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| N_A N_A array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute matrix a. N_A (global) desca( n_ ) the number of columns in the distri mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca[ n_ ] the number of columns in the globa mb_a (global) desca[ mb_ ] the blocking factor used to distribu- array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca[ n_ ] the number of columns in the globa mb_a (global) desca[ mb_ ] the blocking factor used to distribu- array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute matrix a. N_A (global) desca( n_ ) the number of columns in the distri mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca[ n_ ] the number of columns in the globa mb_a (global) desca[ mb_ ] the blocking factor used to distribu- array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute matrix a. N_A (global) desca( n_ ) the number of columns in the distri mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca[ n_ ] the number of columns in the globa mb_a (global) desca[ mb_ ] the blocking factor used to distribu- array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute matrix a. N_A (global) desca( n_ ) the number of columns in the distri mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute array a. N_A (global) desca( n_ ) the number of columns in the globa mb_a (global) desca( mb_ ) the blocking factor used to distribute |
| N_B N_B ferr (local output) real array, dimension locc(N_B x(j) (the j-th column of the solution matrix ferr (local output) real array, dimension (loc(N_B) x(j) (the j-th column of the solution matrix x). ferr (local output) double precision array, dimension locc(N_B x(j) (the j-th column of the solution matrix ferr (local output) double precision array, dimension (loc(N_B) x(j) (the j-th column of the solution matrix x). ferr (local output) real array, dimension locc(N_B x(j) (the j-th column of the solution matrix ferr (local output) real array, dimension (loc(N_B) x(j) (the j-th column of the solution matrix x). ferr (local output) double precision array, dimension locc(N_B x(j) (the j-th column of the solution matrix ferr (local output) double precision array, dimension (loc(N_B) x(j) (the j-th column of the solution matrix x). |
| N_P N_P if( nprow.eq.npcol ) then ldw = locr( N_P + mod(jp-1, nb_p) ) + nb_ ldw = locr( n_p + mod(jp-1, nb_p) ) + if( nprow.eq.npcol ) then ldw = locr( N_P + mod(jp-1, nb_p) ) + nb_ ldw = locr( n_p + mod(jp-1, nb_p) ) + if( nprow.eq.npcol ) then ldw = locr( N_P + mod(jp-1, nb_p) ) + nb_ ldw = locr( n_p + mod(jp-1, nb_p) ) + if( nprow.eq.npcol ) then ldw = locr( N_P + mod(jp-1, nb_p) ) + nb_ ldw = locr( n_p + mod(jp-1, nb_p) ) + |
| nal nal distributed matrix a(ia:ia+n-1,ja:ja+n-k) so that elements below the k-th subdiagonal are zero. the reduction is performed by an orthogo matrices v and t which determine q as a block reflector i - v*t*v', distributed matrix a(ia:ia+n-1,ja:ja+n-k) so that elements below the k-th subdiagonal are zero. the reduction is performed by an orthogo matrices v and t which determine q as a block reflector i - v*t*v', |
| NAME NAME NAME (global input) character*(* lower case. |
| named named the serial version clacon has been contributed by nick higham, university of manchester. it was originally named sonest, date the serial version dlacon has been contributed by nick higham, university of manchester. it was originally named sonest, date the serial version slacon has been contributed by nick higham, university of manchester. it was originally named sonest, date the serial version zlacon has been contributed by nick higham, university of manchester. it was originally named sonest, date |
| namely namely the distributed submatrix sub( a ) must verify some alignment proper- ties, namely the following expressions should be true the distributed submatrix sub( a ) must verify some alignment proper- ties, namely the following expressions should be true the distributed submatrix sub( a ) must verify some alignment proper- ties, namely the following expression should be true the distributed submatrix sub( a ) must verify some alignment proper- ties, namely the following expression should be true the distributed submatrices sub( a ) and sub( b ) must verify some alignment properties, namely the following expression should be true ( mb_a.eq.mb_b .and. iroffa.eq.iroffb .and. iarow.eq.ibrow ) the distributed submatrices sub( a ) and sub( b ) must verify some alignment properties, namely the following expression should be true ( nb_a.eq.nb_b .and. icoffa.eq.icoffb .and. iacol.eq.ibcol ) the distributed submatrices a(ia:*, ja:*) and c(ic:ic+m-1,jc:jc+n-1) must verify some alignment properties, namely the followin the distributed submatrices sub( a ), sub( z ) must verify some alignment properties, namely the following expressio ( mb_a.eq.nb_a.eq.mb_z.eq.nb_z .and. iroffa.eq.icoffa .and. the distributed submatrices a(ia:*, ja:*) and c(ic:ic+m-1,jc:jc+n-1) must verify some alignment properties, namely the followin and b( ib:ib+n-1, jb:jb+n-1 ) must verify some alignment properties, namely the following expressions should be true desca(mb_) = desca(nb_) the distributed submatrix sub( a ) must verify some alignment proper- ties, namely the following expression should be true iroffa = mod( ia-1, mb_a ) and icoffa = mod( ja-1, nb_a ). the distributed submatrix sub( a ) must verify some alignment proper- ties, namely the following expression should be true iroffa = mod( ia-1, mb_a ) and icoffa = mod( ja-1, nb_a ). the distributed submatrix sub( a ) must verify some alignment proper- ties, namely the following expression should be true iroffa = mod( ia-1, mb_a ) and icoffa = mod( ja-1, nb_a ). the global increment for the elements of x. only two values of incx are supported in this version, namely 1 and m_x the distributed submatrices v(iv:*, jv:*) and c(ic:ic+m-1,jc:jc+n-1) must verify some alignment properties, namely the followin the global increment for the elements of x. only two values of incx are supported in this version, namely 1 and m_x the distributed submatrices v(iv:*, jv:*) and c(ic:ic+m-1,jc:jc+n-1) must verify some alignment properties, namely the followin the global increment for the elements of x. only two values of incx are supported in this version, namely 1 and m_x the global increment for the elements of x. only two values of incx are supported in this version, namely 1 and m_x the global increment for the elements of x. only two values of incx are supported in this version, namely 1 and m_x ===================================================================== the distributed submatrices a(ia:*, ja:*) and c(ic:ic+m-1,jc:jc+n-1) must verify some alignment properties, namely the followin the distributed submatrices a(ia:*, ja:*) and c(ic:ic+m-1,jc:jc+n-1) must verify some alignment properties, namely the followin the distributed submatrices a(ia:*, ja:*) and c(ic:ic+m-1,jc:jc+n-1) must verify some alignment properties, namely the followin the distributed submatrices a(ia:*, ja:*) and c(ic:ic+m-1,jc:jc+n-1) must verify some alignment properties, namely the followin the distributed submatrices a(ia:*, ja:*) and c(ic:ic+m-1,jc:jc+n-1) must verify some alignment properties, namely the followin the distributed submatrices a(ia:*, ja:*) and c(ic:ic+m-1,jc:jc+n-1) must verify some alignment properties, namely the followin the distributed submatrices a(ia:*, ja:*) and c(ic:ic+m-1,jc:jc+n-1) must verify some alignment properties, namely the followin the distributed submatrices a(ia:*, ja:*) and c(ic:ic+m-1,jc:jc+n-1) must verify some alignment properties, namely the followin the distributed submatrices a(ia:*, ja:*) and c(ic:ic+m-1,jc:jc+n-1) must verify some alignment properties, namely the followin the distributed submatrices a(ia:*, ja:*) and c(ic:ic+m-1,jc:jc+n-1) must verify some alignment properties, namely the followin the distributed submatrices a(ia:*, ja:*) and c(ic:ic+m-1,jc:jc+n-1) must verify some alignment properties, namely the followin the distributed submatrices a(ia:*, ja:*) and c(ic:ic+m-1,jc:jc+n-1) must verify some alignment properties, namely the followin the distributed submatrices a(ia:*, ja:*) and c(ic:ic+m-1,jc:jc+n-1) must verify some alignment properties, namely the followin the distributed submatrix sub( a ) must verify some alignment proper- ties, namely the following expressions should be true the distributed submatrix sub( a ) must verify some alignment proper- ties, namely the following expressions should be true the distributed submatrix sub( a ) must verify some alignment proper- ties, namely the following expression should be true the distributed submatrix sub( a ) must verify some alignment proper- ties, namely the following expression should be true the distributed submatrices sub( a ) and sub( b ) must verify some alignment properties, namely the following expression should be true ( mb_a.eq.mb_b .and. iroffa.eq.iroffb .and. iarow.eq.ibrow ) the distributed submatrices sub( a ) and sub( b ) must verify some alignment properties, namely the following expression should be true ( nb_a.eq.nb_b .and. icoffa.eq.icoffb .and. iacol.eq.ibcol ) the distributed submatrices v(iv:*, jv:*) and c(ic:ic+m-1,jc:jc+n-1) must verify some alignment properties, namely the followin the global increment for the elements of x. only two values of incx are supported in this version, namely 1 and m_x the distributed submatrices v(iv:*, jv:*) and c(ic:ic+m-1,jc:jc+n-1) must verify some alignment properties, namely the followin the global increment for the elements of x. only two values of incx are supported in this version, namely 1 and m_x the distributed submatrices a(ia:*, ja:*) and c(ic:ic+m-1,jc:jc+n-1) must verify some alignment properties, namely the followin the distributed submatrices a(ia:*, ja:*) and c(ic:ic+m-1,jc:jc+n-1) must verify some alignment properties, namely the followin the distributed submatrices a(ia:*, ja:*) and c(ic:ic+m-1,jc:jc+n-1) must verify some alignment properties, namely the followin the distributed submatrices a(ia:*, ja:*) and c(ic:ic+m-1,jc:jc+n-1) must verify some alignment properties, namely the followin the distributed submatrices a(ia:*, ja:*) and c(ic:ic+m-1,jc:jc+n-1) must verify some alignment properties, namely the followin the distributed submatrices a(ia:*, ja:*) and c(ic:ic+m-1,jc:jc+n-1) must verify some alignment properties, namely the followin the distributed submatrices a(ia:*, ja:*) and c(ic:ic+m-1,jc:jc+n-1) must verify some alignment properties, namely the followin the distributed submatrices a(ia:*, ja:*) and c(ic:ic+m-1,jc:jc+n-1) must verify some alignment properties, namely the followin the distributed submatrices a(ia:*, ja:*) and c(ic:ic+m-1,jc:jc+n-1) must verify some alignment properties, namely the followin the distributed submatrices a(ia:*, ja:*) and c(ic:ic+m-1,jc:jc+n-1) must verify some alignment properties, namely the followin the distributed submatrices a(ia:*, ja:*) and c(ic:ic+m-1,jc:jc+n-1) must verify some alignment properties, namely the followin the distributed submatrices a(ia:*, ja:*) and c(ic:ic+m-1,jc:jc+n-1) must verify some alignment properties, namely the followin the distributed submatrices a(ia:*, ja:*) and c(ic:ic+m-1,jc:jc+n-1) must verify some alignment properties, namely the followin the global increment for the elements of x. only two values of incx are supported in this version, namely 1 and m_x ===================================================================== the distributed submatrices a(ia:*, ja:*) and z(iz:iz+m-1,jz:jz+n-1) must verify some alignment properties, namely the followin the distributed submatrices sub( a ), sub( z ) must verify some alignment properties, namely the following expressio ( mb_a.eq.nb_a.eq.mb_z.eq.nb_z .and. iroffa.eq.icoffa .and. the distributed submatrices a(ia:*, ja:*) and c(ic:ic+m-1,jc:jc+n-1) must verify some alignment properties, namely the followin and b( ib:ib+n-1, jb:jb+n-1 ) must verify some alignment properties, namely the following expressions should be true desca(mb_) = desca(nb_) the distributed submatrix sub( a ) must verify some alignment proper- ties, namely the following expression should be true iroffa = mod( ia-1, mb_a ) and icoffa = mod( ja-1, nb_a ). the distributed submatrix sub( a ) must verify some alignment proper- ties, namely the following expression should be true iroffa = mod( ia-1, mb_a ) and icoffa = mod( ja-1, nb_a ). the distributed submatrix sub( a ) must verify some alignment proper- ties, namely the following expression should be true iroffa = mod( ia-1, mb_a ) and icoffa = mod( ja-1, nb_a ). the global increment for the elements of x. only two values of incx are supported in this version, namely 1 and m_x ===================================================================== the global increment for the elements of x. only two values of incx are supported in this version, namely 1 and m_x ===================================================================== the distributed submatrix sub( a ) must verify some alignment proper- ties, namely the following expressions should be true the distributed submatrix sub( a ) must verify some alignment proper- ties, namely the following expressions should be true the distributed submatrix sub( a ) must verify some alignment proper- ties, namely the following expression should be true the distributed submatrix sub( a ) must verify some alignment proper- ties, namely the following expression should be true the distributed submatrices sub( a ) and sub( b ) must verify some alignment properties, namely the following expression should be true ( mb_a.eq.mb_b .and. iroffa.eq.iroffb .and. iarow.eq.ibrow ) the distributed submatrices sub( a ) and sub( b ) must verify some alignment properties, namely the following expression should be true ( nb_a.eq.nb_b .and. icoffa.eq.icoffb .and. iacol.eq.ibcol ) the distributed submatrices v(iv:*, jv:*) and c(ic:ic+m-1,jc:jc+n-1) must verify some alignment properties, namely the followin the global increment for the elements of x. only two values of incx are supported in this version, namely 1 and m_x the distributed submatrices v(iv:*, jv:*) and c(ic:ic+m-1,jc:jc+n-1) must verify some alignment properties, namely the followin the global increment for the elements of x. only two values of incx are supported in this version, namely 1 and m_x the distributed submatrices a(ia:*, ja:*) and c(ic:ic+m-1,jc:jc+n-1) must verify some alignment properties, namely the followin the distributed submatrices a(ia:*, ja:*) and c(ic:ic+m-1,jc:jc+n-1) must verify some alignment properties, namely the followin the distributed submatrices a(ia:*, ja:*) and c(ic:ic+m-1,jc:jc+n-1) must verify some alignment properties, namely the followin the distributed submatrices a(ia:*, ja:*) and c(ic:ic+m-1,jc:jc+n-1) must verify some alignment properties, namely the followin the distributed submatrices a(ia:*, ja:*) and c(ic:ic+m-1,jc:jc+n-1) must verify some alignment properties, namely the followin the distributed submatrices a(ia:*, ja:*) and c(ic:ic+m-1,jc:jc+n-1) must verify some alignment properties, namely the followin the distributed submatrices a(ia:*, ja:*) and c(ic:ic+m-1,jc:jc+n-1) must verify some alignment properties, namely the followin the distributed submatrices a(ia:*, ja:*) and c(ic:ic+m-1,jc:jc+n-1) must verify some alignment properties, namely the followin the distributed submatrices a(ia:*, ja:*) and c(ic:ic+m-1,jc:jc+n-1) must verify some alignment properties, namely the followin the distributed submatrices a(ia:*, ja:*) and c(ic:ic+m-1,jc:jc+n-1) must verify some alignment properties, namely the followin the distributed submatrices a(ia:*, ja:*) and c(ic:ic+m-1,jc:jc+n-1) must verify some alignment properties, namely the followin the distributed submatrices a(ia:*, ja:*) and c(ic:ic+m-1,jc:jc+n-1) must verify some alignment properties, namely the followin the distributed submatrices a(ia:*, ja:*) and c(ic:ic+m-1,jc:jc+n-1) must verify some alignment properties, namely the followin the global increment for the elements of x. only two values of incx are supported in this version, namely 1 and m_x ===================================================================== the distributed submatrices a(ia:*, ja:*) and z(iz:iz+m-1,jz:jz+n-1) must verify some alignment properties, namely the followin the distributed submatrices sub( a ), sub( z ) must verify some alignment properties, namely the following expressio ( mb_a.eq.nb_a.eq.mb_z.eq.nb_z .and. iroffa.eq.icoffa .and. the distributed submatrices a(ia:*, ja:*) and c(ic:ic+m-1,jc:jc+n-1) must verify some alignment properties, namely the followin and b( ib:ib+n-1, jb:jb+n-1 ) must verify some alignment properties, namely the following expressions should be true desca(mb_) = desca(nb_) the distributed submatrix sub( a ) must verify some alignment proper- ties, namely the following expression should be true iroffa = mod( ia-1, mb_a ) and icoffa = mod( ja-1, nb_a ). the distributed submatrix sub( a ) must verify some alignment proper- ties, namely the following expression should be true iroffa = mod( ia-1, mb_a ) and icoffa = mod( ja-1, nb_a ). the distributed submatrix sub( a ) must verify some alignment proper- ties, namely the following expression should be true iroffa = mod( ia-1, mb_a ) and icoffa = mod( ja-1, nb_a ). the global increment for the elements of x. only two values of incx are supported in this version, namely 1 and m_x ===================================================================== the distributed submatrix sub( a ) must verify some alignment proper- ties, namely the following expressions should be true the distributed submatrix sub( a ) must verify some alignment proper- ties, namely the following expressions should be true the distributed submatrix sub( a ) must verify some alignment proper- ties, namely the following expression should be true the distributed submatrix sub( a ) must verify some alignment proper- ties, namely the following expression should be true the distributed submatrices sub( a ) and sub( b ) must verify some alignment properties, namely the following expression should be true ( mb_a.eq.mb_b .and. iroffa.eq.iroffb .and. iarow.eq.ibrow ) the distributed submatrices sub( a ) and sub( b ) must verify some alignment properties, namely the following expression should be true ( nb_a.eq.nb_b .and. icoffa.eq.icoffb .and. iacol.eq.ibcol ) the distributed submatrices a(ia:*, ja:*) and c(ic:ic+m-1,jc:jc+n-1) must verify some alignment properties, namely the followin the distributed submatrices sub( a ), sub( z ) must verify some alignment properties, namely the following expressio ( mb_a.eq.nb_a.eq.mb_z.eq.nb_z .and. iroffa.eq.icoffa .and. the distributed submatrices a(ia:*, ja:*) and c(ic:ic+m-1,jc:jc+n-1) must verify some alignment properties, namely the followin and b( ib:ib+n-1, jb:jb+n-1 ) must verify some alignment properties, namely the following expressions should be true desca(mb_) = desca(nb_) the distributed submatrix sub( a ) must verify some alignment proper- ties, namely the following expression should be true iroffa = mod( ia-1, mb_a ) and icoffa = mod( ja-1, nb_a ). the distributed submatrix sub( a ) must verify some alignment proper- ties, namely the following expression should be true iroffa = mod( ia-1, mb_a ) and icoffa = mod( ja-1, nb_a ). the distributed submatrix sub( a ) must verify some alignment proper- ties, namely the following expression should be true iroffa = mod( ia-1, mb_a ) and icoffa = mod( ja-1, nb_a ). the global increment for the elements of x. only two values of incx are supported in this version, namely 1 and m_x the distributed submatrices v(iv:*, jv:*) and c(ic:ic+m-1,jc:jc+n-1) must verify some alignment properties, namely the followin the global increment for the elements of x. only two values of incx are supported in this version, namely 1 and m_x the distributed submatrices v(iv:*, jv:*) and c(ic:ic+m-1,jc:jc+n-1) must verify some alignment properties, namely the followin the global increment for the elements of x. only two values of incx are supported in this version, namely 1 and m_x the global increment for the elements of x. only two values of incx are supported in this version, namely 1 and m_x the distributed submatrices a(ia:*, ja:*) and c(ic:ic+m-1,jc:jc+n-1) must verify some alignment properties, namely the followin the distributed submatrices a(ia:*, ja:*) and c(ic:ic+m-1,jc:jc+n-1) must verify some alignment properties, namely the followin the distributed submatrices a(ia:*, ja:*) and c(ic:ic+m-1,jc:jc+n-1) must verify some alignment properties, namely the followin the distributed submatrices a(ia:*, ja:*) and c(ic:ic+m-1,jc:jc+n-1) must verify some alignment properties, namely the followin the distributed submatrices a(ia:*, ja:*) and c(ic:ic+m-1,jc:jc+n-1) must verify some alignment properties, namely the followin the distributed submatrices a(ia:*, ja:*) and c(ic:ic+m-1,jc:jc+n-1) must verify some alignment properties, namely the followin the distributed submatrices a(ia:*, ja:*) and c(ic:ic+m-1,jc:jc+n-1) must verify some alignment properties, namely the followin the distributed submatrices a(ia:*, ja:*) and c(ic:ic+m-1,jc:jc+n-1) must verify some alignment properties, namely the followin the distributed submatrices a(ia:*, ja:*) and c(ic:ic+m-1,jc:jc+n-1) must verify some alignment properties, namely the followin the distributed submatrices a(ia:*, ja:*) and c(ic:ic+m-1,jc:jc+n-1) must verify some alignment properties, namely the followin the distributed submatrices a(ia:*, ja:*) and c(ic:ic+m-1,jc:jc+n-1) must verify some alignment properties, namely the followin the distributed submatrices a(ia:*, ja:*) and c(ic:ic+m-1,jc:jc+n-1) must verify some alignment properties, namely the followin the distributed submatrices a(ia:*, ja:*) and c(ic:ic+m-1,jc:jc+n-1) must verify some alignment properties, namely the followin |
| names names currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer for tridiagonal matrices, it is obvious: n/p >> bw(=1), and so d&c currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer for tridiagonal matrices, it is obvious: n/p >> bw(=1), and so d&c currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer for tridiagonal matrices, it is obvious: n/p >> bw(=1), and so d&c currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer for tridiagonal matrices, it is obvious: n/p >> bw(=1), and so d&c currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer for tridiagonal matrices, it is obvious: n/p >> bw(=1), and so d&c currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer for tridiagonal matrices, it is obvious: n/p >> bw(=1), and so d&c currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer for tridiagonal matrices, it is obvious: n/p >> bw(=1), and so d&c currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer for tridiagonal matrices, it is obvious: n/p >> bw(=1), and so d&c currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer for tridiagonal matrices, it is obvious: n/p >> bw(=1), and so d&c currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer for tridiagonal matrices, it is obvious: n/p >> bw(=1), and so d&c currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer for tridiagonal matrices, it is obvious: n/p >> bw(=1), and so d&c currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer for tridiagonal matrices, it is obvious: n/p >> bw(=1), and so d&c currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer for tridiagonal matrices, it is obvious: n/p >> bw(=1), and so d&c currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer for tridiagonal matrices, it is obvious: n/p >> bw(=1), and so d&c currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer for tridiagonal matrices, it is obvious: n/p >> bw(=1), and so d&c currently, only algorithms designed for the case n/p >> bw are implemented. these go by many names, including divide and conquer for tridiagonal matrices, it is obvious: n/p >> bw(=1), and so d&c |
| narrower narrower 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. specifies the criterion for "convergence" of an interval. = 0 : when an interval is narrower than abstol, or tha it is considered to have "converged". 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. specifies the criterion for "convergence" of an interval. = 0 : when an interval is narrower than abstol, or tha it is considered to have "converged". |
| narrowly narrowly the divide and conqer algorithm assumes the matrix is narrowly it is best to distribute the input matrix a one-dimensionally, the divide and conqer algorithm assumes the matrix is narrowly it is best to distribute the input matrix a one-dimensionally, the divide and conqer algorithm assumes the matrix is narrowly it is best to distribute the input matrix a one-dimensionally, the divide and conqer algorithm assumes the matrix is narrowly it is best to distribute the input matrix a one-dimensionally, the divide and conqer algorithm assumes the matrix is narrowly it is best to distribute the input matrix a one-dimensionally, the divide and conqer algorithm assumes the matrix is narrowly it is best to distribute the input matrix a one-dimensionally, the divide and conqer algorithm assumes the matrix is narrowly it is best to distribute the input matrix a one-dimensionally, the divide and conqer algorithm assumes the matrix is narrowly it is best to distribute the input matrix a one-dimensionally, the divide and conqer algorithm assumes the matrix is narrowly it is best to distribute the input matrix a one-dimensionally, the divide and conqer algorithm assumes the matrix is narrowly it is best to distribute the input matrix a one-dimensionally, the divide and conqer algorithm assumes the matrix is narrowly it is best to distribute the input matrix a one-dimensionally, the divide and conqer algorithm assumes the matrix is narrowly it is best to distribute the input matrix a one-dimensionally, the divide and conqer algorithm assumes the matrix is narrowly it is best to distribute the input matrix a one-dimensionally, the divide and conqer algorithm assumes the matrix is narrowly it is best to distribute the input matrix a one-dimensionally, the divide and conqer algorithm assumes the matrix is narrowly it is best to distribute the input matrix a one-dimensionally, the divide and conqer algorithm assumes the matrix is narrowly it is best to distribute the input matrix a one-dimensionally, the divide and conqer algorithm assumes the matrix is narrowly it is best to distribute the input matrix a one-dimensionally, the divide and conqer algorithm assumes the matrix is narrowly it is best to distribute the input matrix a one-dimensionally, the divide and conqer algorithm assumes the matrix is narrowly it is best to distribute the input matrix a one-dimensionally, the divide and conqer algorithm assumes the matrix is narrowly it is best to distribute the input matrix a one-dimensionally, the divide and conqer algorithm assumes the matrix is narrowly it is best to distribute the input matrix a one-dimensionally, the divide and conqer algorithm assumes the matrix is narrowly it is best to distribute the input matrix a one-dimensionally, the divide and conqer algorithm assumes the matrix is narrowly it is best to distribute the input matrix a one-dimensionally, the divide and conqer algorithm assumes the matrix is narrowly it is best to distribute the input matrix a one-dimensionally, the divide and conqer algorithm assumes the matrix is narrowly it is best to distribute the input matrix a one-dimensionally, the divide and conqer algorithm assumes the matrix is narrowly it is best to distribute the input matrix a one-dimensionally, the divide and conqer algorithm assumes the matrix is narrowly it is best to distribute the input matrix a one-dimensionally, the divide and conqer algorithm assumes the matrix is narrowly it is best to distribute the input matrix a one-dimensionally, the divide and conqer algorithm assumes the matrix is narrowly it is best to distribute the input matrix a one-dimensionally, the divide and conqer algorithm assumes the matrix is narrowly it is best to distribute the input matrix a one-dimensionally, the divide and conqer algorithm assumes the matrix is narrowly it is best to distribute the input matrix a one-dimensionally, the divide and conqer algorithm assumes the matrix is narrowly it is best to distribute the input matrix a one-dimensionally, the divide and conqer algorithm assumes the matrix is narrowly it is best to distribute the input matrix a one-dimensionally, the divide and conqer algorithm assumes the matrix is narrowly it is best to distribute the input matrix a one-dimensionally, the divide and conqer algorithm assumes the matrix is narrowly it is best to distribute the input matrix a one-dimensionally, the divide and conqer algorithm assumes the matrix is narrowly it is best to distribute the input matrix a one-dimensionally, the divide and conqer algorithm assumes the matrix is narrowly it is best to distribute the input matrix a one-dimensionally, the divide and conqer algorithm assumes the matrix is narrowly it is best to distribute the input matrix a one-dimensionally, the divide and conqer algorithm assumes the matrix is narrowly it is best to distribute the input matrix a one-dimensionally, the divide and conqer algorithm assumes the matrix is narrowly it is best to distribute the input matrix a one-dimensionally, |
| National National 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 |
| Natonal Natonal andrew j. cleary, livermore national lab and university of tenn., and marbwus hegland, australian Natonal university. feb., 1997 andrew j. cleary, livermore national lab and university of tenn., and marbwus hegland, australian Natonal university. feb., 1997 |
| naturally naturally we delay spreading v across to all processor columns (which would naturally happen at the bottom of the loop) in order t we delay spreading v across to all processor columns (which would naturally happen at the bottom of the loop) in order t we delay spreading v across to all processor columns (which would naturally happen at the bottom of the loop) in order t we delay spreading v across to all processor columns (which would naturally happen at the bottom of the loop) in order t |
| nature nature p*nb>= mod(ja-1,nb)+n. the mapping for matrices must be blocked, reflecting the nature this formula in words is: no processor may have more than one p*nb>= mod(ja-1,nb)+n. the mapping for matrices must be blocked, reflecting the nature this formula in words is: no processor may have more than one p*nb>= mod(ja-1,nb)+n. the mapping for matrices must be blocked, reflecting the nature this formula in words is: no processor may have more than one p*nb>= mod(ja-1,nb)+n. the mapping for matrices must be blocked, reflecting the nature this formula in words is: no processor may have more than one p*nb>= mod(ja-1,nb)+n. the mapping for matrices must be blocked, reflecting the nature this formula in words is: no processor may have more than one p*nb>= mod(ja-1,nb)+n. the mapping for matrices must be blocked, reflecting the nature this formula in words is: no processor may have more than one p*nb>= mod(ja-1,nb)+n. the mapping for matrices must be blocked, reflecting the nature this formula in words is: no processor may have more than one p*nb>= mod(ja-1,nb)+n. the mapping for matrices must be blocked, reflecting the nature this formula in words is: no processor may have more than one p*nb>= mod(ja-1,nb)+n. the mapping for matrices must be blocked, reflecting the nature this formula in words is: no processor may have more than one p*nb>= mod(ja-1,nb)+n. the mapping for matrices must be blocked, reflecting the nature this formula in words is: no processor may have more than one p*nb>= mod(ja-1,nb)+n. the mapping for matrices must be blocked, reflecting the nature this formula in words is: no processor may have more than one p*nb>= mod(ja-1,nb)+n. the mapping for matrices must be blocked, reflecting the nature this formula in words is: no processor may have more than one p*nb>= mod(ja-1,nb)+n. the mapping for matrices must be blocked, reflecting the nature this formula in words is: no processor may have more than one p*nb>= mod(ja-1,nb)+n. the mapping for matrices must be blocked, reflecting the nature this formula in words is: no processor may have more than one p*nb>= mod(ja-1,nb)+n. the mapping for matrices must be blocked, reflecting the nature this formula in words is: no processor may have more than one p*nb>= mod(ja-1,nb)+n. the mapping for matrices must be blocked, reflecting the nature this formula in words is: no processor may have more than one p*nb>= mod(ja-1,nb)+n. the mapping for matrices must be blocked, reflecting the nature this formula in words is: no processor may have more than one p*nb>= mod(ja-1,nb)+n. the mapping for matrices must be blocked, reflecting the nature this formula in words is: no processor may have more than one p*nb>= mod(ja-1,nb)+n. the mapping for matrices must be blocked, reflecting the nature this formula in words is: no processor may have more than one p*nb>= mod(ja-1,nb)+n. the mapping for matrices must be blocked, reflecting the nature this formula in words is: no processor may have more than one p*nb>= mod(ja-1,nb)+n. the mapping for matrices must be blocked, reflecting the nature this formula in words is: no processor may have more than one p*nb>= mod(ja-1,nb)+n. the mapping for matrices must be blocked, reflecting the nature this formula in words is: no processor may have more than one p*nb>= mod(ja-1,nb)+n. the mapping for matrices must be blocked, reflecting the nature this formula in words is: no processor may have more than one p*nb>= mod(ja-1,nb)+n. the mapping for matrices must be blocked, reflecting the nature this formula in words is: no processor may have more than one p*nb>= mod(ja-1,nb)+n. the mapping for matrices must be blocked, reflecting the nature this formula in words is: no processor may have more than one p*nb>= mod(ja-1,nb)+n. the mapping for matrices must be blocked, reflecting the nature this formula in words is: no processor may have more than one p*nb>= mod(ja-1,nb)+n. the mapping for matrices must be blocked, reflecting the nature this formula in words is: no processor may have more than one p*nb>= mod(ja-1,nb)+n. the mapping for matrices must be blocked, reflecting the nature this formula in words is: no processor may have more than one p*nb>= mod(ja-1,nb)+n. the mapping for matrices must be blocked, reflecting the nature this formula in words is: no processor may have more than one p*nb>= mod(ja-1,nb)+n. the mapping for matrices must be blocked, reflecting the nature this formula in words is: no processor may have more than one p*nb>= mod(ja-1,nb)+n. the mapping for matrices must be blocked, reflecting the nature this formula in words is: no processor may have more than one p*nb>= mod(ja-1,nb)+n. the mapping for matrices must be blocked, reflecting the nature this formula in words is: no processor may have more than one p*nb>= mod(ja-1,nb)+n. the mapping for matrices must be blocked, reflecting the nature this formula in words is: no processor may have more than one p*nb>= mod(ja-1,nb)+n. the mapping for matrices must be blocked, reflecting the nature this formula in words is: no processor may have more than one p*nb>= mod(ja-1,nb)+n. the mapping for matrices must be blocked, reflecting the nature this formula in words is: no processor may have more than one p*nb>= mod(ja-1,nb)+n. the mapping for matrices must be blocked, reflecting the nature this formula in words is: no processor may have more than one p*nb>= mod(ja-1,nb)+n. the mapping for matrices must be blocked, reflecting the nature this formula in words is: no processor may have more than one p*nb>= mod(ja-1,nb)+n. the mapping for matrices must be blocked, reflecting the nature this formula in words is: no processor may have more than one p*nb>= mod(ja-1,nb)+n. the mapping for matrices must be blocked, reflecting the nature this formula in words is: no processor may have more than one p*nb>= mod(ja-1,nb)+n. the mapping for matrices must be blocked, reflecting the nature this formula in words is: no processor may have more than one |
| NB_ NB_ the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first aligned with d. must be of size >= desca( NB_ ) factors of the matrix. aligned with d. must be of size >= desca( NB_ ) factors of the matrix. the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of a. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first distribute the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used t rsrc_a (global) desca( rsrc_ ) the process row over which the the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first factors of the matrix. must be of size >= desca( NB_ ) e (local input/local output) complex pointer to local factors of the matrix. must be of size >= desca( NB_ ) e (local input/local output) complex pointer to local te the rows of the array. NB_a (global) desca[ nb_ ] the blocking factor used to distribu rsrc_a (global) desca[ rsrc_ ] the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first aligned with d. must be of size >= desca( NB_ ) factors of the matrix. aligned with d. must be of size >= desca( NB_ ) factors of the matrix. the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first factors of the matrix. must be of size >= desca( NB_ ) e (local input/local output) double precision pointer to local factors of the matrix. must be of size >= desca( NB_ ) e (local input/local output) double precision pointer to local te the rows of the array. NB_a (global) desca[ nb_ ] the blocking factor used to distribu rsrc_a (global) desca[ rsrc_ ] the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of a. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first distribute the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used t rsrc_a (global) desca( rsrc_ ) the process row over which the the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first aligned with d. must be of size >= desca( NB_ ) factors of the matrix. aligned with d. must be of size >= desca( NB_ ) factors of the matrix. the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first factors of the matrix. must be of size >= desca( NB_ ) e (local input/local output) real pointer to local factors of the matrix. must be of size >= desca( NB_ ) e (local input/local output) real pointer to local te the rows of the array. NB_a (global) desca[ nb_ ] the blocking factor used to distribu rsrc_a (global) desca[ rsrc_ ] the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of a. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first distribute the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used t rsrc_a (global) desca( rsrc_ ) the process row over which the the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first te the rows of the array. NB_a (global) desca[ nb_ ] the blocking factor used to distribu rsrc_a (global) desca[ rsrc_ ] the process row over which the first aligned with d. must be of size >= desca( NB_ ) factors of the matrix. aligned with d. must be of size >= desca( NB_ ) factors of the matrix. the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of a. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first distribute the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used t rsrc_a (global) desca( rsrc_ ) the process row over which the the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first factors of the matrix. must be of size >= desca( NB_ ) e (local input/local output) complex*16 pointer to local factors of the matrix. must be of size >= desca( NB_ ) e (local input/local output) complex*16 pointer to local the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_a (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first |
| NB_A NB_A the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of a. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first should be true: ( mb_a.eq.NB_A.eq.mb_z.eq.nb_z .and. iroffa.eq.icoffa .and with iroffa = mod( ia-1, mb_a ) the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first distribute the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used t rsrc_a (global) desca( rsrc_ ) the process row over which the the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first t (local output) complex array, dimension (NB_A,nb_a the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first te the rows of the array. NB_A (global) desca[ nb_ ] the blocking factor used to distribu rsrc_a (global) desca[ rsrc_ ] the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first t (local output) double precision array, dimension (NB_A,nb_a the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first te the rows of the array. NB_A (global) desca[ nb_ ] the blocking factor used to distribu rsrc_a (global) desca[ rsrc_ ] the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of a. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first should be true: ( mb_a.eq.NB_A.eq.mb_z.eq.nb_z .and. iroffa.eq.icoffa .and with iroffa = mod( ia-1, mb_a ) the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first distribute the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used t rsrc_a (global) desca( rsrc_ ) the process row over which the the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first t (local output) real array, dimension (NB_A,nb_a the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first te the rows of the array. NB_A (global) desca[ nb_ ] the blocking factor used to distribu rsrc_a (global) desca[ rsrc_ ] the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of a. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first should be true: ( mb_a.eq.NB_A.eq.mb_z.eq.nb_z .and. iroffa.eq.icoffa .and with iroffa = mod( ia-1, mb_a ) the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first distribute the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used t rsrc_a (global) desca( rsrc_ ) the process row over which the the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first te the rows of the array. NB_A (global) desca[ nb_ ] the blocking factor used to distribu rsrc_a (global) desca[ rsrc_ ] the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of a. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first should be true: ( mb_a.eq.NB_A.eq.mb_z.eq.nb_z .and. iroffa.eq.icoffa .and with iroffa = mod( ia-1, mb_a ) the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first distribute the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used t rsrc_a (global) desca( rsrc_ ) the process row over which the the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first t (local output) complex*16 array, dimension (NB_A,nb_a the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first the rows of the array. NB_A (global) desca( nb_ ) the blocking factor used to distribut rsrc_a (global) desca( rsrc_ ) the process row over which the first |
| NB_B NB_B iroffb = mod( ib-1, mb_b ), icoffb = mod( jb-1, NB_B ) ibcol = indxg2p( jb, nb_b, mycol, csrc_b, npcol ), iroffb = mod( ib-1, mb_b ), icoffb = mod( jb-1, NB_B ) ibcol = indxg2p( jb, nb_b, mycol, csrc_b, npcol ), mb_a * mb_a, NB_B * ( ppb0 + nqb0 + nb_b ) ), wher iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), iroffb = mod( ib-1, mb_b ), icoffb = mod( jb-1, NB_B ) ibcol = indxg2p( jb, nb_b, mycol, csrc_b, npcol ), iroffb = mod( ib-1, mb_b ), icoffb = mod( jb-1, NB_B ) ibcol = indxg2p( jb, nb_b, mycol, csrc_b, npcol ), mb_a * mb_a, NB_B * ( ppb0 + nqb0 + nb_b ) ), wher iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), iroffb = mod( ib-1, mb_b ), icoffb = mod( jb-1, NB_B ) ibcol = indxg2p( jb, nb_b, mycol, csrc_b, npcol ), iroffb = mod( ib-1, mb_b ), icoffb = mod( jb-1, NB_B ) ibcol = indxg2p( jb, nb_b, mycol, csrc_b, npcol ), mb_a * mb_a, NB_B * ( ppb0 + nqb0 + nb_b ) ), wher iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), iroffb = mod( ib-1, mb_b ), icoffb = mod( jb-1, NB_B ) ibcol = indxg2p( jb, nb_b, mycol, csrc_b, npcol ), iroffb = mod( ib-1, mb_b ), icoffb = mod( jb-1, NB_B ) ibcol = indxg2p( jb, nb_b, mycol, csrc_b, npcol ), mb_a * mb_a, NB_B * ( ppb0 + nqb0 + nb_b ) ), wher iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), |
| NB_C NB_C iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, NB_C ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, NB_C ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, NB_C ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, NB_C ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), iroffc = mod( icc-1, mb_c ), icoffc = mod( jcc-1, NB_C ) iccol = indxg2p( jcc, nb_c, mycol, csrc_c, npcol ), iroffc = mod( icc-1, mb_c ), icoffc = mod( jcc-1, NB_C ) iccol = indxg2p( jcc, nb_c, mycol, csrc_c, npcol ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, NB_C ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, NB_C ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, NB_C ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, NB_C ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, NB_C ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, NB_C ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, NB_C ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, NB_C ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), iroffc = mod( icc-1, mb_c ), icoffc = mod( jcc-1, NB_C ) iccol = indxg2p( jcc, nb_c, mycol, csrc_c, npcol ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, NB_C ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, NB_C ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, NB_C ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, NB_C ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), iroffc = mod( icc-1, mb_c ), icoffc = mod( jcc-1, NB_C ) iccol = indxg2p( jcc, nb_c, mycol, csrc_c, npcol ), iroffc = mod( icc-1, mb_c ), icoffc = mod( jcc-1, NB_C ) iccol = indxg2p( jcc, nb_c, mycol, csrc_c, npcol ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, NB_C ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, NB_C ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, NB_C ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, NB_C ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, NB_C ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, NB_C ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, NB_C ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, NB_C ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), iroffc = mod( icc-1, mb_c ), icoffc = mod( jcc-1, NB_C ) iccol = indxg2p( jcc, nb_c, mycol, csrc_c, npcol ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, NB_C ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, NB_C ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, NB_C ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, NB_C ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), iroffc = mod( icc-1, mb_c ), icoffc = mod( jcc-1, NB_C ) iccol = indxg2p( jcc, nb_c, mycol, csrc_c, npcol ), iroffc = mod( icc-1, mb_c ), icoffc = mod( jcc-1, NB_C ) iccol = indxg2p( jcc, nb_c, mycol, csrc_c, npcol ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, NB_C ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, NB_C ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, NB_C ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, NB_C ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, NB_C ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, NB_C ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, NB_C ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, NB_C ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), iroffc = mod( icc-1, mb_c ), icoffc = mod( jcc-1, NB_C ) iccol = indxg2p( jcc, nb_c, mycol, csrc_c, npcol ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, NB_C ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, NB_C ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, NB_C ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, NB_C ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), iroffc = mod( icc-1, mb_c ), icoffc = mod( jcc-1, NB_C ) iccol = indxg2p( jcc, nb_c, mycol, csrc_c, npcol ), iroffc = mod( icc-1, mb_c ), icoffc = mod( jcc-1, NB_C ) iccol = indxg2p( jcc, nb_c, mycol, csrc_c, npcol ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, NB_C ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, NB_C ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, NB_C ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, NB_C ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, NB_C ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, NB_C ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, NB_C ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), iroffc = mod( ic-1, mb_c ), icoffc = mod( jc-1, NB_C ) iccol = indxg2p( jc, nb_c, mycol, csrc_c, npcol ), iroffc = mod( icc-1, mb_c ), icoffc = mod( jcc-1, NB_C ) iccol = indxg2p( jcc, nb_c, mycol, csrc_c, npcol ), |
| NB_P NB_P >= locr( ia+m-1 ) + mb_a if pivroc='c' or 'c', >= locc( m + mod(jp-1,NB_P) ) if pivroc='r' or 'r', and >= locr( n + mod(ip-1,mb_p) ) if pivroc='c' or 'c', >= locr( ia+m-1 ) + mb_a if pivroc='c' or 'c', >= locc( m + mod(jp-1,NB_P) ) if pivroc='r' or 'r', and >= locr( n + mod(ip-1,mb_p) ) if pivroc='c' or 'c', >= locr( ia+m-1 ) + mb_a if pivroc='c' or 'c', >= locc( m + mod(jp-1,NB_P) ) if pivroc='r' or 'r', and >= locr( n + mod(ip-1,mb_p) ) if pivroc='c' or 'c', >= locr( ia+m-1 ) + mb_a if pivroc='c' or 'c', >= locc( m + mod(jp-1,NB_P) ) if pivroc='r' or 'r', and >= locr( n + mod(ip-1,mb_p) ) if pivroc='c' or 'c', |
| NB_Q NB_Q np = numroc( n, mb_q, myrow, iqrow, nprow ) nq = numroc( n, NB_Q, mycol, iqcol, npcol iqcol = indxg2p( jq, mb_q, mycol, csrc_q, npcol ) np = numroc( n, mb_q, myrow, iqrow, nprow ) nq = numroc( n, NB_Q, mycol, iqcol, npcol iqcol = indxg2p( jq, mb_q, mycol, csrc_q, npcol ) |
| NB_V NB_V t (local input) complex array, dimension mb_v by mb_v if storev = 'r' and NB_V by nb_v if storev = 'c'. the trian the order of the triangular factor t (= the number of elementary reflectors). 1 <= k <= mb_v (= NB_V) v (input/output) complex pointer into the local memory lwork >= ( nqc0 + max( npv0 + numroc( numroc( n+icoffc, NB_V, 0, 0, npcol ), nb_v, 0, 0, lcmq ) end if the order of the triangular factor t (= the number of elementary reflectors). 1 <= k <= mb_v (= NB_V) v (input/output) complex pointer into the local memory t (local input) double precision array, dimension mb_v by mb_v if storev = 'r' and NB_V by nb_v if storev = 'c'. the trian the order of the triangular factor t (= the number of elementary reflectors). 1 <= k <= mb_v (= NB_V) v (input/output) double precision pointer into the local memory lwork >= ( nqc0 + max( npv0 + numroc( numroc( n+icoffc, NB_V, 0, 0, npcol ), nb_v, 0, 0, lcmq ) end if the order of the triangular factor t (= the number of elementary reflectors). 1 <= k <= mb_v (= NB_V) v (input/output) double precision pointer into the local memory t (local input) real array, dimension mb_v by mb_v if storev = 'r' and NB_V by nb_v if storev = 'c'. the trian the order of the triangular factor t (= the number of elementary reflectors). 1 <= k <= mb_v (= NB_V) v (input/output) real pointer into the local memory lwork >= ( nqc0 + max( npv0 + numroc( numroc( n+icoffc, NB_V, 0, 0, npcol ), nb_v, 0, 0, lcmq ) end if the order of the triangular factor t (= the number of elementary reflectors). 1 <= k <= mb_v (= NB_V) v (input/output) real pointer into the local memory t (local input) complex*16 array, dimension mb_v by mb_v if storev = 'r' and NB_V by nb_v if storev = 'c'. the trian the order of the triangular factor t (= the number of elementary reflectors). 1 <= k <= mb_v (= NB_V) v (input/output) complex*16 pointer into the local memory lwork >= ( nqc0 + max( npv0 + numroc( numroc( n+icoffc, NB_V, 0, 0, npcol ), nb_v, 0, 0, lcmq ) end if the order of the triangular factor t (= the number of elementary reflectors). 1 <= k <= mb_v (= NB_V) v (input/output) complex*16 pointer into the local memory |
| NB_W NB_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 ). |
| NB_Y NB_Y nq = numroc( n+mod( ia-1, NB_Y ), nb_y, mycol, iacol, npcol nq = numroc( n+mod( ia-1, NB_Y ), nb_y, mycol, iacol, npcol nq = numroc( n+mod( ia-1, NB_Y ), nb_y, mycol, iacol, npcol nq = numroc( n+mod( ia-1, NB_Y ), nb_y, mycol, iacol, npcol |
| NB_Z NB_Z should be true: ( mb_a.eq.nb_a.eq.mb_z.eq.NB_Z .and. iroffa.eq.icoffa .and with iroffa = mod( ia-1, mb_a ) should be true: ( mb_a.eq.nb_a.eq.mb_z.eq.NB_Z .and. iroffa.eq.icoffa .and with iroffa = mod( ia-1, mb_a ) should be true: ( mb_a.eq.nb_a.eq.mb_z.eq.NB_Z .and. iroffa.eq.icoffa .and with iroffa = mod( ia-1, mb_a ) should be true: ( mb_a.eq.nb_a.eq.mb_z.eq.NB_Z .and. iroffa.eq.icoffa .and with iroffa = mod( ia-1, mb_a ) |
| nblk nblk find starting and ending indices of block nblk find starting and ending indices of block nblk |
| NBULGE NBULGE clamsh should only be called when there are multiple shifts/bulges (NBULGE > 1) and the first shift is starting in the middle of a small subdiagonal elements. dlamsh should only be called when there are multiple shifts/bulges (NBULGE > 1) and the first shift is starting in the middle of a subdiagonal elements. NBULGE is the number of bulges that will be attempte NBULGE is the number of bulges that will be attempte NBULGE is the number of bulges that will be attempte NBULGE is the number of bulges that will be attempte slamsh should only be called when there are multiple shifts/bulges (NBULGE > 1) and the first shift is starting in the middle of a subdiagonal elements. zlamsh should only be called when there are multiple shifts/bulges (NBULGE > 1) and the first shift is starting in the middle of a small subdiagonal elements. |
| NCVT NCVT wbdtosvd = size*(wantu*nru + wantvt*NCVT) max(wantu*wpcormbrqln, wantvt*wpcormbrprt)), wbdtosvd = size*(wantu*nru + wantvt*NCVT) max(wantu*wpdormbrqln, wantvt*wpdormbrprt)), wbdtosvd = size*(wantu*nru + wantvt*NCVT) max(wantu*wpsormbrqln, wantvt*wpsormbrprt)), wbdtosvd = size*(wantu*nru + wantvt*NCVT) max(wantu*wpzormbrqln, wantvt*wpzormbrprt)), |
| nearest nearest ****************************** reduced system has been solved, communicate solutions to nearest ****************************** reduced system has been solved, communicate solutions to nearest ****************************** reduced system has been solved, communicate solutions to nearest ****************************** reduced system has been solved, communicate solutions to nearest ****************************** reduced system has been solved, communicate solutions to nearest ****************************** reduced system has been solved, communicate solutions to nearest ****************************** reduced system has been solved, communicate solutions to nearest ****************************** reduced system has been solved, communicate solutions to nearest ****************************** reduced system has been solved, communicate solutions to nearest ****************************** reduced system has been solved, communicate solutions to nearest ****************************** reduced system has been solved, communicate solutions to nearest ****************************** reduced system has been solved, communicate solutions to nearest ****************************** reduced system has been solved, communicate solutions to nearest ****************************** reduced system has been solved, communicate solutions to nearest ****************************** reduced system has been solved, communicate solutions to nearest ****************************** reduced system has been solved, communicate solutions to nearest |
| necessary necessary the following method uses more flops than necessary bu rwork (workspace) real array, dimension (1+4*sizeb) on exit, if info = 0, rwork(1) returns the necessary siz = 'e': the matrix a(ia:ia+n-1,ja:ja+n-1) will be equili- brated if necessary, then copied t relatively even if each is not very small. thus it is necessary to scan the "tridiagonal portion of the matrix." i l and examines the else part of this if needs updated vcopy, this was not necessary in pslahqr or a column. the pivot vector should be aligned with the distributed matrix a. this routine will transpose the pivot vector if necessary sub( a ), pass rowcol='c' and pivroc='c'. compute x(j) = b(j) / a(j,j), scaling x if necessary xj = cabs1( x( j ) ) the following method uses more flops than necessary bu = 'n': the matrix a will be copied to af and factored. = 'e': the matrix a will be equilibrated if necessary, the the following method uses more flops than necessary bu = 'e': the matrix a(ia:ia+n-1,ja:ja+n-1) will be equili- brated if necessary, then copied t relatively even if each is not very small. thus it is necessary to scan the "tridiagonal portion of the matrix." i l and examines or a column. the pivot vector should be aligned with the distributed matrix a. this routine will transpose the pivot vector if necessary sub( a ), pass rowcol='c' and pivroc='c'. the following method uses more flops than necessary bu = 'n': the matrix a will be copied to af and factored. = 'e': the matrix a will be equilibrated if necessary, the the following method uses more flops than necessary bu = 'e': the matrix a(ia:ia+n-1,ja:ja+n-1) will be equili- brated if necessary, then copied t relatively even if each is not very small. thus it is necessary to scan the "tridiagonal portion of the matrix." i l and examines or a column. the pivot vector should be aligned with the distributed matrix a. this routine will transpose the pivot vector if necessary sub( a ), pass rowcol='c' and pivroc='c'. the following method uses more flops than necessary bu = 'n': the matrix a will be copied to af and factored. = 'e': the matrix a will be equilibrated if necessary, the the following method uses more flops than necessary bu rwork (workspace) real array, dimension (1+4*sizeb) on exit, if info = 0, rwork(1) returns the necessary siz = 'e': the matrix a(ia:ia+n-1,ja:ja+n-1) will be equili- brated if necessary, then copied t relatively even if each is not very small. thus it is necessary to scan the "tridiagonal portion of the matrix." i l and examines the else part of this if needs updated vcopy, this was not necessary in pdlahqr or a column. the pivot vector should be aligned with the distributed matrix a. this routine will transpose the pivot vector if necessary sub( a ), pass rowcol='c' and pivroc='c'. compute x(j) = b(j) / a(j,j), scaling x if necessary xj = cabs1( x( j ) ) the following method uses more flops than necessary bu = 'n': the matrix a will be copied to af and factored. = 'e': the matrix a will be equilibrated if necessary, the |
| necessitate necessitate the following method uses more flops than necessary but does not necessitate the writing of a new blas routine the following method uses more flops than necessary but does not necessitate the writing of a new blas routine the following method uses more flops than necessary but does not necessitate the writing of a new blas routine the following method uses more flops than necessary but does not necessitate the writing of a new blas routine the following method uses more flops than necessary but does not necessitate the writing of a new blas routine the following method uses more flops than necessary but does not necessitate the writing of a new blas routine the following method uses more flops than necessary but does not necessitate the writing of a new blas routine the following method uses more flops than necessary but does not necessitate the writing of a new blas routine |
| need need on entry, the matrix a in band storage, in rows kl+1 to 2*kl+ku+1; rows 1 to kl of the array need not be set array ab as follows: eigenvalues only are being computed, only the active submatrix need be transformed on entry, the matrix a in band storage, in rows kl+1 to 2*kl+ku+1; rows 1 to kl of the array need not be set array ab as follows: transfer last triangle d_i of local matrix to next processor which needs it to calculate fillin due to factorization o overlap the send with the factorization of a_i. the last processor does not need to send anything eigenvalues only are being computed, only the active submatrix need be transformed transfer last triangle d_i of local matrix to next processor which needs it to calculate fillin due to factorization o overlap the send with the factorization of a_i. transfer last triangle d_i of local matrix to next processor which needs it to calculate fillin due to factorization o overlap the send with the factorization of a_i. the last processor does not need to send anything eigenvalues only are being computed, only the active submatrix need be transformed transfer last triangle d_i of local matrix to next processor which needs it to calculate fillin due to factorization o overlap the send with the factorization of a_i. pjlaenv is patterned after ilaenv and keeps the same interface in anticipation of future needs, even though pjlaenv is only sparsel data layout blocking factor as the algorithmic blocking factor - transfer last triangle d_i of local matrix to next processor which needs it to calculate fillin due to factorization o overlap the send with the factorization of a_i. the last processor does not need to send anything eigenvalues only are being computed, only the active submatrix need be transformed transfer last triangle d_i of local matrix to next processor which needs it to calculate fillin due to factorization o overlap the send with the factorization of a_i. transfer last triangle d_i of local matrix to next processor which needs it to calculate fillin due to factorization o overlap the send with the factorization of a_i. the last processor does not need to send anything eigenvalues only are being computed, only the active submatrix need be transformed transfer last triangle d_i of local matrix to next processor which needs it to calculate fillin due to factorization o overlap the send with the factorization of a_i. on entry, the matrix a in band storage, in rows kl+1 to 2*kl+ku+1; rows 1 to kl of the array need not be set array ab as follows: on entry, the matrix a in band storage, in rows kl+1 to 2*kl+ku+1; rows 1 to kl of the array need not be set array ab as follows: eigenvalues only are being computed, only the active submatrix need be transformed |
| needed needed initiate send of off-diag block(s) to overlap with next part. off-diagonal block needed on neighboring processor to star do until this proc is needed to modify other procs' equation initiate send of off-diag block(s) to overlap with next part. off-diagonal block needed on neighboring processor to star do until this proc is needed to modify other procs' equation dimension (lwork) on output, work(1) returns the workspace needed to guarante may also be incorrect. dimension (lwork) on output, work(1) returns the workspace needed for th for optimal performance, greater workspace is needed, i.e where lwork is as defined above, and for optimal performance, greater workspace is needed, i.e nhegst_lwopt ) for optimal performance, greater workspace is needed, i.e ictxt = desca( ctxt_ ) or lower bidiagonal form by an unitary transformation q' * a * p, and returns the matrices x and y which are needed to apply the transfor the elements of the vectors v together form the (n-k+1)-by-nb matrix v which is needed, with t and y, to apply the transformation to th a(ia:ia+n-1,ja:ja+n-k) := (i-v*t*v')*(a(ia:ia+n-1,ja:ja+n-k)-y*v'). q' * sub( a ) * q, and returns the matrices v and w which are needed to apply the transformation to the unreduced part of sub( a ) if uplo = 'u', pclatrd reduces the last nb rows and columns of a if the scaling needed for a in the dot product is 1 initiate send of off-diag block(s) to overlap with next part. off-diagonal block needed on neighboring processor to star do until this proc is needed to modify other procs' equation initiate send of off-diag block(s) to overlap with next part. off-diagonal block needed on neighboring processor to star do until this proc is needed to modify other procs' equation orthogonalization (see orfac). note that this may overestimate the minimum workspace needed lwork (local input) integer initiate send of off-diag block(s) to overlap with next part. off-diagonal block needed on neighboring processor to star do until this proc is needed to modify other procs' equation initiate send of off-diag block(s) to overlap with next part. off-diagonal block needed on neighboring processor to star do until this proc is needed to modify other procs' equation and redefine the underflow and overflow limits to be the square roots of the values computed by pdlamch. this subroutine is needed becaus the exponent range, as is found on a cray. or lower bidiagonal form by an orthogonal transformation q' * a * p, and returns the matrices x and y which are needed to apply th the elements of the vectors v together form the (n-k+1)-by-nb matrix v which is needed, with t and y, to apply the transformation to th a(ia:ia+n-1,ja:ja+n-k) := (i-v*t*v')*(a(ia:ia+n-1,ja:ja+n-k)-y*v'). form by an orthogonal similarity transformation q' * sub( a ) * q, and returns the matrices v and w which are needed to apply th initiate send of off-diag block(s) to overlap with next part. off-diagonal block needed on neighboring processor to star do until this proc is needed to modify other procs' equation initiate send of off-diag block(s) to overlap with next part. off-diagonal block needed on neighboring processor to star do until this proc is needed to modify other procs' equation to 1 (in slmake.inc). the features of ieee arithmetic that are needed for the "fast" sturm count are : (a) infinit point number is assumed be in the 32nd bit position dimension (lwork) on output, work(1) returns the workspace needed lwork (local input/output) integer, orthogonalization (see orfac). note that this may overestimate the minimum workspace needed lwork (local input) integer version 1.0: on output, work(1) returns the workspace needed to guarantee completion incorrect. for optimal performance, greater workspace may be needed, i.e where: for optimal performance, greater workspace may be needed, i.e nsygst_lwopt ) for optimal performance, greater workspace is needed, i.e ictxt = desca( ctxt_ ) initiate send of off-diag block(s) to overlap with next part. off-diagonal block needed on neighboring processor to star do until this proc is needed to modify other procs' equation initiate send of off-diag block(s) to overlap with next part. off-diagonal block needed on neighboring processor to star do until this proc is needed to modify other procs' equation and redefine the underflow and overflow limits to be the square roots of the values computed by pslamch. this subroutine is needed becaus the exponent range, as is found on a cray. or lower bidiagonal form by an orthogonal transformation q' * a * p, and returns the matrices x and y which are needed to apply th the elements of the vectors v together form the (n-k+1)-by-nb matrix v which is needed, with t and y, to apply the transformation to th a(ia:ia+n-1,ja:ja+n-k) := (i-v*t*v')*(a(ia:ia+n-1,ja:ja+n-k)-y*v'). form by an orthogonal similarity transformation q' * sub( a ) * q, and returns the matrices v and w which are needed to apply th initiate send of off-diag block(s) to overlap with next part. off-diagonal block needed on neighboring processor to star do until this proc is needed to modify other procs' equation initiate send of off-diag block(s) to overlap with next part. off-diagonal block needed on neighboring processor to star do until this proc is needed to modify other procs' equation to 1 (in slmake.inc). the features of ieee arithmetic that are needed for the "fast" sturm count are : (a) infinit point number is assumed be in the 32nd or 64th bit position dimension (lwork) on output, work(1) returns the workspace needed lwork (local input/output) integer, orthogonalization (see orfac). note that this may overestimate the minimum workspace needed lwork (local input) integer version 1.0: on output, work(1) returns the workspace needed to guarantee completion incorrect. for optimal performance, greater workspace may be needed, i.e where: for optimal performance, greater workspace may be needed, i.e nsygst_lwopt ) for optimal performance, greater workspace is needed, i.e ictxt = desca( ctxt_ ) initiate send of off-diag block(s) to overlap with next part. off-diagonal block needed on neighboring processor to star do until this proc is needed to modify other procs' equation initiate send of off-diag block(s) to overlap with next part. off-diagonal block needed on neighboring processor to star do until this proc is needed to modify other procs' equation dimension (lwork) on output, work(1) returns the workspace needed to guarante may also be incorrect. dimension (lwork) on output, work(1) returns the workspace needed for th for optimal performance, greater workspace is needed, i.e where lwork is as defined above, and for optimal performance, greater workspace is needed, i.e nhegst_lwopt ) for optimal performance, greater workspace is needed, i.e ictxt = desca( ctxt_ ) or lower bidiagonal form by an unitary transformation q' * a * p, and returns the matrices x and y which are needed to apply the transfor the elements of the vectors v together form the (n-k+1)-by-nb matrix v which is needed, with t and y, to apply the transformation to th a(ia:ia+n-1,ja:ja+n-k) := (i-v*t*v')*(a(ia:ia+n-1,ja:ja+n-k)-y*v'). q' * sub( a ) * q, and returns the matrices v and w which are needed to apply the transformation to the unreduced part of sub( a ) if uplo = 'u', pzlatrd reduces the last nb rows and columns of a if the scaling needed for a in the dot product is 1 initiate send of off-diag block(s) to overlap with next part. off-diagonal block needed on neighboring processor to star do until this proc is needed to modify other procs' equation initiate send of off-diag block(s) to overlap with next part. off-diagonal block needed on neighboring processor to star do until this proc is needed to modify other procs' equation orthogonalization (see orfac). note that this may overestimate the minimum workspace needed lwork (local input) integer |
| needs needs transfer last triangle d_i of local matrix to next processor which needs it to calculate fillin due to factorization o overlap the send with the factorization of a_i. transfer last triangle d_i of local matrix to next processor which needs it to calculate fillin due to factorization o overlap the send with the factorization of a_i. z, ldz -> z, iz, jz, descz workspace needs are larger for pcheevx the values are stored, if there are any values that a node needs, they will be sent and received. then the next majo small subdiagonals. everyone needs to receive the new nbulg transfer last triangle d_i of local matrix to next processor which needs it to calculate fillin due to factorization o overlap the send with the factorization of a_i. transfer last triangle d_i of local matrix to next processor which needs it to calculate fillin due to factorization o overlap the send with the factorization of a_i. transfer last triangle d_i of local matrix to next processor which needs it to calculate fillin due to factorization o overlap the send with the factorization of a_i. transfer last triangle d_i of local matrix to next processor which needs it to calculate fillin due to factorization o overlap the send with the factorization of a_i. the values are stored, if there are any values that a node needs, they will be sent and received. then the next majo small subdiagonals. transfer last triangle d_i of local matrix to next processor which needs it to calculate fillin due to factorization o overlap the send with the factorization of a_i. transfer last triangle d_i of local matrix to next processor which needs it to calculate fillin due to factorization o overlap the send with the factorization of a_i. a value of 1 should work, but on machines with sloppy arithmetic, this needs to be larger. the default fo the worst machine around. note that this has no effect z, ldz -> z, iz, jz, descz workspace needs are larger for pdsyevx pjlaenv is patterned after ilaenv and keeps the same interface in anticipation of future needs, even though pjlaenv is only sparsel data layout blocking factor as the algorithmic blocking factor - transfer last triangle d_i of local matrix to next processor which needs it to calculate fillin due to factorization o overlap the send with the factorization of a_i. transfer last triangle d_i of local matrix to next processor which needs it to calculate fillin due to factorization o overlap the send with the factorization of a_i. the values are stored, if there are any values that a node needs, they will be sent and received. then the next majo small subdiagonals. transfer last triangle d_i of local matrix to next processor which needs it to calculate fillin due to factorization o overlap the send with the factorization of a_i. transfer last triangle d_i of local matrix to next processor which needs it to calculate fillin due to factorization o overlap the send with the factorization of a_i. a value of 1 should work, but on machines with sloppy arithmetic, this needs to be larger. the default fo the worst machine around. note that this has no effect z, ldz -> z, iz, jz, descz workspace needs are larger for pssyevx transfer last triangle d_i of local matrix to next processor which needs it to calculate fillin due to factorization o overlap the send with the factorization of a_i. transfer last triangle d_i of local matrix to next processor which needs it to calculate fillin due to factorization o overlap the send with the factorization of a_i. z, ldz -> z, iz, jz, descz workspace needs are larger for pzheevx the values are stored, if there are any values that a node needs, they will be sent and received. then the next majo small subdiagonals. everyone needs to receive the new nbulg transfer last triangle d_i of local matrix to next processor which needs it to calculate fillin due to factorization o overlap the send with the factorization of a_i. transfer last triangle d_i of local matrix to next processor which needs it to calculate fillin due to factorization o overlap the send with the factorization of a_i. |
| negative negative no reorthogonalization will be done if orfac equals zero. a default value of 10^-3 is used if orfac is negative no reorthogonalization will be done if orfac equals zero. a default value of 10^-3 is used if orfac is negative scale is assumed to be non-negative and scl returns the valu scl = max( scale, abs( real( x( i ) ) ), abs( aimag( x( i ) ) ) ), no orthogonalization will be done if orfac equals zero. a default value of 10^-3 is used if orfac is negative pdlapdct counts the number of negative eigenvalues of (t - sigma i) the innermost loop to avoid overflow and determine the sign of a where x( i ) = sub( x ) = x( ix+(jx-1)*descx(m_)+(i-1)*incx ). the value of sumsq is assumed to be non-negative and scl returns th point number is assumed be in the 32nd bit position (c) the sign of negative zero see w. kahan "accurate eigenvalues of a symmetric tridiagonal no orthogonalization will be done if orfac equals zero. a default value of 10^-3 is used if orfac is negative no reorthogonalization will be done if orfac equals zero. a default value of 10^-3 is used if orfac is negative no reorthogonalization will be done if orfac equals zero. a default value of 10^-3 is used if orfac is negative pslapdct counts the number of negative eigenvalues of (t - sigma i) the innermost loop to avoid overflow and determine the sign of a where x( i ) = sub( x ) = x( ix+(jx-1)*descx(m_)+(i-1)*incx ). the value of sumsq is assumed to be non-negative and scl returns th point number is assumed be in the 32nd or 64th bit position (c) the sign of negative zero see w. kahan "accurate eigenvalues of a symmetric tridiagonal no orthogonalization will be done if orfac equals zero. a default value of 10^-3 is used if orfac is negative no reorthogonalization will be done if orfac equals zero. a default value of 10^-3 is used if orfac is negative no reorthogonalization will be done if orfac equals zero. a default value of 10^-3 is used if orfac is negative no reorthogonalization will be done if orfac equals zero. a default value of 10^-3 is used if orfac is negative no reorthogonalization will be done if orfac equals zero. a default value of 10^-3 is used if orfac is negative scale is assumed to be non-negative and scl returns the valu scl = max( scale, abs( real( x( i ) ) ), abs( aimag( x( i ) ) ) ), no orthogonalization will be done if orfac equals zero. a default value of 10^-3 is used if orfac is negative |
| negligible negligible eigenvalues i+1 to ihi have already converged. either l = ilo, or h(l,l-1) is negligible so that the matrix splits given by h44, h33, & h43h34 and see if this would make a subdiagonal negligible notes and columns l to i. eigenvalues i+1 to ihi have already converged. either l = ilo or the global a(l,l-1) is negligible given by h44, h33, & h43h34 and see if this would make a subdiagonal negligible notes and columns l to i. eigenvalues i+1 to ihi have already converged. either l = ilo or the global a(l,l-1) is negligible given by h44, h33, & h43h34 and see if this would make a subdiagonal negligible notes and columns l to i. eigenvalues i+1 to ihi have already converged. either l = ilo or the global a(l,l-1) is negligible given by h44, h33, & h43h34 and see if this would make a subdiagonal negligible notes and columns l to i. eigenvalues i+1 to ihi have already converged. either l = ilo or the global a(l,l-1) is negligible eigenvalues i+1 to ihi have already converged. either l = ilo, or h(l,l-1) is negligible so that the matrix splits |
| NEIG NEIG lrwork >= 4*n + max( 5*nn, np0 * mq0 ) + iceil( NEIG, nprow*npcol)*n the computed eigenvectors may not be orthogonal if the lrwork >= 4*n + max( 5*nn, np0 * mq0 ) + iceil( NEIG, nprow*npcol)*n the computed eigenvectors may not be orthogonal if the lwork >= 5*n + max( 5*nn, np0 * mq0 + 2 * nb * nb ) + iceil( NEIG, nprow*npcol)*n the computed eigenvectors may not be orthogonal if the lwork >= 5 * n + max( 5*nn, np0 * mq0 + 2 * nb * nb ) + iceil( NEIG, nprow*npcol)*n the computed eigenvectors may not be orthogonal if the lwork >= 5*n + max( 5*nn, np0 * mq0 + 2 * nb * nb ) + iceil( NEIG, nprow*npcol)*n the computed eigenvectors may not be orthogonal if the lwork >= 5 * n + max( 5*nn, np0 * mq0 + 2 * nb * nb ) + iceil( NEIG, nprow*npcol)*n the computed eigenvectors may not be orthogonal if the lrwork >= 4*n + max( 5*nn, np0 * mq0 ) + iceil( NEIG, nprow*npcol)*n the computed eigenvectors may not be orthogonal if the lrwork >= 4*n + max( 5*nn, np0 * mq0 ) + iceil( NEIG, nprow*npcol)*n the computed eigenvectors may not be orthogonal if the |
| neighboring neighboring initiate send of off-diag block(s) to overlap with next part. off-diagonal block needed on neighboring processor to star initiate send of off-diag block(s) to overlap with next part. off-diagonal block needed on neighboring processor to star initiate send of off-diag block(s) to overlap with next part. off-diagonal block needed on neighboring processor to star initiate send of off-diag block(s) to overlap with next part. off-diagonal block needed on neighboring processor to star initiate send of off-diag block(s) to overlap with next part. off-diagonal block needed on neighboring processor to star initiate send of off-diag block(s) to overlap with next part. off-diagonal block needed on neighboring processor to star initiate send of off-diag block(s) to overlap with next part. off-diagonal block needed on neighboring processor to star initiate send of off-diag block(s) to overlap with next part. off-diagonal block needed on neighboring processor to star initiate send of off-diag block(s) to overlap with next part. off-diagonal block needed on neighboring processor to star initiate send of off-diag block(s) to overlap with next part. off-diagonal block needed on neighboring processor to star initiate send of off-diag block(s) to overlap with next part. off-diagonal block needed on neighboring processor to star initiate send of off-diag block(s) to overlap with next part. off-diagonal block needed on neighboring processor to star initiate send of off-diag block(s) to overlap with next part. off-diagonal block needed on neighboring processor to star initiate send of off-diag block(s) to overlap with next part. off-diagonal block needed on neighboring processor to star initiate send of off-diag block(s) to overlap with next part. off-diagonal block needed on neighboring processor to star initiate send of off-diag block(s) to overlap with next part. off-diagonal block needed on neighboring processor to star |
| neighbors neighbors reduced system has been solved, communicate solutions to nearest neighbors in preparation for local computation phase reduced system has been solved, communicate solutions to nearest neighbors in preparation for local computation phase reduced system has been solved, communicate solutions to nearest neighbors in preparation for local computation phase reduced system has been solved, communicate solutions to nearest neighbors in preparation for local computation phase reduced system has been solved, communicate solutions to nearest neighbors in preparation for local computation phase reduced system has been solved, communicate solutions to nearest neighbors in preparation for local computation phase reduced system has been solved, communicate solutions to nearest neighbors in preparation for local computation phase reduced system has been solved, communicate solutions to nearest neighbors in preparation for local computation phase reduced system has been solved, communicate solutions to nearest neighbors in preparation for local computation phase reduced system has been solved, communicate solutions to nearest neighbors in preparation for local computation phase reduced system has been solved, communicate solutions to nearest neighbors in preparation for local computation phase reduced system has been solved, communicate solutions to nearest neighbors in preparation for local computation phase reduced system has been solved, communicate solutions to nearest neighbors in preparation for local computation phase reduced system has been solved, communicate solutions to nearest neighbors in preparation for local computation phase reduced system has been solved, communicate solutions to nearest neighbors in preparation for local computation phase reduced system has been solved, communicate solutions to nearest neighbors in preparation for local computation phase |
| neither neither the smallest r(i) to the largest r(i) (ia <= i <= ia+m-1). if rowcnd >= 0.1 and amax is neither too large nor too small if neither of the above error conditions hold and jobz = 'v' ia <= i <= ia+n-1 and ja <= j <= ja+n-1. if scond >= 0.1 and amax is neither too large nor too small, it is not wort the smallest r(i) to the largest r(i) (ia <= i <= ia+m-1). if rowcnd >= 0.1 and amax is neither too large nor too small ia <= i <= ia+n-1 and ja <= j <= ja+n-1. if scond >= 0.1 and amax is neither too large nor too small, it is not wort if neither of the above error conditions hold and jobz = 'v' the smallest r(i) to the largest r(i) (ia <= i <= ia+m-1). if rowcnd >= 0.1 and amax is neither too large nor too small ia <= i <= ia+n-1 and ja <= j <= ja+n-1. if scond >= 0.1 and amax is neither too large nor too small, it is not wort if neither of the above error conditions hold and jobz = 'v' the smallest r(i) to the largest r(i) (ia <= i <= ia+m-1). if rowcnd >= 0.1 and amax is neither too large nor too small if neither of the above error conditions hold and jobz = 'v' ia <= i <= ia+n-1 and ja <= j <= ja+n-1. if scond >= 0.1 and amax is neither too large nor too small, it is not wort |
| netlib netlib (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 ===================================================================== |
| networks networks in addition, this routine performs a global minimization and maximi- zation on these values, to support heterogeneous computing networks arguments in addition, this routine performs a global minimization and maximi- zation on these values, to support heterogeneous computing networks arguments |
| new new note: banded codes can use either the old two dimensional or new one-dimensional descriptors, though the processor grid i form a new blacs grid (the "standard form" grid) with only proc starting at csrc=0, with ja modified to reflect dropped procs. note: banded codes can use either the old two dimensional or new one-dimensional descriptors, though the processor grid i form a new blacs grid (the "standard form" grid) with only proc starting at csrc=0, with ja modified to reflect dropped procs. note: tridiagonal codes can use either the old two dimensional or new one-dimensional descriptors, though the processor grid i form a new blacs grid (the "standard form" grid) with only proc starting at csrc=0, with ja modified to reflect dropped procs. note: tridiagonal codes can use either the old two dimensional or new one-dimensional descriptors, though the processor grid i form a new blacs grid (the "standard form" grid) with only proc starting at csrc=0, with ja modified to reflect dropped procs. note: banded codes can use either the old two dimensional or new one-dimensional descriptors, though the processor grid i form a new blacs grid (the "standard form" grid) with only proc starting at csrc=0, with ja modified to reflect dropped procs. note: banded codes can use either the old two dimensional or new one-dimensional descriptors, though the processor grid i find a new nbulge based on the bulges we have note: banded codes can use either the old two dimensional or new one-dimensional descriptors, though the processor grid i form a new blacs grid (the "standard form" grid) with only proc starting at csrc=0, with ja modified to reflect dropped procs. note: banded codes can use either the old two dimensional or new one-dimensional descriptors, though the processor grid i form a new blacs grid (the "standard form" grid) with only proc starting at csrc=0, with ja modified to reflect dropped procs. note: tridiagonal codes can use either the old two dimensional or new one-dimensional descriptors, though the processor grid i form a new blacs grid (the "standard form" grid) with only proc starting at csrc=0, with ja modified to reflect dropped procs. note: tridiagonal codes can use either the old two dimensional or new one-dimensional descriptors, though the processor grid i form a new blacs grid (the "standard form" grid) with only proc starting at csrc=0, with ja modified to reflect dropped procs. note: banded codes can use either the old two dimensional or new one-dimensional descriptors, though the processor grid i form a new blacs grid (the "standard form" grid) with only proc starting at csrc=0, with ja modified to reflect dropped procs. note: banded codes can use either the old two dimensional or new one-dimensional descriptors, though the processor grid i form a new blacs grid (the "standard form" grid) with only proc starting at csrc=0, with ja modified to reflect dropped procs. note: tridiagonal codes can use either the old two dimensional or new one-dimensional descriptors, though the processor grid i form a new blacs grid (the "standard form" grid) with only proc starting at csrc=0, with ja modified to reflect dropped procs. note: tridiagonal codes can use either the old two dimensional or new one-dimensional descriptors, though the processor grid i form a new blacs grid (the "standard form" grid) with only proc starting at csrc=0, with ja modified to reflect dropped procs. note: banded codes can use either the old two dimensional or new one-dimensional descriptors, though the processor grid i form a new blacs grid (the "standard form" grid) with only proc starting at csrc=0, with ja modified to reflect dropped procs. note: banded codes can use either the old two dimensional or new one-dimensional descriptors, though the processor grid i note: banded codes can use either the old two dimensional or new one-dimensional descriptors, though the processor grid i form a new blacs grid (the "standard form" grid) with only proc starting at csrc=0, with ja modified to reflect dropped procs. note: banded codes can use either the old two dimensional or new one-dimensional descriptors, though the processor grid i form a new blacs grid (the "standard form" grid) with only proc starting at csrc=0, with ja modified to reflect dropped procs. note: tridiagonal codes can use either the old two dimensional or new one-dimensional descriptors, though the processor grid i form a new blacs grid (the "standard form" grid) with only proc starting at csrc=0, with ja modified to reflect dropped procs. note: tridiagonal codes can use either the old two dimensional or new one-dimensional descriptors, though the processor grid i form a new blacs grid (the "standard form" grid) with only proc starting at csrc=0, with ja modified to reflect dropped procs. with myprowc defined when a new context is created as call blacs_gridinit( contextc, 'r', nprocs, 1 ) note: banded codes can use either the old two dimensional or new one-dimensional descriptors, though the processor grid i form a new blacs grid (the "standard form" grid) with only proc starting at csrc=0, with ja modified to reflect dropped procs. note: banded codes can use either the old two dimensional or new one-dimensional descriptors, though the processor grid i form a new blacs grid (the "standard form" grid) with only proc starting at csrc=0, with ja modified to reflect dropped procs. note: tridiagonal codes can use either the old two dimensional or new one-dimensional descriptors, though the processor grid i form a new blacs grid (the "standard form" grid) with only proc starting at csrc=0, with ja modified to reflect dropped procs. note: tridiagonal codes can use either the old two dimensional or new one-dimensional descriptors, though the processor grid i form a new blacs grid (the "standard form" grid) with only proc starting at csrc=0, with ja modified to reflect dropped procs. note: banded codes can use either the old two dimensional or new one-dimensional descriptors, though the processor grid i form a new blacs grid (the "standard form" grid) with only proc starting at csrc=0, with ja modified to reflect dropped procs. note: banded codes can use either the old two dimensional or new one-dimensional descriptors, though the processor grid i note: banded codes can use either the old two dimensional or new one-dimensional descriptors, though the processor grid i form a new blacs grid (the "standard form" grid) with only proc starting at csrc=0, with ja modified to reflect dropped procs. note: banded codes can use either the old two dimensional or new one-dimensional descriptors, though the processor grid i form a new blacs grid (the "standard form" grid) with only proc starting at csrc=0, with ja modified to reflect dropped procs. note: tridiagonal codes can use either the old two dimensional or new one-dimensional descriptors, though the processor grid i form a new blacs grid (the "standard form" grid) with only proc starting at csrc=0, with ja modified to reflect dropped procs. note: tridiagonal codes can use either the old two dimensional or new one-dimensional descriptors, though the processor grid i form a new blacs grid (the "standard form" grid) with only proc starting at csrc=0, with ja modified to reflect dropped procs. with myprowc defined when a new context is created as call blacs_gridinit( contextc, 'r', nprocs, 1 ) note: banded codes can use either the old two dimensional or new one-dimensional descriptors, though the processor grid i form a new blacs grid (the "standard form" grid) with only proc starting at csrc=0, with ja modified to reflect dropped procs. note: banded codes can use either the old two dimensional or new one-dimensional descriptors, though the processor grid i form a new blacs grid (the "standard form" grid) with only proc starting at csrc=0, with ja modified to reflect dropped procs. note: tridiagonal codes can use either the old two dimensional or new one-dimensional descriptors, though the processor grid i form a new blacs grid (the "standard form" grid) with only proc starting at csrc=0, with ja modified to reflect dropped procs. note: tridiagonal codes can use either the old two dimensional or new one-dimensional descriptors, though the processor grid i form a new blacs grid (the "standard form" grid) with only proc starting at csrc=0, with ja modified to reflect dropped procs. note: banded codes can use either the old two dimensional or new one-dimensional descriptors, though the processor grid i form a new blacs grid (the "standard form" grid) with only proc starting at csrc=0, with ja modified to reflect dropped procs. note: banded codes can use either the old two dimensional or new one-dimensional descriptors, though the processor grid i find a new nbulge based on the bulges we have note: banded codes can use either the old two dimensional or new one-dimensional descriptors, though the processor grid i form a new blacs grid (the "standard form" grid) with only proc starting at csrc=0, with ja modified to reflect dropped procs. note: banded codes can use either the old two dimensional or new one-dimensional descriptors, though the processor grid i form a new blacs grid (the "standard form" grid) with only proc starting at csrc=0, with ja modified to reflect dropped procs. note: tridiagonal codes can use either the old two dimensional or new one-dimensional descriptors, though the processor grid i form a new blacs grid (the "standard form" grid) with only proc starting at csrc=0, with ja modified to reflect dropped procs. note: tridiagonal codes can use either the old two dimensional or new one-dimensional descriptors, though the processor grid i form a new blacs grid (the "standard form" grid) with only proc starting at csrc=0, with ja modified to reflect dropped procs. |
| next next find gp & rp for the next iteratio goto put in by g. henry to fix alpha problem save the shift to check eigenvalue spacing at next transfer last triangle d_i of local matrix to next processo its main (odd) block a_i. calculate contribution from this block to next diagonal bloc transfer last triangle d_i of local matrix to next processo its main (odd) block a_i. calculate contribution from this block to next diagonal bloc transfer triangle b_i of local matrix to next processo a few lines after they are set and do hold state from one loop iteration to the next the matrix a: the values are stored, if there are any values that a node needs, they will be sent and received. then the next majo small subdiagonals. do some work so next step is ready.. transfer last triangle d_i of local matrix to next processo its main (odd) block a_i. calculate contribution from this block to next diagonal bloc transfer last triangle d_i of local matrix to next processo its main (odd) block a_i. calculate contribution from this block to next diagonal bloc transfer last triangle d_i of local matrix to next processo its main (odd) block a_i. calculate contribution from this block to next diagonal bloc transfer last triangle d_i of local matrix to next processo its main (odd) block a_i. calculate contribution from this block to next diagonal bloc transfer triangle b_i of local matrix to next processo the values are stored, if there are any values that a node needs, they will be sent and received. then the next majo small subdiagonals. transfer last triangle d_i of local matrix to next processo its main (odd) block a_i. calculate contribution from this block to next diagonal bloc transfer last triangle d_i of local matrix to next processo its main (odd) block a_i. calculate contribution from this block to next diagonal bloc where "ulp" is the machine precision (distance from 1 to the next larger floating point number. fudge double precision, default = 2.0 a few lines after they are set and do hold state from one loop iteration to the next the matrix a: transfer last triangle d_i of local matrix to next processo its main (odd) block a_i. calculate contribution from this block to next diagonal bloc transfer last triangle d_i of local matrix to next processo its main (odd) block a_i. calculate contribution from this block to next diagonal bloc transfer triangle b_i of local matrix to next processo the values are stored, if there are any values that a node needs, they will be sent and received. then the next majo small subdiagonals. transfer last triangle d_i of local matrix to next processo its main (odd) block a_i. calculate contribution from this block to next diagonal bloc transfer last triangle d_i of local matrix to next processo its main (odd) block a_i. calculate contribution from this block to next diagonal bloc where "ulp" is the machine precision (distance from 1 to the next larger floating point number. fudge real, default = 2.0 a few lines after they are set and do hold state from one loop iteration to the next the matrix a: transfer last triangle d_i of local matrix to next processo its main (odd) block a_i. calculate contribution from this block to next diagonal bloc transfer last triangle d_i of local matrix to next processo its main (odd) block a_i. calculate contribution from this block to next diagonal bloc transfer triangle b_i of local matrix to next processo a few lines after they are set and do hold state from one loop iteration to the next the matrix a: the values are stored, if there are any values that a node needs, they will be sent and received. then the next majo small subdiagonals. do some work so next step is ready.. transfer last triangle d_i of local matrix to next processo its main (odd) block a_i. calculate contribution from this block to next diagonal bloc transfer last triangle d_i of local matrix to next processo its main (odd) block a_i. calculate contribution from this block to next diagonal bloc save the shift to check eigenvalue spacing at next find gp & rp for the next iteratio goto put in by g. henry to fix alpha problem |
| NHEGST_LWOPT NHEGST_LWOPT lwork >= max( lwork, n + nhetrd_lwopt, NHEGST_LWOPT nhetrd_lwork = 2*( anb+1 )*( 4*nps+2 ) + lwork >= max( lwork, n + nhetrd_lwopt, NHEGST_LWOPT nhetrd_lwork = 2*( anb+1 )*( 4*nps+2 ) + |
| NHETRD_LWOPT NHETRD_LWOPT for optimal performance, greater workspace is needed, i.e. lwork >= max( lwork, n + NHETRD_LWOPT where lwork is as defined above, and for optimal performance, greater workspace is needed, i.e. lwork >= max( lwork, n + NHETRD_LWOPT where lwork is as defined above, and |
| NHETRD_LWORK NHETRD_LWORK for optimal performance, greater workspace is needed, i.e. lwork >= max( lwork, NHETRD_LWORK nhetrd_lwork = n + 2*( anb+1 )*( 4*nps+2 ) + where lwork is as defined above, and NHETRD_LWORK = 2*( anb+1 )*( 4*nps+2 ) nhegst_lwopt = 2*np0*nb + nq0*nb + nb*nb for optimal performance, greater workspace is needed, i.e. lwork >= max( lwork, NHETRD_LWORK nhetrd_lwork = n + 2*( anb+1 )*( 4*nps+2 ) + where lwork is as defined above, and NHETRD_LWORK = 2*( anb+1 )*( 4*nps+2 ) nhegst_lwopt = 2*np0*nb + nq0*nb + nb*nb |
| Nick Nick the serial version clacon has been contributed by Nick higham march 16, 1988. the serial version was contributed to lapack by Nick higham for us the serial version dlacon has been contributed by Nick higham march 16, 1988. the serial version of this routine was originally contributed by Nick higham for use with zlacon notes the serial version of this routine was originally contributed by Nick higham for use with clacon notes the serial version slacon has been contributed by Nick higham march 16, 1988. the serial version zlacon has been contributed by Nick higham march 16, 1988. the serial version was contributed to lapack by Nick higham for us |
| NN1 NN1 nn (global output) integer, the order of matrix u, (pdlaed1). NN1 (global output) integer, the order of matrix q1, (pdlaed1) ib1 (global output) integer, pointeur on q1, (pdlaed1). nn (global output) integer, the order of matrix u, (pslaed1). NN1 (global output) integer, the order of matrix q1, (pslaed1) ib1 (global output) integer, pointeur on q1, (pslaed1). |
| NN2 NN2 nn1 (global output) integer, the order of matrix q1, (pdlaed1). NN2 (global output) integer, the order of matrix q2, (pdlaed1) ib2 (global output) integer, pointeur on q2, (pdlaed1). nn1 (global output) integer, the order of matrix q1, (pslaed1). NN2 (global output) integer, the order of matrix q2, (pslaed1) ib2 (global output) integer, pointeur on q2, (pslaed1). |
| NNP NNP size of iwork liwork >= 6 * NNP nnp = max( n, nprow*npcol + 1, 4 ) size of iwork liwork >= 6 * NNP nnp = max( n, nprow*npcol + 1, 4 ) size of iwork liwork >= 6 * NNP nnp = max( n, nprow*npcol + 1, 4 ) size of iwork liwork >= 6 * NNP nnp = max( n, nprow*npcol + 1, 4 ) size of iwork liwork >= 6 * NNP nnp = max( n, nprow*npcol + 1, 4 ) size of iwork liwork >= 6 * NNP nnp = max( n, nprow*npcol + 1, 4 ) size of iwork liwork >= 6 * NNP nnp = max( n, nprow*npcol + 1, 4 ) size of iwork liwork >= 6 * NNP nnp = max( n, nprow*npcol + 1, 4 ) |
| NO_IEEE NO_IEEE note : it is assumed that the user is on an ieee machine. if the user is not on an ieee mchine, set the compile time flag NO_IEEE are needed for the "fast" sturm count are : (a) infinity note : it is assumed that the user is on an ieee machine. if the user is not on an ieee mchine, set the compile time flag NO_IEEE are needed for the "fast" sturm count are : (a) infinity |
| node node clamsh sends multiple shifts through a small (single node) matrix t subsequent shifts in an effort to maximize the number of bulges dlamsh sends multiple shifts through a small (single node) matrix t subsequent shifts in an effort to maximize the number of bulges this node will potentially do more work late processors, the first major loop (10) goes over the tridiagonal and has each node store whatever values of the 7 it has tha and can happen in no more than 3 locations per block assuming array into a local replicated array or vise versa. notice that the entire submatrix that is copied gets placed on one node o can receive, or just one row or column of nodes. node (iafirst,jafirst) owns a(1,1 this node will potentially do more work late processors, the first major loop (10) goes over the tridiagonal and has each node store whatever values of the 7 it has tha and can happen in no more than 3 locations per block assuming array into a local replicated array or vise versa. notice that the entire submatrix that is copied gets placed on one node o can receive, or just one row or column of nodes. node (iafirst,jafirst) owns a(1,1 this node will potentially do more work late processors, the first major loop (10) goes over the tridiagonal and has each node store whatever values of the 7 it has tha and can happen in no more than 3 locations per block assuming array into a local replicated array or vise versa. notice that the entire submatrix that is copied gets placed on one node o can receive, or just one row or column of nodes. node (iafirst,jafirst) owns a(1,1 this node will potentially do more work late processors, the first major loop (10) goes over the tridiagonal and has each node store whatever values of the 7 it has tha and can happen in no more than 3 locations per block assuming array into a local replicated array or vise versa. notice that the entire submatrix that is copied gets placed on one node o can receive, or just one row or column of nodes. node (iafirst,jafirst) owns a(1,1 slamsh sends multiple shifts through a small (single node) matrix t subsequent shifts in an effort to maximize the number of bulges zlamsh sends multiple shifts through a small (single node) matrix t subsequent shifts in an effort to maximize the number of bulges |
| nodes nodes the entire submatrix that is copied gets placed on one node or more. the receiving node can be specified precisely, or all nodes the entire submatrix that is copied gets placed on one node or more. the receiving node can be specified precisely, or all nodes the entire submatrix that is copied gets placed on one node or more. the receiving node can be specified precisely, or all nodes the entire submatrix that is copied gets placed on one node or more. the receiving node can be specified precisely, or all nodes |
| noise noise skip the current step: the subdiagonal info is just noise skip the current step: the subdiagonal info is just noise |
| non non non-cyclic restriction: very important the mapping for matrices must be blocked, reflecting the nature non-cyclic restriction: very important the mapping for matrices must be blocked, reflecting the nature non-cyclic restriction: very important the mapping for matrices must be blocked, reflecting the nature non-cyclic restriction: very important the mapping for matrices must be blocked, reflecting the nature info and factored locally was not nonsingular, an if info = k>nprocs, the submatrix stored on processor non-cyclic restriction: very important the mapping for matrices must be blocked, reflecting the nature scale is assumed to be non-negative and scl returns the valu scl = max( scale, abs( real( x( i ) ) ), abs( aimag( x( i ) ) ) ), a is non-unit triangular compute grow = 1/g(j) and xbnd = 1/m(j). non-cyclic restriction: very important the mapping for matrices must be blocked, reflecting the nature non-cyclic restriction: very important the mapping for matrices must be blocked, reflecting the nature non-cyclic restriction: very important the mapping for matrices must be blocked, reflecting the nature non-cyclic restriction: very important the mapping for matrices must be blocked, reflecting the nature diag (global input) character = 'n': a(ia:ia+n-1,ja:ja+n-1) is non-unit triangular diag (global input) character*1 = 'n': sub( a ) is non-unit triangular diag (global input) character*1 = 'n': sub( a ) is non-unit triangula is unit triangular: = 'n': non-unit triangular n-by-nrhs distributed matrix denoted by sub( b ). a check is made to verify that sub( a ) is nonsingular notes non-cyclic restriction: very important the mapping for matrices must be blocked, reflecting the nature non-cyclic restriction: very important the mapping for matrices must be blocked, reflecting the nature non-cyclic restriction: very important the mapping for matrices must be blocked, reflecting the nature non-cyclic restriction: very important the mapping for matrices must be blocked, reflecting the nature info and factored locally was not nonsingular, an if info = k>nprocs, the submatrix stored on processor non-cyclic restriction: very important the mapping for matrices must be blocked, reflecting the nature k (output) integer the number of non-deflated eigenvalues, and the order of th it could conceivably fail on hexadecimal or decimal machines without guard digits, but we know of none arguments where x( i ) = sub( x ) = x( ix+(jx-1)*descx(m_)+(i-1)*incx ). the value of sumsq is assumed to be non-negative and scl returns th non-cyclic restriction: very important the mapping for matrices must be blocked, reflecting the nature non-cyclic restriction: very important the mapping for matrices must be blocked, reflecting the nature non-cyclic restriction: very important the mapping for matrices must be blocked, reflecting the nature non-cyclic restriction: very important the mapping for matrices must be blocked, reflecting the nature diag (global input) character = 'n': a(ia:ia+n-1,ja:ja+n-1) is non-unit triangular diag (global input) character*1 = 'n': sub( a ) is non-unit triangular diag (global input) character*1 = 'n': sub( a ) is non-unit triangula is unit triangular: = 'n': non-unit triangular n-by-nrhs distributed matrix denoted by sub( b ). a check is made to verify that sub( a ) is nonsingular notes non-cyclic restriction: very important the mapping for matrices must be blocked, reflecting the nature non-cyclic restriction: very important the mapping for matrices must be blocked, reflecting the nature non-cyclic restriction: very important the mapping for matrices must be blocked, reflecting the nature non-cyclic restriction: very important the mapping for matrices must be blocked, reflecting the nature info and factored locally was not nonsingular, an if info = k>nprocs, the submatrix stored on processor non-cyclic restriction: very important the mapping for matrices must be blocked, reflecting the nature k (output) integer the number of non-deflated eigenvalues, and the order of th it could conceivably fail on hexadecimal or decimal machines without guard digits, but we know of none arguments where x( i ) = sub( x ) = x( ix+(jx-1)*descx(m_)+(i-1)*incx ). the value of sumsq is assumed to be non-negative and scl returns th non-cyclic restriction: very important the mapping for matrices must be blocked, reflecting the nature non-cyclic restriction: very important the mapping for matrices must be blocked, reflecting the nature non-cyclic restriction: very important the mapping for matrices must be blocked, reflecting the nature non-cyclic restriction: very important the mapping for matrices must be blocked, reflecting the nature diag (global input) character = 'n': a(ia:ia+n-1,ja:ja+n-1) is non-unit triangular diag (global input) character*1 = 'n': sub( a ) is non-unit triangular diag (global input) character*1 = 'n': sub( a ) is non-unit triangula is unit triangular: = 'n': non-unit triangular n-by-nrhs distributed matrix denoted by sub( b ). a check is made to verify that sub( a ) is nonsingular notes non-cyclic restriction: very important the mapping for matrices must be blocked, reflecting the nature non-cyclic restriction: very important the mapping for matrices must be blocked, reflecting the nature non-cyclic restriction: very important the mapping for matrices must be blocked, reflecting the nature non-cyclic restriction: very important the mapping for matrices must be blocked, reflecting the nature info and factored locally was not nonsingular, an if info = k>nprocs, the submatrix stored on processor non-cyclic restriction: very important the mapping for matrices must be blocked, reflecting the nature scale is assumed to be non-negative and scl returns the valu scl = max( scale, abs( real( x( i ) ) ), abs( aimag( x( i ) ) ) ), a is non-unit triangular compute grow = 1/g(j) and xbnd = 1/m(j). non-cyclic restriction: very important the mapping for matrices must be blocked, reflecting the nature non-cyclic restriction: very important the mapping for matrices must be blocked, reflecting the nature non-cyclic restriction: very important the mapping for matrices must be blocked, reflecting the nature non-cyclic restriction: very important the mapping for matrices must be blocked, reflecting the nature diag (global input) character = 'n': a(ia:ia+n-1,ja:ja+n-1) is non-unit triangular diag (global input) character*1 = 'n': sub( a ) is non-unit triangular diag (global input) character*1 = 'n': sub( a ) is non-unit triangula is unit triangular: = 'n': non-unit triangular n-by-nrhs distributed matrix denoted by sub( b ). a check is made to verify that sub( a ) is nonsingular notes |
| nondeflated nondeflated the permutation used to place deflated values of d at the end of the array. indxp(1:k) points to the nondeflated d-value the permutation used to place deflated values of d at the end of the array. indxp(1:k) points to the nondeflated d-value |
| none none it could conceivably fail on hexadecimal or decimal machines without guard digits, but we know of none arguments it could conceivably fail on hexadecimal or decimal machines without guard digits, but we know of none. see dlaed3 for details arguments it could conceivably fail on hexadecimal or decimal machines without guard digits, but we know of none arguments it could conceivably fail on hexadecimal or decimal machines without guard digits, but we know of none. see slaed3 for details arguments |
| nonhermitian nonhermitian clanv2 computes the schur factorization of a complex 2-by-2 nonhermitian matrix in standard form [ a b ] = [ cs -sn ] [ aa bb ] [ cs sn ] zlanv2 computes the schur factorization of a complex 2-by-2 nonhermitian matrix in standard form [ a b ] = [ cs -sn ] [ aa bb ] [ cs sn ] |
| nonpositive nonpositive > 0: if info = k, the k-th diagonal entry of sub( a ) is nonpositive ===================================================================== > 0: if info = k, the k-th diagonal entry of sub( a ) is nonpositive ===================================================================== > 0: if info = k, the k-th diagonal entry of sub( a ) is nonpositive ===================================================================== > 0: if info = k, the k-th diagonal entry of sub( a ) is nonpositive ===================================================================== |
| nonsingular nonsingular info and factored locally was not nonsingular, an if info = k>nprocs, the submatrix stored on processor in particular, if sub( b ) is square and nonsingular, the gq factorization of inv( sub( b ) )* sub( a ): in particular, if sub( b ) is square and nonsingular, the gr factorization of sub( a )*inv( sub( b ) ): n-by-nrhs distributed matrix denoted by sub( b ). a check is made to verify that sub( a ) is nonsingular notes info and factored locally was not nonsingular, an if info = k>nprocs, the submatrix stored on processor in particular, if sub( b ) is square and nonsingular, the gq factorization of inv( sub( b ) )* sub( a ): in particular, if sub( b ) is square and nonsingular, the gr factorization of sub( a )*inv( sub( b ) ): n-by-nrhs distributed matrix denoted by sub( b ). a check is made to verify that sub( a ) is nonsingular notes info and factored locally was not nonsingular, an if info = k>nprocs, the submatrix stored on processor in particular, if sub( b ) is square and nonsingular, the gq factorization of inv( sub( b ) )* sub( a ): in particular, if sub( b ) is square and nonsingular, the gr factorization of sub( a )*inv( sub( b ) ): n-by-nrhs distributed matrix denoted by sub( b ). a check is made to verify that sub( a ) is nonsingular notes info and factored locally was not nonsingular, an if info = k>nprocs, the submatrix stored on processor in particular, if sub( b ) is square and nonsingular, the gq factorization of inv( sub( b ) )* sub( a ): in particular, if sub( b ) is square and nonsingular, the gr factorization of sub( a )*inv( sub( b ) ): n-by-nrhs distributed matrix denoted by sub( b ). a check is made to verify that sub( a ) is nonsingular notes |
| nonzero nonzero from the vector v and applies it from left and right to h, thus creating a nonzero bulge below the subdiagonal each subsequent iteration determines a reflection g to result cto * a(i,j) / cfrom can be represented without over/underflow. cfrom must be nonzero m (global input) integer result cto * a(i,j) / cfrom can be represented without over/underflow. cfrom must be nonzero m (global input) integer result cto * a(i,j) / cfrom can be represented without over/underflow. cfrom must be nonzero m (global input) integer result cto * a(i,j) / cfrom can be represented without over/underflow. cfrom must be nonzero m (global input) integer from the vector v and applies it from left and right to h, thus creating a nonzero bulge below the subdiagonal each subsequent iteration determines a reflection g to |
| nonzeros nonzeros where l is a product of unit lower bidiagonal matrices and u is upper triangular with nonzeros in only the mai where l is a product of unit lower bidiagonal matrices and u is upper triangular with nonzeros in only the mai where l is a product of unit lower bidiagonal matrices and u is upper triangular with nonzeros in only the mai where l is a product of unit lower bidiagonal matrices and u is upper triangular with nonzeros in only the mai |
| nor nor the smallest r(i) to the largest r(i) (ia <= i <= ia+m-1). if rowcnd >= 0.1 and amax is neither too large nor too small the matrix a does not hold the same values that it would in an unblocked code nor the values that it would hold i sub( a ) = a(ia:ia+n-1,ja:ja+n-1) and reduce its condition number (with respect to the two-norm). sr and sc contain the scal buted matrix b with elements b(i,j) = s(i)*a(i,j)*s(j) has ones on the smallest r(i) to the largest r(i) (ia <= i <= ia+m-1). if rowcnd >= 0.1 and amax is neither too large nor too small sub( a ) = a(ia:ia+n-1,ja:ja+n-1) and reduce its condition number (with respect to the two-norm). sr and sc contain the scal buted matrix b with elements b(i,j) = s(i)*a(i,j)*s(j) has ones on the matrix a does not hold the same values that it would in an unblocked code nor the values that it would hold i the smallest r(i) to the largest r(i) (ia <= i <= ia+m-1). if rowcnd >= 0.1 and amax is neither too large nor too small sub( a ) = a(ia:ia+n-1,ja:ja+n-1) and reduce its condition number (with respect to the two-norm). sr and sc contain the scal buted matrix b with elements b(i,j) = s(i)*a(i,j)*s(j) has ones on the matrix a does not hold the same values that it would in an unblocked code nor the values that it would hold i the smallest r(i) to the largest r(i) (ia <= i <= ia+m-1). if rowcnd >= 0.1 and amax is neither too large nor too small the matrix a does not hold the same values that it would in an unblocked code nor the values that it would hold i sub( a ) = a(ia:ia+n-1,ja:ja+n-1) and reduce its condition number (with respect to the two-norm). sr and sc contain the scal buted matrix b with elements b(i,j) = s(i)*a(i,j)*s(j) has ones on |
| norm norm set machine-dependent constants for the stopping criterion. if norm(h) <= sqrt(ovfl), overflow should not occur normalize and scale the righthand side vector pb distributed complex matrix a(ia:ia+n-1,ja:ja+n-1), in either the 1-norm or the infinity-norm, using the lu factorization computed b 2. if trans = 'n' and m < n: find the minimum norm solution o where eps is the machine precision. if abstol is less than or equal to zero, then eps*norm(t) will be used in its place obtained by reducing a to tridiagonal form. the distributed matrix z of eigenvectors. the eigenvectors are normalized as follows if ibtype = 3, z**h*inv( sub( b ) )*z = i. pclacon estimates the 1-norm of a square, complex distributed matri products. x and v are aligned with the distributed matrix a, this set machine-dependent constants for the stopping criterion. if norm(h) <= sqrt(ovfl), overflow should not occur pclange returns the value of the one norm, or the frobenius norm distributed matrix sub( a ) = a(ia:ia+m-1, ja:ja+n-1). refered to as rowsums, and the column sums shown by | are refered to as colsums. infinity-norm = 1-norm = rowsums+colsums uplo = 'u' uplo = 'l' find maximum sum of columns for 1-norm refered to as rowsums, and the column sums shown by | are refered to as colsums. infinity-norm = 1-norm = rowsums+colsums uplo = 'u' uplo = 'l' find maximum sum of columns for 1-norm compute the 1-norm of each column, not including the diagonal pcpocon estimates the reciprocal of the condition number (in the 1-norm) of a complex hermitian positive definite distributed matri pcpotrf. sub( a ) = a(ia:ia+n-1,ja:ja+n-1) and reduce its condition number (with respect to the two-norm). sr and sc contain the scal buted matrix b with elements b(i,j) = s(i)*a(i,j)*s(j) has ones on the error bound depends on the quality of the estimate of norm(inv(a)) computed in the code; if the estimate o triangular distributed matrix a(ia:ia+n-1,ja:ja+n-1), in either the 1-norm or the infinity-norm the norm of a(ia:ia+n-1,ja:ja+n-1) is computed and an estimate is pdgecon estimates the reciprocal of the condition number of a general distributed real matrix a(ia:ia+n-1,ja:ja+n-1), in either the 1-norm 2. if trans = 'n' and m < n: find the minimum norm solution o pdlacon estimates the 1-norm of a square, real distributed matrix a x and v are aligned with the distributed matrix a, this information set machine-dependent constants for the stopping criterion. if norm(h) <= sqrt(ovfl), overflow should not occur pdlange returns the value of the one norm, or the frobenius norm distributed matrix sub( a ) = a(ia:ia+m-1, ja:ja+n-1). find maximum sum of columns for 1-norm refered to as rowsums, and the column sums shown by | are refered to as colsums. infinity-norm = 1-norm = rowsums+colsums uplo = 'u' uplo = 'l' find maximum sum of columns for 1-norm pdpocon estimates the reciprocal of the condition number (in the 1-norm) of a real symmetric positive definite distributed matri pdpotrf. sub( a ) = a(ia:ia+n-1,ja:ja+n-1) and reduce its condition number (with respect to the two-norm). sr and sc contain the scal buted matrix b with elements b(i,j) = s(i)*a(i,j)*s(j) has ones on the error bound depends on the quality of the estimate of norm(inv(a)) computed in the code; if the estimate o less. if abstol is less than or equal to zero, then ulp*|t|
will be used, where |t| means the 1-norm of t
set to the underflow threshold dlamch('u'), not zero.
where eps is the machine precision. if abstol is less than or equal to zero, then eps*norm(t) will be used in its place obtained by reducing a to tridiagonal form. the distributed matrix z of eigenvectors. the eigenvectors are normalized as follows if ibtype = 3, z**t*inv( sub( b ) )*z = i. triangular distributed matrix a(ia:ia+n-1,ja:ja+n-1), in either the 1-norm or the infinity-norm the norm of a(ia:ia+n-1,ja:ja+n-1) is computed and an estimate is psgecon estimates the reciprocal of the condition number of a general distributed real matrix a(ia:ia+n-1,ja:ja+n-1), in either the 1-norm 2. if trans = 'n' and m < n: find the minimum norm solution o pslacon estimates the 1-norm of a square, real distributed matrix a x and v are aligned with the distributed matrix a, this information set machine-dependent constants for the stopping criterion. if norm(h) <= sqrt(ovfl), overflow should not occur pslange returns the value of the one norm, or the frobenius norm distributed matrix sub( a ) = a(ia:ia+m-1, ja:ja+n-1). find maximum sum of columns for 1-norm refered to as rowsums, and the column sums shown by | are refered to as colsums. infinity-norm = 1-norm = rowsums+colsums uplo = 'u' uplo = 'l' find maximum sum of columns for 1-norm pspocon estimates the reciprocal of the condition number (in the 1-norm) of a real symmetric positive definite distributed matri pspotrf. sub( a ) = a(ia:ia+n-1,ja:ja+n-1) and reduce its condition number (with respect to the two-norm). sr and sc contain the scal buted matrix b with elements b(i,j) = s(i)*a(i,j)*s(j) has ones on the error bound depends on the quality of the estimate of norm(inv(a)) computed in the code; if the estimate o less. if abstol is less than or equal to zero, then ulp*|t|
will be used, where |t| means the 1-norm of t
set to the underflow threshold slamch('u'), not zero.
where eps is the machine precision. if abstol is less than or equal to zero, then eps*norm(t) will be used in its place obtained by reducing a to tridiagonal form. the distributed matrix z of eigenvectors. the eigenvectors are normalized as follows if ibtype = 3, z**t*inv( sub( b ) )*z = i. triangular distributed matrix a(ia:ia+n-1,ja:ja+n-1), in either the 1-norm or the infinity-norm the norm of a(ia:ia+n-1,ja:ja+n-1) is computed and an estimate is distributed complex matrix a(ia:ia+n-1,ja:ja+n-1), in either the 1-norm or the infinity-norm, using the lu factorization computed b 2. if trans = 'n' and m < n: find the minimum norm solution o where eps is the machine precision. if abstol is less than or equal to zero, then eps*norm(t) will be used in its place obtained by reducing a to tridiagonal form. the distributed matrix z of eigenvectors. the eigenvectors are normalized as follows if ibtype = 3, z**h*inv( sub( b ) )*z = i. pzlacon estimates the 1-norm of a square, complex distributed matri products. x and v are aligned with the distributed matrix a, this set machine-dependent constants for the stopping criterion. if norm(h) <= sqrt(ovfl), overflow should not occur pzlange returns the value of the one norm, or the frobenius norm distributed matrix sub( a ) = a(ia:ia+m-1, ja:ja+n-1). refered to as rowsums, and the column sums shown by | are refered to as colsums. infinity-norm = 1-norm = rowsums+colsums uplo = 'u' uplo = 'l' find maximum sum of columns for 1-norm refered to as rowsums, and the column sums shown by | are refered to as colsums. infinity-norm = 1-norm = rowsums+colsums uplo = 'u' uplo = 'l' find maximum sum of columns for 1-norm compute the 1-norm of each column, not including the diagonal pzpocon estimates the reciprocal of the condition number (in the 1-norm) of a complex hermitian positive definite distributed matri pzpotrf. sub( a ) = a(ia:ia+n-1,ja:ja+n-1) and reduce its condition number (with respect to the two-norm). sr and sc contain the scal buted matrix b with elements b(i,j) = s(i)*a(i,j)*s(j) has ones on the error bound depends on the quality of the estimate of norm(inv(a)) computed in the code; if the estimate o triangular distributed matrix a(ia:ia+n-1,ja:ja+n-1), in either the 1-norm or the infinity-norm the norm of a(ia:ia+n-1,ja:ja+n-1) is computed and an estimate is normalize and scale the righthand side vector pb set machine-dependent constants for the stopping criterion. if norm(h) <= sqrt(ovfl), overflow should not occur |
| norm1 norm1 ( ( norm1( sub( a ) ), norm = '1', 'o' or 'o ( normi( sub( a ) ), norm = 'i' or 'i' find normi( sub( a ) ) ( = norm1( sub( a ) ), since sub( a ) i find normi( sub( a ) ) ( = norm1( sub( a ) ), since sub( a ) i ( ( norm1( sub( a ) ), norm = '1', 'o' or 'o ( normi( sub( a ) ), norm = 'i' or 'i' find normi( sub( a ) ) ( = norm1( sub( a ) ), since sub( a ) i ( ( norm1( sub( a ) ), norm = '1', 'o' or 'o ( normi( sub( a ) ), norm = 'i' or 'i' find normi( sub( a ) ) ( = norm1( sub( a ) ), since sub( a ) i ( ( norm1( sub( a ) ), norm = '1', 'o' or 'o ( normi( sub( a ) ), norm = 'i' or 'i' find normi( sub( a ) ) ( = norm1( sub( a ) ), since sub( a ) i find normi( sub( a ) ) ( = norm1( sub( a ) ), since sub( a ) i |
| normal normal w (global output) real array, dimension (n) on normal exit, the first m entries contain the selecte w (global output) real array, dimension (n) on normal exit, the first m entries contain the selecte the distributed matrix z of eigenvectors. the eigenvectors are normalized as follows if ibtype = 3, z**h*inv( sub( b ) )*z = i. ifail (global output) integer array, dimension (m) on normal exit, all elements of ifail are zero iterations (as in cstein), then info > 0 is returned. ifail (global output) integer array, dimension (m) on normal exit, all elements of ifail are zero iterations (as in dstein), then info > 0 is returned. w (global output) double precision array, dimension (n) on normal exit, the first m entries contain the selecte w (global output) double precision array, dimension (n) on normal exit, the first m entries contain the selecte the distributed matrix z of eigenvectors. the eigenvectors are normalized as follows if ibtype = 3, z**t*inv( sub( b ) )*z = i. ifail (global output) integer array, dimension (m) on normal exit, all elements of ifail are zero iterations (as in sstein), then info > 0 is returned. w (global output) real array, dimension (n) on normal exit, the first m entries contain the selecte w (global output) real array, dimension (n) on normal exit, the first m entries contain the selecte the distributed matrix z of eigenvectors. the eigenvectors are normalized as follows if ibtype = 3, z**t*inv( sub( b ) )*z = i. w (global output) double precision array, dimension (n) on normal exit, the first m entries contain the selecte w (global output) double precision array, dimension (n) on normal exit, the first m entries contain the selecte the distributed matrix z of eigenvectors. the eigenvectors are normalized as follows if ibtype = 3, z**h*inv( sub( b ) )*z = i. ifail (global output) integer array, dimension (m) on normal exit, all elements of ifail are zero iterations (as in zstein), then info > 0 is returned. |
| Normalize Normalize Normalize and scale the righthand side vector pb Normalize and scale the righthand side vector pb |
| normalized normalized the distributed matrix z of eigenvectors. the eigenvectors are normalized as follows if ibtype = 3, z**h*inv( sub( b ) )*z = i. each eigenvector is normalized so that the element of larges (x,y) is taken to be |x| + |y|. the distributed matrix z of eigenvectors. the eigenvectors are normalized as follows if ibtype = 3, z**t*inv( sub( b ) )*z = i. the distributed matrix z of eigenvectors. the eigenvectors are normalized as follows if ibtype = 3, z**t*inv( sub( b ) )*z = i. the distributed matrix z of eigenvectors. the eigenvectors are normalized as follows if ibtype = 3, z**h*inv( sub( b ) )*z = i. each eigenvector is normalized so that the element of larges (x,y) is taken to be |x| + |y|. |
| normF normF ( ( normF( sub( a ) ), norm = 'f', 'f', 'e' or 'e where norm1 denotes the one norm of a matrix (maximum column sum), ( ( normF( sub( a ) ), norm = 'f', 'f', 'e' or 'e where norm1 denotes the one norm of a matrix (maximum column sum), ( ( normF( sub( a ) ), norm = 'f', 'f', 'e' or 'e where norm1 denotes the one norm of a matrix (maximum column sum), ( ( normF( sub( a ) ), norm = 'f', 'f', 'e' or 'e where norm1 denotes the one norm of a matrix (maximum column sum), |
| normI normI ( ( normI( sub( a ) ), norm = 'i' or 'i ( normf( sub( a ) ), norm = 'f', 'f', 'e' or 'e' find normI( sub( a ) ) ( = norm1( sub( a ) ), since sub( a ) i find normI( sub( a ) ) ( = norm1( sub( a ) ), since sub( a ) i ( ( normI( sub( a ) ), norm = 'i' or 'i ( normf( sub( a ) ), norm = 'f', 'f', 'e' or 'e' find normI( sub( a ) ) ( = norm1( sub( a ) ), since sub( a ) i ( ( normI( sub( a ) ), norm = 'i' or 'i ( normf( sub( a ) ), norm = 'f', 'f', 'e' or 'e' find normI( sub( a ) ) ( = norm1( sub( a ) ), since sub( a ) i ( ( normI( sub( a ) ), norm = 'i' or 'i ( normf( sub( a ) ), norm = 'f', 'f', 'e' or 'e' find normI( sub( a ) ) ( = norm1( sub( a ) ), since sub( a ) i find normI( sub( a ) ) ( = norm1( sub( a ) ), since sub( a ) i |
| norms norms scale the column norms by tscal if the maximum element in cnorm i scale the column norms by tscal if the maximum element in cnorm i |
| not not on entry, the matrix a in band storage, in rows kl+1 to 2*kl+ku+1; rows 1 to kl of the array need not be set array ab as follows: the block size must not exceed the limit set by the size of th set machine-dependent constants for the stopping criterion. if norm(h) <= sqrt(ovfl), overflow should not occur do not do a lookahead triangular matrix and the strictly lower triangular part of t is not referenced lower triangular part of the array t must contain the lower on entry, the matrix a in band storage, in rows kl+1 to 2*kl+ku+1; rows 1 to kl of the array need not be set array ab as follows: the block size must not exceed the limit set by the size of th eigenvalues and things couldn't be paired or if the input matrix s was not originally in schur form if stopping criterion was not satisfied, update info an triangular matrix and the strictly lower triangular part of t is not referenced lower triangular part of the array t must contain the lower this local portion is stored in the packed banded format used in lapack. please see the notes below and th distributed matrices. prepare output: set info = 0 if no error, and divide by descmult if error is not in a descriptor entry this local portion is stored in the packed banded format used in lapack. please see the notes below and th distributed matrices. these are alignment restrictions that may or may not be remove part of global vector storing the lower diagonal of the matrix. globally, dl(1) is not referenced, and dl must b must be of size >= desca( nb_ ). prepare output: set info = 0 if no error, and divide by descmult if error is not in a descriptor entry part of global vector storing the lower diagonal of the matrix. globally, dl(1) is not referenced, and dl must b must be of size >= desca( nb_ ). these are alignment restrictions that may or may not be remove this local portion is stored in the packed banded format used in lapack. please see the notes below and th distributed matrices. prepare output: set info = 0 if no error, and divide by descmult if error is not in a descriptor entry this local portion is stored in the packed banded format used in lapack. please see the notes below and th distributed matrices. note number and bignum = largest safe number. use of these scaling factors is not guaranteed to reduce the condition number o note note each global data object is described by an associated description note note note factorization computed by pcgetrf. this method inverts u and then computes the inverse of sub( a ) = a(ia:ia+n-1,ja:ja+n-1) denote factorization computed by pcgetrf. sub( a ) denotes a(ia:ia+n-1,ja:ja+n-1), op( a ) = a, a**t or a** note a description vector is associated with each 2d block-cyclicly dis- jobz (input) character*1 = 'n': compute eigenvalues only; (not implemented yet note in the following sub( a ) denotes a( ia:ia+n-1, ja:ja+n-1 ) an in the following sub( a ) denotes a( ia:ia+n-1, ja:ja+n-1 ) an sub( b )*sub( a )*x=(lambda)*x. here sub( a ) denoting a( ia:ia+n-1, ja:ja+n-1 ) is assumed to b to be hermitian positive definite. in the following sub( a ) denotes a( ia:ia+n-1, ja:ja+n-1 ) an note note note note pclacgv conjugates a complex vector of length n, sub( x ), where sub( x ) denotes x(ix,jx:jx+n-1) if incx = descx( m_ ) an note note pclacp2 copies all or part of a distributed matrix a to anothe performs a local copy sub( a ) := sub( b ), where sub( a ) denotes pclacpy copies all or part of a distributed matrix a to anothe performs a local copy sub( a ) := sub( b ), where sub( a ) denotes set machine-dependent constants for the stopping criterion. if norm(h) <= sqrt(ovfl), overflow should not occur i am not sure that this works correctly when ib and jb are not equa with 1 used in its place. where norm1 denotes the one norm of a matrix (maximum column sum) normf denotes the frobenius norm of a matrix (square root of sum of note note where tau is a complex scalar and v is a complex (n-1)-element vector. note that h is not hermitian if the elements of sub( x ) are all zero and x(iax,jax) is real, note 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. note pclascl multiplies the m-by-n complex distributed matrix sub( a ) denoting a(ia:ia+m-1,ja:ja+n-1) by the real scalar cto/cfrom. thi cto * a(i,j) / cfrom does not over/underflow. type specifies that pclase2 initializes an m-by-n distributed matrix sub( a ) denotin offdiagonals. pclase2 requires that only dimension of the matrix pclaset initializes an m-by-n distributed matrix sub( a ) denotin offdiagonals. note note compute the 1-norm of each column, not including the diagonal where sub( x ) denotes x(ix:ix+n-1,jx) if incx = 1 this local portion is stored in the packed banded format used in lapack. please see the notes below and th distributed matrices. prepare output: set info = 0 if no error, and divide by descmult if error is not in a descriptor entry this local portion is stored in the packed banded format used in lapack. please see the notes below and th distributed matrices. these are alignment restrictions that may or may not be remove note note where sub( a ) denotes a(ia:ia+n-1,ja:ja+n-1) and is an n-by- denoting b(ib:ib+n-1,jb:jb+nrhs-1) are n-by-nrhs distributed error bounds on the solution and a condition estimate are also provided. in the following comments y denotes y(iy:iy+m-1,jy:jy+k-1 note pcpotrf computes the cholesky factorization of an n-by-n complex hermitian positive definite distributed matrix sub( a ) denotin note part of global vector storing the upper diagonal of the matrix. globally, du(n) is not referenced, and du must b on exit, this array contains information containing the prepare output: set info = 0 if no error, and divide by descmult if error is not in a descriptor entry part of global vector storing the upper diagonal of the matrix. globally, du(n) is not referenced, and du must b on exit, this array contains information containing the these are alignment restrictions that may or may not be remove 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 in parallel, using inverse iteration. the eigenvectors found correspond to user specified eigenvalues. pcstein does not of orthogonalization is controlled by the input parameter lwork. note where y' denotes the conjugate transpose of the vector y if all eigenvectors are requested, the routine may either return the the solution matrix x must be computed by pctrtrs or some other means before entering this routine. pctrrfs does not do iterativ note note where sub( a ) denotes a(ia:ia+n-1,ja:ja+n-1) and is a triangula n-by-nrhs distributed matrix denoted by sub( b ). a check is made this local portion is stored in the packed banded format used in lapack. please see the notes below and th distributed matrices. prepare output: set info = 0 if no error, and divide by descmult if error is not in a descriptor entry this local portion is stored in the packed banded format used in lapack. please see the notes below and th distributed matrices. these are alignment restrictions that may or may not be remove part of global vector storing the lower diagonal of the matrix. globally, dl(1) is not referenced, and dl must b must be of size >= desca( nb_ ). prepare output: set info = 0 if no error, and divide by descmult if error is not in a descriptor entry part of global vector storing the lower diagonal of the matrix. globally, dl(1) is not referenced, and dl must b must be of size >= desca( nb_ ). these are alignment restrictions that may or may not be remove this local portion is stored in the packed banded format used in lapack. please see the notes below and th distributed matrices. prepare output: set info = 0 if no error, and divide by descmult if error is not in a descriptor entry this local portion is stored in the packed banded format used in lapack. please see the notes below and th distributed matrices. note number and bignum = largest safe number. use of these scaling factors is not guaranteed to reduce the condition number o note note each global data object is described by an associated description note note note factorization computed by pdgetrf. this method inverts u and then computes the inverse of sub( a ) = a(ia:ia+n-1,ja:ja+n-1) denote factorization computed by pdgetrf. sub( a ) denotes a(ia:ia+n-1,ja:ja+n-1), op( a ) = a or a**t an of the values computed by pdlamch. this subroutine is needed because pdlamch does not compensate for poor arithmetic in the upper half o note note pdlacp2 copies all or part of a distributed matrix a to anothe performs a local copy sub( a ) := sub( b ), where sub( a ) denotes pdlacpy copies all or part of a distributed matrix a to anothe performs a local copy sub( a ) := sub( b ), where sub( a ) denotes this is a scalapack internal subroutine and arguments are not i.e., on output, all intervals [ intvl(2*i-1), intvl(2*i) ], i < kf, have converged. note that the input intervals may be reordered b set machine-dependent constants for the stopping criterion. if norm(h) <= sqrt(ovfl), overflow should not occur eps = relative machine precision sfmin = safe minimum, such that 1/sfmin does not overflo prec = eps*base i am not sure that this works correctly when ib and jb are not equa with 1 used in its place. where norm1 denotes the one norm of a matrix (maximum column sum) normf denotes the frobenius norm of a matrix (square root of sum of this is a scalapack internal procedure and arguments are not checke note note note note note note pdlascl multiplies the m-by-n real distributed matrix sub( a ) denoting a(ia:ia+m-1,ja:ja+n-1) by the real scalar cto/cfrom. thi cto * a(i,j) / cfrom does not over/underflow. type specifies that pdlase2 initializes an m-by-n distributed matrix sub( a ) denotin offdiagonals. pdlase2 requires that only dimension of the matrix pdlaset initializes an m-by-n distributed matrix sub( a ) denotin offdiagonals. = 'i': sort d in increasing order; = 'd': sort d in decreasing order. (not implemented yet n (global input) integer note note this local portion is stored in the packed banded format used in lapack. please see the notes below and th distributed matrices. prepare output: set info = 0 if no error, and divide by descmult if error is not in a descriptor entry this local portion is stored in the packed banded format used in lapack. please see the notes below and th distributed matrices. these are alignment restrictions that may or may not be remove note note where sub( a ) denotes a(ia:ia+n-1,ja:ja+n-1) and is an n-by- denoting b(ib:ib+n-1,jb:jb+nrhs-1) are n-by-nrhs distributed error bounds on the solution and a condition estimate are also provided. in the following comments y denotes y(iy:iy+m-1,jy:jy+k-1 note pdpotrf computes the cholesky factorization of an n-by-n real symmetric positive definite distributed matrix sub( a ) denotin note part of global vector storing the upper diagonal of the matrix. globally, du(n) is not referenced, and du must b on exit, this array contains information containing the prepare output: set info = 0 if no error, and divide by descmult if error is not in a descriptor entry part of global vector storing the upper diagonal of the matrix. globally, du(n) is not referenced, and du must b on exit, this array contains information containing the these are alignment restrictions that may or may not be remove 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, note : it is assumed that the user is on an ieee machine. if the use to 1 (in slmake.inc). the features of ieee arithmetic that compz (input) character*1 = 'n': compute eigenvalues only. (not implemented yet = 'v': compute eigenvectors of original dense symmetric in parallel, using inverse iteration. the eigenvectors found correspond to user specified eigenvalues. pdstein does not of orthogonalization is controlled by the input parameter lwork. note a description vector is associated with each 2d block-cyclicly dis- jobz (input) character*1 = 'n': compute eigenvalues only; (not implemented yet note in the following sub( a ) denotes a( ia:ia+n-1, ja:ja+n-1 ) an in the following sub( a ) denotes a( ia:ia+n-1, ja:ja+n-1 ) an sub( b )*sub( a )*x=(lambda)*x. here sub( a ) denoting a( ia:ia+n-1, ja:ja+n-1 ) is assumed to b to be symmetric positive definite. in the following sub( a ) denotes a( ia:ia+n-1, ja:ja+n-1 ) an note note note note note the solution matrix x must be computed by pdtrtrs or some other means before entering this routine. pdtrrfs does not do iterativ note note where sub( a ) denotes a(ia:ia+n-1,ja:ja+n-1) and is a triangula n-by-nrhs distributed matrix denoted by sub( b ). a check is made this version provides a set of parameters which should give good, but not optimal, performance on many of the currently availabl the tuning parameters for their particular machine using the option this local portion is stored in the packed banded format used in lapack. please see the notes below and th distributed matrices. prepare output: set info = 0 if no error, and divide by descmult if error is not in a descriptor entry this local portion is stored in the packed banded format used in lapack. please see the notes below and th distributed matrices. these are alignment restrictions that may or may not be remove part of global vector storing the lower diagonal of the matrix. globally, dl(1) is not referenced, and dl must b must be of size >= desca( nb_ ). prepare output: set info = 0 if no error, and divide by descmult if error is not in a descriptor entry part of global vector storing the lower diagonal of the matrix. globally, dl(1) is not referenced, and dl must b must be of size >= desca( nb_ ). these are alignment restrictions that may or may not be remove this local portion is stored in the packed banded format used in lapack. please see the notes below and th distributed matrices. prepare output: set info = 0 if no error, and divide by descmult if error is not in a descriptor entry this local portion is stored in the packed banded format used in lapack. please see the notes below and th distributed matrices. note number and bignum = largest safe number. use of these scaling factors is not guaranteed to reduce the condition number o note note each global data object is described by an associated description note note note factorization computed by psgetrf. this method inverts u and then computes the inverse of sub( a ) = a(ia:ia+n-1,ja:ja+n-1) denote factorization computed by psgetrf. sub( a ) denotes a(ia:ia+n-1,ja:ja+n-1), op( a ) = a or a**t an of the values computed by pslamch. this subroutine is needed because pslamch does not compensate for poor arithmetic in the upper half o note note pslacp2 copies all or part of a distributed matrix a to anothe performs a local copy sub( a ) := sub( b ), where sub( a ) denotes pslacpy copies all or part of a distributed matrix a to anothe performs a local copy sub( a ) := sub( b ), where sub( a ) denotes this is a scalapack internal subroutine and arguments are not i.e., on output, all intervals [ intvl(2*i-1), intvl(2*i) ], i < kf, have converged. note that the input intervals may be reordered b set machine-dependent constants for the stopping criterion. if norm(h) <= sqrt(ovfl), overflow should not occur eps = relative machine precision sfmin = safe minimum, such that 1/sfmin does not overflo prec = eps*base i am not sure that this works correctly when ib and jb are not equa with 1 used in its place. where norm1 denotes the one norm of a matrix (maximum column sum) normf denotes the frobenius norm of a matrix (square root of sum of this is a scalapack internal procedure and arguments are not checke note note note note note note pslascl multiplies the m-by-n real distributed matrix sub( a ) denoting a(ia:ia+m-1,ja:ja+n-1) by the real scalar cto/cfrom. thi cto * a(i,j) / cfrom does not over/underflow. type specifies that pslase2 initializes an m-by-n distributed matrix sub( a ) denotin offdiagonals. pslase2 requires that only dimension of the matrix pslaset initializes an m-by-n distributed matrix sub( a ) denotin offdiagonals. = 'i': sort d in increasing order; = 'd': sort d in decreasing order. (not implemented yet n (global input) integer note note this local portion is stored in the packed banded format used in lapack. please see the notes below and th distributed matrices. prepare output: set info = 0 if no error, and divide by descmult if error is not in a descriptor entry this local portion is stored in the packed banded format used in lapack. please see the notes below and th distributed matrices. these are alignment restrictions that may or may not be remove note note where sub( a ) denotes a(ia:ia+n-1,ja:ja+n-1) and is an n-by- denoting b(ib:ib+n-1,jb:jb+nrhs-1) are n-by-nrhs distributed error bounds on the solution and a condition estimate are also provided. in the following comments y denotes y(iy:iy+m-1,jy:jy+k-1 note pspotrf computes the cholesky factorization of an n-by-n real symmetric positive definite distributed matrix sub( a ) denotin note part of global vector storing the upper diagonal of the matrix. globally, du(n) is not referenced, and du must b on exit, this array contains information containing the prepare output: set info = 0 if no error, and divide by descmult if error is not in a descriptor entry part of global vector storing the upper diagonal of the matrix. globally, du(n) is not referenced, and du must b on exit, this array contains information containing the these are alignment restrictions that may or may not be remove 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, note : it is assumed that the user is on an ieee machine. if the use to 1 (in slmake.inc). the features of ieee arithmetic that compz (input) character*1 = 'n': compute eigenvalues only. (not implemented yet = 'v': compute eigenvectors of original dense symmetric in parallel, using inverse iteration. the eigenvectors found correspond to user specified eigenvalues. psstein does not of orthogonalization is controlled by the input parameter lwork. note a description vector is associated with each 2d block-cyclicly dis- jobz (input) character*1 = 'n': compute eigenvalues only; (not implemented yet note in the following sub( a ) denotes a( ia:ia+n-1, ja:ja+n-1 ) an in the following sub( a ) denotes a( ia:ia+n-1, ja:ja+n-1 ) an sub( b )*sub( a )*x=(lambda)*x. here sub( a ) denoting a( ia:ia+n-1, ja:ja+n-1 ) is assumed to b to be symmetric positive definite. in the following sub( a ) denotes a( ia:ia+n-1, ja:ja+n-1 ) an note note note note note the solution matrix x must be computed by pstrtrs or some other means before entering this routine. pstrrfs does not do iterativ note note where sub( a ) denotes a(ia:ia+n-1,ja:ja+n-1) and is a triangula n-by-nrhs distributed matrix denoted by sub( b ). a check is made this local portion is stored in the packed banded format used in lapack. please see the notes below and th distributed matrices. prepare output: set info = 0 if no error, and divide by descmult if error is not in a descriptor entry this local portion is stored in the packed banded format used in lapack. please see the notes below and th distributed matrices. these are alignment restrictions that may or may not be remove 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 part of global vector storing the lower diagonal of the matrix. globally, dl(1) is not referenced, and dl must b must be of size >= desca( nb_ ). prepare output: set info = 0 if no error, and divide by descmult if error is not in a descriptor entry part of global vector storing the lower diagonal of the matrix. globally, dl(1) is not referenced, and dl must b must be of size >= desca( nb_ ). these are alignment restrictions that may or may not be remove this local portion is stored in the packed banded format used in lapack. please see the notes below and th distributed matrices. prepare output: set info = 0 if no error, and divide by descmult if error is not in a descriptor entry this local portion is stored in the packed banded format used in lapack. please see the notes below and th distributed matrices. note number and bignum = largest safe number. use of these scaling factors is not guaranteed to reduce the condition number o note note each global data object is described by an associated description note note note factorization computed by pzgetrf. this method inverts u and then computes the inverse of sub( a ) = a(ia:ia+n-1,ja:ja+n-1) denote factorization computed by pzgetrf. sub( a ) denotes a(ia:ia+n-1,ja:ja+n-1), op( a ) = a, a**t or a** note a description vector is associated with each 2d block-cyclicly dis- jobz (input) character*1 = 'n': compute eigenvalues only; (not implemented yet note in the following sub( a ) denotes a( ia:ia+n-1, ja:ja+n-1 ) an in the following sub( a ) denotes a( ia:ia+n-1, ja:ja+n-1 ) an sub( b )*sub( a )*x=(lambda)*x. here sub( a ) denoting a( ia:ia+n-1, ja:ja+n-1 ) is assumed to b to be hermitian positive definite. in the following sub( a ) denotes a( ia:ia+n-1, ja:ja+n-1 ) an note note note note pzlacgv conjugates a complex vector of length n, sub( x ), where sub( x ) denotes x(ix,jx:jx+n-1) if incx = descx( m_ ) an note note pzlacp2 copies all or part of a distributed matrix a to anothe performs a local copy sub( a ) := sub( b ), where sub( a ) denotes pzlacpy copies all or part of a distributed matrix a to anothe performs a local copy sub( a ) := sub( b ), where sub( a ) denotes set machine-dependent constants for the stopping criterion. if norm(h) <= sqrt(ovfl), overflow should not occur i am not sure that this works correctly when ib and jb are not equa with 1 used in its place. where norm1 denotes the one norm of a matrix (maximum column sum) normf denotes the frobenius norm of a matrix (square root of sum of note note where tau is a complex scalar and v is a complex (n-1)-element vector. note that h is not hermitian if the elements of sub( x ) are all zero and x(iax,jax) is real, note 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. note pzlascl multiplies the m-by-n complex distributed matrix sub( a ) denoting a(ia:ia+m-1,ja:ja+n-1) by the real scalar cto/cfrom. thi cto * a(i,j) / cfrom does not over/underflow. type specifies that pzlase2 initializes an m-by-n distributed matrix sub( a ) denotin offdiagonals. pzlase2 requires that only dimension of the matrix pzlaset initializes an m-by-n distributed matrix sub( a ) denotin offdiagonals. note note compute the 1-norm of each column, not including the diagonal where sub( x ) denotes x(ix:ix+n-1,jx) if incx = 1 this local portion is stored in the packed banded format used in lapack. please see the notes below and th distributed matrices. prepare output: set info = 0 if no error, and divide by descmult if error is not in a descriptor entry this local portion is stored in the packed banded format used in lapack. please see the notes below and th distributed matrices. these are alignment restrictions that may or may not be remove note note where sub( a ) denotes a(ia:ia+n-1,ja:ja+n-1) and is an n-by- denoting b(ib:ib+n-1,jb:jb+nrhs-1) are n-by-nrhs distributed error bounds on the solution and a condition estimate are also provided. in the following comments y denotes y(iy:iy+m-1,jy:jy+k-1 note pzpotrf computes the cholesky factorization of an n-by-n complex hermitian positive definite distributed matrix sub( a ) denotin note part of global vector storing the upper diagonal of the matrix. globally, du(n) is not referenced, and du must b on exit, this array contains information containing the prepare output: set info = 0 if no error, and divide by descmult if error is not in a descriptor entry part of global vector storing the upper diagonal of the matrix. globally, du(n) is not referenced, and du must b on exit, this array contains information containing the these are alignment restrictions that may or may not be remove in parallel, using inverse iteration. the eigenvectors found correspond to user specified eigenvalues. pzstein does not of orthogonalization is controlled by the input parameter lwork. note where y' denotes the conjugate transpose of the vector y if all eigenvectors are requested, the routine may either return the the solution matrix x must be computed by pztrtrs or some other means before entering this routine. pztrrfs does not do iterativ note note where sub( a ) denotes a(ia:ia+n-1,ja:ja+n-1) and is a triangula n-by-nrhs distributed matrix denoted by sub( b ). a check is made on entry, the matrix a in band storage, in rows kl+1 to 2*kl+ku+1; rows 1 to kl of the array need not be set array ab as follows: the block size must not exceed the limit set by the size of th eigenvalues and things couldn't be paired or if the input matrix s was not originally in schur form if stopping criterion was not satisfied, update info an triangular matrix and the strictly lower triangular part of t is not referenced lower triangular part of the array t must contain the lower on entry, the matrix a in band storage, in rows kl+1 to 2*kl+ku+1; rows 1 to kl of the array need not be set array ab as follows: the block size must not exceed the limit set by the size of th set machine-dependent constants for the stopping criterion. if norm(h) <= sqrt(ovfl), overflow should not occur do not do a lookahead triangular matrix and the strictly lower triangular part of t is not referenced lower triangular part of the array t must contain the lower |
| NOTATION NOTATION NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_) the descriptor type. NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dt_a (global) desca[ dt_ ] the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dt_a (global) desca[ dt_ ] the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_) the descriptor type. NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dt_a (global) desca[ dt_ ] the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_) the descriptor type. NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dt_a (global) desca[ dt_ ] the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_) the descriptor type. NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, NOTATION stored in explanatio dtype_a(global) desca( dtype_ )the descriptor type. in this case, |
| Note Note this local portion is stored in the packed banded format used in lapack. please see the Notes below and th distributed matrices. calculate off-diagonal block(s) of reduced system. Note: for ease of use in solution of reduced system, stor this local portion is stored in the packed banded format used in lapack. please see the Notes below and th distributed matrices. contains information of mapping of a to memory. please see Notes below for full description and options b (local input/local output) complex pointer into calculate off-diagonal block(s) of reduced system. Note: for ease of use in solution of reduced system, stor contains information of mapping of a to memory. please see Notes below for full description and options b (local input/local output) complex pointer into this local portion is stored in the packed banded format used in lapack. please see the Notes below and th distributed matrices. lbwl, lbwu: lower and upper bandwidth of local solver Note that for mycol > 0 one has lower triangular blocks mycol = 0 where it is bwu less and mycol=npcol-1 where it this local portion is stored in the packed banded format used in lapack. please see the Notes below and th distributed matrices. Note siam j. sci. comput., 6:20 (1999), pp. 2223--2236. (see also lapack working Note 132 Note Note Note where norm1 deNotes the one norm of a matrix (maximum column sum) normf denotes the frobenius norm of a matrix (square root of sum of where tau is a complex scalar and v is a complex (n-1)-element vector. Note that h is not hermitian if the elements of sub( x ) are all zero and x(iax,jax) is real, already been broadcast along the process row or column. also Note that this routine will only work for k1-k2 being in th pclapiv. where sub( x ) deNotes x(ix:ix+n-1,jx) if incx = 1 this local portion is stored in the packed banded format used in lapack. please see the Notes below and th distributed matrices. calculate off-diagonal block(s) of reduced system.
Note: for ease of use in solution of reduced system, stor
{f_i}^c = {h_i}{{b'}_i}^c
this local portion is stored in the packed banded format used in lapack. please see the Notes below and th distributed matrices. error bounds on the solution and a condition estimate are also provided. in the following comments y deNotes y(iy:iy+m-1,jy:jy+k-1 contains information of mapping of a to memory. please see Notes below for full description and options b (local input/local output) complex pointer into calculate off-diagonal block(s) of reduced system.
Note: for ease of use in solution of reduced system, stor
{f_i}^c = {h_i}{{b'}_i}^c
contains information of mapping of a to memory. please see Notes below for full description and options b (local input/local output) complex pointer into Note : if the eigenvectors obtained are not orthogonal, increas this local portion is stored in the packed banded format used in lapack. please see the Notes below and th distributed matrices. calculate off-diagonal block(s) of reduced system. Note: for ease of use in solution of reduced system, stor this local portion is stored in the packed banded format used in lapack. please see the Notes below and th distributed matrices. contains information of mapping of a to memory. please see Notes below for full description and options b (local input/local output) double precision pointer into calculate off-diagonal block(s) of reduced system. Note: for ease of use in solution of reduced system, stor contains information of mapping of a to memory. please see Notes below for full description and options b (local input/local output) double precision pointer into this local portion is stored in the packed banded format used in lapack. please see the Notes below and th distributed matrices. lbwl, lbwu: lower and upper bandwidth of local solver Note that for mycol > 0 one has lower triangular blocks mycol = 0 where it is bwu less and mycol=npcol-1 where it this local portion is stored in the packed banded format used in lapack. please see the Notes below and th distributed matrices. Note small, i.e., converged. Note : this should be at least radix*machine epsilon pivmin (input) double precision i.e., on output, all intervals [ intvl(2*i-1), intvl(2*i) ], i < kf, have converged. Note that the input intervals may be reordered b where norm1 deNotes the one norm of a matrix (maximum column sum) normf denotes the frobenius norm of a matrix (square root of sum of already been broadcast along the process row or column. also Note that this routine will only work for k1-k2 being in th pdlapiv. this local portion is stored in the packed banded format used in lapack. please see the Notes below and th distributed matrices. calculate off-diagonal block(s) of reduced system.
Note: for ease of use in solution of reduced system, stor
{f_i}^t = {h_i}{{b'}_i}^t
this local portion is stored in the packed banded format used in lapack. please see the Notes below and th distributed matrices. error bounds on the solution and a condition estimate are also provided. in the following comments y deNotes y(iy:iy+m-1,jy:jy+k-1 contains information of mapping of a to memory. please see Notes below for full description and options b (local input/local output) double precision pointer into calculate off-diagonal block(s) of reduced system.
Note: for ease of use in solution of reduced system, stor
{f_i}^t = {h_i}{{b'}_i}^t
contains information of mapping of a to memory. please see Notes below for full description and options b (local input/local output) double precision pointer into Note : it is assumed that the user is on an ieee machine. if the use to 1 (in slmake.inc). the features of ieee arithmetic that siam j. sci. comput., 6:20 (1999), pp. 2223--2236. (see also lapack working Note 132 Note : if the eigenvectors obtained are not orthogonal, increas siam j. sci. comput., 6:20 (1999), pp. 2223--2236. (see also lapack working Note 132 Note Note Note where sub( x ) deNotes x(ix:ix+n-1,jx:jx), if incx = 1 where sub( x ) deNotes x(ix:ix+n-1,jx:jx), if incx = 1 this local portion is stored in the packed banded format used in lapack. please see the Notes below and th distributed matrices. calculate off-diagonal block(s) of reduced system. Note: for ease of use in solution of reduced system, stor this local portion is stored in the packed banded format used in lapack. please see the Notes below and th distributed matrices. contains information of mapping of a to memory. please see Notes below for full description and options b (local input/local output) real pointer into calculate off-diagonal block(s) of reduced system. Note: for ease of use in solution of reduced system, stor contains information of mapping of a to memory. please see Notes below for full description and options b (local input/local output) real pointer into this local portion is stored in the packed banded format used in lapack. please see the Notes below and th distributed matrices. lbwl, lbwu: lower and upper bandwidth of local solver Note that for mycol > 0 one has lower triangular blocks mycol = 0 where it is bwu less and mycol=npcol-1 where it this local portion is stored in the packed banded format used in lapack. please see the Notes below and th distributed matrices. Note small, i.e., converged. Note : this should be at least radix*machine epsilon pivmin (input) real i.e., on output, all intervals [ intvl(2*i-1), intvl(2*i) ], i < kf, have converged. Note that the input intervals may be reordered b where norm1 deNotes the one norm of a matrix (maximum column sum) normf denotes the frobenius norm of a matrix (square root of sum of already been broadcast along the process row or column. also Note that this routine will only work for k1-k2 being in th pslapiv. this local portion is stored in the packed banded format used in lapack. please see the Notes below and th distributed matrices. calculate off-diagonal block(s) of reduced system.
Note: for ease of use in solution of reduced system, stor
{f_i}^t = {h_i}{{b'}_i}^t
this local portion is stored in the packed banded format used in lapack. please see the Notes below and th distributed matrices. error bounds on the solution and a condition estimate are also provided. in the following comments y deNotes y(iy:iy+m-1,jy:jy+k-1 contains information of mapping of a to memory. please see Notes below for full description and options b (local input/local output) real pointer into calculate off-diagonal block(s) of reduced system.
Note: for ease of use in solution of reduced system, stor
{f_i}^t = {h_i}{{b'}_i}^t
contains information of mapping of a to memory. please see Notes below for full description and options b (local input/local output) real pointer into Note : it is assumed that the user is on an ieee machine. if the use to 1 (in slmake.inc). the features of ieee arithmetic that siam j. sci. comput., 6:20 (1999), pp. 2223--2236. (see also lapack working Note 132 Note : if the eigenvectors obtained are not orthogonal, increas siam j. sci. comput., 6:20 (1999), pp. 2223--2236. (see also lapack working Note 132 Note Note Note this local portion is stored in the packed banded format used in lapack. please see the Notes below and th distributed matrices. calculate off-diagonal block(s) of reduced system. Note: for ease of use in solution of reduced system, stor this local portion is stored in the packed banded format used in lapack. please see the Notes below and th distributed matrices. contains information of mapping of a to memory. please see Notes below for full description and options b (local input/local output) complex*16 pointer into calculate off-diagonal block(s) of reduced system. Note: for ease of use in solution of reduced system, stor contains information of mapping of a to memory. please see Notes below for full description and options b (local input/local output) complex*16 pointer into this local portion is stored in the packed banded format used in lapack. please see the Notes below and th distributed matrices. lbwl, lbwu: lower and upper bandwidth of local solver Note that for mycol > 0 one has lower triangular blocks mycol = 0 where it is bwu less and mycol=npcol-1 where it this local portion is stored in the packed banded format used in lapack. please see the Notes below and th distributed matrices. Note siam j. sci. comput., 6:20 (1999), pp. 2223--2236. (see also lapack working Note 132 Note Note Note where norm1 deNotes the one norm of a matrix (maximum column sum) normf denotes the frobenius norm of a matrix (square root of sum of where tau is a complex scalar and v is a complex (n-1)-element vector. Note that h is not hermitian if the elements of sub( x ) are all zero and x(iax,jax) is real, already been broadcast along the process row or column. also Note that this routine will only work for k1-k2 being in th pzlapiv. where sub( x ) deNotes x(ix:ix+n-1,jx) if incx = 1 this local portion is stored in the packed banded format used in lapack. please see the Notes below and th distributed matrices. calculate off-diagonal block(s) of reduced system.
Note: for ease of use in solution of reduced system, stor
{f_i}^c = {h_i}{{b'}_i}^c
this local portion is stored in the packed banded format used in lapack. please see the Notes below and th distributed matrices. error bounds on the solution and a condition estimate are also provided. in the following comments y deNotes y(iy:iy+m-1,jy:jy+k-1 contains information of mapping of a to memory. please see Notes below for full description and options b (local input/local output) complex*16 pointer into calculate off-diagonal block(s) of reduced system.
Note: for ease of use in solution of reduced system, stor
{f_i}^c = {h_i}{{b'}_i}^c
contains information of mapping of a to memory. please see Notes below for full description and options b (local input/local output) complex*16 pointer into Note : if the eigenvectors obtained are not orthogonal, increas |
| noted noted to opposite requirements for the orientation of the blacs grid, and as noted before, the *same* blacs context must be used i to opposite requirements for the orientation of the blacs grid, and as noted before, the *same* blacs context must be used i to opposite requirements for the orientation of the blacs grid, and as noted before, the *same* blacs context must be used i to opposite requirements for the orientation of the blacs grid, and as noted before, the *same* blacs context must be used i to opposite requirements for the orientation of the blacs grid, and as noted before, the *same* blacs context must be used i to opposite requirements for the orientation of the blacs grid, and as noted before, the *same* blacs context must be used i to opposite requirements for the orientation of the blacs grid, and as noted before, the *same* blacs context must be used i to opposite requirements for the orientation of the blacs grid, and as noted before, the *same* blacs context must be used i to opposite requirements for the orientation of the blacs grid, and as noted before, the *same* blacs context must be used i to opposite requirements for the orientation of the blacs grid, and as noted before, the *same* blacs context must be used i to opposite requirements for the orientation of the blacs grid, and as noted before, the *same* blacs context must be used i to opposite requirements for the orientation of the blacs grid, and as noted before, the *same* blacs context must be used i to opposite requirements for the orientation of the blacs grid, and as noted before, the *same* blacs context must be used i to opposite requirements for the orientation of the blacs grid, and as noted before, the *same* blacs context must be used i to opposite requirements for the orientation of the blacs grid, and as noted before, the *same* blacs context must be used i to opposite requirements for the orientation of the blacs grid, and as noted before, the *same* blacs context must be used i to opposite requirements for the orientation of the blacs grid, and as noted before, the *same* blacs context must be used i to opposite requirements for the orientation of the blacs grid, and as noted before, the *same* blacs context must be used i to opposite requirements for the orientation of the blacs grid, and as noted before, the *same* blacs context must be used i to opposite requirements for the orientation of the blacs grid, and as noted before, the *same* blacs context must be used i to opposite requirements for the orientation of the blacs grid, and as noted before, the *same* blacs context must be used i to opposite requirements for the orientation of the blacs grid, and as noted before, the *same* blacs context must be used i to opposite requirements for the orientation of the blacs grid, and as noted before, the *same* blacs context must be used i to opposite requirements for the orientation of the blacs grid, and as noted before, the *same* blacs context must be used i to opposite requirements for the orientation of the blacs grid, and as noted before, the *same* blacs context must be used i to opposite requirements for the orientation of the blacs grid, and as noted before, the *same* blacs context must be used i to opposite requirements for the orientation of the blacs grid, and as noted before, the *same* blacs context must be used i to opposite requirements for the orientation of the blacs grid, and as noted before, the *same* blacs context must be used i to opposite requirements for the orientation of the blacs grid, and as noted before, the *same* blacs context must be used i to opposite requirements for the orientation of the blacs grid, and as noted before, the *same* blacs context must be used i to opposite requirements for the orientation of the blacs grid, and as noted before, the *same* blacs context must be used i to opposite requirements for the orientation of the blacs grid, and as noted before, the *same* blacs context must be used i to opposite requirements for the orientation of the blacs grid, and as noted before, the *same* blacs context must be used i to opposite requirements for the orientation of the blacs grid, and as noted before, the *same* blacs context must be used i to opposite requirements for the orientation of the blacs grid, and as noted before, the *same* blacs context must be used i to opposite requirements for the orientation of the blacs grid, and as noted before, the *same* blacs context must be used i to opposite requirements for the orientation of the blacs grid, and as noted before, the *same* blacs context must be used i to opposite requirements for the orientation of the blacs grid, and as noted before, the *same* blacs context must be used i to opposite requirements for the orientation of the blacs grid, and as noted before, the *same* blacs context must be used i to opposite requirements for the orientation of the blacs grid, and as noted before, the *same* blacs context must be used i |
| Notes Notes 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. contains information of mapping of a to memory. please see Notes below for full description and options b (local input/local output) complex pointer into contains information of mapping of a to memory. please see Notes below for full description and options b (local input/local output) complex pointer into 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. Notes Notes Notes Notes Notes Notes Notes Notes where sub( b ) deNotes b( ib:ib+m-1, jb:jb+nrhs-1 ) when trans = 'n vectors b and solution vectors x can be handled in a single call; Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes each global data object is described by an associated description Notes Notes Notes Notes factorization computed by pcgetrf. sub( a ) deNotes a(ia:ia+n-1,ja:ja+n-1), op( a ) = a, a**t or a** where inv( sub( b ) ) deNotes the inverse of the matrix sub( b ) where inv( sub( b ) ) deNotes the inverse of the matrix sub( b ) Notes a description vector is associated with each 2d block-cyclicly dis- Notes in the following sub( a ) deNotes a( ia:ia+n-1, ja:ja+n-1 ) an in the following sub( a ) deNotes a( ia:ia+n-1, ja:ja+n-1 ) an Notes in the following sub( a ) deNotes a( ia:ia+n-1, ja:ja+n-1 ) an Notes Notes Notes Notes Notes pclacgv conjugates a complex vector of length n, sub( x ), where sub( x ) deNotes x(ix,jx:jx+n-1) if incx = descx( m_ ) an Notes Notes distributed matrix b. no communication is performed, pclacp2 performs a local copy sub( a ) := sub( b ), where sub( a ) deNotes pclacp2 requires that only dimension of the matrix operands is Notes distributed matrix b. no communication is performed, pclacpy performs a local copy sub( a ) := sub( b ), where sub( a ) deNotes Notes Notes where norm1 deNotes the one norm of a matrix (maximum column sum) normf denotes the frobenius norm of a matrix (square root of sum of Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes where sub( x ) deNotes x(ix:ix+n-1,jx) if incx = 1 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. Notes Notes Notes where sub( a ) deNotes a(ia:ia+n-1,ja:ja+n-1) and is an n-by- denoting b(ib:ib+n-1,jb:jb+nrhs-1) are n-by-nrhs distributed error bounds on the solution and a condition estimate are also provided. in the following comments y deNotes y(iy:iy+m-1,jy:jy+k-1 Notes Notes Notes where sub( a ) deNotes a(ia:ia+n-1,ja:ja+n-1) and is a n-by- factorization sub( a ) = u**h*u or l*l**h computed by pcpotrf. contains information of mapping of a to memory. please see Notes below for full description and options b (local input/local output) complex pointer into contains information of mapping of a to memory. please see Notes below for full description and options b (local input/local output) complex pointer into where sub( x ) deNotes x(ix:ix+n-1,jx:jx), if incx = 1 Notes Notes where y' deNotes the conjugate transpose of the vector y if all eigenvectors are requested, the routine may either return the Notes Notes Notes where sub( a ) deNotes a(ia:ia+n-1,ja:ja+n-1) and is a triangula n-by-nrhs distributed matrix denoted by sub( b ). a check is made Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes 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. contains information of mapping of a to memory. please see Notes below for full description and options b (local input/local output) double precision pointer into contains information of mapping of a to memory. please see Notes below for full description and options b (local input/local output) double precision pointer into 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. Notes Notes Notes Notes Notes Notes Notes Notes where sub( b ) deNotes b( ib:ib+m-1, jb:jb+nrhs-1 ) when trans = 'n vectors b and solution vectors x can be handled in a single call; Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes each global data object is described by an associated description Notes Notes Notes Notes factorization computed by pdgetrf. sub( a ) deNotes a(ia:ia+n-1,ja:ja+n-1), op( a ) = a or a**t an where inv( sub( b ) ) deNotes the inverse of the matrix sub( b ) where inv( sub( b ) ) deNotes the inverse of the matrix sub( b ) Notes Notes Notes distributed matrix b. no communication is performed, pdlacp2 performs a local copy sub( a ) := sub( b ), where sub( a ) deNotes pdlacp2 requires that only dimension of the matrix operands is Notes distributed matrix b. no communication is performed, pdlacpy performs a local copy sub( a ) := sub( b ), where sub( a ) deNotes Notes Notes where norm1 deNotes the one norm of a matrix (maximum column sum) normf denotes the frobenius norm of a matrix (square root of sum of Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes 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. Notes Notes Notes where sub( a ) deNotes a(ia:ia+n-1,ja:ja+n-1) and is an n-by- denoting b(ib:ib+n-1,jb:jb+nrhs-1) are n-by-nrhs distributed error bounds on the solution and a condition estimate are also provided. in the following comments y deNotes y(iy:iy+m-1,jy:jy+k-1 Notes Notes Notes where sub( a ) deNotes a(ia:ia+n-1,ja:ja+n-1) and is a n-by- factorization sub( a ) = u**t*u or l*l**t computed by pdpotrf. contains information of mapping of a to memory. please see Notes below for full description and options b (local input/local output) double precision pointer into contains information of mapping of a to memory. please see Notes below for full description and options b (local input/local output) double precision pointer into where sub( x ) deNotes x(ix:ix+n-1,jx:jx), if incx = 1 Notes Notes a description vector is associated with each 2d block-cyclicly dis- Notes in the following sub( a ) deNotes a( ia:ia+n-1, ja:ja+n-1 ) an in the following sub( a ) deNotes a( ia:ia+n-1, ja:ja+n-1 ) an Notes in the following sub( a ) deNotes a( ia:ia+n-1, ja:ja+n-1 ) an Notes Notes Notes Notes Notes Notes Notes Notes where sub( a ) deNotes a(ia:ia+n-1,ja:ja+n-1) and is a triangula n-by-nrhs distributed matrix denoted by sub( b ). a check is made Notes where sub( x ) deNotes x(ix:ix+n-1,jx:jx), if incx = 1 where sub( x ) deNotes x(ix:ix+n-1,jx:jx), if incx = 1 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. contains information of mapping of a to memory. please see Notes below for full description and options b (local input/local output) real pointer into contains information of mapping of a to memory. please see Notes below for full description and options b (local input/local output) real pointer into 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. Notes Notes Notes Notes Notes Notes Notes Notes where sub( b ) deNotes b( ib:ib+m-1, jb:jb+nrhs-1 ) when trans = 'n vectors b and solution vectors x can be handled in a single call; Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes each global data object is described by an associated description Notes Notes Notes Notes factorization computed by psgetrf. sub( a ) deNotes a(ia:ia+n-1,ja:ja+n-1), op( a ) = a or a**t an where inv( sub( b ) ) deNotes the inverse of the matrix sub( b ) where inv( sub( b ) ) deNotes the inverse of the matrix sub( b ) Notes Notes Notes distributed matrix b. no communication is performed, pslacp2 performs a local copy sub( a ) := sub( b ), where sub( a ) deNotes pslacp2 requires that only dimension of the matrix operands is Notes distributed matrix b. no communication is performed, pslacpy performs a local copy sub( a ) := sub( b ), where sub( a ) deNotes Notes Notes where norm1 deNotes the one norm of a matrix (maximum column sum) normf denotes the frobenius norm of a matrix (square root of sum of Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes 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. Notes Notes Notes where sub( a ) deNotes a(ia:ia+n-1,ja:ja+n-1) and is an n-by- denoting b(ib:ib+n-1,jb:jb+nrhs-1) are n-by-nrhs distributed error bounds on the solution and a condition estimate are also provided. in the following comments y deNotes y(iy:iy+m-1,jy:jy+k-1 Notes Notes Notes where sub( a ) deNotes a(ia:ia+n-1,ja:ja+n-1) and is a n-by- factorization sub( a ) = u**t*u or l*l**t computed by pspotrf. contains information of mapping of a to memory. please see Notes below for full description and options b (local input/local output) real pointer into contains information of mapping of a to memory. please see Notes below for full description and options b (local input/local output) real pointer into where sub( x ) deNotes x(ix:ix+n-1,jx:jx), if incx = 1 Notes Notes a description vector is associated with each 2d block-cyclicly dis- Notes in the following sub( a ) deNotes a( ia:ia+n-1, ja:ja+n-1 ) an in the following sub( a ) deNotes a( ia:ia+n-1, ja:ja+n-1 ) an Notes in the following sub( a ) deNotes a( ia:ia+n-1, ja:ja+n-1 ) an Notes Notes Notes Notes Notes Notes Notes Notes where sub( a ) deNotes a(ia:ia+n-1,ja:ja+n-1) and is a triangula n-by-nrhs distributed matrix denoted by sub( b ). a check is made Notes 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. where sub( x ) deNotes x(ix:ix+n-1,jx:jx), if incx = 1 contains information of mapping of a to memory. please see Notes below for full description and options b (local input/local output) complex*16 pointer into contains information of mapping of a to memory. please see Notes below for full description and options b (local input/local output) complex*16 pointer into 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. Notes Notes Notes Notes Notes Notes Notes Notes where sub( b ) deNotes b( ib:ib+m-1, jb:jb+nrhs-1 ) when trans = 'n vectors b and solution vectors x can be handled in a single call; Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes each global data object is described by an associated description Notes Notes Notes Notes factorization computed by pzgetrf. sub( a ) deNotes a(ia:ia+n-1,ja:ja+n-1), op( a ) = a, a**t or a** where inv( sub( b ) ) deNotes the inverse of the matrix sub( b ) where inv( sub( b ) ) deNotes the inverse of the matrix sub( b ) Notes a description vector is associated with each 2d block-cyclicly dis- Notes in the following sub( a ) deNotes a( ia:ia+n-1, ja:ja+n-1 ) an in the following sub( a ) deNotes a( ia:ia+n-1, ja:ja+n-1 ) an Notes in the following sub( a ) deNotes a( ia:ia+n-1, ja:ja+n-1 ) an Notes Notes Notes Notes Notes pzlacgv conjugates a complex vector of length n, sub( x ), where sub( x ) deNotes x(ix,jx:jx+n-1) if incx = descx( m_ ) an Notes Notes distributed matrix b. no communication is performed, pzlacp2 performs a local copy sub( a ) := sub( b ), where sub( a ) deNotes pzlacp2 requires that only dimension of the matrix operands is Notes distributed matrix b. no communication is performed, pzlacpy performs a local copy sub( a ) := sub( b ), where sub( a ) deNotes Notes Notes where norm1 deNotes the one norm of a matrix (maximum column sum) normf denotes the frobenius norm of a matrix (square root of sum of Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes where sub( x ) deNotes x(ix:ix+n-1,jx) if incx = 1 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. Notes Notes Notes where sub( a ) deNotes a(ia:ia+n-1,ja:ja+n-1) and is an n-by- denoting b(ib:ib+n-1,jb:jb+nrhs-1) are n-by-nrhs distributed error bounds on the solution and a condition estimate are also provided. in the following comments y deNotes y(iy:iy+m-1,jy:jy+k-1 Notes Notes Notes where sub( a ) deNotes a(ia:ia+n-1,ja:ja+n-1) and is a n-by- factorization sub( a ) = u**h*u or l*l**h computed by pzpotrf. contains information of mapping of a to memory. please see Notes below for full description and options b (local input/local output) complex*16 pointer into contains information of mapping of a to memory. please see Notes below for full description and options b (local input/local output) complex*16 pointer into Notes Notes where y' deNotes the conjugate transpose of the vector y if all eigenvectors are requested, the routine may either return the Notes Notes Notes where sub( a ) deNotes a(ia:ia+n-1,ja:ja+n-1) and is a triangula n-by-nrhs distributed matrix denoted by sub( b ). a check is made Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes Notes |
| Notice Notice 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 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 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 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 |
| November November implemented by: g. henry, November 17, 199 ===================================================================== implemented by: g. henry, November 17, 199 ===================================================================== implemented by: g. henry, November 17, 199 ===================================================================== implemented by: g. henry, November 17, 199 ===================================================================== implemented by: g. henry, November 17, 199 ===================================================================== implemented by: g. henry, November 17, 199 ===================================================================== implemented by: g. henry, November 17, 199 ===================================================================== implemented by: g. henry, November 17, 199 ===================================================================== implemented by: g. henry, November 17, 199 ===================================================================== implemented by: g. henry, November 17, 199 ===================================================================== |
| now now now the active submatrix is in rows and columns l to i. i need be transformed. descriptors now have *types* and differ from scalapack 1.0 note: banded codes can use either the old two dimensional descriptors now have *types* and differ from scalapack 1.0 note: banded codes can use either the old two dimensional descriptors now have *types* and differ from scalapack 1.0 note: tridiagonal codes can use either the old two dimensional descriptors now have *types* and differ from scalapack 1.0 note: tridiagonal codes can use either the old two dimensional descriptors now have *types* and differ from scalapack 1.0 note: banded codes can use either the old two dimensional descriptors now have *types* and differ from scalapack 1.0 note: banded codes can use either the old two dimensional now the active submatrix is in rows and columns l to i. i need be transformed. descriptors now have *types* and differ from scalapack 1.0 note: banded codes can use either the old two dimensional descriptors now have *types* and differ from scalapack 1.0 note: banded codes can use either the old two dimensional descriptors now have *types* and differ from scalapack 1.0 note: tridiagonal codes can use either the old two dimensional descriptors now have *types* and differ from scalapack 1.0 note: tridiagonal codes can use either the old two dimensional descriptors now have *types* and differ from scalapack 1.0 note: banded codes can use either the old two dimensional descriptors now have *types* and differ from scalapack 1.0 note: banded codes can use either the old two dimensional descriptors now have *types* and differ from scalapack 1.0 note: tridiagonal codes can use either the old two dimensional descriptors now have *types* and differ from scalapack 1.0 note: tridiagonal codes can use either the old two dimensional descriptors now have *types* and differ from scalapack 1.0 note: banded codes can use either the old two dimensional descriptors now have *types* and differ from scalapack 1.0 note: banded codes can use either the old two dimensional on entry, the off-diagonal element associated with the rank-1 cut which originally split the two submatrices which are now on exit, rho has been modified to the value required by it could conceivably fail on hexadecimal or decimal machines without guard digits, but we know of none arguments now the active submatrix is in rows and columns l to i. i need be transformed. descriptors now have *types* and differ from scalapack 1.0 note: banded codes can use either the old two dimensional descriptors now have *types* and differ from scalapack 1.0 note: banded codes can use either the old two dimensional descriptors now have *types* and differ from scalapack 1.0 note: tridiagonal codes can use either the old two dimensional descriptors now have *types* and differ from scalapack 1.0 note: tridiagonal codes can use either the old two dimensional descriptors now have *types* and differ from scalapack 1.0 note: banded codes can use either the old two dimensional descriptors now have *types* and differ from scalapack 1.0 note: banded codes can use either the old two dimensional descriptors now have *types* and differ from scalapack 1.0 note: tridiagonal codes can use either the old two dimensional descriptors now have *types* and differ from scalapack 1.0 note: tridiagonal codes can use either the old two dimensional descriptors now have *types* and differ from scalapack 1.0 note: banded codes can use either the old two dimensional descriptors now have *types* and differ from scalapack 1.0 note: banded codes can use either the old two dimensional on entry, the off-diagonal element associated with the rank-1 cut which originally split the two submatrices which are now on exit, rho has been modified to the value required by it could conceivably fail on hexadecimal or decimal machines without guard digits, but we know of none arguments now the active submatrix is in rows and columns l to i. i need be transformed. descriptors now have *types* and differ from scalapack 1.0 note: banded codes can use either the old two dimensional descriptors now have *types* and differ from scalapack 1.0 note: banded codes can use either the old two dimensional descriptors now have *types* and differ from scalapack 1.0 note: tridiagonal codes can use either the old two dimensional descriptors now have *types* and differ from scalapack 1.0 note: tridiagonal codes can use either the old two dimensional descriptors now have *types* and differ from scalapack 1.0 note: banded codes can use either the old two dimensional descriptors now have *types* and differ from scalapack 1.0 note: banded codes can use either the old two dimensional descriptors now have *types* and differ from scalapack 1.0 note: tridiagonal codes can use either the old two dimensional descriptors now have *types* and differ from scalapack 1.0 note: tridiagonal codes can use either the old two dimensional descriptors now have *types* and differ from scalapack 1.0 note: banded codes can use either the old two dimensional descriptors now have *types* and differ from scalapack 1.0 note: banded codes can use either the old two dimensional now the active submatrix is in rows and columns l to i. i need be transformed. descriptors now have *types* and differ from scalapack 1.0 note: banded codes can use either the old two dimensional descriptors now have *types* and differ from scalapack 1.0 note: banded codes can use either the old two dimensional descriptors now have *types* and differ from scalapack 1.0 note: tridiagonal codes can use either the old two dimensional descriptors now have *types* and differ from scalapack 1.0 note: tridiagonal codes can use either the old two dimensional now the active submatrix is in rows and columns l to i. i need be transformed. |
| NP0 NP0 if no eigenvectors are requested (jobz = 'n') then lwork >= max( nb*( NP0+1 ), 3 ) +3* the amount of workspace required: if eigenvectors are requested: lwork = n + ( NP0 + mq0 + nb ) * nb mq0 = numroc( max( n, nb, 2 ), nb, 0, 0, npcol ) size of work array. if only eigenvalues are requested: lwork >= n + max( nb * ( NP0 + 1 ), 3 lwork >= n + ( np0 + mq0 + nb ) * nb size of work array. if only eigenvalues are requested: lwork >= n + max( nb * ( NP0 + 1 ), 3 lwork >= n + ( np0 + mq0 + nb ) * nb 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 if no eigenvectors are requested (jobz = 'n') then lwork >= 5 * n + max( 5 * nn, nb * ( NP0 + 1 ) the amount of workspace required to guarantee that all if no eigenvectors are requested (jobz = 'n') then lwork >= 5 * n + max( 5 * nn, nb * ( NP0 + 1 ) the amount of workspace required to guarantee that all 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 if no eigenvectors are requested (jobz = 'n') then lwork >= 5 * n + max( 5 * nn, nb * ( NP0 + 1 ) the amount of workspace required to guarantee that all if no eigenvectors are requested (jobz = 'n') then lwork >= 5 * n + max( 5 * nn, nb * ( NP0 + 1 ) the amount of workspace required to guarantee that all 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 if no eigenvectors are requested (jobz = 'n') then lwork >= max( nb*( NP0+1 ), 3 ) +3* the amount of workspace required: if eigenvectors are requested: lwork = n + ( NP0 + mq0 + nb ) * nb mq0 = numroc( max( n, nb, 2 ), nb, 0, 0, npcol ) size of work array. if only eigenvalues are requested: lwork >= n + max( nb * ( NP0 + 1 ), 3 lwork >= n + ( np0 + mq0 + nb ) * nb size of work array. if only eigenvalues are requested: lwork >= n + max( nb * ( NP0 + 1 ), 3 lwork >= n + ( np0 + mq0 + nb ) * nb 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 |
| NP00 NP00 allocated on each process is nvec = floor(( lwork- max(5*n,NP00*mq00) )/n) nvec - ceil(m/p) + 1 are guaranteed to be orthogonal ( the allocated on each process is nvec = floor(( lwork- max(5*n,NP00*mq00) )/n) nvec - ceil(m/p) + 1 are guaranteed to be orthogonal ( the allocated on each process is nvec = floor(( lwork- max(5*n,NP00*mq00) )/n) nvec - ceil(m/p) + 1 are guaranteed to be orthogonal ( the allocated on each process is nvec = floor(( lwork- max(5*n,NP00*mq00) )/n) nvec - ceil(m/p) + 1 are guaranteed to be orthogonal ( the |
| NpA0 NpA0 lwork is local input and must be at least lwork >= nb + max( NpA0, nb where nb = mb_a = nb_a, iroffa = mod( ia-1, nb ), lwork is local input and must be at least lwork >= max( nb_a * ( NpA0 + mqa0 + nb_a ) nb_a * nb_a, else if side = 'r', lwork >= max( (nb_a*(nb_a-1))/2, ( nqc0 + max( NpA0 nb_a, 0, 0, lcmq ), mpc0 ) )*nb_a ) + mi = m; ni = ihi-ilo; icc = ic; jcc = jc + ilo; lwork >= max( (nb_a*(nb_a-1))/2, ( nqc0 + max( NpA0 nb_a, 0, 0, lcmq ), mpc0 ) )*nb_a ) + else if side = 'r', lwork >= max( (nb_a*(nb_a-1))/2, ( nqc0 + max( NpA0 nb_a, 0, 0, lcmq ), mpc0 ) )*nb_a ) + else if side = 'r', lwork >= max( (nb_a*(nb_a-1))/2, ( nqc0 + max( NpA0 nb_a, 0, 0, lcmq ), mpc0 ) )*nb_a ) + mi = m; mi = n-1; lwork >= max( (nb_a*(nb_a-1))/2, ( nqc0 + max( NpA0 nb_a, 0, 0, lcmq ), mpc0 ) )*nb_a ) + lwork is local input and must be at least lwork >= nb + max( NpA0, nb where nb = mb_a = nb_a, iroffa = mod( ia-1, nb ), lwork is local input and must be at least lwork >= max( nb_a * ( NpA0 + mqa0 + nb_a ) nb_a * nb_a, else if side = 'r', lwork >= max( (nb_a*(nb_a-1))/2, ( nqc0 + max( NpA0 nb_a, 0, 0, lcmq ), mpc0 ) )*nb_a ) + mi = m; ni = ihi-ilo; icc = ic; jcc = jc + ilo; lwork >= max( (nb_a*(nb_a-1))/2, ( nqc0 + max( NpA0 nb_a, 0, 0, lcmq ), mpc0 ) )*nb_a ) + else if side = 'r', lwork >= max( (nb_a*(nb_a-1))/2, ( nqc0 + max( NpA0 nb_a, 0, 0, lcmq ), mpc0 ) )*nb_a ) + else if side = 'r', lwork >= max( (nb_a*(nb_a-1))/2, ( nqc0 + max( NpA0 nb_a, 0, 0, lcmq ), mpc0 ) )*nb_a ) + mi = m; mi = n-1; lwork >= max( (nb_a*(nb_a-1))/2, ( nqc0 + max( NpA0 nb_a, 0, 0, lcmq ), mpc0 ) )*nb_a ) + lwork is local input and must be at least lwork >= nb + max( NpA0, nb where nb = mb_a = nb_a, iroffa = mod( ia-1, nb ), lwork is local input and must be at least lwork >= max( nb_a * ( NpA0 + mqa0 + nb_a ) nb_a * nb_a, else if side = 'r', lwork >= max( (nb_a*(nb_a-1))/2, ( nqc0 + max( NpA0 nb_a, 0, 0, lcmq ), mpc0 ) )*nb_a ) + mi = m; ni = ihi-ilo; icc = ic; jcc = jc + ilo; lwork >= max( (nb_a*(nb_a-1))/2, ( nqc0 + max( NpA0 nb_a, 0, 0, lcmq ), mpc0 ) )*nb_a ) + else if side = 'r', lwork >= max( (nb_a*(nb_a-1))/2, ( nqc0 + max( NpA0 nb_a, 0, 0, lcmq ), mpc0 ) )*nb_a ) + else if side = 'r', lwork >= max( (nb_a*(nb_a-1))/2, ( nqc0 + max( NpA0 nb_a, 0, 0, lcmq ), mpc0 ) )*nb_a ) + mi = m; mi = n-1; lwork >= max( (nb_a*(nb_a-1))/2, ( nqc0 + max( NpA0 nb_a, 0, 0, lcmq ), mpc0 ) )*nb_a ) + lwork is local input and must be at least lwork >= nb + max( NpA0, nb where nb = mb_a = nb_a, iroffa = mod( ia-1, nb ), lwork is local input and must be at least lwork >= max( nb_a * ( NpA0 + mqa0 + nb_a ) nb_a * nb_a, else if side = 'r', lwork >= max( (nb_a*(nb_a-1))/2, ( nqc0 + max( NpA0 nb_a, 0, 0, lcmq ), mpc0 ) )*nb_a ) + mi = m; ni = ihi-ilo; icc = ic; jcc = jc + ilo; lwork >= max( (nb_a*(nb_a-1))/2, ( nqc0 + max( NpA0 nb_a, 0, 0, lcmq ), mpc0 ) )*nb_a ) + else if side = 'r', lwork >= max( (nb_a*(nb_a-1))/2, ( nqc0 + max( NpA0 nb_a, 0, 0, lcmq ), mpc0 ) )*nb_a ) + else if side = 'r', lwork >= max( (nb_a*(nb_a-1))/2, ( nqc0 + max( NpA0 nb_a, 0, 0, lcmq ), mpc0 ) )*nb_a ) + mi = m; mi = n-1; lwork >= max( (nb_a*(nb_a-1))/2, ( nqc0 + max( NpA0 nb_a, 0, 0, lcmq ), mpc0 ) )*nb_a ) + |
| NPACT NPACT the two integers NPACT (nu. of active processors) and npst loop. the two integers NPACT (nu. of active processors) and npst loop. the two integers NPACT (nu. of active processors) and npst loop. the two integers NPACT (nu. of active processors) and npst loop. |
| NpB0 NpB0 lwf = mb_a * ( mpa0 + nqa0 + mb_a ) lws = max( (mb_a*(mb_a-1))/2, ( NpB0 + max( nqa0 mb_a, 0, 0, lcmp ), nrhsqb0 ) )*mb_a ) + lwork >= max( nb_a * ( npa0 + mqa0 + nb_a ), max( (nb_a*(nb_a-1))/2, (pqb0 + NpB0)*nb_a ) mb_b * ( npb0 + pqb0 + mb_b ) ), where lwf = mb_a * ( mpa0 + nqa0 + mb_a ) lws = max( (mb_a*(mb_a-1))/2, ( NpB0 + max( nqa0 mb_a, 0, 0, lcmp ), nrhsqb0 ) )*mb_a ) + lwork >= max( nb_a * ( npa0 + mqa0 + nb_a ), max( (nb_a*(nb_a-1))/2, (pqb0 + NpB0)*nb_a ) mb_b * ( npb0 + pqb0 + mb_b ) ), where lwf = mb_a * ( mpa0 + nqa0 + mb_a ) lws = max( (mb_a*(mb_a-1))/2, ( NpB0 + max( nqa0 mb_a, 0, 0, lcmp ), nrhsqb0 ) )*mb_a ) + lwork >= max( nb_a * ( npa0 + mqa0 + nb_a ), max( (nb_a*(nb_a-1))/2, (pqb0 + NpB0)*nb_a ) mb_b * ( npb0 + pqb0 + mb_b ) ), where lwf = mb_a * ( mpa0 + nqa0 + mb_a ) lws = max( (mb_a*(mb_a-1))/2, ( NpB0 + max( nqa0 mb_a, 0, 0, lcmp ), nrhsqb0 ) )*mb_a ) + lwork >= max( nb_a * ( npa0 + mqa0 + nb_a ), max( (nb_a*(nb_a-1))/2, (pqb0 + NpB0)*nb_a ) mb_b * ( npb0 + pqb0 + mb_b ) ), where |
| NpC0 NpC0 mpc0 = numroc( m+iroffc, mb_c, myrow, icrow, nprow ), NpC0 = numroc( n+icoffc, mb_c, myrow, icrow, nprow ) mpc0 = numroc( m+iroffc, mb_c, myrow, icrow, nprow ), NpC0 = numroc( n+icoffc, mb_c, myrow, icrow, nprow ) mpc0 = numroc( m+iroffc, mb_c, myrow, icrow, nprow ), NpC0 = numroc( n+icoffc, mb_c, myrow, icrow, nprow ) mpc0 = numroc( m+iroffc, mb_c, myrow, icrow, nprow ), NpC0 = numroc( n+icoffc, mb_c, myrow, icrow, nprow ) mpc0 = numroc( m+iroffc, mb_c, myrow, icrow, nprow ), NpC0 = numroc( n+icoffc, mb_c, myrow, icrow, nprow ) mpc0 = numroc( m+iroffc, mb_c, myrow, icrow, nprow ), NpC0 = numroc( n+icoffc, mb_c, myrow, icrow, nprow ) mpc0 = numroc( m+iroffc, mb_c, myrow, icrow, nprow ), NpC0 = numroc( n+icoffc, mb_c, myrow, icrow, nprow ) mpc0 = numroc( m+iroffc, mb_c, myrow, icrow, nprow ), NpC0 = numroc( n+icoffc, mb_c, myrow, icrow, nprow ) |
| NPCOL NPCOL locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a end of "if( mycol/level_dist .le. (NPCOL-1)/level_dist-2 )... ************ returned in work(1) and an error code is returned. lwork>= (12*NPCOL+3*nb end of "if( mycol/level_dist .le. (NPCOL-1)/level_dist-2 )... returned in work(1) and an error code is returned. lwork>= 10*NPCOL+4*nrh info (local output) integer end of "if( mycol/level_dist .le. (NPCOL-1)/level_dist-2 )... ************ locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a 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 locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) arguments with np0 = numroc( max( n, nb, 2 ), nb, 0, 0, nprow ) mq0 = numroc( max( n, nb, 2 ), nb, 0, 0, NPCOL if lwork = -1, then lwork is global input and a workspace locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locp( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locq( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locp( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a end of "if( mycol/level_dist .le. (NPCOL-1)/level_dist-2 )... locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a end of "if( mycol/level_dist .le. (NPCOL-1)/level_dist-2 )... ************ locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a returned in work(1) and an error code is returned. lwork>= (12*NPCOL + 3*nb end of "if( mycol/level_dist .le. (NPCOL-1)/level_dist-2 )... returned in work(1) and an error code is returned. lwork>= (10+2*min(100,nrhs))*NPCOL+4*nrh info (local output) integer end of "if( mycol/level_dist .le. (NPCOL-1)/level_dist-2 )... ************ locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a end of "if( mycol/level_dist .le. (NPCOL-1)/level_dist-2 )... ************ returned in work(1) and an error code is returned. lwork>= (12*NPCOL+3*nb end of "if( mycol/level_dist .le. (NPCOL-1)/level_dist-2 )... returned in work(1) and an error code is returned. lwork>= 10*NPCOL+4*nrh info (local output) integer end of "if( mycol/level_dist .le. (NPCOL-1)/level_dist-2 )... ************ locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a 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 locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a np = numroc( n, mb_q, myrow, iqrow, nprow ) nq = numroc( n, nb_q, mycol, iqcol, NPCOL iqcol = indxg2p( jq, mb_q, mycol, csrc_q, npcol ) iwork (local workspace/output) integer array, dimension 7*n + 8*NPCOL + info (global output) integer the process column over which the first column of the matrix d is distributed. 0 <= dcol < NPCOL q (input/output) double precision array, dimension (ldq, n) the process column over which the first column of the matrix d is distributed. 0 <= dcol < NPCOL q (input/output) double precision array, dimension (ldq, n) locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a np = numroc( n, nb, myrow, iarow, nprow ), nq = numroc( n, nb, mycol, descq( csrc_ ), NPCOL iwork (local workspace/local output) integer array, locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a end of "if( mycol/level_dist .le. (NPCOL-1)/level_dist-2 )... locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a end of "if( mycol/level_dist .le. (NPCOL-1)/level_dist-2 )... ************ locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a returned in work(1) and an error code is returned. lwork>= (12*NPCOL + 3*nb end of "if( mycol/level_dist .le. (NPCOL-1)/level_dist-2 )... returned in work(1) and an error code is returned. lwork>= (10+2*min(100,nrhs))*NPCOL+4*nrh info (local output) integer end of "if( mycol/level_dist .le. (NPCOL-1)/level_dist-2 )... ************ locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a np = numroc( n, nb, myrow, descq( rsrc_ ), nprow ) nq = numroc( n, nb, mycol, descq( csrc_ ), NPCOL if lwork = -1, the lwork is global input and a workspace locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) arguments np = numroc( n, nb, myrow, iarow, nprow ) nq = numroc( n, nb, mycol, iacol, NPCOL if lwork = -1, the lwork is global input and a workspace locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locp( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locq( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locp( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a end of "if( mycol/level_dist .le. (NPCOL-1)/level_dist-2 )... ************ returned in work(1) and an error code is returned. lwork>= (12*NPCOL+3*nb end of "if( mycol/level_dist .le. (NPCOL-1)/level_dist-2 )... returned in work(1) and an error code is returned. lwork>= 10*NPCOL+4*nrh info (local output) integer end of "if( mycol/level_dist .le. (NPCOL-1)/level_dist-2 )... ************ locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a 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 locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a np = numroc( n, mb_q, myrow, iqrow, nprow ) nq = numroc( n, nb_q, mycol, iqcol, NPCOL iqcol = indxg2p( jq, mb_q, mycol, csrc_q, npcol ) iwork (local workspace/output) integer array, dimension 7*n + 8*NPCOL + info (global output) integer the process column over which the first column of the matrix d is distributed. 0 <= dcol < NPCOL q (input/output) real array, dimension (ldq, n) the process column over which the first column of the matrix d is distributed. 0 <= dcol < NPCOL q (input/output) real array, dimension (ldq, n) locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a np = numroc( n, nb, myrow, iarow, nprow ), nq = numroc( n, nb, mycol, descq( csrc_ ), NPCOL iwork (local workspace/local output) integer array, locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a end of "if( mycol/level_dist .le. (NPCOL-1)/level_dist-2 )... locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a end of "if( mycol/level_dist .le. (NPCOL-1)/level_dist-2 )... ************ locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a returned in work(1) and an error code is returned. lwork>= (12*NPCOL + 3*nb end of "if( mycol/level_dist .le. (NPCOL-1)/level_dist-2 )... returned in work(1) and an error code is returned. lwork>= (10+2*min(100,nrhs))*NPCOL+4*nrh info (local output) integer end of "if( mycol/level_dist .le. (NPCOL-1)/level_dist-2 )... ************ locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a np = numroc( n, nb, myrow, descq( rsrc_ ), nprow ) nq = numroc( n, nb, mycol, descq( csrc_ ), NPCOL if lwork = -1, the lwork is global input and a workspace locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) arguments np = numroc( n, nb, myrow, iarow, nprow ) nq = numroc( n, nb, mycol, iacol, NPCOL if lwork = -1, the lwork is global input and a workspace locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locp( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locq( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locp( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a end of "if( mycol/level_dist .le. (NPCOL-1)/level_dist-2 )... ************ locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a returned in work(1) and an error code is returned. lwork>= (12*NPCOL+3*nb end of "if( mycol/level_dist .le. (NPCOL-1)/level_dist-2 )... returned in work(1) and an error code is returned. lwork>= 10*NPCOL+4*nrh info (local output) integer end of "if( mycol/level_dist .le. (NPCOL-1)/level_dist-2 )... ************ locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a 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 locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) arguments with np0 = numroc( max( n, nb, 2 ), nb, 0, 0, nprow ) mq0 = numroc( max( n, nb, 2 ), nb, 0, 0, NPCOL if lwork = -1, then lwork is global input and a workspace locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locp( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locq( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locp( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a end of "if( mycol/level_dist .le. (NPCOL-1)/level_dist-2 )... locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a end of "if( mycol/level_dist .le. (NPCOL-1)/level_dist-2 )... ************ locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a returned in work(1) and an error code is returned. lwork>= (12*NPCOL + 3*nb end of "if( mycol/level_dist .le. (NPCOL-1)/level_dist-2 )... returned in work(1) and an error code is returned. lwork>= (10+2*min(100,nrhs))*NPCOL+4*nrh info (local output) integer end of "if( mycol/level_dist .le. (NPCOL-1)/level_dist-2 )... ************ locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a locr( m ) = numroc( m, mb_a, myrow, rsrc_a, nprow ), locc( n ) = numroc( n, nb_a, mycol, csrc_a, NPCOL ) locr( m ) <= ceil( ceil(m/mb_a)/nprow )*mb_a |
| NPCOLC NPCOLC call blacs_gridinit( contextc, 'r', nprocs, 1 ) call blacs_gridinfo( contextc, nprowc, NPCOLC, myprowc call blacs_gridinit( contextc, 'r', nprocs, 1 ) call blacs_gridinfo( contextc, nprowc, NPCOLC, myprowc |
| NPM0 NPM0 nq: the number of local columns in a( 1:n, 1:n ) NPM0: the number of local rows in a( index:n, index:n npm1: the number of local rows in a( index+1:n, index:n ) nq: the number of local columns in a( 1:n, 1:n ) NPM0: the number of local rows in a( index:n, index:n npm1: the number of local rows in a( index+1:n, index:n ) nq: the number of local columns in a( 1:n, 1:n ) NPM0: the number of local rows in a( index:n, index:n npm1: the number of local rows in a( index+1:n, index:n ) nq: the number of local columns in a( 1:n, 1:n ) NPM0: the number of local rows in a( index:n, index:n npm1: the number of local rows in a( index+1:n, index:n ) |
| NPM1 NPM1 nqm0: the number of local columns in a( index:n, index:n ) NPM1: the number of local rows in a( index+1:n, index:n ltnm0: the number of local rows & columns in nqm0: the number of local columns in a( index:n, index:n ) NPM1: the number of local rows in a( index+1:n, index:n ltnm0: the number of local rows & columns in nqm0: the number of local columns in a( index:n, index:n ) NPM1: the number of local rows in a( index+1:n, index:n ltnm0: the number of local rows & columns in nqm0: the number of local columns in a( index:n, index:n ) NPM1: the number of local rows in a( index+1:n, index:n ltnm0: the number of local rows & columns in |
| NPROCS NPROCS info = -i. > 0: if info = k<=NPROCS, the submatrix stored on processo diagonally dominant-like, and info = -i. > 0: if info = k<=NPROCS, the submatrix stored on processo diagonally dominant-like, and info = -i. > 0: if info = k<=NPROCS, the submatrix stored on processo nonsingular, and nvs (global input) integer array, dimension( NPROCS+1 number of eigenvectors held by processes [0,i-1) info = -i. > 0: if info = k<=NPROCS, the submatrix stored on processo positive definite, and info = -i. > 0: if info = k<=NPROCS, the submatrix stored on processo positive definite, and info = -i. > 0: if info = k<=NPROCS, the submatrix stored on processo diagonally dominant-like, and info = -i. > 0: if info = k<=NPROCS, the submatrix stored on processo diagonally dominant-like, and info = -i. > 0: if info = k<=NPROCS, the submatrix stored on processo nonsingular, and nvs (global input) integer array, dimension( NPROCS+1 number of eigenvectors held by processes [0,i-1) info = -i. > 0: if info = k<=NPROCS, the submatrix stored on processo positive definite, and info = -i. > 0: if info = k<=NPROCS, the submatrix stored on processo positive definite, and liwork (local input) integer size of array iwork must be >= max( 4*n, 14, NPROCS query is assumed; the routine only calculates the minimum nq = numroc( max( n, nb, 2 ), nb, 0, 0, npcol ) nrc = numroc( n, nb, myprowc, 0, NPROCS sizemqrleft = the workspace requirement for pdormtr info = -i. > 0: if info = k<=NPROCS, the submatrix stored on processo diagonally dominant-like, and info = -i. > 0: if info = k<=NPROCS, the submatrix stored on processo diagonally dominant-like, and info = -i. > 0: if info = k<=NPROCS, the submatrix stored on processo nonsingular, and nvs (global input) integer array, dimension( NPROCS+1 number of eigenvectors held by processes [0,i-1) info = -i. > 0: if info = k<=NPROCS, the submatrix stored on processo positive definite, and info = -i. > 0: if info = k<=NPROCS, the submatrix stored on processo positive definite, and liwork (local input) integer size of array iwork must be >= max( 4*n, 14, NPROCS query is assumed; the routine only calculates the minimum nq = numroc( max( n, nb, 2 ), nb, 0, 0, npcol ) nrc = numroc( n, nb, myprowc, 0, NPROCS sizemqrleft = the workspace requirement for psormtr info = -i. > 0: if info = k<=NPROCS, the submatrix stored on processo diagonally dominant-like, and info = -i. > 0: if info = k<=NPROCS, the submatrix stored on processo diagonally dominant-like, and info = -i. > 0: if info = k<=NPROCS, the submatrix stored on processo nonsingular, and nvs (global input) integer array, dimension( NPROCS+1 number of eigenvectors held by processes [0,i-1) info = -i. > 0: if info = k<=NPROCS, the submatrix stored on processo positive definite, and info = -i. > 0: if info = k<=NPROCS, the submatrix stored on processo positive definite, and |
| NPROW NPROW scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: to the scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) lwork = n + ( np0 + mq0 + nb ) * nb, with np0 = numroc( max( n, nb, 2 ), nb, 0, 0, NPROW scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: the scalapack tool function, numroc: locp( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: lwork is local input and must be at least lwork >= nb * numroc( n, 1, 0, 0, NPROW ===================================================================== scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: to the scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: lwork = 6*n + 2*np*nq, with np = numroc( n, mb_q, myrow, iqrow, NPROW iqrow = indxg2p( iq, nb_q, myrow, rsrc_q, nprow ) the process row over which the first row of the matrix d is distributed. 0 <= drow < NPROW dcol (global input) integer the process row over which the first row of the matrix d is distributed. 0 <= drow < NPROW dcol (global input) integer scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: lwork is local input and must be at least lwork >= nb * numroc( n, 1, 0, 0, NPROW ===================================================================== scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: where np = numroc( n, nb, myrow, iarow, NPROW ) scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: lwork = 6*n + 2*np*nq np = numroc( n, nb, myrow, descq( rsrc_ ), NPROW scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) trilwmin = 3*n + max( nb*( np+1 ), 3*nb ) np = numroc( n, nb, myrow, iarow, NPROW scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: the scalapack tool function, numroc: locp( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: to the scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: lwork = 6*n + 2*np*nq, with np = numroc( n, mb_q, myrow, iqrow, NPROW iqrow = indxg2p( iq, nb_q, myrow, rsrc_q, nprow ) the process row over which the first row of the matrix d is distributed. 0 <= drow < NPROW dcol (global input) integer the process row over which the first row of the matrix d is distributed. 0 <= drow < NPROW dcol (global input) integer scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: lwork is local input and must be at least lwork >= nb * numroc( n, 1, 0, 0, NPROW ===================================================================== scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: where np = numroc( n, nb, myrow, iarow, NPROW ) scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: lwork = 6*n + 2*np*nq np = numroc( n, nb, myrow, descq( rsrc_ ), NPROW scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) trilwmin = 3*n + max( nb*( np+1 ), 3*nb ) np = numroc( n, nb, myrow, iarow, NPROW scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: the scalapack tool function, numroc: locp( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: to the scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) lwork = n + ( np0 + mq0 + nb ) * nb, with np0 = numroc( max( n, nb, 2 ), nb, 0, 0, NPROW scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: the scalapack tool function, numroc: locp( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: lwork is local input and must be at least lwork >= nb * numroc( n, 1, 0, 0, NPROW ===================================================================== scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: scalapack tool function, numroc: locr( m ) = numroc( m, mb_a, myrow, rsrc_a, NPROW ) an upper bound for these quantities may be computed by: |
| NPROWC NPROWC call blacs_gridinit( contextc, 'r', nprocs, 1 ) call blacs_gridinfo( contextc, NPROWC, npcolc, myprowc call blacs_gridinit( contextc, 'r', nprocs, 1 ) call blacs_gridinfo( contextc, NPROWC, npcolc, myprowc |
| NPROWxNPCOL NPROWxNPCOL lcm(nprow,npcol) ) here lcm is least common multiple, and NPROWxNPCOL is th lcm(nprow,npcol) ) here lcm is least common multiple, and NPROWxNPCOL is th lcm(nprow,npcol) ) here lcm is least common multiple, and NPROWxNPCOL is th lcm(nprow,npcol) ) here lcm is least common multiple, and NPROWxNPCOL is th lcm(nprow,npcol) ) here lcm is least common multiple, and NPROWxNPCOL is th lcm(nprow,npcol) ) here lcm is least common multiple, and NPROWxNPCOL is th lcm(nprow,npcol) ) here lcm is least common multiple, and NPROWxNPCOL is th lcm(nprow,npcol) ) here lcm is least common multiple, and NPROWxNPCOL is th |
| NPS NPS where lwork is as defined above, and nhetrd_lwork = n + 2*( anb+1 )*( 4*NPS+2 ) where lwork is as defined above, and nhetrd_lwork = 2*( anb+1 )*( 4*NPS+2 ) nhegst_lwopt = 2*np0*nb + nq0*nb + nb*nb for optimal performance, greater workspace is needed, i.e. lwork >= 2*( anb+1 )*( 4*NPS+2 ) + ( nps + 4 ) * np anb = pjlaenv( ictxt, 3, 'pchettrd', 'l', 0, 0, 0, 0 ) the dimension of the array work. lwork >= 2*( anb+1 )*( 4*NPS+2 ) + np nps = max( numroc( n, 1, 0, 0, nprow ), 2*anb ) of eigenvectors requested, and nsytrd_lwopt = n + 2*( anb+1 )*( 4*NPS+2 ) of eigenvectors requested, and nsytrd_lwopt = n + 2*( anb+1 )*( 4*NPS+2 ) nsygst_lwopt = 2*np0*nb + nq0*nb + nb*nb for optimal performance, greater workspace is needed, i.e. lwork >= 2*( anb+1 )*( 4*NPS+2 ) + ( nps + 4 ) * np anb = pjlaenv( ictxt, 3, 'pdsyttrd', 'l', 0, 0, 0, 0 ) the dimension of the array work. lwork >= 2*( anb+1 )*( 4*NPS+2 ) + np nps = max( numroc( n, 1, 0, 0, nprow ), 2*anb ) of eigenvectors requested, and nsytrd_lwopt = n + 2*( anb+1 )*( 4*NPS+2 ) of eigenvectors requested, and nsytrd_lwopt = n + 2*( anb+1 )*( 4*NPS+2 ) nsygst_lwopt = 2*np0*nb + nq0*nb + nb*nb for optimal performance, greater workspace is needed, i.e. lwork >= 2*( anb+1 )*( 4*NPS+2 ) + ( nps + 4 ) * np anb = pjlaenv( ictxt, 3, 'pssyttrd', 'l', 0, 0, 0, 0 ) the dimension of the array work. lwork >= 2*( anb+1 )*( 4*NPS+2 ) + np nps = max( numroc( n, 1, 0, 0, nprow ), 2*anb ) where lwork is as defined above, and nhetrd_lwork = n + 2*( anb+1 )*( 4*NPS+2 ) where lwork is as defined above, and nhetrd_lwork = 2*( anb+1 )*( 4*NPS+2 ) nhegst_lwopt = 2*np0*nb + nq0*nb + nb*nb for optimal performance, greater workspace is needed, i.e. lwork >= 2*( anb+1 )*( 4*NPS+2 ) + ( nps + 4 ) * np anb = pjlaenv( ictxt, 3, 'pzhettrd', 'l', 0, 0, 0, 0 ) the dimension of the array work. lwork >= 2*( anb+1 )*( 4*NPS+2 ) + np nps = max( numroc( n, 1, 0, 0, nprow ), 2*anb ) |
| NPSTR NPSTR the two integers npact (nu. of active processors) and NPSTR loop. the two integers npact (nu. of active processors) and NPSTR loop. the two integers npact (nu. of active processors) and NPSTR loop. the two integers npact (nu. of active processors) and NPSTR loop. |
| NpV0 NpV0 else if side = 'r', lwork >= ( nqc0 + max( NpV0 + numroc( numroc( n+icoffc mpc0 ) ) * k else if side = 'r', lwork >= ( nqc0 + max( NpV0 + numroc( numroc( n+icoffc mpc0 ) ) * k else if side = 'r', lwork >= ( nqc0 + max( NpV0 + numroc( numroc( n+icoffc mpc0 ) ) * k else if side = 'r', lwork >= ( nqc0 + max( NpV0 + numroc( numroc( n+icoffc mpc0 ) ) * k else if side = 'r', lwork >= ( nqc0 + max( NpV0 + numroc( numroc( n+icoffc mpc0 ) ) * k else if side = 'r', lwork >= ( nqc0 + max( NpV0 + numroc( numroc( n+icoffc mpc0 ) ) * k else if side = 'r', lwork >= ( nqc0 + max( NpV0 + numroc( numroc( n+icoffc mpc0 ) ) * k else if side = 'r', lwork >= ( nqc0 + max( NpV0 + numroc( numroc( n+icoffc mpc0 ) ) * k |
| NQ0 NQ0 lwork is local input and must be at least lwork >= NQ0 + max( 1, mp0 ), wher iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), lwork is local input and must be at least lwork >= mb_a * ( mp0 + NQ0 + mb_a ), wher iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), lwork is local input and must be at least lwork >= mp0 + max( 1, NQ0 ), wher iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), lwork is local input and must be at least lwork >= nb_a * ( mp0 + NQ0 + nb_a ), wher iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), lwork is local input and must be at least lwork >= max(3,mp0 + NQ0) if lwork = -1, then lwork is global input and a workspace lwork is local input and must be at least lwork >= mp0 + max( 1, NQ0 ), wher iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), lwork is local input and must be at least lwork >= nb_a * ( mp0 + NQ0 + nb_a ), wher iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), lwork is local input and must be at least lwork >= NQ0 + max( 1, mp0 ), wher iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), lwork is local input and must be at least lwork >= mb_a * ( mp0 + NQ0 + mb_a ), wher iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), wpclange = mp, wpslared1d = NQ0 wpcgebrd = nb*(mp + nq + 1) + nq, the amount of workspace required: lwork >= (np0 + NQ0 + nb)*nb + 3*n + n^ variable definitions: lwork >= n + ( np0 + mq0 + nb ) * nb with NQ0 = numroc( nn, nb, 0, 0, npcol ) for optimal performance, greater workspace is needed, i.e. lwork >= n + ( np0 + mq0 + nb ) * nb with NQ0 = numroc( nn, nb, 0, 0, npcol ) for optimal performance, greater workspace is needed, i.e. 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 lwork >= 0 if norm = 'm' or 'm' (not referenced), NQ0 if norm = '1', 'o' or 'o' 0 if norm = 'f', 'f', 'e' or 'e' (not referenced), work (local workspace) complex array, dimension (lwork) lwork >= NQ0 + max( 1, mp0 ), wher iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), lwork is local input and must be at least lwork >= mb_a * ( mp0 + NQ0 + mb_a ), wher iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), lwork is local input and must be at least lwork >= NQ0 + max( 1, mp0 ), wher iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), lwork is local input and must be at least lwork >= mb_a * ( mp0 + NQ0 + mb_a ), wher iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), lwork is local input and must be at least lwork >= mp0 + max( 1, NQ0 ), wher iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), lwork is local input and must be at least lwork >= nb_a * ( mp0 + NQ0 + nb_a ), wher iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), lwork is local input and must be at least lwork >= max(3,mp0 + NQ0) + locc(ja+n-1)+nq0 iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), lwork is local input and must be at least lwork >= mp0 + max( 1, NQ0 ), wher iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), lwork is local input and must be at least lwork >= nb_a * ( mp0 + NQ0 + nb_a ), wher iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), lwork is local input and must be at least lwork >= NQ0 + max( 1, mp0 ), wher iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), lwork is local input and must be at least lwork >= mb_a * ( mp0 + NQ0 + mb_a ), wher iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), wpdlange = mp, wpdlared1d = NQ0 wpdgebrd = nb*(mp + nq + 1) + nq, lwork >= 0 if norm = 'm' or 'm' (not referenced), NQ0 if norm = '1', 'o' or 'o' 0 if norm = 'f', 'f', 'e' or 'e' (not referenced), work (local workspace) double precision array, dimension (lwork) lwork >= NQ0 + max( 1, mp0 ), wher iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), ( nps + 3 ) * nps nsygst_lwopt = 2*np0*nb + NQ0*nb + nb*n anb = pjlaenv( desca( ctxt_), 3, 'pdsyttrd', 'l', 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 lwork is local input and must be at least lwork >= mb_a * ( mp0 + NQ0 + mb_a ), wher iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), lwork is local input and must be at least lwork >= NQ0 + max( 1, mp0 ), wher iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), lwork is local input and must be at least lwork >= mb_a * ( mp0 + NQ0 + mb_a ), wher iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), lwork is local input and must be at least lwork >= mp0 + max( 1, NQ0 ), wher iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), lwork is local input and must be at least lwork >= nb_a * ( mp0 + NQ0 + nb_a ), wher iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), lwork is local input and must be at least lwork >= max(3,mp0 + NQ0) + locc(ja+n-1)+nq0 iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), lwork is local input and must be at least lwork >= mp0 + max( 1, NQ0 ), wher iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), lwork is local input and must be at least lwork >= nb_a * ( mp0 + NQ0 + nb_a ), wher iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), lwork is local input and must be at least lwork >= NQ0 + max( 1, mp0 ), wher iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), lwork is local input and must be at least lwork >= mb_a * ( mp0 + NQ0 + mb_a ), wher iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), wpslange = mp, wpslared1d = NQ0 wpsgebrd = nb*(mp + nq + 1) + nq, lwork >= 0 if norm = 'm' or 'm' (not referenced), NQ0 if norm = '1', 'o' or 'o' 0 if norm = 'f', 'f', 'e' or 'e' (not referenced), work (local workspace) real array, dimension (lwork) lwork >= NQ0 + max( 1, mp0 ), wher iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), ( nps + 3 ) * nps nsygst_lwopt = 2*np0*nb + NQ0*nb + nb*n anb = pjlaenv( desca( ctxt_), 3, 'pssyttrd', 'l', 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 lwork is local input and must be at least lwork >= mb_a * ( mp0 + NQ0 + mb_a ), wher iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), lwork is local input and must be at least lwork >= NQ0 + max( 1, mp0 ), wher iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), lwork is local input and must be at least lwork >= mb_a * ( mp0 + NQ0 + mb_a ), wher iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), lwork is local input and must be at least lwork >= mp0 + max( 1, NQ0 ), wher iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), lwork is local input and must be at least lwork >= nb_a * ( mp0 + NQ0 + nb_a ), wher iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), lwork is local input and must be at least lwork >= max(3,mp0 + NQ0) if lwork = -1, then lwork is global input and a workspace lwork is local input and must be at least lwork >= mp0 + max( 1, NQ0 ), wher iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), lwork is local input and must be at least lwork >= nb_a * ( mp0 + NQ0 + nb_a ), wher iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), lwork is local input and must be at least lwork >= NQ0 + max( 1, mp0 ), wher iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), lwork is local input and must be at least lwork >= mb_a * ( mp0 + NQ0 + mb_a ), wher iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), wpzlange = mp, wpdlared1d = NQ0 wpzgebrd = nb*(mp + nq + 1) + nq, the amount of workspace required: lwork >= (np0 + NQ0 + nb)*nb + 3*n + n^ variable definitions: lwork >= n + ( np0 + mq0 + nb ) * nb with NQ0 = numroc( nn, nb, 0, 0, npcol ) for optimal performance, greater workspace is needed, i.e. lwork >= n + ( np0 + mq0 + nb ) * nb with NQ0 = numroc( nn, nb, 0, 0, npcol ) for optimal performance, greater workspace is needed, i.e. 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 lwork >= 0 if norm = 'm' or 'm' (not referenced), NQ0 if norm = '1', 'o' or 'o' 0 if norm = 'f', 'f', 'e' or 'e' (not referenced), work (local workspace) complex*16 array, dimension (lwork) lwork >= NQ0 + max( 1, mp0 ), wher iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), lwork is local input and must be at least lwork >= mb_a * ( mp0 + NQ0 + mb_a ), wher iroff = mod( ia-1, mb_a ), icoff = mod( ja-1, nb_a ), |
| NqA0 NqA0 lwork is local input and must be at least lwork >= max( mpa0, NqA0 where nb = mb_a = nb_a, iroffa = mod( ia-1, nb ) lwork is local input and must be at least lwork >= nb*( mpa0 + NqA0 + 1 ) + nqa where nb = mb_a = nb_a, ltau = numroc( ja+min(m,n)-1, nb_a, mycol, csrc_a, npcol ), lwf = nb_a * ( mpa0 + NqA0 + nb_a nb_a * nb_a lwork is local input and must be at least lwork >= max( mb_a * ( mpa0 + NqA0 + mb_a ) mb_a * mb_a, lwork is local input and must be at least lwork >= mpa0 + max( 1, NqA0 ), wher iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), lwork is local input and must be at least lwork >= mpa0 + max( 1, NqA0 ), wher iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), lwork is local input and must be at least lwork >= NqA0 + max( 1, mpa0 ), wher iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), lwork is local input and must be at least lwork >= mb_a * ( mpa0 + NqA0 + mb_a ), wher iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), lwork is local input and must be at least lwork >= nb_a * ( NqA0 + mpa0 + nb_a ), wher iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), lwork is local input and must be at least lwork >= nb_a * ( NqA0 + mpa0 + nb_a ), wher iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), lwork is local input and must be at least lwork >= NqA0 + max( 1, mpa0 ), wher iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), lwork is local input and must be at least lwork >= mb_a * ( mpa0 + NqA0 + mb_a ), wher iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), lwork is local input and must be at least lwork >= max( mpa0, NqA0 where nb = mb_a = nb_a, iroffa = mod( ia-1, nb ) lwork is local input and must be at least lwork >= nb*( mpa0 + NqA0 + 1 ) + nqa where nb = mb_a = nb_a, ltau = numroc( ja+min(m,n)-1, nb_a, mycol, csrc_a, npcol ), lwf = nb_a * ( mpa0 + NqA0 + nb_a nb_a * nb_a lwork is local input and must be at least lwork >= max( mb_a * ( mpa0 + NqA0 + mb_a ) mb_a * mb_a, lwork is local input and must be at least lwork >= mpa0 + max( 1, NqA0 ), wher iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), lwork is local input and must be at least lwork >= mpa0 + max( 1, NqA0 ), wher iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), lwork is local input and must be at least lwork >= NqA0 + max( 1, mpa0 ), wher iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), lwork is local input and must be at least lwork >= mb_a * ( mpa0 + NqA0 + mb_a ), wher iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), lwork is local input and must be at least lwork >= nb_a * ( NqA0 + mpa0 + nb_a ), wher iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), lwork is local input and must be at least lwork >= nb_a * ( NqA0 + mpa0 + nb_a ), wher iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), lwork is local input and must be at least lwork >= NqA0 + max( 1, mpa0 ), wher iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), lwork is local input and must be at least lwork >= mb_a * ( mpa0 + NqA0 + mb_a ), wher iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), lwork is local input and must be at least lwork >= max( mpa0, NqA0 where nb = mb_a = nb_a, iroffa = mod( ia-1, nb ) lwork is local input and must be at least lwork >= nb*( mpa0 + NqA0 + 1 ) + nqa where nb = mb_a = nb_a, ltau = numroc( ja+min(m,n)-1, nb_a, mycol, csrc_a, npcol ), lwf = nb_a * ( mpa0 + NqA0 + nb_a nb_a * nb_a lwork is local input and must be at least lwork >= max( mb_a * ( mpa0 + NqA0 + mb_a ) mb_a * mb_a, lwork is local input and must be at least lwork >= mpa0 + max( 1, NqA0 ), wher iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), lwork is local input and must be at least lwork >= mpa0 + max( 1, NqA0 ), wher iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), lwork is local input and must be at least lwork >= NqA0 + max( 1, mpa0 ), wher iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), lwork is local input and must be at least lwork >= mb_a * ( mpa0 + NqA0 + mb_a ), wher iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), lwork is local input and must be at least lwork >= nb_a * ( NqA0 + mpa0 + nb_a ), wher iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), lwork is local input and must be at least lwork >= nb_a * ( NqA0 + mpa0 + nb_a ), wher iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), lwork is local input and must be at least lwork >= NqA0 + max( 1, mpa0 ), wher iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), lwork is local input and must be at least lwork >= mb_a * ( mpa0 + NqA0 + mb_a ), wher iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), lwork is local input and must be at least lwork >= max( mpa0, NqA0 where nb = mb_a = nb_a, iroffa = mod( ia-1, nb ) lwork is local input and must be at least lwork >= nb*( mpa0 + NqA0 + 1 ) + nqa where nb = mb_a = nb_a, ltau = numroc( ja+min(m,n)-1, nb_a, mycol, csrc_a, npcol ), lwf = nb_a * ( mpa0 + NqA0 + nb_a nb_a * nb_a lwork is local input and must be at least lwork >= max( mb_a * ( mpa0 + NqA0 + mb_a ) mb_a * mb_a, lwork is local input and must be at least lwork >= mpa0 + max( 1, NqA0 ), wher iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), lwork is local input and must be at least lwork >= mpa0 + max( 1, NqA0 ), wher iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), lwork is local input and must be at least lwork >= NqA0 + max( 1, mpa0 ), wher iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), lwork is local input and must be at least lwork >= mb_a * ( mpa0 + NqA0 + mb_a ), wher iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), lwork is local input and must be at least lwork >= nb_a * ( NqA0 + mpa0 + nb_a ), wher iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), lwork is local input and must be at least lwork >= nb_a * ( NqA0 + mpa0 + nb_a ), wher iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), lwork is local input and must be at least lwork >= NqA0 + max( 1, mpa0 ), wher iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), lwork is local input and must be at least lwork >= mb_a * ( mpa0 + NqA0 + mb_a ), wher iroffa = mod( ia-1, mb_a ), icoffa = mod( ja-1, nb_a ), |
| NqB0 NqB0 lwork >= max( mb_a * ( mpa0 + nqa0 + mb_a ), max( (mb_a*(mb_a-1))/2, (ppb0 + NqB0)*mb_a ) nb_b * ( ppb0 + nqb0 + nb_b ) ), where lwork >= max( mb_a * ( mpa0 + nqa0 + mb_a ), max( (mb_a*(mb_a-1))/2, (ppb0 + NqB0)*mb_a ) nb_b * ( ppb0 + nqb0 + nb_b ) ), where lwork >= max( mb_a * ( mpa0 + nqa0 + mb_a ), max( (mb_a*(mb_a-1))/2, (ppb0 + NqB0)*mb_a ) nb_b * ( ppb0 + nqb0 + nb_b ) ), where lwork >= max( mb_a * ( mpa0 + nqa0 + mb_a ), max( (mb_a*(mb_a-1))/2, (ppb0 + NqB0)*mb_a ) nb_b * ( ppb0 + nqb0 + nb_b ) ), where |
| NqC0 NqC0 if side = 'l', lwork >= ( NqC0 + mpc0 ) * lwork >= ( nqc0 + max( npv0 + numroc( numroc( n+icoffc, if side = 'l', lwork >= ( NqC0 + mpc0 ) * lwork >= ( nqc0 + max( npv0 + numroc( numroc( n+icoffc, lwork is local input and must be at least if side = 'l', lwork >= mpc0 + max( 1, NqC0 ) numroc( n+icoffc,nb_a,0,0,npcol ),nb_a,0,0,lcmq ) ); lwork is local input and must be at least if side = 'l', lwork >= mpc0 + max( 1, NqC0 ) numroc( n+icoffc,nb_a,0,0,npcol ),nb_a,0,0,lcmq ) ); if side = 'l', lwork >= max( (nb_a*(nb_a-1))/2, (NqC0 + mpc0)*nb_a ) else if side = 'r', mi = ihi-ilo; ni = n; icc = ic + ilo; jcc = jc; lwork >= max( (nb_a*(nb_a-1))/2, (NqC0 + mpc0)*nb_a ) else if side = 'r', lwork is local input and must be at least if side = 'l', lwork >= mpc0 + max( max( 1, NqC0 ), numroc if side = 'r', lwork >= nqc0 + max( 1, mpc0 ); 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 >= max( (nb_a*(nb_a-1))/2, (NqC0 + mpc0)*nb_a ) else if side = 'r', if side = 'l', lwork >= max( (nb_a*(nb_a-1))/2, (NqC0 + mpc0)*nb_a ) else if side = 'r', lwork is local input and must be at least if side = 'l', lwork >= mpc0 + max( max( 1, NqC0 ), numroc if side = 'r', lwork >= nqc0 + max( 1, mpc0 ); lwork is local input and must be at least if side = 'l', lwork >= mpc0 + max( max( 1, NqC0 ), numroc if side = 'r', lwork >= nqc0 + max( 1, mpc0 ); 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', mi = m-1; ni = n; lwork >= max( (nb_a*(nb_a-1))/2, (NqC0 + mpc0)*nb_a ) else if side = 'r', if side = 'l', lwork >= ( NqC0 + mpc0 ) * lwork >= ( nqc0 + max( npv0 + numroc( numroc( n+icoffc, if side = 'l', lwork >= ( NqC0 + mpc0 ) * lwork >= ( nqc0 + max( npv0 + numroc( numroc( n+icoffc, lwork is local input and must be at least if side = 'l', lwork >= mpc0 + max( 1, NqC0 ) numroc( n+icoffc,nb_a,0,0,npcol ),nb_a,0,0,lcmq ) ); lwork is local input and must be at least if side = 'l', lwork >= mpc0 + max( 1, NqC0 ) numroc( n+icoffc,nb_a,0,0,npcol ),nb_a,0,0,lcmq ) ); if side = 'l', lwork >= max( (nb_a*(nb_a-1))/2, (NqC0 + mpc0)*nb_a ) else if side = 'r', mi = ihi-ilo; ni = n; icc = ic + ilo; jcc = jc; lwork >= max( (nb_a*(nb_a-1))/2, (NqC0 + mpc0)*nb_a ) else if side = 'r', lwork is local input and must be at least if side = 'l', lwork >= mpc0 + max( max( 1, NqC0 ), numroc if side = 'r', lwork >= nqc0 + max( 1, mpc0 ); 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 >= max( (nb_a*(nb_a-1))/2, (NqC0 + mpc0)*nb_a ) else if side = 'r', if side = 'l', lwork >= max( (nb_a*(nb_a-1))/2, (NqC0 + mpc0)*nb_a ) else if side = 'r', lwork is local input and must be at least if side = 'l', lwork >= mpc0 + max( max( 1, NqC0 ), numroc if side = 'r', lwork >= nqc0 + max( 1, mpc0 ); lwork is local input and must be at least if side = 'l', lwork >= mpc0 + max( max( 1, NqC0 ), numroc if side = 'r', lwork >= nqc0 + max( 1, mpc0 ); 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', mi = m-1; ni = n; lwork >= max( (nb_a*(nb_a-1))/2, (NqC0 + mpc0)*nb_a ) else if side = 'r', if side = 'l', lwork >= ( NqC0 + mpc0 ) * lwork >= ( nqc0 + max( npv0 + numroc( numroc( n+icoffc, if side = 'l', lwork >= ( NqC0 + mpc0 ) * lwork >= ( nqc0 + max( npv0 + numroc( numroc( n+icoffc, lwork is local input and must be at least if side = 'l', lwork >= mpc0 + max( 1, NqC0 ) numroc( n+icoffc,nb_a,0,0,npcol ),nb_a,0,0,lcmq ) ); lwork is local input and must be at least if side = 'l', lwork >= mpc0 + max( 1, NqC0 ) numroc( n+icoffc,nb_a,0,0,npcol ),nb_a,0,0,lcmq ) ); if side = 'l', lwork >= max( (nb_a*(nb_a-1))/2, (NqC0 + mpc0)*nb_a ) else if side = 'r', mi = ihi-ilo; ni = n; icc = ic + ilo; jcc = jc; lwork >= max( (nb_a*(nb_a-1))/2, (NqC0 + mpc0)*nb_a ) else if side = 'r', lwork is local input and must be at least if side = 'l', lwork >= mpc0 + max( max( 1, NqC0 ), numroc if side = 'r', lwork >= nqc0 + max( 1, mpc0 ); 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 >= max( (nb_a*(nb_a-1))/2, (NqC0 + mpc0)*nb_a ) else if side = 'r', if side = 'l', lwork >= max( (nb_a*(nb_a-1))/2, (NqC0 + mpc0)*nb_a ) else if side = 'r', lwork is local input and must be at least if side = 'l', lwork >= mpc0 + max( max( 1, NqC0 ), numroc if side = 'r', lwork >= nqc0 + max( 1, mpc0 ); lwork is local input and must be at least if side = 'l', lwork >= mpc0 + max( max( 1, NqC0 ), numroc if side = 'r', lwork >= nqc0 + max( 1, mpc0 ); 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', mi = m-1; ni = n; lwork >= max( (nb_a*(nb_a-1))/2, (NqC0 + mpc0)*nb_a ) else if side = 'r', if side = 'l', lwork >= ( NqC0 + mpc0 ) * lwork >= ( nqc0 + max( npv0 + numroc( numroc( n+icoffc, if side = 'l', lwork >= ( NqC0 + mpc0 ) * lwork >= ( nqc0 + max( npv0 + numroc( numroc( n+icoffc, lwork is local input and must be at least if side = 'l', lwork >= mpc0 + max( 1, NqC0 ) numroc( n+icoffc,nb_a,0,0,npcol ),nb_a,0,0,lcmq ) ); lwork is local input and must be at least if side = 'l', lwork >= mpc0 + max( 1, NqC0 ) numroc( n+icoffc,nb_a,0,0,npcol ),nb_a,0,0,lcmq ) ); if side = 'l', lwork >= max( (nb_a*(nb_a-1))/2, (NqC0 + mpc0)*nb_a ) else if side = 'r', mi = ihi-ilo; ni = n; icc = ic + ilo; jcc = jc; lwork >= max( (nb_a*(nb_a-1))/2, (NqC0 + mpc0)*nb_a ) else if side = 'r', lwork is local input and must be at least if side = 'l', lwork >= mpc0 + max( max( 1, NqC0 ), numroc if side = 'r', lwork >= nqc0 + max( 1, mpc0 ); 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 >= max( (nb_a*(nb_a-1))/2, (NqC0 + mpc0)*nb_a ) else if side = 'r', if side = 'l', lwork >= max( (nb_a*(nb_a-1))/2, (NqC0 + mpc0)*nb_a ) else if side = 'r', lwork is local input and must be at least if side = 'l', lwork >= mpc0 + max( max( 1, NqC0 ), numroc if side = 'r', lwork >= nqc0 + max( 1, mpc0 ); lwork is local input and must be at least if side = 'l', lwork >= mpc0 + max( max( 1, NqC0 ), numroc if side = 'r', lwork >= nqc0 + max( 1, mpc0 ); 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', mi = m-1; ni = n; lwork >= max( (nb_a*(nb_a-1))/2, (NqC0 + mpc0)*nb_a ) else if side = 'r', |
| NQM0 NQM0 npm0: the number of local rows in a( index:n, index:n ) NQM0: the number of local columns in a( index:n, index:n nqm1: the number of local columns in a( index+1:n, index:n ) npm0: the number of local rows in a( index:n, index:n ) NQM0: the number of local columns in a( index:n, index:n nqm1: the number of local columns in a( index+1:n, index:n ) npm0: the number of local rows in a( index:n, index:n ) NQM0: the number of local columns in a( index:n, index:n nqm1: the number of local columns in a( index+1:n, index:n ) npm0: the number of local rows in a( index:n, index:n ) NQM0: the number of local columns in a( index:n, index:n nqm1: the number of local columns in a( index+1:n, index:n ) |
| NQM1 NQM1 npm1: the number of local rows in a( index+1:n, index:n ) NQM1: the number of local columns in a( index+1:n, index:n tril( a( index:n, index:n ) ) npm1: the number of local rows in a( index+1:n, index:n ) NQM1: the number of local columns in a( index+1:n, index:n tril( a( index:n, index:n ) ) npm1: the number of local rows in a( index+1:n, index:n ) NQM1: the number of local columns in a( index+1:n, index:n tril( a( index:n, index:n ) ) npm1: the number of local rows in a( index+1:n, index:n ) NQM1: the number of local columns in a( index+1:n, index:n tril( a( index:n, index:n ) ) |
| NRC NRC nq = numroc( max( n, nb, 2 ), nb, 0, 0, npcol ) NRC = numroc( n, nb, myprowc, 0, nprocs sizemqrleft = the workspace requirement for pdormtr nq = numroc( max( n, nb, 2 ), nb, 0, 0, npcol ) NRC = numroc( n, nb, myprowc, 0, nprocs sizemqrleft = the workspace requirement for psormtr |
| NRHS NRHS NRHS (input) intege of the matrix b. nrhs >= 0. NRHS (input) intege of the matrix b. nrhs >= 0. NRHS (input) intege of the matrix b. nrhs >= 0. NRHS (input) intege of the matrix b. nrhs >= 0. a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:NRHS where a(1:n, ja:ja+n-1) is an n-by-n complex a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:NRHS a(1:n, ja:ja+n-1)' * x = b(ib:ib+n-1, 1:nrhs) a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:NRHS where a(1:n, ja:ja+n-1) is an n-by-n complex a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:NRHS a(1:n, ja:ja+n-1)' * x = b(ib:ib+n-1, 1:nrhs) a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:NRHS where a(1:n, ja:ja+n-1) is an n-by-n complex a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:NRHS a(1:n, ja:ja+n-1)' * x = b(ib:ib+n-1, 1:nrhs) where sub( b ) denotes b( ib:ib+m-1, jb:jb+NRHS-1 ) when trans = 'n vectors b and solution vectors x can be handled in a single call; in the following comments, sub( a ), sub( x ) and sub( b ) denote respectively a(ia:ia+n-1,ja:ja+n-1), x(ix:ix+n-1,jx:jx+NRHS-1) an where sub( a ) = a(ia:ia+n-1,ja:ja+n-1) is an n-by-n distributed matrix and x and sub( b ) = b(ib:ib+n-1,jb:jb+NRHS-1) are n-by-nrh a(ia:ia+n-1,ja:ja+n-1) * x = b(ib:ib+n-1,jb:jb+NRHS-1) where a(ia:ia+n-1,ja:ja+n-1) is an n-by-n matrix and x and sub( a ) denotes a(ia:ia+n-1,ja:ja+n-1), op( a ) = a, a**t or a**h and sub( b ) denotes b(ib:ib+n-1,jb:jb+NRHS-1) notes a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:NRHS where a(1:n, ja:ja+n-1) is an n-by-n complex a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:NRHS where a(1:n, ja:ja+n-1) is the matrix used to produce the factors in the following comments, sub( a ), sub( x ) and sub( b ) denote respectively a(ia:ia+n-1,ja:ja+n-1), x(ix:ix+n-1,jx:jx+NRHS-1) an hermitian distributed positive definite matrix and x and sub( b ) denoting b(ib:ib+n-1,jb:jb+NRHS-1) are n-by-nrhs distribute a(ia:ia+n-1,ja:ja+n-1) * x = b(ib:ib+n-1,jb:jb+NRHS-1) where a(ia:ia+n-1,ja:ja+n-1) is an n-by-n matrix and x and sub( a ) * x = sub( b ) a(ia:ia+n-1,ja:ja+n-1)*x = b(ib:ib+n-1,jb:jb+NRHS-1 where sub( a ) denotes a(ia:ia+n-1,ja:ja+n-1) and is a n-by-n a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:NRHS where a(1:n, ja:ja+n-1) is an n-by-n complex a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:NRHS where a(1:n, ja:ja+n-1) is the matrix used to produce the factors in the following comments, sub( a ), sub( x ) and sub( b ) denote respectively a(ia:ia+n-1,ja:ja+n-1), x(ix:ix+n-1,jx:jx+NRHS-1) an where sub( a ) denotes a(ia:ia+n-1,ja:ja+n-1) and is a triangular distributed matrix of order n, and b(ib:ib+n-1,jb:jb+NRHS-1) is a to verify that sub( a ) is nonsingular. a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:NRHS where a(1:n, ja:ja+n-1) is an n-by-n real a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:NRHS a(1:n, ja:ja+n-1)' * x = b(ib:ib+n-1, 1:nrhs) a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:NRHS where a(1:n, ja:ja+n-1) is an n-by-n real a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:NRHS a(1:n, ja:ja+n-1)' * x = b(ib:ib+n-1, 1:nrhs) a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:NRHS where a(1:n, ja:ja+n-1) is an n-by-n real a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:NRHS a(1:n, ja:ja+n-1)' * x = b(ib:ib+n-1, 1:nrhs) where sub( b ) denotes b( ib:ib+m-1, jb:jb+NRHS-1 ) when trans = 'n vectors b and solution vectors x can be handled in a single call; in the following comments, sub( a ), sub( x ) and sub( b ) denote respectively a(ia:ia+n-1,ja:ja+n-1), x(ix:ix+n-1,jx:jx+NRHS-1) an where sub( a ) = a(ia:ia+n-1,ja:ja+n-1) is an n-by-n distributed matrix and x and sub( b ) = b(ib:ib+n-1,jb:jb+NRHS-1) are n-by-nrh a(ia:ia+n-1,ja:ja+n-1) * x = b(ib:ib+n-1,jb:jb+NRHS-1) where a(ia:ia+n-1,ja:ja+n-1) is an n-by-n matrix and x and sub( a ) denotes a(ia:ia+n-1,ja:ja+n-1), op( a ) = a or a**t and sub( b ) denotes b(ib:ib+n-1,jb:jb+NRHS-1) notes a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:NRHS where a(1:n, ja:ja+n-1) is an n-by-n real a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:NRHS where a(1:n, ja:ja+n-1) is the matrix used to produce the factors in the following comments, sub( a ), sub( x ) and sub( b ) denote respectively a(ia:ia+n-1,ja:ja+n-1), x(ix:ix+n-1,jx:jx+NRHS-1) an symmetric distributed positive definite matrix and x and sub( b ) denoting b(ib:ib+n-1,jb:jb+NRHS-1) are n-by-nrhs distribute a(ia:ia+n-1,ja:ja+n-1) * x = b(ib:ib+n-1,jb:jb+NRHS-1) where a(ia:ia+n-1,ja:ja+n-1) is an n-by-n matrix and x and sub( a ) * x = sub( b ) a(ia:ia+n-1,ja:ja+n-1)*x = b(ib:ib+n-1,jb:jb+NRHS-1 where sub( a ) denotes a(ia:ia+n-1,ja:ja+n-1) and is a n-by-n a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:NRHS where a(1:n, ja:ja+n-1) is an n-by-n real a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:NRHS where a(1:n, ja:ja+n-1) is the matrix used to produce the factors in the following comments, sub( a ), sub( x ) and sub( b ) denote respectively a(ia:ia+n-1,ja:ja+n-1), x(ix:ix+n-1,jx:jx+NRHS-1) an where sub( a ) denotes a(ia:ia+n-1,ja:ja+n-1) and is a triangular distributed matrix of order n, and b(ib:ib+n-1,jb:jb+NRHS-1) is a to verify that sub( a ) is nonsingular. a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:NRHS where a(1:n, ja:ja+n-1) is an n-by-n real a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:NRHS a(1:n, ja:ja+n-1)' * x = b(ib:ib+n-1, 1:nrhs) a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:NRHS where a(1:n, ja:ja+n-1) is an n-by-n real a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:NRHS a(1:n, ja:ja+n-1)' * x = b(ib:ib+n-1, 1:nrhs) a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:NRHS where a(1:n, ja:ja+n-1) is an n-by-n real a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:NRHS a(1:n, ja:ja+n-1)' * x = b(ib:ib+n-1, 1:nrhs) where sub( b ) denotes b( ib:ib+m-1, jb:jb+NRHS-1 ) when trans = 'n vectors b and solution vectors x can be handled in a single call; in the following comments, sub( a ), sub( x ) and sub( b ) denote respectively a(ia:ia+n-1,ja:ja+n-1), x(ix:ix+n-1,jx:jx+NRHS-1) an where sub( a ) = a(ia:ia+n-1,ja:ja+n-1) is an n-by-n distributed matrix and x and sub( b ) = b(ib:ib+n-1,jb:jb+NRHS-1) are n-by-nrh a(ia:ia+n-1,ja:ja+n-1) * x = b(ib:ib+n-1,jb:jb+NRHS-1) where a(ia:ia+n-1,ja:ja+n-1) is an n-by-n matrix and x and sub( a ) denotes a(ia:ia+n-1,ja:ja+n-1), op( a ) = a or a**t and sub( b ) denotes b(ib:ib+n-1,jb:jb+NRHS-1) notes a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:NRHS where a(1:n, ja:ja+n-1) is an n-by-n real a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:NRHS where a(1:n, ja:ja+n-1) is the matrix used to produce the factors in the following comments, sub( a ), sub( x ) and sub( b ) denote respectively a(ia:ia+n-1,ja:ja+n-1), x(ix:ix+n-1,jx:jx+NRHS-1) an symmetric distributed positive definite matrix and x and sub( b ) denoting b(ib:ib+n-1,jb:jb+NRHS-1) are n-by-nrhs distribute a(ia:ia+n-1,ja:ja+n-1) * x = b(ib:ib+n-1,jb:jb+NRHS-1) where a(ia:ia+n-1,ja:ja+n-1) is an n-by-n matrix and x and sub( a ) * x = sub( b ) a(ia:ia+n-1,ja:ja+n-1)*x = b(ib:ib+n-1,jb:jb+NRHS-1 where sub( a ) denotes a(ia:ia+n-1,ja:ja+n-1) and is a n-by-n a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:NRHS where a(1:n, ja:ja+n-1) is an n-by-n real a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:NRHS where a(1:n, ja:ja+n-1) is the matrix used to produce the factors in the following comments, sub( a ), sub( x ) and sub( b ) denote respectively a(ia:ia+n-1,ja:ja+n-1), x(ix:ix+n-1,jx:jx+NRHS-1) an where sub( a ) denotes a(ia:ia+n-1,ja:ja+n-1) and is a triangular distributed matrix of order n, and b(ib:ib+n-1,jb:jb+NRHS-1) is a to verify that sub( a ) is nonsingular. a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:NRHS where a(1:n, ja:ja+n-1) is an n-by-n complex a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:NRHS a(1:n, ja:ja+n-1)' * x = b(ib:ib+n-1, 1:nrhs) a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:NRHS where a(1:n, ja:ja+n-1) is an n-by-n complex a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:NRHS a(1:n, ja:ja+n-1)' * x = b(ib:ib+n-1, 1:nrhs) a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:NRHS where a(1:n, ja:ja+n-1) is an n-by-n complex a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:NRHS a(1:n, ja:ja+n-1)' * x = b(ib:ib+n-1, 1:nrhs) where sub( b ) denotes b( ib:ib+m-1, jb:jb+NRHS-1 ) when trans = 'n vectors b and solution vectors x can be handled in a single call; in the following comments, sub( a ), sub( x ) and sub( b ) denote respectively a(ia:ia+n-1,ja:ja+n-1), x(ix:ix+n-1,jx:jx+NRHS-1) an where sub( a ) = a(ia:ia+n-1,ja:ja+n-1) is an n-by-n distributed matrix and x and sub( b ) = b(ib:ib+n-1,jb:jb+NRHS-1) are n-by-nrh a(ia:ia+n-1,ja:ja+n-1) * x = b(ib:ib+n-1,jb:jb+NRHS-1) where a(ia:ia+n-1,ja:ja+n-1) is an n-by-n matrix and x and sub( a ) denotes a(ia:ia+n-1,ja:ja+n-1), op( a ) = a, a**t or a**h and sub( b ) denotes b(ib:ib+n-1,jb:jb+NRHS-1) notes a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:NRHS where a(1:n, ja:ja+n-1) is an n-by-n complex a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:NRHS where a(1:n, ja:ja+n-1) is the matrix used to produce the factors in the following comments, sub( a ), sub( x ) and sub( b ) denote respectively a(ia:ia+n-1,ja:ja+n-1), x(ix:ix+n-1,jx:jx+NRHS-1) an hermitian distributed positive definite matrix and x and sub( b ) denoting b(ib:ib+n-1,jb:jb+NRHS-1) are n-by-nrhs distribute a(ia:ia+n-1,ja:ja+n-1) * x = b(ib:ib+n-1,jb:jb+NRHS-1) where a(ia:ia+n-1,ja:ja+n-1) is an n-by-n matrix and x and sub( a ) * x = sub( b ) a(ia:ia+n-1,ja:ja+n-1)*x = b(ib:ib+n-1,jb:jb+NRHS-1 where sub( a ) denotes a(ia:ia+n-1,ja:ja+n-1) and is a n-by-n a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:NRHS where a(1:n, ja:ja+n-1) is an n-by-n complex a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:NRHS where a(1:n, ja:ja+n-1) is the matrix used to produce the factors in the following comments, sub( a ), sub( x ) and sub( b ) denote respectively a(ia:ia+n-1,ja:ja+n-1), x(ix:ix+n-1,jx:jx+NRHS-1) an where sub( a ) denotes a(ia:ia+n-1,ja:ja+n-1) and is a triangular distributed matrix of order n, and b(ib:ib+n-1,jb:jb+NRHS-1) is a to verify that sub( a ) is nonsingular. NRHS (input) intege of the matrix b. nrhs >= 0. NRHS (input) intege of the matrix b. nrhs >= 0. NRHS (input) intege of the matrix b. nrhs >= 0. NRHS (input) intege of the matrix b. nrhs >= 0. |
| NRHSqB0 NRHSqB0 lwf = nb_a * ( mpa0 + nqa0 + nb_a ) lws = max( (nb_a*(nb_a-1))/2, (NRHSqB0 + mpb0)*nb_a ) else lwf = nb_a * ( mpa0 + nqa0 + nb_a ) lws = max( (nb_a*(nb_a-1))/2, (NRHSqB0 + mpb0)*nb_a ) else lwf = nb_a * ( mpa0 + nqa0 + nb_a ) lws = max( (nb_a*(nb_a-1))/2, (NRHSqB0 + mpb0)*nb_a ) else lwf = nb_a * ( mpa0 + nqa0 + nb_a ) lws = max( (nb_a*(nb_a-1))/2, (NRHSqB0 + mpb0)*nb_a ) else |
| NRU NRU wbdtosvd = size*(wantu*NRU + wantvt*ncvt) max(wantu*wpcormbrqln, wantvt*wpcormbrprt)), wbdtosvd = size*(wantu*NRU + wantvt*ncvt) max(wantu*wpdormbrqln, wantvt*wpdormbrprt)), wbdtosvd = size*(wantu*NRU + wantvt*ncvt) max(wantu*wpsormbrqln, wantvt*wpsormbrprt)), wbdtosvd = size*(wantu*NRU + wantvt*ncvt) max(wantu*wpzormbrqln, wantvt*wpzormbrprt)), |
| NSPLIT NSPLIT the second of rows/columns isplit(1)+1 through isplit(2), etc., and the NSPLIT-th consists of rows/column isplit from psstebz is expected here.) NSPLIT (global output) intege 1 <= nsplit <= n. the second of rows/columns isplit(1)+1 through isplit(2), etc., and the NSPLIT-th consists of rows/column isplit from pdstebz is expected here.) NSPLIT (global output) intege 1 <= nsplit <= n. the second of rows/columns isplit(1)+1 through isplit(2), etc., and the NSPLIT-th consists of rows/column isplit from psstebz is expected here.) the second of rows/columns isplit(1)+1 through isplit(2), etc., and the NSPLIT-th consists of rows/column isplit from pdstebz is expected here.) |
| NSYGST_LWOPT NSYGST_LWOPT lwork >= max( lwork, 5 * n + nsytrd_lwopt, NSYGST_LWOPT lwork, as defined previously, depends upon the number lwork >= max( lwork, 5 * n + nsytrd_lwopt, NSYGST_LWOPT lwork, as defined previously, depends upon the number |
| NSYTRD_LWOPT NSYTRD_LWOPT needed, i.e. lwork >= max( lwork, 5*n + NSYTRD_LWOPT lwork, as defined previously, depends upon the number needed, i.e. lwork >= max( lwork, 5 * n + NSYTRD_LWOPT where: needed, i.e. lwork >= max( lwork, 5*n + NSYTRD_LWOPT lwork, as defined previously, depends upon the number needed, i.e. lwork >= max( lwork, 5 * n + NSYTRD_LWOPT where: |
| null null top of the loop still holds, but with bindex = 0, h and v are null matrices after the current column of a is updated, top of the loop still holds, but with bindex = 0, h and v are null matrices after the current column of a is updated, top of the loop still holds, but with bindex = 0, h and v are null matrices after the current column of a is updated, top of the loop still holds, but with bindex = 0, h and v are null matrices after the current column of a is updated, |
| number number m (input) integer the number of rows of the matrix a. m >= 0 n (input) integer kv is the number of superdiagonals in the factor nrhs (input) integer the number of right hand sides, i.e., the number of column itn is the total number of qr iterations allowed see how consecutive small subdiagonal elements are modified by subsequent shifts in an effort to maximize the number of bulge clamsh should only be called when there are multiple shifts/bulges istart (global input) integer specifies the "number" of the first reflector. this i istart is ignored if block is .false.. nrhs (input) integer the number of right hand sides, i.e., the number of column m (input) integer the number of rows of the matrix a. m >= 0 n (input) integer kv is the number of superdiagonals in the factor nrhs (input) integer the number of right hand sides, i.e., the number of column see how consecutive small subdiagonal elements are modified by subsequent shifts in an effort to maximize the number of bulge dlamsh should only be called when there are multiple shifts/bulges istart (global input) integer specifies the "number" of the first reflector. this i istart is ignored if block is .false.. info (local input) integer this is set if the input matrix had an odd number of rea matrix s was not originally in schur form. nrhs (input) integer the number of right hand sides, i.e., the number of column initialize seed for random number generator dlarnv n (global input) integer the number of rows and columns to be operated on, i.e. th want to find errors with min( ), so if no error, set it to a big number. if there already is an error, multiply by the th n (global input) integer the number of rows and columns to be operated on, i.e. th want to find errors with min( ), so if no error, set it to a big number. if there already is an error, multiply by the th n (global input) integer the number of rows and columns to be operated on, i.e. th want to find errors with min( ), so if no error, set it to a big number. if there already is an error, multiply by the th n (global input) integer the number of rows and columns to be operated on, i.e. th want to find errors with min( ), so if no error, set it to a big number. if there already is an error, multiply by the th n (global input) integer the number of rows and columns to be operated on, i.e. th want to find errors with min( ), so if no error, set it to a big number. if there already is an error, multiply by the th n (global input) integer the number of rows and columns to be operated on, i.e. th value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global pcgecon estimates the reciprocal of the condition number of a genera 1-norm or the infinity-norm, using the lu factorization computed by m-by-n distributed matrix sub( a ) = a(ia:ia+n-1,ja:ja:ja+n-1) and reduce its condition number. r returns the row scale factors and each row and column of the distributed matrix b with elements value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a 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n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the distribute n_a (global) desca( n_ ) the number of columns in the distri- np = the number of rows local to a given process value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the 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(global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global n (global input) integer the number of rows and columns to be operated on, i.e. th want to find errors with min( ), so if no error, set it to a big number. if there already is an error, multiply by the th n (global input) integer the number of rows and columns to be operated on, i.e. th want to find errors with min( ), so if no error, set it to a big number. if there already is an error, multiply by the th pcpocon estimates the reciprocal of the condition number (in th using the cholesky factorization a = u**h*u or a = l*l**h computed by equilibrate a distributed hermitian positive definite matrix sub( a ) = a(ia:ia+n-1,ja:ja+n-1) and reduce its condition number factors, s(i) = 1/sqrt(a(i,i)), chosen so that the scaled distri- value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global n (global input) integer the number of rows and columns to be operated on, i.e. th want to find errors with min( ), so if no error, set it to a big number. if there already is an error, multiply by the th n (global input) integer the number of rows and columns to be operated on, i.e. th want to find errors with min( ), so if no error, set it to a big number. if there already is an error, multiply by the th value) may vary. m_a (global) desca[ m_ ] the number of rows in the globa n_a (global) desca[ n_ ] the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global pctrcon estimates the reciprocal of the condition number of 1-norm or the infinity-norm. value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global n (global input) integer the number of rows and columns to be operated on, i.e. th want to find errors with min( ), so if no error, set it to a big number. if there already is an error, multiply by the th n (global input) integer the number of rows and columns to be operated on, i.e. th want to find errors with min( ), so if no error, set it to a big number. if there already is an error, multiply by the th n (global input) integer the number of rows and columns to be operated on, i.e. th want to find errors with min( ), so if no error, set it to a big number. if there already is an error, multiply by the th n (global input) integer the number of rows and columns to be operated on, i.e. th want to find errors with min( ), so if no error, set it to a big number. if there already is an error, multiply by the th n (global input) integer the number of rows and columns to be operated on, i.e. th want to find errors with min( ), so if no error, set it to a big number. if there already is an error, multiply by the th n (global input) integer the number of rows and columns to be operated on, i.e. th value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global pdgecon estimates the reciprocal of the condition number of a genera or the infinity-norm, using the lu factorization computed by pdgetrf. m-by-n distributed matrix sub( a ) = a(ia:ia+n-1,ja:ja:ja+n-1) and reduce its condition number. r returns the row scale factors and each row and column of the distributed matrix b with elements value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global endpoints of the interval. = 1 : find a floating point number contained in the initia = 2 : perform bisection iteration to find eigenvalues of t. k (output) integer the number of non-deflated eigenvalues, and the order of th k (output) integer the number of non-deflated eigenvalues, and the order of th value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global determine the number of columns we have so we can check workspac n (global input) integer the number of rows and columns to be operated on, i.e. th n >= 0. prec = eps*base t = number of (base) digits in the mantiss emin = minimum exponent before (gradual) underflow value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global pdlapdct counts the number of negative eigenvalues of (t - sigma i) the innermost loop to avoid overflow and determine the sign of a value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global pdlasrt sort the numbers in d in increasing order and th value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global n (global input) integer the number of rows and columns to be operated on, i.e. th want to find errors with min( ), so if no error, set it to a big number. if there already is an error, multiply by the th n (global input) integer the number of rows and columns to be operated on, i.e. th want to find errors with min( ), so if no error, set it to a big number. if there already is an error, multiply by the th pdpocon estimates the reciprocal of the condition number (in th using the cholesky factorization a = u**t*u or a = l*l**t computed by equilibrate a distributed symmetric positive definite matrix sub( a ) = a(ia:ia+n-1,ja:ja+n-1) and reduce its condition number factors, s(i) = 1/sqrt(a(i,i)), chosen so that the scaled distri- value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global n (global input) integer the number of rows and columns to be operated on, i.e. th want to find errors with min( ), so if no error, set it to a big number. if there already is an error, multiply by the th n (global input) integer the number of rows and columns to be operated on, i.e. th want to find errors with min( ), so if no error, set it to a big number. if there already is an error, multiply by the th value) may vary. m_a (global) desca[ m_ ] the number of rows in the globa n_a (global) desca[ n_ ] the number of columns in the global static partitioning of work is done at the beginning of pdstebz which results in all processes finding an (almost) equal number o value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the distribute n_a (global) desca( n_ ) the number of columns in the distri- np = the number of rows local to a given process value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global pdtrcon estimates the reciprocal of the condition number of 1-norm or the infinity-norm. value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global n (global input) integer the number of rows and columns to be operated on, i.e. th want to find errors with min( ), so if no error, set it to a big number. if there already is an error, multiply by the th n (global input) integer the number of rows and columns to be operated on, i.e. th want to find errors with min( ), so if no error, set it to a big number. if there already is an error, multiply by the th n (global input) integer the number of rows and columns to be operated on, i.e. th want to find errors with min( ), so if no error, set it to a big number. if there already is an error, multiply by the th n (global input) integer the number of rows and columns to be operated on, i.e. th want to find errors with min( ), so if no error, set it to a big number. if there already is an error, multiply by the th n (global input) integer the number of rows and columns to be operated on, i.e. th want to find errors with min( ), so if no error, set it to a big number. if there already is an error, multiply by the th n (global input) integer the number of rows and columns to be operated on, i.e. th value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global psgecon estimates the reciprocal of the condition number of a genera or the infinity-norm, using the lu factorization computed by psgetrf. m-by-n distributed matrix sub( a ) = a(ia:ia+n-1,ja:ja:ja+n-1) and reduce its condition number. r returns the row scale factors and each row and column of the distributed matrix b with elements value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global endpoints of the interval. = 1 : find a floating point number contained in the initia = 2 : perform bisection iteration to find eigenvalues of t. k (output) integer the number of non-deflated eigenvalues, and the order of th k (output) integer the number of non-deflated eigenvalues, and the order of th value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global determine the number of columns we have so we can check workspac n (global input) integer the number of rows and columns to be operated on, i.e. th n >= 0. prec = eps*base t = number of (base) digits in the mantiss emin = minimum exponent before (gradual) underflow value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global pslapdct counts the number of negative eigenvalues of (t - sigma i) the innermost loop to avoid overflow and determine the sign of a value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global pslasrt sort the numbers in d in increasing order and th value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global n (global input) integer the number of rows and columns to be operated on, i.e. th want to find errors with min( ), so if no error, set it to a big number. if there already is an error, multiply by the th n (global input) integer the number of rows and columns to be operated on, i.e. th want to find errors with min( ), so if no error, set it to a big number. if there already is an error, multiply by the th pspocon estimates the reciprocal of the condition number (in th using the cholesky factorization a = u**t*u or a = l*l**t computed by equilibrate a distributed symmetric positive definite matrix sub( a ) = a(ia:ia+n-1,ja:ja+n-1) and reduce its condition number factors, s(i) = 1/sqrt(a(i,i)), chosen so that the scaled distri- value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global n (global input) integer the number of rows and columns to be operated on, i.e. th want to find errors with min( ), so if no error, set it to a big number. if there already is an error, multiply by the th n (global input) integer the number of rows and columns to be operated on, i.e. th want to find errors with min( ), so if no error, set it to a big number. if there already is an error, multiply by the th value) may vary. m_a (global) desca[ m_ ] the number of rows in the globa n_a (global) desca[ n_ ] the number of columns in the global static partitioning of work is done at the beginning of psstebz which results in all processes finding an (almost) equal number o value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the distribute n_a (global) desca( n_ ) the number of columns in the distri- np = the number of rows local to a given process value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global pstrcon estimates the reciprocal of the condition number of 1-norm or the infinity-norm. value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global n (global input) integer the number of rows and columns to be operated on, i.e. th want to find errors with min( ), so if no error, set it to a big number. if there already is an error, multiply by the th n (global input) integer the number of rows and columns to be operated on, i.e. th want to find errors with min( ), so if no error, set it to a big number. if there already is an error, multiply by the th value) may vary. m_a (global) desca[ m_ ] the number of rows in the globa n_a (global) desca[ n_ ] the number of columns in the global n (global input) integer the number of rows and columns to be operated on, i.e. th want to find errors with min( ), so if no error, set it to a big number. if there already is an error, multiply by the th n (global input) integer the number of rows and columns to be operated on, i.e. th want to find errors with min( ), so if no error, set it to a big number. if there already is an error, multiply by the th n (global input) integer the number of rows and columns to be operated on, i.e. th want to find errors with min( ), so if no error, set it to a big number. if there already is an error, multiply by the th n (global input) integer the number of rows and columns to be operated on, i.e. th value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global pzgecon estimates the reciprocal of the condition number of a genera 1-norm or the infinity-norm, using the lu factorization computed by m-by-n distributed matrix sub( a ) = a(ia:ia+n-1,ja:ja:ja+n-1) and reduce its condition number. r returns the row scale factors and each row and column of the distributed matrix b with elements value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the distribute n_a (global) desca( n_ ) the number of columns in the distri- np = the number of rows local to a given process value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global determine the number of columns we have so we can check workspac n (global input) integer the number of rows and columns to be operated on, i.e. th n >= 0. value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global n (global input) integer the number of rows and columns to be operated on, i.e. th want to find errors with min( ), so if no error, set it to a big number. if there already is an error, multiply by the th n (global input) integer the number of rows and columns to be operated on, i.e. th want to find errors with min( ), so if no error, set it to a big number. if there already is an error, multiply by the th pzpocon estimates the reciprocal of the condition number (in th using the cholesky factorization a = u**h*u or a = l*l**h computed by equilibrate a distributed hermitian positive definite matrix sub( a ) = a(ia:ia+n-1,ja:ja+n-1) and reduce its condition number factors, s(i) = 1/sqrt(a(i,i)), chosen so that the scaled distri- value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global n (global input) integer the number of rows and columns to be operated on, i.e. th want to find errors with min( ), so if no error, set it to a big number. if there already is an error, multiply by the th n (global input) integer the number of rows and columns to be operated on, i.e. th want to find errors with min( ), so if no error, set it to a big number. if there already is an error, multiply by the th value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global pztrcon estimates the reciprocal of the condition number of 1-norm or the infinity-norm. value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global value) may vary. m_a (global) desca( m_ ) the number of rows in the globa n_a (global) desca( n_ ) the number of columns in the global m (input) integer the number of rows of the matrix a. m >= 0 n (input) integer kv is the number of superdiagonals in the factor nrhs (input) integer the number of right hand sides, i.e., the number of column see how consecutive small subdiagonal elements are modified by subsequent shifts in an effort to maximize the number of bulge slamsh should only be called when there are multiple shifts/bulges istart (global input) integer specifies the "number" of the first reflector. this i istart is ignored if block is .false.. info (local input) integer this is set if the input matrix had an odd number of rea matrix s was not originally in schur form. nrhs (input) integer the number of right hand sides, i.e., the number of column initialize seed for random number generator slarnv m (input) integer the number of rows of the matrix a. m >= 0 n (input) integer kv is the number of superdiagonals in the factor nrhs (input) integer the number of right hand sides, i.e., the number of column itn is the total number of qr iterations allowed see how consecutive small subdiagonal elements are modified by subsequent shifts in an effort to maximize the number of bulge zlamsh should only be called when there are multiple shifts/bulges istart (global input) integer specifies the "number" of the first reflector. this i istart is ignored if block is .false.. nrhs (input) integer the number of right hand sides, i.e., the number of column |
| numbers numbers which is about to be factorized. the number of rows in the partitioning are jb, i2, i3 respectively, and the numbers and the subdiagonal elements of a31 lie outside the band. which is about to be factorized. the number of rows in the partitioning are jb, i2, i3 respectively, and the numbers and the subdiagonal elements of a31 lie outside the band. pdlasrt sort the numbers in d in increasing order and th specifies the order in which the eigenvalues and their block numbers are stored in w and iblock split-off block (see iblock, isplit) and pslasrt sort the numbers in d in increasing order and th specifies the order in which the eigenvalues and their block numbers are stored in w and iblock split-off block (see iblock, isplit) and which is about to be factorized. the number of rows in the partitioning are jb, i2, i3 respectively, and the numbers and the subdiagonal elements of a31 lie outside the band. which is about to be factorized. the number of rows in the partitioning are jb, i2, i3 respectively, and the numbers and the subdiagonal elements of a31 lie outside the band. |
| NUMROC NUMROC 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 ). 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 ). 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 ). 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 ). 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 ). 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 ). 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 ). 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 ). 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 ). lwork = n + ( np0 + mq0 + nb ) * nb, with np0 = NUMROC( max( n, nb, 2 ), nb, 0, 0, nprow 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 ). 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 ). the values of locp() and locq() may be determined via a call to the scalapack tool function, NUMROC locq( 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 ). 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 ). 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 ). lwork is local input and must be at least lwork >= nb * NUMROC( n, 1, 0, 0, nprow ===================================================================== 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 ). 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 ). 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 ). 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 ). 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 ). 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 ). 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 ). 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 ). 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 ). 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 ). 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 ). 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 ). 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 ). 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 ). 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 ). 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 ). 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 ). 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 ). 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 ). 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 ). 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 ). 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 ). 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 ). 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 ). 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 ). 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 ). 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 ). lwork = 6*n + 2*np*nq, with np = NUMROC( n, mb_q, myrow, iqrow, nprow iqrow = indxg2p( iq, nb_q, myrow, rsrc_q, nprow ) 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 ). lwork is local input and must be at least lwork >= nb * NUMROC( n, 1, 0, 0, nprow ===================================================================== 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 ). 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 ). 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 ). 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 ). where np = NUMROC( n, nb, myrow, iarow, nprow ) 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 ). 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 ). 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 ). 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 ). 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 ). 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 ). 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 ). 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 ). 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 ). 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 ). 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 ). lwork = 6*n + 2*np*nq np = NUMROC( n, nb, myrow, descq( rsrc_ ), nprow 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 ). trilwmin = 3*n + max( nb*( np+1 ), 3*nb ) np = NUMROC( n, nb, myrow, iarow, nprow 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 ). 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 ). the values of locp() and locq() may be determined via a call to the scalapack tool function, NUMROC locq( 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 ). 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 ). 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 ). 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 ). 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 ). 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 ). 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 ). 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 ). 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 ). 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 ). 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 ). 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 ). 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 ). lwork = 6*n + 2*np*nq, with np = NUMROC( n, mb_q, myrow, iqrow, nprow iqrow = indxg2p( iq, nb_q, myrow, rsrc_q, nprow ) 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 ). lwork is local input and must be at least lwork >= nb * NUMROC( n, 1, 0, 0, nprow ===================================================================== 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 ). 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 ). 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 ). 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 ). where np = NUMROC( n, nb, myrow, iarow, nprow ) 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 ). 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 ). 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 ). 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 ). 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 ). 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 ). 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 ). 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 ). 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 ). 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 ). 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 ). lwork = 6*n + 2*np*nq np = NUMROC( n, nb, myrow, descq( rsrc_ ), nprow 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 ). trilwmin = 3*n + max( nb*( np+1 ), 3*nb ) np = NUMROC( n, nb, myrow, iarow, nprow 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 ). 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 ). the values of locp() and locq() may be determined via a call to the scalapack tool function, NUMROC locq( 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 ). 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 ). 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 ). 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 ). 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 ). 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 ). 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 ). 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 ). 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 ). 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 ). 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 ). lwork = n + ( np0 + mq0 + nb ) * nb, with np0 = NUMROC( max( n, nb, 2 ), nb, 0, 0, nprow 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 ). 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 ). the values of locp() and locq() may be determined via a call to the scalapack tool function, NUMROC locq( 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 ). 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 ). 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 ). lwork is local input and must be at least lwork >= nb * NUMROC( n, 1, 0, 0, nprow ===================================================================== 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 ). 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 ). 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 ). 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 ). 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 ). 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 ). 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 ). 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 ). 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 ). 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 ). 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 ). 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 ). 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 ). 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 ). 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 ). 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 ). 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 ). |
| NVAL NVAL pdlaebz contains the iteration loop which computes the eigeNVALue j = 1,...,minp. it uses and computes the function n(w), which is the counts at the endpoints are identical to the counts specified by NVAL ( see nval ) then the interval i pslaebz contains the iteration loop which computes the eigeNVALue j = 1,...,minp. it uses and computes the function n(w), which is the counts at the endpoints are identical to the counts specified by NVAL ( see nval ) then the interval i |
| NVEC NVEC pcstein computes the eigeNVECtors of a symmetric tridiagonal matri correspond to user specified eigenvalues. pcstein does not pdstein computes the eigeNVECtors of a symmetric tridiagonal matri correspond to user specified eigenvalues. pdstein does not psstein computes the eigeNVECtors of a symmetric tridiagonal matri correspond to user specified eigenvalues. psstein does not pzstein computes the eigeNVECtors of a symmetric tridiagonal matri correspond to user specified eigenvalues. pzstein does not |
| NVS NVS 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 |