably we require that the distributed vectors storing the diagonals of a tridiagonal matrices. thus, for tridiagonal matrices, dtype_a = 501 or 502 can be used interchangeably we require that the distributed vectors storing the diagonals of a tridiagonal matrices. thus, for tridiagonal matrices, dtype_a = 501 or 502 can be used interchangeably we require that the distributed vectors storing the diagonals of a tridiagonal matrices. thus, for tridiagonal matrices, dtype_a = 501 or 502 can be used interchangeably we require that the distributed vectors storing the diagonals of a tridiagonal matrices. thus, for tridiagonal matrices, dtype_a = 501 or 502 can be used interchangeably we require that the distributed vectors storing the diagonals of a tridiagonal matrices. thus, for tridiagonal matrices, dtype_a = 501 or 502 can be used interchangeably we require that the distributed vectors storing the diagonals of a tridiagonal matrices. thus, for tridiagonal matrices, dtype_a = 501 or 502 can be used interchangeably we require that the distributed vectors storing the diagonals of a tridiagonal matrices. thus, for tridiagonal matrices, dtype_a = 501 or 502 can be used interchangeably we require that the distributed vectors storing the diagonals of a tridiagonal matrices. thus, for tridiagonal matrices, dtype_a = 501 or 502 can be used interchangeably we require that the distributed vectors storing the diagonals of a tridiagonal matrices. thus, for tridiagonal matrices, dtype_a = 501 or 502 can be used interchangeably we require that the distributed vectors storing the diagonals of a tridiagonal matrices. thus, for tridiagonal matrices, dtype_a = 501 or 502 can be used interchangeably we require that the distributed vectors storing the diagonals of a tridiagonal matrices. thus, for tridiagonal matrices, dtype_a = 501 or 502 can be used interchangeably we require that the distributed vectors storing the diagonals of a tridiagonal matrices. thus, for tridiagonal matrices, dtype_a = 501 or 502 can be used interchangeably we require that the distributed vectors storing the diagonals of a tridiagonal matrices. thus, for tridiagonal matrices, dtype_a = 501 or 502 can be used interchangeably we require that the distributed vectors storing the diagonals of a tridiagonal matrices. thus, for tridiagonal matrices, dtype_a = 501 or 502 can be used interchangeably we require that the distributed vectors storing the diagonals of a tridiagonal matrices. thus, for tridiagonal matrices, dtype_a = 501 or 502 can be used interchangeably we require that the distributed vectors storing the diagonals of a |
| interchanged interchanged array is tied to the matrix a, ipiv(k) = l implies rows (or columns) k and l are to be interchanged ===================================================================== array is tied to the matrix a, ipiv(k) = l implies rows (or columns) k and l are to be interchanged ===================================================================== array is tied to the matrix a, ipiv(k) = l implies rows (or columns) k and l are to be interchanged ===================================================================== array is tied to the matrix a, ipiv(k) = l implies rows (or columns) k and l are to be interchanged ===================================================================== |
| interchanges interchanges cdbtrf computes an lu factorization of a real m-by-n band matrix a without using partial pivoting with row interchanges this is the unblocked version of the algorithm, calling level 2 blas. ddbtrf computes an lu factorization of a real m-by-n band matrix a without using partial pivoting with row interchanges this is the unblocked version of the algorithm, calling level 2 blas. processors was not stably factorable wo/interchanges processors was not stably factorable wo/interchanges the lu decomposition with partial pivoting and row interchanges i tation matrix, l is unit lower triangular, and u is upper triangular. distributed matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1) using partial pivoting with row interchanges the factorization has the form sub( a ) = p * l * u, where p is a matrix sub( a ) = (ia:ia+m-1,ja:ja+n-1) using partial pivoting with row interchanges the factorization has the form sub( a ) = p * l * u, where p is a distributed submatrix sub( a ) to which the row or column interchanges will be applied. on exit, the local piece distributed matrix sub( a ) to which the row or columns interchanges will be applied. on exit, this array contain pclaswp performs a series of row or column interchanges o interchange is initiated for each of rows or columns k1 trough k2 of processors was not stably factorable wo/interchanges processors was not stably factorable wo/interchanges the lu decomposition with partial pivoting and row interchanges i tation matrix, l is unit lower triangular, and u is upper triangular. distributed matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1) using partial pivoting with row interchanges the factorization has the form sub( a ) = p * l * u, where p is a matrix sub( a ) = (ia:ia+m-1,ja:ja+n-1) using partial pivoting with row interchanges the factorization has the form sub( a ) = p * l * u, where p is a distributed submatrix sub( a ) to which the row or column interchanges will be applied. on exit, the local piece distributed matrix sub( a ) to which the row or columns interchanges will be applied. on exit, this array contain pdlaswp performs a series of row or column interchanges o interchange is initiated for each of rows or columns k1 trough k2 of processors was not stably factorable wo/interchanges processors was not stably factorable wo/interchanges the lu decomposition with partial pivoting and row interchanges i tation matrix, l is unit lower triangular, and u is upper triangular. distributed matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1) using partial pivoting with row interchanges the factorization has the form sub( a ) = p * l * u, where p is a matrix sub( a ) = (ia:ia+m-1,ja:ja+n-1) using partial pivoting with row interchanges the factorization has the form sub( a ) = p * l * u, where p is a distributed submatrix sub( a ) to which the row or column interchanges will be applied. on exit, the local piece distributed matrix sub( a ) to which the row or columns interchanges will be applied. on exit, this array contain pslaswp performs a series of row or column interchanges o interchange is initiated for each of rows or columns k1 trough k2 of processors was not stably factorable wo/interchanges processors was not stably factorable wo/interchanges the lu decomposition with partial pivoting and row interchanges i tation matrix, l is unit lower triangular, and u is upper triangular. distributed matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1) using partial pivoting with row interchanges the factorization has the form sub( a ) = p * l * u, where p is a matrix sub( a ) = (ia:ia+m-1,ja:ja+n-1) using partial pivoting with row interchanges the factorization has the form sub( a ) = p * l * u, where p is a distributed submatrix sub( a ) to which the row or column interchanges will be applied. on exit, the local piece distributed matrix sub( a ) to which the row or columns interchanges will be applied. on exit, this array contain pzlaswp performs a series of row or column interchanges o interchange is initiated for each of rows or columns k1 trough k2 of sdbtrf computes an lu factorization of a real m-by-n band matrix a without using partial pivoting with row interchanges this is the unblocked version of the algorithm, calling level 2 blas. zdbtrf computes an lu factorization of a real m-by-n band matrix a without using partial pivoting with row interchanges this is the unblocked version of the algorithm, calling level 2 blas. |
| intercontext intercontext this routine will interpret the grid properly either way. scalapack routines *do not support intercontext operations* so tha for all array descriptors passed to that routine. this routine will interpret the grid properly either way. scalapack routines *do not support intercontext operations* so tha for all array descriptors passed to that routine. this routine will interpret the grid properly either way. scalapack routines *do not support intercontext operations* so tha for all array descriptors passed to that routine. this routine will interpret the grid properly either way. scalapack routines *do not support intercontext operations* so tha for all array descriptors passed to that routine. this routine will interpret the grid properly either way. scalapack routines *do not support intercontext operations* so tha for all array descriptors passed to that routine. this routine will interpret the grid properly either way. scalapack routines *do not support intercontext operations* so tha for all array descriptors passed to that routine. this routine will interpret the grid properly either way. scalapack routines *do not support intercontext operations* so tha for all array descriptors passed to that routine. this routine will interpret the grid properly either way. scalapack routines *do not support intercontext operations* so tha for all array descriptors passed to that routine. this routine will interpret the grid properly either way. scalapack routines *do not support intercontext operations* so tha for all array descriptors passed to that routine. this routine will interpret the grid properly either way. scalapack routines *do not support intercontext operations* so tha for all array descriptors passed to that routine. this routine will interpret the grid properly either way. scalapack routines *do not support intercontext operations* so tha for all array descriptors passed to that routine. this routine will interpret the grid properly either way. scalapack routines *do not support intercontext operations* so tha for all array descriptors passed to that routine. this routine will interpret the grid properly either way. scalapack routines *do not support intercontext operations* so tha for all array descriptors passed to that routine. this routine will interpret the grid properly either way. scalapack routines *do not support intercontext operations* so tha for all array descriptors passed to that routine. this routine will interpret the grid properly either way. scalapack routines *do not support intercontext operations* so tha for all array descriptors passed to that routine. this routine will interpret the grid properly either way. scalapack routines *do not support intercontext operations* so tha for all array descriptors passed to that routine. this routine will interpret the grid properly either way. scalapack routines *do not support intercontext operations* so tha for all array descriptors passed to that routine. this routine will interpret the grid properly either way. scalapack routines *do not support intercontext operations* so tha for all array descriptors passed to that routine. this routine will interpret the grid properly either way. scalapack routines *do not support intercontext operations* so tha for all array descriptors passed to that routine. this routine will interpret the grid properly either way. scalapack routines *do not support intercontext operations* so tha for all array descriptors passed to that routine. this routine will interpret the grid properly either way. scalapack routines *do not support intercontext operations* so tha for all array descriptors passed to that routine. this routine will interpret the grid properly either way. scalapack routines *do not support intercontext operations* so tha for all array descriptors passed to that routine. this routine will interpret the grid properly either way. scalapack routines *do not support intercontext operations* so tha for all array descriptors passed to that routine. this routine will interpret the grid properly either way. scalapack routines *do not support intercontext operations* so tha for all array descriptors passed to that routine. this routine will interpret the grid properly either way. scalapack routines *do not support intercontext operations* so tha for all array descriptors passed to that routine. this routine will interpret the grid properly either way. scalapack routines *do not support intercontext operations* so tha for all array descriptors passed to that routine. this routine will interpret the grid properly either way. scalapack routines *do not support intercontext operations* so tha for all array descriptors passed to that routine. this routine will interpret the grid properly either way. scalapack routines *do not support intercontext operations* so tha for all array descriptors passed to that routine. this routine will interpret the grid properly either way. scalapack routines *do not support intercontext operations* so tha for all array descriptors passed to that routine. this routine will interpret the grid properly either way. scalapack routines *do not support intercontext operations* so tha for all array descriptors passed to that routine. this routine will interpret the grid properly either way. scalapack routines *do not support intercontext operations* so tha for all array descriptors passed to that routine. this routine will interpret the grid properly either way. scalapack routines *do not support intercontext operations* so tha for all array descriptors passed to that routine. this routine will interpret the grid properly either way. scalapack routines *do not support intercontext operations* so tha for all array descriptors passed to that routine. this routine will interpret the grid properly either way. scalapack routines *do not support intercontext operations* so tha for all array descriptors passed to that routine. this routine will interpret the grid properly either way. scalapack routines *do not support intercontext operations* so tha for all array descriptors passed to that routine. this routine will interpret the grid properly either way. scalapack routines *do not support intercontext operations* so tha for all array descriptors passed to that routine. this routine will interpret the grid properly either way. scalapack routines *do not support intercontext operations* so tha for all array descriptors passed to that routine. this routine will interpret the grid properly either way. scalapack routines *do not support intercontext operations* so tha for all array descriptors passed to that routine. this routine will interpret the grid properly either way. scalapack routines *do not support intercontext operations* so tha for all array descriptors passed to that routine. this routine will interpret the grid properly either way. scalapack routines *do not support intercontext operations* so tha for all array descriptors passed to that routine. |
| interface interface at present, ia, ja, mb and nb are restricted to those values allowed by pchetrd to keep the interface simple. these restrictions ar at present, ia, ja, mb and nb are restricted to those values allowed by pdsytrd to keep the interface simple. these restrictions ar pjlaenv is patterned after ilaenv and keeps the same interface i used at present in scalapack. most scalapack codes use the input at present, ia, ja, mb and nb are restricted to those values allowed by pssytrd to keep the interface simple. these restrictions ar at present, ia, ja, mb and nb are restricted to those values allowed by pzhetrd to keep the interface simple. these restrictions ar |
| interleaved interleaved elements of the tridiagonal matrix t. these elements are assumed to be interleaved in memory for better cach d(1),d(3),...,d(2*n-1), while the squares of the off-diagonal elements of the tridiagonal matrix t. these elements are assumed to be interleaved in memory for better cach d(1),d(3),...,d(2*n-1), while the squares of the off-diagonal elements of the tridiagonal matrix t. these elements are assumed to be interleaved in memory for better cach d(1),d(3),...,d(2*n-1), while the squares of the off-diagonal elements of the tridiagonal matrix t. these elements are assumed to be interleaved in memory for better cach d(1),d(3),...,d(2*n-1), while the squares of the off-diagonal |
| intermediate intermediate local memory to an array of dimension locr(n+mod(ix-1,mb_x)). on an intermediate return, a * x, if kase=1, set all values for bulges. all bulges are stored in intermediate steps as loops over ki. their current "task however, because there are many bulges, k1(ki) & k2(ki) might gather the intermediate results to process (0,0) gather the intermediate results to process (0,0) use a level 1 pblas solve, scaling intermediate results local memory to an array of dimension locr(n+mod(ix-1,mb_x)). on an intermediate return, a * x, if kase=1, set all values for bulges. all bulges are stored in intermediate steps as loops over ki. their current "task however, because there are many bulges, k1(ki) & k2(ki) might gather the intermediate results to process (0,0) gather the intermediate results to process (0,0) local memory to an array of dimension locr(n+mod(ix-1,mb_x)). on an intermediate return, a * x, if kase=1, set all values for bulges. all bulges are stored in intermediate steps as loops over ki. their current "task however, because there are many bulges, k1(ki) & k2(ki) might gather the intermediate results to process (0,0) gather the intermediate results to process (0,0) local memory to an array of dimension locr(n+mod(ix-1,mb_x)). on an intermediate return, a * x, if kase=1, set all values for bulges. all bulges are stored in intermediate steps as loops over ki. their current "task however, because there are many bulges, k1(ki) & k2(ki) might gather the intermediate results to process (0,0) gather the intermediate results to process (0,0) use a level 1 pblas solve, scaling intermediate results |
| Internal Internal Internal parameter Internal parameter Internal parameter Internal parameter Internal parameter this is a scalapack Internal subroutine and arguments are no this is a scalapack Internal procedure and arguments are not checke this is a scalapack Internal procedure and arguments are not checke Internal parameter Internal parameter Internal parameter Internal parameter Internal parameter this is a scalapack Internal subroutine and arguments are no this is a scalapack Internal procedure and arguments are not checke this is a scalapack Internal procedure and arguments are not checke Internal parameter Internal parameter Internal parameter Internal parameter Internal parameter Internal parameter Internal parameter Internal parameter |
| interpret interpret (501 or 502) is input. this routine will interpret the grid properly either way the grid passed to a single scalapack routine *must be the same* (501 or 502) is input. this routine will interpret the grid properly either way the grid passed to a single scalapack routine *must be the same* (501 or 502) is input. this routine will interpret the grid properly either way the grid passed to a single scalapack routine *must be the same* (501 or 502) is input. this routine will interpret the grid properly either way the grid passed to a single scalapack routine *must be the same* (501 or 502) is input. this routine will interpret the grid properly either way the grid passed to a single scalapack routine *must be the same* (501 or 502) is input. this routine will interpret the grid properly either way the grid passed to a single scalapack routine *must be the same* (501 or 502) is input. this routine will interpret the grid properly either way the grid passed to a single scalapack routine *must be the same* (501 or 502) is input. this routine will interpret the grid properly either way the grid passed to a single scalapack routine *must be the same* (501 or 502) is input. this routine will interpret the grid properly either way the grid passed to a single scalapack routine *must be the same* (501 or 502) is input. this routine will interpret the grid properly either way the grid passed to a single scalapack routine *must be the same* (501 or 502) is input. this routine will interpret the grid properly either way the grid passed to a single scalapack routine *must be the same* (501 or 502) is input. this routine will interpret the grid properly either way the grid passed to a single scalapack routine *must be the same* (501 or 502) is input. this routine will interpret the grid properly either way the grid passed to a single scalapack routine *must be the same* (501 or 502) is input. this routine will interpret the grid properly either way the grid passed to a single scalapack routine *must be the same* (501 or 502) is input. this routine will interpret the grid properly either way the grid passed to a single scalapack routine *must be the same* (501 or 502) is input. this routine will interpret the grid properly either way the grid passed to a single scalapack routine *must be the same* (501 or 502) is input. this routine will interpret the grid properly either way the grid passed to a single scalapack routine *must be the same* (501 or 502) is input. this routine will interpret the grid properly either way the grid passed to a single scalapack routine *must be the same* (501 or 502) is input. this routine will interpret the grid properly either way the grid passed to a single scalapack routine *must be the same* (501 or 502) is input. this routine will interpret the grid properly either way the grid passed to a single scalapack routine *must be the same* (501 or 502) is input. this routine will interpret the grid properly either way the grid passed to a single scalapack routine *must be the same* (501 or 502) is input. this routine will interpret the grid properly either way the grid passed to a single scalapack routine *must be the same* (501 or 502) is input. this routine will interpret the grid properly either way the grid passed to a single scalapack routine *must be the same* (501 or 502) is input. this routine will interpret the grid properly either way the grid passed to a single scalapack routine *must be the same* (501 or 502) is input. this routine will interpret the grid properly either way the grid passed to a single scalapack routine *must be the same* (501 or 502) is input. this routine will interpret the grid properly either way the grid passed to a single scalapack routine *must be the same* (501 or 502) is input. this routine will interpret the grid properly either way the grid passed to a single scalapack routine *must be the same* (501 or 502) is input. this routine will interpret the grid properly either way the grid passed to a single scalapack routine *must be the same* (501 or 502) is input. this routine will interpret the grid properly either way the grid passed to a single scalapack routine *must be the same* (501 or 502) is input. this routine will interpret the grid properly either way the grid passed to a single scalapack routine *must be the same* (501 or 502) is input. this routine will interpret the grid properly either way the grid passed to a single scalapack routine *must be the same* (501 or 502) is input. this routine will interpret the grid properly either way the grid passed to a single scalapack routine *must be the same* (501 or 502) is input. this routine will interpret the grid properly either way the grid passed to a single scalapack routine *must be the same* (501 or 502) is input. this routine will interpret the grid properly either way the grid passed to a single scalapack routine *must be the same* (501 or 502) is input. this routine will interpret the grid properly either way the grid passed to a single scalapack routine *must be the same* (501 or 502) is input. this routine will interpret the grid properly either way the grid passed to a single scalapack routine *must be the same* (501 or 502) is input. this routine will interpret the grid properly either way the grid passed to a single scalapack routine *must be the same* (501 or 502) is input. this routine will interpret the grid properly either way the grid passed to a single scalapack routine *must be the same* (501 or 502) is input. this routine will interpret the grid properly either way the grid passed to a single scalapack routine *must be the same* (501 or 502) is input. this routine will interpret the grid properly either way the grid passed to a single scalapack routine *must be the same* |
| interval interval = 'a': all eigenvalues will be found. = 'v': all eigenvalues in the interval [vl,vu] will be found = 'a': all eigenvalues will be found. = 'v': all eigenvalues in the interval [vl,vu] will be found pdlaebz contains the iteration loop which computes the eigenvalues contained in the input intervals [ intvl(2*j-1), intvl(2*j) ] wher the count of eigenvalues of a symmetric tridiagonal matrix less than pdlaecv checks if the input intervals [ intvl(2*i-1), intvl(2*i) ] pdlaecv modifies kf to be the index of the last converged interval, parallel. the user may ask for all eigenvalues, all eigenvalues in the interval [vl, vu], or the eigenvalues indexed il through iu. results in all processes finding an (almost) equal number of = 'a': all eigenvalues will be found. = 'v': all eigenvalues in the interval [vl,vu] will be found = 'a': all eigenvalues will be found. = 'v': all eigenvalues in the interval [vl,vu] will be found pslaebz contains the iteration loop which computes the eigenvalues contained in the input intervals [ intvl(2*j-1), intvl(2*j) ] wher the count of eigenvalues of a symmetric tridiagonal matrix less than pslaecv checks if the input intervals [ intvl(2*i-1), intvl(2*i) ] pslaecv modifies kf to be the index of the last converged interval, parallel. the user may ask for all eigenvalues, all eigenvalues in the interval [vl, vu], or the eigenvalues indexed il through iu. results in all processes finding an (almost) equal number of = 'a': all eigenvalues will be found. = 'v': all eigenvalues in the interval [vl,vu] will be found = 'a': all eigenvalues will be found. = 'v': all eigenvalues in the interval [vl,vu] will be found = 'a': all eigenvalues will be found. = 'v': all eigenvalues in the interval [vl,vu] will be found = 'a': all eigenvalues will be found. = 'v': all eigenvalues in the interval [vl,vu] will be found |
| intervals intervals pdlaebz contains the iteration loop which computes the eigenvalues contained in the input intervals [ intvl(2*j-1), intvl(2*j) ] wher the count of eigenvalues of a symmetric tridiagonal matrix less than pdlaecv checks if the input intervals [ intvl(2*i-1), intvl(2*i) ] pdlaecv modifies kf to be the index of the last converged interval, fudge double precision, default = 2.0 a "fudge factor" to widen the gershgorin intervals. ideally arithmetic, this needs to be larger. the default for pslaebz contains the iteration loop which computes the eigenvalues contained in the input intervals [ intvl(2*j-1), intvl(2*j) ] wher the count of eigenvalues of a symmetric tridiagonal matrix less than pslaecv checks if the input intervals [ intvl(2*i-1), intvl(2*i) ] pslaecv modifies kf to be the index of the last converged interval, fudge real, default = 2.0 a "fudge factor" to widen the gershgorin intervals. ideally arithmetic, this needs to be larger. the default for |
| into into specifies the "number" of the first reflector. this is used as an index into vecs if block is set sort into decreasing orde specifies the "number" of the first reflector. this is used as an index into vecs if block is set sort into decreasing orde is used to factor a reordering of the matrix into l u see pcdbtrf and pcdbtrs for details. convert descriptor into standard form for easy access t a (local input/local output) complex pointer into lld_a >=(bwl+bwu+1) (stored in desca). convert descriptor into standard form for easy access t is used to factor a reordering of the matrix into l u see pcdttrf and pcdttrs for details. convert descriptor into standard form for easy access t b (local input/local output) complex pointer into on entry, this array contains the convert descriptor into standard form for easy access t is used to factor a reordering of the matrix into p l u see pcgbtrf and pcgbtrs for details. convert descriptor into standard form for easy access t a (local input/local output) complex pointer into lld_a >=(2*bwl+2*bwu+1) (stored in desca). a (local input/local output) complex pointer into th on entry, this array contains the local pieces of the a (local input/local output) complex pointer into th on entry, this array contains the local pieces of the a (local input) complex pointer into the local memor this array contains the local pieces of the factors l and u a (local input) complex pointer into the local memor local pieces of the m-by-n distributed matrix whose a (local input/local output) complex pointer into th on entry, this array contains the local pieces of the n-by-n a (local input/local output) complex pointer into th on entry, this array contains the local pieces of the n-by-n a (local input/local output) complex pointer into th on entry, the local pieces of the m-by-n distributed matrix a (local input/local output) complex pointer into th on entry, the local pieces of the m-by-n distributed matrix a (local input/local output) complex pointer into th ( lld_a, locc(ja+n-1) ). on entry, the m-by-n matrix a. a (local input/local output) complex pointer into th on entry, the local pieces of the m-by-n distributed matrix a (local input/local output) complex pointer into th on entry, the local pieces of the m-by-n distributed matrix a (local input/local output) complex pointer into th on entry, the local pieces of the m-by-n distributed matrix a (local input/local output) complex pointer into th on entry, the local pieces of the m-by-n distributed matrix a (local input/local output) complex pointer into th on entry, the local pieces of the m-by-n distributed matrix a (local input) complex pointer into the loca this array contains the local pieces of the distributed a (local input/local output) complex pointer into th on entry, the local pieces of the m-by-n distributed matrix a (local input/local output) complex pointer into th on entry, the local pieces of the m-by-n distributed matrix a (local input/local output) complex pointer into th on entry, the local pieces of the n-by-n distributed matrix a (local input/local output) complex pointer into (lld_a,locc(ja+n-1)). on entry, the n-by-n matrix a (local input/local output) complex pointer into th on entry, this array contains the local pieces of the m-by-n a (local input/local output) complex pointer into th on entry, this array contains the local pieces of the m-by-n a (local input/local output) complex pointer into th on entry, the local pieces of the l and u obtained by the a (local input) complex pointer into the loca on entry, this array contains the local pieces of the factors a (local input/local output) complex pointer into th on entry, the local pieces of the n-by-m distributed matrix a (local input/local output) complex pointer into th on entry, the local pieces of the m-by-n distributed matrix a (local input/local output) complex pointer into th on entry, this array contains the local pieces of the a (local input/local output) complex pointer into th on entry, this array contains the local pieces of the a (local input/local output) complex pointer into th on entry, this array contains the local pieces of the a (local input/local output) complex pointer into th on entry, this array contains the local pieces of the a (local input/local output) complex pointer into th on entry, this array contains the local pieces of the a (local input/local output) complex pointer into th on entry, this array contains the local pieces of the a (local input/local output) complex pointer into th on entry, this array contains the local pieces of the a (local input/local output) complex pointer into th on entry, this array contains the local pieces of the a (local input/local output) complex pointer into th on entry, this array contains the local pieces of the x (local input/local output) complex pointer into th on entry the vector to be conjugated v (local workspace) complex pointer into the loca the final return, v = a*w, where est = norm(v)/norm(w) a (local input) complex pointer into the local memor contains the local pieces of the distributed matrix sub( a ) pclacp3 is an auxiliary routine that copies from a global parallel array into a local replicated array or vise versa. notice tha more. the receiving node can be specified precisely, or all nodes a (local input) complex pointer into the local memor contains the local pieces of the distributed matrix sub( a ) column application to h. here we do something a little more clever. we break each transformation down into 1.) the minimum amount of work it takes to determine a (local input/local output) complex pointer into locc(ja+n-k)). on entry, this array contains the the local a (local output) complex*16 pointer into th on output, a is replicated across all processes in a (local input) complex pointer into the local memor local pieces of the distributed matrix sub( a ). ii, jj : local indices into array icurcol : process column containing diagonal block ii, jj : local indices into array icurcol : process column containing diagonal block a (local input/local output) complex pointer into th on entry, this array contains the local pieces of the a (local input/local output) complex pointer into th on entry, this local array contains the local pieces of the a (local input/local output) complex pointer into th containing on entry the m-by-n matrix sub( a ). on exit, a (input/output) complex pointer into the loca on entry, the local pieces of the distributed symmetric v (local input) complex pointer into the local memor storev = 'c', ( lld_v, locc(jv+m-1)) if storev = 'r' and x (local input/local output) complex, pointer into th contains the local pieces of the distributed vector sub( x ). v (input/output) complex pointer into the local memor if storev = 'c', and (locr(iv+k-1),locc(jv+n-1)) if v (local input) complex pointer into the local memor (lld_v, locc(jv+n-1)) if side = 'r'. it contains the local v (input/output) complex pointer into the local memor the distributed matrix v contains the householder vectors. a (local input/local output) complex pointer into th this array contains the local pieces of the distributed a (local output) complex pointer into the local memor contains the local pieces of the distributed matrix sub( a ) a (local output) complex pointer into the local memor contains the local pieces of the distributed matrix sub( a ) a (local input/local output) complex pointer into th on entry, this array contains the local pieces of the distri- a (local input) complex pointer into the local memor contains the local pieces of the distributed matrix the trace a (local input/local output) complex pointer into th on entry, this array contains the local pieces of the a (local input/local output) complex pointer into th on entry, the local pieces of the m-by-n distributed matrix a (local input/local output) complex pointer into th on entry, the local pieces of the triangular factor l or u. a (local input/local output) complex pointer into th on entry, the local pieces of the triangular factor l or u. pclawil gets the transform given by h44,h33, & h43h34 into cholesky factorization is used to factor a reordering of the matrix into l l' see pcpbtrf and pcpbtrs for details. convert descriptor into standard form for easy access t a (local input/local output) complex pointer into lld_a >=(bw+1) (stored in desca). convert descriptor into standard form for easy access t a (local input) complex pointer into the local memory t array contains the local pieces of the factors l or u from a (local input) complex pointer into the local memory to a n-by-n hermitian positive definite distributed matrix a (local input) complex pointer into the loca this array contains the local pieces of the n-by-n hermitian a (local input/local output) complex pointer into th on entry, this array contains the local pieces of the a (local input/local output) complex pointer into ( lld_a, locc(ja+n-1) ). a (local input/local output) complex pointer into th on entry, this array contains the local pieces of the a (local input/local output) complex pointer into th on entry, this array contains the local pieces of the a (local input/local output) complex pointer into th on entry, the local pieces of the triangular factor u or l a (local input) complex pointer into local memory t array contains the factors l or u from the cholesky facto- cholesky factorization is used to factor a reordering of the matrix into l l' see pcpttrf and pcpttrs for details. convert descriptor into standard form for easy access t b (local input/local output) complex pointer into on entry, this array contains the convert descriptor into standard form for easy access t isplit (global input) integer array, dimension (n) the splitting points, at which t breaks up into submatrices the second of rows/columns isplit(1)+1 through isplit(2), a (local input) complex pointer into the local memor contains the local pieces of the triangular distributed a (local input) complex pointer into the local memor array contains the local pieces of the original triangular a (local input/local output) complex pointer into th this array contains the local pieces of the triangular matrix a (local input/local output) complex pointer into th on entry, this array contains the local pieces of the a (local input) complex pointer into the local memor contains the local pieces of the distributed triangular a (local input/local output) complex pointer into th on entry, the local pieces of the m-by-n distributed matrix a (local input/local output) complex pointer into th on entry, the j-th column must contain the vector which a (local input/local output) complex pointer into th on entry, the j-th column must contain the vector which a (local input/local output) complex pointer into th on entry, the i-th row must contain the vector which defines a (local input/local output) complex pointer into th on entry, the i-th row must contain the vector which defines a (local input/local output) complex pointer into th on entry, the j-th column must contain the vector which a (local input/local output) complex pointer into th on entry, the j-th column must contain the vector which a (local input/local output) complex pointer into th on entry, the i-th row must contain the vector which defines a (local input/local output) complex pointer into th on entry, the i-th row must contain the vector which defines a (local input) complex pointer into the local memor j-th column must contain the vector which defines the elemen- a (local input) complex pointer into the local memor j-th column must contain the vector which defines the elemen- a (local input) complex pointer into the local memor vect='q', and (lld_a,locc(ja+nq-1)) if vect = 'p'. nq = m a (local input) complex pointer into the local memor and (lld_a,locc(ja+n-1)) if side = 'r'. the vectors which a (local input) complex pointer into the local memor and (lld_a,locc(ja+n-1)) if side='r', where a (local input) complex pointer into the local memor and (lld_a,locc(ja+n-1)) if side='r', where a (local input) complex pointer into the local memor j-th column must contain the vector which defines the elemen- a (local input) complex pointer into the local memor j-th column must contain the vector which defines the elemen- a (local input) complex pointer into the local memor and (lld_a,locc(ja+n-1)) if side='r', where a (local input) complex pointer into the local memor and (lld_a,locc(ja+n-1)) if side='r', where a (local input) complex pointer into the local memor and (lld_a,locc(ja+n-1)) if side='r', where a (local input) complex pointer into the local memor and (lld_a,locc(ja+n-1)) if side='r', where a (local input) complex pointer into the local memor or (lld_a,locc(ja+n-1)) if side = 'r'. the vectors which is used to factor a reordering of the matrix into l u see pddbtrf and pddbtrs for details. convert descriptor into standard form for easy access t a (local input/local output) double precision pointer into lld_a >=(bwl+bwu+1) (stored in desca). convert descriptor into standard form for easy access t is used to factor a reordering of the matrix into l u see pddttrf and pddttrs for details. convert descriptor into standard form for easy access t b (local input/local output) double precision pointer into on entry, this array contains the convert descriptor into standard form for easy access t is used to factor a reordering of the matrix into p l u see pdgbtrf and pdgbtrs for details. convert descriptor into standard form for easy access t a (local input/local output) double precision pointer into lld_a >=(2*bwl+2*bwu+1) (stored in desca). a (local input/local output) double precision pointer into th on entry, this array contains the local pieces of the a (local input/local output) double precision pointer into th on entry, this array contains the local pieces of the a (local input) double precision pointer into the local memor this array contains the local pieces of the factors l and u a (local input) double precision pointer into the local memor local pieces of the m-by-n distributed matrix whose a (local input/local output) double precision pointer into th on entry, this array contains the local pieces of the n-by-n a (local input/local output) double precision pointer into th on entry, this array contains the local pieces of the n-by-n a (local input/local output) double precision pointer into th on entry, the local pieces of the m-by-n distributed matrix a (local input/local output) double precision pointer into th on entry, the local pieces of the m-by-n distributed matrix a (local input/local output) double precision pointer into th ( lld_a, locc(ja+n-1) ). on entry, the m-by-n matrix a. a (local input/local output) double precision pointer into th on entry, the local pieces of the m-by-n distributed matrix a (local input/local output) double precision pointer into th on entry, the local pieces of the m-by-n distributed matrix a (local input/local output) double precision pointer into th on entry, the local pieces of the m-by-n distributed matrix a (local input/local output) double precision pointer into th on entry, the local pieces of the m-by-n distributed matrix a (local input/local output) double precision pointer into th on entry, the local pieces of the m-by-n distributed matrix a (local input) double precision pointer into the loca this array contains the local pieces of the distributed a (local input/local output) double precision pointer into th on entry, the local pieces of the m-by-n distributed matrix a (local input/local output) double precision pointer into th on entry, the local pieces of the m-by-n distributed matrix a (local input/local output) double precision pointer into th on entry, the local pieces of the n-by-n distributed matrix a (local input/local output) double precision pointer into (lld_a,locc(ja+n-1)). on entry, the n-by-n matrix a (local input/local output) double precision pointer into th on entry, this array contains the local pieces of the m-by-n a (local input/local output) double precision pointer into th on entry, this array contains the local pieces of the m-by-n a (local input/local output) double precision pointer into th on entry, the local pieces of the l and u obtained by the a (local input) double precision pointer into the loca on entry, this array contains the local pieces of the factors a (local input/local output) double precision pointer into th on entry, the local pieces of the n-by-m distributed matrix a (local input/local output) double precision pointer into th on entry, the local pieces of the m-by-n distributed matrix a (local input/local output) double precision pointer into th on entry, this array contains the local pieces of the v (local workspace) double precision pointer into the loca the final return, v = a*w, where est = norm(v)/norm(w) a (local input) double precision pointer into the local memor contains the local pieces of the distributed matrix sub( a ) pdlacp3 is an auxiliary routine that copies from a global parallel array into a local replicated array or vise versa. notice tha more. the receiving node can be specified precisely, or all nodes a (local input) double precision pointer into the local memor contains the local pieces of the distributed matrix sub( a ) pdlaed2 sorts the two sets of eigenvalues together into a singl there are two ways in which deflation can occur: when two or more on exit, d contains the trailing (n-k) updated eigenvalues (those which were deflated) sorted into increasing order drow (global input) integer column application to h. here we do something a little more clever. we break each transformation down into 1.) the minimum amount of work it takes to determine a (local input/local output) double precision pointer into locc(ja+n-k)). on entry, this array contains the the local a (local output) complex*16 pointer into th on output, a is replicated across all processes in a (local input) double precision pointer into the local memor local pieces of the distributed matrix sub( a ). ii, jj : local indices into array icurcol : process column containing diagonal block a (local input/local output) double precision pointer into th on entry, this array contains the local pieces of the a (local input/local output) double precision pointer into th on entry, this local array contains the local pieces of the a (local input/local output) double precision pointer into th containing on entry the m-by-n matrix sub( a ). on exit, a (input/output) double precision pointer into the loca on entry, the local pieces of the distributed symmetric v (local input) double precision pointer into the local memor storev = 'c', ( lld_v, locc(jv+m-1)) if storev = 'r' and x (local input/local output) double precision, pointer into th contains the local pieces of the distributed vector sub( x ). v (input/output) double precision pointer into the local memor if storev = 'c', and (locr(iv+k-1),locc(jv+n-1)) if v (local input) double precision pointer into the local memor (lld_v, locc(jv+n-1)) if side = 'r'. it contains the local v (input/output) double precision pointer into the local memor the distributed matrix v contains the householder vectors. a (local input/local output) double precision pointer into th this array contains the local pieces of the distributed a (local output) double precision pointer into the local memor contains the local pieces of the distributed matrix sub( a ) a (local output) double precision pointer into the local memor contains the local pieces of the distributed matrix sub( a ) q (local input) double precision pointer into the local memor contains the local pieces of the distributed matrix sub( a ) a (local input/local output) double precision pointer into th on entry, this array contains the local pieces of the distri- a (local input) double precision pointer into the local memor contains the local pieces of the distributed matrix the trace a (local input/local output) double precision pointer into th on entry, this array contains the local pieces of the a (local input/local output) double precision pointer into th on entry, the local pieces of the m-by-n distributed matrix a (local input/local output) double precision pointer into th on entry, the local pieces of the triangular factor l or u. a (local input/local output) double precision pointer into th on entry, the local pieces of the triangular factor l or u. pdlawil gets the transform given by h44,h33, & h43h34 into a (local input/local output) double precision pointer into th on entry, the j-th column must contain the vector which a (local input/local output) double precision pointer into th on entry, the j-th column must contain the vector which a (local input/local output) double precision pointer into th on entry, the i-th row must contain the vector which defines a (local input/local output) double precision pointer into th on entry, the i-th row must contain the vector which defines a (local input/local output) double precision pointer into th on entry, the j-th column must contain the vector which a (local input/local output) double precision pointer into th on entry, the j-th column must contain the vector which a (local input/local output) double precision pointer into th on entry, the i-th row must contain the vector which defines a (local input/local output) double precision pointer into th on entry, the i-th row must contain the vector which defines a (local input) double precision pointer into the local memor j-th column must contain the vector which defines the elemen- a (local input) double precision pointer into the local memor j-th column must contain the vector which defines the elemen- a (local input) double precision pointer into the local memor vect='q', and (lld_a,locc(ja+nq-1)) if vect = 'p'. nq = m a (local input) double precision pointer into the local memor and (lld_a,locc(ja+n-1)) if side = 'r'. the vectors which a (local input) double precision pointer into the local memor and (lld_a,locc(ja+n-1)) if side='r', where a (local input) double precision pointer into the local memor and (lld_a,locc(ja+n-1)) if side='r', where a (local input) double precision pointer into the local memor j-th column must contain the vector which defines the elemen- a (local input) double precision pointer into the local memor j-th column must contain the vector which defines the elemen- a (local input) double precision pointer into the local memor and (lld_a,locc(ja+n-1)) if side='r', where a (local input) double precision pointer into the local memor and (lld_a,locc(ja+n-1)) if side='r', where a (local input) double precision pointer into the local memor and (lld_a,locc(ja+n-1)) if side='r', where a (local input) double precision pointer into the local memor and (lld_a,locc(ja+n-1)) if side='r', where a (local input) double precision pointer into the local memor or (lld_a,locc(ja+n-1)) if side = 'r'. the vectors which cholesky factorization is used to factor a reordering of the matrix into l l' see pdpbtrf and pdpbtrs for details. convert descriptor into standard form for easy access t a (local input/local output) double precision pointer into lld_a >=(bw+1) (stored in desca). convert descriptor into standard form for easy access t a (local input) double precision pointer into the local memor this array contains the local pieces of the factors l or u a (local input) double precision pointer into the local memor n-by-n symmetric positive definite distributed matrix a (local input) double precision pointer into the loca this array contains the local pieces of the n-by-n symmetric a (local input/local output) double precision pointer into th on entry, this array contains the local pieces of the a (local input/local output) double precision pointer into ( lld_a, locc(ja+n-1) ). a (local input/local output) double precision pointer into th on entry, this array contains the local pieces of the a (local input/local output) double precision pointer into th on entry, this array contains the local pieces of the a (local input/local output) double precision pointer into th on entry, the local pieces of the triangular factor u or l a (local input) double precision pointer into local memory t array contains the factors l or u from the cholesky facto- cholesky factorization is used to factor a reordering of the matrix into l l' see pdpttrf and pdpttrs for details. convert descriptor into standard form for easy access t b (local input/local output) double precision pointer into on entry, this array contains the convert descriptor into standard form for easy access t at each row/column j where e(j) is zero or small, the matrix t is considered to split into a block diagona to the number of blocks) the eigenvalue w(i) belongs to. isplit (global input) integer array, dimension (n) the splitting points, at which t breaks up into submatrices the second of rows/columns isplit(1)+1 through isplit(2), a (local input/local output) double precision pointer into th on entry, this array contains the local pieces of the a (local input/local output) double precision pointer into th on entry, this array contains the local pieces of the a (local input/local output) double precision pointer into th on entry, this array contains the local pieces of the a (local input/local output) double precision pointer into th on entry, this array contains the local pieces of the a (local input/local output) double precision pointer into th on entry, this array contains the local pieces of the a (local input/local output) double precision pointer into th on entry, this array contains the local pieces of the a (local input/local output) double precision pointer into th on entry, this array contains the local pieces of the a (local input/local output) double precision pointer into th on entry, this array contains the local pieces of the a (local input) double precision pointer into the local memor contains the local pieces of the triangular distributed a (local input) double precision pointer into the local memor array contains the local pieces of the original triangular a (local input/local output) double precision pointer into th this array contains the local pieces of the triangular matrix a (local input/local output) double precision pointer into th on entry, this array contains the local pieces of the a (local input) double precision pointer into the local memor contains the local pieces of the distributed triangular a (local input/local output) double precision pointer into th on entry, the local pieces of the m-by-n distributed matrix the character options to the subroutine name, concatenated into a single character string. for example, uplo = 'u' be specified as opts = 'utn'. is used to factor a reordering of the matrix into l u see psdbtrf and psdbtrs for details. convert descriptor into standard form for easy access t a (local input/local output) real pointer into lld_a >=(bwl+bwu+1) (stored in desca). convert descriptor into standard form for easy access t is used to factor a reordering of the matrix into l u see psdttrf and psdttrs for details. convert descriptor into standard form for easy access t b (local input/local output) real pointer into on entry, this array contains the convert descriptor into standard form for easy access t is used to factor a reordering of the matrix into p l u see psgbtrf and psgbtrs for details. convert descriptor into standard form for easy access t a (local input/local output) real pointer into lld_a >=(2*bwl+2*bwu+1) (stored in desca). a (local input/local output) real pointer into th on entry, this array contains the local pieces of the a (local input/local output) real pointer into th on entry, this array contains the local pieces of the a (local input) real pointer into the local memor this array contains the local pieces of the factors l and u a (local input) real pointer into the local memor local pieces of the m-by-n distributed matrix whose a (local input/local output) real pointer into th on entry, this array contains the local pieces of the n-by-n a (local input/local output) real pointer into th on entry, this array contains the local pieces of the n-by-n a (local input/local output) real pointer into th on entry, the local pieces of the m-by-n distributed matrix a (local input/local output) real pointer into th on entry, the local pieces of the m-by-n distributed matrix a (local input/local output) real pointer into th ( lld_a, locc(ja+n-1) ). on entry, the m-by-n matrix a. a (local input/local output) real pointer into th on entry, the local pieces of the m-by-n distributed matrix a (local input/local output) real pointer into th on entry, the local pieces of the m-by-n distributed matrix a (local input/local output) real pointer into th on entry, the local pieces of the m-by-n distributed matrix a (local input/local output) real pointer into th on entry, the local pieces of the m-by-n distributed matrix a (local input/local output) real pointer into th on entry, the local pieces of the m-by-n distributed matrix a (local input) real pointer into the loca this array contains the local pieces of the distributed a (local input/local output) real pointer into th on entry, the local pieces of the m-by-n distributed matrix a (local input/local output) real pointer into th on entry, the local pieces of the m-by-n distributed matrix a (local input/local output) real pointer into th on entry, the local pieces of the n-by-n distributed matrix a (local input/local output) real pointer into (lld_a,locc(ja+n-1)). on entry, the n-by-n matrix a (local input/local output) real pointer into th on entry, this array contains the local pieces of the m-by-n a (local input/local output) real pointer into th on entry, this array contains the local pieces of the m-by-n a (local input/local output) real pointer into th on entry, the local pieces of the l and u obtained by the a (local input) real pointer into the loca on entry, this array contains the local pieces of the factors a (local input/local output) real pointer into th on entry, the local pieces of the n-by-m distributed matrix a (local input/local output) real pointer into th on entry, the local pieces of the m-by-n distributed matrix a (local input/local output) real pointer into th on entry, this array contains the local pieces of the v (local workspace) real pointer into the loca the final return, v = a*w, where est = norm(v)/norm(w) a (local input) real pointer into the local memor contains the local pieces of the distributed matrix sub( a ) pslacp3 is an auxiliary routine that copies from a global parallel array into a local replicated array or vise versa. notice tha more. the receiving node can be specified precisely, or all nodes a (local input) real pointer into the local memor contains the local pieces of the distributed matrix sub( a ) pslaed2 sorts the two sets of eigenvalues together into a singl there are two ways in which deflation can occur: when two or more on exit, d contains the trailing (n-k) updated eigenvalues (those which were deflated) sorted into increasing order drow (global input) integer column application to h. here we do something a little more clever. we break each transformation down into 1.) the minimum amount of work it takes to determine a (local input/local output) real pointer into locc(ja+n-k)). on entry, this array contains the the local a (local output) complex*16 pointer into th on output, a is replicated across all processes in a (local input) real pointer into the local memor local pieces of the distributed matrix sub( a ). ii, jj : local indices into array icurcol : process column containing diagonal block a (local input/local output) real pointer into th on entry, this array contains the local pieces of the a (local input/local output) real pointer into th on entry, this local array contains the local pieces of the a (local input/local output) real pointer into th containing on entry the m-by-n matrix sub( a ). on exit, a (input/output) real pointer into the loca on entry, the local pieces of the distributed symmetric v (local input) real pointer into the local memor storev = 'c', ( lld_v, locc(jv+m-1)) if storev = 'r' and x (local input/local output) real, pointer into th contains the local pieces of the distributed vector sub( x ). v (input/output) real pointer into the local memor if storev = 'c', and (locr(iv+k-1),locc(jv+n-1)) if v (local input) real pointer into the local memor (lld_v, locc(jv+n-1)) if side = 'r'. it contains the local v (input/output) real pointer into the local memor the distributed matrix v contains the householder vectors. a (local input/local output) real pointer into th this array contains the local pieces of the distributed a (local output) real pointer into the local memor contains the local pieces of the distributed matrix sub( a ) a (local output) real pointer into the local memor contains the local pieces of the distributed matrix sub( a ) q (local input) real pointer into the local memor contains the local pieces of the distributed matrix sub( a ) a (local input/local output) real pointer into th on entry, this array contains the local pieces of the distri- a (local input) real pointer into the local memor contains the local pieces of the distributed matrix the trace a (local input/local output) real pointer into th on entry, this array contains the local pieces of the a (local input/local output) real pointer into th on entry, the local pieces of the m-by-n distributed matrix a (local input/local output) real pointer into th on entry, the local pieces of the triangular factor l or u. a (local input/local output) real pointer into th on entry, the local pieces of the triangular factor l or u. pslawil gets the transform given by h44,h33, & h43h34 into a (local input/local output) real pointer into th on entry, the j-th column must contain the vector which a (local input/local output) real pointer into th on entry, the j-th column must contain the vector which a (local input/local output) real pointer into th on entry, the i-th row must contain the vector which defines a (local input/local output) real pointer into th on entry, the i-th row must contain the vector which defines a (local input/local output) real pointer into th on entry, the j-th column must contain the vector which a (local input/local output) real pointer into th on entry, the j-th column must contain the vector which a (local input/local output) real pointer into th on entry, the i-th row must contain the vector which defines a (local input/local output) real pointer into th on entry, the i-th row must contain the vector which defines a (local input) real pointer into the local memor j-th column must contain the vector which defines the elemen- a (local input) real pointer into the local memor j-th column must contain the vector which defines the elemen- a (local input) real pointer into the local memor vect='q', and (lld_a,locc(ja+nq-1)) if vect = 'p'. nq = m a (local input) real pointer into the local memor and (lld_a,locc(ja+n-1)) if side = 'r'. the vectors which a (local input) real pointer into the local memor and (lld_a,locc(ja+n-1)) if side='r', where a (local input) real pointer into the local memor and (lld_a,locc(ja+n-1)) if side='r', where a (local input) real pointer into the local memor j-th column must contain the vector which defines the elemen- a (local input) real pointer into the local memor j-th column must contain the vector which defines the elemen- a (local input) real pointer into the local memor and (lld_a,locc(ja+n-1)) if side='r', where a (local input) real pointer into the local memor and (lld_a,locc(ja+n-1)) if side='r', where a (local input) real pointer into the local memor and (lld_a,locc(ja+n-1)) if side='r', where a (local input) real pointer into the local memor and (lld_a,locc(ja+n-1)) if side='r', where a (local input) real pointer into the local memor or (lld_a,locc(ja+n-1)) if side = 'r'. the vectors which cholesky factorization is used to factor a reordering of the matrix into l l' see pspbtrf and pspbtrs for details. convert descriptor into standard form for easy access t a (local input/local output) real pointer into lld_a >=(bw+1) (stored in desca). convert descriptor into standard form for easy access t a (local input) real pointer into the local memory t array contains the local pieces of the factors l or u from a (local input) real pointer into the local memory to a n-by-n symmetric positive definite distributed matrix a (local input) real pointer into the loca this array contains the local pieces of the n-by-n symmetric a (local input/local output) real pointer into th on entry, this array contains the local pieces of the a (local input/local output) real pointer into ( lld_a, locc(ja+n-1) ). a (local input/local output) real pointer into th on entry, this array contains the local pieces of the a (local input/local output) real pointer into th on entry, this array contains the local pieces of the a (local input/local output) real pointer into th on entry, the local pieces of the triangular factor u or l a (local input) real pointer into local memory t array contains the factors l or u from the cholesky facto- cholesky factorization is used to factor a reordering of the matrix into l l' see pspttrf and pspttrs for details. convert descriptor into standard form for easy access t b (local input/local output) real pointer into on entry, this array contains the convert descriptor into standard form for easy access t at each row/column j where e(j) is zero or small, the matrix t is considered to split into a block diagona to the number of blocks) the eigenvalue w(i) belongs to. isplit (global input) integer array, dimension (n) the splitting points, at which t breaks up into submatrices the second of rows/columns isplit(1)+1 through isplit(2), a (local input/local output) real pointer into th on entry, this array contains the local pieces of the a (local input/local output) real pointer into th on entry, this array contains the local pieces of the a (local input/local output) real pointer into th on entry, this array contains the local pieces of the a (local input/local output) real pointer into th on entry, this array contains the local pieces of the a (local input/local output) real pointer into th on entry, this array contains the local pieces of the a (local input/local output) real pointer into th on entry, this array contains the local pieces of the a (local input/local output) real pointer into th on entry, this array contains the local pieces of the a (local input/local output) real pointer into th on entry, this array contains the local pieces of the a (local input) real pointer into the local memor contains the local pieces of the triangular distributed a (local input) real pointer into the local memor array contains the local pieces of the original triangular a (local input/local output) real pointer into th this array contains the local pieces of the triangular matrix a (local input/local output) real pointer into th on entry, this array contains the local pieces of the a (local input) real pointer into the local memor contains the local pieces of the distributed triangular a (local input/local output) real pointer into th on entry, the local pieces of the m-by-n distributed matrix is used to factor a reordering of the matrix into l u see pzdbtrf and pzdbtrs for details. convert descriptor into standard form for easy access t a (local input/local output) complex*16 pointer into lld_a >=(bwl+bwu+1) (stored in desca). convert descriptor into standard form for easy access t is used to factor a reordering of the matrix into l u see pzdttrf and pzdttrs for details. convert descriptor into standard form for easy access t b (local input/local output) complex*16 pointer into on entry, this array contains the convert descriptor into standard form for easy access t is used to factor a reordering of the matrix into p l u see pzgbtrf and pzgbtrs for details. convert descriptor into standard form for easy access t a (local input/local output) complex*16 pointer into lld_a >=(2*bwl+2*bwu+1) (stored in desca). a (local input/local output) complex*16 pointer into th on entry, this array contains the local pieces of the a (local input/local output) complex*16 pointer into th on entry, this array contains the local pieces of the a (local input) complex*16 pointer into the local memor this array contains the local pieces of the factors l and u a (local input) complex*16 pointer into the local memor local pieces of the m-by-n distributed matrix whose a (local input/local output) complex*16 pointer into th on entry, this array contains the local pieces of the n-by-n a (local input/local output) complex*16 pointer into th on entry, this array contains the local pieces of the n-by-n a (local input/local output) complex*16 pointer into th on entry, the local pieces of the m-by-n distributed matrix a (local input/local output) complex*16 pointer into th on entry, the local pieces of the m-by-n distributed matrix a (local input/local output) complex*16 pointer into th ( lld_a, locc(ja+n-1) ). on entry, the m-by-n matrix a. a (local input/local output) complex*16 pointer into th on entry, the local pieces of the m-by-n distributed matrix a (local input/local output) complex*16 pointer into th on entry, the local pieces of the m-by-n distributed matrix a (local input/local output) complex*16 pointer into th on entry, the local pieces of the m-by-n distributed matrix a (local input/local output) complex*16 pointer into th on entry, the local pieces of the m-by-n distributed matrix a (local input/local output) complex*16 pointer into th on entry, the local pieces of the m-by-n distributed matrix a (local input) complex*16 pointer into the loca this array contains the local pieces of the distributed a (local input/local output) complex*16 pointer into th on entry, the local pieces of the m-by-n distributed matrix a (local input/local output) complex*16 pointer into th on entry, the local pieces of the m-by-n distributed matrix a (local input/local output) complex*16 pointer into th on entry, the local pieces of the n-by-n distributed matrix a (local input/local output) complex*16 pointer into (lld_a,locc(ja+n-1)). on entry, the n-by-n matrix a (local input/local output) complex*16 pointer into th on entry, this array contains the local pieces of the m-by-n a (local input/local output) complex*16 pointer into th on entry, this array contains the local pieces of the m-by-n a (local input/local output) complex*16 pointer into th on entry, the local pieces of the l and u obtained by the a (local input) complex*16 pointer into the loca on entry, this array contains the local pieces of the factors a (local input/local output) complex*16 pointer into th on entry, the local pieces of the n-by-m distributed matrix a (local input/local output) complex*16 pointer into th on entry, the local pieces of the m-by-n distributed matrix a (local input/local output) complex*16 pointer into th on entry, this array contains the local pieces of the a (local input/local output) complex*16 pointer into th on entry, this array contains the local pieces of the a (local input/local output) complex*16 pointer into th on entry, this array contains the local pieces of the a (local input/local output) complex*16 pointer into th on entry, this array contains the local pieces of the a (local input/local output) complex*16 pointer into th on entry, this array contains the local pieces of the a (local input/local output) complex*16 pointer into th on entry, this array contains the local pieces of the a (local input/local output) complex*16 pointer into th on entry, this array contains the local pieces of the a (local input/local output) complex*16 pointer into th on entry, this array contains the local pieces of the a (local input/local output) complex*16 pointer into th on entry, this array contains the local pieces of the x (local input/local output) complex*16 pointer into th on entry the vector to be conjugated v (local workspace) complex*16 pointer into the loca the final return, v = a*w, where est = norm(v)/norm(w) a (local input) complex*16 pointer into the local memor contains the local pieces of the distributed matrix sub( a ) pzlacp3 is an auxiliary routine that copies from a global parallel array into a local replicated array or vise versa. notice tha more. the receiving node can be specified precisely, or all nodes a (local input) complex*16 pointer into the local memor contains the local pieces of the distributed matrix sub( a ) column application to h. here we do something a little more clever. we break each transformation down into 1.) the minimum amount of work it takes to determine a (local input/local output) complex*16 pointer into locc(ja+n-k)). on entry, this array contains the the local a (local output) complex*16 pointer into th on output, a is replicated across all processes in a (local input) complex*16 pointer into the local memor local pieces of the distributed matrix sub( a ). ii, jj : local indices into array icurcol : process column containing diagonal block ii, jj : local indices into array icurcol : process column containing diagonal block a (local input/local output) complex*16 pointer into th on entry, this array contains the local pieces of the a (local input/local output) complex*16 pointer into th on entry, this local array contains the local pieces of the a (local input/local output) complex*16 pointer into th containing on entry the m-by-n matrix sub( a ). on exit, a (input/output) complex*16 pointer into the loca on entry, the local pieces of the distributed symmetric v (local input) complex*16 pointer into the local memor storev = 'c', ( lld_v, locc(jv+m-1)) if storev = 'r' and x (local input/local output) complex*16, pointer into th contains the local pieces of the distributed vector sub( x ). v (input/output) complex*16 pointer into the local memor if storev = 'c', and (locr(iv+k-1),locc(jv+n-1)) if v (local input) complex*16 pointer into the local memor (lld_v, locc(jv+n-1)) if side = 'r'. it contains the local v (input/output) complex*16 pointer into the local memor the distributed matrix v contains the householder vectors. a (local input/local output) complex*16 pointer into th this array contains the local pieces of the distributed a (local output) complex*16 pointer into the local memor contains the local pieces of the distributed matrix sub( a ) a (local output) complex*16 pointer into the local memor contains the local pieces of the distributed matrix sub( a ) a (local input/local output) complex*16 pointer into th on entry, this array contains the local pieces of the distri- a (local input) complex*16 pointer into the local memor contains the local pieces of the distributed matrix the trace a (local input/local output) complex*16 pointer into th on entry, this array contains the local pieces of the a (local input/local output) complex*16 pointer into th on entry, the local pieces of the m-by-n distributed matrix a (local input/local output) complex*16 pointer into th on entry, the local pieces of the triangular factor l or u. a (local input/local output) complex*16 pointer into th on entry, the local pieces of the triangular factor l or u. pzlawil gets the transform given by h44,h33, & h43h34 into cholesky factorization is used to factor a reordering of the matrix into l l' see pzpbtrf and pzpbtrs for details. convert descriptor into standard form for easy access t a (local input/local output) complex*16 pointer into lld_a >=(bw+1) (stored in desca). convert descriptor into standard form for easy access t a (local input) complex*16 pointer into the local memory t array contains the local pieces of the factors l or u from a (local input) complex*16 pointer into the local memory to a n-by-n hermitian positive definite distributed matrix a (local input) complex*16 pointer into the loca this array contains the local pieces of the n-by-n hermitian a (local input/local output) complex*16 pointer into th on entry, this array contains the local pieces of the a (local input/local output) complex*16 pointer into ( lld_a, locc(ja+n-1) ). a (local input/local output) complex*16 pointer into th on entry, this array contains the local pieces of the a (local input/local output) complex*16 pointer into th on entry, this array contains the local pieces of the a (local input/local output) complex*16 pointer into th on entry, the local pieces of the triangular factor u or l a (local input) complex*16 pointer into local memory t array contains the factors l or u from the cholesky facto- cholesky factorization is used to factor a reordering of the matrix into l l' see pzpttrf and pzpttrs for details. convert descriptor into standard form for easy access t b (local input/local output) complex*16 pointer into on entry, this array contains the convert descriptor into standard form for easy access t isplit (global input) integer array, dimension (n) the splitting points, at which t breaks up into submatrices the second of rows/columns isplit(1)+1 through isplit(2), a (local input) complex*16 pointer into the local memor contains the local pieces of the triangular distributed a (local input) complex*16 pointer into the local memor array contains the local pieces of the original triangular a (local input/local output) complex*16 pointer into th this array contains the local pieces of the triangular matrix a (local input/local output) complex*16 pointer into th on entry, this array contains the local pieces of the a (local input) complex*16 pointer into the local memor contains the local pieces of the distributed triangular a (local input/local output) complex*16 pointer into th on entry, the local pieces of the m-by-n distributed matrix a (local input/local output) complex*16 pointer into th on entry, the j-th column must contain the vector which a (local input/local output) complex*16 pointer into th on entry, the j-th column must contain the vector which a (local input/local output) complex*16 pointer into th on entry, the i-th row must contain the vector which defines a (local input/local output) complex*16 pointer into th on entry, the i-th row must contain the vector which defines a (local input/local output) complex*16 pointer into th on entry, the j-th column must contain the vector which a (local input/local output) complex*16 pointer into th on entry, the j-th column must contain the vector which a (local input/local output) complex*16 pointer into th on entry, the i-th row must contain the vector which defines a (local input/local output) complex*16 pointer into th on entry, the i-th row must contain the vector which defines a (local input) complex*16 pointer into the local memor j-th column must contain the vector which defines the elemen- a (local input) complex*16 pointer into the local memor j-th column must contain the vector which defines the elemen- a (local input) complex*16 pointer into the local memor vect='q', and (lld_a,locc(ja+nq-1)) if vect = 'p'. nq = m a (local input) complex*16 pointer into the local memor and (lld_a,locc(ja+n-1)) if side = 'r'. the vectors which a (local input) complex*16 pointer into the local memor and (lld_a,locc(ja+n-1)) if side='r', where a (local input) complex*16 pointer into the local memor and (lld_a,locc(ja+n-1)) if side='r', where a (local input) complex*16 pointer into the local memor j-th column must contain the vector which defines the elemen- a (local input) complex*16 pointer into the local memor j-th column must contain the vector which defines the elemen- a (local input) complex*16 pointer into the local memor and (lld_a,locc(ja+n-1)) if side='r', where a (local input) complex*16 pointer into the local memor and (lld_a,locc(ja+n-1)) if side='r', where a (local input) complex*16 pointer into the local memor and (lld_a,locc(ja+n-1)) if side='r', where a (local input) complex*16 pointer into the local memor and (lld_a,locc(ja+n-1)) if side='r', where a (local input) complex*16 pointer into the local memor or (lld_a,locc(ja+n-1)) if side = 'r'. the vectors which sort into decreasing orde specifies the "number" of the first reflector. this is used as an index into vecs if block is set sort into decreasing orde specifies the "number" of the first reflector. this is used as an index into vecs if block is set |
| Intrinsic Intrinsic .. Intrinsic functions . .. .. Intrinsic functions . .. executable statements .. .. .. Intrinsic functions . .. statement functions .. .. .. Intrinsic functions . .. executable statements .. .. .. Intrinsic functions . .. executable statements .. .. .. Intrinsic functions . .. executable statements .. .. .. Intrinsic functions . .. executable statements .. .. .. Intrinsic functions . .. executable statements .. .. .. Intrinsic functions . .. executable statements .. .. .. Intrinsic functions . .. executable statements .. .. .. Intrinsic functions . .. executable statements .. .. .. Intrinsic functions . .. .. .. Intrinsic functions . .. executable statements .. .. .. Intrinsic functions . .. executable statements .. .. .. Intrinsic functions . .. executable statements .. .. .. Intrinsic functions . .. executable statements .. .. .. Intrinsic functions . .. executable statements .. .. .. Intrinsic functions . .. executable statements .. .. .. Intrinsic functions . .. executable statements .. .. .. Intrinsic functions . .. executable statements .. .. .. Intrinsic functions . .. statement functions .. .. .. Intrinsic functions . .. executable statements .. .. .. Intrinsic functions . .. executable statements .. .. .. Intrinsic functions . .. executable statements .. .. .. Intrinsic functions . .. executable statements .. .. Intrinsic functions . .. .. Intrinsic functions . .. executable statements .. .. .. Intrinsic functions . .. executable statements .. .. .. Intrinsic functions . .. executable statements .. .. .. Intrinsic functions . .. executable statements .. .. .. Intrinsic functions . .. executable statements .. .. Intrinsic functions . .. Intrinsic functions . .. .. Intrinsic functions . .. executable statements .. .. .. Intrinsic functions . .. executable statements .. .. .. Intrinsic functions . .. executable statements .. .. .. Intrinsic functions . .. executable statements .. .. Intrinsic functions . .. .. Intrinsic functions . .. executable statements .. .. .. Intrinsic functions . .. executable statements .. .. .. Intrinsic functions . .. executable statements .. .. .. Intrinsic functions . .. executable statements .. .. .. Intrinsic functions . .. executable statements .. .. .. Intrinsic functions . .. executable statements .. .. Intrinsic functions . .. Intrinsic functions . .. .. Intrinsic functions . .. executable statements .. .. .. Intrinsic functions . .. executable statements .. .. .. Intrinsic functions . .. executable statements .. .. .. Intrinsic functions . .. executable statements .. .. .. Intrinsic functions . .. executable statements .. .. Intrinsic functions . .. Intrinsic functions . .. .. Intrinsic functions . .. executable statements .. .. .. Intrinsic functions . .. executable statements .. .. .. Intrinsic functions . .. executable statements .. .. .. Intrinsic functions . .. executable statements .. .. Intrinsic functions . .. .. Intrinsic functions . .. executable statements .. .. .. Intrinsic functions . .. executable statements .. .. .. Intrinsic functions . .. executable statements .. .. .. Intrinsic functions . .. executable statements .. .. .. Intrinsic functions . .. executable statements .. .. .. Intrinsic functions . .. executable statements .. .. Intrinsic functions . .. Intrinsic functions . .. .. Intrinsic functions . .. executable statements .. .. .. Intrinsic functions . .. executable statements .. .. .. Intrinsic functions . .. executable statements .. .. .. Intrinsic functions . .. executable statements .. .. .. Intrinsic functions . .. executable statements .. .. .. Intrinsic functions . .. .. .. Intrinsic functions . .. executable statements .. .. .. Intrinsic functions . .. executable statements .. .. .. Intrinsic functions . .. executable statements .. .. .. Intrinsic functions . .. executable statements .. .. .. Intrinsic functions . .. executable statements .. .. .. Intrinsic functions . .. executable statements .. .. .. Intrinsic functions . .. executable statements .. .. .. Intrinsic functions . .. executable statements .. .. .. Intrinsic functions . .. statement functions .. .. .. Intrinsic functions . .. executable statements .. .. .. Intrinsic functions . .. executable statements .. .. .. Intrinsic functions . .. executable statements .. .. .. Intrinsic functions . .. executable statements .. .. Intrinsic functions . .. .. Intrinsic functions . .. executable statements .. .. .. Intrinsic functions . .. executable statements .. .. .. Intrinsic functions . .. executable statements .. .. Intrinsic functions . .. .. Intrinsic functions . .. executable statements .. .. .. Intrinsic functions . .. statement functions .. |
| introduce introduce transformation matrix, z( k ), whose conjugate transpose is used to introduce zeros into the (m - k + 1)th row of sub( a ), is given i transformation matrix, z( k ), whose conjugate transpose is used to introduce zeros into the (m - k + 1)th row of sub( a ), is given i the factorization is obtained by householder's method. the kth transformation matrix, z( k ), which is used to introduce zeros int the factorization is obtained by householder's method. the kth transformation matrix, z( k ), which is used to introduce zeros int the factorization is obtained by householder's method. the kth transformation matrix, z( k ), which is used to introduce zeros int the factorization is obtained by householder's method. the kth transformation matrix, z( k ), which is used to introduce zeros int transformation matrix, z( k ), whose conjugate transpose is used to introduce zeros into the (m - k + 1)th row of sub( a ), is given i transformation matrix, z( k ), whose conjugate transpose is used to introduce zeros into the (m - k + 1)th row of sub( a ), is given i |
| INTVL INTVL pdlaebz contains the iteration loop which computes the eigenvalues contained in the input intervals [ INTVL(2*j-1), intvl(2*j) ] wher the count of eigenvalues of a symmetric tridiagonal matrix less than pdlaecv checks if the input intervals [ INTVL(2*i-1), intvl(2*i) ] pdlaecv modifies kf to be the index of the last converged interval, pslaebz contains the iteration loop which computes the eigenvalues contained in the input intervals [ INTVL(2*j-1), intvl(2*j) ] wher the count of eigenvalues of a symmetric tridiagonal matrix less than pslaecv checks if the input intervals [ INTVL(2*i-1), intvl(2*i) ] pslaecv modifies kf to be the index of the last converged interval, |
| INTVLCT INTVLCT INTVLCT (input/output) integer array, dimension (2*mmax is the count at the left endpoint of the j-th interval, i.e., INTVLCT (input/output) integer array, dimension (2*(kl-kf) is the count at the left endpoint of the j-th interval, i.e., INTVLCT (input/output) integer array, dimension (2*mmax is the count at the left endpoint of the j-th interval, i.e., INTVLCT (input/output) integer array, dimension (2*(kl-kf) is the count at the left endpoint of the j-th interval, i.e., |
| inv inv an estimate is obtained for norm(inv(a(ia:ia+n-1,ja:ja+n-1))), an rcond = 1 / ( norm( a(ia:ia+n-1,ja:ja+n-1) ) * the system: trans = 'n': diag(r)*a*diag(c) *inv(diag(c))*x = diag(r)* trans = 'c': (diag(r)*a*diag(c))**h *inv(diag(r))*x = diag(c)*b pcgetri computes the inverse of a distributed matrix using the l computes the inverse of sub( a ) = a(ia:ia+n-1,ja:ja+n-1) denoted factorization of sub( a ) and sub( b ) implicitly gives the qr factorization of inv( sub( b ) )* sub( a ) inv( sub( b ) )*sub( a )= z'*(inv(t)*r) factorization of sub( a ) and sub( b ) implicitly gives the rq factorization of sub( a )*inv( sub( b ) ) sub( a )*inv( sub( b ) ) = (r*inv(t))*z' if ibtype = 1, the problem is sub( a )*x = lambda*sub( b )*x, and sub( a ) is overwritten by inv(u**h)*sub( a )*inv(u) o if ibtype = 1, the problem is sub( a )*x = lambda*sub( b )*x, and sub( a ) is overwritten by inv(u**h)*sub( a )*inv(u) o if ibtype = 1 or 2, z**h*sub( b )*z = i; if ibtype = 3, z**h*inv( sub( b ) )*z = i or the lower triangle (if uplo='l') of sub( a ), including if ibtype = 1, the problem is sub( a )*x = lambda*sub( b )*x, and sub( a ) is overwritten by inv(u**h)*sub( a )*inv(u) o pchettrd uses five local arrays: work ( inv ) dimension ( np, anb+1): array work ( invt ) dimension ( nq, anb+1): transpose of the array v pclapiv applies either p (permutation matrix indicated by ipiv) or inv( p ) to a general m-by-n distributed matri pivoting. the pivot vector may be distributed across a process row pclapv2 applies either p (permutation matrix indicated by ipiv) or inv( p ) to a m-by-n distributed matrix sub( a ) denotin pivot vector should be aligned with the distributed matrix a. for an estimate is obtained for norm(inv(a(ia:ia+n-1,ja:ja+n-1))), an rcond = 1 / ( norm( a(ia:ia+n-1,ja:ja+n-1) ) * the system: diag(sr) * a * diag(sc) * inv(diag(sc)) * x = diag(sr) * scaling of the matrix a, but if equilibration is used, a is the norm of a(ia:ia+n-1,ja:ja+n-1) is computed and an estimate is obtained for norm(inv(a(ia:ia+n-1,ja:ja+n-1))), then the reciproca rcond = 1 / ( norm( a(ia:ia+n-1,ja:ja+n-1) ) * an estimate is obtained for norm(inv(a(ia:ia+n-1,ja:ja+n-1))), an rcond = 1 / ( norm( a(ia:ia+n-1,ja:ja+n-1) ) * the system: trans = 'n': diag(r)*a*diag(c) *inv(diag(c))*x = diag(r)* trans = 'c': (diag(r)*a*diag(c))**h *inv(diag(r))*x = diag(c)*b pdgetri computes the inverse of a distributed matrix using the l computes the inverse of sub( a ) = a(ia:ia+n-1,ja:ja+n-1) denoted factorization of sub( a ) and sub( b ) implicitly gives the qr factorization of inv( sub( b ) )* sub( a ) inv( sub( b ) )*sub( a )= z'*(inv(t)*r) factorization of sub( a ) and sub( b ) implicitly gives the rq factorization of sub( a )*inv( sub( b ) ) sub( a )*inv( sub( b ) ) = (r*inv(t))*z' pdlapiv applies either p (permutation matrix indicated by ipiv) or inv( p ) to a general m-by-n distributed matri pivoting. the pivot vector may be distributed across a process row pdlapv2 applies either p (permutation matrix indicated by ipiv) or inv( p ) to a m-by-n distributed matrix sub( a ) denotin pivot vector should be aligned with the distributed matrix a. for an estimate is obtained for norm(inv(a(ia:ia+n-1,ja:ja+n-1))), an rcond = 1 / ( norm( a(ia:ia+n-1,ja:ja+n-1) ) * the system: diag(sr) * a * diag(sc) * inv(diag(sc)) * x = diag(sr) * scaling of the matrix a, but if equilibration is used, a is if ibtype = 1, the problem is sub( a )*x = lambda*sub( b )*x, and sub( a ) is overwritten by inv(u**t)*sub( a )*inv(u) o if ibtype = 1, the problem is sub( a )*x = lambda*sub( b )*x, and sub( a ) is overwritten by inv(u**t)*sub( a )*inv(u) o if ibtype = 1 or 2, z**t*sub( b )*z = i; if ibtype = 3, z**t*inv( sub( b ) )*z = i or the lower triangle (if uplo='l') of sub( a ), including if ibtype = 1, the problem is sub( a )*x = lambda*sub( b )*x, and sub( a ) is overwritten by inv(u**h)*sub( a )*inv(u) o pdsyttrd uses five local arrays: work ( inv ) dimension ( np, anb+1): array work ( invt ) dimension ( nq, anb+1): transpose of the array v the norm of a(ia:ia+n-1,ja:ja+n-1) is computed and an estimate is obtained for norm(inv(a(ia:ia+n-1,ja:ja+n-1))), then the reciproca rcond = 1 / ( norm( a(ia:ia+n-1,ja:ja+n-1) ) * an estimate is obtained for norm(inv(a(ia:ia+n-1,ja:ja+n-1))), an rcond = 1 / ( norm( a(ia:ia+n-1,ja:ja+n-1) ) * the system: trans = 'n': diag(r)*a*diag(c) *inv(diag(c))*x = diag(r)* trans = 'c': (diag(r)*a*diag(c))**h *inv(diag(r))*x = diag(c)*b psgetri computes the inverse of a distributed matrix using the l computes the inverse of sub( a ) = a(ia:ia+n-1,ja:ja+n-1) denoted factorization of sub( a ) and sub( b ) implicitly gives the qr factorization of inv( sub( b ) )* sub( a ) inv( sub( b ) )*sub( a )= z'*(inv(t)*r) factorization of sub( a ) and sub( b ) implicitly gives the rq factorization of sub( a )*inv( sub( b ) ) sub( a )*inv( sub( b ) ) = (r*inv(t))*z' pslapiv applies either p (permutation matrix indicated by ipiv) or inv( p ) to a general m-by-n distributed matri pivoting. the pivot vector may be distributed across a process row pslapv2 applies either p (permutation matrix indicated by ipiv) or inv( p ) to a m-by-n distributed matrix sub( a ) denotin pivot vector should be aligned with the distributed matrix a. for an estimate is obtained for norm(inv(a(ia:ia+n-1,ja:ja+n-1))), an rcond = 1 / ( norm( a(ia:ia+n-1,ja:ja+n-1) ) * the system: diag(sr) * a * diag(sc) * inv(diag(sc)) * x = diag(sr) * scaling of the matrix a, but if equilibration is used, a is if ibtype = 1, the problem is sub( a )*x = lambda*sub( b )*x, and sub( a ) is overwritten by inv(u**t)*sub( a )*inv(u) o if ibtype = 1, the problem is sub( a )*x = lambda*sub( b )*x, and sub( a ) is overwritten by inv(u**t)*sub( a )*inv(u) o if ibtype = 1 or 2, z**t*sub( b )*z = i; if ibtype = 3, z**t*inv( sub( b ) )*z = i or the lower triangle (if uplo='l') of sub( a ), including if ibtype = 1, the problem is sub( a )*x = lambda*sub( b )*x, and sub( a ) is overwritten by inv(u**h)*sub( a )*inv(u) o pssyttrd uses five local arrays: work ( inv ) dimension ( np, anb+1): array work ( invt ) dimension ( nq, anb+1): transpose of the array v the norm of a(ia:ia+n-1,ja:ja+n-1) is computed and an estimate is obtained for norm(inv(a(ia:ia+n-1,ja:ja+n-1))), then the reciproca rcond = 1 / ( norm( a(ia:ia+n-1,ja:ja+n-1) ) * an estimate is obtained for norm(inv(a(ia:ia+n-1,ja:ja+n-1))), an rcond = 1 / ( norm( a(ia:ia+n-1,ja:ja+n-1) ) * the system: trans = 'n': diag(r)*a*diag(c) *inv(diag(c))*x = diag(r)* trans = 'c': (diag(r)*a*diag(c))**h *inv(diag(r))*x = diag(c)*b pzgetri computes the inverse of a distributed matrix using the l computes the inverse of sub( a ) = a(ia:ia+n-1,ja:ja+n-1) denoted factorization of sub( a ) and sub( b ) implicitly gives the qr factorization of inv( sub( b ) )* sub( a ) inv( sub( b ) )*sub( a )= z'*(inv(t)*r) factorization of sub( a ) and sub( b ) implicitly gives the rq factorization of sub( a )*inv( sub( b ) ) sub( a )*inv( sub( b ) ) = (r*inv(t))*z' if ibtype = 1, the problem is sub( a )*x = lambda*sub( b )*x, and sub( a ) is overwritten by inv(u**h)*sub( a )*inv(u) o if ibtype = 1, the problem is sub( a )*x = lambda*sub( b )*x, and sub( a ) is overwritten by inv(u**h)*sub( a )*inv(u) o if ibtype = 1 or 2, z**h*sub( b )*z = i; if ibtype = 3, z**h*inv( sub( b ) )*z = i or the lower triangle (if uplo='l') of sub( a ), including if ibtype = 1, the problem is sub( a )*x = lambda*sub( b )*x, and sub( a ) is overwritten by inv(u**h)*sub( a )*inv(u) o pzhettrd uses five local arrays: work ( inv ) dimension ( np, anb+1): array work ( invt ) dimension ( nq, anb+1): transpose of the array v pzlapiv applies either p (permutation matrix indicated by ipiv) or inv( p ) to a general m-by-n distributed matri pivoting. the pivot vector may be distributed across a process row pzlapv2 applies either p (permutation matrix indicated by ipiv) or inv( p ) to a m-by-n distributed matrix sub( a ) denotin pivot vector should be aligned with the distributed matrix a. for an estimate is obtained for norm(inv(a(ia:ia+n-1,ja:ja+n-1))), an rcond = 1 / ( norm( a(ia:ia+n-1,ja:ja+n-1) ) * the system: diag(sr) * a * diag(sc) * inv(diag(sc)) * x = diag(sr) * scaling of the matrix a, but if equilibration is used, a is the norm of a(ia:ia+n-1,ja:ja+n-1) is computed and an estimate is obtained for norm(inv(a(ia:ia+n-1,ja:ja+n-1))), then the reciproca rcond = 1 / ( norm( a(ia:ia+n-1,ja:ja+n-1) ) * |
| InvA InvA computes the inverse of sub( a ) = a(ia:ia+n-1,ja:ja+n-1) denoted InvA by solving the system inva*l = inv(u) for inva notes computes the inverse of sub( a ) = a(ia:ia+n-1,ja:ja+n-1) denoted InvA by solving the system inva*l = inv(u) for inva notes computes the inverse of sub( a ) = a(ia:ia+n-1,ja:ja+n-1) denoted InvA by solving the system inva*l = inv(u) for inva notes computes the inverse of sub( a ) = a(ia:ia+n-1,ja:ja+n-1) denoted InvA by solving the system inva*l = inv(u) for inva notes |
| invariant invariant invariants nq = nqm0 + lij - 1 invariants nq = nqm0 + lij - 1 invariants nq = nqm0 + lij - 1 invariants nq = nqm0 + lij - 1 |
| Invariants Invariants Invariants nq = nqm0 + lij - 1 Invariants nq = nqm0 + lij - 1 Invariants nq = nqm0 + lij - 1 Invariants nq = nqm0 + lij - 1 |
| inverse inverse pcgetri computes the inverse of a distributed matrix using the l computes the inverse of sub( a ) = a(ia:ia+n-1,ja:ja+n-1) denoted where inv( sub( b ) ) denotes the inverse of the matrix sub( b ) where inv( sub( b ) ) denotes the inverse of the matrix sub( b ) pcpotri computes the inverse of a complex hermitian positive definit cholesky factorization sub( a ) = u**h*u or l*l**h computed by pcstein computes the eigenvectors of a symmetric tridiagonal matrix in parallel, using inverse iteration. the eigenvectors foun orthogonalize vectors that are on different processes. the extent pctrti2 computes the inverse of a complex upper or lower triangula contained in one and only one process memory space (local operation). pctrtri computes the inverse of a upper or lower triangula pdgetri computes the inverse of a distributed matrix using the l computes the inverse of sub( a ) = a(ia:ia+n-1,ja:ja+n-1) denoted where inv( sub( b ) ) denotes the inverse of the matrix sub( b ) where inv( sub( b ) ) denotes the inverse of the matrix sub( b ) pdpotri computes the inverse of a real symmetric positive definit cholesky factorization sub( a ) = u**t*u or l*l**t computed by set to the underflow threshold dlamch('u'), not zero.
note : if eigenvectors are desired later by inverse iteratio
pdstein computes the eigenvectors of a symmetric tridiagonal matrix in parallel, using inverse iteration. the eigenvectors foun orthogonalize vectors that are on different processes. the extent pdtrti2 computes the inverse of a real upper or lower triangula contained in one and only one process memory space (local operation). pdtrtri computes the inverse of a upper or lower triangula psgetri computes the inverse of a distributed matrix using the l computes the inverse of sub( a ) = a(ia:ia+n-1,ja:ja+n-1) denoted where inv( sub( b ) ) denotes the inverse of the matrix sub( b ) where inv( sub( b ) ) denotes the inverse of the matrix sub( b ) pspotri computes the inverse of a real symmetric positive definit cholesky factorization sub( a ) = u**t*u or l*l**t computed by set to the underflow threshold slamch('u'), not zero.
note : if eigenvectors are desired later by inverse iteratio
psstein computes the eigenvectors of a symmetric tridiagonal matrix in parallel, using inverse iteration. the eigenvectors foun orthogonalize vectors that are on different processes. the extent pstrti2 computes the inverse of a real upper or lower triangula contained in one and only one process memory space (local operation). pstrtri computes the inverse of a upper or lower triangula pzgetri computes the inverse of a distributed matrix using the l computes the inverse of sub( a ) = a(ia:ia+n-1,ja:ja+n-1) denoted where inv( sub( b ) ) denotes the inverse of the matrix sub( b ) where inv( sub( b ) ) denotes the inverse of the matrix sub( b ) pzpotri computes the inverse of a complex hermitian positive definit cholesky factorization sub( a ) = u**h*u or l*l**h computed by pzstein computes the eigenvectors of a symmetric tridiagonal matrix in parallel, using inverse iteration. the eigenvectors foun orthogonalize vectors that are on different processes. the extent pztrti2 computes the inverse of a complex upper or lower triangula contained in one and only one process memory space (local operation). pztrtri computes the inverse of a upper or lower triangula |
| inverted inverted n-by-n upper triangular part of the matrix sub( a ) contains the upper triangular matrix to be inverted, and the strictl if uplo = 'l', the leading n-by-n lower triangular part of n-by-n upper triangular part of the matrix sub( a ) contains the upper triangular matrix to be inverted, and the strictl if uplo = 'l', the leading n-by-n lower triangular part of n-by-n upper triangular part of the matrix sub( a ) contains the upper triangular matrix to be inverted, and the strictl if uplo = 'l', the leading n-by-n lower triangular part of n-by-n upper triangular part of the matrix sub( a ) contains the upper triangular matrix to be inverted, and the strictl if uplo = 'l', the leading n-by-n lower triangular part of |
| inverts inverts pcgetri computes the inverse of a distributed matrix using the lu factorization computed by pcgetrf. this method inverts u and the inva by solving the system inva*l = inv(u) for inva. pdgetri computes the inverse of a distributed matrix using the lu factorization computed by pdgetrf. this method inverts u and the inva by solving the system inva*l = inv(u) for inva. psgetri computes the inverse of a distributed matrix using the lu factorization computed by psgetrf. this method inverts u and the inva by solving the system inva*l = inv(u) for inva. pzgetri computes the inverse of a distributed matrix using the lu factorization computed by pzgetrf. this method inverts u and the inva by solving the system inva*l = inv(u) for inva. |
| involved involved updating the current column of a is not (only the current processor column is involved) in the following overview of the steps performed, m in the updating the current column of a is not (only the current processor column is involved) in the following overview of the steps performed, m in the updating the current column of a is not (only the current processor column is involved) in the following overview of the steps performed, m in the updating the current column of a is not (only the current processor column is involved) in the following overview of the steps performed, m in the |
| involves involves trans (global input) character = 'n': the linear system involves sub( a ) then, the processes which receive the answer will be (note that if an operation involves more than one vector, the processes which re each vector): trans (global input) character = 'n': the linear system involves sub( a ) then, the processes which receive the answer will be (note that if an operation involves more than one vector, the processes which re each vector): then, the processes which receive the answer will be (note that if an operation involves more than one vector, the processes which re each vector): trans (global input) character = 'n': the linear system involves sub( a ) trans (global input) character = 'n': the linear system involves sub( a ) then, the processes which receive the answer will be (note that if an operation involves more than one vector, the processes which re each vector): |
| involving involving pcgels solves overdetermined or underdetermined complex linear systems involving an m-by-n matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1) sub( a ). it is assumed that sub( a ) has full rank. pdgels solves overdetermined or underdetermined real linear systems involving an m-by-n matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1) assumed that sub( a ) has full rank. psgels solves overdetermined or underdetermined real linear systems involving an m-by-n matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1) assumed that sub( a ) has full rank. pzgels solves overdetermined or underdetermined complex linear systems involving an m-by-n matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1) sub( a ). it is assumed that sub( a ) has full rank. |
| InVT InVT work ( inh ) dimension ( np, anb+1): array h work ( InVT ) dimension ( nq, anb+1): transpose of the array work ( invtt ) dimension ( nq, 1): transpose of the array vt work ( inh ) dimension ( np, anb+1): array h work ( InVT ) dimension ( nq, anb+1): transpose of the array work ( invtt ) dimension ( nq, 1): transpose of the array vt work ( inh ) dimension ( np, anb+1): array h work ( InVT ) dimension ( nq, anb+1): transpose of the array work ( invtt ) dimension ( nq, 1): transpose of the array vt work ( inh ) dimension ( np, anb+1): array h work ( InVT ) dimension ( nq, anb+1): transpose of the array work ( invtt ) dimension ( nq, 1): transpose of the array vt |
| InVTT InVTT work ( inht ) dimension ( nq, anb+1): transpose of the array h work ( InVTT ) dimension ( nq, 1): transpose of the array v arrays v and h are replicated across all processor columns. work ( inht ) dimension ( nq, anb+1): transpose of the array h work ( InVTT ) dimension ( nq, 1): transpose of the array v arrays v and h are replicated across all processor columns. work ( inht ) dimension ( nq, anb+1): transpose of the array h work ( InVTT ) dimension ( nq, 1): transpose of the array v arrays v and h are replicated across all processor columns. work ( inht ) dimension ( nq, anb+1): transpose of the array h work ( InVTT ) dimension ( nq, 1): transpose of the array v arrays v and h are replicated across all processor columns. |
| IOFF IOFF where nb = mb_a = nb_a, iroffa = mod( ia-1, nb ), icoffa = mod( ja-1, nb ), IOFF = mod( ia+ilo-2, nb ) ihip = numroc( ihi+iroffa, nb, myrow, iarow, nprow ), where nb = mb_a = nb_a, iroffa = mod( ia-1, nb ), icoffa = mod( ja-1, nb ), IOFF = mod( ia+ilo-2, nb ) ihip = numroc( ihi+iroffa, nb, myrow, iarow, nprow ), where nb = mb_a = nb_a, iroffa = mod( ia-1, nb ), icoffa = mod( ja-1, nb ), IOFF = mod( ia+ilo-2, nb ) ihip = numroc( ihi+iroffa, nb, myrow, iarow, nprow ), where nb = mb_a = nb_a, iroffa = mod( ia-1, nb ), icoffa = mod( ja-1, nb ), IOFF = mod( ia+ilo-2, nb ) ihip = numroc( ihi+iroffa, nb, myrow, iarow, nprow ), |
| IPIV IPIV IPIV (local output) integer array, dimension >= desca( nb ) users *should not* alter the contents between IPIV (local output) integer array, dimension >= desca( nb ) users *should not* alter the contents between IPIV (local output) integer array, dimension locc(ja+n-1) was the global k-th column of sub( a ). ipiv is tied to the IPIV (local input) integer array of dimension locr(m_af)+mb_af by pcgetrf. ipiv(i) -> the global row local row i IPIV (local output) integer array, dimension ( locr(m_a)+mb_a ipiv(i) -> the global row local row i was swapped with. equilibrated before it is factored. = 'f': on entry, af(iaf:iaf+n-1,jaf:jaf+n-1) and IPIV con if equed is not 'n', the matrix IPIV (local output) integer array, dimension ( locr(m_a)+mb_a ipiv(i) -> the global row local row i was swapped with. IPIV (local output) integer array, dimension ( locr(m_a)+mb_a ipiv(i) -> the global row local row i was swapped with. IPIV (local input) integer array, dimension locr(m_a)+mb_ global row index the local row i was swapped with. this IPIV (local input) integer array, dimension ( locr(m_a)+mb_a ipiv(i) -> the global row local row i was swapped with. pclapiv applies either p (permutation matrix indicated by IPIV sub( a ) = a(ia:ia+m-1,ja:ja+n-1), resulting in row or column pclapv2 applies either p (permutation matrix indicated by IPIV a(ia:ia+m-1,ja:ja+n-1), resulting in row or column pivoting. the k1 (global input) integer the first element of IPIV for which a row or column inter IPIV (local output) integer array, dimension >= desca( nb ) users *should not* alter the contents between IPIV (local output) integer array, dimension >= desca( nb ) users *should not* alter the contents between IPIV (local output) integer array, dimension locc(ja+n-1) was the global k-th column of sub( a ). ipiv is tied to the IPIV (local input) integer array of dimension locr(m_af)+mb_af by pdgetrf. ipiv(i) -> the global row local row i IPIV (local output) integer array, dimension ( locr(m_a)+mb_a ipiv(i) -> the global row local row i was swapped with. equilibrated before it is factored. = 'f': on entry, af(iaf:iaf+n-1,jaf:jaf+n-1) and IPIV con if equed is not 'n', the matrix IPIV (local output) integer array, dimension ( locr(m_a)+mb_a ipiv(i) -> the global row local row i was swapped with. IPIV (local output) integer array, dimension ( locr(m_a)+mb_a ipiv(i) -> the global row local row i was swapped with. IPIV (local input) integer array, dimension locr(m_a)+mb_ global row index the local row i was swapped with. this IPIV (local input) integer array, dimension ( locr(m_a)+mb_a ipiv(i) -> the global row local row i was swapped with. pdlapiv applies either p (permutation matrix indicated by IPIV sub( a ) = a(ia:ia+m-1,ja:ja+n-1), resulting in row or column pdlapv2 applies either p (permutation matrix indicated by IPIV a(ia:ia+m-1,ja:ja+n-1), resulting in row or column pivoting. the k1 (global input) integer the first element of IPIV for which a row or column inter IPIV (local output) integer array, dimension >= desca( nb ) users *should not* alter the contents between IPIV (local output) integer array, dimension >= desca( nb ) users *should not* alter the contents between IPIV (local output) integer array, dimension locc(ja+n-1) was the global k-th column of sub( a ). ipiv is tied to the IPIV (local input) integer array of dimension locr(m_af)+mb_af by psgetrf. ipiv(i) -> the global row local row i IPIV (local output) integer array, dimension ( locr(m_a)+mb_a ipiv(i) -> the global row local row i was swapped with. equilibrated before it is factored. = 'f': on entry, af(iaf:iaf+n-1,jaf:jaf+n-1) and IPIV con if equed is not 'n', the matrix IPIV (local output) integer array, dimension ( locr(m_a)+mb_a ipiv(i) -> the global row local row i was swapped with. IPIV (local output) integer array, dimension ( locr(m_a)+mb_a ipiv(i) -> the global row local row i was swapped with. IPIV (local input) integer array, dimension locr(m_a)+mb_ global row index the local row i was swapped with. this IPIV (local input) integer array, dimension ( locr(m_a)+mb_a ipiv(i) -> the global row local row i was swapped with. pslapiv applies either p (permutation matrix indicated by IPIV sub( a ) = a(ia:ia+m-1,ja:ja+n-1), resulting in row or column pslapv2 applies either p (permutation matrix indicated by IPIV a(ia:ia+m-1,ja:ja+n-1), resulting in row or column pivoting. the k1 (global input) integer the first element of IPIV for which a row or column inter IPIV (local output) integer array, dimension >= desca( nb ) users *should not* alter the contents between IPIV (local output) integer array, dimension >= desca( nb ) users *should not* alter the contents between IPIV (local output) integer array, dimension locc(ja+n-1) was the global k-th column of sub( a ). ipiv is tied to the IPIV (local input) integer array of dimension locr(m_af)+mb_af by pzgetrf. ipiv(i) -> the global row local row i IPIV (local output) integer array, dimension ( locr(m_a)+mb_a ipiv(i) -> the global row local row i was swapped with. equilibrated before it is factored. = 'f': on entry, af(iaf:iaf+n-1,jaf:jaf+n-1) and IPIV con if equed is not 'n', the matrix IPIV (local output) integer array, dimension ( locr(m_a)+mb_a ipiv(i) -> the global row local row i was swapped with. IPIV (local output) integer array, dimension ( locr(m_a)+mb_a ipiv(i) -> the global row local row i was swapped with. IPIV (local input) integer array, dimension locr(m_a)+mb_ global row index the local row i was swapped with. this IPIV (local input) integer array, dimension ( locr(m_a)+mb_a ipiv(i) -> the global row local row i was swapped with. pzlapiv applies either p (permutation matrix indicated by IPIV sub( a ) = a(ia:ia+m-1,ja:ja+n-1), resulting in row or column pzlapv2 applies either p (permutation matrix indicated by IPIV a(ia:ia+m-1,ja:ja+n-1), resulting in row or column pivoting. the k1 (global input) integer the first element of IPIV for which a row or column inter |
| IQCOL IQCOL np = numroc( n, mb_q, myrow, iqrow, nprow ) nq = numroc( n, nb_q, mycol, IQCOL, npcol iqcol = indxg2p( jq, mb_q, mycol, csrc_q, npcol ) proc (iqrow, IQCOL) receive the parts of z np = numroc( n, mb_q, myrow, iqrow, nprow ) nq = numroc( n, nb_q, mycol, IQCOL, npcol iqcol = indxg2p( jq, mb_q, mycol, csrc_q, npcol ) proc (iqrow, IQCOL) receive the parts of z |
| IQROW IQROW lwork = 6*n + 2*np*nq, with np = numroc( n, mb_q, myrow, IQROW, nprow iqrow = indxg2p( iq, nb_q, myrow, rsrc_q, nprow ) proc (IQROW, iqcol) receive the parts of z lwork = 6*n + 2*np*nq, with np = numroc( n, mb_q, myrow, IQROW, nprow iqrow = indxg2p( iq, nb_q, myrow, rsrc_q, nprow ) proc (IQROW, iqcol) receive the parts of z |
| IROFF IROFF IROFF = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFF = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFF = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFF = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFF = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFF = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFF = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFF = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFF = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFF = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFF = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFF = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFF = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFF = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFF = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFF = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFF = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFF = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFF = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFF = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFF = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFF = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFF = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFF = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFF = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFF = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFF = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFF = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFF = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFF = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFF = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFF = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFF = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFF = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFF = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFF = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFF = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFF = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFF = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFF = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFF = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFF = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFF = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFF = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), |
| IROFFA IROFFA where nb = mb_a = nb_a, IROFFA = mod( ia-1, nb iacol = indxg2p( ja, nb, mycol, csrc_a, npcol ), where nb = mb_a = nb_a, IROFFA = mod( ia-1, nb ), icoffa = mod( ja-1, nb ) iacol = indxg2p( ja, nb, mycol, csrc_a, npcol ), where nb = mb_a = nb_a, IROFFA = mod( ia-1, nb ) npa0 = numroc( ihi+iroffa, nb, myrow, iarow, nprow ), where nb = mb_a = nb_a, IROFFA = mod( ia-1, nb ) iarow = indxg2p( ia, nb, myrow, rsrc_a, nprow ), IROFFA = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFFA = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFFA = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), ( mb_a.eq.nb_a.eq.mb_z .and. IROFFA.eq.iroffz .and. iroffa.eq.0 .and where should be true: ( mb_a.eq.nb_a.eq.mb_z.eq.nb_z .and. IROFFA.eq.icoffa .and with iroffa = mod( ia-1, mb_a ) ( mb_a.eq.nb_a.eq.mb_z .and. IROFFA.eq.iroffz .and. iroffa.eq.0 .and where ties, namely the following expression should be true: ( mb_a.eq.nb_a .and. IROFFA.eq.icoffa .and. iroffa.eq.0 ) wit ties, namely the following expression should be true: ( mb_a.eq.nb_a .and. IROFFA.eq.icoffa ) wit ties, namely the following expression should be true: ( mb_a.eq.nb_a .and. IROFFA.eq.icoffa .and. iroffa.eq.0 ) wit IROFFA = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFFA = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFFA = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFFA = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFFA = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFFA = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFFA = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFFA = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFFA = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), if side = 'l', ( mb_a.eq.mb_c .and. IROFFA.eq.iroffc .and. iarow.eq.icrow ( mb_a.eq.nb_c .and. iroffa.eq.icoffc ) if side = 'l', ( mb_a.eq.mb_c .and. IROFFA.eq.iroffc .and. iarow.eq.icrow ( mb_a.eq.nb_c .and. iroffa.eq.icoffc ) IROFFA = mod( iaa-1, mb_a ), icoffa = mod( jaa-1, nb_a ) iacol = indxg2p( jaa, nb_a, mycol, csrc_a, npcol ), IROFFA = mod( iaa-1, mb_a ), icoffa = mod( jaa-1, nb_a ) npa0 = numroc( ni+iroffa, mb_a, myrow, iarow, nprow ), IROFFA = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ) mqa0 = numroc( m+icoffa, nb_a, mycol, iacol, npcol ), IROFFA = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ) npa0 = numroc( n+iroffa, mb_a, myrow, iarow, nprow ), IROFFA = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ) npa0 = numroc( n+iroffa, mb_a, myrow, iarow, nprow ), IROFFA = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ) mqa0 = numroc( m+icoffa, nb_a, mycol, iacol, npcol ), IROFFA = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ) mqa0 = numroc( m+icoffa, nb_a, mycol, iacol, npcol ), IROFFA = mod( iaa-1, mb_a ), icoffa = mod( jaa-1, nb_a ) npa0 = numroc( ni+iroffa, mb_a, myrow, iarow, nprow ), where nb = mb_a = nb_a, IROFFA = mod( ia-1, nb iacol = indxg2p( ja, nb, mycol, csrc_a, npcol ), where nb = mb_a = nb_a, IROFFA = mod( ia-1, nb ), icoffa = mod( ja-1, nb ) iacol = indxg2p( ja, nb, mycol, csrc_a, npcol ), where nb = mb_a = nb_a, IROFFA = mod( ia-1, nb ) npa0 = numroc( ihi+iroffa, nb, myrow, iarow, nprow ), where nb = mb_a = nb_a, IROFFA = mod( ia-1, nb ) iarow = indxg2p( ia, nb, myrow, rsrc_a, nprow ), IROFFA = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFFA = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFFA = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFFA = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFFA = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFFA = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFFA = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFFA = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFFA = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFFA = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFFA = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFFA = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), if side = 'l', ( mb_a.eq.mb_c .and. IROFFA.eq.iroffc .and. iarow.eq.icrow ( mb_a.eq.nb_c .and. iroffa.eq.icoffc ) if side = 'l', ( mb_a.eq.mb_c .and. IROFFA.eq.iroffc .and. iarow.eq.icrow ( mb_a.eq.nb_c .and. iroffa.eq.icoffc ) IROFFA = mod( iaa-1, mb_a ), icoffa = mod( jaa-1, nb_a ) iacol = indxg2p( jaa, nb_a, mycol, csrc_a, npcol ), IROFFA = mod( iaa-1, mb_a ), icoffa = mod( jaa-1, nb_a ) npa0 = numroc( ni+iroffa, mb_a, myrow, iarow, nprow ), IROFFA = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ) mqa0 = numroc( m+icoffa, nb_a, mycol, iacol, npcol ), IROFFA = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ) npa0 = numroc( n+iroffa, mb_a, myrow, iarow, nprow ), IROFFA = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ) npa0 = numroc( n+iroffa, mb_a, myrow, iarow, nprow ), IROFFA = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ) mqa0 = numroc( m+icoffa, nb_a, mycol, iacol, npcol ), IROFFA = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ) mqa0 = numroc( m+icoffa, nb_a, mycol, iacol, npcol ), IROFFA = mod( iaa-1, mb_a ), icoffa = mod( jaa-1, nb_a ) npa0 = numroc( ni+iroffa, mb_a, myrow, iarow, nprow ), ( mb_a.eq.nb_a.eq.mb_z .and. IROFFA.eq.iroffz .and. iroffa.eq.0 .and where should be true: ( mb_a.eq.nb_a.eq.mb_z.eq.nb_z .and. IROFFA.eq.icoffa .and with iroffa = mod( ia-1, mb_a ) ( mb_a.eq.nb_a.eq.mb_z .and. IROFFA.eq.iroffz .and. iroffa.eq.0 .and where ties, namely the following expression should be true: ( mb_a.eq.nb_a .and. IROFFA.eq.icoffa .and. iroffa.eq.0 ) wit ties, namely the following expression should be true: ( mb_a.eq.nb_a .and. IROFFA.eq.icoffa ) wit ties, namely the following expression should be true: ( mb_a.eq.nb_a .and. IROFFA.eq.icoffa .and. iroffa.eq.0 ) wit where nb = mb_a = nb_a, IROFFA = mod( ia-1, nb iacol = indxg2p( ja, nb, mycol, csrc_a, npcol ), where nb = mb_a = nb_a, IROFFA = mod( ia-1, nb ), icoffa = mod( ja-1, nb ) iacol = indxg2p( ja, nb, mycol, csrc_a, npcol ), where nb = mb_a = nb_a, IROFFA = mod( ia-1, nb ) npa0 = numroc( ihi+iroffa, nb, myrow, iarow, nprow ), where nb = mb_a = nb_a, IROFFA = mod( ia-1, nb ) iarow = indxg2p( ia, nb, myrow, rsrc_a, nprow ), IROFFA = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFFA = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFFA = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFFA = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFFA = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFFA = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFFA = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFFA = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFFA = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFFA = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFFA = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFFA = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), if side = 'l', ( mb_a.eq.mb_c .and. IROFFA.eq.iroffc .and. iarow.eq.icrow ( mb_a.eq.nb_c .and. iroffa.eq.icoffc ) if side = 'l', ( mb_a.eq.mb_c .and. IROFFA.eq.iroffc .and. iarow.eq.icrow ( mb_a.eq.nb_c .and. iroffa.eq.icoffc ) IROFFA = mod( iaa-1, mb_a ), icoffa = mod( jaa-1, nb_a ) iacol = indxg2p( jaa, nb_a, mycol, csrc_a, npcol ), IROFFA = mod( iaa-1, mb_a ), icoffa = mod( jaa-1, nb_a ) npa0 = numroc( ni+iroffa, mb_a, myrow, iarow, nprow ), IROFFA = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ) mqa0 = numroc( m+icoffa, nb_a, mycol, iacol, npcol ), IROFFA = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ) npa0 = numroc( n+iroffa, mb_a, myrow, iarow, nprow ), IROFFA = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ) npa0 = numroc( n+iroffa, mb_a, myrow, iarow, nprow ), IROFFA = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ) mqa0 = numroc( m+icoffa, nb_a, mycol, iacol, npcol ), IROFFA = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ) mqa0 = numroc( m+icoffa, nb_a, mycol, iacol, npcol ), IROFFA = mod( iaa-1, mb_a ), icoffa = mod( jaa-1, nb_a ) npa0 = numroc( ni+iroffa, mb_a, myrow, iarow, nprow ), ( mb_a.eq.nb_a.eq.mb_z .and. IROFFA.eq.iroffz .and. iroffa.eq.0 .and where should be true: ( mb_a.eq.nb_a.eq.mb_z.eq.nb_z .and. IROFFA.eq.icoffa .and with iroffa = mod( ia-1, mb_a ) ( mb_a.eq.nb_a.eq.mb_z .and. IROFFA.eq.iroffz .and. iroffa.eq.0 .and where ties, namely the following expression should be true: ( mb_a.eq.nb_a .and. IROFFA.eq.icoffa .and. iroffa.eq.0 ) wit ties, namely the following expression should be true: ( mb_a.eq.nb_a .and. IROFFA.eq.icoffa ) wit ties, namely the following expression should be true: ( mb_a.eq.nb_a .and. IROFFA.eq.icoffa .and. iroffa.eq.0 ) wit where nb = mb_a = nb_a, IROFFA = mod( ia-1, nb iacol = indxg2p( ja, nb, mycol, csrc_a, npcol ), where nb = mb_a = nb_a, IROFFA = mod( ia-1, nb ), icoffa = mod( ja-1, nb ) iacol = indxg2p( ja, nb, mycol, csrc_a, npcol ), where nb = mb_a = nb_a, IROFFA = mod( ia-1, nb ) npa0 = numroc( ihi+iroffa, nb, myrow, iarow, nprow ), where nb = mb_a = nb_a, IROFFA = mod( ia-1, nb ) iarow = indxg2p( ia, nb, myrow, rsrc_a, nprow ), IROFFA = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFFA = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFFA = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), ( mb_a.eq.nb_a.eq.mb_z .and. IROFFA.eq.iroffz .and. iroffa.eq.0 .and where should be true: ( mb_a.eq.nb_a.eq.mb_z.eq.nb_z .and. IROFFA.eq.icoffa .and with iroffa = mod( ia-1, mb_a ) ( mb_a.eq.nb_a.eq.mb_z .and. IROFFA.eq.iroffz .and. iroffa.eq.0 .and where ties, namely the following expression should be true: ( mb_a.eq.nb_a .and. IROFFA.eq.icoffa .and. iroffa.eq.0 ) wit ties, namely the following expression should be true: ( mb_a.eq.nb_a .and. IROFFA.eq.icoffa ) wit ties, namely the following expression should be true: ( mb_a.eq.nb_a .and. IROFFA.eq.icoffa .and. iroffa.eq.0 ) wit IROFFA = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFFA = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFFA = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFFA = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFFA = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFFA = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFFA = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFFA = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), IROFFA = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ) iacol = indxg2p( ja, nb_a, mycol, csrc_a, npcol ), if side = 'l', ( mb_a.eq.mb_c .and. IROFFA.eq.iroffc .and. iarow.eq.icrow ( mb_a.eq.nb_c .and. iroffa.eq.icoffc ) if side = 'l', ( mb_a.eq.mb_c .and. IROFFA.eq.iroffc .and. iarow.eq.icrow ( mb_a.eq.nb_c .and. iroffa.eq.icoffc ) IROFFA = mod( iaa-1, mb_a ), icoffa = mod( jaa-1, nb_a ) iacol = indxg2p( jaa, nb_a, mycol, csrc_a, npcol ), IROFFA = mod( iaa-1, mb_a ), icoffa = mod( jaa-1, nb_a ) npa0 = numroc( ni+iroffa, mb_a, myrow, iarow, nprow ), IROFFA = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ) mqa0 = numroc( m+icoffa, nb_a, mycol, iacol, npcol ), IROFFA = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ) npa0 = numroc( n+iroffa, mb_a, myrow, iarow, nprow ), IROFFA = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ) npa0 = numroc( n+iroffa, mb_a, myrow, iarow, nprow ), IROFFA = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ) mqa0 = numroc( m+icoffa, nb_a, mycol, iacol, npcol ), IROFFA = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ) mqa0 = numroc( m+icoffa, nb_a, mycol, iacol, npcol ), IROFFA = mod( iaa-1, mb_a ), icoffa = mod( jaa-1, nb_a ) npa0 = numroc( ni+iroffa, mb_a, myrow, iarow, nprow ), |
| IROFFB IROFFB lws = max( (mb_a*(mb_a-1))/2, ( npb0 + max( nqa0 + numroc( numroc( n+IROFFB, mb_a, 0, 0, nprow ) mb_a * mb_a IROFFB = mod( ib-1, mb_b ), icoffb = mod( jb-1, nb_b ) ibcol = indxg2p( jb, nb_b, mycol, csrc_b, npcol ), IROFFB = mod( ib-1, mb_b ), icoffb = mod( jb-1, nb_b ) ibcol = indxg2p( jb, nb_b, mycol, csrc_b, npcol ), lws = max( (mb_a*(mb_a-1))/2, ( npb0 + max( nqa0 + numroc( numroc( n+IROFFB, mb_a, 0, 0, nprow ) mb_a * mb_a IROFFB = mod( ib-1, mb_b ), icoffb = mod( jb-1, nb_b ) ibcol = indxg2p( jb, nb_b, mycol, csrc_b, npcol ), IROFFB = mod( ib-1, mb_b ), icoffb = mod( jb-1, nb_b ) ibcol = indxg2p( jb, nb_b, mycol, csrc_b, npcol ), lws = max( (mb_a*(mb_a-1))/2, ( npb0 + max( nqa0 + numroc( numroc( n+IROFFB, mb_a, 0, 0, nprow ) mb_a * mb_a IROFFB = mod( ib-1, mb_b ), icoffb = mod( jb-1, nb_b ) ibcol = indxg2p( jb, nb_b, mycol, csrc_b, npcol ), IROFFB = mod( ib-1, mb_b ), icoffb = mod( jb-1, nb_b ) ibcol = indxg2p( jb, nb_b, mycol, csrc_b, npcol ), lws = max( (mb_a*(mb_a-1))/2, ( npb0 + max( nqa0 + numroc( numroc( n+IROFFB, mb_a, 0, 0, nprow ) mb_a * mb_a IROFFB = mod( ib-1, mb_b ), icoffb = mod( jb-1, nb_b ) ibcol = indxg2p( jb, nb_b, mycol, csrc_b, npcol ), IROFFB = mod( ib-1, mb_b ), icoffb = mod( jb-1, nb_b ) ibcol = indxg2p( jb, nb_b, mycol, csrc_b, npcol ), |
| IROFFC IROFFC if side = 'l', lwork >= ( mpc0 + max( mqv0 + numroc( numroc( m+IROFFC nqc0 ) ) * k if side = 'l', lwork >= ( mpc0 + max( mqv0 + numroc( numroc( m+IROFFC nqc0 ) ) * k IROFFC = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), IROFFC = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), lwork >= max( (mb_a*(mb_a-1))/2, ( mpc0 + max( mqa0 + numroc( numroc( mi+IROFFC, mb_a, 0, 0, nprow ) mb_a * mb_a IROFFC = mod( icc-1, mb_c ), icoffc = mod( jcc-1, nb_c ) iccol = indxg2p( jcc, nb_c, mycol, csrc_c, npcol ), if side = 'l', lwork >= mpc0 + max( max( 1, nqc0 ), numroc( numroc( m+IROFFC,mb_a,0,0,nprow ),mb_a,0,0,lcmp ) ) lwork >= max( (mb_a*(mb_a-1))/2, ( mpc0 + max( mqa0 + numroc( numroc( m+IROFFC, mb_a, 0, 0, nprow ) mb_a * mb_a IROFFC = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), IROFFC = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), if side = 'l', lwork >= mpc0 + max( max( 1, nqc0 ), numroc( numroc( m+IROFFC,mb_a,0,0,nprow ),mb_a,0,0,lcmp ) ) if side = 'l', lwork >= mpc0 + max( max( 1, nqc0 ), numroc( numroc( m+IROFFC,mb_a,0,0,nprow ),mb_a,0,0,lcmp ) ) lwork >= max( (mb_a*(mb_a-1))/2, ( mpc0 + max( mqa0 + numroc( numroc( m+IROFFC, mb_a, 0, 0, nprow ) mb_a * mb_a lwork >= max( (mb_a*(mb_a-1))/2, ( mpc0 + max( mqa0 + numroc( numroc( m+IROFFC, mb_a, 0, 0, nprow ) mb_a * mb_a IROFFC = mod( icc-1, mb_c ), icoffc = mod( jcc-1, nb_c ) iccol = indxg2p( jcc, nb_c, mycol, csrc_c, npcol ), if side = 'l', lwork >= ( mpc0 + max( mqv0 + numroc( numroc( m+IROFFC nqc0 ) ) * k if side = 'l', lwork >= ( mpc0 + max( mqv0 + numroc( numroc( m+IROFFC nqc0 ) ) * k IROFFC = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), IROFFC = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), lwork >= max( (mb_a*(mb_a-1))/2, ( mpc0 + max( mqa0 + numroc( numroc( mi+IROFFC, mb_a, 0, 0, nprow ) mb_a * mb_a IROFFC = mod( icc-1, mb_c ), icoffc = mod( jcc-1, nb_c ) iccol = indxg2p( jcc, nb_c, mycol, csrc_c, npcol ), if side = 'l', lwork >= mpc0 + max( max( 1, nqc0 ), numroc( numroc( m+IROFFC,mb_a,0,0,nprow ),mb_a,0,0,lcmp ) ) lwork >= max( (mb_a*(mb_a-1))/2, ( mpc0 + max( mqa0 + numroc( numroc( m+IROFFC, mb_a, 0, 0, nprow ) mb_a * mb_a IROFFC = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), IROFFC = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), if side = 'l', lwork >= mpc0 + max( max( 1, nqc0 ), numroc( numroc( m+IROFFC,mb_a,0,0,nprow ),mb_a,0,0,lcmp ) ) if side = 'l', lwork >= mpc0 + max( max( 1, nqc0 ), numroc( numroc( m+IROFFC,mb_a,0,0,nprow ),mb_a,0,0,lcmp ) ) lwork >= max( (mb_a*(mb_a-1))/2, ( mpc0 + max( mqa0 + numroc( numroc( m+IROFFC, mb_a, 0, 0, nprow ) mb_a * mb_a lwork >= max( (mb_a*(mb_a-1))/2, ( mpc0 + max( mqa0 + numroc( numroc( m+IROFFC, mb_a, 0, 0, nprow ) mb_a * mb_a IROFFC = mod( icc-1, mb_c ), icoffc = mod( jcc-1, nb_c ) iccol = indxg2p( jcc, nb_c, mycol, csrc_c, npcol ), if side = 'l', lwork >= ( mpc0 + max( mqv0 + numroc( numroc( m+IROFFC nqc0 ) ) * k if side = 'l', lwork >= ( mpc0 + max( mqv0 + numroc( numroc( m+IROFFC nqc0 ) ) * k IROFFC = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), IROFFC = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), lwork >= max( (mb_a*(mb_a-1))/2, ( mpc0 + max( mqa0 + numroc( numroc( mi+IROFFC, mb_a, 0, 0, nprow ) mb_a * mb_a IROFFC = mod( icc-1, mb_c ), icoffc = mod( jcc-1, nb_c ) iccol = indxg2p( jcc, nb_c, mycol, csrc_c, npcol ), if side = 'l', lwork >= mpc0 + max( max( 1, nqc0 ), numroc( numroc( m+IROFFC,mb_a,0,0,nprow ),mb_a,0,0,lcmp ) ) lwork >= max( (mb_a*(mb_a-1))/2, ( mpc0 + max( mqa0 + numroc( numroc( m+IROFFC, mb_a, 0, 0, nprow ) mb_a * mb_a IROFFC = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), IROFFC = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), if side = 'l', lwork >= mpc0 + max( max( 1, nqc0 ), numroc( numroc( m+IROFFC,mb_a,0,0,nprow ),mb_a,0,0,lcmp ) ) if side = 'l', lwork >= mpc0 + max( max( 1, nqc0 ), numroc( numroc( m+IROFFC,mb_a,0,0,nprow ),mb_a,0,0,lcmp ) ) lwork >= max( (mb_a*(mb_a-1))/2, ( mpc0 + max( mqa0 + numroc( numroc( m+IROFFC, mb_a, 0, 0, nprow ) mb_a * mb_a lwork >= max( (mb_a*(mb_a-1))/2, ( mpc0 + max( mqa0 + numroc( numroc( m+IROFFC, mb_a, 0, 0, nprow ) mb_a * mb_a IROFFC = mod( icc-1, mb_c ), icoffc = mod( jcc-1, nb_c ) iccol = indxg2p( jcc, nb_c, mycol, csrc_c, npcol ), if side = 'l', lwork >= ( mpc0 + max( mqv0 + numroc( numroc( m+IROFFC nqc0 ) ) * k if side = 'l', lwork >= ( mpc0 + max( mqv0 + numroc( numroc( m+IROFFC nqc0 ) ) * k IROFFC = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), IROFFC = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), lwork >= max( (mb_a*(mb_a-1))/2, ( mpc0 + max( mqa0 + numroc( numroc( mi+IROFFC, mb_a, 0, 0, nprow ) mb_a * mb_a IROFFC = mod( icc-1, mb_c ), icoffc = mod( jcc-1, nb_c ) iccol = indxg2p( jcc, nb_c, mycol, csrc_c, npcol ), if side = 'l', lwork >= mpc0 + max( max( 1, nqc0 ), numroc( numroc( m+IROFFC,mb_a,0,0,nprow ),mb_a,0,0,lcmp ) ) lwork >= max( (mb_a*(mb_a-1))/2, ( mpc0 + max( mqa0 + numroc( numroc( m+IROFFC, mb_a, 0, 0, nprow ) mb_a * mb_a IROFFC = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), IROFFC = mod( ic-1, mb_c ), icoffc = mod( jc-1, nb_c ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), if side = 'l', lwork >= mpc0 + max( max( 1, nqc0 ), numroc( numroc( m+IROFFC,mb_a,0,0,nprow ),mb_a,0,0,lcmp ) ) if side = 'l', lwork >= mpc0 + max( max( 1, nqc0 ), numroc( numroc( m+IROFFC,mb_a,0,0,nprow ),mb_a,0,0,lcmp ) ) lwork >= max( (mb_a*(mb_a-1))/2, ( mpc0 + max( mqa0 + numroc( numroc( m+IROFFC, mb_a, 0, 0, nprow ) mb_a * mb_a lwork >= max( (mb_a*(mb_a-1))/2, ( mpc0 + max( mqa0 + numroc( numroc( m+IROFFC, mb_a, 0, 0, nprow ) mb_a * mb_a IROFFC = mod( icc-1, mb_c ), icoffc = mod( jcc-1, nb_c ) iccol = indxg2p( jcc, nb_c, mycol, csrc_c, npcol ), |
| IROFFC2 IROFFC2 transpose row vector v (icoffv = IROFFC2 transpose row vector v (icoffv = IROFFC2 transpose row vector v (icoffv = IROFFC2 transpose row vector v (icoffv = IROFFC2 transpose row vector v (icoffv = IROFFC2 transpose row vector v (icoffv = IROFFC2 |
| IROFFV IROFFV IROFFV = mod( iv-1, mb_v ), icoffv = mod( jv-1, nb_v ) ivcol = indxg2p( jv, nb_v, mycol, csrc_v, npcol ), transpose column vector v (IROFFV = icoffc2 IROFFV = mod( iv-1, mb_v ), icoffv = mod( jv-1, nb_v ) ivcol = indxg2p( jv, nb_v, mycol, csrc_v, npcol ), transpose column vector v (IROFFV = icoffc2 IROFFV = mod( iv-1, mb_v ), icoffv = mod( jv-1, nb_v ) ivcol = indxg2p( jv, nb_v, mycol, csrc_v, npcol ), transpose column vector v (IROFFV = icoffc2 IROFFV = mod( iv-1, mb_v ), icoffv = mod( jv-1, nb_v ) ivcol = indxg2p( jv, nb_v, mycol, csrc_v, npcol ), IROFFV = mod( iv-1, mb_v ), icoffv = mod( jv-1, nb_v ) ivcol = indxg2p( jv, nb_v, mycol, csrc_v, npcol ), transpose column vector v (IROFFV = icoffc2 IROFFV = mod( iv-1, mb_v ), icoffv = mod( jv-1, nb_v ) ivcol = indxg2p( jv, nb_v, mycol, csrc_v, npcol ), IROFFV = mod( iv-1, mb_v ), icoffv = mod( jv-1, nb_v ) ivcol = indxg2p( jv, nb_v, mycol, csrc_v, npcol ), transpose column vector v (IROFFV = icoffc2 IROFFV = mod( iv-1, mb_v ), icoffv = mod( jv-1, nb_v ) ivcol = indxg2p( jv, nb_v, mycol, csrc_v, npcol ), transpose column vector v (IROFFV = icoffc2 |
| IROFFZ IROFFZ ( mb_a.eq.nb_a.eq.mb_z .and. iroffa.eq.IROFFZ .and. iroffa.eq.0 .and where ( mb_a.eq.nb_a.eq.mb_z.eq.nb_z .and. iroffa.eq.icoffa .and. iroffa.eq.0 .and.iroffa.eq.IROFFZ. and. iarow.eq.izrow and icoffa = mod( ja-1, nb_a ). ( mb_a.eq.nb_a.eq.mb_z .and. iroffa.eq.IROFFZ .and. iroffa.eq.0 .and where ( mb_a.eq.nb_a.eq.mb_z .and. iroffa.eq.IROFFZ .and. iroffa.eq.0 .and where ( mb_a.eq.nb_a.eq.mb_z.eq.nb_z .and. iroffa.eq.icoffa .and. iroffa.eq.0 .and.iroffa.eq.IROFFZ. and. iarow.eq.izrow and icoffa = mod( ja-1, nb_a ). ( mb_a.eq.nb_a.eq.mb_z .and. iroffa.eq.IROFFZ .and. iroffa.eq.0 .and where ( mb_a.eq.nb_a.eq.mb_z .and. iroffa.eq.IROFFZ .and. iroffa.eq.0 .and where ( mb_a.eq.nb_a.eq.mb_z.eq.nb_z .and. iroffa.eq.icoffa .and. iroffa.eq.0 .and.iroffa.eq.IROFFZ. and. iarow.eq.izrow and icoffa = mod( ja-1, nb_a ). ( mb_a.eq.nb_a.eq.mb_z .and. iroffa.eq.IROFFZ .and. iroffa.eq.0 .and where ( mb_a.eq.nb_a.eq.mb_z .and. iroffa.eq.IROFFZ .and. iroffa.eq.0 .and where ( mb_a.eq.nb_a.eq.mb_z.eq.nb_z .and. iroffa.eq.icoffa .and. iroffa.eq.0 .and.iroffa.eq.IROFFZ. and. iarow.eq.izrow and icoffa = mod( ja-1, nb_a ). ( mb_a.eq.nb_a.eq.mb_z .and. iroffa.eq.IROFFZ .and. iroffa.eq.0 .and where |
| IROW1 IROW1 IROW1 (local input/output) intege undefined on output. IROW1 (local input/output) intege undefined on output. (IROW1,icol1) is (i,j)-coordinates of h(istart,istart (IROW1,icol1) is (i,j)-coordinates of h(istart,istart (IROW1,icol1) is (i,j)-coordinates of h(istart,istart (IROW1,icol1) is (i,j)-coordinates of h(istart,istart IROW1 (local input/output) intege undefined on output. IROW1 (local input/output) intege undefined on output. |
| IROWX IROWX if( ( myrow.eq.itmp1x ) .and. ( mycol.eq.itmp2x ) ) $ x( IROWX ) = xjtm if( ( myrow.eq.itmp1x ) .and. ( mycol.eq.itmp2x ) ) $ x( IROWX ) = xjtm |
| irrespective irrespective ctxt entry in the descriptor may be *either* p-by-1 or 1-by-p irrespective of which one-dimensional descriptor typ this routine will interpret the grid properly either way. ctxt entry in the descriptor may be *either* p-by-1 or 1-by-p irrespective of which one-dimensional descriptor typ this routine will interpret the grid properly either way. ctxt entry in the descriptor may be *either* p-by-1 or 1-by-p irrespective of which one-dimensional descriptor typ this routine will interpret the grid properly either way. ctxt entry in the descriptor may be *either* p-by-1 or 1-by-p irrespective of which one-dimensional descriptor typ this routine will interpret the grid properly either way. ctxt entry in the descriptor may be *either* p-by-1 or 1-by-p irrespective of which one-dimensional descriptor typ this routine will interpret the grid properly either way. ctxt entry in the descriptor may be *either* p-by-1 or 1-by-p irrespective of which one-dimensional descriptor typ this routine will interpret the grid properly either way. ctxt entry in the descriptor may be *either* p-by-1 or 1-by-p irrespective of which one-dimensional descriptor typ this routine will interpret the grid properly either way. ctxt entry in the descriptor may be *either* p-by-1 or 1-by-p irrespective of which one-dimensional descriptor typ this routine will interpret the grid properly either way. ctxt entry in the descriptor may be *either* p-by-1 or 1-by-p irrespective of which one-dimensional descriptor typ this routine will interpret the grid properly either way. ctxt entry in the descriptor may be *either* p-by-1 or 1-by-p irrespective of which one-dimensional descriptor typ this routine will interpret the grid properly either way. ctxt entry in the descriptor may be *either* p-by-1 or 1-by-p irrespective of which one-dimensional descriptor typ this routine will interpret the grid properly either way. ctxt entry in the descriptor may be *either* p-by-1 or 1-by-p irrespective of which one-dimensional descriptor typ this routine will interpret the grid properly either way. ctxt entry in the descriptor may be *either* p-by-1 or 1-by-p irrespective of which one-dimensional descriptor typ this routine will interpret the grid properly either way. ctxt entry in the descriptor may be *either* p-by-1 or 1-by-p irrespective of which one-dimensional descriptor typ this routine will interpret the grid properly either way. ctxt entry in the descriptor may be *either* p-by-1 or 1-by-p irrespective of which one-dimensional descriptor typ this routine will interpret the grid properly either way. ctxt entry in the descriptor may be *either* p-by-1 or 1-by-p irrespective of which one-dimensional descriptor typ this routine will interpret the grid properly either way. ctxt entry in the descriptor may be *either* p-by-1 or 1-by-p irrespective of which one-dimensional descriptor typ this routine will interpret the grid properly either way. ctxt entry in the descriptor may be *either* p-by-1 or 1-by-p irrespective of which one-dimensional descriptor typ this routine will interpret the grid properly either way. ctxt entry in the descriptor may be *either* p-by-1 or 1-by-p irrespective of which one-dimensional descriptor typ this routine will interpret the grid properly either way. ctxt entry in the descriptor may be *either* p-by-1 or 1-by-p irrespective of which one-dimensional descriptor typ this routine will interpret the grid properly either way. ctxt entry in the descriptor may be *either* p-by-1 or 1-by-p irrespective of which one-dimensional descriptor typ this routine will interpret the grid properly either way. ctxt entry in the descriptor may be *either* p-by-1 or 1-by-p irrespective of which one-dimensional descriptor typ this routine will interpret the grid properly either way. ctxt entry in the descriptor may be *either* p-by-1 or 1-by-p irrespective of which one-dimensional descriptor typ this routine will interpret the grid properly either way. ctxt entry in the descriptor may be *either* p-by-1 or 1-by-p irrespective of which one-dimensional descriptor typ this routine will interpret the grid properly either way. ctxt entry in the descriptor may be *either* p-by-1 or 1-by-p irrespective of which one-dimensional descriptor typ this routine will interpret the grid properly either way. ctxt entry in the descriptor may be *either* p-by-1 or 1-by-p irrespective of which one-dimensional descriptor typ this routine will interpret the grid properly either way. ctxt entry in the descriptor may be *either* p-by-1 or 1-by-p irrespective of which one-dimensional descriptor typ this routine will interpret the grid properly either way. ctxt entry in the descriptor may be *either* p-by-1 or 1-by-p irrespective of which one-dimensional descriptor typ this routine will interpret the grid properly either way. ctxt entry in the descriptor may be *either* p-by-1 or 1-by-p irrespective of which one-dimensional descriptor typ this routine will interpret the grid properly either way. ctxt entry in the descriptor may be *either* p-by-1 or 1-by-p irrespective of which one-dimensional descriptor typ this routine will interpret the grid properly either way. ctxt entry in the descriptor may be *either* p-by-1 or 1-by-p irrespective of which one-dimensional descriptor typ this routine will interpret the grid properly either way. ctxt entry in the descriptor may be *either* p-by-1 or 1-by-p irrespective of which one-dimensional descriptor typ this routine will interpret the grid properly either way. ctxt entry in the descriptor may be *either* p-by-1 or 1-by-p irrespective of which one-dimensional descriptor typ this routine will interpret the grid properly either way. ctxt entry in the descriptor may be *either* p-by-1 or 1-by-p irrespective of which one-dimensional descriptor typ this routine will interpret the grid properly either way. ctxt entry in the descriptor may be *either* p-by-1 or 1-by-p irrespective of which one-dimensional descriptor typ this routine will interpret the grid properly either way. ctxt entry in the descriptor may be *either* p-by-1 or 1-by-p irrespective of which one-dimensional descriptor typ this routine will interpret the grid properly either way. ctxt entry in the descriptor may be *either* p-by-1 or 1-by-p irrespective of which one-dimensional descriptor typ this routine will interpret the grid properly either way. ctxt entry in the descriptor may be *either* p-by-1 or 1-by-p irrespective of which one-dimensional descriptor typ this routine will interpret the grid properly either way. ctxt entry in the descriptor may be *either* p-by-1 or 1-by-p irrespective of which one-dimensional descriptor typ this routine will interpret the grid properly either way. ctxt entry in the descriptor may be *either* p-by-1 or 1-by-p irrespective of which one-dimensional descriptor typ this routine will interpret the grid properly either way. |
| IRSC0 IRSC0 icurcol : process column containing diagonal block IRSC0 : pointer to part of work used to store the rowsums whil irsr0 : pointer to part of work used to store the rowsums after icurcol : process column containing diagonal block IRSC0 : pointer to part of work used to store the rowsums whil irsr0 : pointer to part of work used to store the rowsums after icurcol : process column containing diagonal block IRSC0 : pointer to part of work used to store the rowsums whil irsr0 : pointer to part of work used to store the rowsums after icurcol : process column containing diagonal block IRSC0 : pointer to part of work used to store the rowsums whil irsr0 : pointer to part of work used to store the rowsums after icurcol : process column containing diagonal block IRSC0 : pointer to part of work used to store the rowsums whil irsr0 : pointer to part of work used to store the rowsums after icurcol : process column containing diagonal block IRSC0 : pointer to part of work used to store the rowsums whil irsr0 : pointer to part of work used to store the rowsums after |
| IRSR0 IRSR0 they are stored along a process column IRSR0 : pointer to part of work used to store the rowsums afte they are stored along a process column IRSR0 : pointer to part of work used to store the rowsums afte they are stored along a process column IRSR0 : pointer to part of work used to store the rowsums afte they are stored along a process column IRSR0 : pointer to part of work used to store the rowsums afte they are stored along a process column IRSR0 : pointer to part of work used to store the rowsums afte they are stored along a process column IRSR0 : pointer to part of work used to store the rowsums afte |
| ISGN ISGN ISGN (local workspace) integer array, dimensio ISGN (local workspace) integer array, dimensio |
| ISPEC ISPEC tailored eigen-routines to choose problem-dependent parameters for the local environment. see ISPEC |
| ISPLIT ISPLIT ISPLIT (global input) integer array, dimension (n the first submatrix consists of rows/columns 1 to isplit(1), = 'b': ("by block") the eigenvalues will be grouped by
split-off block (see iblock, ISPLIT) an
the block.
ISPLIT (global input) integer array, dimension (n the first submatrix consists of rows/columns 1 to isplit(1), = 'b': ("by block") the eigenvalues will be grouped by
split-off block (see iblock, ISPLIT) an
the block.
ISPLIT (global input) integer array, dimension (n the first submatrix consists of rows/columns 1 to isplit(1), ISPLIT (global input) integer array, dimension (n the first submatrix consists of rows/columns 1 to isplit(1), |
| issued issued values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla info (local output) integer values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla info (global output) integer values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla rwork (local workspace/local output) real array, values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla info (local output) integer values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla info (global output) integer values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla info (local output) integer values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla info (global output) integer values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla info (global output) integer values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla info (local output) integer values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla info (global output) integer values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla rwork (local workspace/local output) real array, values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla info (local output) integer values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla info (global output) integer values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla rwork (local workspace/local output) real array, values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla info (local output) integer values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla info (global output) integer size for the work array. the required workspace is returned as the first element of work and no error message is issued values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla rwork (local workspace/local output) real array, values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla iwork (local workspace/local output) integer array, values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla info (global output) integer values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla info (global output) integer size for the work array. the required workspace is returned as the first element of work and no error message is issued entry of the corresponding work array, and no error message is issued by pxerbla rwork (local workspace/output) real array, values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla rwork (local workspace/output) real array, in the first entry of the correspondingwork array, and no error message is issued by pxerbla rwork (local workspace/output) real array, values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla info (global output) integer values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla info (local output) integer values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla info (global output) integer values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla rwork (local workspace/local output) real array, values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla rwork (local workspace/local output) real array, values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla rwork (local workspace/local output) real array, values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla iwork (local workspace/global output) integer array, values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla rwork (local workspace/local output) real array, values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla rwork (local workspace/local output) real array, values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla info (global output) integer values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla info (local output) integer values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla info (global output) integer values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla iwork (local workspace/local output) integer array, values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla info (local output) integer values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla info (global output) integer values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla info (local output) integer values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla info (global output) integer values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla info (global output) integer values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla info (local output) integer values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla info (global output) integer values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla info (local output) integer values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla info (global output) integer values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla iwork (local workspace/local output) integer array, values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla info (local output) integer values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla info (global output) integer size for the work array. the required workspace is returned as the first element of work and no error message is issued values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla iwork (local workspace/local output) integer array, values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla iwork (local workspace/local output) integer array, values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla info (global output) integer values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla info (global output) integer values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla iwork (local workspace/local output) integer array, values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla iwork (local workspace/local output) integer array, values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla iwork (local workspace/local output) integer array, values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla iwork (local workspace) integer array, dimension ( max( 4*n, 14 ) ) size for the work array. the required workspace is returned as the first element of work and no error message is issued values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla iwork (local workspace/global output) integer array, size for the work array. the required workspace is returned as the first element of work and no error message is issued size for the work array. the required workspace is returned as the first element of work and no error message is issued these values is returned in the first entry of the corresponding work arrays, and no error message is issued b each of these values is returned in the first entry of the corresponding work array, and no error message is issued b values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla info (global output) integer values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla info (local output) integer values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla info (global output) integer values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla iwork (local workspace/local output) integer array, values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla iwork (local workspace/local output) integer array, values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla info (global output) integer values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla info (local output) integer values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla info (global output) integer values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla iwork (local workspace/local output) integer array, values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla info (local output) integer values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla info (global output) integer values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla info (local output) integer values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla info (global output) integer values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla info (global output) integer values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla info (local output) integer values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla info (global output) integer values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla info (local output) integer values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla info (global output) integer values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla iwork (local workspace/local output) integer array, values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla info (local output) integer values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla info (global output) integer size for the work array. the required workspace is returned as the first element of work and no error message is issued values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla iwork (local workspace/local output) integer array, values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla iwork (local workspace/local output) integer array, values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla info (global output) integer values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla info (global output) integer values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla iwork (local workspace/local output) integer array, values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla iwork (local workspace/local output) integer array, values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla iwork (local workspace/local output) integer array, values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla iwork (local workspace) integer array, dimension ( max( 4*n, 14 ) ) size for the work array. the required workspace is returned as the first element of work and no error message is issued values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla iwork (local workspace/global output) integer array, size for the work array. the required workspace is returned as the first element of work and no error message is issued size for the work array. the required workspace is returned as the first element of work and no error message is issued these values is returned in the first entry of the corresponding work arrays, and no error message is issued b each of these values is returned in the first entry of the corresponding work array, and no error message is issued b values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla info (global output) integer values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla info (local output) integer values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla info (global output) integer values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla iwork (local workspace/local output) integer array, values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla iwork (local workspace/local output) integer array, values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla info (global output) integer values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla info (local output) integer values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla info (global output) integer values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla rwork (local workspace/local output) double precision array, values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla info (local output) integer values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla info (global output) integer values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla info (local output) integer values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla info (global output) integer values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla info (global output) integer values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla info (local output) integer values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla info (global output) integer values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla rwork (local workspace/local output) double precision array, values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla info (local output) integer values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla info (global output) integer values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla rwork (local workspace/local output) double precision array, values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla info (local output) integer values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla info (global output) integer size for the work array. the required workspace is returned as the first element of work and no error message is issued values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla rwork (local workspace/local output) double precision array, values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla iwork (local workspace/local output) integer array, values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla info (global output) integer values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla info (global output) integer size for the work array. the required workspace is returned as the first element of work and no error message is issued entry of the corresponding work array, and no error message is issued by pxerbla rwork (local workspace/output) double precision array, values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla rwork (local workspace/output) double precision array, in the first entry of the correspondingwork array, and no error message is issued by pxerbla rwork (local workspace/output) double precision array, values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla info (global output) integer values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla info (local output) integer values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla info (global output) integer values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla rwork (local workspace/local output) double precision array, values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla rwork (local workspace/local output) double precision array, values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla rwork (local workspace/local output) double precision array, values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla iwork (local workspace/global output) integer array, values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla rwork (local workspace/local output) double precision array, values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla rwork (local workspace/local output) double precision array, values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla info (global output) integer values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla |
| ISTART ISTART ISTART (global input) intege used as an index into vecs if block is set. ISTART (global input) intege used as an index into vecs if block is set. a.) work at the start of a border when mod(ISTART-1,hbl) = hbl- mod(istart-1,hbl) = hbl-1 a.) work at the start of a border when mod(ISTART-1,hbl) = hbl- mod(istart-1,hbl) = hbl-1 a.) work at the start of a border when mod(ISTART-1,hbl) = hbl- mod(istart-1,hbl) = hbl-1 a.) work at the start of a border when mod(ISTART-1,hbl) = hbl- mod(istart-1,hbl) = hbl-1 ISTART (global input) intege used as an index into vecs if block is set. ISTART (global input) intege used as an index into vecs if block is set. |
| ISTOP ISTOP ISTOP (global input) intege used as an index into vecs if block is set. ISTOP (global input) intege used as an index into vecs if block is set. ISTOP (global input) intege used as an index into vecs if block is set. ISTOP (global input) intege used as an index into vecs if block is set. |
| ISTR1 ISTR1 up and left and a buffer to send right. each of these buffers is actually stored in one buffer buf where buf(ISTR1+1) start the values are stored, if there are any values that a node up and left and a buffer to send right. each of these buffers is actually stored in one buffer buf where buf(ISTR1+1) start the values are stored, if there are any values that a node up and left and a buffer to send right. each of these buffers is actually stored in one buffer buf where buf(ISTR1+1) start the values are stored, if there are any values that a node up and left and a buffer to send right. each of these buffers is actually stored in one buffer buf where buf(ISTR1+1) start the values are stored, if there are any values that a node |
| ISTR2 ISTR2 is actually stored in one buffer buf where buf(istr1+1) starts the first buffer, buf(ISTR2+1) starts the second, etc.. afte needs, they will be sent and received. then the next major is actually stored in one buffer buf where buf(istr1+1) starts the first buffer, buf(ISTR2+1) starts the second, etc.. afte needs, they will be sent and received. then the next major is actually stored in one buffer buf where buf(istr1+1) starts the first buffer, buf(ISTR2+1) starts the second, etc.. afte needs, they will be sent and received. then the next major is actually stored in one buffer buf where buf(istr1+1) starts the first buffer, buf(ISTR2+1) starts the second, etc.. afte needs, they will be sent and received. then the next major |
| ISUB ISUB smalla(2,1,ki) = zero work(ISUB+k-2) = zer smalla(2,1,ki) = zero work(ISUB+k-2) = zer |
| iterate iterate check the infinity norm of the iterate specified eigenvalues. any vector which fails to converge is set to its current iterate after maxits iterations ( se on output, z is distributed across the p processes in block specified eigenvalues. any vector which fails to converge is set to its current iterate after maxits iterations ( se on output, z is distributed across the p processes in block specified eigenvalues. any vector which fails to converge is set to its current iterate after maxits iterations ( se on output, z is distributed across the p processes in block specified eigenvalues. any vector which fails to converge is set to its current iterate after maxits iterations ( se on output, z is distributed across the p processes in block check the infinity norm of the iterate |
| iteration iteration itn is the total number of qr iterations allowed qr iteration look for small superdiagonal element. update iteration count determine where the matrix splits and choose ql or qr iteration element is smaller. a few lines after they are set and do hold state from one loop iteration to the next the matrix a: pclaconsb looks for two consecutive small subdiagonal elements by seeing the effect of starting a double shift qr iteration subdiagonal negligible. itn is the total number of qr iterations allowed h43h34 (global input) complex these three values are for the double shift qr iteration pcstein computes the eigenvectors of a symmetric tridiagonal matrix in parallel, using inverse iteration. the eigenvectors foun orthogonalize vectors that are on different processes. the extent pdlaconsb looks for two consecutive small subdiagonal elements by seeing the effect of starting a double shift qr iteration subdiagonal negligible. pdlaebz contains the iteration loop which computes the eigenvalue j = 1,...,minp. it uses and computes the function n(w), which is itn is the total number of qr iterations allowed h43h34 (global input) double precision these three values are for the double shift qr iteration set to the underflow threshold dlamch('u'), not zero.
note : if eigenvectors are desired later by inverse iteration
pdstein computes the eigenvectors of a symmetric tridiagonal matrix in parallel, using inverse iteration. the eigenvectors foun orthogonalize vectors that are on different processes. the extent a few lines after they are set and do hold state from one loop iteration to the next the matrix a: pslaconsb looks for two consecutive small subdiagonal elements by seeing the effect of starting a double shift qr iteration subdiagonal negligible. pslaebz contains the iteration loop which computes the eigenvalue j = 1,...,minp. it uses and computes the function n(w), which is itn is the total number of qr iterations allowed h43h34 (global input) real these three values are for the double shift qr iteration set to the underflow threshold slamch('u'), not zero.
note : if eigenvectors are desired later by inverse iteration
psstein computes the eigenvectors of a symmetric tridiagonal matrix in parallel, using inverse iteration. the eigenvectors foun orthogonalize vectors that are on different processes. the extent a few lines after they are set and do hold state from one loop iteration to the next the matrix a: a few lines after they are set and do hold state from one loop iteration to the next the matrix a: pzlaconsb looks for two consecutive small subdiagonal elements by seeing the effect of starting a double shift qr iteration subdiagonal negligible. itn is the total number of qr iterations allowed h43h34 (global input) complex*16 these three values are for the double shift qr iteration pzstein computes the eigenvectors of a symmetric tridiagonal matrix in parallel, using inverse iteration. the eigenvectors foun orthogonalize vectors that are on different processes. the extent update iteration count determine where the matrix splits and choose ql or qr iteration element is smaller. itn is the total number of qr iterations allowed qr iteration look for small superdiagonal element. |
| iterations iterations itn is the total number of qr iterations allowed continue for additional iterations after norm reache > 0: if info = 1 through n, the i(th) eigenvalue did not converge in csteqr2 after a total of 30*n iterations by finding that eigenvalues were not identical across itn is the total number of qr iterations allowed specified eigenvalues. any vector which fails to converge is set to its current iterate after maxits iterations ( se on output, z is distributed across the p processes in block itn is the total number of qr iterations allowed specified eigenvalues. any vector which fails to converge is set to its current iterate after maxits iterations ( se on output, z is distributed across the p processes in block > 0: if info = 1 through n, the i(th) eigenvalue did not converge in dsteqr2 after a total of 30*n iterations by finding that eigenvalues were not identical across itn is the total number of qr iterations allowed specified eigenvalues. any vector which fails to converge is set to its current iterate after maxits iterations ( se on output, z is distributed across the p processes in block > 0: if info = 1 through n, the i(th) eigenvalue did not converge in ssteqr2 after a total of 30*n iterations by finding that eigenvalues were not identical across > 0: if info = 1 through n, the i(th) eigenvalue did not converge in zsteqr2 after a total of 30*n iterations by finding that eigenvalues were not identical across itn is the total number of qr iterations allowed specified eigenvalues. any vector which fails to converge is set to its current iterate after maxits iterations ( se on output, z is distributed across the p processes in block continue for additional iterations after norm reache itn is the total number of qr iterations allowed |
| Iterative Iterative itmax is the maximum number of steps of Iterative refinement notes 5. Iterative refinement is applied to improve the computed solutio for it. itmax is the maximum number of steps of Iterative refinement notes 5. Iterative refinement is applied to improve the computed solutio for it. the solution matrix x must be computed by pctrtrs or some other means before entering this routine. pctrrfs does not do Iterative itmax is the maximum number of steps of Iterative refinement notes 5. Iterative refinement is applied to improve the computed solutio for it. itmax is the maximum number of steps of Iterative refinement notes 5. Iterative refinement is applied to improve the computed solutio for it. the solution matrix x must be computed by pdtrtrs or some other means before entering this routine. pdtrrfs does not do Iterative itmax is the maximum number of steps of Iterative refinement notes 5. Iterative refinement is applied to improve the computed solutio for it. itmax is the maximum number of steps of Iterative refinement notes 5. Iterative refinement is applied to improve the computed solutio for it. the solution matrix x must be computed by pstrtrs or some other means before entering this routine. pstrrfs does not do Iterative itmax is the maximum number of steps of Iterative refinement notes 5. Iterative refinement is applied to improve the computed solutio for it. itmax is the maximum number of steps of Iterative refinement notes 5. Iterative refinement is applied to improve the computed solutio for it. the solution matrix x must be computed by pztrtrs or some other means before entering this routine. pztrrfs does not do Iterative |
| ITERMAX ITERMAX ITERMAX = node (iafirst,jafirst) owns a(1,1) ITERMAX = node (iafirst,jafirst) owns a(1,1) |
| ith ith pcgeqpf computes a qr factorization with column pivoting of pdgeqpf computes a qr factorization with column pivoting of where z = q'u, u is a vector of length n with ones in th this code makes very mild assumptions about floating point arithmetic. it will work on machines with a guard digit i which subtract like the cray x-mp, cray y-mp, cray c-90, or cray-2. psgeqpf computes a qr factorization with column pivoting of where z = q'u, u is a vector of length n with ones in th this code makes very mild assumptions about floating point arithmetic. it will work on machines with a guard digit i which subtract like the cray x-mp, cray y-mp, cray c-90, or cray-2. pzgeqpf computes a qr factorization with column pivoting of |
| ITMAX ITMAX ITMAX is the maximum number of steps of iterative refinement notes ITMAX is the maximum number of steps of iterative refinement notes ITMAX is the maximum number of steps of iterative refinement notes ITMAX is the maximum number of steps of iterative refinement notes ITMAX is the maximum number of steps of iterative refinement notes ITMAX is the maximum number of steps of iterative refinement notes ITMAX is the maximum number of steps of iterative refinement notes ITMAX is the maximum number of steps of iterative refinement notes |
| ITMP1 ITMP1 ITMP1 (local input) intege first column. for columns, this is the local first row. ITMP1 (local input) intege first column. for columns, this is the local first row. ITMP1 (local input) intege first column. for columns, this is the local first row. ITMP1 (local input) intege first column. for columns, this is the local first row. |
| ITMP1X ITMP1X xj = cabs1( x( j ) ) if( ( myrow.eq.ITMP1X ) .and. ( mycol.eq.itmp2x ) tjjs = a( j, j )*tscal xj = cabs1( x( j ) ) if( ( myrow.eq.ITMP1X ) .and. ( mycol.eq.itmp2x ) tjjs = a( j, j )*tscal |
| ITMP2 ITMP2 ITMP2 (local input) intege column. for columns, this is the local last row. ITMP2 (local input) intege column. for columns, this is the local last row. ITMP2 (local input) intege column. for columns, this is the local last row. ITMP2 (local input) intege column. for columns, this is the local last row. |
| ITMP2X ITMP2X xj = cabs1( x( j ) ) if( ( myrow.eq.itmp1x ) .and. ( mycol.eq.ITMP2X ) tjjs = a( j, j )*tscal xj = cabs1( x( j ) ) if( ( myrow.eq.itmp1x ) .and. ( mycol.eq.ITMP2X ) tjjs = a( j, j )*tscal |
| ITN ITN ITN is the total number of qr iterations allowed ITN is the total number of qr iterations allowed ITN is the total number of qr iterations allowed ITN is the total number of qr iterations allowed ITN is the total number of qr iterations allowed ITN is the total number of qr iterations allowed |
| its its ccombamax1 finds the element having maximum real part absolute value as well as its corresponding globl index arguments if remaining matrix is 2-by-2, use slae2 or slaev2 to compute its eigensystem determine where the matrix splits and choose ql or qr iteratio element is smaller. a small (max(bwl,bwu)* (p-1)) system is formed representing interaction of the larger blocks, and is stored (as are its algorithm is used. for a linear system, a parallel front solve which needs it to calculate fillin due to factorization of its main (odd) block a_i a small (max(bwl,bwu)* (p-1)) system is formed representing interaction of the larger blocks, and is stored (as are its algorithm is used. for a linear system, a parallel front solve the last processor does not participate in the solution of the reduced system, having sent its contribution already a small ((p-1)) system is formed representing interaction of the larger blocks, and is stored (as are its algorithm is used. for a linear system, a parallel front solve which needs it to calculate fillin due to factorization of its main (odd) block a_i a small ((p-1)) system is formed representing interaction of the larger blocks, and is stored (as are its algorithm is used. for a linear system, a parallel front solve the last processor does not participate in the solution of the reduced system, having sent its contribution already a small (max(bwl,bwu)* (p-1)) system is formed representing interaction of the larger blocks, and is stored (as are its algorithm is used. for a linear system, a parallel front solve a small (max(bwl,bwu)* (p-1)) system is formed representing interaction of the larger blocks, and is stored (as are its algorithm is used. for a linear system, a parallel front solve vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces m-by-n distributed matrix sub( a ) = a(ia:ia+n-1,ja:ja:ja+n-1) and reduce its condition number. r returns the row scale factors and each row and column of the distributed matrix b with elements vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces systems involving an m-by-n matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1), or its conjugate-transpose, using a qr or lq factorization o vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces where sigma is an m-by-n matrix which is zero except for its v is an n-by-n orthogonal matrix. the diagonal elements of sigma vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces in its present form, pcheev assumes a homogeneous system and make different processes. because of this, it is possible that a vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its correspondin vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces to 1. indeed, i suspect that ib should always be set to 1 or ignored with 1 used in its place pclamr1d has not been tested except withint the contect of vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces pclarfb applies a complex block reflector q or its conjugat denoting c(ic:ic+m-1,jc:jc+n-1), from the left or the right. vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces pclarzb applies a complex block reflector q or its conjugat denoting c(ic:ic+m-1,jc:jc+n-1), from the left or the right. vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces scale x so that its components are less than or equal t vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces a small (bw* (p-1)) system is formed representing interaction of the larger blocks, and is stored (as are its algorithm is used. for a linear system, a parallel front solve which needs it to calculate fillin due to factorization of its main (odd) block a_i a small (bw* (p-1)) system is formed representing interaction of the larger blocks, and is stored (as are its algorithm is used. for a linear system, a parallel front solve the last processor does not participate in the solution of the reduced system, having sent its contribution already vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces equilibrate a distributed hermitian positive definite matrix sub( a ) = a(ia:ia+n-1,ja:ja+n-1) and reduce its condition numbe factors, s(i) = 1/sqrt(a(i,i)), chosen so that the scaled distri- vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces a small ((p-1)) system is formed representing interaction of the larger blocks, and is stored (as are its algorithm is used. for a linear system, a parallel front solve which needs it to calculate fillin due to factorization of its main (odd) block a_i a small ((p-1)) system is formed representing interaction of the larger blocks, and is stored (as are its algorithm is used. for a linear system, a parallel front solve the last processor does not participate in the solution of the reduced system, having sent its contribution already vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces a small (max(bwl,bwu)* (p-1)) system is formed representing interaction of the larger blocks, and is stored (as are its algorithm is used. for a linear system, a parallel front solve which needs it to calculate fillin due to factorization of its main (odd) block a_i a small (max(bwl,bwu)* (p-1)) system is formed representing interaction of the larger blocks, and is stored (as are its algorithm is used. for a linear system, a parallel front solve the last processor does not participate in the solution of the reduced system, having sent its contribution already a small ((p-1)) system is formed representing interaction of the larger blocks, and is stored (as are its algorithm is used. for a linear system, a parallel front solve which needs it to calculate fillin due to factorization of its main (odd) block a_i a small ((p-1)) system is formed representing interaction of the larger blocks, and is stored (as are its algorithm is used. for a linear system, a parallel front solve the last processor does not participate in the solution of the reduced system, having sent its contribution already a small (max(bwl,bwu)* (p-1)) system is formed representing interaction of the larger blocks, and is stored (as are its algorithm is used. for a linear system, a parallel front solve a small (max(bwl,bwu)* (p-1)) system is formed representing interaction of the larger blocks, and is stored (as are its algorithm is used. for a linear system, a parallel front solve vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces m-by-n distributed matrix sub( a ) = a(ia:ia+n-1,ja:ja:ja+n-1) and reduce its condition number. r returns the row scale factors and each row and column of the distributed matrix b with elements vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces systems involving an m-by-n matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1), or its transpose, using a qr or lq factorization of sub( a ). it i vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces where sigma is an m-by-n matrix which is zero except for its v is an n-by-n orthogonal matrix. the diagonal elements of sigma vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces the count of eigenvalues of a symmetric tridiagonal matrix less than or equal to its argument w this is a scalapack internal subroutine and arguments are not the blacs context handle, indicating the global context of the operation on the matrix. the context itself is global k (output) integer arithmetic. it will work on machines with a guard digit in add/subtract, or on those binary machines without guard digits it could conceivably fail on hexadecimal or decimal machines vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces to 1. indeed, i suspect that ib should always be set to 1 or ignored with 1 used in its place pdlamr1d has not been tested except withint the contect of vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces entries are d(2),d(4),...,d(2*n-2). to avoid overflow, the matrix must be scaled so that its largest entry is no greate and for greatest accuracy, it should not be much smaller vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces pdlarfb applies a real block reflector q or its transpose q**t to from the left or the right. vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces pdlarzb applies a real block reflector q or its transpose q**t t from the left or the right. vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces a small (bw* (p-1)) system is formed representing interaction of the larger blocks, and is stored (as are its algorithm is used. for a linear system, a parallel front solve which needs it to calculate fillin due to factorization of its main (odd) block a_i a small (bw* (p-1)) system is formed representing interaction of the larger blocks, and is stored (as are its algorithm is used. for a linear system, a parallel front solve the last processor does not participate in the solution of the reduced system, having sent its contribution already vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces equilibrate a distributed symmetric positive definite matrix sub( a ) = a(ia:ia+n-1,ja:ja+n-1) and reduce its condition numbe factors, s(i) = 1/sqrt(a(i,i)), chosen so that the scaled distri- vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces a small ((p-1)) system is formed representing interaction of the larger blocks, and is stored (as are its algorithm is used. for a linear system, a parallel front solve which needs it to calculate fillin due to factorization of its main (odd) block a_i a small ((p-1)) system is formed representing interaction of the larger blocks, and is stored (as are its algorithm is used. for a linear system, a parallel front solve the last processor does not participate in the solution of the reduced system, having sent its contribution already vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces the n diagonal elements of the tridiagonal matrix t. to avoid overflow, the matrix must be scaled so that its larges in absolute value, and for greatest accuracy, it should not vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces in its present form, pdsyev assumes a homogeneous system and make the different processes. because of this, it is possible that a in its present form, pdsyevd assumes a homogeneous system and make the different processes. because of this, it is possible that a vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its correspondin vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces a small (max(bwl,bwu)* (p-1)) system is formed representing interaction of the larger blocks, and is stored (as are its algorithm is used. for a linear system, a parallel front solve which needs it to calculate fillin due to factorization of its main (odd) block a_i a small (max(bwl,bwu)* (p-1)) system is formed representing interaction of the larger blocks, and is stored (as are its algorithm is used. for a linear system, a parallel front solve the last processor does not participate in the solution of the reduced system, having sent its contribution already a small ((p-1)) system is formed representing interaction of the larger blocks, and is stored (as are its algorithm is used. for a linear system, a parallel front solve which needs it to calculate fillin due to factorization of its main (odd) block a_i a small ((p-1)) system is formed representing interaction of the larger blocks, and is stored (as are its algorithm is used. for a linear system, a parallel front solve the last processor does not participate in the solution of the reduced system, having sent its contribution already a small (max(bwl,bwu)* (p-1)) system is formed representing interaction of the larger blocks, and is stored (as are its algorithm is used. for a linear system, a parallel front solve a small (max(bwl,bwu)* (p-1)) system is formed representing interaction of the larger blocks, and is stored (as are its algorithm is used. for a linear system, a parallel front solve vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces m-by-n distributed matrix sub( a ) = a(ia:ia+n-1,ja:ja:ja+n-1) and reduce its condition number. r returns the row scale factors and each row and column of the distributed matrix b with elements vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces systems involving an m-by-n matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1), or its transpose, using a qr or lq factorization of sub( a ). it i vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces where sigma is an m-by-n matrix which is zero except for its v is an n-by-n orthogonal matrix. the diagonal elements of sigma vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces the count of eigenvalues of a symmetric tridiagonal matrix less than or equal to its argument w this is a scalapack internal subroutine and arguments are not the blacs context handle, indicating the global context of the operation on the matrix. the context itself is global k (output) integer arithmetic. it will work on machines with a guard digit in add/subtract, or on those binary machines without guard digits it could conceivably fail on hexadecimal or decimal machines vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces to 1. indeed, i suspect that ib should always be set to 1 or ignored with 1 used in its place pslamr1d has not been tested except withint the contect of vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces entries are d(2),d(4),...,d(2*n-2). to avoid overflow, the matrix must be scaled so that its largest entry is no greate and for greatest accuracy, it should not be much smaller vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces pslarfb applies a real block reflector q or its transpose q**t to from the left or the right. vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces pslarzb applies a real block reflector q or its transpose q**t t from the left or the right. vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces a small (bw* (p-1)) system is formed representing interaction of the larger blocks, and is stored (as are its algorithm is used. for a linear system, a parallel front solve which needs it to calculate fillin due to factorization of its main (odd) block a_i a small (bw* (p-1)) system is formed representing interaction of the larger blocks, and is stored (as are its algorithm is used. for a linear system, a parallel front solve the last processor does not participate in the solution of the reduced system, having sent its contribution already vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces equilibrate a distributed symmetric positive definite matrix sub( a ) = a(ia:ia+n-1,ja:ja+n-1) and reduce its condition numbe factors, s(i) = 1/sqrt(a(i,i)), chosen so that the scaled distri- vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces a small ((p-1)) system is formed representing interaction of the larger blocks, and is stored (as are its algorithm is used. for a linear system, a parallel front solve which needs it to calculate fillin due to factorization of its main (odd) block a_i a small ((p-1)) system is formed representing interaction of the larger blocks, and is stored (as are its algorithm is used. for a linear system, a parallel front solve the last processor does not participate in the solution of the reduced system, having sent its contribution already vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces the n diagonal elements of the tridiagonal matrix t. to avoid overflow, the matrix must be scaled so that its larges in absolute value, and for greatest accuracy, it should not vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces in its present form, pssyev assumes a homogeneous system and make the different processes. because of this, it is possible that a in its present form, pssyevd assumes a homogeneous system and make the different processes. because of this, it is possible that a vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its correspondin vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces a small (max(bwl,bwu)* (p-1)) system is formed representing interaction of the larger blocks, and is stored (as are its algorithm is used. for a linear system, a parallel front solve which needs it to calculate fillin due to factorization of its main (odd) block a_i a small (max(bwl,bwu)* (p-1)) system is formed representing interaction of the larger blocks, and is stored (as are its algorithm is used. for a linear system, a parallel front solve the last processor does not participate in the solution of the reduced system, having sent its contribution already vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces a small ((p-1)) system is formed representing interaction of the larger blocks, and is stored (as are its algorithm is used. for a linear system, a parallel front solve which needs it to calculate fillin due to factorization of its main (odd) block a_i a small ((p-1)) system is formed representing interaction of the larger blocks, and is stored (as are its algorithm is used. for a linear system, a parallel front solve the last processor does not participate in the solution of the reduced system, having sent its contribution already a small (max(bwl,bwu)* (p-1)) system is formed representing interaction of the larger blocks, and is stored (as are its algorithm is used. for a linear system, a parallel front solve a small (max(bwl,bwu)* (p-1)) system is formed representing interaction of the larger blocks, and is stored (as are its algorithm is used. for a linear system, a parallel front solve vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces m-by-n distributed matrix sub( a ) = a(ia:ia+n-1,ja:ja:ja+n-1) and reduce its condition number. r returns the row scale factors and each row and column of the distributed matrix b with elements vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces systems involving an m-by-n matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1), or its conjugate-transpose, using a qr or lq factorization o vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces where sigma is an m-by-n matrix which is zero except for its v is an n-by-n orthogonal matrix. the diagonal elements of sigma vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces in its present form, pzheev assumes a homogeneous system and make different processes. because of this, it is possible that a vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its correspondin vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces to 1. indeed, i suspect that ib should always be set to 1 or ignored with 1 used in its place pzlamr1d has not been tested except withint the contect of vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces pzlarfb applies a complex block reflector q or its conjugat denoting c(ic:ic+m-1,jc:jc+n-1), from the left or the right. vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces pzlarzb applies a complex block reflector q or its conjugat denoting c(ic:ic+m-1,jc:jc+n-1), from the left or the right. vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces scale x so that its components are less than or equal t vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces a small (bw* (p-1)) system is formed representing interaction of the larger blocks, and is stored (as are its algorithm is used. for a linear system, a parallel front solve which needs it to calculate fillin due to factorization of its main (odd) block a_i a small (bw* (p-1)) system is formed representing interaction of the larger blocks, and is stored (as are its algorithm is used. for a linear system, a parallel front solve the last processor does not participate in the solution of the reduced system, having sent its contribution already vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces equilibrate a distributed hermitian positive definite matrix sub( a ) = a(ia:ia+n-1,ja:ja+n-1) and reduce its condition numbe factors, s(i) = 1/sqrt(a(i,i)), chosen so that the scaled distri- vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces a small ((p-1)) system is formed representing interaction of the larger blocks, and is stored (as are its algorithm is used. for a linear system, a parallel front solve which needs it to calculate fillin due to factorization of its main (odd) block a_i a small ((p-1)) system is formed representing interaction of the larger blocks, and is stored (as are its algorithm is used. for a linear system, a parallel front solve the last processor does not participate in the solution of the reduced system, having sent its contribution already vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces vector. this vector stores the information required to establish the mapping between an object element and its corresponding proces determine where the matrix splits and choose ql or qr iteratio element is smaller. zcombamax1 finds the element having maximum real part absolute value as well as its corresponding globl index arguments if remaining matrix is 2-by-2, use dlae2 or dlaev2 to compute its eigensystem |
| itself itself the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. indicating the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs context handle, indicating the global context of the operation on the matrix. the context itself is global k (output) integer the blacs context handle, indicating the global context of the operation on the matrix. the context itself is global k (output) integer the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. indicating the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs context handle, indicating the global context of the operation on the matrix. the context itself is global k (output) integer the blacs context handle, indicating the global context of the operation on the matrix. the context itself is global k (output) integer the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. indicating the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. indicating the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs process grid a is distribu- ted over. the context itself is glo value) may vary. the blacs 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| IVCOL IVCOL ivrow = indxg2p( iv, mb_v, myrow, rsrc_v, nprow ), IVCOL = indxg2p( jv, nb_v, mycol, csrc_v, npcol ) npv0 = numroc( n+iroffv, mb_v, myrow, ivrow, nprow ), ivrow = indxg2p( iv, mb_v, myrow, rsrc_v, nprow ), IVCOL = indxg2p( jv, nb_v, mycol, csrc_v, npcol ) npv0 = numroc( n+iroffv, mb_v, myrow, ivrow, nprow ), ivrow = indxg2p( iv, mb_v, myrow, rsrc_v, nprow ), IVCOL = indxg2p( jv, nb_v, mycol, csrc_v, npcol ) npv0 = numroc( n+iroffv, mb_v, myrow, ivrow, nprow ), ivrow = indxg2p( iv, mb_v, myrow, rsrc_v, nprow ), IVCOL = indxg2p( jv, nb_v, mycol, csrc_v, npcol ) npv0 = numroc( n+iroffv, mb_v, myrow, ivrow, nprow ), ivrow = indxg2p( iv, mb_v, myrow, rsrc_v, nprow ), IVCOL = indxg2p( jv, nb_v, mycol, csrc_v, npcol ) npv0 = numroc( n+iroffv, mb_v, myrow, ivrow, nprow ), ivrow = indxg2p( iv, mb_v, myrow, rsrc_v, nprow ), IVCOL = indxg2p( jv, nb_v, mycol, csrc_v, npcol ) npv0 = numroc( n+iroffv, mb_v, myrow, ivrow, nprow ), ivrow = indxg2p( iv, mb_v, myrow, rsrc_v, nprow ), IVCOL = indxg2p( jv, nb_v, mycol, csrc_v, npcol ) npv0 = numroc( n+iroffv, mb_v, myrow, ivrow, nprow ), ivrow = indxg2p( iv, mb_v, myrow, rsrc_v, nprow ), IVCOL = indxg2p( jv, nb_v, mycol, csrc_v, npcol ) npv0 = numroc( n+iroffv, mb_v, myrow, ivrow, nprow ), |
| IVROW IVROW iroffv = mod( iv-1, mb_v ), icoffv = mod( jv-1, nb_v ), IVROW = indxg2p( iv, mb_v, myrow, rsrc_v, nprow ) mqv0 = numroc( m+icoffv, nb_v, mycol, ivcol, npcol ), iroffv = mod( iv-1, mb_v ), icoffv = mod( jv-1, nb_v ), IVROW = indxg2p( iv, mb_v, myrow, rsrc_v, nprow ) mqv0 = numroc( m+icoffv, nb_v, mycol, ivcol, npcol ), iroffv = mod( iv-1, mb_v ), icoffv = mod( jv-1, nb_v ), IVROW = indxg2p( iv, mb_v, myrow, rsrc_v, nprow ) mqv0 = numroc( m+icoffv, nb_v, mycol, ivcol, npcol ), iroffv = mod( iv-1, mb_v ), icoffv = mod( jv-1, nb_v ), IVROW = indxg2p( iv, mb_v, myrow, rsrc_v, nprow ) mqv0 = numroc( m+icoffv, nb_v, mycol, ivcol, npcol ), iroffv = mod( iv-1, mb_v ), icoffv = mod( jv-1, nb_v ), IVROW = indxg2p( iv, mb_v, myrow, rsrc_v, nprow ) mqv0 = numroc( m+icoffv, nb_v, mycol, ivcol, npcol ), iroffv = mod( iv-1, mb_v ), icoffv = mod( jv-1, nb_v ), IVROW = indxg2p( iv, mb_v, myrow, rsrc_v, nprow ) mqv0 = numroc( m+icoffv, nb_v, mycol, ivcol, npcol ), iroffv = mod( iv-1, mb_v ), icoffv = mod( jv-1, nb_v ), IVROW = indxg2p( iv, mb_v, myrow, rsrc_v, nprow ) mqv0 = numroc( m+icoffv, nb_v, mycol, ivcol, npcol ), iroffv = mod( iv-1, mb_v ), icoffv = mod( jv-1, nb_v ), IVROW = indxg2p( iv, mb_v, myrow, rsrc_v, nprow ) mqv0 = numroc( m+icoffv, nb_v, mycol, ivcol, npcol ), |
| IVT IVT IVT (global input) intege row of sub( vt ). IVT (global input) intege row of sub( vt ). IVT (global input) intege row of sub( vt ). IVT (global input) intege row of sub( vt ). |
| IWORK IWORK IWORK (local workspace/local output) integer array on exit, iwork(1) returns the minimal and optimal liwork. IWORK (local workspace/output) integer array, dimension (liwork IWORK (local workspace) integer arra required. IWORK (local workspace) integer arra required. IWORK (local workspace) integer array, dimension (ldw transposition, and the storage of the tranposed ipiv: IWORK (local workspace/global output) integer array on return, iwork(1) contains the amount of integer workspace IWORK (local workspace/local output) integer array on exit, iwork(1) returns the minimal and optimal liwork. IWORK (local workspace/local output) integer array on exit, iwork(1) returns the minimal and optimal liwork. IWORK (local workspace/local output) integer array on exit, iwork(1) returns the minimal and optimal liwork. IWORK (local workspace/local output) integer array on exit, iwork(1) returns the minimal and optimal liwork. IWORK (local workspace/output) integer array, dimension (liwork IWORK (local workspace/output) integer array IWORK (local workspace) integer array, dimension (ldw transposition, and the storage of the tranposed ipiv: IWORK (local workspace/local output) integer array IWORK (local workspace/local output) integer array on exit, iwork(1) returns the minimal and optimal liwork. IWORK (local workspace/local output) integer array on exit, iwork(1) returns the minimal and optimal liwork. IWORK (local workspace/local output) integer array on exit, iwork(1) returns the minimal and optimal liwork. IWORK (local workspace) integer array, dimension ( max( 4*n, 14 ) liwork (local input) integer IWORK (local workspace/output) integer array, dimension (liwork IWORK (local workspace/global output) integer array on return, iwork(1) contains the amount of integer workspace IWORK (local workspace/output) integer array, dimension (liwork IWORK (local workspace) integer arra required. IWORK (local workspace) integer arra required. IWORK (local workspace/local output) integer array on exit, iwork(1) returns the minimal and optimal liwork. IWORK (local workspace/local output) integer array on exit, iwork(1) returns the minimal and optimal liwork. IWORK (local workspace/local output) integer array on exit, iwork(1) returns the minimal and optimal liwork. IWORK (local workspace/local output) integer array on exit, iwork(1) returns the minimal and optimal liwork. IWORK (local workspace/local output) integer array on exit, iwork(1) returns the minimal and optimal liwork. IWORK (local workspace/local output) integer array on exit, iwork(1) returns the minimal and optimal liwork. IWORK (local workspace/output) integer array, dimension (liwork IWORK (local workspace/output) integer array IWORK (local workspace) integer array, dimension (ldw transposition, and the storage of the tranposed ipiv: IWORK (local workspace/local output) integer array IWORK (local workspace/local output) integer array on exit, iwork(1) returns the minimal and optimal liwork. IWORK (local workspace/local output) integer array on exit, iwork(1) returns the minimal and optimal liwork. IWORK (local workspace/local output) integer array on exit, iwork(1) returns the minimal and optimal liwork. IWORK (local workspace) integer array, dimension ( max( 4*n, 14 ) liwork (local input) integer IWORK (local workspace/output) integer array, dimension (liwork IWORK (local workspace/global output) integer array on return, iwork(1) contains the amount of integer workspace IWORK (local workspace/output) integer array, dimension (liwork IWORK (local workspace) integer arra required. IWORK (local workspace) integer arra required. IWORK (local workspace/local output) integer array on exit, iwork(1) returns the minimal and optimal liwork. IWORK (local workspace/local output) integer array on exit, iwork(1) returns the minimal and optimal liwork. IWORK (local workspace/local output) integer array on exit, iwork(1) returns the minimal and optimal liwork. IWORK (local workspace/output) integer array, dimension (liwork IWORK (local workspace) integer arra required. IWORK (local workspace) integer arra required. IWORK (local workspace) integer array, dimension (ldw transposition, and the storage of the tranposed ipiv: IWORK (local workspace/global output) integer array on return, iwork(1) contains the amount of integer workspace |
| IZROW IZROW ( mb_a.eq.nb_a.eq.mb_z .and. iroffa.eq.iroffz .and. iroffa.eq.0 .and. iarow.eq.IZROW iroffa = mod( ia-1, mb_a ) and icoffa = mod( ja-1, nb_a ). ( mb_a.eq.nb_a.eq.mb_z.eq.nb_z .and. iroffa.eq.icoffa .and. iroffa.eq.0 .and.iroffa.eq.iroffz. and. iarow.eq.IZROW and icoffa = mod( ja-1, nb_a ). ( mb_a.eq.nb_a.eq.mb_z .and. iroffa.eq.iroffz .and. iroffa.eq.0 .and. iarow.eq.IZROW iroffa = mod( ia-1, mb_a ) and icoffa = mod( ja-1, nb_a ). ( mb_a.eq.nb_a.eq.mb_z .and. iroffa.eq.iroffz .and. iroffa.eq.0 .and. iarow.eq.IZROW iroffa = mod( ia-1, mb_a ) and icoffa = mod( ja-1, nb_a ). ( mb_a.eq.nb_a.eq.mb_z.eq.nb_z .and. iroffa.eq.icoffa .and. iroffa.eq.0 .and.iroffa.eq.iroffz. and. iarow.eq.IZROW and icoffa = mod( ja-1, nb_a ). ( mb_a.eq.nb_a.eq.mb_z .and. iroffa.eq.iroffz .and. iroffa.eq.0 .and. iarow.eq.IZROW iroffa = mod( ia-1, mb_a ) and icoffa = mod( ja-1, nb_a ). ( mb_a.eq.nb_a.eq.mb_z .and. iroffa.eq.iroffz .and. iroffa.eq.0 .and. iarow.eq.IZROW iroffa = mod( ia-1, mb_a ) and icoffa = mod( ja-1, nb_a ). ( mb_a.eq.nb_a.eq.mb_z.eq.nb_z .and. iroffa.eq.icoffa .and. iroffa.eq.0 .and.iroffa.eq.iroffz. and. iarow.eq.IZROW and icoffa = mod( ja-1, nb_a ). ( mb_a.eq.nb_a.eq.mb_z .and. iroffa.eq.iroffz .and. iroffa.eq.0 .and. iarow.eq.IZROW iroffa = mod( ia-1, mb_a ) and icoffa = mod( ja-1, nb_a ). ( mb_a.eq.nb_a.eq.mb_z .and. iroffa.eq.iroffz .and. iroffa.eq.0 .and. iarow.eq.IZROW iroffa = mod( ia-1, mb_a ) and icoffa = mod( ja-1, nb_a ). ( mb_a.eq.nb_a.eq.mb_z.eq.nb_z .and. iroffa.eq.icoffa .and. iroffa.eq.0 .and.iroffa.eq.iroffz. and. iarow.eq.IZROW and icoffa = mod( ja-1, nb_a ). ( mb_a.eq.nb_a.eq.mb_z .and. iroffa.eq.iroffz .and. iroffa.eq.0 .and. iarow.eq.IZROW iroffa = mod( ia-1, mb_a ) and icoffa = mod( ja-1, nb_a ). |