Back| L- |
| L_i L_i
factor main partition a_i = L_i {u_i} in each processo
factor main partition a_i = L_i {u_i} in each processo
factor main partition p_i a_i = L_i u_i on each processo lbwl, lbwu: lower and upper bandwidth of local solver
factor main partition a_i = L_i {l_i}^c in each processo
factor main partition a_i = L_i {l_i}^c in each processo
factor main partition a_i = L_i {u_i} in each processo
factor main partition a_i = L_i {u_i} in each processo
factor main partition p_i a_i = L_i u_i on each processo lbwl, lbwu: lower and upper bandwidth of local solver
factor main partition a_i = L_i {l_i}^t in each processo
factor main partition a_i = L_i {l_i}^t in each processo
factor main partition a_i = L_i {u_i} in each processo
factor main partition a_i = L_i {u_i} in each processo
factor main partition p_i a_i = L_i u_i on each processo lbwl, lbwu: lower and upper bandwidth of local solver
factor main partition a_i = L_i {l_i}^t in each processo
factor main partition a_i = L_i {l_i}^t in each processo
factor main partition a_i = L_i {u_i} in each processo
factor main partition a_i = L_i {u_i} in each processo
factor main partition p_i a_i = L_i u_i on each processo lbwl, lbwu: lower and upper bandwidth of local solver
factor main partition a_i = L_i {l_i}^c in each processo
factor main partition a_i = L_i {l_i}^c in each processo
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| Lab Lab implemented for scalapack by: andrew j. cleary, livermore national Lab and university of tenn. based on code written by : peter arbenz, eth zurich, 1996. implemented for scalapack by: andrew j. cleary, livermore national Lab and university of tenn. based on code written by : peter arbenz, eth zurich, 1996. implemented for scalapack by: andrew j. cleary, livermore national Lab and university of tenn. based on code written by : peter arbenz, eth zurich, 1996. implemented for scalapack by: andrew j. cleary, livermore national Lab and university of tenn. based on code written by : peter arbenz, eth zurich, 1996. |
| label label 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; 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; |
| Labs Labs code developer: andrew j. cleary, university of tennessee. current address: lawrence livermore national Labs code developer: andrew j. cleary, university of tennessee. current address: lawrence livermore national Labs code developer: andrew j. cleary, university of tennessee. current address: lawrence livermore national Labs code developer: andrew j. cleary, university of tennessee. current address: lawrence livermore national Labs code developer: andrew j. cleary, university of tennessee. current address: lawrence livermore national Labs code developer: andrew j. cleary, university of tennessee. current address: lawrence livermore national Labs code developer: andrew j. cleary, university of tennessee. current address: lawrence livermore national Labs code developer: andrew j. cleary, university of tennessee. current address: lawrence livermore national Labs code developer: andrew j. cleary, university of tennessee. current address: lawrence livermore national Labs code developer: andrew j. cleary, university of tennessee. current address: lawrence livermore national Labs code developer: andrew j. cleary, university of tennessee. current address: lawrence livermore national Labs ===================================================================== code developer: andrew j. cleary, university of tennessee. current address: lawrence livermore national Labs code developer: andrew j. cleary, university of tennessee. current address: lawrence livermore national Labs ===================================================================== code developer: andrew j. cleary, university of tennessee. current address: lawrence livermore national Labs code developer: andrew j. cleary, university of tennessee. current address: lawrence livermore national Labs code developer: andrew j. cleary, university of tennessee. current address: lawrence livermore national Labs ===================================================================== code developer: andrew j. cleary, university of tennessee. current address: lawrence livermore national Labs code developer: andrew j. cleary, university of tennessee. current address: lawrence livermore national Labs ===================================================================== code developer: andrew j. cleary, university of tennessee. current address: lawrence livermore national Labs code developer: andrew j. cleary, university of tennessee. current address: lawrence livermore national Labs ===================================================================== code developer: andrew j. cleary, university of tennessee. current address: lawrence livermore national Labs code developer: andrew j. cleary, university of tennessee. current address: lawrence livermore national Labs ===================================================================== code developer: andrew j. cleary, university of tennessee. current address: lawrence livermore national Labs code developer: andrew j. cleary, university of tennessee. current address: lawrence livermore national Labs code developer: andrew j. cleary, university of tennessee. current address: lawrence livermore national Labs ===================================================================== code developer: andrew j. cleary, university of tennessee. current address: lawrence livermore national Labs code developer: andrew j. cleary, university of tennessee. current address: lawrence livermore national Labs ===================================================================== code developer: andrew j. cleary, university of tennessee. current address: lawrence livermore national Labs code developer: andrew j. cleary, university of tennessee. current address: lawrence livermore national Labs code developer: andrew j. cleary, university of tennessee. current address: lawrence livermore national Labs code developer: andrew j. cleary, university of tennessee. current address: lawrence livermore national Labs code developer: andrew j. cleary, university of tennessee. current address: lawrence livermore national Labs code developer: andrew j. cleary, university of tennessee. current address: lawrence livermore national Labs code developer: andrew j. cleary, university of tennessee. current address: lawrence livermore national Labs code developer: andrew j. cleary, university of tennessee. current address: lawrence livermore national Labs code developer: andrew j. cleary, university of tennessee. current address: lawrence livermore national Labs |
| lack lack iclustr(2*i-1) to iclustr(2*i), could not be reorthogonalized due to lack of workspace. hence th orthogonal. iclustr() is a zero terminated array. iclustr(2*i-1) to iclustr(2*i), could not be reorthogonalized due to lack of workspace. hence th orthogonal. iclustr() is a zero terminated array. eigenvalues indexed iclustr(2*i-1) to iclustr(2*i), i = 1 to info/(m+1), could not be orthogonalized due to lack o clusters may not be orthogonal. iclustr is a zero terminated eigenvalues indexed iclustr(2*i-1) to iclustr(2*i), i = 1 to info/(m+1), could not be orthogonalized due to lack o clusters may not be orthogonal. iclustr is a zero terminated iclustr(2*i-1) to iclustr(2*i), could not be reorthogonalized due to lack of workspace. hence th orthogonal. iclustr() is a zero terminated array. iclustr(2*i-1) to iclustr(2*i), could not be reorthogonalized due to lack of workspace. hence th orthogonal. iclustr() is a zero terminated array. eigenvalues indexed iclustr(2*i-1) to iclustr(2*i), i = 1 to info/(m+1), could not be orthogonalized due to lack o clusters may not be orthogonal. iclustr is a zero terminated iclustr(2*i-1) to iclustr(2*i), could not be reorthogonalized due to lack of workspace. hence th orthogonal. iclustr() is a zero terminated array. iclustr(2*i-1) to iclustr(2*i), could not be reorthogonalized due to lack of workspace. hence th orthogonal. iclustr() is a zero terminated array. iclustr(2*i-1) to iclustr(2*i), could not be reorthogonalized due to lack of workspace. hence th orthogonal. iclustr() is a zero terminated array. iclustr(2*i-1) to iclustr(2*i), could not be reorthogonalized due to lack of workspace. hence th orthogonal. iclustr() is a zero terminated array. eigenvalues indexed iclustr(2*i-1) to iclustr(2*i), i = 1 to info/(m+1), could not be orthogonalized due to lack o clusters may not be orthogonal. iclustr is a zero terminated |
| laf laf put minimum value of laf into af( 1 check worksize af (local output) complex array, dimension laf fillin is created during the factorization routine put minimum value of laf into af( 1 check worksize af (local output) complex array, dimension laf fillin is created during the factorization routine put minimum value of laf into af( 1 check worksize af (local output) complex array, dimension laf fillin is created during the factorization routine put minimum value of laf into af( 1 check worksize af (local output) complex array, dimension laf fillin is created during the factorization routine put minimum value of laf into af( 1 check worksize af (local output) complex array, dimension laf fillin is created during the factorization routine put minimum value of laf into af( 1 check worksize af (local output) double precision array, dimension laf fillin is created during the factorization routine put minimum value of laf into af( 1 check worksize af (local output) double precision array, dimension laf fillin is created during the factorization routine put minimum value of laf into af( 1 check worksize af (local output) double precision array, dimension laf fillin is created during the factorization routine put minimum value of laf into af( 1 check worksize af (local output) double precision array, dimension laf fillin is created during the factorization routine put minimum value of laf into af( 1 check worksize af (local output) double precision array, dimension laf fillin is created during the factorization routine put minimum value of laf into af( 1 check worksize af (local output) real array, dimension laf fillin is created during the factorization routine put minimum value of laf into af( 1 check worksize af (local output) real array, dimension laf fillin is created during the factorization routine put minimum value of laf into af( 1 check worksize af (local output) real array, dimension laf fillin is created during the factorization routine put minimum value of laf into af( 1 check worksize af (local output) real array, dimension laf fillin is created during the factorization routine put minimum value of laf into af( 1 check worksize af (local output) real array, dimension laf fillin is created during the factorization routine put minimum value of laf into af( 1 check worksize af (local output) complex*16 array, dimension laf fillin is created during the factorization routine put minimum value of laf into af( 1 check worksize af (local output) complex*16 array, dimension laf fillin is created during the factorization routine put minimum value of laf into af( 1 check worksize af (local output) complex*16 array, dimension laf fillin is created during the factorization routine put minimum value of laf into af( 1 check worksize af (local output) complex*16 array, dimension laf fillin is created during the factorization routine put minimum value of laf into af( 1 check worksize af (local output) complex*16 array, dimension laf fillin is created during the factorization routine |
| lambda lambda 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) of a complex generalized hermitian-definite eigenproblem, of the form sub( a )*x=(lambda)*sub( b )*x, sub( a )*sub( b )x=(lambda)*x, o here sub( a ) denoting a( ia:ia+n-1, ja:ja+n-1 ) is assumed to be 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**t) if ibtype = 1, the problem is sub( a )*x = lambda*sub( b )*x inv(l)*sub( a )*inv(l**t) of a real generalized sy-definite eigenproblem, of the form sub( a )*x=(lambda)*sub( b )*x, sub( a )*sub( b )x=(lambda)*x, o here sub( a ) denoting a( ia:ia+n-1, ja:ja+n-1 ) is assumed to be 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**t) if ibtype = 1, the problem is sub( a )*x = lambda*sub( b )*x inv(l)*sub( a )*inv(l**t) of a real generalized sy-definite eigenproblem, of the form sub( a )*x=(lambda)*sub( b )*x, sub( a )*sub( b )x=(lambda)*x, o here sub( a ) denoting a( ia:ia+n-1, ja:ja+n-1 ) is assumed to be 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) if ibtype = 1, the problem is sub( a )*x = lambda*sub( b )*x inv(l)*sub( a )*inv(l**h) of a complex generalized hermitian-definite eigenproblem, of the form sub( a )*x=(lambda)*sub( b )*x, sub( a )*sub( b )x=(lambda)*x, o here sub( a ) denoting a( ia:ia+n-1, ja:ja+n-1 ) is assumed to be if ibtype = 1, the problem is sub( a )*x = lambda*sub( b )*x inv(l)*sub( a )*inv(l**h) |
| LAPACK LAPACK this local portion is stored in the packed banded format used in LAPACK. please see the notes below and th distributed matrices. this local portion is stored in the packed banded format used in LAPACK. please see the notes below and th distributed matrices. this local portion is stored in the packed banded format used in LAPACK. please see the notes below and th distributed matrices. is nr+bwu where nr is the number of columns on the last processor finally aptr is the pointer to the first element of a. as LAPACK has to be adjusted on processor mycol=0. this local portion is stored in the packed banded format used in LAPACK. please see the notes below and th distributed matrices. row. the values of locr() and locc() may be determined via a call to the scaLAPACK tool function, numroc locc( n ) = numroc( n, nb_a, mycol, csrc_a, npcol ). siam j. sci. comput., 6:20 (1999), pp. 2223--2236. (see also LAPACK working note 132 of a complex hermitian matrix a by calling the recommended sequence of scaLAPACK routines. eigenvalues/vectors can be selected b eigenvalues. the values of locr() and locc() may be determined via a call to the scaLAPACK tool function, numroc locc( n ) = numroc( n, nb_a, mycol, csrc_a, npcol ). the values of locr() and locc() may be determined via a call to the scaLAPACK tool function, numroc locc( n ) = numroc( n, nb_a, mycol, csrc_a, npcol ). the values of locr() and locc() may be determined via a call to the scaLAPACK tool function, numroc locc( n ) = numroc( n, nb_a, mycol, csrc_a, npcol ). the values of locr() and locc() may be determined via a call to the scaLAPACK tool function, numroc locc( n ) = numroc( n, nb_a, mycol, csrc_a, npcol ). this local portion is stored in the packed banded format used in LAPACK. please see the notes below and th distributed matrices. this local portion is stored in the packed banded format used in LAPACK. please see the notes below and th distributed matrices. process. pcstein decides on the allocation of work among the processes and then calls sstein2 (modified LAPACK routine) on eac expected orthogonalization may not be done. this local portion is stored in the packed banded format used in LAPACK. please see the notes below and th distributed matrices. this local portion is stored in the packed banded format used in LAPACK. please see the notes below and th distributed matrices. this local portion is stored in the packed banded format used in LAPACK. please see the notes below and th distributed matrices. is nr+bwu where nr is the number of columns on the last processor finally aptr is the pointer to the first element of a. as LAPACK has to be adjusted on processor mycol=0. this local portion is stored in the packed banded format used in LAPACK. please see the notes below and th distributed matrices. row. the values of locr() and locc() may be determined via a call to the scaLAPACK tool function, numroc locc( n ) = numroc( n, nb_a, mycol, csrc_a, npcol ). the values of locr() and locc() may be determined via a call to the scaLAPACK tool function, numroc locc( n ) = numroc( n, nb_a, mycol, csrc_a, npcol ). the values of locr() and locc() may be determined via a call to the scaLAPACK tool function, numroc locc( n ) = numroc( n, nb_a, mycol, csrc_a, npcol ). this local portion is stored in the packed banded format used in LAPACK. please see the notes below and th distributed matrices. this local portion is stored in the packed banded format used in LAPACK. please see the notes below and th distributed matrices. siam j. sci. comput., 6:20 (1999), pp. 2223--2236. (see also LAPACK working note 132 process. pdstein decides on the allocation of work among the processes and then calls dstein2 (modified LAPACK routine) on eac expected orthogonalization may not be done. of a real symmetric matrix a by calling the recommended sequence of scaLAPACK routines in its present form, pdsyevd assumes a homogeneous system and makes of a real symmetric matrix a by calling the recommended sequence of scaLAPACK routines. eigenvalues/vectors can be selected b eigenvalues. the values of locr() and locc() may be determined via a call to the scaLAPACK tool function, numroc locc( n ) = numroc( n, nb_a, mycol, csrc_a, npcol ). pjlaenv is called from the scaLAPACK symmetric and hermitia problem-dependent parameters for the local environment. see ispec this local portion is stored in the packed banded format used in LAPACK. please see the notes below and th distributed matrices. this local portion is stored in the packed banded format used in LAPACK. please see the notes below and th distributed matrices. this local portion is stored in the packed banded format used in LAPACK. please see the notes below and th distributed matrices. is nr+bwu where nr is the number of columns on the last processor finally aptr is the pointer to the first element of a. as LAPACK has to be adjusted on processor mycol=0. this local portion is stored in the packed banded format used in LAPACK. please see the notes below and th distributed matrices. row. the values of locr() and locc() may be determined via a call to the scaLAPACK tool function, numroc locc( n ) = numroc( n, nb_a, mycol, csrc_a, npcol ). the values of locr() and locc() may be determined via a call to the scaLAPACK tool function, numroc locc( n ) = numroc( n, nb_a, mycol, csrc_a, npcol ). the values of locr() and locc() may be determined via a call to the scaLAPACK tool function, numroc locc( n ) = numroc( n, nb_a, mycol, csrc_a, npcol ). this local portion is stored in the packed banded format used in LAPACK. please see the notes below and th distributed matrices. this local portion is stored in the packed banded format used in LAPACK. please see the notes below and th distributed matrices. siam j. sci. comput., 6:20 (1999), pp. 2223--2236. (see also LAPACK working note 132 process. psstein decides on the allocation of work among the processes and then calls sstein2 (modified LAPACK routine) on eac expected orthogonalization may not be done. of a real symmetric matrix a by calling the recommended sequence of scaLAPACK routines in its present form, pssyevd assumes a homogeneous system and makes of a real symmetric matrix a by calling the recommended sequence of scaLAPACK routines. eigenvalues/vectors can be selected b eigenvalues. the values of locr() and locc() may be determined via a call to the scaLAPACK tool function, numroc locc( n ) = numroc( n, nb_a, mycol, csrc_a, npcol ). this local portion is stored in the packed banded format used in LAPACK. please see the notes below and th distributed matrices. this local portion is stored in the packed banded format used in LAPACK. please see the notes below and th distributed matrices. this local portion is stored in the packed banded format used in LAPACK. please see the notes below and th distributed matrices. is nr+bwu where nr is the number of columns on the last processor finally aptr is the pointer to the first element of a. as LAPACK has to be adjusted on processor mycol=0. this local portion is stored in the packed banded format used in LAPACK. please see the notes below and th distributed matrices. row. the values of locr() and locc() may be determined via a call to the scaLAPACK tool function, numroc locc( n ) = numroc( n, nb_a, mycol, csrc_a, npcol ). siam j. sci. comput., 6:20 (1999), pp. 2223--2236. (see also LAPACK working note 132 of a complex hermitian matrix a by calling the recommended sequence of scaLAPACK routines. eigenvalues/vectors can be selected b eigenvalues. the values of locr() and locc() may be determined via a call to the scaLAPACK tool function, numroc locc( n ) = numroc( n, nb_a, mycol, csrc_a, npcol ). the values of locr() and locc() may be determined via a call to the scaLAPACK tool function, numroc locc( n ) = numroc( n, nb_a, mycol, csrc_a, npcol ). the values of locr() and locc() may be determined via a call to the scaLAPACK tool function, numroc locc( n ) = numroc( n, nb_a, mycol, csrc_a, npcol ). the values of locr() and locc() may be determined via a call to the scaLAPACK tool function, numroc locc( n ) = numroc( n, nb_a, mycol, csrc_a, npcol ). this local portion is stored in the packed banded format used in LAPACK. please see the notes below and th distributed matrices. this local portion is stored in the packed banded format used in LAPACK. please see the notes below and th distributed matrices. process. pzstein decides on the allocation of work among the processes and then calls dstein2 (modified LAPACK routine) on eac expected orthogonalization may not be done. |
| LARED1D LARED1D watobd = max(max(wpclange,wpcgebrd), max(wpclared2d,wp(pre)LARED1D)) where wpclange, wpclared1d, wpclared2d, wpcgebrd are the watobd = max(max(wpdlange,wpdgebrd), max(wpdlared2d,wp(pre)LARED1D)) where wpdlange, wpdlared1d, wpdlared2d, wpdgebrd are the watobd = max(max(wpslange,wpsgebrd), max(wpslared2d,wp(pre)LARED1D)) where wpslange, wpslared1d, wpslared2d, wpsgebrd are the watobd = max(max(wpzlange,wpzgebrd), max(wpzlared2d,wp(pre)LARED1D)) where wpzlange, wpzlared1d, wpzlared2d, wpzgebrd are the |
| large large nb*(bwl+bwu)+6*max(bwl,bwu)*max(bwl,bwu) if laf is not large enough, an error code will be returne 2*(nb+2) if laf is not large enough, an error code will be returne (nb+bwu)*(bwl+bwu)+6*(bwl+bwu)*(bwl+2*bwu) if laf is not large enough, an error code will be returne reduce its condition number. r returns the row scale factors and c the column scale factors, chosen to try to make the largest entry i b(i,j) = r(i) * a(i,j) * c(j) have absolute value 1. il (global input) integer if range='i', the index (from smallest to largest) of th not referenced if range = 'a' or 'v'. il (global input) integer if range='i', the index (from smallest to largest) of th not referenced if range = 'a' or 'v'. rowcnd (global input) real the global ratio of the smallest r(i) to the largest r(i) ratio of the smallest sr(i) (respectively sc(j)) to the largest sr(i) (respectively sc(j)), with ia <= i <= ia+n- (nb+2*bw)*bw if laf is not large enough, an error code will be returne if info = 0, scond contains the ratio of the smallest sr(i) (or sc(j)) to the largest sr(i) (or sc(j)), wit and amax is neither too large nor too small, it is not worth (nb+2) if laf is not large enough, an error code will be returne nb*(bwl+bwu)+6*max(bwl,bwu)*max(bwl,bwu) if laf is not large enough, an error code will be returne 2*(nb+2) if laf is not large enough, an error code will be returne (nb+bwu)*(bwl+bwu)+6*(bwl+bwu)*(bwl+2*bwu) if laf is not large enough, an error code will be returne reduce its condition number. r returns the row scale factors and c the column scale factors, chosen to try to make the largest entry i b(i,j) = r(i) * a(i,j) * c(j) have absolute value 1. and overflow, and returns the square root of each of these values if the log of large is sufficiently large. this subroutine is intende and redefine the underflow and overflow limits to be the square roots rowcnd (global input) double precision the global ratio of the smallest r(i) to the largest r(i) ratio of the smallest sr(i) (respectively sc(j)) to the largest sr(i) (respectively sc(j)), with ia <= i <= ia+n- (nb+2*bw)*bw if laf is not large enough, an error code will be returne if info = 0, scond contains the ratio of the smallest sr(i) (or sc(j)) to the largest sr(i) (or sc(j)), wit and amax is neither too large nor too small, it is not worth (nb+2) if laf is not large enough, an error code will be returne split-off block (see iblock, isplit) and
ordered from smallest to largest withi
= 'e': ("entire matrix")
il (global input) integer if range='i', the index (from smallest to largest) of th not referenced if range = 'a' or 'v'. il (global input) integer if range='i', the index (from smallest to largest) of th not referenced if range = 'a' or 'v'. nb*(bwl+bwu)+6*max(bwl,bwu)*max(bwl,bwu) if laf is not large enough, an error code will be returne 2*(nb+2) if laf is not large enough, an error code will be returne (nb+bwu)*(bwl+bwu)+6*(bwl+bwu)*(bwl+2*bwu) if laf is not large enough, an error code will be returne reduce its condition number. r returns the row scale factors and c the column scale factors, chosen to try to make the largest entry i b(i,j) = r(i) * a(i,j) * c(j) have absolute value 1. and overflow, and returns the square root of each of these values if the log of large is sufficiently large. this subroutine is intende and redefine the underflow and overflow limits to be the square roots rowcnd (global input) real the global ratio of the smallest r(i) to the largest r(i) ratio of the smallest sr(i) (respectively sc(j)) to the largest sr(i) (respectively sc(j)), with ia <= i <= ia+n- (nb+2*bw)*bw if laf is not large enough, an error code will be returne if info = 0, scond contains the ratio of the smallest sr(i) (or sc(j)) to the largest sr(i) (or sc(j)), wit and amax is neither too large nor too small, it is not worth (nb+2) if laf is not large enough, an error code will be returne split-off block (see iblock, isplit) and
ordered from smallest to largest withi
= 'e': ("entire matrix")
il (global input) integer if range='i', the index (from smallest to largest) of th not referenced if range = 'a' or 'v'. il (global input) integer if range='i', the index (from smallest to largest) of th not referenced if range = 'a' or 'v'. nb*(bwl+bwu)+6*max(bwl,bwu)*max(bwl,bwu) if laf is not large enough, an error code will be returne 2*(nb+2) if laf is not large enough, an error code will be returne (nb+bwu)*(bwl+bwu)+6*(bwl+bwu)*(bwl+2*bwu) if laf is not large enough, an error code will be returne reduce its condition number. r returns the row scale factors and c the column scale factors, chosen to try to make the largest entry i b(i,j) = r(i) * a(i,j) * c(j) have absolute value 1. il (global input) integer if range='i', the index (from smallest to largest) of th not referenced if range = 'a' or 'v'. il (global input) integer if range='i', the index (from smallest to largest) of th not referenced if range = 'a' or 'v'. rowcnd (global input) double precision the global ratio of the smallest r(i) to the largest r(i) ratio of the smallest sr(i) (respectively sc(j)) to the largest sr(i) (respectively sc(j)), with ia <= i <= ia+n- (nb+2*bw)*bw if laf is not large enough, an error code will be returne if info = 0, scond contains the ratio of the smallest sr(i) (or sc(j)) to the largest sr(i) (or sc(j)), wit and amax is neither too large nor too small, it is not worth (nb+2) if laf is not large enough, an error code will be returne |
| larger larger 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 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 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 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 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 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 z, ldz -> z, iz, jz, descz workspace needs are larger for pcheevx 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 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 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 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 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 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 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 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 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 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 the minimum (absolute) width of an interval. when an interval is narrower than abstol, or than reltol times the larger (i small, i.e., converged. = 0 : when an interval is narrower than abstol, or than reltol times the larger (in magnitude) endpoint, the = 1 : when an interval is narrower than abstol, or than 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 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 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 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 where "ulp" is the machine precision (distance from 1 to the next larger floating point number. fudge double precision, default = 2.0 z, ldz -> z, iz, jz, descz workspace needs are larger for pdsyevx 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 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 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 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 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 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 the minimum (absolute) width of an interval. when an interval is narrower than abstol, or than reltol times the larger (i small, i.e., converged. = 0 : when an interval is narrower than abstol, or than reltol times the larger (in magnitude) endpoint, the = 1 : when an interval is narrower than abstol, or than 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 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 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 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 where "ulp" is the machine precision (distance from 1 to the next larger floating point number. fudge real, default = 2.0 z, ldz -> z, iz, jz, descz workspace needs are larger for pssyevx 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 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 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 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 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 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 z, ldz -> z, iz, jz, descz workspace needs are larger for pzheevx 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 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 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 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 |
| largest largest partition d( start:endd ) and stack parts, largest one firs choose partition entry as median of 3 partition d( start:endd ) and stack parts, largest one firs choose partition entry as median of 3 reduce its condition number. r returns the row scale factors and c the column scale factors, chosen to try to make the largest entry i b(i,j) = r(i) * a(i,j) * c(j) have absolute value 1. to sub( x ), ferr is an estimated upper bound for the magnitude of the largest element in (sub( x ) - xtrue the estimate is as reliable as the estimate for rcond, and x(ix:ix+n-1,jx:jx+nrhs-1). if xtrue is the true solution, ferr(j) bounds the magnitude of the largest entry i in x(j). the estimate is as reliable as the estimate for il (global input) integer if range='i', the index (from smallest to largest) of th not referenced if range = 'a' or 'v'. il (global input) integer if range='i', the index (from smallest to largest) of th not referenced if range = 'a' or 'v'. pclange returns the value of the one norm, or the frobenius norm, or the infinity norm, or the element of largest absolute value of rowcnd (global input) real the global ratio of the smallest r(i) to the largest r(i) ratio of the smallest sr(i) (respectively sc(j)) to the largest sr(i) (respectively sc(j)), with ia <= i <= ia+n- amax (global output) pointer to real the absolute value of the largest entry of the distribute if info = 0, scond contains the ratio of the smallest sr(i) (or sc(j)) to the largest sr(i) (or sc(j)), wit and amax is neither too large nor too small, it is not worth to sub( x ), ferr is an estimated upper bound for the magnitude of the largest element in (sub( x ) - xtrue the estimate is as reliable as the estimate for rcond, and if xtrue is the true solution, ferr(j) bounds the magnitude of the largest entry in (x(j) - xtrue) divided b the error bound depends on the quality of the estimate of eigenvalues should be grouped by split-off block and ordered from smallest to largest within the block (the output arra array should be replicated on all processes. each eigenvector is normalized so that the element of largest (x,y) is taken to be |x| + |y|. each solution vector of sub( x ). if xtrue is the true solution, ferr bounds the magnitude of the largest entr largest entry in sub( x ). the estimate is as reliable as reduce its condition number. r returns the row scale factors and c the column scale factors, chosen to try to make the largest entry i b(i,j) = r(i) * a(i,j) * c(j) have absolute value 1. to sub( x ), ferr is an estimated upper bound for the magnitude of the largest element in (sub( x ) - xtrue the estimate is as reliable as the estimate for rcond, and x(ix:ix+n-1,jx:jx+nrhs-1). if xtrue is the true solution, ferr(j) bounds the magnitude of the largest entry i in x(j). the estimate is as reliable as the estimate for 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 rmin = underflow threshold - base**(emin-1) emax = largest exponent before overflo pdlange returns the value of the one norm, or the frobenius norm, or the infinity norm, or the element of largest absolute value of 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 rowcnd (global input) double precision the global ratio of the smallest r(i) to the largest r(i) ratio of the smallest sr(i) (respectively sc(j)) to the largest sr(i) (respectively sc(j)), with ia <= i <= ia+n- if info = 0, scond contains the ratio of the smallest sr(i) (or sc(j)) to the largest sr(i) (or sc(j)), wit and amax is neither too large nor too small, it is not worth to sub( x ), ferr is an estimated upper bound for the magnitude of the largest element in (sub( x ) - xtrue the estimate is as reliable as the estimate for rcond, and if xtrue is the true solution, ferr(j) bounds the magnitude of the largest entry in (x(j) - xtrue) divided b the error bound depends on the quality of the estimate of split-off block (see iblock, isplit) and
ordered from smallest to largest withi
= 'e': ("entire matrix")
eigenvalues should be grouped by split-off block and ordered from smallest to largest within the block (the output arra array should be replicated on all processes. il (global input) integer if range='i', the index (from smallest to largest) of th not referenced if range = 'a' or 'v'. il (global input) integer if range='i', the index (from smallest to largest) of th not referenced if range = 'a' or 'v'. each solution vector of sub( x ). if xtrue is the true solution, ferr bounds the magnitude of the largest entr largest entry in sub( x ). the estimate is as reliable as reduce its condition number. r returns the row scale factors and c the column scale factors, chosen to try to make the largest entry i b(i,j) = r(i) * a(i,j) * c(j) have absolute value 1. to sub( x ), ferr is an estimated upper bound for the magnitude of the largest element in (sub( x ) - xtrue the estimate is as reliable as the estimate for rcond, and x(ix:ix+n-1,jx:jx+nrhs-1). if xtrue is the true solution, ferr(j) bounds the magnitude of the largest entry i in x(j). the estimate is as reliable as the estimate for 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 rmin = underflow threshold - base**(emin-1) emax = largest exponent before overflo pslange returns the value of the one norm, or the frobenius norm, or the infinity norm, or the element of largest absolute value of 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 rowcnd (global input) real the global ratio of the smallest r(i) to the largest r(i) ratio of the smallest sr(i) (respectively sc(j)) to the largest sr(i) (respectively sc(j)), with ia <= i <= ia+n- if info = 0, scond contains the ratio of the smallest sr(i) (or sc(j)) to the largest sr(i) (or sc(j)), wit and amax is neither too large nor too small, it is not worth to sub( x ), ferr is an estimated upper bound for the magnitude of the largest element in (sub( x ) - xtrue the estimate is as reliable as the estimate for rcond, and if xtrue is the true solution, ferr(j) bounds the magnitude of the largest entry in (x(j) - xtrue) divided b the error bound depends on the quality of the estimate of split-off block (see iblock, isplit) and
ordered from smallest to largest withi
= 'e': ("entire matrix")
eigenvalues should be grouped by split-off block and ordered from smallest to largest within the block (the output arra array should be replicated on all processes. il (global input) integer if range='i', the index (from smallest to largest) of th not referenced if range = 'a' or 'v'. il (global input) integer if range='i', the index (from smallest to largest) of th not referenced if range = 'a' or 'v'. each solution vector of sub( x ). if xtrue is the true solution, ferr bounds the magnitude of the largest entr largest entry in sub( x ). the estimate is as reliable as reduce its condition number. r returns the row scale factors and c the column scale factors, chosen to try to make the largest entry i b(i,j) = r(i) * a(i,j) * c(j) have absolute value 1. to sub( x ), ferr is an estimated upper bound for the magnitude of the largest element in (sub( x ) - xtrue the estimate is as reliable as the estimate for rcond, and x(ix:ix+n-1,jx:jx+nrhs-1). if xtrue is the true solution, ferr(j) bounds the magnitude of the largest entry i in x(j). the estimate is as reliable as the estimate for il (global input) integer if range='i', the index (from smallest to largest) of th not referenced if range = 'a' or 'v'. il (global input) integer if range='i', the index (from smallest to largest) of th not referenced if range = 'a' or 'v'. pzlange returns the value of the one norm, or the frobenius norm, or the infinity norm, or the element of largest absolute value of rowcnd (global input) double precision the global ratio of the smallest r(i) to the largest r(i) ratio of the smallest sr(i) (respectively sc(j)) to the largest sr(i) (respectively sc(j)), with ia <= i <= ia+n- amax (global output) pointer to double precision the absolute value of the largest entry of the distribute if info = 0, scond contains the ratio of the smallest sr(i) (or sc(j)) to the largest sr(i) (or sc(j)), wit and amax is neither too large nor too small, it is not worth to sub( x ), ferr is an estimated upper bound for the magnitude of the largest element in (sub( x ) - xtrue the estimate is as reliable as the estimate for rcond, and if xtrue is the true solution, ferr(j) bounds the magnitude of the largest entry in (x(j) - xtrue) divided b the error bound depends on the quality of the estimate of eigenvalues should be grouped by split-off block and ordered from smallest to largest within the block (the output arra array should be replicated on all processes. each eigenvector is normalized so that the element of largest (x,y) is taken to be |x| + |y|. each solution vector of sub( x ). if xtrue is the true solution, ferr bounds the magnitude of the largest entr largest entry in sub( x ). the estimate is as reliable as partition d( start:endd ) and stack parts, largest one firs choose partition entry as median of 3 partition d( start:endd ) and stack parts, largest one firs choose partition entry as median of 3 |
| last last ju is the index of the last column affected by the curren 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. istop (global input) integer specifies the "number" of the last reflector. this i istop is ignored if block is .false.. ju is the index of the last column affected by the curren istop (global input) integer specifies the "number" of the last reflector. this i istop is ignored if block is .false.. transfer last triangle d_i of local matrix to next processo its main (odd) block a_i. the last processor does not participate in the solution of th transfer last triangle d_i of local matrix to next processo its main (odd) block a_i. the last processor does not participate in the solution of th the last processor does not need to send anything 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. when rowcol='r' or 'r' and pivroc='c' or 'c', or rowcol='c' or 'c' and pivroc='r' or 'r', the last piece of this array o this array is tied to the distributed matrix a. the pivoting information. ipiv(i) is the global row (column), local row (column) i was swapped with. the last piece of th tied to the distributed matrix a. k2 (global input) integer the last element of ipiv for which a row or column inter if uplo = 'u', pclatrd reduces the last nb rows and columns of if uplo = 'l', pclatrd reduces the first nb rows and columns of a transfer last triangle d_i of local matrix to next processo its main (odd) block a_i. the last processor does not participate in the solution of th transfer last triangle d_i of local matrix to next processo its main (odd) block a_i. the last processor does not participate in the solution of th a(ia:ia+m-1,ja:ja+n-1) with orthonormal columns, which is defined as the last n columns of a product of k elementary reflectors of order q = h(k) . . . h(2) h(1) a(ia:ia+m-1,ja:ja+n-1) with orthonormal columns, which is defined as the last n columns of a product of k elementary reflectors of order q = h(k) . . . h(2) h(1) a(ia:ia+m-1,ja:ja+n-1) with orthonormal rows, which is defined as the last m rows of a product of k elementary reflectors of order q = h(1)' h(2)' . . . h(k)' a(ia:ia+m-1,ja:ja+n-1) with orthonormal rows, which is defined as the last m rows of a product of k elementary reflectors of order q = h(1)' h(2)' . . . h(k)' transfer last triangle d_i of local matrix to next processo its main (odd) block a_i. the last processor does not participate in the solution of th transfer last triangle d_i of local matrix to next processo its main (odd) block a_i. the last processor does not participate in the solution of th the last processor does not need to send anything based on code written by : peter arbenz, eth zurich, 1996. last modified by: peter arbenz, institute of scientific computing = 0 : all intervals converged. = 1 - mmax : the last info intervals did not converge 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 n1 (input) integer the location of the last eigenvalue in the leadin min(1,n) <= n1 <= n. n1 (input) integer the location of the last eigenvalue in the leading sub-matrix on exit, q contains the trailing (n-k) updated eigenvectors (those which were deflated) in its last n-k columns ldq (input) integer form z1 which consist of the last row of q 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. when rowcol='r' or 'r' and pivroc='c' or 'c', or rowcol='c' or 'c' and pivroc='r' or 'r', the last piece of this array o this array is tied to the distributed matrix a. the pivoting information. ipiv(i) is the global row (column), local row (column) i was swapped with. the last piece of th tied to the distributed matrix a. k2 (global input) integer the last element of ipiv for which a row or column inter if uplo = 'u', pdlatrd reduces the last nb rows and columns of if uplo = 'l', pdlatrd reduces the first nb rows and columns of a a(ia:ia+m-1,ja:ja+n-1) with orthonormal columns, which is defined as the last n columns of a product of k elementary reflectors of order q = h(k) . . . h(2) h(1) a(ia:ia+m-1,ja:ja+n-1) with orthonormal columns, which is defined as the last n columns of a product of k elementary reflectors of order q = h(k) . . . h(2) h(1) a(ia:ia+m-1,ja:ja+n-1) with orthonormal rows, which is defined as the last m rows of a product of k elementary reflectors of order q = h(1) h(2) . . . h(k) a(ia:ia+m-1,ja:ja+n-1) with orthonormal rows, which is defined as the last m rows of a product of k elementary reflectors of order q = h(1) h(2) . . . h(k) transfer last triangle d_i of local matrix to next processo its main (odd) block a_i. the last processor does not participate in the solution of th transfer last triangle d_i of local matrix to next processo its main (odd) block a_i. the last processor does not participate in the solution of th transfer last triangle d_i of local matrix to next processo its main (odd) block a_i. the last processor does not participate in the solution of th transfer last triangle d_i of local matrix to next processo its main (odd) block a_i. the last processor does not participate in the solution of th the last processor does not need to send anything based on code written by : peter arbenz, eth zurich, 1996. last modified by: peter arbenz, institute of scientific computing = 0 : all intervals converged. = 1 - mmax : the last info intervals did not converge 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 n1 (input) integer the location of the last eigenvalue in the leadin min(1,n) <= n1 <= n. n1 (input) integer the location of the last eigenvalue in the leading sub-matrix on exit, q contains the trailing (n-k) updated eigenvectors (those which were deflated) in its last n-k columns ldq (input) integer form z1 which consist of the last row of q 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. when rowcol='r' or 'r' and pivroc='c' or 'c', or rowcol='c' or 'c' and pivroc='r' or 'r', the last piece of this array o this array is tied to the distributed matrix a. the pivoting information. ipiv(i) is the global row (column), local row (column) i was swapped with. the last piece of th tied to the distributed matrix a. k2 (global input) integer the last element of ipiv for which a row or column inter if uplo = 'u', pslatrd reduces the last nb rows and columns of if uplo = 'l', pslatrd reduces the first nb rows and columns of a a(ia:ia+m-1,ja:ja+n-1) with orthonormal columns, which is defined as the last n columns of a product of k elementary reflectors of order q = h(k) . . . h(2) h(1) a(ia:ia+m-1,ja:ja+n-1) with orthonormal columns, which is defined as the last n columns of a product of k elementary reflectors of order q = h(k) . . . h(2) h(1) a(ia:ia+m-1,ja:ja+n-1) with orthonormal rows, which is defined as the last m rows of a product of k elementary reflectors of order q = h(1) h(2) . . . h(k) a(ia:ia+m-1,ja:ja+n-1) with orthonormal rows, which is defined as the last m rows of a product of k elementary reflectors of order q = h(1) h(2) . . . h(k) transfer last triangle d_i of local matrix to next processo its main (odd) block a_i. the last processor does not participate in the solution of th transfer last triangle d_i of local matrix to next processo its main (odd) block a_i. the last processor does not participate in the solution of th transfer last triangle d_i of local matrix to next processo its main (odd) block a_i. the last processor does not participate in the solution of th transfer last triangle d_i of local matrix to next processo its main (odd) block a_i. the last processor does not participate in the solution of th the last processor does not need to send anything 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. when rowcol='r' or 'r' and pivroc='c' or 'c', or rowcol='c' or 'c' and pivroc='r' or 'r', the last piece of this array o this array is tied to the distributed matrix a. the pivoting information. ipiv(i) is the global row (column), local row (column) i was swapped with. the last piece of th tied to the distributed matrix a. k2 (global input) integer the last element of ipiv for which a row or column inter if uplo = 'u', pzlatrd reduces the last nb rows and columns of if uplo = 'l', pzlatrd reduces the first nb rows and columns of a transfer last triangle d_i of local matrix to next processo its main (odd) block a_i. the last processor does not participate in the solution of th transfer last triangle d_i of local matrix to next processo its main (odd) block a_i. the last processor does not participate in the solution of th a(ia:ia+m-1,ja:ja+n-1) with orthonormal columns, which is defined as the last n columns of a product of k elementary reflectors of order q = h(k) . . . h(2) h(1) a(ia:ia+m-1,ja:ja+n-1) with orthonormal columns, which is defined as the last n columns of a product of k elementary reflectors of order q = h(k) . . . h(2) h(1) a(ia:ia+m-1,ja:ja+n-1) with orthonormal rows, which is defined as the last m rows of a product of k elementary reflectors of order q = h(1)' h(2)' . . . h(k)' a(ia:ia+m-1,ja:ja+n-1) with orthonormal rows, which is defined as the last m rows of a product of k elementary reflectors of order q = h(1)' h(2)' . . . h(k)' ju is the index of the last column affected by the curren istop (global input) integer specifies the "number" of the last reflector. this i istop is ignored if block is .false.. ju is the index of the last column affected by the curren 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. istop (global input) integer specifies the "number" of the last reflector. this i istop is ignored if block is .false.. |
| later later this node will potentially do more work later however, because there are many bulges, k1(ki) & k2(ki) might go past that range while later bulges (ki+1,ki+2,etc..) ar communication sometimes k1(ki)=hbl-2 & k2(ki)=hbl-1 so both this node will potentially do more work later however, because there are many bulges, k1(ki) & k2(ki) might go past that range while later bulges (ki+1,ki+2,etc..) ar set to the underflow threshold dlamch('u'), not zero.
note : if eigenvectors are desired later by inverse iteratio
this node will potentially do more work later however, because there are many bulges, k1(ki) & k2(ki) might go past that range while later bulges (ki+1,ki+2,etc..) ar set to the underflow threshold slamch('u'), not zero.
note : if eigenvectors are desired later by inverse iteratio
this node will potentially do more work later however, because there are many bulges, k1(ki) & k2(ki) might go past that range while later bulges (ki+1,ki+2,etc..) ar communication sometimes k1(ki)=hbl-2 & k2(ki)=hbl-1 so both |
| latest latest corresponding to the selected eigenvalues. if an eigenvector fails to converge, then that column of z contains the latest eigenvector is returned in ifail. corresponding to the selected eigenvalues. if an eigenvector fails to converge, then that column of z contains the latest eigenvector is returned in ifail. corresponding to the selected eigenvalues. if an eigenvector fails to converge, then that column of z contains the latest eigenvector is returned in ifail. corresponding to the selected eigenvalues. if an eigenvector fails to converge, then that column of z contains the latest eigenvector is returned in ifail. corresponding to the selected eigenvalues. if an eigenvector fails to converge, then that column of z contains the latest eigenvector is returned in ifail. corresponding to the selected eigenvalues. if an eigenvector fails to converge, then that column of z contains the latest eigenvector is returned in ifail. corresponding to the selected eigenvalues. if an eigenvector fails to converge, then that column of z contains the latest eigenvector is returned in ifail. corresponding to the selected eigenvalues. if an eigenvector fails to converge, then that column of z contains the latest eigenvector is returned in ifail. |
| lative lative berr (local output) real array of local dimension locc(jb+nrhs-1). the componentwise relative backwar lative change in any entry of sub( a ) or sub( b ) berr (local output) real array of local dimension locc(jb+nrhs-1). the componentwise relative backwar lative change in any entry of sub( a ) or sub( b ) berr (local output) real array of local dimension locc(jb+nrhs-1). the componentwise relative backwar lative change in any entry of sub( a ) or sub( b ) berr (local output) double precision array of local dimension locc(jb+nrhs-1). the componentwise relative backwar lative change in any entry of sub( a ) or sub( b ) berr (local output) double precision array of local dimension locc(jb+nrhs-1). the componentwise relative backwar lative change in any entry of sub( a ) or sub( b ) berr (local output) double precision array of local dimension locc(jb+nrhs-1). the componentwise relative backwar lative change in any entry of sub( a ) or sub( b ) berr (local output) real array of local dimension locc(jb+nrhs-1). the componentwise relative backwar lative change in any entry of sub( a ) or sub( b ) berr (local output) real array of local dimension locc(jb+nrhs-1). the componentwise relative backwar lative change in any entry of sub( a ) or sub( b ) berr (local output) real array of local dimension locc(jb+nrhs-1). the componentwise relative backwar lative change in any entry of sub( a ) or sub( b ) berr (local output) double precision array of local dimension locc(jb+nrhs-1). the componentwise relative backwar lative change in any entry of sub( a ) or sub( b ) berr (local output) double precision array of local dimension locc(jb+nrhs-1). the componentwise relative backwar lative change in any entry of sub( a ) or sub( b ) berr (local output) double precision array of local dimension locc(jb+nrhs-1). the componentwise relative backwar lative change in any entry of sub( a ) or sub( b ) |
| lawn132 lawn132 (see also lapack working note 132) http://www.netlib.org/lapack/lawns/lawn132.p ===================================================================== (see also lapack working note 132) http://www.netlib.org/lapack/lawns/lawn132.p ===================================================================== (see also lapack working note 132) http://www.netlib.org/lapack/lawns/lawn132.p ===================================================================== (see also lapack working note 132) http://www.netlib.org/lapack/lawns/lawn132.p ===================================================================== (see also lapack working note 132) http://www.netlib.org/lapack/lawns/lawn132.p ===================================================================== (see also lapack working note 132) http://www.netlib.org/lapack/lawns/lawn132.p ===================================================================== |
| lawns lawns (see also lapack working note 132) http://www.netlib.org/lapack/lawns/lawn132.p ===================================================================== (see also lapack working note 132) http://www.netlib.org/lapack/lawns/lawn132.p ===================================================================== (see also lapack working note 132) http://www.netlib.org/lapack/lawns/lawn132.p ===================================================================== (see also lapack working note 132) http://www.netlib.org/lapack/lawns/lawn132.p ===================================================================== (see also lapack working note 132) http://www.netlib.org/lapack/lawns/lawn132.p ===================================================================== (see also lapack working note 132) http://www.netlib.org/lapack/lawns/lawn132.p ===================================================================== |
| Lawrence Lawrence code developer: andrew j. cleary, university of tennessee. current address: Lawrence livermore national labs code developer: andrew j. cleary, university of tennessee. current address: Lawrence livermore national labs code developer: andrew j. cleary, university of tennessee. current address: Lawrence livermore national labs code developer: andrew j. cleary, university of tennessee. current address: Lawrence livermore national labs code developer: andrew j. cleary, university of tennessee. current address: Lawrence livermore national labs code developer: andrew j. cleary, university of tennessee. current address: Lawrence livermore national labs code developer: andrew j. cleary, university of tennessee. current address: Lawrence livermore national labs code developer: andrew j. cleary, university of tennessee. current address: Lawrence livermore national labs code developer: andrew j. cleary, university of tennessee. current address: Lawrence livermore national labs code developer: andrew j. cleary, university of tennessee. current address: Lawrence livermore national labs code developer: andrew j. cleary, university of tennessee. current address: Lawrence livermore national labs ===================================================================== code developer: andrew j. cleary, university of tennessee. current address: Lawrence livermore national labs code developer: andrew j. cleary, university of tennessee. current address: Lawrence livermore national labs ===================================================================== code developer: andrew j. cleary, university of tennessee. current address: Lawrence livermore national labs code developer: andrew j. cleary, university of tennessee. current address: Lawrence livermore national labs code developer: andrew j. cleary, university of tennessee. current address: Lawrence livermore national labs ===================================================================== code developer: andrew j. cleary, university of tennessee. current address: Lawrence livermore national labs code developer: andrew j. cleary, university of tennessee. current address: Lawrence livermore national labs ===================================================================== code developer: andrew j. cleary, university of tennessee. current address: Lawrence livermore national labs code developer: andrew j. cleary, university of tennessee. current address: Lawrence livermore national labs ===================================================================== code developer: andrew j. cleary, university of tennessee. current address: Lawrence livermore national labs code developer: andrew j. cleary, university of tennessee. current address: Lawrence livermore national labs ===================================================================== code developer: andrew j. cleary, university of tennessee. current address: Lawrence livermore national labs code developer: andrew j. cleary, university of tennessee. current address: Lawrence livermore national labs code developer: andrew j. cleary, university of tennessee. current address: Lawrence livermore national labs ===================================================================== code developer: andrew j. cleary, university of tennessee. current address: Lawrence livermore national labs code developer: andrew j. cleary, university of tennessee. current address: Lawrence livermore national labs ===================================================================== code developer: andrew j. cleary, university of tennessee. current address: Lawrence livermore national labs code developer: andrew j. cleary, university of tennessee. current address: Lawrence livermore national labs code developer: andrew j. cleary, university of tennessee. current address: Lawrence livermore national labs code developer: andrew j. cleary, university of tennessee. current address: Lawrence livermore national labs code developer: andrew j. cleary, university of tennessee. current address: Lawrence livermore national labs code developer: andrew j. cleary, university of tennessee. current address: Lawrence livermore national labs code developer: andrew j. cleary, university of tennessee. current address: Lawrence livermore national labs code developer: andrew j. cleary, university of tennessee. current address: Lawrence livermore national labs code developer: andrew j. cleary, university of tennessee. current address: Lawrence livermore national labs |
| layout layout 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. pjlaenv. = 1: the data layout blocksize = 3: the algorithmic blocking factor; 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. |
| LBWL LBWL LBWL, lbwu: lower and upper bandwidth of local solve lm is the number of rows which is usually nb except for LBWL, lbwu: lower and upper bandwidth of local solve lm is the number of rows which is usually nb except for LBWL, lbwu: lower and upper bandwidth of local solve lm is the number of rows which is usually nb except for LBWL, lbwu: lower and upper bandwidth of local solve lm is the number of rows which is usually nb except for |
| LBWU LBWU lbwl, LBWU: lower and upper bandwidth of local solve lm is the number of rows which is usually nb except for lbwl, LBWU: lower and upper bandwidth of local solve lm is the number of rows which is usually nb except for lbwl, LBWU: lower and upper bandwidth of local solve lm is the number of rows which is usually nb except for lbwl, LBWU: lower and upper bandwidth of local solve lm is the number of rows which is usually nb except for |
| LCM LCM numroc( numroc( n+iroffb, mb_a, 0, 0, nprow ), mb_a, 0, 0, LCMp ), nrhsqb0 ) )*mb_a ) end if liwork = locc( n_a + mod(ja-1, nb_a) ) + max( ceil(ceil(locr(m_a)/mb_a)/(LCM/nprow)) where lcm is the least common multiple of process this must be at least 7*ceil( ceil( (i-l)/hbl ) / LCM(nprow,npcol) logical grid size. make sure it's divisible by LCM (we want even workloads! let LCM be the least common multiple of nprow and npcol if( nprow.eq.npcol ) then lwork >= ( nqc0 + max( npv0 + numroc( numroc( n+icoffc, nb_v, 0, 0, npcol ), nb_v, 0, 0, LCMq ) end if lwork >= ( nqc0 + max( npv0 + numroc( numroc( n+icoffc, nb_v, 0, 0, npcol ), nb_v, 0, 0, LCMq ) end if this must be at least 2*ceil( ceil( (i-l)/hbl ) / LCM(nprow,npcol) logical grid size. 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 ), numroc( numroc( ni+icoffc, nb_a, 0, 0, npcol ), nb_a, 0, 0, LCMq ), mpc0 ) )*nb_a ) end if numroc( numroc( ni+icoffc, nb_a, 0, 0, npcol ), nb_a, 0, 0, LCMq ), mpc0 ) )*nb_a ) end if if side = 'l', lwork >= mpc0 + max( max( 1, nqc0 ), numroc( numroc( m+iroffc,mb_a,0,0,nprow ),mb_a,0,0,LCMp ) ) numroc( numroc( m+iroffc, mb_a, 0, 0, nprow ), mb_a, 0, 0, LCMp ), nqc0 ) )*mb_a ) else if side = 'r', numroc( numroc( n+icoffc, nb_a, 0, 0, npcol ), nb_a, 0, 0, LCMq ), mpc0 ) )*nb_a ) end if numroc( numroc( n+icoffc, nb_a, 0, 0, npcol ), nb_a, 0, 0, LCMq ), mpc0 ) )*nb_a ) end if 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 ) ) numroc( numroc( m+iroffc, mb_a, 0, 0, nprow ), mb_a, 0, 0, LCMp ), nqc0 ) )*mb_a ) else if side = 'r', numroc( numroc( m+iroffc, mb_a, 0, 0, nprow ), mb_a, 0, 0, LCMp ), nqc0 ) )*mb_a ) else if side = 'r', numroc( numroc( ni+icoffc, nb_a, 0, 0, npcol ), nb_a, 0, 0, LCMq ), mpc0 ) )*nb_a ) end if numroc( numroc( n+iroffb, mb_a, 0, 0, nprow ), mb_a, 0, 0, LCMp ), nrhsqb0 ) )*mb_a ) end if liwork = locc( n_a + mod(ja-1, nb_a) ) + max( ceil(ceil(locr(m_a)/mb_a)/(LCM/nprow)) where lcm is the least common multiple of process this must be at least 7*ceil( ceil( (i-l)/hbl ) / LCM(nprow,npcol) logical grid size. make sure it's divisible by LCM (we want even workloads! let LCM be the least common multiple of nprow and npcol if( nprow.eq.npcol ) then lwork >= ( nqc0 + max( npv0 + numroc( numroc( n+icoffc, nb_v, 0, 0, npcol ), nb_v, 0, 0, LCMq ) end if lwork >= ( nqc0 + max( npv0 + numroc( numroc( n+icoffc, nb_v, 0, 0, npcol ), nb_v, 0, 0, LCMq ) end if this must be at least 2*ceil( ceil( (i-l)/hbl ) / LCM(nprow,npcol) logical grid size. 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 ), numroc( numroc( ni+icoffc, nb_a, 0, 0, npcol ), nb_a, 0, 0, LCMq ), mpc0 ) )*nb_a ) end if numroc( numroc( ni+icoffc, nb_a, 0, 0, npcol ), nb_a, 0, 0, LCMq ), mpc0 ) )*nb_a ) end if if side = 'l', lwork >= mpc0 + max( max( 1, nqc0 ), numroc( numroc( m+iroffc,mb_a,0,0,nprow ),mb_a,0,0,LCMp ) ) numroc( numroc( m+iroffc, mb_a, 0, 0, nprow ), mb_a, 0, 0, LCMp ), nqc0 ) )*mb_a ) else if side = 'r', numroc( numroc( n+icoffc, nb_a, 0, 0, npcol ), nb_a, 0, 0, LCMq ), mpc0 ) )*nb_a ) end if numroc( numroc( n+icoffc, nb_a, 0, 0, npcol ), nb_a, 0, 0, LCMq ), mpc0 ) )*nb_a ) end if 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 ) ) numroc( numroc( m+iroffc, mb_a, 0, 0, nprow ), mb_a, 0, 0, LCMp ), nqc0 ) )*mb_a ) else if side = 'r', numroc( numroc( m+iroffc, mb_a, 0, 0, nprow ), mb_a, 0, 0, LCMp ), nqc0 ) )*mb_a ) else if side = 'r', numroc( numroc( ni+icoffc, nb_a, 0, 0, npcol ), nb_a, 0, 0, LCMq ), mpc0 ) )*nb_a ) end if numroc( numroc( n+iroffb, mb_a, 0, 0, nprow ), mb_a, 0, 0, LCMp ), nrhsqb0 ) )*mb_a ) end if liwork = locc( n_a + mod(ja-1, nb_a) ) + max( ceil(ceil(locr(m_a)/mb_a)/(LCM/nprow)) where lcm is the least common multiple of process this must be at least 7*ceil( ceil( (i-l)/hbl ) / LCM(nprow,npcol) logical grid size. make sure it's divisible by LCM (we want even workloads! let LCM be the least common multiple of nprow and npcol if( nprow.eq.npcol ) then lwork >= ( nqc0 + max( npv0 + numroc( numroc( n+icoffc, nb_v, 0, 0, npcol ), nb_v, 0, 0, LCMq ) end if lwork >= ( nqc0 + max( npv0 + numroc( numroc( n+icoffc, nb_v, 0, 0, npcol ), nb_v, 0, 0, LCMq ) end if this must be at least 2*ceil( ceil( (i-l)/hbl ) / LCM(nprow,npcol) logical grid size. 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 ), numroc( numroc( ni+icoffc, nb_a, 0, 0, npcol ), nb_a, 0, 0, LCMq ), mpc0 ) )*nb_a ) end if numroc( numroc( ni+icoffc, nb_a, 0, 0, npcol ), nb_a, 0, 0, LCMq ), mpc0 ) )*nb_a ) end if if side = 'l', lwork >= mpc0 + max( max( 1, nqc0 ), numroc( numroc( m+iroffc,mb_a,0,0,nprow ),mb_a,0,0,LCMp ) ) numroc( numroc( m+iroffc, mb_a, 0, 0, nprow ), mb_a, 0, 0, LCMp ), nqc0 ) )*mb_a ) else if side = 'r', numroc( numroc( n+icoffc, nb_a, 0, 0, npcol ), nb_a, 0, 0, LCMq ), mpc0 ) )*nb_a ) end if numroc( numroc( n+icoffc, nb_a, 0, 0, npcol ), nb_a, 0, 0, LCMq ), mpc0 ) )*nb_a ) end if 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 ) ) numroc( numroc( m+iroffc, mb_a, 0, 0, nprow ), mb_a, 0, 0, LCMp ), nqc0 ) )*mb_a ) else if side = 'r', numroc( numroc( m+iroffc, mb_a, 0, 0, nprow ), mb_a, 0, 0, LCMp ), nqc0 ) )*mb_a ) else if side = 'r', numroc( numroc( ni+icoffc, nb_a, 0, 0, npcol ), nb_a, 0, 0, LCMq ), mpc0 ) )*nb_a ) end if numroc( numroc( n+iroffb, mb_a, 0, 0, nprow ), mb_a, 0, 0, LCMp ), nrhsqb0 ) )*mb_a ) end if liwork = locc( n_a + mod(ja-1, nb_a) ) + max( ceil(ceil(locr(m_a)/mb_a)/(LCM/nprow)) where lcm is the least common multiple of process this must be at least 7*ceil( ceil( (i-l)/hbl ) / LCM(nprow,npcol) logical grid size. make sure it's divisible by LCM (we want even workloads! let LCM be the least common multiple of nprow and npcol if( nprow.eq.npcol ) then lwork >= ( nqc0 + max( npv0 + numroc( numroc( n+icoffc, nb_v, 0, 0, npcol ), nb_v, 0, 0, LCMq ) end if lwork >= ( nqc0 + max( npv0 + numroc( numroc( n+icoffc, nb_v, 0, 0, npcol ), nb_v, 0, 0, LCMq ) end if this must be at least 2*ceil( ceil( (i-l)/hbl ) / LCM(nprow,npcol) logical grid size. 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 ), numroc( numroc( ni+icoffc, nb_a, 0, 0, npcol ), nb_a, 0, 0, LCMq ), mpc0 ) )*nb_a ) end if numroc( numroc( ni+icoffc, nb_a, 0, 0, npcol ), nb_a, 0, 0, LCMq ), mpc0 ) )*nb_a ) end if if side = 'l', lwork >= mpc0 + max( max( 1, nqc0 ), numroc( numroc( m+iroffc,mb_a,0,0,nprow ),mb_a,0,0,LCMp ) ) numroc( numroc( m+iroffc, mb_a, 0, 0, nprow ), mb_a, 0, 0, LCMp ), nqc0 ) )*mb_a ) else if side = 'r', numroc( numroc( n+icoffc, nb_a, 0, 0, npcol ), nb_a, 0, 0, LCMq ), mpc0 ) )*nb_a ) end if numroc( numroc( n+icoffc, nb_a, 0, 0, npcol ), nb_a, 0, 0, LCMq ), mpc0 ) )*nb_a ) end if 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 ) ) numroc( numroc( m+iroffc, mb_a, 0, 0, nprow ), mb_a, 0, 0, LCMp ), nqc0 ) )*mb_a ) else if side = 'r', numroc( numroc( m+iroffc, mb_a, 0, 0, nprow ), mb_a, 0, 0, LCMp ), nqc0 ) )*mb_a ) else if side = 'r', numroc( numroc( ni+icoffc, nb_a, 0, 0, npcol ), nb_a, 0, 0, LCMq ), mpc0 ) )*nb_a ) end if |
| LCMP LCMP numroc( numroc( n+iroffb, mb_a, 0, 0, nprow ), mb_a, 0, 0, LCMP ), nrhsqb0 ) )*mb_a ) end if lwork >= ( mpc0 + max( mqv0 + numroc( numroc( m+iroffc, mb_v, 0, 0, nprow ), mb_v, 0, 0, LCMP ) else if side = 'r', lwork >= ( mpc0 + max( mqv0 + numroc( numroc( m+iroffc, mb_v, 0, 0, nprow ), mb_v, 0, 0, LCMP ) else if side = 'r', numroc( numroc( mi+iroffc, mb_a, 0, 0, nprow ), mb_a, 0, 0, LCMP ), nqc0 ) )*mb_a ) else if side = 'r', if side = 'l', lwork >= mpc0 + max( max( 1, nqc0 ), numroc( numroc( m+iroffc,mb_a,0,0,nprow ),mb_a,0,0,LCMP ) ) numroc( numroc( m+iroffc, mb_a, 0, 0, nprow ), mb_a, 0, 0, LCMP ), nqc0 ) )*mb_a ) else if side = 'r', 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 ) ) numroc( numroc( m+iroffc, mb_a, 0, 0, nprow ), mb_a, 0, 0, LCMP ), nqc0 ) )*mb_a ) else if side = 'r', numroc( numroc( m+iroffc, mb_a, 0, 0, nprow ), mb_a, 0, 0, LCMP ), nqc0 ) )*mb_a ) else if side = 'r', numroc( numroc( n+iroffb, mb_a, 0, 0, nprow ), mb_a, 0, 0, LCMP ), nrhsqb0 ) )*mb_a ) end if lwork >= ( mpc0 + max( mqv0 + numroc( numroc( m+iroffc, mb_v, 0, 0, nprow ), mb_v, 0, 0, LCMP ) else if side = 'r', lwork >= ( mpc0 + max( mqv0 + numroc( numroc( m+iroffc, mb_v, 0, 0, nprow ), mb_v, 0, 0, LCMP ) else if side = 'r', numroc( numroc( mi+iroffc, mb_a, 0, 0, nprow ), mb_a, 0, 0, LCMP ), nqc0 ) )*mb_a ) else if side = 'r', if side = 'l', lwork >= mpc0 + max( max( 1, nqc0 ), numroc( numroc( m+iroffc,mb_a,0,0,nprow ),mb_a,0,0,LCMP ) ) numroc( numroc( m+iroffc, mb_a, 0, 0, nprow ), mb_a, 0, 0, LCMP ), nqc0 ) )*mb_a ) else if side = 'r', 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 ) ) numroc( numroc( m+iroffc, mb_a, 0, 0, nprow ), mb_a, 0, 0, LCMP ), nqc0 ) )*mb_a ) else if side = 'r', numroc( numroc( m+iroffc, mb_a, 0, 0, nprow ), mb_a, 0, 0, LCMP ), nqc0 ) )*mb_a ) else if side = 'r', numroc( numroc( n+iroffb, mb_a, 0, 0, nprow ), mb_a, 0, 0, LCMP ), nrhsqb0 ) )*mb_a ) end if lwork >= ( mpc0 + max( mqv0 + numroc( numroc( m+iroffc, mb_v, 0, 0, nprow ), mb_v, 0, 0, LCMP ) else if side = 'r', lwork >= ( mpc0 + max( mqv0 + numroc( numroc( m+iroffc, mb_v, 0, 0, nprow ), mb_v, 0, 0, LCMP ) else if side = 'r', numroc( numroc( mi+iroffc, mb_a, 0, 0, nprow ), mb_a, 0, 0, LCMP ), nqc0 ) )*mb_a ) else if side = 'r', if side = 'l', lwork >= mpc0 + max( max( 1, nqc0 ), numroc( numroc( m+iroffc,mb_a,0,0,nprow ),mb_a,0,0,LCMP ) ) numroc( numroc( m+iroffc, mb_a, 0, 0, nprow ), mb_a, 0, 0, LCMP ), nqc0 ) )*mb_a ) else if side = 'r', 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 ) ) numroc( numroc( m+iroffc, mb_a, 0, 0, nprow ), mb_a, 0, 0, LCMP ), nqc0 ) )*mb_a ) else if side = 'r', numroc( numroc( m+iroffc, mb_a, 0, 0, nprow ), mb_a, 0, 0, LCMP ), nqc0 ) )*mb_a ) else if side = 'r', numroc( numroc( n+iroffb, mb_a, 0, 0, nprow ), mb_a, 0, 0, LCMP ), nrhsqb0 ) )*mb_a ) end if lwork >= ( mpc0 + max( mqv0 + numroc( numroc( m+iroffc, mb_v, 0, 0, nprow ), mb_v, 0, 0, LCMP ) else if side = 'r', lwork >= ( mpc0 + max( mqv0 + numroc( numroc( m+iroffc, mb_v, 0, 0, nprow ), mb_v, 0, 0, LCMP ) else if side = 'r', numroc( numroc( mi+iroffc, mb_a, 0, 0, nprow ), mb_a, 0, 0, LCMP ), nqc0 ) )*mb_a ) else if side = 'r', if side = 'l', lwork >= mpc0 + max( max( 1, nqc0 ), numroc( numroc( m+iroffc,mb_a,0,0,nprow ),mb_a,0,0,LCMP ) ) numroc( numroc( m+iroffc, mb_a, 0, 0, nprow ), mb_a, 0, 0, LCMP ), nqc0 ) )*mb_a ) else if side = 'r', 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 ) ) numroc( numroc( m+iroffc, mb_a, 0, 0, nprow ), mb_a, 0, 0, LCMP ), nqc0 ) )*mb_a ) else if side = 'r', numroc( numroc( m+iroffc, mb_a, 0, 0, nprow ), mb_a, 0, 0, LCMP ), nqc0 ) )*mb_a ) else if side = 'r', |
| LCMQ LCMQ lwork >= ( nqc0 + max( npv0 + numroc( numroc( n+icoffc, nb_v, 0, 0, npcol ), nb_v, 0, 0, LCMQ ) end if lwork >= ( nqc0 + max( npv0 + numroc( numroc( n+icoffc, nb_v, 0, 0, npcol ), nb_v, 0, 0, LCMQ ) end if 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 ), numroc( numroc( ni+icoffc, nb_a, 0, 0, npcol ), nb_a, 0, 0, LCMQ ), mpc0 ) )*nb_a ) end if numroc( numroc( ni+icoffc, nb_a, 0, 0, npcol ), nb_a, 0, 0, LCMQ ), mpc0 ) )*nb_a ) end if numroc( numroc( n+icoffc, nb_a, 0, 0, npcol ), nb_a, 0, 0, LCMQ ), mpc0 ) )*nb_a ) end if numroc( numroc( n+icoffc, nb_a, 0, 0, npcol ), nb_a, 0, 0, LCMQ ), mpc0 ) )*nb_a ) end if numroc( numroc( ni+icoffc, nb_a, 0, 0, npcol ), nb_a, 0, 0, LCMQ ), mpc0 ) )*nb_a ) end if lwork >= ( nqc0 + max( npv0 + numroc( numroc( n+icoffc, nb_v, 0, 0, npcol ), nb_v, 0, 0, LCMQ ) end if lwork >= ( nqc0 + max( npv0 + numroc( numroc( n+icoffc, nb_v, 0, 0, npcol ), nb_v, 0, 0, LCMQ ) end if 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 ), numroc( numroc( ni+icoffc, nb_a, 0, 0, npcol ), nb_a, 0, 0, LCMQ ), mpc0 ) )*nb_a ) end if numroc( numroc( ni+icoffc, nb_a, 0, 0, npcol ), nb_a, 0, 0, LCMQ ), mpc0 ) )*nb_a ) end if numroc( numroc( n+icoffc, nb_a, 0, 0, npcol ), nb_a, 0, 0, LCMQ ), mpc0 ) )*nb_a ) end if numroc( numroc( n+icoffc, nb_a, 0, 0, npcol ), nb_a, 0, 0, LCMQ ), mpc0 ) )*nb_a ) end if numroc( numroc( ni+icoffc, nb_a, 0, 0, npcol ), nb_a, 0, 0, LCMQ ), mpc0 ) )*nb_a ) end if lwork >= ( nqc0 + max( npv0 + numroc( numroc( n+icoffc, nb_v, 0, 0, npcol ), nb_v, 0, 0, LCMQ ) end if lwork >= ( nqc0 + max( npv0 + numroc( numroc( n+icoffc, nb_v, 0, 0, npcol ), nb_v, 0, 0, LCMQ ) end if 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 ), numroc( numroc( ni+icoffc, nb_a, 0, 0, npcol ), nb_a, 0, 0, LCMQ ), mpc0 ) )*nb_a ) end if numroc( numroc( ni+icoffc, nb_a, 0, 0, npcol ), nb_a, 0, 0, LCMQ ), mpc0 ) )*nb_a ) end if numroc( numroc( n+icoffc, nb_a, 0, 0, npcol ), nb_a, 0, 0, LCMQ ), mpc0 ) )*nb_a ) end if numroc( numroc( n+icoffc, nb_a, 0, 0, npcol ), nb_a, 0, 0, LCMQ ), mpc0 ) )*nb_a ) end if numroc( numroc( ni+icoffc, nb_a, 0, 0, npcol ), nb_a, 0, 0, LCMQ ), mpc0 ) )*nb_a ) end if lwork >= ( nqc0 + max( npv0 + numroc( numroc( n+icoffc, nb_v, 0, 0, npcol ), nb_v, 0, 0, LCMQ ) end if lwork >= ( nqc0 + max( npv0 + numroc( numroc( n+icoffc, nb_v, 0, 0, npcol ), nb_v, 0, 0, LCMQ ) end if 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 ), numroc( numroc( ni+icoffc, nb_a, 0, 0, npcol ), nb_a, 0, 0, LCMQ ), mpc0 ) )*nb_a ) end if numroc( numroc( ni+icoffc, nb_a, 0, 0, npcol ), nb_a, 0, 0, LCMQ ), mpc0 ) )*nb_a ) end if numroc( numroc( n+icoffc, nb_a, 0, 0, npcol ), nb_a, 0, 0, LCMQ ), mpc0 ) )*nb_a ) end if numroc( numroc( n+icoffc, nb_a, 0, 0, npcol ), nb_a, 0, 0, LCMQ ), mpc0 ) )*nb_a ) end if numroc( numroc( ni+icoffc, nb_a, 0, 0, npcol ), nb_a, 0, 0, LCMQ ), mpc0 ) )*nb_a ) end if |
| LDA LDA a (global input/output) complex array, (LDA,* the updated matrix on exit. ldt - integer. on entry, LDA specifies the first dimension of a as declare max( 1, n ). a (global input/output) double precision array, (LDA,* the updated matrix on exit. ldt - integer. on entry, LDA specifies the first dimension of a as declare max( 1, n ). a, LDA -> a, ia, ja, desc workspace needs are larger for pcheevx. $ (mod(k-1,hbl) .gt. 1) ) then h11 = a((icol1-3)*LDA+irow1-2 h22 = a((icol1-2)*lda+irow1-1) a, LDA -> a, ia, ja, desc workspace needs are larger for pdsyevx. $ (mod(k-1,hbl) .gt. 1) ) then h11 = a((icol1-3)*LDA+irow1-2 h22 = a((icol1-2)*lda+irow1-1) a, LDA -> a, ia, ja, desc workspace needs are larger for pssyevx. a, LDA -> a, ia, ja, desc workspace needs are larger for pzheevx. a (global input/output) real array, (LDA,* the updated matrix on exit. ldt - integer. on entry, LDA specifies the first dimension of a as declare max( 1, n ). a (global input/output) complex*16 array, (LDA,* the updated matrix on exit. ldt - integer. on entry, LDA specifies the first dimension of a as declare max( 1, n ). |
| LDAB LDAB ab (input/output) complex array, dimension (LDAB,n 2*kl+ku+1; rows 1 to kl of the array need not be set. ab (input/output) double precision array, dimension (LDAB,n 2*kl+ku+1; rows 1 to kl of the array need not be set. ab (input/output) real array, dimension (LDAB,n 2*kl+ku+1; rows 1 to kl of the array need not be set. ab (input/output) complex*16 array, dimension (LDAB,n 2*kl+ku+1; rows 1 to kl of the array need not be set. |
| LDB LDB b (input/output) complex array, dimension (LDB,nrhs on exit, b is overwritten by the solution matrix x. b (input/output) complex array, dimension (LDB,nrhs on exit, the solution matrix x. b (input/output) complex array, dimension (LDB,nrhs on exit, b is overwritten by the solution matrix x. b (input/output) complex array, dimension (LDB,nrhs on exit, the solution matrix x. element (l,ln+1) is swapped with element (j,ln+1) etc furthermore, the elements in the same row are LDB=llda-1 apar data format: b (local input/output) complex array of size (LDB,m a(i:i+m-1,i:i+m-1). element (l,ln+1) is swapped with element (j,ln+1) etc furthermore, the elements in the same row are LDB=llda-1 apar data format: b (local input/output) double precision array of size (LDB,m a(i:i+m-1,i:i+m-1). element (l,ln+1) is swapped with element (j,ln+1) etc furthermore, the elements in the same row are LDB=llda-1 apar data format: b (local input/output) real array of size (LDB,m a(i:i+m-1,i:i+m-1). element (l,ln+1) is swapped with element (j,ln+1) etc furthermore, the elements in the same row are LDB=llda-1 apar data format: b (local input/output) complex*16 array of size (LDB,m a(i:i+m-1,i:i+m-1). b (input/output) complex array, dimension (LDB,nrhs on exit, b is overwritten by the solution matrix x. b (input/output) complex array, dimension (LDB,nrhs on exit, the solution matrix x. b (input/output) complex array, dimension (LDB,nrhs on exit, b is overwritten by the solution matrix x. b (input/output) complex array, dimension (LDB,nrhs on exit, the solution matrix x. |
| LDC LDC qrmem = 2*n-2 lwmin = 5*n + n*LDC + max( sizemqrleft, qrmem ) + variable definitions: qrmem = 2*n-2 lwmin = 5*n + n*LDC + max( sizemqrleft, qrmem ) + variable definitions: |
| LDH LDH h (local input/output) complex array ( LDH,n h should be aligned so that the starting row is 2. h (local input/output) double precision array (LDH,n h should be aligned so that the starting row is 2. if( tst1.eq.zero ) $ tst1 = clanhs( '1', i-l+1, h( l, l ), LDH, work $ go to 30 if( tst1.eq.zero ) $ tst1 = dlanhs( '1', i-l+1, h( l, l ), LDH, work $ go to 30 if( tst1.eq.zero ) $ tst1 = slanhs( '1', i-l+1, h( l, l ), LDH, work $ go to 30 if( tst1.eq.zero ) $ tst1 = zlanhs( '1', i-l+1, h( l, l ), LDH, work $ go to 30 h (local input/output) real array (LDH,n h should be aligned so that the starting row is 2. h (local input/output) complex*16 array ( LDH,n h should be aligned so that the starting row is 2. |
| LDQ LDQ q (input/output) double precision array, dimension (LDQ, n the two square blocks with corners at (1,1), (n1,n1) q (input/output) double precision array, dimension (LDQ, n the two square blocks with corners at (1,1), (n1,n1) q (input/output) real array, dimension (LDQ, n the two square blocks with corners at (1,1), (n1,n1) q (input/output) real array, dimension (LDQ, n the two square blocks with corners at (1,1), (n1,n1) |
| LDQ2 LDQ2 q2 (output) double precision array, dimension (LDQ2, nq q2 (output) real array, dimension (LDQ2, nq |
| LDS LDS s (local input/output) complex array, ( LDS,* is referenced. it is assumed that s has jblk double shifts s (local input/output) double precision array, (LDS,* referenced. it is assumed that s has jblk double shifts s (local input/output) double precision array, dimension LDS on exit, the diagonal blocks of s have been rewritten to pair s (local input/output) real array, (LDS,* referenced. it is assumed that s has jblk double shifts s (local input/output) real array, dimension LDS on exit, the diagonal blocks of s have been rewritten to pair s (local input/output) complex*16 array, ( LDS,* is referenced. it is assumed that s has jblk double shifts |
| LDT LDT t - complex array of dimension ( LDT, n ) upper triangular part of the array t must contain the upper t - double precision array of dimension ( LDT, n ) upper triangular part of the array t must contain the upper t - real array of dimension ( LDT, n ) upper triangular part of the array t must contain the upper t - complex*16 array of dimension ( LDT, n ) upper triangular part of the array t must contain the upper |
| LDU LDU u (global output) double precision array global dimension (n, n), local dimension (LDU, nq) tridiagonal matrix. u (global output) real array global dimension (n, n), local dimension (LDU, nq) tridiagonal matrix. |
| LDW LDW iwork (local workspace) integer array, dimension (LDW transposition, and the storage of the tranposed ipiv: iwork (local workspace) integer array, dimension (LDW transposition, and the storage of the tranposed ipiv: iwork (local workspace) integer array, dimension (LDW transposition, and the storage of the tranposed ipiv: iwork (local workspace) integer array, dimension (LDW transposition, and the storage of the tranposed ipiv: |
| LDZ LDZ z (global input/output) complex array, (LDZ,* this is changed only if wantz is set. z (global input/output) double precision array, (LDZ,* this is changed only if wantz is set. a, lda -> a, ia, ja, desca z, LDZ -> z, iz, jz, desc liwork parameter added a, lda -> a, ia, ja, desca z, LDZ -> z, iz, jz, desc liwork parameter added a, lda -> a, ia, ja, desca z, LDZ -> z, iz, jz, desc liwork parameter added a, lda -> a, ia, ja, desca z, LDZ -> z, iz, jz, desc liwork parameter added z (global input/output) real array, (LDZ,* this is changed only if wantz is set. z (global input/output) complex*16 array, (LDZ,* this is changed only if wantz is set. |
| LDZI LDZI 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 |
| lead lead b (local input/local output) complex pointer into local memory to an array of local lead dimension lld_b>=nb the local pieces of the right hand sides b (local input/local output) complex pointer into local memory to an array of local lead dimension lld_b>=nb the local pieces of the right hand sides b (local input/local output) complex pointer into local memory to an array of local lead dimension lld_b>=nb the local pieces of the right hand sides b (local input/local output) complex pointer into local memory to an array of local lead dimension lld_b>=nb the local pieces of the right hand sides b (local input/local output) complex pointer into local memory to an array of local lead dimension lld_b>=nb the local pieces of the right hand sides b (local input/local output) complex pointer into local memory to an array of local lead dimension lld_b>=nb the local pieces of the right hand sides b (local input/local output) complex pointer into local memory to an array of local lead dimension lld_b>=nb the local pieces of the right hand sides b (local input/local output) complex pointer into local memory to an array of local lead dimension lld_b>=nb the local pieces of the right hand sides b (local input/local output) complex pointer into local memory to an array of local lead dimension lld_b>=nb the local pieces of the right hand sides b (local input/local output) complex pointer into local memory to an array of local lead dimension lld_b>=nb the local pieces of the right hand sides b (local input/local output) double precision pointer into local memory to an array of local lead dimension lld_b>=nb the local pieces of the right hand sides b (local input/local output) double precision pointer into local memory to an array of local lead dimension lld_b>=nb the local pieces of the right hand sides b (local input/local output) double precision pointer into local memory to an array of local lead dimension lld_b>=nb the local pieces of the right hand sides b (local input/local output) double precision pointer into local memory to an array of local lead dimension lld_b>=nb the local pieces of the right hand sides b (local input/local output) double precision pointer into local memory to an array of local lead dimension lld_b>=nb the local pieces of the right hand sides b (local input/local output) double precision pointer into local memory to an array of local lead dimension lld_b>=nb the local pieces of the right hand sides b (local input/local output) double precision pointer into local memory to an array of local lead dimension lld_b>=nb the local pieces of the right hand sides b (local input/local output) double precision pointer into local memory to an array of local lead dimension lld_b>=nb the local pieces of the right hand sides b (local input/local output) double precision pointer into local memory to an array of local lead dimension lld_b>=nb the local pieces of the right hand sides b (local input/local output) double precision pointer into local memory to an array of local lead dimension lld_b>=nb the local pieces of the right hand sides b (local input/local output) real pointer into local memory to an array of local lead dimension lld_b>=nb the local pieces of the right hand sides b (local input/local output) real pointer into local memory to an array of local lead dimension lld_b>=nb the local pieces of the right hand sides b (local input/local output) real pointer into local memory to an array of local lead dimension lld_b>=nb the local pieces of the right hand sides b (local input/local output) real pointer into local memory to an array of local lead dimension lld_b>=nb the local pieces of the right hand sides b (local input/local output) real pointer into local memory to an array of local lead dimension lld_b>=nb the local pieces of the right hand sides b (local input/local output) real pointer into local memory to an array of local lead dimension lld_b>=nb the local pieces of the right hand sides b (local input/local output) real pointer into local memory to an array of local lead dimension lld_b>=nb the local pieces of the right hand sides b (local input/local output) real pointer into local memory to an array of local lead dimension lld_b>=nb the local pieces of the right hand sides b (local input/local output) real pointer into local memory to an array of local lead dimension lld_b>=nb the local pieces of the right hand sides b (local input/local output) real pointer into local memory to an array of local lead dimension lld_b>=nb the local pieces of the right hand sides b (local input/local output) complex*16 pointer into local memory to an array of local lead dimension lld_b>=nb the local pieces of the right hand sides b (local input/local output) complex*16 pointer into local memory to an array of local lead dimension lld_b>=nb the local pieces of the right hand sides b (local input/local output) complex*16 pointer into local memory to an array of local lead dimension lld_b>=nb the local pieces of the right hand sides b (local input/local output) complex*16 pointer into local memory to an array of local lead dimension lld_b>=nb the local pieces of the right hand sides b (local input/local output) complex*16 pointer into local memory to an array of local lead dimension lld_b>=nb the local pieces of the right hand sides b (local input/local output) complex*16 pointer into local memory to an array of local lead dimension lld_b>=nb the local pieces of the right hand sides b (local input/local output) complex*16 pointer into local memory to an array of local lead dimension lld_b>=nb the local pieces of the right hand sides b (local input/local output) complex*16 pointer into local memory to an array of local lead dimension lld_b>=nb the local pieces of the right hand sides b (local input/local output) complex*16 pointer into local memory to an array of local lead dimension lld_b>=nb the local pieces of the right hand sides b (local input/local output) complex*16 pointer into local memory to an array of local lead dimension lld_b>=nb the local pieces of the right hand sides |
| Leading Leading ldab (input) integer the Leading dimension of the array ab. ldab >= 2*kl+ku+1 info (output) integer ldb (input) integer the Leading dimension of the array b. ldb >= max(1,n) info (output) integer lds (local input) integer on entry, the Leading dimension of s. unchanged on exit lda (local input) integer on entry, the Leading dimension of a. unchanged on exit wantz (global input) logical ldb (input) integer the Leading dimension of the array b. ldb >= max(1,n) info (output) integer t - complex array of dimension ( ldt, n ). before entry with uplo = 'u' or 'u', the Leading n by triangular matrix and the strictly lower triangular part of ldab (input) integer the Leading dimension of the array ab. ldab >= 2*kl+ku+1 info (output) integer ldb (input) integer the Leading dimension of the array b. ldb >= max(1,n) info (output) integer lds (local input) integer on entry, the Leading dimension of s. unchanged on exit lda (local input) integer on entry, the Leading dimension of a. unchanged on exit wantz (global input) logical lds (local input) integer on entry, the Leading dimension of the local array s ldb (input) integer the Leading dimension of the array b. ldb >= max(1,n) info (output) integer t - double precision array of dimension ( ldt, n ). before entry with uplo = 'u' or 'u', the Leading n by triangular matrix and the strictly lower triangular part of the matrix a as p a p^t and then factoring the principal Leading submatrix of size equal to the sum of the sizes o these submatrices overwrite the corresponding parts of a the matrix a as p a p^t and then factoring the principal Leading submatrix of size equal to the sum of the sizes o these submatrices overwrite the corresponding parts of a the matrix a as p a p^t and then factoring the principal Leading submatrix of size equal to the sum of the sizes o these submatrices overwrite the corresponding parts of a the matrix a as p a p^t and then factoring the principal Leading submatrix of size equal to the sum of the sizes o these submatrices overwrite the corresponding parts of a the matrix a as p a p^t and then factoring the principal Leading submatrix of size equal to the sum of the sizes o these submatrices overwrite the corresponding parts of a pointer to first element of block bidiagonal matrix in af Leading dimension of block bidiagonal syste the matrix a as p a p^t and then factoring the principal Leading submatrix of size equal to the sum of the sizes o these submatrices overwrite the corresponding parts of a distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca first column of a is distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed matrix a. distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca the matrix a as p a p^t and then factoring the principal Leading submatrix of size equal to the sum of the sizes o these submatrices overwrite the corresponding parts of a the matrix a as p a p^t and then factoring the principal Leading submatrix of size equal to the sum of the sizes o these submatrices overwrite the corresponding parts of a distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca the matrix a as p a p^t and then factoring the principal Leading submatrix of size equal to the sum of the sizes o these submatrices overwrite the corresponding parts of a the matrix a as p a p^t and then factoring the principal Leading submatrix of size equal to the sum of the sizes o these submatrices overwrite the corresponding parts of a distributed. lld_a (local) desca[ lld_ ] the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca the matrix a as p a p^t and then factoring the principal Leading submatrix of size equal to the sum of the sizes o these submatrices overwrite the corresponding parts of a the matrix a as p a p^t and then factoring the principal Leading submatrix of size equal to the sum of the sizes o these submatrices overwrite the corresponding parts of a the matrix a as p a p^t and then factoring the principal Leading submatrix of size equal to the sum of the sizes o these submatrices overwrite the corresponding parts of a the matrix a as p a p^t and then factoring the principal Leading submatrix of size equal to the sum of the sizes o these submatrices overwrite the corresponding parts of a the matrix a as p a p^t and then factoring the principal Leading submatrix of size equal to the sum of the sizes o these submatrices overwrite the corresponding parts of a pointer to first element of block bidiagonal matrix in af Leading dimension of block bidiagonal syste the matrix a as p a p^t and then factoring the principal Leading submatrix of size equal to the sum of the sizes o these submatrices overwrite the corresponding parts of a distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca n1 (input) integer the location of the last eigenvalue in the Leading min(1,n) <= n1 <= n. n1 (input) integer the location of the last eigenvalue in the Leading sub-matrix ldq (input) integer the Leading dimension of the array q. ldq >= max(1,nq) rho (global input/output) double precision distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca the matrix a as p a p^t and then factoring the principal Leading submatrix of size equal to the sum of the sizes o these submatrices overwrite the corresponding parts of a the matrix a as p a p^t and then factoring the principal Leading submatrix of size equal to the sum of the sizes o these submatrices overwrite the corresponding parts of a distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca the matrix a as p a p^t and then factoring the principal Leading submatrix of size equal to the sum of the sizes o these submatrices overwrite the corresponding parts of a the matrix a as p a p^t and then factoring the principal Leading submatrix of size equal to the sum of the sizes o these submatrices overwrite the corresponding parts of a distributed. lld_a (local) desca[ lld_ ] the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca first column of a is distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed matrix a. distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca the matrix a as p a p^t and then factoring the principal Leading submatrix of size equal to the sum of the sizes o these submatrices overwrite the corresponding parts of a the matrix a as p a p^t and then factoring the principal Leading submatrix of size equal to the sum of the sizes o these submatrices overwrite the corresponding parts of a the matrix a as p a p^t and then factoring the principal Leading submatrix of size equal to the sum of the sizes o these submatrices overwrite the corresponding parts of a the matrix a as p a p^t and then factoring the principal Leading submatrix of size equal to the sum of the sizes o these submatrices overwrite the corresponding parts of a the matrix a as p a p^t and then factoring the principal Leading submatrix of size equal to the sum of the sizes o these submatrices overwrite the corresponding parts of a pointer to first element of block bidiagonal matrix in af Leading dimension of block bidiagonal syste the matrix a as p a p^t and then factoring the principal Leading submatrix of size equal to the sum of the sizes o these submatrices overwrite the corresponding parts of a distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca n1 (input) integer the location of the last eigenvalue in the Leading min(1,n) <= n1 <= n. n1 (input) integer the location of the last eigenvalue in the Leading sub-matrix ldq (input) integer the Leading dimension of the array q. ldq >= max(1,nq) rho (global input/output) real distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca the matrix a as p a p^t and then factoring the principal Leading submatrix of size equal to the sum of the sizes o these submatrices overwrite the corresponding parts of a the matrix a as p a p^t and then factoring the principal Leading submatrix of size equal to the sum of the sizes o these submatrices overwrite the corresponding parts of a distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca the matrix a as p a p^t and then factoring the principal Leading submatrix of size equal to the sum of the sizes o these submatrices overwrite the corresponding parts of a the matrix a as p a p^t and then factoring the principal Leading submatrix of size equal to the sum of the sizes o these submatrices overwrite the corresponding parts of a distributed. lld_a (local) desca[ lld_ ] the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca first column of a is distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed matrix a. distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca the matrix a as p a p^t and then factoring the principal Leading submatrix of size equal to the sum of the sizes o these submatrices overwrite the corresponding parts of a the matrix a as p a p^t and then factoring the principal Leading submatrix of size equal to the sum of the sizes o these submatrices overwrite the corresponding parts of a distributed. lld_a (local) desca[ lld_ ] the Leading dimension of the loca the matrix a as p a p^t and then factoring the principal Leading submatrix of size equal to the sum of the sizes o these submatrices overwrite the corresponding parts of a the matrix a as p a p^t and then factoring the principal Leading submatrix of size equal to the sum of the sizes o these submatrices overwrite the corresponding parts of a the matrix a as p a p^t and then factoring the principal Leading submatrix of size equal to the sum of the sizes o these submatrices overwrite the corresponding parts of a pointer to first element of block bidiagonal matrix in af Leading dimension of block bidiagonal syste the matrix a as p a p^t and then factoring the principal Leading submatrix of size equal to the sum of the sizes o these submatrices overwrite the corresponding parts of a distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca first column of a is distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed matrix a. distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca the matrix a as p a p^t and then factoring the principal Leading submatrix of size equal to the sum of the sizes o these submatrices overwrite the corresponding parts of a the matrix a as p a p^t and then factoring the principal Leading submatrix of size equal to the sum of the sizes o these submatrices overwrite the corresponding parts of a distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca the matrix a as p a p^t and then factoring the principal Leading submatrix of size equal to the sum of the sizes o these submatrices overwrite the corresponding parts of a the matrix a as p a p^t and then factoring the principal Leading submatrix of size equal to the sum of the sizes o these submatrices overwrite the corresponding parts of a distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca distributed. lld_a (local) desca( lld_ ) the Leading dimension of the loca ldab (input) integer the Leading dimension of the array ab. ldab >= 2*kl+ku+1 info (output) integer ldb (input) integer the Leading dimension of the array b. ldb >= max(1,n) info (output) integer lds (local input) integer on entry, the Leading dimension of s. unchanged on exit lda (local input) integer on entry, the Leading dimension of a. unchanged on exit wantz (global input) logical lds (local input) integer on entry, the Leading dimension of the local array s ldb (input) integer the Leading dimension of the array b. ldb >= max(1,n) info (output) integer t - real array of dimension ( ldt, n ). before entry with uplo = 'u' or 'u', the Leading n by triangular matrix and the strictly lower triangular part of ldab (input) integer the Leading dimension of the array ab. ldab >= 2*kl+ku+1 info (output) integer ldb (input) integer the Leading dimension of the array b. ldb >= max(1,n) info (output) integer lds (local input) integer on entry, the Leading dimension of s. unchanged on exit lda (local input) integer on entry, the Leading dimension of a. unchanged on exit wantz (global input) logical ldb (input) integer the Leading dimension of the array b. ldb >= max(1,n) info (output) integer t - complex*16 array of dimension ( ldt, n ). before entry with uplo = 'u' or 'u', the Leading n by triangular matrix and the strictly lower triangular part of |
| least least on entry, the size of h. if all the bulges are expected to go through, n should be at least 4*nbulge+2 on entry, n specifies the order of the matrix a. n must be at least zero on entry, the size of h. if all the bulges are expected to go through, n should be at least 4*nbulge+2 on entry, n specifies the order of the matrix a. n must be at least zero the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least max( 2, max(nb_a*ceil(nprow-1,npcol),locc(n+mod(ja-1,nb_a)) + the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least 1. if trans = 'n' and m >= n: find the least squares solution o minimize || sub( b ) - sub( a )*x ||. the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least + locr( n_a ). the dimension of the array work. lwork is local input and must be at least copy of at most an entire column block of sub( a ). the dimension of the array work. lwork is local input and must be at least max( (nb_a*(nb_a-1))/2, (pqb0 + npb0)*nb_a ) + the dimension of the array work. lwork is local input and must be at least max( (mb_a*(mb_a-1))/2, (ppb0 + nqb0)*mb_a ) + the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least on exit, lwork is the size of the work buffer. this must be at least 7*ceil( ceil( (i-l)/hbl ) here lcm is least common multiple, and nprowxnpcol is the the dimension of the array work. lwork is local input and must be at least let lcm be the least common multiple of nprow and npcol if( nprow.eq.npcol ) then on exit, lwork is the size of the work buffer. this must be at least 2*ceil( ceil( (i-l)/hbl ) here lcm is least common multiple, and nprowxnpcol is the where x( i ) = sub( x ) = abs( x( ix+(jx-1)*descx(m_)+(i-1)*incx ) ). the value of sumsq is assumed to be at least unity and the value o x (local input) complex array containing the local pieces of a distributed matrix of dimension of at least this array contains the entries of the distributed vector the dimension of the array work. lwork is local input and must be at least max( 2, max(nb_a*max(1,ceil(p-1,q)),locc(n+mod(ja-1,nb_a)) + the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least + locr( n_a ). containing the local pieces of a distributed matrix of dimension of at least this array contains the entries of the distributed vector the dimension of the array work. lwork is local input and must be at least max( 2, max(nb_a*ceil(p-1,q),locc(n+mod(ja-1,nb_a)) + the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least if side = 'r', lwork >= nqc0 + max( max( 1, mpc0 ), numroc( the dimension of the array work. lwork is local input and must be at least if side = 'r', lwork >= nqc0 + max( max( 1, mpc0 ), numroc( the dimension of the array work. lwork is local input and must be at least nq = m; the dimension of the array work. lwork is local input and must be at least iaa = ia + ilo; jaa = ja+ilo-1; the dimension of the array work. lwork is local input and must be at least numroc( m+iroffc,mb_a,0,0,nprow ),mb_a,0,0,lcmp ) ); the dimension of the array work. lwork is local input and must be at least lwork >= max( (mb_a*(mb_a-1))/2, ( mpc0 + max( mqa0 + the dimension of the array work. lwork is local input and must be at least lwork >= max( (nb_a*(nb_a-1))/2, (nqc0 + mpc0)*nb_a ) + the dimension of the array work. lwork is local input and must be at least lwork >= max( (nb_a*(nb_a-1))/2, (nqc0 + mpc0)*nb_a ) + the dimension of the array work. lwork is local input and must be at least numroc( m+iroffc,mb_a,0,0,nprow ),mb_a,0,0,lcmp ) ); the dimension of the array work. lwork is local input and must be at least numroc( m+iroffc,mb_a,0,0,nprow ),mb_a,0,0,lcmp ) ); the dimension of the array work. lwork is local input and must be at least lwork >= max( (mb_a*(mb_a-1))/2, ( mpc0 + max( mqa0 + the dimension of the array work. lwork is local input and must be at least lwork >= max( (mb_a*(mb_a-1))/2, ( mpc0 + max( mqa0 + the dimension of the array work. lwork is local input and must be at least if uplo = 'u', the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least + max( 2, max( nb_a*max( 1, ceil(nprow-1,npcol) ), the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least 1. if trans = 'n' and m >= n: find the least squares solution o minimize || sub( b ) - sub( a )*x ||. the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least + locr( n_a ). the dimension of the array work. lwork is local input and must be at least copy of at most an entire column block of sub( a ). the dimension of the array work. lwork is local input and must be at least max( (nb_a*(nb_a-1))/2, (pqb0 + npb0)*nb_a ) + the dimension of the array work. lwork is local input and must be at least max( (mb_a*(mb_a-1))/2, (ppb0 + nqb0)*mb_a ) + on exit, lwork is the size of the work buffer. this must be at least 7*ceil( ceil( (i-l)/hbl ) here lcm is least common multiple, and nprowxnpcol is the small, i.e., converged. this must be at least zero reltol (input) double precision small, i.e., converged. note : this must be at least zero reltol (input) double precision the dimension of the array work. lwork is local input and must be at least implementation of the sturm sequence loop. this must be at least max_j |e(j)^2| *safe_min, and at least safe_min, wher without overflow. let lcm be the least common multiple of nprow and npcol if( nprow.eq.npcol ) then on exit, lwork is the size of the work buffer. this must be at least 2*ceil( ceil( (i-l)/hbl ) here lcm is least common multiple, and nprowxnpcol is the the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least if side = 'r', lwork >= nqc0 + max( max( 1, mpc0 ), numroc( the dimension of the array work. lwork is local input and must be at least if side = 'r', lwork >= nqc0 + max( max( 1, mpc0 ), numroc( the dimension of the array work. lwork is local input and must be at least nq = m; the dimension of the array work. lwork is local input and must be at least iaa = ia + ilo; jaa = ja+ilo-1; the dimension of the array work. lwork is local input and must be at least numroc( m+iroffc,mb_a,0,0,nprow ),mb_a,0,0,lcmp ) ); the dimension of the array work. lwork is local input and must be at least lwork >= max( (mb_a*(mb_a-1))/2, ( mpc0 + max( mqa0 + the dimension of the array work. lwork is local input and must be at least lwork >= max( (nb_a*(nb_a-1))/2, (nqc0 + mpc0)*nb_a ) + the dimension of the array work. lwork is local input and must be at least lwork >= max( (nb_a*(nb_a-1))/2, (nqc0 + mpc0)*nb_a ) + the dimension of the array work. lwork is local input and must be at least numroc( m+iroffc,mb_a,0,0,nprow ),mb_a,0,0,lcmp ) ); the dimension of the array work. lwork is local input and must be at least numroc( m+iroffc,mb_a,0,0,nprow ),mb_a,0,0,lcmp ) ); the dimension of the array work. lwork is local input and must be at least lwork >= max( (mb_a*(mb_a-1))/2, ( mpc0 + max( mqa0 + the dimension of the array work. lwork is local input and must be at least lwork >= max( (mb_a*(mb_a-1))/2, ( mpc0 + max( mqa0 + the dimension of the array work. lwork is local input and must be at least if uplo = 'u', the dimension of the array work. lwork is local input and must be at least max( 2, max(nb_a*ceil(nprow-1,npcol),locc(n+mod(ja-1,nb_a)) + the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least + locr( n_a ). containing the local pieces of a distributed matrix of dimension of at least this array contains the entries of the distributed vector if range='i', the index (from smallest to largest) of the smallest eigenvalue to be returned. il must be at least 1 the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least + max( 2, max( nb_a*max( 1, ceil(nprow-1,npcol) ), the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least x (local input) complex*16 array containing the local pieces of a distributed matrix of dimension of at least this array contains the entries of the distributed vector x (local input) complex array containing the local pieces of a distributed matrix of dimension of at least this array contains the entries of the distributed vector the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least + max( 2, max( nb_a*max( 1, ceil(nprow-1,npcol) ), the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least 1. if trans = 'n' and m >= n: find the least squares solution o minimize || sub( b ) - sub( a )*x ||. the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least + locr( n_a ). the dimension of the array work. lwork is local input and must be at least copy of at most an entire column block of sub( a ). the dimension of the array work. lwork is local input and must be at least max( (nb_a*(nb_a-1))/2, (pqb0 + npb0)*nb_a ) + the dimension of the array work. lwork is local input and must be at least max( (mb_a*(mb_a-1))/2, (ppb0 + nqb0)*mb_a ) + on exit, lwork is the size of the work buffer. this must be at least 7*ceil( ceil( (i-l)/hbl ) here lcm is least common multiple, and nprowxnpcol is the small, i.e., converged. this must be at least zero reltol (input) real small, i.e., converged. note : this must be at least zero reltol (input) real the dimension of the array work. lwork is local input and must be at least implementation of the sturm sequence loop. this must be at least max_j |e(j)^2| *safe_min, and at least safe_min, wher without overflow. let lcm be the least common multiple of nprow and npcol if( nprow.eq.npcol ) then on exit, lwork is the size of the work buffer. this must be at least 2*ceil( ceil( (i-l)/hbl ) here lcm is least common multiple, and nprowxnpcol is the the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least if side = 'r', lwork >= nqc0 + max( max( 1, mpc0 ), numroc( the dimension of the array work. lwork is local input and must be at least if side = 'r', lwork >= nqc0 + max( max( 1, mpc0 ), numroc( the dimension of the array work. lwork is local input and must be at least nq = m; the dimension of the array work. lwork is local input and must be at least iaa = ia + ilo; jaa = ja+ilo-1; the dimension of the array work. lwork is local input and must be at least numroc( m+iroffc,mb_a,0,0,nprow ),mb_a,0,0,lcmp ) ); the dimension of the array work. lwork is local input and must be at least lwork >= max( (mb_a*(mb_a-1))/2, ( mpc0 + max( mqa0 + the dimension of the array work. lwork is local input and must be at least lwork >= max( (nb_a*(nb_a-1))/2, (nqc0 + mpc0)*nb_a ) + the dimension of the array work. lwork is local input and must be at least lwork >= max( (nb_a*(nb_a-1))/2, (nqc0 + mpc0)*nb_a ) + the dimension of the array work. lwork is local input and must be at least numroc( m+iroffc,mb_a,0,0,nprow ),mb_a,0,0,lcmp ) ); the dimension of the array work. lwork is local input and must be at least numroc( m+iroffc,mb_a,0,0,nprow ),mb_a,0,0,lcmp ) ); the dimension of the array work. lwork is local input and must be at least lwork >= max( (mb_a*(mb_a-1))/2, ( mpc0 + max( mqa0 + the dimension of the array work. lwork is local input and must be at least lwork >= max( (mb_a*(mb_a-1))/2, ( mpc0 + max( mqa0 + the dimension of the array work. lwork is local input and must be at least if uplo = 'u', the dimension of the array work. lwork is local input and must be at least max( 2, max(nb_a*ceil(nprow-1,npcol),locc(n+mod(ja-1,nb_a)) + the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least + locr( n_a ). containing the local pieces of a distributed matrix of dimension of at least this array contains the entries of the distributed vector if range='i', the index (from smallest to largest) of the smallest eigenvalue to be returned. il must be at least 1 the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least + max( 2, max( nb_a*max( 1, ceil(nprow-1,npcol) ), the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least containing the local pieces of a distributed matrix of dimension of at least this array contains the entries of the distributed vector the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least max( 2, max(nb_a*ceil(nprow-1,npcol),locc(n+mod(ja-1,nb_a)) + the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least 1. if trans = 'n' and m >= n: find the least squares solution o minimize || sub( b ) - sub( a )*x ||. the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least + locr( n_a ). the dimension of the array work. lwork is local input and must be at least copy of at most an entire column block of sub( a ). the dimension of the array work. lwork is local input and must be at least max( (nb_a*(nb_a-1))/2, (pqb0 + npb0)*nb_a ) + the dimension of the array work. lwork is local input and must be at least max( (mb_a*(mb_a-1))/2, (ppb0 + nqb0)*mb_a ) + the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least on exit, lwork is the size of the work buffer. this must be at least 7*ceil( ceil( (i-l)/hbl ) here lcm is least common multiple, and nprowxnpcol is the the dimension of the array work. lwork is local input and must be at least let lcm be the least common multiple of nprow and npcol if( nprow.eq.npcol ) then on exit, lwork is the size of the work buffer. this must be at least 2*ceil( ceil( (i-l)/hbl ) here lcm is least common multiple, and nprowxnpcol is the where x( i ) = sub( x ) = abs( x( ix+(jx-1)*descx(m_)+(i-1)*incx ) ). the value of sumsq is assumed to be at least unity and the value o x (local input) complex*16 array containing the local pieces of a distributed matrix of dimension of at least this array contains the entries of the distributed vector the dimension of the array work. lwork is local input and must be at least max( 2, max(nb_a*max(1,ceil(p-1,q)),locc(n+mod(ja-1,nb_a)) + the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least + locr( n_a ). the dimension of the array work. lwork is local input and must be at least max( 2, max(nb_a*ceil(p-1,q),locc(n+mod(ja-1,nb_a)) + the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least the dimension of the array work. lwork is local input and must be at least if side = 'r', lwork >= nqc0 + max( max( 1, mpc0 ), numroc( the dimension of the array work. lwork is local input and must be at least if side = 'r', lwork >= nqc0 + max( max( 1, mpc0 ), numroc( the dimension of the array work. lwork is local input and must be at least nq = m; the dimension of the array work. lwork is local input and must be at least iaa = ia + ilo; jaa = ja+ilo-1; the dimension of the array work. lwork is local input and must be at least numroc( m+iroffc,mb_a,0,0,nprow ),mb_a,0,0,lcmp ) ); the dimension of the array work. lwork is local input and must be at least lwork >= max( (mb_a*(mb_a-1))/2, ( mpc0 + max( mqa0 + the dimension of the array work. lwork is local input and must be at least lwork >= max( (nb_a*(nb_a-1))/2, (nqc0 + mpc0)*nb_a ) + the dimension of the array work. lwork is local input and must be at least lwork >= max( (nb_a*(nb_a-1))/2, (nqc0 + mpc0)*nb_a ) + the dimension of the array work. lwork is local input and must be at least numroc( m+iroffc,mb_a,0,0,nprow ),mb_a,0,0,lcmp ) ); the dimension of the array work. lwork is local input and must be at least numroc( m+iroffc,mb_a,0,0,nprow ),mb_a,0,0,lcmp ) ); the dimension of the array work. lwork is local input and must be at least lwork >= max( (mb_a*(mb_a-1))/2, ( mpc0 + max( mqa0 + the dimension of the array work. lwork is local input and must be at least lwork >= max( (mb_a*(mb_a-1))/2, ( mpc0 + max( mqa0 + the dimension of the array work. lwork is local input and must be at least if uplo = 'u', on entry, the size of h. if all the bulges are expected to go through, n should be at least 4*nbulge+2 on entry, n specifies the order of the matrix a. n must be at least zero on entry, the size of h. if all the bulges are expected to go through, n should be at least 4*nbulge+2 on entry, n specifies the order of the matrix a. n must be at least zero |
| left left the first iteration of this loop determines a reflection g from the vector v and applies it from left and right to h if 'r': apply reflectors to the rows of the matrix (apply from left unchanged on exit. if 'r': apply reflectors to the rows of the matrix (apply from left unchanged on exit. receive and add contribution to diagonal block from the left receive and add contribution to righthand sides from left receive and add contribution to diagonal block from the left receive and add contribution to righthand sides from left backsolve left sid pcgesvd computes the singular value decomposition (svd) of an m-by-n matrix a, optionally computing the left and/or righ if equed = 'r' or 'b', a(ia:ia+n-1,ja:ja+n-1) is multiplied on the left by diag(r); if equed='n' or 'c', r is not acces an output variable. ltli: lower triangular local index i: the local row for the upper left entry in tril( a(index, index) upper left entry in tril( a(index+1, index+1) ) values: a buffer to send diagonally down and right, a buffer to send up, a buffer to send left, a buffer to send diagonall is actually stored in one buffer buf where buf(istr1+1) starts transpose q**h to a complex m-by-n distributed matrix sub( c ) denoting c(ic:ic+m-1,jc:jc+n-1), from the left or the right notes transpose q**h to a complex m-by-n distributed matrix sub( c ) denoting c(ic:ic+m-1,jc:jc+n-1), from the left or the right q is a product of k elementary reflectors as returned by pctzrzf. pclatra computes the trace of an n-by-n distributed matrix sub( a ) denoting a( ia:ia+n-1, ja:ja+n-1 ). the result is left on ever receive and add contribution to diagonal block from the left receive and add contribution to righthand sides from left receive and add contribution to diagonal block from the left receive and add contribution to righthand sides from left pctrevc computes some or all of the right and/or left eigenvectors o side (global input) character = 'l': apply q or q**h from the left side (global input) character = 'l': apply q or q**h from the left side (global input) character = 'l': apply q, q**h, p or p**h from the left side (global input) character = 'l': apply q or q**h from the left side (global input) character = 'l': apply q or q**h from the left side (global input) character = 'l': apply q or q**h from the left side (global input) character = 'l': apply q or q**h from the left side (global input) character = 'l': apply q or q**h from the left side (global input) character = 'l': apply q or q**h from the left side (global input) character = 'l': apply q or q**h from the left side (global input) character = 'l': apply q or q**h from the left side (global input) character = 'l': apply q or q**h from the left side (global input) character = 'l': apply q or q**h from the left receive and add contribution to diagonal block from the left receive and add contribution to righthand sides from left receive and add contribution to diagonal block from the left receive and add contribution to righthand sides from left backsolve left sid pdgesvd computes the singular value decomposition (svd) of an m-by-n matrix a, optionally computing the left and/or righ if equed = 'r' or 'b', a(ia:ia+n-1,ja:ja+n-1) is multiplied on the left by diag(r); if equed='n' or 'c', r is not acces an output variable. values: a buffer to send diagonally down and right, a buffer to send up, a buffer to send left, a buffer to send diagonall is actually stored in one buffer buf where buf(istr1+1) starts intvl (input/output) double precision array, dimension (2*mmax) the endpoints of the intervals. intvl(2*j-1) is the left endpoint of the j-th interval. the input intervals will, intvl (input/output) double precision array, dimension (2*(kl-kf)) the endpoints of the intervals. intvl(2*j-1) is the left endpoint of the j-th interval. the input intervals will, real distributed m-by-n matrix sub( c ) = c(ic:ic+m-1,jc:jc+n-1) from the left or the right notes a real distributed m-by-n matrix sub( c ) = c(ic:ic+m-1,jc:jc+n-1) from the left or the right q is a product of k elementary reflectors as returned by pdtzrzf. pdlatra computes the trace of an n-by-n distributed matrix sub( a ) denoting a( ia:ia+n-1, ja:ja+n-1 ). the result is left on ever side (global input) character = 'l': apply q or q**t from the left side (global input) character = 'l': apply q or q**t from the left side (global input) character = 'l': apply q, q**t, p or p**t from the left side (global input) character = 'l': apply q or q**t from the left side (global input) character = 'l': apply q or q**t from the left side (global input) character = 'l': apply q or q**t from the left side (global input) character = 'l': apply q or q**t from the left side (global input) character = 'l': apply q or q**t from the left side (global input) character = 'l': apply q or q**t from the left side (global input) character = 'l': apply q or q**t from the left side (global input) character = 'l': apply q or q**t from the left side (global input) character = 'l': apply q or q**t from the left side (global input) character = 'l': apply q or q**t from the left receive and add contribution to diagonal block from the left receive and add contribution to righthand sides from left receive and add contribution to diagonal block from the left receive and add contribution to righthand sides from left ltli: lower triangular local index i: the local row for the upper left entry in tril( a(index, index) upper left entry in tril( a(index+1, index+1) ) receive and add contribution to diagonal block from the left receive and add contribution to righthand sides from left receive and add contribution to diagonal block from the left receive and add contribution to righthand sides from left backsolve left sid psgesvd computes the singular value decomposition (svd) of an m-by-n matrix a, optionally computing the left and/or righ if equed = 'r' or 'b', a(ia:ia+n-1,ja:ja+n-1) is multiplied on the left by diag(r); if equed='n' or 'c', r is not acces an output variable. values: a buffer to send diagonally down and right, a buffer to send up, a buffer to send left, a buffer to send diagonall is actually stored in one buffer buf where buf(istr1+1) starts intvl (input/output) real array, dimension (2*mmax) the endpoints of the intervals. intvl(2*j-1) is the left endpoint of the j-th interval. the input intervals will, intvl (input/output) real array, dimension (2*(kl-kf)) the endpoints of the intervals. intvl(2*j-1) is the left endpoint of the j-th interval. the input intervals will, real distributed m-by-n matrix sub( c ) = c(ic:ic+m-1,jc:jc+n-1) from the left or the right notes a real distributed m-by-n matrix sub( c ) = c(ic:ic+m-1,jc:jc+n-1) from the left or the right q is a product of k elementary reflectors as returned by pstzrzf. pslatra computes the trace of an n-by-n distributed matrix sub( a ) denoting a( ia:ia+n-1, ja:ja+n-1 ). the result is left on ever side (global input) character = 'l': apply q or q**t from the left side (global input) character = 'l': apply q or q**t from the left side (global input) character = 'l': apply q, q**t, p or p**t from the left side (global input) character = 'l': apply q or q**t from the left side (global input) character = 'l': apply q or q**t from the left side (global input) character = 'l': apply q or q**t from the left side (global input) character = 'l': apply q or q**t from the left side (global input) character = 'l': apply q or q**t from the left side (global input) character = 'l': apply q or q**t from the left side (global input) character = 'l': apply q or q**t from the left side (global input) character = 'l': apply q or q**t from the left side (global input) character = 'l': apply q or q**t from the left side (global input) character = 'l': apply q or q**t from the left receive and add contribution to diagonal block from the left receive and add contribution to righthand sides from left receive and add contribution to diagonal block from the left receive and add contribution to righthand sides from left ltli: lower triangular local index i: the local row for the upper left entry in tril( a(index, index) upper left entry in tril( a(index+1, index+1) ) receive and add contribution to diagonal block from the left receive and add contribution to righthand sides from left receive and add contribution to diagonal block from the left receive and add contribution to righthand sides from left backsolve left sid pzgesvd computes the singular value decomposition (svd) of an m-by-n matrix a, optionally computing the left and/or righ if equed = 'r' or 'b', a(ia:ia+n-1,ja:ja+n-1) is multiplied on the left by diag(r); if equed='n' or 'c', r is not acces an output variable. ltli: lower triangular local index i: the local row for the upper left entry in tril( a(index, index) upper left entry in tril( a(index+1, index+1) ) values: a buffer to send diagonally down and right, a buffer to send up, a buffer to send left, a buffer to send diagonall is actually stored in one buffer buf where buf(istr1+1) starts transpose q**h to a complex m-by-n distributed matrix sub( c ) denoting c(ic:ic+m-1,jc:jc+n-1), from the left or the right notes transpose q**h to a complex m-by-n distributed matrix sub( c ) denoting c(ic:ic+m-1,jc:jc+n-1), from the left or the right q is a product of k elementary reflectors as returned by pztzrzf. pzlatra computes the trace of an n-by-n distributed matrix sub( a ) denoting a( ia:ia+n-1, ja:ja+n-1 ). the result is left on ever receive and add contribution to diagonal block from the left receive and add contribution to righthand sides from left receive and add contribution to diagonal block from the left receive and add contribution to righthand sides from left pztrevc computes some or all of the right and/or left eigenvectors o side (global input) character = 'l': apply q or q**h from the left side (global input) character = 'l': apply q or q**h from the left side (global input) character = 'l': apply q, q**h, p or p**h from the left side (global input) character = 'l': apply q or q**h from the left side (global input) character = 'l': apply q or q**h from the left side (global input) character = 'l': apply q or q**h from the left side (global input) character = 'l': apply q or q**h from the left side (global input) character = 'l': apply q or q**h from the left side (global input) character = 'l': apply q or q**h from the left side (global input) character = 'l': apply q or q**h from the left side (global input) character = 'l': apply q or q**h from the left side (global input) character = 'l': apply q or q**h from the left side (global input) character = 'l': apply q or q**h from the left if 'r': apply reflectors to the rows of the matrix (apply from left unchanged on exit. the first iteration of this loop determines a reflection g from the vector v and applies it from left and right to h if 'r': apply reflectors to the rows of the matrix (apply from left unchanged on exit. |
| LEND LEND scale submatrix in rows and columns l to LEND scale submatrix in rows and columns l to LEND |
| length length pclacgv conjugates a complex vector of length n, sub( x ), wher x(ix:ix+n-1,jx) if incx = 1, and n (global input) integer the length of the distributed vectors v and x. n >= 0 v (local workspace) complex pointer into the local n (global input) integer the length of the distributed vector sub( x ) x (input) complex n (global input) integer if rowcol = 'r', the length of the rows of the distribute if rowcol = 'c', the length of the columns of the distributed n (global input) integer the length of the distributed vectors v and x. n >= 0 v (local workspace) double precision pointer into the local where z = q'u, u is a vector of length n with ones in th n (global input) integer the length of the distributed vector sub( x ) x (input) double precision n (global input) integer if rowcol = 'r', the length of the rows of the distribute if rowcol = 'c', the length of the columns of the distributed n (global input) integer the length of the distributed vectors v and x. n >= 0 v (local workspace) real pointer into the local where z = q'u, u is a vector of length n with ones in th n (global input) integer the length of the distributed vector sub( x ) x (input) real n (global input) integer if rowcol = 'r', the length of the rows of the distribute if rowcol = 'c', the length of the columns of the distributed pzlacgv conjugates a complex vector of length n, sub( x ), wher x(ix:ix+n-1,jx) if incx = 1, and n (global input) integer the length of the distributed vectors v and x. n >= 0 v (local workspace) complex*16 pointer into the local n (global input) integer the length of the distributed vector sub( x ) x (input) complex*16 n (global input) integer if rowcol = 'r', the length of the rows of the distribute if rowcol = 'c', the length of the columns of the distributed |
| less less on entry, the number of bulges to send through h ( >1 ). nbulge should be less than the maximum determined (jblk) on exit, the maximum number of bulges that can be sent on entry, the number of bulges to send through h ( >1 ). nbulge should be less than the maximum determined (jblk) on exit, the maximum number of bulges that can be sent lm is the number of rows which is usually nb except for mycol = 0 where it is bwu less and mycol=npcol-1 where i finally aptr is the pointer to the first element of a. as lapack of the matrix a. if the reciprocal of the condition number is less than machine precision, steps 4-6 are skipped 4. the system of equations is solved for x using the factored form when it is determined to lie in an interval [a,b] of width less than or equal t abstol + eps * max( |a|,|b| ) , when it is determined to lie in an interval [a,b] of width less than or equal t abstol + eps * max( |a|,|b| ) , scale x so that its components are less than or equal t of the matrix a. if the reciprocal of the condition number is less than machine precision, steps 4-6 are skipped 4. the system of equations is solved for x using the factored form lm is the number of rows which is usually nb except for mycol = 0 where it is bwu less and mycol=npcol-1 where i finally aptr is the pointer to the first element of a. as lapack of the matrix a. if the reciprocal of the condition number is less than machine precision, steps 4-6 are skipped 4. the system of equations is solved for x using the factored form j = 1,...,minp. it uses and computes the function n(w), which is the count of eigenvalues of a symmetric tridiagonal matrix less tha sigma (input) double precision the shift. pdlapdct finds the number of eigenvalues of t less of the matrix a. if the reciprocal of the condition number is less than machine precision, steps 4-6 are skipped 4. the system of equations is solved for x using the factored form if range='v', the lower bound of the interval to be searched for eigenvalues. eigenvalues less than vl will not b when it is determined to lie in an interval [a,b] of width less than or equal t abstol + eps * max( |a|,|b| ) , when it is determined to lie in an interval [a,b] of width less than or equal t abstol + eps * max( |a|,|b| ) , lm is the number of rows which is usually nb except for mycol = 0 where it is bwu less and mycol=npcol-1 where i finally aptr is the pointer to the first element of a. as lapack of the matrix a. if the reciprocal of the condition number is less than machine precision, steps 4-6 are skipped 4. the system of equations is solved for x using the factored form j = 1,...,minp. it uses and computes the function n(w), which is the count of eigenvalues of a symmetric tridiagonal matrix less tha sigma (input) real the shift. pslapdct finds the number of eigenvalues of t less of the matrix a. if the reciprocal of the condition number is less than machine precision, steps 4-6 are skipped 4. the system of equations is solved for x using the factored form if range='v', the lower bound of the interval to be searched for eigenvalues. eigenvalues less than vl will not b when it is determined to lie in an interval [a,b] of width less than or equal t abstol + eps * max( |a|,|b| ) , when it is determined to lie in an interval [a,b] of width less than or equal t abstol + eps * max( |a|,|b| ) , lm is the number of rows which is usually nb except for mycol = 0 where it is bwu less and mycol=npcol-1 where i finally aptr is the pointer to the first element of a. as lapack of the matrix a. if the reciprocal of the condition number is less than machine precision, steps 4-6 are skipped 4. the system of equations is solved for x using the factored form when it is determined to lie in an interval [a,b] of width less than or equal t abstol + eps * max( |a|,|b| ) , when it is determined to lie in an interval [a,b] of width less than or equal t abstol + eps * max( |a|,|b| ) , scale x so that its components are less than or equal t of the matrix a. if the reciprocal of the condition number is less than machine precision, steps 4-6 are skipped 4. the system of equations is solved for x using the factored form on entry, the number of bulges to send through h ( >1 ). nbulge should be less than the maximum determined (jblk) on exit, the maximum number of bulges that can be sent on entry, the number of bulges to send through h ( >1 ). nbulge should be less than the maximum determined (jblk) on exit, the maximum number of bulges that can be sent |
| Let Let diagonally dominant-like, and the factorization was not compLeted info-nprocs representing interactions with other Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as diagonally dominant-like, and the factorization was not compLeted info-nprocs representing interactions with other Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as nonsingular, and the factorization was not compLeted info-nprocs representing interactions with other Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as in the following comments, the character _ should be read as "of the distributed matrix". Let a be a generic term for any 2 Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distribute such a global array has an associated description vector desca. Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as positive definite, and the factorization was not compLeted info-nprocs representing interactions with other Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as positive definite, and the factorization was not compLeted info-nprocs representing interactions with other Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let nq = m if side = 'l' and nq = n if side = 'r'. thus nq is th Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as diagonally dominant-like, and the factorization was not compLeted info-nprocs representing interactions with other Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as diagonally dominant-like, and the factorization was not compLeted info-nprocs representing interactions with other Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as nonsingular, and the factorization was not compLeted info-nprocs representing interactions with other Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let nq = m if side = 'l' and nq = n if side = 'r'. thus nq is th Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as positive definite, and the factorization was not compLeted info-nprocs representing interactions with other Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as positive definite, and the factorization was not compLeted info-nprocs representing interactions with other Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as in the following comments, the character _ should be read as "of the distributed matrix". Let a be a generic term for any 2 Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distribute such a global array has an associated description vector desca. Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as diagonally dominant-like, and the factorization was not compLeted info-nprocs representing interactions with other Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as diagonally dominant-like, and the factorization was not compLeted info-nprocs representing interactions with other Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as nonsingular, and the factorization was not compLeted info-nprocs representing interactions with other Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let nq = m if side = 'l' and nq = n if side = 'r'. thus nq is th Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as positive definite, and the factorization was not compLeted info-nprocs representing interactions with other Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as positive definite, and the factorization was not compLeted info-nprocs representing interactions with other Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as in the following comments, the character _ should be read as "of the distributed matrix". Let a be a generic term for any 2 Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distribute such a global array has an associated description vector desca. Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as diagonally dominant-like, and the factorization was not compLeted info-nprocs representing interactions with other Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as diagonally dominant-like, and the factorization was not compLeted info-nprocs representing interactions with other Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as nonsingular, and the factorization was not compLeted info-nprocs representing interactions with other Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as in the following comments, the character _ should be read as "of the distributed matrix". Let a be a generic term for any 2 Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distribute such a global array has an associated description vector desca. Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as positive definite, and the factorization was not compLeted info-nprocs representing interactions with other Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as positive definite, and the factorization was not compLeted info-nprocs representing interactions with other Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let nq = m if side = 'l' and nq = n if side = 'r'. thus nq is th Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as Let a be a generic term for any 2d block cyclicly distributed array in the following comments, the character _ should be read as |
| level level this is the unblocked version of the algorithm, calling level 2 blas arguments level 2 blas routine this is the unblocked version of the algorithm, calling level 2 blas arguments level 2 blas routine the distance for sending and receiving for each level start the distance for sending and receiving for each level start the distance for sending and receiving for each level start the distance for sending and receiving for each level start in this case the loop over the levels will not b this is the right-looking parallel level 2 blas version of th this is the right-looking parallel level 3 blas version of th compute a bound on the computed solution vector to see if the level 2 pblas routine pctrsv can be used this is the unblocked form of the algorithm, calling level 2 blas on should be strictly local to one process. this is the blocked form of the algorithm, calling level 3 pblas notes based on pcamax from level 1 pblas. the change is to use th the distance for sending and receiving for each level start the distance for sending and receiving for each level start the distance for sending and receiving for each level start the distance for sending and receiving for each level start the distance for sending and receiving for each level start the distance for sending and receiving for each level start the distance for sending and receiving for each level start the distance for sending and receiving for each level start in this case the loop over the levels will not b this is the right-looking parallel level 2 blas version of th this is the right-looking parallel level 3 blas version of th this is the unblocked form of the algorithm, calling level 2 blas on should be strictly local to one process. this is the blocked form of the algorithm, calling level 3 pblas notes the distance for sending and receiving for each level start the distance for sending and receiving for each level start the distance for sending and receiving for each level start the distance for sending and receiving for each level start based on pdzasum from the level 1 pblas. the change i based on pscasum from the level 1 pblas. the change i the distance for sending and receiving for each level start the distance for sending and receiving for each level start the distance for sending and receiving for each level start the distance for sending and receiving for each level start in this case the loop over the levels will not b this is the right-looking parallel level 2 blas version of th this is the right-looking parallel level 3 blas version of th this is the unblocked form of the algorithm, calling level 2 blas on should be strictly local to one process. this is the blocked form of the algorithm, calling level 3 pblas notes the distance for sending and receiving for each level start the distance for sending and receiving for each level start the distance for sending and receiving for each level start the distance for sending and receiving for each level start the distance for sending and receiving for each level start the distance for sending and receiving for each level start the distance for sending and receiving for each level start the distance for sending and receiving for each level start in this case the loop over the levels will not b this is the right-looking parallel level 2 blas version of th this is the right-looking parallel level 3 blas version of th compute a bound on the computed solution vector to see if the level 2 pblas routine pztrsv can be used this is the unblocked form of the algorithm, calling level 2 blas on should be strictly local to one process. this is the blocked form of the algorithm, calling level 3 pblas notes based on pzamax from level 1 pblas. the change is to use th the distance for sending and receiving for each level start the distance for sending and receiving for each level start the distance for sending and receiving for each level start the distance for sending and receiving for each level start this is the unblocked version of the algorithm, calling level 2 blas arguments level 2 blas routine this is the unblocked version of the algorithm, calling level 2 blas arguments level 2 blas routine |
| level_dist level_dist end of "if( mycol/level_dist .le. (npcol-1)/level_dist-2 )... ************ end of "if( mycol/level_dist .le. (npcol-1)/level_dist-2 )... end of "if( mycol/level_dist .le. (npcol-1)/level_dist-2 )... ************ end of "if( mycol/level_dist .le. (npcol-1)/level_dist-2 )... end of "if( mycol/level_dist .le. (npcol-1)/level_dist-2 )... ************ end of "if( mycol/level_dist .le. (npcol-1)/level_dist-2 )... end of "if( mycol/level_dist .le. (npcol-1)/level_dist-2 )... ************ end of "if( mycol/level_dist .le. (npcol-1)/level_dist-2 )... ************ end of "if( mycol/level_dist .le. (npcol-1)/level_dist-2 )... end of "if( mycol/level_dist .le. (npcol-1)/level_dist-2 )... ************ end of "if( mycol/level_dist .le. (npcol-1)/level_dist-2 )... end of "if( mycol/level_dist .le. (npcol-1)/level_dist-2 )... ************ end of "if( mycol/level_dist .le. (npcol-1)/level_dist-2 )... end of "if( mycol/level_dist .le. (npcol-1)/level_dist-2 )... ************ end of "if( mycol/level_dist .le. (npcol-1)/level_dist-2 )... ************ end of "if( mycol/level_dist .le. (npcol-1)/level_dist-2 )... end of "if( mycol/level_dist .le. (npcol-1)/level_dist-2 )... ************ end of "if( mycol/level_dist .le. (npcol-1)/level_dist-2 )... end of "if( mycol/level_dist .le. (npcol-1)/level_dist-2 )... ************ end of "if( mycol/level_dist .le. (npcol-1)/level_dist-2 )... end of "if( mycol/level_dist .le. (npcol-1)/level_dist-2 )... ************ end of "if( mycol/level_dist .le. (npcol-1)/level_dist-2 )... ************ end of "if( mycol/level_dist .le. (npcol-1)/level_dist-2 )... end of "if( mycol/level_dist .le. (npcol-1)/level_dist-2 )... ************ end of "if( mycol/level_dist .le. (npcol-1)/level_dist-2 )... end of "if( mycol/level_dist .le. (npcol-1)/level_dist-2 )... ************ end of "if( mycol/level_dist .le. (npcol-1)/level_dist-2 )... end of "if( mycol/level_dist .le. (npcol-1)/level_dist-2 )... ************ |
| levels levels in this case the loop over the levels will not b in this case the loop over the levels will not b in this case the loop over the levels will not b in this case the loop over the levels will not b |
| lie lie of columns are jb, j2, j3. the superdiagonal elements of a13 and the subdiagonal elements of a31 lie outside the band of columns are jb, j2, j3. the superdiagonal elements of a13 and the subdiagonal elements of a31 lie outside the band an approximate eigenvalue is accepted as converged when it is determined to lie in an interval [a,b an approximate eigenvalue is accepted as converged when it is determined to lie in an interval [a,b (or cluster) is considered to be located if it has been determined to lie in an interval whose width is abstol o will be used, where |t| means the 1-norm of t. an approximate eigenvalue is accepted as converged when it is determined to lie in an interval [a,b an approximate eigenvalue is accepted as converged when it is determined to lie in an interval [a,b (or cluster) is considered to be located if it has been determined to lie in an interval whose width is abstol o will be used, where |t| means the 1-norm of t. an approximate eigenvalue is accepted as converged when it is determined to lie in an interval [a,b an approximate eigenvalue is accepted as converged when it is determined to lie in an interval [a,b an approximate eigenvalue is accepted as converged when it is determined to lie in an interval [a,b an approximate eigenvalue is accepted as converged when it is determined to lie in an interval [a,b of columns are jb, j2, j3. the superdiagonal elements of a13 and the subdiagonal elements of a31 lie outside the band of columns are jb, j2, j3. the superdiagonal elements of a13 and the subdiagonal elements of a31 lie outside the band |
| lies lies relfac double precision, default = 2.0 the relative tolerance. an interval [a,b] lies withi where "ulp" is the machine precision (distance from 1 to relfac real, default = 2.0 the relative tolerance. an interval [a,b] lies withi where "ulp" is the machine precision (distance from 1 to |
| LIHIZ LIHIZ liloz LIHIZ (local input) intege when wantz is set. liloz LIHIZ (local input) intege when wantz is set. liloz LIHIZ (local input) intege when wantz is set. liloz LIHIZ (local input) intege when wantz is set. |
| LII LII column in the trailing block of a. LIIb, lijb: the first row, column i the following variables point into the arrays a, v, h, v^t, h^t: column in the trailing block of a. LIIb, lijb: the first row, column i the following variables point into the arrays a, v, h, v^t, h^t: column in the trailing block of a. LIIb, lijb: the first row, column i the following variables point into the arrays a, v, h, v^t, h^t: column in the trailing block of a. LIIb, lijb: the first row, column i the following variables point into the arrays a, v, h, v^t, h^t: |
| LIIB LIIB column in the trailing block of a. LIIB, lijb: the first row, column i the following variables point into the arrays a, v, h, v^t, h^t: column in the trailing block of a. LIIB, lijb: the first row, column i the following variables point into the arrays a, v, h, v^t, h^t: column in the trailing block of a. LIIB, lijb: the first row, column i the following variables point into the arrays a, v, h, v^t, h^t: column in the trailing block of a. LIIB, lijb: the first row, column i the following variables point into the arrays a, v, h, v^t, h^t: |
| LIIP1 LIIP1 lij: local index j: the local column number for column index LIIP1: local index i+1: the local row number for row index+ ltli: lower triangular local index i: the local row for the lij: local index j: the local column number for column index LIIP1: local index i+1: the local row number for row index+ ltli: lower triangular local index i: the local row for the lij: local index j: the local column number for column index LIIP1: local index i+1: the local row number for row index+ ltli: lower triangular local index i: the local row for the lij: local index j: the local column number for column index LIIP1: local index i+1: the local row number for row index+ ltli: lower triangular local index i: the local row for the |
| LIJ LIJ column in the trailing block of a. liib, LIJb: the first row, column i the following variables point into the arrays a, v, h, v^t, h^t: column in the trailing block of a. liib, LIJb: the first row, column i the following variables point into the arrays a, v, h, v^t, h^t: column in the trailing block of a. liib, LIJb: the first row, column i the following variables point into the arrays a, v, h, v^t, h^t: column in the trailing block of a. liib, LIJb: the first row, column i the following variables point into the arrays a, v, h, v^t, h^t: |
| LIJB LIJB column in the trailing block of a. liib, LIJB: the first row, column i the following variables point into the arrays a, v, h, v^t, h^t: column in the trailing block of a. liib, LIJB: the first row, column i the following variables point into the arrays a, v, h, v^t, h^t: column in the trailing block of a. liib, LIJB: the first row, column i the following variables point into the arrays a, v, h, v^t, h^t: column in the trailing block of a. liib, LIJB: the first row, column i the following variables point into the arrays a, v, h, v^t, h^t: |
| LIJP1 LIJP1 liip1: local index i+1: the local row number for row index+1 LIJP1: local index j+1: the local col number for col index+ upper left entry in tril( a(index, index) ) liip1: local index i+1: the local row number for row index+1 LIJP1: local index j+1: the local col number for col index+ upper left entry in tril( a(index, index) ) liip1: local index i+1: the local row number for row index+1 LIJP1: local index j+1: the local col number for col index+ upper left entry in tril( a(index, index) ) liip1: local index i+1: the local row number for row index+1 LIJP1: local index j+1: the local col number for col index+ upper left entry in tril( a(index, index) ) |
| like like where a(1:n, ja:ja+n-1) is an n-by-n complex banded diagonally dominant-like distribute a(1:n, ja:ja+n-1) is an n-by-n complex banded diagonally dominant-like distribute where a(1:n, ja:ja+n-1) is an n-by-n complex tridiagonal diagonally dominant-like distribute a(1:n, ja:ja+n-1) is an n-by-n complex tridiagonal diagonally dominant-like distribute where a(1:n, ja:ja+n-1) is an n-by-n real banded diagonally dominant-like distribute a(1:n, ja:ja+n-1) is an n-by-n real banded diagonally dominant-like distribute where a(1:n, ja:ja+n-1) is an n-by-n real tridiagonal diagonally dominant-like distribute a(1:n, ja:ja+n-1) is an n-by-n real tridiagonal diagonally dominant-like distribute add/subtract, or on those binary machines without guard digits which subtract like the cray x-mp, cray y-mp, cray c-90, or cray-2 without guard digits, but we know of none. add/subtract, or on those binary machines without guard digits which subtract like the cray x-mp, cray y-mp, cray c-90, or cray-2 without guard digits, but we know of none. see dlaed3 for details. where a(1:n, ja:ja+n-1) is an n-by-n real banded diagonally dominant-like distribute a(1:n, ja:ja+n-1) is an n-by-n real banded diagonally dominant-like distribute where a(1:n, ja:ja+n-1) is an n-by-n real tridiagonal diagonally dominant-like distribute a(1:n, ja:ja+n-1) is an n-by-n real tridiagonal diagonally dominant-like distribute add/subtract, or on those binary machines without guard digits which subtract like the cray x-mp, cray y-mp, cray c-90, or cray-2 without guard digits, but we know of none. add/subtract, or on those binary machines without guard digits which subtract like the cray x-mp, cray y-mp, cray c-90, or cray-2 without guard digits, but we know of none. see slaed3 for details. where a(1:n, ja:ja+n-1) is an n-by-n complex banded diagonally dominant-like distribute a(1:n, ja:ja+n-1) is an n-by-n complex banded diagonally dominant-like distribute where a(1:n, ja:ja+n-1) is an n-by-n complex tridiagonal diagonally dominant-like distribute a(1:n, ja:ja+n-1) is an n-by-n complex tridiagonal diagonally dominant-like distribute |
| LILOZ LILOZ LILOZ these serve the same purpose as itmp1,itmp2 but for z LILOZ these serve the same purpose as itmp1,itmp2 but for z LILOZ these serve the same purpose as itmp1,itmp2 but for z LILOZ these serve the same purpose as itmp1,itmp2 but for z |
| limit limit the block size must not exceed the limit set by the size of th the block size must not exceed the limit set by the size of th where nq0 and mp0 refer, respectively, to the values obtained at mycol = 0 and myrow = 0. in general, the upper limit fo processor (0,0): orthogonally will cause serious degradation in performance. in the limit (i.e. clustersize = n-1 processor. orthogonally will cause serious degradation in performance. in the limit (i.e. clustersize = n-1 for clustersize = n/sqrt(nprow*npcol) reorthogonalizing where nq0 and mp0 refer, respectively, to the values obtained at mycol = 0 and myrow = 0. in general, the upper limit fo processor (0,0): orthogonally will cause serious degradation in performance. in the limit (i.e. clustersize = n-1 processor. orthogonally will cause serious degradation in performance. in the limit (i.e. clustersize = n-1 for clustersize = n/sqrt(nprow*npcol) reorthogonalizing where nq0 and mp0 refer, respectively, to the values obtained at mycol = 0 and myrow = 0. in general, the upper limit fo processor (0,0): orthogonally will cause serious degradation in performance. in the limit (i.e. clustersize = n-1 processor. orthogonally will cause serious degradation in performance. in the limit (i.e. clustersize = n-1 for clustersize = n/sqrt(nprow*npcol) reorthogonalizing where nq0 and mp0 refer, respectively, to the values obtained at mycol = 0 and myrow = 0. in general, the upper limit fo processor (0,0): orthogonally will cause serious degradation in performance. in the limit (i.e. clustersize = n-1 processor. orthogonally will cause serious degradation in performance. in the limit (i.e. clustersize = n-1 for clustersize = n/sqrt(nprow*npcol) reorthogonalizing the block size must not exceed the limit set by the size of th the block size must not exceed the limit set by the size of th |
| limitations limitations are temporary and will be removed in future releases, while others may reflect fundamental technical limitations non-cyclic restriction: very important! are temporary and will be removed in future releases, while others may reflect fundamental technical limitations non-cyclic restriction: very important! are temporary and will be removed in future releases, while others may reflect fundamental technical limitations non-cyclic restriction: very important! are temporary and will be removed in future releases, while others may reflect fundamental technical limitations non-cyclic restriction: very important! are temporary and will be removed in future releases, while others may reflect fundamental technical limitations non-cyclic restriction: very important! are temporary and will be removed in future releases, while others may reflect fundamental technical limitations non-cyclic restriction: very important! version 1.4 limitations desca(m_) = descz(m_) version 1.4 limitations desca(m_) = descz(m_) are temporary and will be removed in future releases, while others may reflect fundamental technical limitations non-cyclic restriction: very important! are temporary and will be removed in future releases, while others may reflect fundamental technical limitations non-cyclic restriction: very important! are temporary and will be removed in future releases, while others may reflect fundamental technical limitations non-cyclic restriction: very important! are temporary and will be removed in future releases, while others may reflect fundamental technical limitations non-cyclic restriction: very important! are temporary and will be removed in future releases, while others may reflect fundamental technical limitations non-cyclic restriction: very important! are temporary and will be removed in future releases, while others may reflect fundamental technical limitations non-cyclic restriction: very important! are temporary and will be removed in future releases, while others may reflect fundamental technical limitations non-cyclic restriction: very important! are temporary and will be removed in future releases, while others may reflect fundamental technical limitations non-cyclic restriction: very important! are temporary and will be removed in future releases, while others may reflect fundamental technical limitations non-cyclic restriction: very important! are temporary and will be removed in future releases, while others may reflect fundamental technical limitations non-cyclic restriction: very important! are temporary and will be removed in future releases, while others may reflect fundamental technical limitations non-cyclic restriction: very important! are temporary and will be removed in future releases, while others may reflect fundamental technical limitations non-cyclic restriction: very important! are temporary and will be removed in future releases, while others may reflect fundamental technical limitations non-cyclic restriction: very important! are temporary and will be removed in future releases, while others may reflect fundamental technical limitations non-cyclic restriction: very important! version 1.4 limitations desca(m_) = descz(m_) version 1.4 limitations desca(m_) = descz(m_) are temporary and will be removed in future releases, while others may reflect fundamental technical limitations non-cyclic restriction: very important! are temporary and will be removed in future releases, while others may reflect fundamental technical limitations non-cyclic restriction: very important! are temporary and will be removed in future releases, while others may reflect fundamental technical limitations non-cyclic restriction: very important! are temporary and will be removed in future releases, while others may reflect fundamental technical limitations non-cyclic restriction: very important! are temporary and will be removed in future releases, while others may reflect fundamental technical limitations non-cyclic restriction: very important! are temporary and will be removed in future releases, while others may reflect fundamental technical limitations non-cyclic restriction: very important! are temporary and will be removed in future releases, while others may reflect fundamental technical limitations non-cyclic restriction: very important! are temporary and will be removed in future releases, while others may reflect fundamental technical limitations non-cyclic restriction: very important! are temporary and will be removed in future releases, while others may reflect fundamental technical limitations non-cyclic restriction: very important! are temporary and will be removed in future releases, while others may reflect fundamental technical limitations non-cyclic restriction: very important! version 1.4 limitations desca(m_) = descz(m_) version 1.4 limitations desca(m_) = descz(m_) are temporary and will be removed in future releases, while others may reflect fundamental technical limitations non-cyclic restriction: very important! are temporary and will be removed in future releases, while others may reflect fundamental technical limitations non-cyclic restriction: very important! are temporary and will be removed in future releases, while others may reflect fundamental technical limitations non-cyclic restriction: very important! are temporary and will be removed in future releases, while others may reflect fundamental technical limitations non-cyclic restriction: very important! are temporary and will be removed in future releases, while others may reflect fundamental technical limitations non-cyclic restriction: very important! are temporary and will be removed in future releases, while others may reflect fundamental technical limitations non-cyclic restriction: very important! version 1.4 limitations desca(m_) = descz(m_) version 1.4 limitations desca(m_) = descz(m_) are temporary and will be removed in future releases, while others may reflect fundamental technical limitations non-cyclic restriction: very important! are temporary and will be removed in future releases, while others may reflect fundamental technical limitations non-cyclic restriction: very important! are temporary and will be removed in future releases, while others may reflect fundamental technical limitations non-cyclic restriction: very important! are temporary and will be removed in future releases, while others may reflect fundamental technical limitations non-cyclic restriction: very important! |
| limited limited support for uplo='u' is limited to calling the old, slow, pchetr support for uplo='u' is limited to calling the old, slow, pdsytr support for uplo='u' is limited to calling the old, slow, pssytr support for uplo='u' is limited to calling the old, slow, pzhetr |
| limits limits to identify machines with a large exponent range, such as the crays, and redefine the underflow and overflow limits to be the square root pdlamch does not compensate for poor arithmetic in the upper half of to identify machines with a large exponent range, such as the crays, and redefine the underflow and overflow limits to be the square root pslamch does not compensate for poor arithmetic in the upper half of |
| linear linear pcdbsv solves a system of linear equation a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs) pcdbtrs solves a system of linear equation a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs) pcdtsv solves a system of linear equation a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs) pcdttrs solves a system of linear equation a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs) pcgbsv solves a system of linear equation a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs) pcgbtrs solves a system of linear equation a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs) pcgels solves overdetermined or underdetermined complex linear or its conjugate-transpose, using a qr or lq factorization of pcgerfs improves the computed solution to a system of linear the solutions. pcgesv computes the solution to a complex system of linear equation sub( a ) * x = sub( b ), pcgesvx uses the lu factorization to compute the solution to a complex system of linear equation a(ia:ia+n-1,ja:ja+n-1) * x = b(ib:ib+n-1,jb:jb+nrhs-1), pcgetrs solves a system of distributed linear equation op( sub( a ) ) * x = sub( b ) pcpbsv solves a system of linear equation a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs) pcpbtrs solves a system of linear equation a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs) pcporfs improves the computed solution to a system of linear and provides error bounds and backward error estimates for the pcposv computes the solution to a complex system of linear equation sub( a ) * x = sub( b ), pcposvx uses the cholesky factorization a = u**h*u or a = l*l**h to compute the solution to a complex system of linear equation a(ia:ia+n-1,ja:ja+n-1) * x = b(ib:ib+n-1,jb:jb+nrhs-1), pcpotrs solves a system of linear equation sub( a ) * x = sub( b ) pcptsv solves a system of linear equation a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs) pcpttrs solves a system of linear equation a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs) pctrrfs provides error bounds and backward error estimates for the solution to a system of linear equations with a triangula pddbsv solves a system of linear equation a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs) pddbtrs solves a system of linear equation a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs) pddtsv solves a system of linear equation a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs) pddttrs solves a system of linear equation a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs) pdgbsv solves a system of linear equation a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs) pdgbtrs solves a system of linear equation a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs) pdgels solves overdetermined or underdetermined real linear or its transpose, using a qr or lq factorization of sub( a ). it is pdgerfs improves the computed solution to a system of linear the solutions. pdgesv computes the solution to a real system of linear equation sub( a ) * x = sub( b ), pdgesvx uses the lu factorization to compute the solution to a real system of linear equation a(ia:ia+n-1,ja:ja+n-1) * x = b(ib:ib+n-1,jb:jb+nrhs-1), pdgetrs solves a system of distributed linear equation op( sub( a ) ) * x = sub( b ) pdpbsv solves a system of linear equation a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs) pdpbtrs solves a system of linear equation a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs) pdporfs improves the computed solution to a system of linear and provides error bounds and backward error estimates for the pdposv computes the solution to a real system of linear equation sub( a ) * x = sub( b ), pdposvx uses the cholesky factorization a = u**t*u or a = l*l**t to compute the solution to a real system of linear equation a(ia:ia+n-1,ja:ja+n-1) * x = b(ib:ib+n-1,jb:jb+nrhs-1), pdpotrs solves a system of linear equation sub( a ) * x = sub( b ) pdptsv solves a system of linear equation a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs) pdpttrs solves a system of linear equation a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs) pdtrrfs provides error bounds and backward error estimates for the solution to a system of linear equations with a triangula psdbsv solves a system of linear equation a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs) psdbtrs solves a system of linear equation a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs) psdtsv solves a system of linear equation a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs) psdttrs solves a system of linear equation a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs) psgbsv solves a system of linear equation a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs) psgbtrs solves a system of linear equation a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs) psgels solves overdetermined or underdetermined real linear or its transpose, using a qr or lq factorization of sub( a ). it is psgerfs improves the computed solution to a system of linear the solutions. psgesv computes the solution to a real system of linear equation sub( a ) * x = sub( b ), psgesvx uses the lu factorization to compute the solution to a real system of linear equation a(ia:ia+n-1,ja:ja+n-1) * x = b(ib:ib+n-1,jb:jb+nrhs-1), psgetrs solves a system of distributed linear equation op( sub( a ) ) * x = sub( b ) pspbsv solves a system of linear equation a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs) pspbtrs solves a system of linear equation a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs) psporfs improves the computed solution to a system of linear and provides error bounds and backward error estimates for the psposv computes the solution to a real system of linear equation sub( a ) * x = sub( b ), psposvx uses the cholesky factorization a = u**t*u or a = l*l**t to compute the solution to a real system of linear equation a(ia:ia+n-1,ja:ja+n-1) * x = b(ib:ib+n-1,jb:jb+nrhs-1), pspotrs solves a system of linear equation sub( a ) * x = sub( b ) psptsv solves a system of linear equation a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs) pspttrs solves a system of linear equation a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs) pstrrfs provides error bounds and backward error estimates for the solution to a system of linear equations with a triangula pzdbsv solves a system of linear equation a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs) pzdbtrs solves a system of linear equation a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs) pzdtsv solves a system of linear equation a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs) pzdttrs solves a system of linear equation a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs) pzgbsv solves a system of linear equation a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs) pzgbtrs solves a system of linear equation a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs) pzgels solves overdetermined or underdetermined complex linear or its conjugate-transpose, using a qr or lq factorization of pzgerfs improves the computed solution to a system of linear the solutions. pzgesv computes the solution to a complex system of linear equation sub( a ) * x = sub( b ), pzgesvx uses the lu factorization to compute the solution to a complex system of linear equation a(ia:ia+n-1,ja:ja+n-1) * x = b(ib:ib+n-1,jb:jb+nrhs-1), pzgetrs solves a system of distributed linear equation op( sub( a ) ) * x = sub( b ) pzpbsv solves a system of linear equation a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs) pzpbtrs solves a system of linear equation a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs) pzporfs improves the computed solution to a system of linear and provides error bounds and backward error estimates for the pzposv computes the solution to a complex system of linear equation sub( a ) * x = sub( b ), pzposvx uses the cholesky factorization a = u**h*u or a = l*l**h to compute the solution to a complex system of linear equation a(ia:ia+n-1,ja:ja+n-1) * x = b(ib:ib+n-1,jb:jb+nrhs-1), pzpotrs solves a system of linear equation sub( a ) * x = sub( b ) pzptsv solves a system of linear equation a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs) pzpttrs solves a system of linear equation a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs) pztrrfs provides error bounds and backward error estimates for the solution to a system of linear equations with a triangula |
| lines lines temporary variables. the following variables are used within a few lines after they are set and do hold state from one loo temporary variables. the following variables are used within a few lines after they are set and do hold state from one loo temporary variables. the following variables are used within a few lines after they are set and do hold state from one loo temporary variables. the following variables are used within a few lines after they are set and do hold state from one loo |
| LIPIV LIPIV ipiv (local input) integer array, dimension (LIPIV) where lipiv i >= locr( ia+m-1 ) + mb_a if pivroc='c' or 'c', ipiv (local input) integer array, dimension (LIPIV) where lipiv i >= locr( ia+m-1 ) + mb_a if pivroc='c' or 'c', ipiv (local input) integer array, dimension (LIPIV) where lipiv i >= locr( ia+m-1 ) + mb_a if pivroc='c' or 'c', ipiv (local input) integer array, dimension (LIPIV) where lipiv i >= locr( ia+m-1 ) + mb_a if pivroc='c' or 'c', |
| list list subroutine name, in the same order that they appear in the argument list for name, even if they are not used in determinin 2) the problem dimensions n1, n2, n3, n4 are specified in the order |
| little little clahqr used to have a single row application and a single column application to h. here we do something a little parts: dlahqr used to have a single row application and a single column application to h. here we do something a little parts: slahqr used to have a single row application and a single column application to h. here we do something a little parts: zlahqr used to have a single row application and a single column application to h. here we do something a little parts: |
| Livermore Livermore code developer: andrew j. cleary, university of tennessee. current address: lawrence Livermore national labs code developer: andrew j. cleary, university of tennessee. current address: lawrence Livermore national labs code developer: andrew j. cleary, university of tennessee. current address: lawrence Livermore national labs code developer: andrew j. cleary, university of tennessee. current address: lawrence Livermore national labs code developer: andrew j. cleary, university of tennessee. current address: lawrence Livermore national labs implemented for scalapack by: andrew j. cleary, Livermore national lab and university of tenn. based on code written by : peter arbenz, eth zurich, 1996. code developer: andrew j. cleary, university of tennessee. current address: lawrence Livermore national labs code developer: andrew j. cleary, university of tennessee. current address: lawrence Livermore national labs code developer: andrew j. cleary, university of tennessee. current address: lawrence Livermore national labs code developer: andrew j. cleary, university of tennessee. current address: lawrence Livermore national labs code developer: andrew j. cleary, university of tennessee. current address: lawrence Livermore national labs code developer: andrew j. cleary, university of tennessee. current address: lawrence Livermore national labs ===================================================================== code developer: andrew j. cleary, university of tennessee. current address: lawrence Livermore national labs code developer: andrew j. cleary, university of tennessee. current address: lawrence Livermore national labs ===================================================================== code developer: andrew j. cleary, university of tennessee. current address: lawrence Livermore national labs implemented for scalapack by: andrew j. cleary, Livermore national lab and university of tenn. based on code written by : peter arbenz, eth zurich, 1996. code developer: andrew j. cleary, university of tennessee. current address: lawrence Livermore national labs code developer: andrew j. cleary, university of tennessee. current address: lawrence Livermore national labs ===================================================================== code developer: andrew j. cleary, university of tennessee. current address: lawrence Livermore national labs code developer: andrew j. cleary, university of tennessee. current address: lawrence Livermore national labs ===================================================================== code developer: andrew j. cleary, university of tennessee. current address: lawrence Livermore national labs code developer: andrew j. cleary, university of tennessee. current address: lawrence Livermore national labs ===================================================================== code developer: andrew j. cleary, university of tennessee. current address: lawrence Livermore national labs code developer: andrew j. cleary, university of tennessee. current address: lawrence Livermore national labs ===================================================================== code developer: andrew j. cleary, university of tennessee. current address: lawrence Livermore national labs implemented for scalapack by: andrew j. cleary, Livermore national lab and university of tenn. based on code written by : peter arbenz, eth zurich, 1996. code developer: andrew j. cleary, university of tennessee. current address: lawrence Livermore national labs code developer: andrew j. cleary, university of tennessee. current address: lawrence Livermore national labs ===================================================================== code developer: andrew j. cleary, university of tennessee. current address: lawrence Livermore national labs code developer: andrew j. cleary, university of tennessee. current address: lawrence Livermore national labs ===================================================================== code developer: andrew j. cleary, university of tennessee. current address: lawrence Livermore national labs code developer: andrew j. cleary, university of tennessee. current address: lawrence Livermore national labs code developer: andrew j. cleary, university of tennessee. current address: lawrence Livermore national labs code developer: andrew j. cleary, university of tennessee. current address: lawrence Livermore national labs code developer: andrew j. cleary, university of tennessee. current address: lawrence Livermore national labs implemented for scalapack by: andrew j. cleary, Livermore national lab and university of tenn. based on code written by : peter arbenz, eth zurich, 1996. code developer: andrew j. cleary, university of tennessee. current address: lawrence Livermore national labs code developer: andrew j. cleary, university of tennessee. current address: lawrence Livermore national labs code developer: andrew j. cleary, university of tennessee. current address: lawrence Livermore national labs code developer: andrew j. cleary, university of tennessee. current address: lawrence Livermore national labs |
| LIWORK LIWORK iwork (local workspace/local output) integer array, dimension (LIWORK iwork (local workspace/output) integer array, dimension (LIWORK LIWORK (local input) intege liwork >= 6 * nnp LIWORK (local input) intege liwork >= 6 * nnp LIWORK (local input) intege iwork (local workspace/local output) integer array, dimension (LIWORK iwork (local workspace/local output) integer array, dimension (LIWORK iwork (local workspace/local output) integer array, dimension (LIWORK iwork (local workspace/local output) integer array, dimension (LIWORK iwork (local workspace/output) integer array, dimension (LIWORK iwork (local workspace/local output) integer array, dimension (LIWORK liwork (local or global input) integer iwork (local workspace/local output) integer array, dimension (LIWORK iwork (local workspace/local output) integer array, dimension (LIWORK iwork (local workspace/local output) integer array, dimension (LIWORK LIWORK (local input) intege if liwork = -1, then liwork is global input and a workspace iwork (local workspace/output) integer array, dimension (LIWORK LIWORK (local input) intege iwork (local workspace/output) integer array, dimension (LIWORK LIWORK (local input) intege liwork >= 6 * nnp LIWORK (local input) intege liwork >= 6 * nnp iwork (local workspace/local output) integer array, dimension (LIWORK iwork (local workspace/local output) integer array, dimension (LIWORK iwork (local workspace/local output) integer array, dimension (LIWORK iwork (local workspace/local output) integer array, dimension (LIWORK iwork (local workspace/local output) integer array, dimension (LIWORK iwork (local workspace/local output) integer array, dimension (LIWORK iwork (local workspace/output) integer array, dimension (LIWORK iwork (local workspace/local output) integer array, dimension (LIWORK liwork (local or global input) integer iwork (local workspace/local output) integer array, dimension (LIWORK iwork (local workspace/local output) integer array, dimension (LIWORK iwork (local workspace/local output) integer array, dimension (LIWORK LIWORK (local input) intege if liwork = -1, then liwork is global input and a workspace iwork (local workspace/output) integer array, dimension (LIWORK LIWORK (local input) intege iwork (local workspace/output) integer array, dimension (LIWORK LIWORK (local input) intege liwork >= 6 * nnp LIWORK (local input) intege liwork >= 6 * nnp iwork (local workspace/local output) integer array, dimension (LIWORK iwork (local workspace/local output) integer array, dimension (LIWORK iwork (local workspace/local output) integer array, dimension (LIWORK iwork (local workspace/output) integer array, dimension (LIWORK LIWORK (local input) intege liwork >= 6 * nnp LIWORK (local input) intege liwork >= 6 * nnp LIWORK (local input) intege |
| LLD_ LLD_ local memory to an array with first dimension LLD_a >=(bwl+bwu+1) (stored in desca) this local portion is stored in the packed banded format local memory to an array with first dimension LLD_a >=(bwl+bwu+1) (stored in desca) n-by-n unsymmetric banded distributed cholesky factor l or b (local input/local output) complex pointer into local memory to an array of local lead dimension LLD_b>=nb the local pieces of the right hand sides b (local input/local output) complex pointer into local memory to an array of local lead dimension LLD_b>=nb the local pieces of the right hand sides local memory to an array with first dimension LLD_a >=(2*bwl+2*bwu+1) (stored in desca) this local portion is stored in the packed banded format local memory to an array with first dimension LLD_a >=(2*bwl+2*bwu+1) (stored in desca) n-by-n unsymmetric banded distributed cholesky factor l or distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca first column of a is distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed matrix a. distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca local memory to an array with first dimension LLD_a >=(bw+1) (stored in desca) this local portion is stored in the packed banded format local memory to an array with first dimension LLD_a >=(bw+1) (stored in desca) n-by-n symmetric banded distributed cholesky factor l or distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca b (local input/local output) complex pointer into local memory to an array of local lead dimension LLD_b>=nb the local pieces of the right hand sides b (local input/local output) complex pointer into local memory to an array of local lead dimension LLD_b>=nb the local pieces of the right hand sides distributed. LLD_a (local) desca[ lld_ ] the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca local memory to an array with first dimension LLD_a >=(bwl+bwu+1) (stored in desca) this local portion is stored in the packed banded format local memory to an array with first dimension LLD_a >=(bwl+bwu+1) (stored in desca) n-by-n unsymmetric banded distributed cholesky factor l or b (local input/local output) double precision pointer into local memory to an array of local lead dimension LLD_b>=nb the local pieces of the right hand sides b (local input/local output) double precision pointer into local memory to an array of local lead dimension LLD_b>=nb the local pieces of the right hand sides local memory to an array with first dimension LLD_a >=(2*bwl+2*bwu+1) (stored in desca) this local portion is stored in the packed banded format local memory to an array with first dimension LLD_a >=(2*bwl+2*bwu+1) (stored in desca) n-by-n unsymmetric banded distributed cholesky factor l or distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca local memory to an array with first dimension LLD_a >=(bw+1) (stored in desca) this local portion is stored in the packed banded format local memory to an array with first dimension LLD_a >=(bw+1) (stored in desca) n-by-n symmetric banded distributed cholesky factor l or distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca b (local input/local output) double precision pointer into local memory to an array of local lead dimension LLD_b>=nb the local pieces of the right hand sides b (local input/local output) double precision pointer into local memory to an array of local lead dimension LLD_b>=nb the local pieces of the right hand sides distributed. LLD_a (local) desca[ lld_ ] the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca first column of a is distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed matrix a. distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca local memory to an array with first dimension LLD_a >=(bwl+bwu+1) (stored in desca) this local portion is stored in the packed banded format local memory to an array with first dimension LLD_a >=(bwl+bwu+1) (stored in desca) n-by-n unsymmetric banded distributed cholesky factor l or b (local input/local output) real pointer into local memory to an array of local lead dimension LLD_b>=nb the local pieces of the right hand sides b (local input/local output) real pointer into local memory to an array of local lead dimension LLD_b>=nb the local pieces of the right hand sides local memory to an array with first dimension LLD_a >=(2*bwl+2*bwu+1) (stored in desca) this local portion is stored in the packed banded format local memory to an array with first dimension LLD_a >=(2*bwl+2*bwu+1) (stored in desca) n-by-n unsymmetric banded distributed cholesky factor l or distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca local memory to an array with first dimension LLD_a >=(bw+1) (stored in desca) this local portion is stored in the packed banded format local memory to an array with first dimension LLD_a >=(bw+1) (stored in desca) n-by-n symmetric banded distributed cholesky factor l or distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca b (local input/local output) real pointer into local memory to an array of local lead dimension LLD_b>=nb the local pieces of the right hand sides b (local input/local output) real pointer into local memory to an array of local lead dimension LLD_b>=nb the local pieces of the right hand sides distributed. LLD_a (local) desca[ lld_ ] the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca first column of a is distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed matrix a. distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca local memory to an array with first dimension LLD_a >=(bwl+bwu+1) (stored in desca) this local portion is stored in the packed banded format local memory to an array with first dimension LLD_a >=(bwl+bwu+1) (stored in desca) n-by-n unsymmetric banded distributed cholesky factor l or distributed. LLD_a (local) desca[ lld_ ] the leading dimension of the loca b (local input/local output) complex*16 pointer into local memory to an array of local lead dimension LLD_b>=nb the local pieces of the right hand sides b (local input/local output) complex*16 pointer into local memory to an array of local lead dimension LLD_b>=nb the local pieces of the right hand sides local memory to an array with first dimension LLD_a >=(2*bwl+2*bwu+1) (stored in desca) this local portion is stored in the packed banded format local memory to an array with first dimension LLD_a >=(2*bwl+2*bwu+1) (stored in desca) n-by-n unsymmetric banded distributed cholesky factor l or distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca first column of a is distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed matrix a. distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca local memory to an array with first dimension LLD_a >=(bw+1) (stored in desca) this local portion is stored in the packed banded format local memory to an array with first dimension LLD_a >=(bw+1) (stored in desca) n-by-n symmetric banded distributed cholesky factor l or distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca b (local input/local output) complex*16 pointer into local memory to an array of local lead dimension LLD_b>=nb the local pieces of the right hand sides b (local input/local output) complex*16 pointer into local memory to an array of local lead dimension LLD_b>=nb the local pieces of the right hand sides distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_a (local) desca( lld_ ) the leading dimension of the loca |
| LLD_A LLD_A local memory to an array with first dimension LLD_A >=(bwl+bwu+1) (stored in desca) this local portion is stored in the packed banded format local memory to an array with first dimension LLD_A >=(bwl+bwu+1) (stored in desca) n-by-n unsymmetric banded distributed cholesky factor l or distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca local memory to an array with first dimension LLD_A >=(2*bwl+2*bwu+1) (stored in desca) this local portion is stored in the packed banded format local memory to an array with first dimension LLD_A >=(2*bwl+2*bwu+1) (stored in desca) n-by-n unsymmetric banded distributed cholesky factor l or distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca first column of a is distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed matrix a. a (local input/workspace) block cyclic complex array, global dimension (n, n), local dimension ( LLD_A distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca a (local input/local output) complex pointer into the local memory to an array of dimension (LLD_A pieces of the n-by-(n-k+1) general distributed matrix distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca local memory to an array with first dimension LLD_A >=(bw+1) (stored in desca) this local portion is stored in the packed banded format local memory to an array with first dimension LLD_A >=(bw+1) (stored in desca) n-by-n symmetric banded distributed cholesky factor l or distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca[ lld_ ] the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca local memory to an array with first dimension LLD_A >=(bwl+bwu+1) (stored in desca) this local portion is stored in the packed banded format local memory to an array with first dimension LLD_A >=(bwl+bwu+1) (stored in desca) n-by-n unsymmetric banded distributed cholesky factor l or distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca local memory to an array with first dimension LLD_A >=(2*bwl+2*bwu+1) (stored in desca) this local portion is stored in the packed banded format local memory to an array with first dimension LLD_A >=(2*bwl+2*bwu+1) (stored in desca) n-by-n unsymmetric banded distributed cholesky factor l or distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca a (local input/local output) double precision pointer into the local memory to an array of dimension (LLD_A pieces of the n-by-(n-k+1) general distributed matrix distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca local memory to an array with first dimension LLD_A >=(bw+1) (stored in desca) this local portion is stored in the packed banded format local memory to an array with first dimension LLD_A >=(bw+1) (stored in desca) n-by-n symmetric banded distributed cholesky factor l or distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca[ lld_ ] the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca first column of a is distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed matrix a. a (local input/workspace) block cyclic double precision array, global dimension (n, n), local dimension ( LLD_A on entry, the symmetric matrix a. if uplo = 'u', only the distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca local memory to an array with first dimension LLD_A >=(bwl+bwu+1) (stored in desca) this local portion is stored in the packed banded format local memory to an array with first dimension LLD_A >=(bwl+bwu+1) (stored in desca) n-by-n unsymmetric banded distributed cholesky factor l or distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca local memory to an array with first dimension LLD_A >=(2*bwl+2*bwu+1) (stored in desca) this local portion is stored in the packed banded format local memory to an array with first dimension LLD_A >=(2*bwl+2*bwu+1) (stored in desca) n-by-n unsymmetric banded distributed cholesky factor l or distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca a (local input/local output) real pointer into the local memory to an array of dimension (LLD_A pieces of the n-by-(n-k+1) general distributed matrix distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca local memory to an array with first dimension LLD_A >=(bw+1) (stored in desca) this local portion is stored in the packed banded format local memory to an array with first dimension LLD_A >=(bw+1) (stored in desca) n-by-n symmetric banded distributed cholesky factor l or distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca[ lld_ ] the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca first column of a is distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed matrix a. a (local input/workspace) block cyclic real array, global dimension (n, n), local dimension ( LLD_A on entry, the symmetric matrix a. if uplo = 'u', only the distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca local memory to an array with first dimension LLD_A >=(bwl+bwu+1) (stored in desca) this local portion is stored in the packed banded format local memory to an array with first dimension LLD_A >=(bwl+bwu+1) (stored in desca) n-by-n unsymmetric banded distributed cholesky factor l or distributed. LLD_A (local) desca[ lld_ ] the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca local memory to an array with first dimension LLD_A >=(2*bwl+2*bwu+1) (stored in desca) this local portion is stored in the packed banded format local memory to an array with first dimension LLD_A >=(2*bwl+2*bwu+1) (stored in desca) n-by-n unsymmetric banded distributed cholesky factor l or distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca first column of a is distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed matrix a. a (local input/workspace) block cyclic complex*16 array, global dimension (n, n), local dimension ( LLD_A distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca a (local input/local output) complex*16 pointer into the local memory to an array of dimension (LLD_A pieces of the n-by-(n-k+1) general distributed matrix distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca local memory to an array with first dimension LLD_A >=(bw+1) (stored in desca) this local portion is stored in the packed banded format local memory to an array with first dimension LLD_A >=(bw+1) (stored in desca) n-by-n symmetric banded distributed cholesky factor l or distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca distributed. LLD_A (local) desca( lld_ ) the leading dimension of the loca |
| LLD_AF LLD_AF af (local input) complex pointer into the local memory to an array of local dimension (LLD_AF,locc(ja+n-1)) factors of the matrix sub( a ) = p * l * u as computed by into the local memory to an array of local dimension (LLD_AF,locc(ja+n-1)). if fact = 'f', the entry contains the factors l and u from the factorization af (local input) complex pointer into the local memory to an array of local dimension (LLD_AF,locc(ja+n-1)) cholesky factorization sub( a ) = l*l**h or u**h*u, as into the local memory to an array of local dimension ( LLD_AF, locc(ja+n-1)) contains the triangular factor u or l from the cholesky af (local input) double precision pointer into the local memory to an array of local dimension (LLD_AF,locc(ja+n-1)) factors of the matrix sub( a ) = p * l * u as computed by into the local memory to an array of local dimension (LLD_AF,locc(ja+n-1)). if fact = 'f', the entry contains the factors l and u from the factorization af (local input) double precision pointer into the local memory to an array of local dimension (LLD_AF,locc(ja+n-1)) cholesky factorization sub( a ) = l*l**t or u**t*u, as into the local memory to an array of local dimension ( LLD_AF, locc(ja+n-1)) contains the triangular factor u or l from the cholesky af (local input) real pointer into the local memory to an array of local dimension (LLD_AF,locc(ja+n-1)) factors of the matrix sub( a ) = p * l * u as computed by into the local memory to an array of local dimension (LLD_AF,locc(ja+n-1)). if fact = 'f', the entry contains the factors l and u from the factorization af (local input) real pointer into the local memory to an array of local dimension (LLD_AF,locc(ja+n-1)) cholesky factorization sub( a ) = l*l**t or u**t*u, as into the local memory to an array of local dimension ( LLD_AF, locc(ja+n-1)) contains the triangular factor u or l from the cholesky af (local input) complex*16 pointer into the local memory to an array of local dimension (LLD_AF,locc(ja+n-1)) factors of the matrix sub( a ) = p * l * u as computed by into the local memory to an array of local dimension (LLD_AF,locc(ja+n-1)). if fact = 'f', the entry contains the factors l and u from the factorization af (local input) complex*16 pointer into the local memory to an array of local dimension (LLD_AF,locc(ja+n-1)) cholesky factorization sub( a ) = l*l**h or u**h*u, as into the local memory to an array of local dimension ( LLD_AF, locc(ja+n-1)) contains the triangular factor u or l from the cholesky |
| LLD_B LLD_B b (local input/local output) complex pointer into local memory to an array of local lead dimension LLD_B>=nb the local pieces of the right hand sides b (local input/local output) complex pointer into local memory to an array of local lead dimension LLD_B>=nb the local pieces of the right hand sides b (local input/local output) complex pointer into local memory to an array of local lead dimension LLD_B>=nb the local pieces of the right hand sides b (local input/local output) complex pointer into local memory to an array of local lead dimension LLD_B>=nb the local pieces of the right hand sides b (local input/local output) complex pointer into local memory to an array of local lead dimension LLD_B>=nb the local pieces of the right hand sides b (local input/local output) complex pointer into local memory to an array of local lead dimension LLD_B>=nb the local pieces of the right hand sides local memory to an array of local dimension (LLD_B, locc(jb+nrhs-1)). on entry, this array contains th vectors, stored columnwise; memory to an array of local dimension (LLD_B,locc(jb+nrhs-1)). this array contains the loca sub( b ). local memory to an array of dimension (LLD_B,locc(jb+nrhs-1)). on entry, the right hand sid is overwritten by the solution distributed matrix x. into the local memory to an array of local dimension (LLD_B,locc(jb+nrhs-1) ). on entry, the n-by-nrhs right-han equed = 'n', b(ib:ib+n-1,jb:jb+nrhs-1) is not modified; if local memory to an array of dimension (LLD_B,locc(jb+nrhs-1)). on entry, the right hand side distributed matrix x. b (local input/local output) complex pointer into the local memory to an array of dimension (LLD_B, locc(jb+p-1)) sub( b ) which is to be factored. on exit, if n <= p, the b (local input/local output) complex pointer into the local memory to an array of dimension (LLD_B, locc(jb+n-1)) sub( b ) which is to be factored. on exit, the elements on b (local input) complex pointer into the local memory to an array of dimension (LLD_B, locc(jb+n-1)). on entry from the cholesky factorization of sub( b ), as returned by b (local input) complex pointer into the local memory to an array of dimension (LLD_B, locc(jb+n-1)). on entry from the cholesky factorization of sub( b ), as returned by b (local input/local output) complex pointer into the local memory to an array of dimension (LLD_B, locc(jb+n-1)) n-by-n hermitian distributed matrix sub( b ). if uplo = 'u', b (local input) complex pointer into the local memory to an array of dimension (LLD_B, locc(jb+n-1)). on entry from the cholesky factorization of sub( b ), as returned by b (local output) complex pointer into the local memory to an array of dimension (LLD_B, locc(jb+n-1) ). this arra sub( b ) set as follows: b (local output) complex pointer into the local memory to an array of dimension (LLD_B, locc(jb+n-1) ). this arra sub( b ) set as follows: b (local input/local output) complex pointer into local memory to an array of local lead dimension LLD_B>=nb the local pieces of the right hand sides b (local input/local output) complex pointer into local memory to an array of local lead dimension LLD_B>=nb the local pieces of the right hand sides b (local input) complex pointer into the local memory to an array of local dimension (LLD_B, locc(jb+nrhs-1) ) right hand sides sub( b ). b (local input/local output) complex pointer into the local memory to an array of dimension (LLD_B,loc(jb+nrhs-1)) ted matrix sub( b ). on exit, if info = 0, sub( b ) is over- the local memory to an array of local dimension ( LLD_B, locc(jb+nrhs-1) ) on exit, if equed = 'n', b is not modified; if trans = 'n' local memory to an array of local dimension (LLD_B,locc(jb+nrhs-1)). on entry, this array contains th on exit, this array contains the local pieces of the solution b (local input/local output) complex pointer into local memory to an array of local lead dimension LLD_B>=nb the local pieces of the right hand sides b (local input/local output) complex pointer into local memory to an array of local lead dimension LLD_B>=nb the local pieces of the right hand sides b (local input) complex pointer into the local memory to an array of local dimension (LLD_B, locc(jb+nrhs-1) ) right hand sides sub( b ). local memory to an array of dimension (LLD_B,locc(jb+nrhs-1)). on entry, this array contains th sub( b ). on exit, if info = 0, sub( b ) is overwritten by b (local input/local output) double precision pointer into local memory to an array of local lead dimension LLD_B>=nb the local pieces of the right hand sides b (local input/local output) double precision pointer into local memory to an array of local lead dimension LLD_B>=nb the local pieces of the right hand sides b (local input/local output) double precision pointer into local memory to an array of local lead dimension LLD_B>=nb the local pieces of the right hand sides b (local input/local output) double precision pointer into local memory to an array of local lead dimension LLD_B>=nb the local pieces of the right hand sides b (local input/local output) double precision pointer into local memory to an array of local lead dimension LLD_B>=nb the local pieces of the right hand sides b (local input/local output) double precision pointer into local memory to an array of local lead dimension LLD_B>=nb the local pieces of the right hand sides local memory to an array of local dimension (LLD_B, locc(jb+nrhs-1)). on entry, this array contains th vectors, stored columnwise; memory to an array of local dimension (LLD_B,locc(jb+nrhs-1)). this array contains the loca sub( b ). local memory to an array of dimension (LLD_B,locc(jb+nrhs-1)). on entry, the right hand sid is overwritten by the solution distributed matrix x. into the local memory to an array of local dimension (LLD_B,locc(jb+nrhs-1) ). on entry, the n-by-nrhs right-han equed = 'n', b(ib:ib+n-1,jb:jb+nrhs-1) is not modified; if local memory to an array of dimension (LLD_B,locc(jb+nrhs-1)). on entry, the right hand side distributed matrix x. b (local input/local output) double precision pointer into the local memory to an array of dimension (LLD_B, locc(jb+p-1)) sub( b ) which is to be factored. on exit, if n <= p, the b (local input/local output) double precision pointer into the local memory to an array of dimension (LLD_B, locc(jb+n-1)) sub( b ) which is to be factored. on exit, the elements on b (local output) double precision pointer into the local memory to an array of dimension (LLD_B, locc(jb+n-1) ). this arra sub( b ) set as follows: b (local output) double precision pointer into the local memory to an array of dimension (LLD_B, locc(jb+n-1) ). this arra sub( b ) set as follows: b (local input/local output) double precision pointer into local memory to an array of local lead dimension LLD_B>=nb the local pieces of the right hand sides b (local input/local output) double precision pointer into local memory to an array of local lead dimension LLD_B>=nb the local pieces of the right hand sides b (local input) double precision pointer into the local memory to an array of local dimension (LLD_B, locc(jb+nrhs-1) ) right hand sides sub( b ). b (local input/local output) double precision pointer into the local memory to an array of dimension (LLD_B,loc(jb+nrhs-1)) ted matrix sub( b ). on exit, if info = 0, sub( b ) is over- the local memory to an array of local dimension ( LLD_B, locc(jb+nrhs-1) ) on exit, if equed = 'n', b is not modified; if trans = 'n' local memory to an array of local dimension (LLD_B,locc(jb+nrhs-1)). on entry, this array contains th on exit, this array contains the local pieces of the solution b (local input/local output) double precision pointer into local memory to an array of local lead dimension LLD_B>=nb the local pieces of the right hand sides b (local input/local output) double precision pointer into local memory to an array of local lead dimension LLD_B>=nb the local pieces of the right hand sides b (local input) double precision pointer into the local memory to an array of dimension (LLD_B, locc(jb+n-1)). on entry from the cholesky factorization of sub( b ), as returned by b (local input) double precision pointer into the local memory to an array of dimension (LLD_B, locc(jb+n-1)). on entry from the cholesky factorization of sub( b ), as returned by b (local input/local output) double precision pointer into the local memory to an array of dimension (LLD_B, locc(jb+n-1)) n-by-n symmetric distributed matrix sub( b ). if uplo = 'u', b (local input) double precision pointer into the local memory to an array of dimension (LLD_B, locc(jb+n-1)). on entry from the cholesky factorization of sub( b ), as returned by b (local input) double precision pointer into the local memory to an array of local dimension (LLD_B, locc(jb+nrhs-1) ) right hand sides sub( b ). local memory to an array of dimension (LLD_B,locc(jb+nrhs-1)). on entry, this array contains th sub( b ). on exit, if info = 0, sub( b ) is overwritten by b (local input/local output) real pointer into local memory to an array of local lead dimension LLD_B>=nb the local pieces of the right hand sides b (local input/local output) real pointer into local memory to an array of local lead dimension LLD_B>=nb the local pieces of the right hand sides b (local input/local output) real pointer into local memory to an array of local lead dimension LLD_B>=nb the local pieces of the right hand sides b (local input/local output) real pointer into local memory to an array of local lead dimension LLD_B>=nb the local pieces of the right hand sides b (local input/local output) real pointer into local memory to an array of local lead dimension LLD_B>=nb the local pieces of the right hand sides b (local input/local output) real pointer into local memory to an array of local lead dimension LLD_B>=nb the local pieces of the right hand sides local memory to an array of local dimension (LLD_B, locc(jb+nrhs-1)). on entry, this array contains th vectors, stored columnwise; memory to an array of local dimension (LLD_B,locc(jb+nrhs-1)). this array contains the loca sub( b ). local memory to an array of dimension (LLD_B,locc(jb+nrhs-1)). on entry, the right hand sid is overwritten by the solution distributed matrix x. into the local memory to an array of local dimension (LLD_B,locc(jb+nrhs-1) ). on entry, the n-by-nrhs right-han equed = 'n', b(ib:ib+n-1,jb:jb+nrhs-1) is not modified; if local memory to an array of dimension (LLD_B,locc(jb+nrhs-1)). on entry, the right hand side distributed matrix x. b (local input/local output) real pointer into the local memory to an array of dimension (LLD_B, locc(jb+p-1)) sub( b ) which is to be factored. on exit, if n <= p, the b (local input/local output) real pointer into the local memory to an array of dimension (LLD_B, locc(jb+n-1)) sub( b ) which is to be factored. on exit, the elements on b (local output) real pointer into the local memory to an array of dimension (LLD_B, locc(jb+n-1) ). this arra sub( b ) set as follows: b (local output) real pointer into the local memory to an array of dimension (LLD_B, locc(jb+n-1) ). this arra sub( b ) set as follows: b (local input/local output) real pointer into local memory to an array of local lead dimension LLD_B>=nb the local pieces of the right hand sides b (local input/local output) real pointer into local memory to an array of local lead dimension LLD_B>=nb the local pieces of the right hand sides b (local input) real pointer into the local memory to an array of local dimension (LLD_B, locc(jb+nrhs-1) ) right hand sides sub( b ). b (local input/local output) real pointer into the local memory to an array of dimension (LLD_B,loc(jb+nrhs-1)) ted matrix sub( b ). on exit, if info = 0, sub( b ) is over- the local memory to an array of local dimension ( LLD_B, locc(jb+nrhs-1) ) on exit, if equed = 'n', b is not modified; if trans = 'n' local memory to an array of local dimension (LLD_B,locc(jb+nrhs-1)). on entry, this array contains th on exit, this array contains the local pieces of the solution b (local input/local output) real pointer into local memory to an array of local lead dimension LLD_B>=nb the local pieces of the right hand sides b (local input/local output) real pointer into local memory to an array of local lead dimension LLD_B>=nb the local pieces of the right hand sides b (local input) real pointer into the local memory to an array of dimension (LLD_B, locc(jb+n-1)). on entry from the cholesky factorization of sub( b ), as returned by b (local input) real pointer into the local memory to an array of dimension (LLD_B, locc(jb+n-1)). on entry from the cholesky factorization of sub( b ), as returned by b (local input/local output) real pointer into the local memory to an array of dimension (LLD_B, locc(jb+n-1)) n-by-n symmetric distributed matrix sub( b ). if uplo = 'u', b (local input) real pointer into the local memory to an array of dimension (LLD_B, locc(jb+n-1)). on entry from the cholesky factorization of sub( b ), as returned by b (local input) real pointer into the local memory to an array of local dimension (LLD_B, locc(jb+nrhs-1) ) right hand sides sub( b ). local memory to an array of dimension (LLD_B,locc(jb+nrhs-1)). on entry, this array contains th sub( b ). on exit, if info = 0, sub( b ) is overwritten by b (local input/local output) complex*16 pointer into local memory to an array of local lead dimension LLD_B>=nb the local pieces of the right hand sides b (local input/local output) complex*16 pointer into local memory to an array of local lead dimension LLD_B>=nb the local pieces of the right hand sides b (local input/local output) complex*16 pointer into local memory to an array of local lead dimension LLD_B>=nb the local pieces of the right hand sides b (local input/local output) complex*16 pointer into local memory to an array of local lead dimension LLD_B>=nb the local pieces of the right hand sides b (local input/local output) complex*16 pointer into local memory to an array of local lead dimension LLD_B>=nb the local pieces of the right hand sides b (local input/local output) complex*16 pointer into local memory to an array of local lead dimension LLD_B>=nb the local pieces of the right hand sides local memory to an array of local dimension (LLD_B, locc(jb+nrhs-1)). on entry, this array contains th vectors, stored columnwise; memory to an array of local dimension (LLD_B,locc(jb+nrhs-1)). this array contains the loca sub( b ). local memory to an array of dimension (LLD_B,locc(jb+nrhs-1)). on entry, the right hand sid is overwritten by the solution distributed matrix x. into the local memory to an array of local dimension (LLD_B,locc(jb+nrhs-1) ). on entry, the n-by-nrhs right-han equed = 'n', b(ib:ib+n-1,jb:jb+nrhs-1) is not modified; if local memory to an array of dimension (LLD_B,locc(jb+nrhs-1)). on entry, the right hand side distributed matrix x. b (local input/local output) complex*16 pointer into the local memory to an array of dimension (LLD_B, locc(jb+p-1)) sub( b ) which is to be factored. on exit, if n <= p, the b (local input/local output) complex*16 pointer into the local memory to an array of dimension (LLD_B, locc(jb+n-1)) sub( b ) which is to be factored. on exit, the elements on b (local input) complex*16 pointer into the local memory to an array of dimension (LLD_B, locc(jb+n-1)). on entry from the cholesky factorization of sub( b ), as returned by b (local input) complex*16 pointer into the local memory to an array of dimension (LLD_B, locc(jb+n-1)). on entry from the cholesky factorization of sub( b ), as returned by b (local input/local output) complex*16 pointer into the local memory to an array of dimension (LLD_B, locc(jb+n-1)) n-by-n hermitian distributed matrix sub( b ). if uplo = 'u', b (local input) complex*16 pointer into the local memory to an array of dimension (LLD_B, locc(jb+n-1)). on entry from the cholesky factorization of sub( b ), as returned by b (local output) complex*16 pointer into the local memory to an array of dimension (LLD_B, locc(jb+n-1) ). this arra sub( b ) set as follows: b (local output) complex*16 pointer into the local memory to an array of dimension (LLD_B, locc(jb+n-1) ). this arra sub( b ) set as follows: b (local input/local output) complex*16 pointer into local memory to an array of local lead dimension LLD_B>=nb the local pieces of the right hand sides b (local input/local output) complex*16 pointer into local memory to an array of local lead dimension LLD_B>=nb the local pieces of the right hand sides b (local input) complex*16 pointer into the local memory to an array of local dimension (LLD_B, locc(jb+nrhs-1) ) right hand sides sub( b ). b (local input/local output) complex*16 pointer into the local memory to an array of dimension (LLD_B,loc(jb+nrhs-1)) ted matrix sub( b ). on exit, if info = 0, sub( b ) is over- the local memory to an array of local dimension ( LLD_B, locc(jb+nrhs-1) ) on exit, if equed = 'n', b is not modified; if trans = 'n' local memory to an array of local dimension (LLD_B,locc(jb+nrhs-1)). on entry, this array contains th on exit, this array contains the local pieces of the solution b (local input/local output) complex*16 pointer into local memory to an array of local lead dimension LLD_B>=nb the local pieces of the right hand sides b (local input/local output) complex*16 pointer into local memory to an array of local lead dimension LLD_B>=nb the local pieces of the right hand sides b (local input) complex*16 pointer into the local memory to an array of local dimension (LLD_B, locc(jb+nrhs-1) ) right hand sides sub( b ). local memory to an array of dimension (LLD_B,locc(jb+nrhs-1)). on entry, this array contains th sub( b ). on exit, if info = 0, sub( b ) is overwritten by |
| LLD_C LLD_C c (local input/local output) complex pointer into the local memory to an array of dimension (LLD_C,locc(jc+n-1)) sub( c ) is overwritten by q*sub( c ) or q'*sub( c ) or c (local input/local output) complex pointer into the local memory to an array of dimension (LLD_C,locc(jc+n-1)) sub( c ) is overwritten by q*sub( c ) or q'*sub( c ) or c (local input/local output) complex pointer into the local memory to an array of dimension (LLD_C,locc(jc+n-1)) on exit, sub( c ) is overwritten by q*sub( c ) or q'*sub( c ) c (local input/local output) complex pointer into the local memory to an array of dimension (LLD_C,locc(jc+n-1)) on exit, sub( c ) is overwritten by q*sub( c ) or q'*sub( c ) c (local input/local output) complex pointer into the local memory to an array of dimension (LLD_C,locc(jc+n-1)) on exit, if vect='q', sub( c ) is overwritten by q*sub( c ) c (local input/local output) complex pointer into the local memory to an array of dimension (LLD_C,locc(jc+n-1)) on exit, sub( c ) is overwritten by q*sub( c ) or q'*sub( c ) c (local input/local output) complex pointer into the local memory to an array of dimension (LLD_C,locc(jc+n-1)) on exit, sub( c ) is overwritten by q*sub( c ) or q'*sub( c ) c (local input/local output) complex pointer into the local memory to an array of dimension (LLD_C,locc(jc+n-1)) on exit, sub( c ) is overwritten by q*sub( c ) or q'*sub( c ) c (local input/local output) complex pointer into the local memory to an array of dimension (LLD_C,locc(jc+n-1)) on exit, sub( c ) is overwritten by q*sub( c ) or q'*sub( c ) c (local input/local output) complex pointer into the local memory to an array of dimension (LLD_C,locc(jc+n-1)) on exit, sub( c ) is overwritten by q*sub( c ) or q'*sub( c ) c (local input/local output) complex pointer into the local memory to an array of dimension (LLD_C,locc(jc+n-1)) on exit, sub( c ) is overwritten by q*sub( c ) or q'*sub( c ) c (local input/local output) complex pointer into the local memory to an array of dimension (LLD_C,locc(jc+n-1)) on exit, sub( c ) is overwritten by q*sub( c ) or q'*sub( c ) c (local input/local output) complex pointer into the local memory to an array of dimension (LLD_C,locc(jc+n-1)) on exit, sub( c ) is overwritten by q*sub( c ) or q'*sub( c ) c (local input/local output) complex pointer into the local memory to an array of dimension (LLD_C,locc(jc+n-1)) on exit, sub( c ) is overwritten by q*sub( c ) or q'*sub( c ) c (local input/local output) complex pointer into the local memory to an array of dimension (LLD_C,locc(jc+n-1)) on exit, sub( c ) is overwritten by q*sub( c ) or q'*sub( c ) c (local input/local output) double precision pointer into the local memory to an array of dimension (LLD_C,locc(jc+n-1)) sub( c ) is overwritten by q*sub( c ) or q'*sub( c ) or c (local input/local output) double precision pointer into the local memory to an array of dimension (LLD_C,locc(jc+n-1)) sub( c ) is overwritten by q*sub( c ) or q'*sub( c ) or c (local input/local output) double precision pointer into the local memory to an array of dimension (LLD_C,locc(jc+n-1)) on exit, sub( c ) is overwritten by q*sub( c ) or q'*sub( c ) c (local input/local output) double precision pointer into the local memory to an array of dimension (LLD_C,locc(jc+n-1)) on exit, sub( c ) is overwritten by q*sub( c ) or q'*sub( c ) c (local input/local output) double precision pointer into the local memory to an array of dimension (LLD_C,locc(jc+n-1)) on exit, if vect='q', sub( c ) is overwritten by q*sub( c ) c (local input/local output) double precision pointer into the local memory to an array of dimension (LLD_C,locc(jc+n-1)) on exit, sub( c ) is overwritten by q*sub( c ) or q'*sub( c ) c (local input/local output) double precision pointer into the local memory to an array of dimension (LLD_C,locc(jc+n-1)) on exit, sub( c ) is overwritten by q*sub( c ) or q'*sub( c ) c (local input/local output) double precision pointer into the local memory to an array of dimension (LLD_C,locc(jc+n-1)) on exit, sub( c ) is overwritten by q*sub( c ) or q'*sub( c ) c (local input/local output) double precision pointer into the local memory to an array of dimension (LLD_C,locc(jc+n-1)) on exit, sub( c ) is overwritten by q*sub( c ) or q'*sub( c ) c (local input/local output) double precision pointer into the local memory to an array of dimension (LLD_C,locc(jc+n-1)) on exit, sub( c ) is overwritten by q*sub( c ) or q'*sub( c ) c (local input/local output) double precision pointer into the local memory to an array of dimension (LLD_C,locc(jc+n-1)) on exit, sub( c ) is overwritten by q*sub( c ) or q'*sub( c ) c (local input/local output) double precision pointer into the local memory to an array of dimension (LLD_C,locc(jc+n-1)) on exit, sub( c ) is overwritten by q*sub( c ) or q'*sub( c ) c (local input/local output) double precision pointer into the local memory to an array of dimension (LLD_C,locc(jc+n-1)) on exit, sub( c ) is overwritten by q*sub( c ) or q'*sub( c ) c (local input/local output) double precision pointer into the local memory to an array of dimension (LLD_C,locc(jc+n-1)) on exit, sub( c ) is overwritten by q*sub( c ) or q'*sub( c ) c (local input/local output) double precision pointer into the local memory to an array of dimension (LLD_C,locc(jc+n-1)) on exit, sub( c ) is overwritten by q*sub( c ) or q'*sub( c ) c (local input/local output) real pointer into the local memory to an array of dimension (LLD_C,locc(jc+n-1)) sub( c ) is overwritten by q*sub( c ) or q'*sub( c ) or c (local input/local output) real pointer into the local memory to an array of dimension (LLD_C,locc(jc+n-1)) sub( c ) is overwritten by q*sub( c ) or q'*sub( c ) or c (local input/local output) real pointer into the local memory to an array of dimension (LLD_C,locc(jc+n-1)) on exit, sub( c ) is overwritten by q*sub( c ) or q'*sub( c ) c (local input/local output) real pointer into the local memory to an array of dimension (LLD_C,locc(jc+n-1)) on exit, sub( c ) is overwritten by q*sub( c ) or q'*sub( c ) c (local input/local output) real pointer into the local memory to an array of dimension (LLD_C,locc(jc+n-1)) on exit, if vect='q', sub( c ) is overwritten by q*sub( c ) c (local input/local output) real pointer into the local memory to an array of dimension (LLD_C,locc(jc+n-1)) on exit, sub( c ) is overwritten by q*sub( c ) or q'*sub( c ) c (local input/local output) real pointer into the local memory to an array of dimension (LLD_C,locc(jc+n-1)) on exit, sub( c ) is overwritten by q*sub( c ) or q'*sub( c ) c (local input/local output) real pointer into the local memory to an array of dimension (LLD_C,locc(jc+n-1)) on exit, sub( c ) is overwritten by q*sub( c ) or q'*sub( c ) c (local input/local output) real pointer into the local memory to an array of dimension (LLD_C,locc(jc+n-1)) on exit, sub( c ) is overwritten by q*sub( c ) or q'*sub( c ) c (local input/local output) real pointer into the local memory to an array of dimension (LLD_C,locc(jc+n-1)) on exit, sub( c ) is overwritten by q*sub( c ) or q'*sub( c ) c (local input/local output) real pointer into the local memory to an array of dimension (LLD_C,locc(jc+n-1)) on exit, sub( c ) is overwritten by q*sub( c ) or q'*sub( c ) c (local input/local output) real pointer into the local memory to an array of dimension (LLD_C,locc(jc+n-1)) on exit, sub( c ) is overwritten by q*sub( c ) or q'*sub( c ) c (local input/local output) real pointer into the local memory to an array of dimension (LLD_C,locc(jc+n-1)) on exit, sub( c ) is overwritten by q*sub( c ) or q'*sub( c ) c (local input/local output) real pointer into the local memory to an array of dimension (LLD_C,locc(jc+n-1)) on exit, sub( c ) is overwritten by q*sub( c ) or q'*sub( c ) c (local input/local output) real pointer into the local memory to an array of dimension (LLD_C,locc(jc+n-1)) on exit, sub( c ) is overwritten by q*sub( c ) or q'*sub( c ) c (local input/local output) complex*16 pointer into the local memory to an array of dimension (LLD_C,locc(jc+n-1)) sub( c ) is overwritten by q*sub( c ) or q'*sub( c ) or c (local input/local output) complex*16 pointer into the local memory to an array of dimension (LLD_C,locc(jc+n-1)) sub( c ) is overwritten by q*sub( c ) or q'*sub( c ) or c (local input/local output) complex*16 pointer into the local memory to an array of dimension (LLD_C,locc(jc+n-1)) on exit, sub( c ) is overwritten by q*sub( c ) or q'*sub( c ) c (local input/local output) complex*16 pointer into the local memory to an array of dimension (LLD_C,locc(jc+n-1)) on exit, sub( c ) is overwritten by q*sub( c ) or q'*sub( c ) c (local input/local output) complex*16 pointer into the local memory to an array of dimension (LLD_C,locc(jc+n-1)) on exit, if vect='q', sub( c ) is overwritten by q*sub( c ) c (local input/local output) complex*16 pointer into the local memory to an array of dimension (LLD_C,locc(jc+n-1)) on exit, sub( c ) is overwritten by q*sub( c ) or q'*sub( c ) c (local input/local output) complex*16 pointer into the local memory to an array of dimension (LLD_C,locc(jc+n-1)) on exit, sub( c ) is overwritten by q*sub( c ) or q'*sub( c ) c (local input/local output) complex*16 pointer into the local memory to an array of dimension (LLD_C,locc(jc+n-1)) on exit, sub( c ) is overwritten by q*sub( c ) or q'*sub( c ) c (local input/local output) complex*16 pointer into the local memory to an array of dimension (LLD_C,locc(jc+n-1)) on exit, sub( c ) is overwritten by q*sub( c ) or q'*sub( c ) c (local input/local output) complex*16 pointer into the local memory to an array of dimension (LLD_C,locc(jc+n-1)) on exit, sub( c ) is overwritten by q*sub( c ) or q'*sub( c ) c (local input/local output) complex*16 pointer into the local memory to an array of dimension (LLD_C,locc(jc+n-1)) on exit, sub( c ) is overwritten by q*sub( c ) or q'*sub( c ) c (local input/local output) complex*16 pointer into the local memory to an array of dimension (LLD_C,locc(jc+n-1)) on exit, sub( c ) is overwritten by q*sub( c ) or q'*sub( c ) c (local input/local output) complex*16 pointer into the local memory to an array of dimension (LLD_C,locc(jc+n-1)) on exit, sub( c ) is overwritten by q*sub( c ) or q'*sub( c ) c (local input/local output) complex*16 pointer into the local memory to an array of dimension (LLD_C,locc(jc+n-1)) on exit, sub( c ) is overwritten by q*sub( c ) or q'*sub( c ) c (local input/local output) complex*16 pointer into the local memory to an array of dimension (LLD_C,locc(jc+n-1)) on exit, sub( c ) is overwritten by q*sub( c ) or q'*sub( c ) |
| LLD_Q LLD_Q global dimension (n, n), local dimension ( LLD_Q, locc(jq+n-1) tridiagonal matrix. global dimension (n, n), local dimension ( LLD_Q, locc(jq+n-1) tridiagonal matrix. q (local input) double precision pointer into the local memory to an array of dimension (LLD_Q, locc(jq+n-1) ). this arra to be copied from. q (local output) double precision array, local dimension ( LLD_Q, locc(jq+n-1) tridiagonal matrix. global dimension (n, n), local dimension ( LLD_Q, locc(jq+n-1) tridiagonal matrix. global dimension (n, n), local dimension ( LLD_Q, locc(jq+n-1) tridiagonal matrix. q (local input) real pointer into the local memory to an array of dimension (LLD_Q, locc(jq+n-1) ). this arra to be copied from. q (local output) real array, local dimension ( LLD_Q, locc(jq+n-1) tridiagonal matrix. |
| LLD_V LLD_V v (local input) complex pointer into the local memory to an array of dimension ( LLD_V, locc(jv+k-1) ) i side = 'l', ( lld_v, locc(jv+n-1) ) if storev = 'r' and v (local input) complex pointer into the local memory to an array of dimension (LLD_V, locc(jv+m-1)) if side = 'l' pieces of the distributed vectors v representing the v (local input) double precision pointer into the local memory to an array of dimension ( LLD_V, locc(jv+k-1) ) i side = 'l', ( lld_v, locc(jv+n-1) ) if storev = 'r' and v (local input) double precision pointer into the local memory to an array of dimension (LLD_V, locc(jv+m-1)) if side = 'l' pieces of the distributed vectors v representing the v (local input) real pointer into the local memory to an array of dimension ( LLD_V, locc(jv+k-1) ) i side = 'l', ( lld_v, locc(jv+n-1) ) if storev = 'r' and v (local input) real pointer into the local memory to an array of dimension (LLD_V, locc(jv+m-1)) if side = 'l' pieces of the distributed vectors v representing the v (local input) complex*16 pointer into the local memory to an array of dimension ( LLD_V, locc(jv+k-1) ) i side = 'l', ( lld_v, locc(jv+n-1) ) if storev = 'r' and v (local input) complex*16 pointer into the local memory to an array of dimension (LLD_V, locc(jv+m-1)) if side = 'l' pieces of the distributed vectors v representing the |
| LLD_W LLD_W w (local output) complex pointer into the local memory to an array of dimension (LLD_W,nb_w), this array contain update the unreduced part of sub( a ). w (local output) double precision pointer into the local memory to an array of dimension (LLD_W,nb_w), this array contain update the unreduced part of sub( a ). w (local output) real pointer into the local memory to an array of dimension (LLD_W,nb_w), this array contain update the unreduced part of sub( a ). w (local output) complex*16 pointer into the local memory to an array of dimension (LLD_W,nb_w), this array contain update the unreduced part of sub( a ). |
| LLD_X LLD_X local memory to an array of local dimension (LLD_X,locc(jx+nrhs-1)). on entry, this array contain sub( x ). on exit, the improved solution vectors. into the local memory to an array of local dimension (LLD_X, locc(jx+nrhs-1)). if info = 0, the n-by-nrh system of equations. note that a(ia:ia+n-1,ja:ja+n-1) and x (local output) complex pointer into the local memory to an array of dimension (LLD_X,nb). on exit, the loca x(ix:ix+m-1,jx:jx+nb-1) required to update the unreduced x (local input/local output) complex pointer into the local memory to an array of dimension (LLD_X,*) x( i ) = x(ix+(jx-1)*m_x +(i-1)*incx ), 1 <= i <= n. x (local input/local output) complex, pointer into the local memory to an array of dimension (LLD_X,*). this arra before entry, the incremented array sub( x ) must contain x (local input) complex pointer into the local memory to an array of local dimension (LLD_X, locc(jx+nrhs-1) ) solution vectors sub( x ). on exit, it contains the the local memory to an array of local dimension ( LLD_X, locc(jx+nrhs-1) ) system of equations. note that a and b are modified on exit x (local input) complex pointer into the local memory to an array of local dimension (LLD_X, locc(jx+nrhs-1) ) solution vectors sub( x ). local memory to an array of local dimension (LLD_X,locc(jx+nrhs-1)). on entry, this array contain sub( x ). on exit, the improved solution vectors. into the local memory to an array of local dimension (LLD_X, locc(jx+nrhs-1)). if info = 0, the n-by-nrh system of equations. note that a(ia:ia+n-1,ja:ja+n-1) and x (local output) double precision pointer into the local memory to an array of dimension (LLD_X,nb). on exit, the loca x(ix:ix+m-1,jx:jx+nb-1) required to update the unreduced x (local input/local output) double precision, pointer into the local memory to an array of dimension (LLD_X,*). this arra before entry, the incremented array sub( x ) must contain x (local input) double precision pointer into the local memory to an array of local dimension (LLD_X, locc(jx+nrhs-1) ) solution vectors sub( x ). on exit, it contains the the local memory to an array of local dimension ( LLD_X, locc(jx+nrhs-1) ) system of equations. note that a and b are modified on exit x (local input) double precision pointer into the local memory to an array of local dimension (LLD_X, locc(jx+nrhs-1) ) solution vectors sub( x ). local memory to an array of local dimension (LLD_X,locc(jx+nrhs-1)). on entry, this array contain sub( x ). on exit, the improved solution vectors. into the local memory to an array of local dimension (LLD_X, locc(jx+nrhs-1)). if info = 0, the n-by-nrh system of equations. note that a(ia:ia+n-1,ja:ja+n-1) and x (local output) real pointer into the local memory to an array of dimension (LLD_X,nb). on exit, the loca x(ix:ix+m-1,jx:jx+nb-1) required to update the unreduced x (local input/local output) real, pointer into the local memory to an array of dimension (LLD_X,*). this arra before entry, the incremented array sub( x ) must contain x (local input) real pointer into the local memory to an array of local dimension (LLD_X, locc(jx+nrhs-1) ) solution vectors sub( x ). on exit, it contains the the local memory to an array of local dimension ( LLD_X, locc(jx+nrhs-1) ) system of equations. note that a and b are modified on exit x (local input) real pointer into the local memory to an array of local dimension (LLD_X, locc(jx+nrhs-1) ) solution vectors sub( x ). local memory to an array of local dimension (LLD_X,locc(jx+nrhs-1)). on entry, this array contain sub( x ). on exit, the improved solution vectors. into the local memory to an array of local dimension (LLD_X, locc(jx+nrhs-1)). if info = 0, the n-by-nrh system of equations. note that a(ia:ia+n-1,ja:ja+n-1) and x (local output) complex*16 pointer into the local memory to an array of dimension (LLD_X,nb). on exit, the loca x(ix:ix+m-1,jx:jx+nb-1) required to update the unreduced x (local input/local output) complex*16 pointer into the local memory to an array of dimension (LLD_X,*) x( i ) = x(ix+(jx-1)*m_x +(i-1)*incx ), 1 <= i <= n. x (local input/local output) complex*16, pointer into the local memory to an array of dimension (LLD_X,*). this arra before entry, the incremented array sub( x ) must contain x (local input) complex*16 pointer into the local memory to an array of local dimension (LLD_X, locc(jx+nrhs-1) ) solution vectors sub( x ). on exit, it contains the the local memory to an array of local dimension ( LLD_X, locc(jx+nrhs-1) ) system of equations. note that a and b are modified on exit x (local input) complex*16 pointer into the local memory to an array of local dimension (LLD_X, locc(jx+nrhs-1) ) solution vectors sub( x ). |
| LLD_Y LLD_Y y (local output) complex pointer into the local memory to an array of dimension (LLD_Y,nb). on exit, the loca y(iy:iy+n-1,jy:jy+nb-1) required to update the unreduced y (local output) complex pointer into the local memory to an array of dimension (LLD_Y,nb_a). on exit, this arra matrix y. lld_y >= locr(ia+n-1). y (local output) double precision pointer into the local memory to an array of dimension (LLD_Y,nb). on exit, the loca y(iy:iy+n-1,jy:jy+nb-1) required to update the unreduced y (local output) double precision pointer into the local memory to an array of dimension (LLD_Y,nb_a). on exit, this arra matrix y. lld_y >= locr(ia+n-1). y (local output) real pointer into the local memory to an array of dimension (LLD_Y,nb). on exit, the loca y(iy:iy+n-1,jy:jy+nb-1) required to update the unreduced y (local output) real pointer into the local memory to an array of dimension (LLD_Y,nb_a). on exit, this arra matrix y. lld_y >= locr(ia+n-1). y (local output) complex*16 pointer into the local memory to an array of dimension (LLD_Y,nb). on exit, the loca y(iy:iy+n-1,jy:jy+nb-1) required to update the unreduced y (local output) complex*16 pointer into the local memory to an array of dimension (LLD_Y,nb_a). on exit, this arra matrix y. lld_y >= locr(ia+n-1). |
| LLD_Z LLD_Z global dimension (n, n), local dimension (LLD_Z, locc(jz+n-1) contain the orthonormal eigenvectors of the matrix global dimension (n, n), local dimension ( LLD_Z, locc(jz+n-1) global dimension (n, n), local dimension ( LLD_Z, locc(jz+n-1) contain the orthonormal eigenvectors of the matrix global dimension (n, n), local dimension ( LLD_Z, locc(jz+n-1) contain the orthonormal eigenvectors of the matrix global dimension (n, n), local dimension ( LLD_Z, locc(jz+n-1) contain the orthonormal eigenvectors of the matrix global dimension (n, n), local dimension ( LLD_Z, locc(jz+n-1) of the symmetric matrix a. global dimension (n, n), local dimension ( LLD_Z, locc(jz+n-1) contain the orthonormal eigenvectors of the matrix global dimension (n, n), local dimension ( LLD_Z, locc(jz+n-1) contain the orthonormal eigenvectors of the matrix global dimension (n, n), local dimension ( LLD_Z, locc(jz+n-1) contain the orthonormal eigenvectors of the matrix global dimension (n, n), local dimension ( LLD_Z, locc(jz+n-1) of the symmetric matrix a. global dimension (n, n), local dimension ( LLD_Z, locc(jz+n-1) contain the orthonormal eigenvectors of the matrix global dimension (n, n), local dimension ( LLD_Z, locc(jz+n-1) contain the orthonormal eigenvectors of the matrix global dimension (n, n), local dimension (LLD_Z, locc(jz+n-1) contain the orthonormal eigenvectors of the matrix global dimension (n, n), local dimension ( LLD_Z, locc(jz+n-1) global dimension (n, n), local dimension ( LLD_Z, locc(jz+n-1) contain the orthonormal eigenvectors of the matrix global dimension (n, n), local dimension ( LLD_Z, locc(jz+n-1) contain the orthonormal eigenvectors of the matrix |
| LLDA LLDA element (l,ln+1) is swapped with element (j,ln+1) etc furthermore, the elements in the same row are ldb=LLDA-1 apar data format: element (l,ln+1) is swapped with element (j,ln+1) etc furthermore, the elements in the same row are ldb=LLDA-1 apar data format: element (l,ln+1) is swapped with element (j,ln+1) etc furthermore, the elements in the same row are ldb=LLDA-1 apar data format: element (l,ln+1) is swapped with element (j,ln+1) etc furthermore, the elements in the same row are ldb=LLDA-1 apar data format: |
| load load work required in updating the current column of a. updating the block column of a is reasonably load balanced wherea processor column is involved). work required in updating the current column of a. updating the block column of a is reasonably load balanced wherea processor column is involved). work required in updating the current column of a. updating the block column of a is reasonably load balanced wherea processor column is involved). work required in updating the current column of a. updating the block column of a is reasonably load balanced wherea processor column is involved). |
| LOC LOC the mapping between an object element and its corresponding process and memory LOCation let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory LOCation let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory LOCation let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory LOCation let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory LOCation let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory LOCation let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory LOCation let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory LOCation let a be a generic term for any 2d block cyclicly distributed array. |
| Local Local v1 (Local input/local output) complex array o its global index. v1(1) = amax, v1(2) = indx. .. .. Local scalars . .. local arrays .. .. Local scalars . .. Local scalars . .. .. Local scalars . .. local arrays .. s (Local input/output) complex array, ( lds,* is referenced. it is assumed that s has jblk double shifts lda (Local input) intege .. Local scalars . .. Local scalars . .. .. Local scalars . .. local arrays .. .. Local scalars . .. Local scalars . s (Local input/output) double precision array, (lds,* referenced. it is assumed that s has jblk double shifts .. .. Local scalars . .. local arrays .. lda (Local input) intege s (Local input/output) double precision array, dimension ld on exit, the diagonal blocks of s have been rewritten to pair .. .. Local scalars . .. local arrays .. .. Local scalars . .. .. Local scalars . .. local arrays .. .. .. Local scalars . .. external functions .. .. Local scalars . a (Local input/local output) complex pointer int lld_a >=(bwl+bwu+1) (stored in desca). .. .. Local scalars . .. local arrays .. a (Local input/local output) complex pointer int lld_a >=(bwl+bwu+1) (stored in desca). .. .. Local scalars . .. local arrays .. dl (Local input/local output) complex pointer to loca matrix. globally, dl(1) is not referenced, and dl must be .. .. Local scalars . .. local arrays .. dl (Local input/local output) complex pointer to loca matrix. globally, dl(1) is not referenced, and dl must be .. .. Local scalars . .. local arrays .. a (Local input/local output) complex pointer int lld_a >=(2*bwl+2*bwu+1) (stored in desca). .. .. Local scalars . .. local arrays .. a (Local input/local output) complex pointer int lld_a >=(2*bwl+2*bwu+1) (stored in desca). distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca first column of a is distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed matrix a. np = the number of rows Local to a given process distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed matrix b. no communication is performed, pclacp2 performs a Local copy sub( a ) := sub( b ), where sub( a ) denote pclacp2 requires that only dimension of the matrix operands is 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 distributed matrix b. no communication is performed, pclacpy performs a Local copy sub( a ) := sub( b ), where sub( a ) denote distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca .. .. Local scalars . .. local arrays .. a (Local input/local output) complex pointer int 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 distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca .. .. Local scalars . .. local arrays .. .. .. Local scalars . .. local arrays .. .. .. Local scalars . .. local arrays .. .. .. Local scalars . .. local arrays .. distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca .. .. Local scalars . .. external subroutines .. distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca .. .. Local scalars . .. external subroutines .. distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca .. .. Local scalars . .. external subroutines .. distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca .. .. Local scalars . .. external subroutines .. distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca .. Local scalars . .. external functions .. distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca .. .. Local scalars . .. external functions .. no communication is performed by this routine, the matrix to operate on should be strictly Local to one process notes distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca a (Local input/local output) complex pointer int lld_a >=(bw+1) (stored in desca). .. .. Local scalars . .. local arrays .. a (Local input/local output) complex pointer int lld_a >=(bw+1) (stored in desca). .. .. Local scalars . .. local arrays .. distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca d (Local input/local output) complex pointer to loca matrix. .. .. Local scalars . .. local arrays .. d (Local input/local output) complex pointer to loca matrix. .. .. Local scalars . .. local arrays .. distributed. lld_a (Local) desca[ lld_ ] the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca block matrix sub( a ) = a(ia:ia+n-1,ja:ja+n-1). this matrix should be contained in one and only one process memory space (Local operation) notes distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca a (Local input/local output) double precision pointer int lld_a >=(bwl+bwu+1) (stored in desca). .. .. Local scalars . .. local arrays .. a (Local input/local output) double precision pointer int lld_a >=(bwl+bwu+1) (stored in desca). .. .. Local scalars . .. local arrays .. dl (Local input/local output) double precision pointer to loca matrix. globally, dl(1) is not referenced, and dl must be .. .. Local scalars . .. local arrays .. dl (Local input/local output) double precision pointer to loca matrix. globally, dl(1) is not referenced, and dl must be .. .. Local scalars . .. local arrays .. a (Local input/local output) double precision pointer int lld_a >=(2*bwl+2*bwu+1) (stored in desca). .. .. Local scalars . .. local arrays .. a (Local input/local output) double precision pointer int lld_a >=(2*bwl+2*bwu+1) (stored in desca). distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca small (Local input/local output) double precisio on exit, if log10(large) is sufficiently large, the square distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed matrix b. no communication is performed, pdlacp2 performs a Local copy sub( a ) := sub( b ), where sub( a ) denote pdlacp2 requires that only dimension of the matrix operands is 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 distributed matrix b. no communication is performed, pdlacpy performs a Local copy sub( a ) := sub( b ), where sub( a ) denote q (Local output) double precision array local dimension ( lld_q, locc(jq+n-1)) q (Local output) double precision array local dimension ( lld_q, locc(jq+n-1)) u (global output) double precision array global dimension (n, n), Local dimension (ldu, nq) tridiagonal matrix. distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca .. .. Local scalars . .. local arrays .. a (Local input/local output) double precision pointer int locc(ja+n-k)). on entry, this array contains the the local .. Local scalars . a (Local output) complex*16 pointer into th on output, a is replicated across all processes in distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca .. .. Local scalars . .. local arrays .. .. .. Local scalars . .. local arrays .. .. .. Local scalars . .. local arrays .. distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca .. .. Local scalars . .. external subroutines .. distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca .. .. Local scalars . .. external subroutines .. distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca q (Local input) double precision pointer into the local memor contains the local pieces of the distributed matrix sub( a ) distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca .. Local scalars . .. external functions .. distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca no communication is performed by this routine, the matrix to operate on should be strictly Local to one process notes distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca a (Local input/local output) double precision pointer int lld_a >=(bw+1) (stored in desca). .. .. Local scalars . .. local arrays .. a (Local input/local output) double precision pointer int lld_a >=(bw+1) (stored in desca). .. .. Local scalars . .. local arrays .. distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca d (Local input/local output) double precision pointer to loca matrix. .. .. Local scalars . .. local arrays .. d (Local input/local output) double precision pointer to loca matrix. .. .. Local scalars . .. local arrays .. distributed. lld_a (Local) desca[ lld_ ] the leading dimension of the loca work (Local workspace) double precision array q (Local output) double precision array q contains the orthonormal eigenvectors of the symmetric distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca first column of a is distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed matrix a. np = the number of rows Local to a given process distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca block matrix sub( a ) = a(ia:ia+n-1,ja:ja+n-1). this matrix should be contained in one and only one process memory space (Local operation) notes distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca tailored eigen-routines to choose problem-dependent parameters for the Local environment. see ispe distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca a (Local input/local output) real pointer int lld_a >=(bwl+bwu+1) (stored in desca). .. .. Local scalars . .. local arrays .. a (Local input/local output) real pointer int lld_a >=(bwl+bwu+1) (stored in desca). .. .. Local scalars . .. local arrays .. dl (Local input/local output) real pointer to loca matrix. globally, dl(1) is not referenced, and dl must be .. .. Local scalars . .. local arrays .. dl (Local input/local output) real pointer to loca matrix. globally, dl(1) is not referenced, and dl must be .. .. Local scalars . .. local arrays .. a (Local input/local output) real pointer int lld_a >=(2*bwl+2*bwu+1) (stored in desca). .. .. Local scalars . .. local arrays .. a (Local input/local output) real pointer int lld_a >=(2*bwl+2*bwu+1) (stored in desca). distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca small (Local input/local output) rea on exit, if log10(large) is sufficiently large, the square distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed matrix b. no communication is performed, pslacp2 performs a Local copy sub( a ) := sub( b ), where sub( a ) denote pslacp2 requires that only dimension of the matrix operands is 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 distributed matrix b. no communication is performed, pslacpy performs a Local copy sub( a ) := sub( b ), where sub( a ) denote q (Local output) real array local dimension ( lld_q, locc(jq+n-1)) q (Local output) real array local dimension ( lld_q, locc(jq+n-1)) u (global output) real array global dimension (n, n), Local dimension (ldu, nq) tridiagonal matrix. distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca .. .. Local scalars . .. local arrays .. a (Local input/local output) real pointer int locc(ja+n-k)). on entry, this array contains the the local .. Local scalars . a (Local output) complex*16 pointer into th on output, a is replicated across all processes in distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca .. .. Local scalars . .. local arrays .. .. .. Local scalars . .. local arrays .. .. .. Local scalars . .. local arrays .. distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca .. .. Local scalars . .. external subroutines .. distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca .. .. Local scalars . .. external subroutines .. distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca q (Local input) real pointer into the local memor contains the local pieces of the distributed matrix sub( a ) distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca .. Local scalars . .. external functions .. distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca no communication is performed by this routine, the matrix to operate on should be strictly Local to one process notes distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca a (Local input/local output) real pointer int lld_a >=(bw+1) (stored in desca). .. .. Local scalars . .. local arrays .. a (Local input/local output) real pointer int lld_a >=(bw+1) (stored in desca). .. .. Local scalars . .. local arrays .. distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca d (Local input/local output) real pointer to loca matrix. .. .. Local scalars . .. local arrays .. d (Local input/local output) real pointer to loca matrix. .. .. Local scalars . .. local arrays .. distributed. lld_a (Local) desca[ lld_ ] the leading dimension of the loca work (Local workspace) real array, dimension ( max( 5*n, 7 ) lwork (local input) integer q (Local output) real array q contains the orthonormal eigenvectors of the symmetric distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca first column of a is distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed matrix a. np = the number of rows Local to a given process distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca block matrix sub( a ) = a(ia:ia+n-1,ja:ja+n-1). this matrix should be contained in one and only one process memory space (Local operation) notes distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca a (Local input/local output) complex*16 pointer int lld_a >=(bwl+bwu+1) (stored in desca). .. .. Local scalars . .. local arrays .. a (Local input/local output) complex*16 pointer int lld_a >=(bwl+bwu+1) (stored in desca). .. .. Local scalars . .. local arrays .. distributed. lld_a (Local) desca[ lld_ ] the leading dimension of the loca dl (Local input/local output) complex*16 pointer to loca matrix. globally, dl(1) is not referenced, and dl must be .. .. Local scalars . .. local arrays .. dl (Local input/local output) complex*16 pointer to loca matrix. globally, dl(1) is not referenced, and dl must be .. .. Local scalars . .. local arrays .. a (Local input/local output) complex*16 pointer int lld_a >=(2*bwl+2*bwu+1) (stored in desca). .. .. Local scalars . .. local arrays .. a (Local input/local output) complex*16 pointer int lld_a >=(2*bwl+2*bwu+1) (stored in desca). distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca first column of a is distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed matrix a. np = the number of rows Local to a given process distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed matrix b. no communication is performed, pzlacp2 performs a Local copy sub( a ) := sub( b ), where sub( a ) denote pzlacp2 requires that only dimension of the matrix operands is 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 distributed matrix b. no communication is performed, pzlacpy performs a Local copy sub( a ) := sub( b ), where sub( a ) denote distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca .. .. Local scalars . .. local arrays .. a (Local input/local output) complex*16 pointer int 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 distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca .. .. Local scalars . .. local arrays .. .. .. Local scalars . .. local arrays .. .. .. Local scalars . .. local arrays .. .. .. Local scalars . .. local arrays .. distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca .. .. Local scalars . .. external subroutines .. distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca .. .. Local scalars . .. external subroutines .. distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca .. .. Local scalars . .. external subroutines .. distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca .. .. Local scalars . .. external subroutines .. distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca .. Local scalars . .. external functions .. distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca .. .. Local scalars . .. external functions .. no communication is performed by this routine, the matrix to operate on should be strictly Local to one process notes distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca a (Local input/local output) complex*16 pointer int lld_a >=(bw+1) (stored in desca). .. .. Local scalars . .. local arrays .. a (Local input/local output) complex*16 pointer int lld_a >=(bw+1) (stored in desca). .. .. Local scalars . .. local arrays .. distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca d (Local input/local output) complex*16 pointer to loca matrix. .. .. Local scalars . .. local arrays .. d (Local input/local output) complex*16 pointer to loca matrix. .. .. Local scalars . .. local arrays .. distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca block matrix sub( a ) = a(ia:ia+n-1,ja:ja+n-1). this matrix should be contained in one and only one process memory space (Local operation) notes distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca distributed. lld_a (Local) desca( lld_ ) the leading dimension of the loca .. .. Local scalars . .. local arrays .. .. Local scalars . .. Local scalars . s (Local input/output) real array, (lds,* referenced. it is assumed that s has jblk double shifts .. .. Local scalars . .. local arrays .. lda (Local input) intege s (Local input/output) real array, dimension ld on exit, the diagonal blocks of s have been rewritten to pair .. .. Local scalars . .. local arrays .. .. Local scalars . .. .. Local scalars . .. local arrays .. .. .. Local scalars . .. external functions .. .. Local scalars . v1 (Local input/local output) complex*16 array o its global index. v1(1) = amax, v1(2) = indx. .. .. Local scalars . .. local arrays .. .. Local scalars . .. Local scalars . .. .. Local scalars . .. local arrays .. s (Local input/output) complex*16 array, ( lds,* is referenced. it is assumed that s has jblk double shifts lda (Local input) intege .. Local scalars . .. Local scalars . |
| LOCALI1 LOCALI1 "a" col defs : main col transforms from LOCALI1 to local "a" col defs : main col transforms from LOCALI1 to local "a" col defs : main col transforms from LOCALI1 to local "a" col defs : main col transforms from LOCALI1 to local |
| LOCALI2 LOCALI2 "a" row defs : main row transforms from localk to LOCALI2 "a" row defs : main row transforms from localk to LOCALI2 "a" row defs : main row transforms from localk to LOCALI2 "a" row defs : main row transforms from localk to LOCALI2 |
| LOCALK LOCALK "a" row defs : main row transforms from LOCALK to locali "a" row defs : main row transforms from LOCALK to locali "a" row defs : main row transforms from LOCALK to locali "a" row defs : main row transforms from LOCALK to locali |
| locally locally > 0: if info = k<=nprocs, the submatrix stored on processor info and factored locally was no the factorization was not completed. if the processor could not locally factor, it jumps here discard temporary matrix stored beginning in use main partition in each processor to solve locally > 0: if info = k<=nprocs, the submatrix stored on processor info and factored locally was no the factorization was not completed. if the processor could not locally factor, it jumps here use main partition in each processor to solve locally > 0: if info = k<=nprocs, the submatrix stored on processor info and factored locally was no the factorization was not completed. rev (global input) integer use rev = 0 to send global a into locally replicated use rev <> 0 to send locally replicated b from node (ii,jj) > 0: if info = k<=nprocs, the submatrix stored on processor info and factored locally was no the factorization was not completed. if the processor could not locally factor, it jumps here discard temporary matrix stored beginning in use main partition in each processor to solve locally > 0: if info = k<=nprocs, the submatrix stored on processor info and factored locally was no the factorization was not completed. if the processor could not locally factor, it jumps here use main partition in each processor to solve locally > 0: if info = k<=nprocs, the submatrix stored on processor info and factored locally was no the factorization was not completed. if the processor could not locally factor, it jumps here discard temporary matrix stored beginning in use main partition in each processor to solve locally > 0: if info = k<=nprocs, the submatrix stored on processor info and factored locally was no the factorization was not completed. if the processor could not locally factor, it jumps here use main partition in each processor to solve locally > 0: if info = k<=nprocs, the submatrix stored on processor info and factored locally was no the factorization was not completed. rev (global input) integer use rev = 0 to send global a into locally replicated use rev <> 0 to send locally replicated b from node (ii,jj) > 0: if info = k<=nprocs, the submatrix stored on processor info and factored locally was no the factorization was not completed. if the processor could not locally factor, it jumps here discard temporary matrix stored beginning in use main partition in each processor to solve locally > 0: if info = k<=nprocs, the submatrix stored on processor info and factored locally was no the factorization was not completed. if the processor could not locally factor, it jumps here use main partition in each processor to solve locally > 0: if info = k<=nprocs, the submatrix stored on processor info and factored locally was no the factorization was not completed. if the processor could not locally factor, it jumps here discard temporary matrix stored beginning in use main partition in each processor to solve locally > 0: if info = k<=nprocs, the submatrix stored on processor info and factored locally was no the factorization was not completed. if the processor could not locally factor, it jumps here use main partition in each processor to solve locally > 0: if info = k<=nprocs, the submatrix stored on processor info and factored locally was no the factorization was not completed. rev (global input) integer use rev = 0 to send global a into locally replicated use rev <> 0 to send locally replicated b from node (ii,jj) > 0: if info = k<=nprocs, the submatrix stored on processor info and factored locally was no the factorization was not completed. if the processor could not locally factor, it jumps here discard temporary matrix stored beginning in use main partition in each processor to solve locally > 0: if info = k<=nprocs, the submatrix stored on processor info and factored locally was no the factorization was not completed. if the processor could not locally factor, it jumps here use main partition in each processor to solve locally > 0: if info = k<=nprocs, the submatrix stored on processor info and factored locally was no the factorization was not completed. if the processor could not locally factor, it jumps here discard temporary matrix stored beginning in use main partition in each processor to solve locally > 0: if info = k<=nprocs, the submatrix stored on processor info and factored locally was no the factorization was not completed. if the processor could not locally factor, it jumps here use main partition in each processor to solve locally > 0: if info = k<=nprocs, the submatrix stored on processor info and factored locally was no the factorization was not completed. rev (global input) integer use rev = 0 to send global a into locally replicated use rev <> 0 to send locally replicated b from node (ii,jj) > 0: if info = k<=nprocs, the submatrix stored on processor info and factored locally was no the factorization was not completed. if the processor could not locally factor, it jumps here discard temporary matrix stored beginning in use main partition in each processor to solve locally > 0: if info = k<=nprocs, the submatrix stored on processor info and factored locally was no the factorization was not completed. if the processor could not locally factor, it jumps here use main partition in each processor to solve locally |
| LOCALM LOCALM "a" col defs : main col transforms from locali1 to LOCALM "a" col defs : main col transforms from locali1 to LOCALM "a" col defs : main col transforms from locali1 to LOCALM "a" col defs : main col transforms from locali1 to LOCALM |
| located located the absolute tolerance for the eigenvalues. an eigenvalue (or cluster) is considered to be located if it has bee less. if abstol is less than or equal to zero, then ulp*|t| the absolute tolerance for the eigenvalues. an eigenvalue (or cluster) is considered to be located if it has bee less. if abstol is less than or equal to zero, then ulp*|t| |
| location location the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. conjugate transpose resulting block to its location the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the last processor does not need to send anything. biptr = location of triangle b_i in memor the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. establish the mapping between a matrix entry and its corresponding process and memory location in the following comments, the character _ should be read as the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. conjugate transpose resulting block to its location the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. eigenvectors that are to be orthogonalized are computed by the same process. pcstein decides on the allocation of work among th individual process. if insufficient workspace is allocated, the the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. transpose resulting block to its location the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the last processor does not need to send anything. biptr = location of triangle b_i in memor the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. n1 (input) integer the location of the last eigenvalue in the leadin min(1,n) <= n1 <= n. n1 (input) integer the location of the last eigenvalue in the leading sub-matrix the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. transpose resulting block to its location the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. eigenvectors that are to be orthogonalized are computed by the same process. pdstein decides on the allocation of work among th individual process. if insufficient workspace is allocated, the establish the mapping between a matrix entry and its corresponding process and memory location in the following comments, the character _ should be read as the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. transpose resulting block to its location the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the last processor does not need to send anything. biptr = location of triangle b_i in memor the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. n1 (input) integer the location of the last eigenvalue in the leadin min(1,n) <= n1 <= n. n1 (input) integer the location of the last eigenvalue in the leading sub-matrix the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. transpose resulting block to its location the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. eigenvectors that are to be orthogonalized are computed by the same process. psstein decides on the allocation of work among th individual process. if insufficient workspace is allocated, the establish the mapping between a matrix entry and its corresponding process and memory location in the following comments, the character _ should be read as the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. conjugate transpose resulting block to its location the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the last processor does not need to send anything. biptr = location of triangle b_i in memor the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. establish the mapping between a matrix entry and its corresponding process and memory location in the following comments, the character _ should be read as the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. conjugate transpose resulting block to its location the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. eigenvectors that are to be orthogonalized are computed by the same process. pzstein decides on the allocation of work among th individual process. if insufficient workspace is allocated, the the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. the mapping between an object element and its corresponding process and memory location let a be a generic term for any 2d block cyclicly distributed array. |
| locations locations the node owning h(m,m) does not. this will occur on a border and can happen in no more than 3 locations per block assumin values: a buffer to send diagonally down and right, a buffer the node owning h(m,m) does not. this will occur on a border and can happen in no more than 3 locations per block assumin values: a buffer to send diagonally down and right, a buffer the node owning h(m,m) does not. this will occur on a border and can happen in no more than 3 locations per block assumin values: a buffer to send diagonally down and right, a buffer the node owning h(m,m) does not. this will occur on a border and can happen in no more than 3 locations per block assumin values: a buffer to send diagonally down and right, a buffer |
| LOCc LOCc process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. distributed over the r processes of its process column. similarly, LOCc( k ) denotes the number of elements of k that a process woul row. the values of locr() and locc() may be determined via a call process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. global dimension (n, n), local dimension ( lld_a, LOCc(ja+n-1) on entry, the symmetric matrix a. if uplo = 'u', only the process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. the local memory to an array of dimension (lld_a, LOCc(ja+n-k)). on entry, this array contains the the loca a(ia:ia+n-1,ja:ja+n-k). on exit, the elements on and above a (local output) complex*16 pointer into the local memory to an array of dimension (LOCc(ja+n-1)) this processor column. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. distributed over the r processes of its process column. similarly, LOCc( k ) denotes the number of elements of k that a process woul row. the values of locr() and locc() may be determined via a call process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. global dimension (n, n), local dimension ( lld_q, LOCc(jq+n-1) tridiagonal matrix. global dimension (n, n), local dimension ( lld_q, LOCc(jq+n-1) tridiagonal matrix. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. the local memory to an array of dimension (lld_a, LOCc(ja+n-k)). on entry, this array contains the the loca a(ia:ia+n-1,ja:ja+n-k). on exit, the elements on and above a (local output) complex*16 pointer into the local memory to an array of dimension (LOCc(ja+n-1)) this processor column. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. q (local input) double precision pointer into the local memory to an array of dimension (lld_q, LOCc(jq+n-1) ). this arra to be copied from. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. q (local output) double precision array, local dimension ( lld_q, LOCc(jq+n-1) tridiagonal matrix. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. global dimension (n, n), local dimension ( lld_a, LOCc(ja+n-1) upper triangular part of a is used to define the elements of process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. distributed over the r processes of its process column. similarly, LOCc( k ) denotes the number of elements of k that a process woul row. the values of locr() and locc() may be determined via a call process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. global dimension (n, n), local dimension ( lld_q, LOCc(jq+n-1) tridiagonal matrix. global dimension (n, n), local dimension ( lld_q, LOCc(jq+n-1) tridiagonal matrix. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. the local memory to an array of dimension (lld_a, LOCc(ja+n-k)). on entry, this array contains the the loca a(ia:ia+n-1,ja:ja+n-k). on exit, the elements on and above a (local output) complex*16 pointer into the local memory to an array of dimension (LOCc(ja+n-1)) this processor column. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. q (local input) real pointer into the local memory to an array of dimension (lld_q, LOCc(jq+n-1) ). this arra to be copied from. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. q (local output) real array, local dimension ( lld_q, LOCc(jq+n-1) tridiagonal matrix. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. global dimension (n, n), local dimension ( lld_a, LOCc(ja+n-1) upper triangular part of a is used to define the elements of process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. distributed over the r processes of its process column. similarly, LOCc( k ) denotes the number of elements of k that a process woul row. the values of locr() and locc() may be determined via a call process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. global dimension (n, n), local dimension ( lld_a, LOCc(ja+n-1) on entry, the symmetric matrix a. if uplo = 'u', only the process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. the local memory to an array of dimension (lld_a, LOCc(ja+n-k)). on entry, this array contains the the loca a(ia:ia+n-1,ja:ja+n-k). on exit, the elements on and above a (local output) complex*16 pointer into the local memory to an array of dimension (LOCc(ja+n-1)) this processor column. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. process column. similarly, LOCc( k ) denotes the number of elements of k that its process row. |
| locl locl ldzi (locl input) intege ldzi (locl input) intege ldzi (locl input) intege ldzi (locl input) intege |
| LOCp LOCp lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCp(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCp(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCp(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCp(m_a)) let k be the number of rows or columns of a distributed matrix, |
| LOCq LOCq process column. similarly, LOCq( k ) denotes the number of elements of k that of its process row. process column. similarly, LOCq( k ) denotes the number of elements of k that of its process row. process column. similarly, LOCq( k ) denotes the number of elements of k that of its process row. process column. similarly, LOCq( k ) denotes the number of elements of k that of its process row. |
| LOCr LOCr lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, and lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, distributed matrix a. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, contains the local pieces of the n-by-nb distributed matrix y. lld_y >= LOCr(ia+n-1) iy (global input) integer lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca[ lld_ ] the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, and lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, contains the local pieces of the n-by-nb distributed matrix y. lld_y >= LOCr(ia+n-1) iy (global input) integer lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca[ lld_ ] the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, distributed matrix a. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, and lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, contains the local pieces of the n-by-nb distributed matrix y. lld_y >= LOCr(ia+n-1) iy (global input) integer lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca[ lld_ ] the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, distributed matrix a. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca[ lld_ ] the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, and lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, distributed matrix a. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, contains the local pieces of the n-by-nb distributed matrix y. lld_y >= LOCr(ia+n-1) iy (global input) integer lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, lld_a (local) desca( lld_ ) the leading dimension of the local array. lld_a >= max(1,LOCr(m_a)) let k be the number of rows or columns of a distributed matrix, |
| log log and overflow, and returns the square root of each of these values if the log of large is sufficiently large. this subroutine is intende and redefine the underflow and overflow limits to be the square roots and overflow, and returns the square root of each of these values if the log of large is sufficiently large. this subroutine is intende and redefine the underflow and overflow limits to be the square roots |
| LOG10 LOG10 on entry, the underflow threshold as computed by pdlamch. on exit, if LOG10(large) is sufficiently large, the squar on entry, the underflow threshold as computed by pslamch. on exit, if LOG10(large) is sufficiently large, the squar |
| Logic Logic here lcm is least common multiple, and nprowxnpcol is the Logical grid size logic: here lcm is least common multiple, and nprowxnpcol is the Logical grid size logic: here lcm is least common multiple, and nprowxnpcol is the Logical grid size logic: here lcm is least common multiple, and nprowxnpcol is the Logical grid size logic: |
| logical logical wantz (global input) logical if .false., then do no additional work on z. wantz (global input) logical if .false., then do no additional work on z. here lcm is least common multiple, and nprowxnpcol is the logical grid size logic: here lcm is least common multiple, and nprowxnpcol is the logical grid size notes: = 's': compute selected right and/or left eigenvectors, specified by the logical array select select (global input) logical array, dimension (n) here lcm is least common multiple, and nprowxnpcol is the logical grid size logic: here lcm is least common multiple, and nprowxnpcol is the logical grid size notes: here lcm is least common multiple, and nprowxnpcol is the logical grid size logic: here lcm is least common multiple, and nprowxnpcol is the logical grid size notes: here lcm is least common multiple, and nprowxnpcol is the logical grid size logic: here lcm is least common multiple, and nprowxnpcol is the logical grid size notes: = 's': compute selected right and/or left eigenvectors, specified by the logical array select select (global input) logical array, dimension (n) wantz (global input) logical if .false., then do no additional work on z. wantz (global input) logical if .false., then do no additional work on z. |
| long long the eigenvalues are computed. therefore, when range='v' and as long as lrwork is large enough to allow pcheevx t eigenvalues and as many eigenvectors as it can. the eigenvalues are computed. therefore, when range='v' and as long as lrwork is large enough to allow pchegvx t eigenvalues and as many eigenvectors as it can. denoting a(ia:ia+m-1,ja:ja+n-1) by the real scalar cto/cfrom. this is done without over/underflow as long as the final resul sub( a ) may be full, upper triangular, lower triangular or upper sub( x ) by the real scalar 1/a. this is done without overflow or underflow as long as the final sub( x )/a does not overflow o denoting a(ia:ia+m-1,ja:ja+n-1) by the real scalar cto/cfrom. this is done without over/underflow as long as the final resul sub( a ) may be full, upper triangular, lower triangular or upper the real scalar 1/a. this is done without overflow or underflow as long as the final result sub( x )/a does not overflow or underflow where sub( x ) denotes x(ix:ix+n-1,jx:jx), if incx = 1, the eigenvalues are computed. therefore, when range='v' and as long as lwork is large enough to allow pdsyevx t eigenvalues and as many eigenvectors as it can. the eigenvalues are computed. therefore, when range='v' and as long as lwork is large enough to allow pdsygvx t eigenvalues and as many eigenvectors as it can. denoting a(ia:ia+m-1,ja:ja+n-1) by the real scalar cto/cfrom. this is done without over/underflow as long as the final resul sub( a ) may be full, upper triangular, lower triangular or upper the real scalar 1/a. this is done without overflow or underflow as long as the final result sub( x )/a does not overflow or underflow where sub( x ) denotes x(ix:ix+n-1,jx:jx), if incx = 1, the eigenvalues are computed. therefore, when range='v' and as long as lwork is large enough to allow pssyevx t eigenvalues and as many eigenvectors as it can. the eigenvalues are computed. therefore, when range='v' and as long as lwork is large enough to allow pssygvx t eigenvalues and as many eigenvectors as it can. sub( x ) by the real scalar 1/a. this is done without overflow or underflow as long as the final sub( x )/a does not overflow o the eigenvalues are computed. therefore, when range='v' and as long as lrwork is large enough to allow pzheevx t eigenvalues and as many eigenvectors as it can. the eigenvalues are computed. therefore, when range='v' and as long as lrwork is large enough to allow pzhegvx t eigenvalues and as many eigenvectors as it can. denoting a(ia:ia+m-1,ja:ja+n-1) by the real scalar cto/cfrom. this is done without over/underflow as long as the final resul sub( a ) may be full, upper triangular, lower triangular or upper |
| longer longer on exit, the diagonal blocks of s have been rewritten to pair the eigenvalues. the resulting matrix is no longer on exit, the diagonal blocks of s have been rewritten to pair the eigenvalues. the resulting matrix is no longer |
| look look look for a single small subdiagonal element lookahead ove look for small subdiagonal element is required to make the odd and even frontal matrices look identica look for a single small subdiagonal element pclasmsub looks for a small subdiagonal element from the botto is required to make the odd and even frontal matrices look identica look for a single small subdiagonal element pdlasmsub looks for a small subdiagonal element from the botto is required to make the odd and even frontal matrices look identica look for a single small subdiagonal element pslasmsub looks for a small subdiagonal element from the botto is required to make the odd and even frontal matrices look identica look for a single small subdiagonal element pzlasmsub looks for a small subdiagonal element from the botto look for small subdiagonal element look for a single small subdiagonal element lookahead ove |
| Lookahead Lookahead Lookahead ove Lookahead ove |
| looking looking this is the right-looking parallel level 2 blas version of th this is the right-looking parallel level 3 blas version of th this is the right-looking parallel level 2 blas version of th this is the right-looking parallel level 3 blas version of th this is the right-looking parallel level 2 blas version of th this is the right-looking parallel level 3 blas version of th this is the right-looking parallel level 2 blas version of th this is the right-looking parallel level 3 blas version of th |
| looks looks pclaconsb looks for two consecutive small subdiagonal elements b given by h44, h33, & h43h34 and see if this would make a pclasmsub looks for a small subdiagonal element from the botto pdlaconsb looks for two consecutive small subdiagonal elements b given by h44, h33, & h43h34 and see if this would make a pdlasmsub looks for a small subdiagonal element from the botto pslaconsb looks for two consecutive small subdiagonal elements b given by h44, h33, & h43h34 and see if this would make a pslasmsub looks for a small subdiagonal element from the botto pzlaconsb looks for two consecutive small subdiagonal elements b given by h44, h33, & h43h34 and see if this would make a pzlasmsub looks for a small subdiagonal element from the botto |
| Loop Loop to which transformations must be applied. if eigenvalues only are being computed, i1 and i2 are set inside the main Loop inner Loop Loop through eigenvalues of block nblk inner Loop end of "if ( mycol .lt. np-1 )..." Loop ************************************* modification Loop the distance for sending and receiving for each level starts end of "if ( mycol .lt. np-1 )..." Loop ************************************* modification Loop the distance for sending and receiving for each level starts only the eliminations of unknowns > ln-bw have an effect on the last bw columns. Loop over them.. temporary variables. the following variables are used within a few lines after they are set and do hold state from one Loop necessary to scan the "tridiagonal portion of the matrix." in the lapack algorithm zlahqr, a Loop of m goes from i-2 down t h(m,m),h(m+1,m+1),h(m+1,m),h(m,m+1),h(m-1,m-1),h(m,m-1), and to which transformations must be applied. if eigenvalues only are being computed, i1 and i2 are set inside the main Loop Loop over the remaining rows/columns of the matrix Loop over remaining block of column Loop over the remaining rows/columns of the matrix Loop over remaining block of column exit the Loop if the growth factor is too small end of "if ( mycol .lt. np-1 )..." Loop ************************************* modification Loop the distance for sending and receiving for each level starts end of "if ( mycol .lt. np-1 )..." Loop ************************************* modification Loop the distance for sending and receiving for each level starts end of "if ( mycol .lt. np-1 )..." Loop ************************************* modification Loop the distance for sending and receiving for each level starts end of "if ( mycol .lt. np-1 )..." Loop ************************************* modification Loop the distance for sending and receiving for each level starts only the eliminations of unknowns > ln-bw have an effect on the last bw columns. Loop over them.. necessary to scan the "tridiagonal portion of the matrix." in the lapack algorithm dlahqr, a Loop of m goes from i-2 down t h(m,m),h(m+1,m+1),h(m+1,m),h(m,m+1),h(m-1,m-1),h(m,m-1), and pdlaebz contains the iteration Loop which computes the eigenvalue j = 1,...,minp. it uses and computes the function n(w), which is to which transformations must be applied. if eigenvalues only are being computed, i1 and i2 are set inside the main Loop Loop over remaining block of column Loop over the remaining rows/columns of the matrix Loop over remaining block of column 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" end of "if ( mycol .lt. np-1 )..." Loop ************************************* modification Loop the distance for sending and receiving for each level starts end of "if ( mycol .lt. np-1 )..." Loop ************************************* modification Loop the distance for sending and receiving for each level starts temporary variables. the following variables are used within a few lines after they are set and do hold state from one Loop end of "if ( mycol .lt. np-1 )..." Loop ************************************* modification Loop the distance for sending and receiving for each level starts end of "if ( mycol .lt. np-1 )..." Loop ************************************* modification Loop the distance for sending and receiving for each level starts only the eliminations of unknowns > ln-bw have an effect on the last bw columns. Loop over them.. necessary to scan the "tridiagonal portion of the matrix." in the lapack algorithm dlahqr, a Loop of m goes from i-2 down t h(m,m),h(m+1,m+1),h(m+1,m),h(m,m+1),h(m-1,m-1),h(m,m-1), and pslaebz contains the iteration Loop which computes the eigenvalue j = 1,...,minp. it uses and computes the function n(w), which is to which transformations must be applied. if eigenvalues only are being computed, i1 and i2 are set inside the main Loop Loop over remaining block of column Loop over the remaining rows/columns of the matrix Loop over remaining block of column 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" end of "if ( mycol .lt. np-1 )..." Loop ************************************* modification Loop the distance for sending and receiving for each level starts end of "if ( mycol .lt. np-1 )..." Loop ************************************* modification Loop the distance for sending and receiving for each level starts temporary variables. the following variables are used within a few lines after they are set and do hold state from one Loop end of "if ( mycol .lt. np-1 )..." Loop ************************************* modification Loop the distance for sending and receiving for each level starts end of "if ( mycol .lt. np-1 )..." Loop ************************************* modification Loop the distance for sending and receiving for each level starts only the eliminations of unknowns > ln-bw have an effect on the last bw columns. Loop over them.. temporary variables. the following variables are used within a few lines after they are set and do hold state from one Loop necessary to scan the "tridiagonal portion of the matrix." in the lapack algorithm zlahqr, a Loop of m goes from i-2 down t h(m,m),h(m+1,m+1),h(m+1,m),h(m,m+1),h(m-1,m-1),h(m,m-1), and to which transformations must be applied. if eigenvalues only are being computed, i1 and i2 are set inside the main Loop Loop over the remaining rows/columns of the matrix Loop over remaining block of column Loop over the remaining rows/columns of the matrix Loop over remaining block of column exit the Loop if the growth factor is too small end of "if ( mycol .lt. np-1 )..." Loop ************************************* modification Loop the distance for sending and receiving for each level starts end of "if ( mycol .lt. np-1 )..." Loop ************************************* modification Loop the distance for sending and receiving for each level starts Loop through eigenvalues of block nblk inner Loop to which transformations must be applied. if eigenvalues only are being computed, i1 and i2 are set inside the main Loop inner Loop |
| loops loops 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 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 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 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 |
| lot lot work is done on that. at the end of the border, the data is passed back and everything stays a lot simpler work is done on that. at the end of the border, the data is passed back and everything stays a lot simpler work is done on that. at the end of the border, the data is passed back and everything stays a lot simpler work is done on that. at the end of the border, the data is passed back and everything stays a lot simpler |
| lower lower a = l * u where l is a product of unit lower bidiagona diagonal and first superdiagonal. where x is an n element vector and t is an n by n upper or lower triangular matrix arguments a = l * u where l is a product of unit lower bidiagona diagonal and first superdiagonal. where x is an n element vector and t is an n by n upper or lower triangular matrix arguments apply factorization to lower connection block bl_ apply factorization to upper connection block bu_i dl (local input/local output) complex pointer to local part of global vector storing the lower diagonal of th aligned with d. apply factorization to lower connection block bl_ dl (local input/local output) complex pointer to local part of global vector storing the lower diagonal of th aligned with d. lbwl, lbwu: lower and upper bandwidth of local solve lm is the number of rows which is usually nb except for pcgebd2 reduces a complex general m-by-n distributed matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1) to upper or lower bidiagona pcgebrd reduces a complex general m-by-n distributed matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1) to upper or lower bidiagona and below the diagonal of sub( a ) contain the m by min(m,n) lower trapezoidal matrix l (l is lower triangular if m <= n) sent the unitary matrix q as a product of elementary and below the diagonal of sub( a ) contain the m by min(m,n) lower trapezoidal matrix l (l is lower triangular if m <= n) sent the unitary matrix q as a product of elementary sub( a ) which is to be factored. on exit, if m >= n, the lower triangle of the distributed submatri triangular matrix l; if m <= n, the elements on and below sub( a ) which is to be factored. on exit, if m >= n, the lower triangle of the distributed submatri triangular matrix l; if m <= n, the elements on and below used to factor sub( a ) as sub( a ) = p * l * u, where p is a permu- tation matrix, l is unit lower triangular, and u is upper triangular used to solve the system of equations sub( a ) * x = sub( b ). a = p * l * u, where p is a permutation matrix, l is a unit lower triangula the factorization has the form sub( a ) = p * l * u, where p is a permutation matrix, l is lower triangular with unit diagona (upper trapezoidal if m < n). the factorization has the form sub( a ) = p * l * u, where p is a permutation matrix, l is lower triangular with unit diagonal ele (upper trapezoidal if m < n). l and u are stored in sub( a ). uplo (global input) character*1 specifies whether the upper or lower triangular part of th = 'u': upper triangular uplo (global input) character*1 specifies whether the upper or lower triangular part of th = 'u': upper triangular uplo (global input) character*1 specifies whether the upper or lower triangular part of th = 'u': upper triangular factored as u**h*u; = 'l': lower triangle of sub( a ) is stored and sub( b ) i factored as u**h*u; = 'l': lower triangle of sub( a ) is stored and sub( b ) i = 'u': upper triangles of sub( a ) and sub( b ) are stored; = 'l': lower triangles of sub( a ) and sub( b ) are stored n (global input) integer factored as u**h*u; = 'l': lower triangle of sub( a ) is stored and sub( b ) i uplo (global input) character specifies whether the upper or lower triangular part of th = 'u': upper triangular uplo (global input) character specifies whether the upper or lower triangular part of th = 'u': upper triangular uplo (global input) character specifies whether the upper or lower triangular part of th = 'u': upper triangular uplo (global input) character specifies whether the upper or lower triangular part of th = 'u': upper triangular m-by-n distributed matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1) to upper or lower bidiagonal form by an unitary transformation q' * a * p, an mation to the unreduced part of sub( a ). est (global output) real an estimate (a lower bound) for norm(a) kase (local input/local output) integer = 'u': upper triangular part is copied; the strictly lower triangular part of sub( a ) is not referenced upper triangular part of sub( a ) is not referenced; = 'u': upper triangular part is copied; the strictly lower triangular part of sub( a ) is not referenced upper triangular part of sub( a ) is not referenced; lower triangular matri uplo (global input) character specifies whether the upper or lower triangular part of th = 'u': upper triangular if direct = 'b', h = h(k) . . . h(2) h(1) and t is lower triangular if storev = 'c', the vector which defines the elementary reflector t (local input) complex array, dimension mb_v by mb_v the lower triangular matrix t in the representation of th if direct = 'b', h = h(k) . . . h(2) h(1) and t is lower triangular if storev = 'c', the vector which defines the elementary reflector cto * a(i,j) / cfrom does not over/underflow. type specifies that sub( a ) may be full, upper triangular, lower triangular or uppe set: = 'u': upper triangular part is set; the strictly lower = 'l': lower triangular part is set; the strictly upper set: = 'u': upper triangular part is set; the strictly lower = 'l': lower triangular part is set; the strictly upper if uplo = 'l', pclatrd reduces the first nb rows and columns of a matrix, of which the lower triangle is supplied this is an auxiliary routine called by pchetrd. a is lower triangular pclauu2 computes the product u * u' or l' * l, where the triangular factor u or l is stored in the upper or lower triangular part o pclauum computes the product u * u' or l' * l, where the triangular factor u or l is stored in the upper or lower triangular part o = 'u': upper triangle of a(1:n, ja:ja+n-1) is stored; = 'l': lower triangle of a(1:n, ja:ja+n-1) is stored n (global input) integer = 'u': upper triangle of a(1:n, ja:ja+n-1) is stored; = 'l': lower triangle of a(1:n, ja:ja+n-1) is stored n (global input) integer specifies whether the factor stored in a(ia:ia+n-1,ja:ja+n-1) is upper or lower triangular = 'l': lower triangular uplo (global input) character*1 specifies whether the upper or lower triangular part of th = 'u': upper triangular where u is an upper triangular matrix and l is a lower triangula system of equations. a = l * l**t, if uplo = 'l', where u is an upper triangular matrix and l is a lower triangula where u is an upper triangular matrix and l is lower triangular notes where u is an upper triangular matrix and l is lower triangular notes = 'u': upper triangle of sub( a ) is stored; = 'l': lower triangle of sub( a ) is stored n (global input) integer = 'u': upper triangle of sub( a ) is stored; = 'l': lower triangle of sub( a ) is stored n (global input) integer = 'u': upper triangle of a(1:n, ja:ja+n-1) is stored; = 'l': lower triangle of a(1:n, ja:ja+n-1) is stored n (global input) integer = 'u': upper triangle of a(1:n, ja:ja+n-1) is stored; = 'l': lower triangle of a(1:n, ja:ja+n-1) is stored n (global input) integer dimension ( lwork ) on output, work(1) gives a lower bound on th orthogonalization (see orfac). = 'u': a(ia:ia+n-1,ja:ja+n-1) is upper triangular; = 'l': a(ia:ia+n-1,ja:ja+n-1) is lower triangular diag (global input) character = 'u': sub( a ) is upper triangular; = 'l': sub( a ) is lower triangular trans (global input) character*1 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 = 'u': sub( a ) is upper triangular; = 'l': sub( a ) is lower triangular trans (global input) character reflectors from pchetrd; = 'l': lower triangle of a(ia:*,ja:*) contains elementar apply factorization to lower connection block bl_ apply factorization to upper connection block bu_i dl (local input/local output) double precision pointer to local part of global vector storing the lower diagonal of th aligned with d. apply factorization to lower connection block bl_ dl (local input/local output) double precision pointer to local part of global vector storing the lower diagonal of th aligned with d. lbwl, lbwu: lower and upper bandwidth of local solve lm is the number of rows which is usually nb except for pdgebd2 reduces a real general m-by-n distributed matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1) to upper or lower bidiagona pdgebrd reduces a real general m-by-n distributed matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1) to upper or lower bidiagona and below the diagonal of sub( a ) contain the m by min(m,n) lower trapezoidal matrix l (l is lower triangular if m <= n) sent the orthogonal matrix q as a product of elementary and below the diagonal of sub( a ) contain the m by min(m,n) lower trapezoidal matrix l (l is lower triangular if m <= n) sent the orthogonal matrix q as a product of elementary sub( a ) which is to be factored. on exit, if m >= n, the lower triangle of the distributed submatri triangular matrix l; if m <= n, the elements on and below sub( a ) which is to be factored. on exit, if m >= n, the lower triangle of the distributed submatri triangular matrix l; if m <= n, the elements on and below used to factor sub( a ) as sub( a ) = p * l * u, where p is a permu- tation matrix, l is unit lower triangular, and u is upper triangular used to solve the system of equations sub( a ) * x = sub( b ). a = p * l * u, where p is a permutation matrix, l is a unit lower triangula the factorization has the form sub( a ) = p * l * u, where p is a permutation matrix, l is lower triangular with unit diagona (upper trapezoidal if m < n). the factorization has the form sub( a ) = p * l * u, where p is a permutation matrix, l is lower triangular with unit diagonal ele (upper trapezoidal if m < n). l and u are stored in sub( a ). m-by-n distributed matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1) to upper or lower bidiagonal form by an orthogonal transformation q' * a * p transformation to the unreduced part of sub( a ). est (global output) double precision an estimate (a lower bound) for norm(a) kase (local input/local output) integer = 'u': upper triangular part is copied; the strictly lower triangular part of sub( a ) is not referenced upper triangular part of sub( a ) is not referenced; = 'u': upper triangular part is copied; the strictly lower triangular part of sub( a ) is not referenced upper triangular part of sub( a ) is not referenced; 2 : dense; 3 : non-zero in the lower half only lower triangular matri uplo (global input) character specifies whether the upper or lower triangular part of th = 'u': upper triangular if direct = 'b', h = h(k) . . . h(2) h(1) and t is lower triangular if storev = 'c', the vector which defines the elementary reflector t (local input) double precision array, dimension mb_v by mb_v the lower triangular matrix t in the representation of th if direct = 'b', h = h(k) . . . h(2) h(1) and t is lower triangular if storev = 'c', the vector which defines the elementary reflector cto * a(i,j) / cfrom does not over/underflow. type specifies that sub( a ) may be full, upper triangular, lower triangular or uppe set: = 'u': upper triangular part is set; the strictly lower = 'l': lower triangular part is set; the strictly upper set: = 'u': upper triangular part is set; the strictly lower = 'l': lower triangular part is set; the strictly upper if uplo = 'l', pdlatrd reduces the first nb rows and columns of a matrix, of which the lower triangle is supplied this is an auxiliary routine called by pdsytrd. pdlauu2 computes the product u * u' or l' * l, where the triangular factor u or l is stored in the upper or lower triangular part o pdlauum computes the product u * u' or l' * l, where the triangular factor u or l is stored in the upper or lower triangular part o reflectors from pdsytrd; = 'l': lower triangle of a(ia:*,ja:*) contains elementar = 'u': upper triangle of a(1:n, ja:ja+n-1) is stored; = 'l': lower triangle of a(1:n, ja:ja+n-1) is stored n (global input) integer = 'u': upper triangle of a(1:n, ja:ja+n-1) is stored; = 'l': lower triangle of a(1:n, ja:ja+n-1) is stored n (global input) integer specifies whether the factor stored in a(ia:ia+n-1,ja:ja+n-1) is upper or lower triangular = 'l': lower triangular uplo (global input) character*1 specifies whether the upper or lower triangular part of th = 'u': upper triangular where u is an upper triangular matrix and l is a lower triangula system of equations. a = l * l**t, if uplo = 'l', where u is an upper triangular matrix and l is a lower triangula where u is an upper triangular matrix and l is lower triangular notes where u is an upper triangular matrix and l is lower triangular notes = 'u': upper triangle of sub( a ) is stored; = 'l': lower triangle of sub( a ) is stored n (global input) integer = 'u': upper triangle of sub( a ) is stored; = 'l': lower triangle of sub( a ) is stored n (global input) integer vl (global input) double precision if range='v', the lower bound of the interval to be searche returned. not referenced if range='a' or 'i'. dimension ( lwork ) on output, work(1) gives a lower bound on th orthogonalization (see orfac). uplo (global input) character*1 specifies whether the upper or lower triangular part of th = 'u': upper triangular uplo (global input) character*1 specifies whether the upper or lower triangular part of th = 'u': upper triangular uplo (global input) character*1 specifies whether the upper or lower triangular part of th = 'u': upper triangular factored as u**t*u; = 'l': lower triangle of sub( a ) is stored and sub( b ) i factored as u**t*u; = 'l': lower triangle of sub( a ) is stored and sub( b ) i = 'u': upper triangles of sub( a ) and sub( b ) are stored; = 'l': lower triangles of sub( a ) and sub( b ) are stored n (global input) integer factored as u**h*u; = 'l': lower triangle of sub( a ) is stored and sub( b ) i uplo (global input) character specifies whether the upper or lower triangular part of th = 'u': upper triangular uplo (global input) character specifies whether the upper or lower triangular part of th = 'u': upper triangular uplo (global input) character specifies whether the upper or lower triangular part of th = 'u': upper triangular uplo (global input) character specifies whether the upper or lower triangular part of th = 'u': upper triangular = 'u': a(ia:ia+n-1,ja:ja+n-1) is upper triangular; = 'l': a(ia:ia+n-1,ja:ja+n-1) is lower triangular diag (global input) character = 'u': sub( a ) is upper triangular; = 'l': sub( a ) is lower triangular trans (global input) character*1 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 = 'u': sub( a ) is upper triangular; = 'l': sub( a ) is lower triangular trans (global input) character this routine will not function correctly if it is converted to all lower case. converting it to all upper case is allowed arguments apply factorization to lower connection block bl_ apply factorization to upper connection block bu_i dl (local input/local output) real pointer to local part of global vector storing the lower diagonal of th aligned with d. apply factorization to lower connection block bl_ dl (local input/local output) real pointer to local part of global vector storing the lower diagonal of th aligned with d. lbwl, lbwu: lower and upper bandwidth of local solve lm is the number of rows which is usually nb except for psgebd2 reduces a real general m-by-n distributed matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1) to upper or lower bidiagona psgebrd reduces a real general m-by-n distributed matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1) to upper or lower bidiagona and below the diagonal of sub( a ) contain the m by min(m,n) lower trapezoidal matrix l (l is lower triangular if m <= n) sent the orthogonal matrix q as a product of elementary and below the diagonal of sub( a ) contain the m by min(m,n) lower trapezoidal matrix l (l is lower triangular if m <= n) sent the orthogonal matrix q as a product of elementary sub( a ) which is to be factored. on exit, if m >= n, the lower triangle of the distributed submatri triangular matrix l; if m <= n, the elements on and below sub( a ) which is to be factored. on exit, if m >= n, the lower triangle of the distributed submatri triangular matrix l; if m <= n, the elements on and below used to factor sub( a ) as sub( a ) = p * l * u, where p is a permu- tation matrix, l is unit lower triangular, and u is upper triangular used to solve the system of equations sub( a ) * x = sub( b ). a = p * l * u, where p is a permutation matrix, l is a unit lower triangula the factorization has the form sub( a ) = p * l * u, where p is a permutation matrix, l is lower triangular with unit diagona (upper trapezoidal if m < n). the factorization has the form sub( a ) = p * l * u, where p is a permutation matrix, l is lower triangular with unit diagonal ele (upper trapezoidal if m < n). l and u are stored in sub( a ). m-by-n distributed matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1) to upper or lower bidiagonal form by an orthogonal transformation q' * a * p transformation to the unreduced part of sub( a ). est (global output) real an estimate (a lower bound) for norm(a) kase (local input/local output) integer = 'u': upper triangular part is copied; the strictly lower triangular part of sub( a ) is not referenced upper triangular part of sub( a ) is not referenced; = 'u': upper triangular part is copied; the strictly lower triangular part of sub( a ) is not referenced upper triangular part of sub( a ) is not referenced; 2 : dense; 3 : non-zero in the lower half only lower triangular matri uplo (global input) character specifies whether the upper or lower triangular part of th = 'u': upper triangular if direct = 'b', h = h(k) . . . h(2) h(1) and t is lower triangular if storev = 'c', the vector which defines the elementary reflector t (local input) real array, dimension mb_v by mb_v the lower triangular matrix t in the representation of th if direct = 'b', h = h(k) . . . h(2) h(1) and t is lower triangular if storev = 'c', the vector which defines the elementary reflector cto * a(i,j) / cfrom does not over/underflow. type specifies that sub( a ) may be full, upper triangular, lower triangular or uppe set: = 'u': upper triangular part is set; the strictly lower = 'l': lower triangular part is set; the strictly upper set: = 'u': upper triangular part is set; the strictly lower = 'l': lower triangular part is set; the strictly upper if uplo = 'l', pslatrd reduces the first nb rows and columns of a matrix, of which the lower triangle is supplied this is an auxiliary routine called by pssytrd. pslauu2 computes the product u * u' or l' * l, where the triangular factor u or l is stored in the upper or lower triangular part o pslauum computes the product u * u' or l' * l, where the triangular factor u or l is stored in the upper or lower triangular part o reflectors from pssytrd; = 'l': lower triangle of a(ia:*,ja:*) contains elementar = 'u': upper triangle of a(1:n, ja:ja+n-1) is stored; = 'l': lower triangle of a(1:n, ja:ja+n-1) is stored n (global input) integer = 'u': upper triangle of a(1:n, ja:ja+n-1) is stored; = 'l': lower triangle of a(1:n, ja:ja+n-1) is stored n (global input) integer specifies whether the factor stored in a(ia:ia+n-1,ja:ja+n-1) is upper or lower triangular = 'l': lower triangular uplo (global input) character*1 specifies whether the upper or lower triangular part of th = 'u': upper triangular where u is an upper triangular matrix and l is a lower triangula system of equations. a = l * l**t, if uplo = 'l', where u is an upper triangular matrix and l is a lower triangula where u is an upper triangular matrix and l is lower triangular notes where u is an upper triangular matrix and l is lower triangular notes = 'u': upper triangle of sub( a ) is stored; = 'l': lower triangle of sub( a ) is stored n (global input) integer = 'u': upper triangle of sub( a ) is stored; = 'l': lower triangle of sub( a ) is stored n (global input) integer vl (global input) real if range='v', the lower bound of the interval to be searche returned. not referenced if range='a' or 'i'. dimension ( lwork ) on output, work(1) gives a lower bound on th orthogonalization (see orfac). uplo (global input) character*1 specifies whether the upper or lower triangular part of th = 'u': upper triangular uplo (global input) character*1 specifies whether the upper or lower triangular part of th = 'u': upper triangular uplo (global input) character*1 specifies whether the upper or lower triangular part of th = 'u': upper triangular factored as u**t*u; = 'l': lower triangle of sub( a ) is stored and sub( b ) i factored as u**t*u; = 'l': lower triangle of sub( a ) is stored and sub( b ) i = 'u': upper triangles of sub( a ) and sub( b ) are stored; = 'l': lower triangles of sub( a ) and sub( b ) are stored n (global input) integer factored as u**h*u; = 'l': lower triangle of sub( a ) is stored and sub( b ) i uplo (global input) character specifies whether the upper or lower triangular part of th = 'u': upper triangular uplo (global input) character specifies whether the upper or lower triangular part of th = 'u': upper triangular uplo (global input) character specifies whether the upper or lower triangular part of th = 'u': upper triangular uplo (global input) character specifies whether the upper or lower triangular part of th = 'u': upper triangular = 'u': a(ia:ia+n-1,ja:ja+n-1) is upper triangular; = 'l': a(ia:ia+n-1,ja:ja+n-1) is lower triangular diag (global input) character = 'u': sub( a ) is upper triangular; = 'l': sub( a ) is lower triangular trans (global input) character*1 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 = 'u': sub( a ) is upper triangular; = 'l': sub( a ) is lower triangular trans (global input) character apply factorization to lower connection block bl_ apply factorization to upper connection block bu_i dl (local input/local output) complex*16 pointer to local part of global vector storing the lower diagonal of th aligned with d. apply factorization to lower connection block bl_ dl (local input/local output) complex*16 pointer to local part of global vector storing the lower diagonal of th aligned with d. lbwl, lbwu: lower and upper bandwidth of local solve lm is the number of rows which is usually nb except for pzgebd2 reduces a complex general m-by-n distributed matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1) to upper or lower bidiagona pzgebrd reduces a complex general m-by-n distributed matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1) to upper or lower bidiagona and below the diagonal of sub( a ) contain the m by min(m,n) lower trapezoidal matrix l (l is lower triangular if m <= n) sent the unitary matrix q as a product of elementary and below the diagonal of sub( a ) contain the m by min(m,n) lower trapezoidal matrix l (l is lower triangular if m <= n) sent the unitary matrix q as a product of elementary sub( a ) which is to be factored. on exit, if m >= n, the lower triangle of the distributed submatri triangular matrix l; if m <= n, the elements on and below sub( a ) which is to be factored. on exit, if m >= n, the lower triangle of the distributed submatri triangular matrix l; if m <= n, the elements on and below used to factor sub( a ) as sub( a ) = p * l * u, where p is a permu- tation matrix, l is unit lower triangular, and u is upper triangular used to solve the system of equations sub( a ) * x = sub( b ). a = p * l * u, where p is a permutation matrix, l is a unit lower triangula the factorization has the form sub( a ) = p * l * u, where p is a permutation matrix, l is lower triangular with unit diagona (upper trapezoidal if m < n). the factorization has the form sub( a ) = p * l * u, where p is a permutation matrix, l is lower triangular with unit diagonal ele (upper trapezoidal if m < n). l and u are stored in sub( a ). uplo (global input) character*1 specifies whether the upper or lower triangular part of th = 'u': upper triangular uplo (global input) character*1 specifies whether the upper or lower triangular part of th = 'u': upper triangular uplo (global input) character*1 specifies whether the upper or lower triangular part of th = 'u': upper triangular factored as u**h*u; = 'l': lower triangle of sub( a ) is stored and sub( b ) i factored as u**h*u; = 'l': lower triangle of sub( a ) is stored and sub( b ) i = 'u': upper triangles of sub( a ) and sub( b ) are stored; = 'l': lower triangles of sub( a ) and sub( b ) are stored n (global input) integer factored as u**h*u; = 'l': lower triangle of sub( a ) is stored and sub( b ) i uplo (global input) character specifies whether the upper or lower triangular part of th = 'u': upper triangular uplo (global input) character specifies whether the upper or lower triangular part of th = 'u': upper triangular uplo (global input) character specifies whether the upper or lower triangular part of th = 'u': upper triangular uplo (global input) character specifies whether the upper or lower triangular part of th = 'u': upper triangular m-by-n distributed matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1) to upper or lower bidiagonal form by an unitary transformation q' * a * p, an mation to the unreduced part of sub( a ). est (global output) double precision an estimate (a lower bound) for norm(a) kase (local input/local output) integer = 'u': upper triangular part is copied; the strictly lower triangular part of sub( a ) is not referenced upper triangular part of sub( a ) is not referenced; = 'u': upper triangular part is copied; the strictly lower triangular part of sub( a ) is not referenced upper triangular part of sub( a ) is not referenced; lower triangular matri uplo (global input) character specifies whether the upper or lower triangular part of th = 'u': upper triangular if direct = 'b', h = h(k) . . . h(2) h(1) and t is lower triangular if storev = 'c', the vector which defines the elementary reflector t (local input) complex*16 array, dimension mb_v by mb_v the lower triangular matrix t in the representation of th if direct = 'b', h = h(k) . . . h(2) h(1) and t is lower triangular if storev = 'c', the vector which defines the elementary reflector cto * a(i,j) / cfrom does not over/underflow. type specifies that sub( a ) may be full, upper triangular, lower triangular or uppe set: = 'u': upper triangular part is set; the strictly lower = 'l': lower triangular part is set; the strictly upper set: = 'u': upper triangular part is set; the strictly lower = 'l': lower triangular part is set; the strictly upper if uplo = 'l', pzlatrd reduces the first nb rows and columns of a matrix, of which the lower triangle is supplied this is an auxiliary routine called by pzhetrd. a is lower triangular pzlauu2 computes the product u * u' or l' * l, where the triangular factor u or l is stored in the upper or lower triangular part o pzlauum computes the product u * u' or l' * l, where the triangular factor u or l is stored in the upper or lower triangular part o = 'u': upper triangle of a(1:n, ja:ja+n-1) is stored; = 'l': lower triangle of a(1:n, ja:ja+n-1) is stored n (global input) integer = 'u': upper triangle of a(1:n, ja:ja+n-1) is stored; = 'l': lower triangle of a(1:n, ja:ja+n-1) is stored n (global input) integer specifies whether the factor stored in a(ia:ia+n-1,ja:ja+n-1) is upper or lower triangular = 'l': lower triangular uplo (global input) character*1 specifies whether the upper or lower triangular part of th = 'u': upper triangular where u is an upper triangular matrix and l is a lower triangula system of equations. a = l * l**t, if uplo = 'l', where u is an upper triangular matrix and l is a lower triangula where u is an upper triangular matrix and l is lower triangular notes where u is an upper triangular matrix and l is lower triangular notes = 'u': upper triangle of sub( a ) is stored; = 'l': lower triangle of sub( a ) is stored n (global input) integer = 'u': upper triangle of sub( a ) is stored; = 'l': lower triangle of sub( a ) is stored n (global input) integer = 'u': upper triangle of a(1:n, ja:ja+n-1) is stored; = 'l': lower triangle of a(1:n, ja:ja+n-1) is stored n (global input) integer = 'u': upper triangle of a(1:n, ja:ja+n-1) is stored; = 'l': lower triangle of a(1:n, ja:ja+n-1) is stored n (global input) integer dimension ( lwork ) on output, work(1) gives a lower bound on th orthogonalization (see orfac). = 'u': a(ia:ia+n-1,ja:ja+n-1) is upper triangular; = 'l': a(ia:ia+n-1,ja:ja+n-1) is lower triangular diag (global input) character = 'u': sub( a ) is upper triangular; = 'l': sub( a ) is lower triangular trans (global input) character*1 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 = 'u': sub( a ) is upper triangular; = 'l': sub( a ) is lower triangular trans (global input) character reflectors from pzhetrd; = 'l': lower triangle of a(ia:*,ja:*) contains elementar a = l * u where l is a product of unit lower bidiagona diagonal and first superdiagonal. where x is an n element vector and t is an n by n upper or lower triangular matrix arguments a = l * u where l is a product of unit lower bidiagona diagonal and first superdiagonal. where x is an n element vector and t is an n by n upper or lower triangular matrix arguments |
| LPTR LPTR LPTR is the pointer to the beginning of th LPTR is the pointer to the beginning of th LPTR is the pointer to the beginning of th LPTR is the pointer to the beginning of th |
| LRWORK LRWORK rwork (local workspace/local output) real array, dimension (LRWORK rwork (local workspace/local output) real array, dimension (LRWORK rwork (local workspace/local output) real array, dimension (LRWORK rwork (local workspace/local output) real array, dimension (LRWORK rwork (local workspace/output) complex array, dimension (LRWORK real workspace needed to rwork (local workspace/output) real array, dimension (LRWORK guarantee completion. if the input parameters are incorrect, rwork (local workspace/output) real array, dimension max(3,LRWORK workspace required for efficient execution. rwork (local workspace/output) real array, dimension max(3,LRWORK required for optimal efficiency rwork (local workspace/local output) complex array, dimension (LRWORK rwork (local workspace) real array, dimension (LRWORK lrwork (local input) integer dimension of rwork rwork (local workspace/local output) real array, dimension (LRWORK rwork (local workspace/local output) real array, dimension (LRWORK rwork (local workspace/local output) real array, dimension (LRWORK rwork (local workspace/local output) real array, dimension (LRWORK rwork (local workspace/local output) real array, dimension (LRWORK rwork (local workspace/local output) double precision array, dimension (LRWORK rwork (local workspace/local output) double precision array, dimension (LRWORK rwork (local workspace/local output) double precision array, dimension (LRWORK rwork (local workspace/local output) double precision array, dimension (LRWORK rwork (local workspace/output) complex*16 array, dimension (LRWORK double precision workspace needed to rwork (local workspace/output) double precision array, dimension (LRWORK guarantee completion. if the input parameters are incorrect, rwork (local workspace/output) double precision array, dimension max(3,LRWORK workspace required for efficient execution. rwork (local workspace/output) double precision array, dimension max(3,LRWORK required for optimal efficiency rwork (local workspace/local output) complex*16 array, dimension (LRWORK rwork (local workspace) double precision array, dimension (LRWORK lrwork (local input) integer dimension of rwork rwork (local workspace/local output) double precision array, dimension (LRWORK rwork (local workspace/local output) double precision array, dimension (LRWORK rwork (local workspace/local output) double precision array, dimension (LRWORK rwork (local workspace/local output) double precision array, dimension (LRWORK rwork (local workspace/local output) double precision array, dimension (LRWORK |
| LSAME LSAME end of "if( LSAME( trans, 'n' ) )".. end of "if( LSAME( trans, 'n' ) )".. end of "if( LSAME( trans, 'n' ) )".. end of "if( LSAME( uplo, 'l' ) )".. end of "if( LSAME( trans, 'n' ) )".. end of "if( LSAME( uplo, 'l' ) )".. end of "if( LSAME( trans, 'n' ) )".. end of "if( LSAME( trans, 'n' ) )".. |
| LSAVE LSAVE LSAVE (output) double precisio if ijob = 1, this is the largest floating point number LSAVE (output) rea if ijob = 1, this is the largest floating point number |
| LTAU LTAU lwork is local input and must be at least lwork >= LTAU + max( lwf, lws ) wher ltau = numroc( ja+min(m,n)-1, nb_a, mycol, csrc_a, npcol ), tau (local input) complex array, dimension LTAU, wher if side = 'l' and uplo = 'l', ltau = locc(ja+m-2), lwork is local input and must be at least lwork >= LTAU + max( lwf, lws ) wher ltau = numroc( ja+min(m,n)-1, nb_a, mycol, csrc_a, npcol ), tau (local input) double precision array, dimension LTAU, wher if side = 'l' and uplo = 'l', ltau = locc(ja+m-2), lwork is local input and must be at least lwork >= LTAU + max( lwf, lws ) wher ltau = numroc( ja+min(m,n)-1, nb_a, mycol, csrc_a, npcol ), tau (local input) real array, dimension LTAU, wher if side = 'l' and uplo = 'l', ltau = locc(ja+m-2), lwork is local input and must be at least lwork >= LTAU + max( lwf, lws ) wher ltau = numroc( ja+min(m,n)-1, nb_a, mycol, csrc_a, npcol ), tau (local input) complex*16 array, dimension LTAU, wher if side = 'l' and uplo = 'l', ltau = locc(ja+m-2), |
| LTLI LTLI lijp1: local index j+1: the local col number for col index+1 LTLI: lower triangular local index i: the local row for th ltlip1: lower triangular local index i+1: the local row for the lijp1: local index j+1: the local col number for col index+1 LTLI: lower triangular local index i: the local row for th ltlip1: lower triangular local index i+1: the local row for the lijp1: local index j+1: the local col number for col index+1 LTLI: lower triangular local index i: the local row for th ltlip1: lower triangular local index i+1: the local row for the lijp1: local index j+1: the local col number for col index+1 LTLI: lower triangular local index i: the local row for th ltlip1: lower triangular local index i+1: the local row for the |
| LTLIP1 LTLIP1 upper left entry in tril( a(index, index) ) LTLIP1: lower triangular local index i+1: the local row for th upper left entry in tril( a(index, index) ) LTLIP1: lower triangular local index i+1: the local row for th upper left entry in tril( a(index, index) ) LTLIP1: lower triangular local index i+1: the local row for th upper left entry in tril( a(index, index) ) LTLIP1: lower triangular local index i+1: the local row for th |
| LTNM0 LTNM0 nqm1: the number of local columns in a( index+1:n, index:n ) LTNM0: the number of local rows & columns i ltnm1: the number of local rows & columns in nqm1: the number of local columns in a( index+1:n, index:n ) LTNM0: the number of local rows & columns i ltnm1: the number of local rows & columns in nqm1: the number of local columns in a( index+1:n, index:n ) LTNM0: the number of local rows & columns i ltnm1: the number of local rows & columns in nqm1: the number of local columns in a( index+1:n, index:n ) LTNM0: the number of local rows & columns i ltnm1: the number of local rows & columns in |
| LTNM1 LTNM1 tril( a( index:n, index:n ) ) LTNM1: the number of local rows & columns i note: ltnm0 == ltnm1 on all processors except the diagonal tril( a( index:n, index:n ) ) LTNM1: the number of local rows & columns i note: ltnm0 == ltnm1 on all processors except the diagonal tril( a( index:n, index:n ) ) LTNM1: the number of local rows & columns i note: ltnm0 == ltnm1 on all processors except the diagonal tril( a( index:n, index:n ) ) LTNM1: the number of local rows & columns i note: ltnm0 == ltnm1 on all processors except the diagonal |
| LWF LWF lwork is local input and must be at least lwork >= ltau + max( LWF, lws ) wher ltau = numroc( ja+min(m,n)-1, nb_a, mycol, csrc_a, npcol ), lwork is local input and must be at least lwork >= ltau + max( LWF, lws ) wher ltau = numroc( ja+min(m,n)-1, nb_a, mycol, csrc_a, npcol ), lwork is local input and must be at least lwork >= ltau + max( LWF, lws ) wher ltau = numroc( ja+min(m,n)-1, nb_a, mycol, csrc_a, npcol ), lwork is local input and must be at least lwork >= ltau + max( LWF, lws ) wher ltau = numroc( ja+min(m,n)-1, nb_a, mycol, csrc_a, npcol ), |
| LWMIN LWMIN qrmem = 2*n-2 LWMIN = 5*n + n*ldc + max( sizemqrleft, qrmem ) + variable definitions: qrmem = 2*n-2 LWMIN = 5*n + n*ldc + max( sizemqrleft, qrmem ) + variable definitions: |
| LWORK LWORK be overwritten in between calls to routines. work must be the size given in LWORK be overwritten in between calls to routines. work must be the size given in LWORK be overwritten in between calls to routines. work must be the size given in LWORK be overwritten in between calls to routines. work must be the size given in LWORK be overwritten in between calls to routines. work must be the size given in LWORK be overwritten in between calls to routines. work must be the size given in LWORK work (local workspace/local output) complex array, dimension (LWORK work (local workspace/local output) complex array, dimension (LWORK work (local workspace/local output) complex array, dimension (LWORK work (local workspace/local output) complex array, dimension (LWORK work (local workspace/local output) complex array, dimension (LWORK work (local workspace/local output) complex array, dimension (LWORK work (local workspace/local output) complex array, dimension (LWORK work (local workspace/local output) complex array, dimension (LWORK work (local workspace/local output) complex array, dimension (LWORK work (local workspace/local output) complex array, dimension (LWORK work (local workspace/local output) complex array, dimension (LWORK work (local workspace/local output) complex array, dimension (LWORK work (local workspace/local output) complex array, dimension (LWORK work (local workspace/local output) complex array, dimension (LWORK work (local workspace/local output) complex array, dimension (LWORK work (local workspace/local output) complex array, dimension (LWORK work (local workspace/output) complex array, dimension (LWORK work (local workspace/local output) complex array, dimension (LWORK work (local workspace/local output) complex array, dimension (LWORK work (local workspace/local output) complex array, dimension (LWORK work (local workspace/local output) complex array, dimension (LWORK work (local workspace/output) complex array, dimension (LWORK completion. if the input parameters are incorrect, work(1) work (local workspace/output) complex array, dimension (LWORK computation. space to hold the eigenvectors in z (m .le. descz(n_)) and sufficient workspace to compute them. (see LWORK below. computation unless range .eq. 'v'. space to hold the eigenvectors in z (m .le. descz(n_)) and sufficient workspace to compute them. (see LWORK below. computation unless range .eq. 'v'. provided, hence pchengst provides improved performance only when LWORK >= 2 * np0 * nb + nq0 * nb + nb * n in the following sub( a ) denotes a( ia:ia+n-1, ja:ja+n-1 ) and work (local workspace/local output) complex array, dimension (LWORK work (local workspace/local output) complex array, dimension (LWORK work (local workspace/local output) complex array, dimension (LWORK work (local workspace) complex array, dimension (LWORK work (local workspace) complex array, dimension (LWORK buf (local output) complex array of size LWORK lwork (global input) integer work (local workspace) complex*16 array, dimension ( LWORK lwork (local input) integer work (local workspace) real array dimension (LWORK nq0 if norm = '1', 'o' or 'o', work (local workspace) complex array, dimension (LWORK if side = 'l', work (local workspace) complex array, dimension (LWORK if side = 'l', buf (local output) complex array of size LWORK lwork (global input) integer work (local workspace) complex array, dimension (LWORK be overwritten in between calls to routines. work must be the size given in LWORK be overwritten in between calls to routines. work must be the size given in LWORK work (local workspace/local output) complex array, dimension (LWORK work (local workspace/local output) complex array, dimension (LWORK work (local workspace/local output) complex array, dimension (LWORK be overwritten in between calls to routines. work must be the size given in LWORK be overwritten in between calls to routines. work must be the size given in LWORK 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 work (local workspace/local output) complex array, dimension (LWORK work (local workspace/local output) complex array, dimension (LWORK work (local workspace/local output) complex array, dimension (LWORK work (local workspace/local output) complex array, dimension (LWORK work (local workspace/local output) complex array, dimension (LWORK work (local workspace/local output) complex array, dimension (LWORK work (local workspace/local output) complex array, dimension (LWORK work (local workspace/local output) complex array, dimension (LWORK work (local workspace/local output) complex array, dimension (LWORK work (local workspace/local output) complex array, dimension (LWORK work (local workspace/local output) complex array, dimension (LWORK work (local workspace/local output) complex array, dimension (LWORK work (local workspace/local output) complex array, dimension (LWORK work (local workspace/local output) complex array, dimension (LWORK work (local workspace/local output) complex array, dimension (LWORK work (local workspace/local output) complex array, dimension (LWORK work (local workspace/local output) complex array, dimension (LWORK work (local workspace/local output) complex array, dimension (LWORK work (local workspace/local output) complex array, dimension (LWORK work (local workspace/local output) complex array, dimension (LWORK work (local workspace/local output) complex array, dimension (LWORK work (local workspace/local output) complex array, dimension (LWORK work (local workspace/local output) complex array, dimension (LWORK work (local workspace/local output) complex array, dimension (LWORK be overwritten in between calls to routines. work must be the size given in LWORK be overwritten in between calls to routines. work must be the size given in LWORK be overwritten in between calls to routines. work must be the size given in LWORK be overwritten in between calls to routines. work must be the size given in LWORK be overwritten in between calls to routines. work must be the size given in LWORK be overwritten in between calls to routines. work must be the size given in LWORK work (local workspace/local output) double precision array, dimension (LWORK work (local workspace/local output) double precision array, dimension (LWORK work (local workspace/local output) double precision array, dimension (LWORK work (local workspace/local output) double precision array, dimension (LWORK work (local workspace/local output) double precision array, dimension (LWORK work (local workspace/local output) double precision array, dimension (LWORK work (local workspace/local output) double precision array, dimension (LWORK work (local workspace/local output) double precision array, dimension (LWORK work (local workspace/local output) double precision array, dimension (LWORK work (local workspace/local output) double precision array, dimension (LWORK work (local workspace/local output) double precision array, dimension (LWORK work (local workspace/local output) double precision array, dimension (LWORK work (local workspace/local output) double precision array, dimension (LWORK work (local workspace/local output) double precision array, dimension (LWORK work (local workspace/local output) double precision array, dimension (LWORK work (local workspace/local output) double precision array, dimension (LWORK work (local workspace/output) double precision array, dimension (LWORK work (local workspace/local output) double precision array, dimension (LWORK work (local workspace/local output) double precision array, dimension (LWORK work (local workspace/local output) double precision array, dimension (LWORK work (local workspace/local output) double precision array, dimension (LWORK work (local workspace) double precision array, dimension (LWORK buf (local output) double precision array of size LWORK lwork (global input) integer work (local workspace ) double precision array, dimension (LWORK np = numroc( n, mb_q, myrow, iqrow, nprow ) work (local workspace) double precision array, dimension (LWORK lwork (local input) integer dimension of work work (local workspace) complex*16 array, dimension ( LWORK lwork (local input) integer work (local workspace) double precision array dimension (LWORK nq0 if norm = '1', 'o' or 'o', work (local workspace) double precision dimension (LWORK work (local workspace) double precision dimension (LWORK work (local workspace) double precision array, dimension (LWORK if side = 'l', work (local workspace) double precision array, dimension (LWORK if side = 'l', buf (local output) double precision array of size LWORK lwork (global input) integer work (local workspace/local output) double precision array, dimension (LWORK the dimension of the array work. work (local workspace) double precision array, dimension (LWORK work (local workspace/local output) double precision array, dimension (LWORK work (local workspace/local output) double precision array, dimension (LWORK work (local workspace/local output) double precision array, dimension (LWORK work (local workspace/local output) double precision array, dimension (LWORK work (local workspace/local output) double precision array, dimension (LWORK work (local workspace/local output) double precision array, dimension (LWORK work (local workspace/local output) double precision array, dimension (LWORK work (local workspace/local output) double precision array, dimension (LWORK work (local workspace/local output) double precision array, dimension (LWORK work (local workspace/local output) double precision array, dimension (LWORK work (local workspace/local output) double precision array, dimension (LWORK work (local workspace/local output) double precision array, dimension (LWORK work (local workspace/local output) double precision array, dimension (LWORK work (local workspace/local output) double precision array, dimension (LWORK work (local workspace/local output) double precision array, dimension (LWORK work (local workspace/local output) double precision array, dimension (LWORK work (local workspace/local output) double precision array, dimension (LWORK work (local workspace/local output) double precision array, dimension (LWORK work (local workspace/local output) double precision array, dimension (LWORK work (local workspace/local output) double precision array, dimension (LWORK work (local workspace/local output) double precision array, dimension (LWORK be overwritten in between calls to routines. work must be the size given in LWORK be overwritten in between calls to routines. work must be the size given in LWORK work (local workspace/local output) double precision array, dimension (LWORK work (local workspace/local output) double precision array, dimension (LWORK work (local workspace/local output) double precision array, dimension (LWORK be overwritten in between calls to routines. work must be the size given in LWORK be overwritten in between calls to routines. work must be the size given in LWORK LWORK (local input) intege if lwork = -1, then lwork is global input and a workspace work (local workspace/output) double precision array, dimension (LWORK 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 work (local workspace/output) double precision array, dimension (LWORK needed to guarantee completion. work (local workspace/output) double precision array, dimension (LWORK space to hold the eigenvectors in z (m .le. descz(n_)) and sufficient workspace to compute them. (see LWORK below. computation unless range .eq. 'v'. space to hold the eigenvectors in z (m .le. descz(n_)) and sufficient workspace to compute them. (see LWORK below. computation unless range .eq. 'v'. provided, hence pdsyngst provides improved performance only when LWORK >= 2 * np0 * nb + nq0 * nb + nb * n in the following sub( a ) denotes a( ia:ia+n-1, ja:ja+n-1 ) and work (local workspace/local output) double precision array, dimension (LWORK work (local workspace/local output) double precision array, dimension (LWORK work (local workspace/local output) double precision array, dimension (LWORK work (local workspace) double precision array, dimension (LWORK work (local workspace/local output) double precision array, dimension (LWORK work (local workspace/local output) double precision array, dimension (LWORK work (local workspace/local output) double precision array, dimension (LWORK be overwritten in between calls to routines. work must be the size given in LWORK be overwritten in between calls to routines. work must be the size given in LWORK be overwritten in between calls to routines. work must be the size given in LWORK be overwritten in between calls to routines. work must be the size given in LWORK be overwritten in between calls to routines. work must be the size given in LWORK be overwritten in between calls to routines. work must be the size given in LWORK work (local workspace/local output) real array, dimension (LWORK work (local workspace/local output) real array, dimension (LWORK work (local workspace/local output) real array, dimension (LWORK work (local workspace/local output) real array, dimension (LWORK work (local workspace/local output) real array, dimension (LWORK work (local workspace/local output) real array, dimension (LWORK work (local workspace/local output) real array, dimension (LWORK work (local workspace/local output) real array, dimension (LWORK work (local workspace/local output) real array, dimension (LWORK work (local workspace/local output) real array, dimension (LWORK work (local workspace/local output) real array, dimension (LWORK work (local workspace/local output) real array, dimension (LWORK work (local workspace/local output) real array, dimension (LWORK work (local workspace/local output) real array, dimension (LWORK work (local workspace/local output) real array, dimension (LWORK work (local workspace/local output) real array, dimension (LWORK work (local workspace/output) real array, dimension (LWORK work (local workspace/local output) real array, dimension (LWORK work (local workspace/local output) real array, dimension (LWORK work (local workspace/local output) real array, dimension (LWORK work (local workspace/local output) real array, dimension (LWORK work (local workspace) real array, dimension (LWORK buf (local output) real array of size LWORK lwork (global input) integer work (local workspace ) real array, dimension (LWORK np = numroc( n, mb_q, myrow, iqrow, nprow ) work (local workspace) real array, dimension (LWORK lwork (local input) integer dimension of work work (local workspace) complex*16 array, dimension ( LWORK lwork (local input) integer work (local workspace) real array dimension (LWORK nq0 if norm = '1', 'o' or 'o', work (local workspace) real dimension (LWORK work (local workspace) real dimension (LWORK work (local workspace) real array, dimension (LWORK if side = 'l', work (local workspace) real array, dimension (LWORK if side = 'l', buf (local output) real array of size LWORK lwork (global input) integer work (local workspace/local output) real array, dimension (LWORK the dimension of the array work. work (local workspace) real array, dimension (LWORK work (local workspace/local output) real array, dimension (LWORK work (local workspace/local output) real array, dimension (LWORK work (local workspace/local output) real array, dimension (LWORK work (local workspace/local output) real array, dimension (LWORK work (local workspace/local output) real array, dimension (LWORK work (local workspace/local output) real array, dimension (LWORK work (local workspace/local output) real array, dimension (LWORK work (local workspace/local output) real array, dimension (LWORK work (local workspace/local output) real array, dimension (LWORK work (local workspace/local output) real array, dimension (LWORK work (local workspace/local output) real array, dimension (LWORK work (local workspace/local output) real array, dimension (LWORK work (local workspace/local output) real array, dimension (LWORK work (local workspace/local output) real array, dimension (LWORK work (local workspace/local output) real array, dimension (LWORK work (local workspace/local output) real array, dimension (LWORK work (local workspace/local output) real array, dimension (LWORK work (local workspace/local output) real array, dimension (LWORK work (local workspace/local output) real array, dimension (LWORK work (local workspace/local output) real array, dimension (LWORK work (local workspace/local output) real array, dimension (LWORK be overwritten in between calls to routines. work must be the size given in LWORK be overwritten in between calls to routines. work must be the size given in LWORK work (local workspace/local output) real array, dimension (LWORK work (local workspace/local output) real array, dimension (LWORK work (local workspace/local output) real array, dimension (LWORK be overwritten in between calls to routines. work must be the size given in LWORK be overwritten in between calls to routines. work must be the size given in LWORK LWORK (local input) intege if lwork = -1, then lwork is global input and a workspace work (local workspace/output) real array, dimension (LWORK 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 work (local workspace/output) real array, dimension (LWORK needed to guarantee completion. work (local workspace/output) real array, dimension (LWORK space to hold the eigenvectors in z (m .le. descz(n_)) and sufficient workspace to compute them. (see LWORK below. computation unless range .eq. 'v'. space to hold the eigenvectors in z (m .le. descz(n_)) and sufficient workspace to compute them. (see LWORK below. computation unless range .eq. 'v'. provided, hence pssyngst provides improved performance only when LWORK >= 2 * np0 * nb + nq0 * nb + nb * n in the following sub( a ) denotes a( ia:ia+n-1, ja:ja+n-1 ) and work (local workspace/local output) real array, dimension (LWORK work (local workspace/local output) real array, dimension (LWORK work (local workspace/local output) real array, dimension (LWORK work (local workspace) real array, dimension (LWORK work (local workspace/local output) real array, dimension (LWORK work (local workspace/local output) real array, dimension (LWORK work (local workspace/local output) real array, dimension (LWORK be overwritten in between calls to routines. work must be the size given in LWORK be overwritten in between calls to routines. work must be the size given in LWORK be overwritten in between calls to routines. work must be the size given in LWORK be overwritten in between calls to routines. work must be the size given in LWORK be overwritten in between calls to routines. work must be the size given in LWORK be overwritten in between calls to routines. work must be the size given in LWORK work (local workspace/local output) complex*16 array, dimension (LWORK work (local workspace/local output) complex*16 array, dimension (LWORK work (local workspace/local output) complex*16 array, dimension (LWORK work (local workspace/local output) complex*16 array, dimension (LWORK work (local workspace/local output) complex*16 array, dimension (LWORK work (local workspace/local output) complex*16 array, dimension (LWORK work (local workspace/local output) complex*16 array, dimension (LWORK work (local workspace/local output) complex*16 array, dimension (LWORK work (local workspace/local output) complex*16 array, dimension (LWORK work (local workspace/local output) complex*16 array, dimension (LWORK work (local workspace/local output) complex*16 array, dimension (LWORK work (local workspace/local output) complex*16 array, dimension (LWORK work (local workspace/local output) complex*16 array, dimension (LWORK work (local workspace/local output) complex*16 array, dimension (LWORK work (local workspace/local output) complex*16 array, dimension (LWORK work (local workspace/local output) complex*16 array, dimension (LWORK work (local workspace/output) complex*16 array, dimension (LWORK work (local workspace/local output) complex*16 array, dimension (LWORK work (local workspace/local output) complex*16 array, dimension (LWORK work (local workspace/local output) complex*16 array, dimension (LWORK work (local workspace/local output) complex*16 array, dimension (LWORK work (local workspace/output) complex*16 array, dimension (LWORK completion. if the input parameters are incorrect, work(1) work (local workspace/output) complex*16 array, dimension (LWORK computation. space to hold the eigenvectors in z (m .le. descz(n_)) and sufficient workspace to compute them. (see LWORK below. computation unless range .eq. 'v'. space to hold the eigenvectors in z (m .le. descz(n_)) and sufficient workspace to compute them. (see LWORK below. computation unless range .eq. 'v'. provided, hence pzhengst provides improved performance only when LWORK >= 2 * np0 * nb + nq0 * nb + nb * n in the following sub( a ) denotes a( ia:ia+n-1, ja:ja+n-1 ) and work (local workspace/local output) complex*16 array, dimension (LWORK work (local workspace/local output) complex*16 array, dimension (LWORK work (local workspace/local output) complex*16 array, dimension (LWORK work (local workspace) complex*16 array, dimension (LWORK work (local workspace) complex*16 array, dimension (LWORK buf (local output) complex*16 array of size LWORK lwork (global input) integer work (local workspace) complex*16 array, dimension ( LWORK lwork (local input) integer work (local workspace) double precision array dimension (LWORK nq0 if norm = '1', 'o' or 'o', work (local workspace) complex*16 array, dimension (LWORK if side = 'l', work (local workspace) complex*16 array, dimension (LWORK if side = 'l', buf (local output) complex*16 array of size LWORK lwork (global input) integer work (local workspace) complex*16 array, dimension (LWORK be overwritten in between calls to routines. work must be the size given in LWORK be overwritten in between calls to routines. work must be the size given in LWORK work (local workspace/local output) complex*16 array, dimension (LWORK work (local workspace/local output) complex*16 array, dimension (LWORK work (local workspace/local output) complex*16 array, dimension (LWORK be overwritten in between calls to routines. work must be the size given in LWORK be overwritten in between calls to routines. work must be the size given in LWORK 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 work (local workspace/local output) complex*16 array, dimension (LWORK work (local workspace/local output) complex*16 array, dimension (LWORK work (local workspace/local output) complex*16 array, dimension (LWORK work (local workspace/local output) complex*16 array, dimension (LWORK work (local workspace/local output) complex*16 array, dimension (LWORK work (local workspace/local output) complex*16 array, dimension (LWORK work (local workspace/local output) complex*16 array, dimension (LWORK work (local workspace/local output) complex*16 array, dimension (LWORK work (local workspace/local output) complex*16 array, dimension (LWORK work (local workspace/local output) complex*16 array, dimension (LWORK work (local workspace/local output) complex*16 array, dimension (LWORK work (local workspace/local output) complex*16 array, dimension (LWORK work (local workspace/local output) complex*16 array, dimension (LWORK work (local workspace/local output) complex*16 array, dimension (LWORK work (local workspace/local output) complex*16 array, dimension (LWORK work (local workspace/local output) complex*16 array, dimension (LWORK work (local workspace/local output) complex*16 array, dimension (LWORK work (local workspace/local output) complex*16 array, dimension (LWORK work (local workspace/local output) complex*16 array, dimension (LWORK work (local workspace/local output) complex*16 array, dimension (LWORK work (local workspace/local output) complex*16 array, dimension (LWORK work (local workspace/local output) complex*16 array, dimension (LWORK work (local workspace/local output) complex*16 array, dimension (LWORK work (local workspace/local output) complex*16 array, dimension (LWORK |
| LWS LWS lwork is local input and must be at least lwork >= ltau + max( lwf, LWS ) wher ltau = numroc( ja+min(m,n)-1, nb_a, mycol, csrc_a, npcol ), lwork is local input and must be at least lwork >= ltau + max( lwf, LWS ) wher ltau = numroc( ja+min(m,n)-1, nb_a, mycol, csrc_a, npcol ), lwork is local input and must be at least lwork >= ltau + max( lwf, LWS ) wher ltau = numroc( ja+min(m,n)-1, nb_a, mycol, csrc_a, npcol ), lwork is local input and must be at least lwork >= ltau + max( lwf, LWS ) wher ltau = numroc( ja+min(m,n)-1, nb_a, mycol, csrc_a, npcol ), |
| lying lying > 0: the algorithm failed to compute the info/(n+1) th eigenvalue while working on the submatrix lying i > 0: the algorithm failed to compute the info/(n+1) th eigenvalue while working on the submatrix lying i > 0: the algorithm failed to compute the info/(n+1) th eigenvalue while working on the submatrix lying i > 0: the algorithm failed to compute the info/(n+1) th eigenvalue while working on the submatrix lying i > 0: the algorithm failed to compute the info/(n+1) th eigenvalue while working on the submatrix lying i > 0: the algorithm failed to compute the info/(n+1) th eigenvalue while working on the submatrix lying i |