PZLAPV2(l)
πΈ NAME πΈ
PZLAPV2 β bestie, this one applies either P (the permutation matrix that IPIV is pointing at) or inv( P ) to a M-by-N distributed matrix sub( A ) (which is shorthand for A(IA:IA+M-1,JA:JA+N-1)), and it comes out the other side as row or column pivoting. That's it, that's the whole thing, and honestly? iconic. π
β¨ SYNOPSIS β¨
SUBROUTINE PZLAPV2( DIREC, ROWCOL, M, N, A, IA, JA, DESCA, IPIV, IP, JP,
DESCIP )
CHARACTER DIREC, ROWCOL
INTEGER IA, IP, JA, JP, M, N
INTEGER DESCA( * ), DESCIP( * ), IPIV( * )
COMPLEX*16 A( * )
Look at those arguments. So many. We love a thorough queen. π
π¦ PURPOSE π¦
PZLAPV2 applies either P (that's the permutation matrix indicated by IPIV) or inv( P ) to a M-by-N distributed matrix sub( A ), which means A(IA:IA+M-1,JA:JA+N-1), and the result is row or column pivoting. Slay.
Real talk though: the pivot vector should be aligned with the distributed matrix A. For pivoting the rows of sub( A ), IPIV should be distributed along a process column and replicated over all process rows. Similarly, for column pivoting, IPIV should be distributed along a process row and replicated over all process columns. No cap. π«Ά
π Notes π
Every global data object is described by an associated description vector, periodt. This vector stores all the info you need to establish the mapping between an object element and its corresponding process and memory location. It's giving personal assistant for arrays.
Let A be a generic term for any 2D block cyclicly distributed array. Such a global array has an associated description vector DESCA. In the following comments, the character _ should be read as "of the global array".
DTYPE_A(global) β stored inDESCA( DTYPE_ )β the descriptor type. In this case,DTYPE_A = 1.CTXT_A(global) β stored inDESCA( CTXT_ )β the BLACS context handle, indicating the BLACS process gridAis distributed over. The context itself is global, but the handle (the integer value) may vary.M_A(global) β stored inDESCA( M_ )β the number of rows in the global arrayA.N_A(global) β stored inDESCA( N_ )β the number of columns in the global arrayA.MB_A(global) β stored inDESCA( MB_ )β the blocking factor used to distribute the rows of the array.NB_A(global) β stored inDESCA( NB_ )β the blocking factor used to distribute the columns of the array.RSRC_A(global) β stored inDESCA( RSRC_ )β the process row over which the first row of the arrayAis distributed.CSRC_A(global) β stored inDESCA( CSRC_ )β the process column over which the first column of the arrayAis distributed.LLD_A(local) β stored inDESCA( LLD_ )β the leading dimension of the local array.LLD_A >= MAX(1,LOCr(M_A)).
Let K be the number of rows or columns of a distributed matrix, and assume that its process grid has dimension p x q.
LOCr( K ) denotes the number of elements of K that a process would receive if K were distributed over the p processes of its process column.
Similarly, LOCc( K ) denotes the number of elements of K that a process would receive if K were distributed over the q processes of its process row.
The values of LOCr() and LOCc() may be determined via a call to the ScaLAPACK tool function, NUMROC:
LOCr( M ) = NUMROC( M, MB_A, MYROW, RSRC_A, NPROW ),
LOCc( N ) = NUMROC( N, NB_A, MYCOL, CSRC_A, NPCOL ).
An upper bound for these quantities may be computed by:
LOCr( M ) <= ceil( ceil(M/MB_A)/NPROW )*MB_A
LOCc( N ) <= ceil( ceil(N/NB_A)/NPCOL )*NB_A
math but make it cute β¨
π ARGUMENTS π
DIRECβ (global input)CHARACTER. Specifies in which order the permutation is applied:= 'F'(Forward) β applies pivots Forward from top of matrix. ComputesP * sub( A ).= 'B'(Backward) β applies pivots Backward from bottom of matrix. Computesinv( P ) * sub( A ).
ROWCOLβ (global input)CHARACTER. Specifies if the rows or columns are to be permuted:= 'R'β Rows will be permuted.= 'C'β Columns will be permuted.
Mβ (global input)INTEGER. The number of rows to be operated on, i.e. the number of rows of the distributed submatrixsub( A ).M >= 0.Nβ (global input)INTEGER. The number of columns to be operated on, i.e. the number of columns of the distributed submatrixsub( A ).N >= 0.Aβ (local input/local output)COMPLEX*16pointer into the local memory to an array of dimension(LLD_A, LOCc(JA+N-1)). On entry, this local array contains the local pieces of the distributed matrixsub( A )to which the row or columns interchanges will be applied. On exit, this array contains the local pieces of the permuted distributed matrix. it goes in one way and comes out the other, that's the whole arc πIAβ (global input)INTEGER. The row index in the global arrayAindicating the first row ofsub( A ).JAβ (global input)INTEGER. The column index in the global arrayAindicating the first column ofsub( A ).DESCAβ (global and local input)INTEGERarray of dimensionDLEN_. The array descriptor for the distributed matrixA.IPIVβ (input)INTEGERarray, dimension>= LOCr(M_A)+MB_AifROWCOL = 'R',LOCc(N_A)+NB_Aotherwise. It contains the pivoting information.IPIV(i)is the global row (column), local row (column)iwas swapped with. The last piece of the array of sizeMB_A(resp.NB_A) is used as workspace.IPIVis tied to the distributed matrixA.IPβ (global input)INTEGER.IPIV's global row index, which points to the beginning of the submatrix which is to be operated on.JPβ (global input)INTEGER.IPIV's global column index, which points to the beginning of the submatrix which is to be operated on.DESCIPβ (global and local input)INTEGERarray of dimension8. The array descriptor for the distributed matrixIPIV.
Heads up bestie:IPIVneeds that extraMB_A(orNB_A) chunk at the end for workspace, so don't skimp on the dimension or it's giving undefined behaviour. π
And that's the whole page, babe. This one's from LAPACK version 1.5, dated 12 May 1997 β yes, it's older than us, and it's still serving. π PZLAPV2(l), out. πβ¨
π¦ where this page comes from
- ubuntu jammy: scalapack-doc 1.5-11
- π girlified by deepseek-ai/DeepSeek-V4.1-Flash on : a language model's rewrite of the original, under its terms