PSLAPV2(l)
π NAME π
PSLAPV2 β okay bestie, this one applies either P (the permutation matrix that IPIV is telling you about) or inv( P ) to an M-by-N distributed matrix sub( A ), which is giving
A(IA:IA+M-1,JA:JA+N-1)
and the result is row or column pivoting. slay.
β¨ SYNOPSIS β¨
SUBROUTINE PSLAPV2( 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( * )
REAL A( * )
π PURPOSE π
So like, PSLAPV2 applies either P (that's the permutation matrix indicated by IPIV) or inv( P ) to an M-by-N distributed matrix sub( A ) denoting A(IA:IA+M-1,JA:JA+N-1), and the whole thing results in row or column pivoting. The pivot vector should be aligned with the distributed matrix A β no cap, that part is non-negotiable.
For pivoting the rows of sub( A ), IPIV should be distributed along a process column and replicated over all process rows. Similarly, IPIV should be distributed along a process row and replicated over all process columns for column pivoting. it's giving symmetry, it's giving structure. π
π Notes π
Every global data object is described by an associated description vector, and that vector stores all the info you need to establish the mapping between an object element and its corresponding process and memory location.
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". iykyk.
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. πM_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
π¦ ARGUMENTS π¦
DIRECβ (global input)CHARACTER. Specifies in which order the permutation is applied:= 'F'(Forward) applies pivots Forward from top of matrix. ComputesP * sub( A );= 'B'(Backward) applies pivots Backward from bottom of matrix. Computesinv( P ) * sub( A ). pick your fighter bestie βROWCOLβ (global input)CHARACTER. Specifies if the rows or columns are to be permuted:= 'R'Rows will be permuted,= 'C'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)REALpointer 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. main character energy honestly 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. π«ΆIPβ (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.
and that's the whole page, bestie π no notes, you ate, periodt.
this was LAPACK version 1.5, dated 12 May 1997 β iconic behavior from a routine older than most of us, and she still serves. 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