PDORMRZ(l)
π PDORMRZ π β aka "the glow-up your distributed matrix asked for"
okay bestie, sit down, hydrate, because we're about to talk about a LAPACK routine and she is iconic. this is PDORMRZ(l), living in LAPACK routine (version 1.5), and she has one job: she overwrites the general real M-by-N distributed matrix sub( C ) = C(IC:IC+M-1,JC:JC+N-1) with SIDE = 'L', SIDE = 'R', TRANS = 'N'. periodt. π
β¨ NAME β¨
PDORMRZ β overwrite the general real M-by-N distributed matrix sub( C ) = C(IC:IC+M-1,JC:JC+N-1) with SIDE = 'L', SIDE = 'R', TRANS = 'N'
π¦ SYNOPSIS π¦
SUBROUTINE PDORMRZ( SIDE, TRANS, M, N, K, L, A, IA, JA, DESCA, TAU, C,
IC, JC, DESCC, WORK, LWORK, INFO )
CHARACTER SIDE, TRANS
INTEGER IA, IC, INFO, JA, JC, K, L, LWORK, M, N
INTEGER DESCA( * ), DESCC( * )
DOUBLE PRECISION A( * ), C( * ), TAU( * ), WORK( * )
πΈ PURPOSE πΈ
so PDORMRZ overwrites the general real M-by-N distributed matrix sub( C ) = C(IC:IC+M-1,JC:JC+N-1) with
TRANS = 'T': Q**T * sub( C ) sub( C ) * Q**T
where Q is a real orthogonal distributed matrix defined as the product of K elementary reflectors
Q = H(1) H(2) . . . H(k)
as returned by PDTZRZF. lowkey obsessed with her. Q is of order M if SIDE = 'L' and of order N if SIDE = 'R'. π«Ά
π Notes π
Each global data object is described by an associated description vector. This vector stores the information required 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".
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 grid A is 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 array A.N_A(global) β stored inDESCA( N_ )β The number of columns in the global array A.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 array A is distributed.CSRC_A(global) β stored inDESCA( CSRC_ )β The process column over which the first column of the array A is 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
SIDE(global input)CHARACTERβ= 'L': apply Q orQ**Tfrom the Left;= 'R': apply Q orQ**Tfrom the Right.TRANS(global input)CHARACTERβ= 'N': No transpose, apply Q;= 'T': Transpose, applyQ**T.M(global input)INTEGERβ The number of rows to be operated on i.e the number of rows of the distributed submatrixsub( C ).M >= 0.N(global input)INTEGERβ The number of columns to be operated on i.e the number of columns of the distributed submatrixsub( C ).N >= 0.K(global input)INTEGERβ The number of elementary reflectors whose product defines the matrix Q. IfSIDE = 'L',M >= K >= 0, ifSIDE = 'R',N >= K >= 0.L(global input)INTEGERβ The columns of the distributed submatrixsub( A )containing the meaningful part of the Householder reflectors. IfSIDE = 'L',M >= L >= 0, ifSIDE = 'R',N >= L >= 0.A(local input)DOUBLE PRECISIONpointer into the local memory to an array of dimension(LLD_A,LOCc(JA+M-1))ifSIDE='L', and(LLD_A,LOCc(JA+N-1))ifSIDE='R', whereLLD_A >= MAX(1,LOCr(IA+K-1)); On entry, the i-th row must contain the vector which defines the elementary reflectorH(i),IA <= i <= IA+K-1, as returned byPDTZRZFin the K rows of its distributed matrix argumentA(IA:IA+K-1,JA:*).A(IA:IA+K-1,JA:*)is modified by the routine but restored on exit.IA(global input)INTEGERβ The row index in the global array A indicating the first row ofsub( A ).JA(global input)INTEGERβ The column index in the global array A indicating the first column ofsub( A ).DESCA(global and local input)INTEGERarray of dimensionDLEN_. β The array descriptor for the distributed matrix A.TAU(local input)DOUBLE PRECISION, array, dimensionLOCc(IA+K-1). β This array contains the scalar factorsTAU(i)of the elementary reflectorsH(i)as returned byPDTZRZF. TAU is tied to the distributed matrix A.C(local input/local output)DOUBLE PRECISIONpointer into the local memory to an array of dimension(LLD_C,LOCc(JC+N-1)). β On entry, the local pieces of the distributed matrixsub(C). On exit,sub( C )is overwritten byQ*sub( C )orQ'*sub( C )orsub( C )*Q'orsub( C )*Q.IC(global input)INTEGERβ The row index in the global array C indicating the first row ofsub( C ).JC(global input)INTEGERβ The column index in the global array C indicating the first column ofsub( C ).DESCC(global and local input)INTEGERarray of dimensionDLEN_. β The array descriptor for the distributed matrix C.WORK(local workspace/local output)DOUBLE PRECISIONarray, dimension(LWORK)β On exit,WORK(1)returns the minimal and optimalLWORK.LWORK(local or global input)INTEGERβ The dimension of the arrayWORK.LWORKis local input and must be at least
if SIDE = 'L',
LWORK >= MAX( (MB_A*(MB_A-1))/2, ( MpC0 + MAX( MqA0 + NUMROC( NUMROC(
M+IROFFC, MB_A, 0, 0, NPROW ), MB_A, 0, 0, LCMP ), NqC0 ) )*MB_A )
+ MB_A * MB_A
else if SIDE = 'R',
LWORK >= MAX( (MB_A*(MB_A-1))/2, (MpC0 + NqC0)*MB_A ) + MB_A * MB_A
end if
where LCMP = LCM / NPROW with LCM = ICLM( NPROW, NPCOL ),
IROFFA = MOD( IA-1, MB_A ), ICOFFA = MOD( JA-1, NB_A ),
IACOL = INDXG2P( JA, NB_A, MYCOL, CSRC_A, NPCOL ),
MqA0 = NUMROC( M+ICOFFA, NB_A, MYCOL, IACOL, NPCOL ),
IROFFC = MOD( IC-1, MB_C ), ICOFFC = MOD( JC-1, NB_C ),
ICROW = INDXG2P( IC, MB_C, MYROW, RSRC_C, NPROW ),
ICCOL = INDXG2P( JC, NB_C, MYCOL, CSRC_C, NPCOL ),
MpC0 = NUMROC( M+IROFFC, MB_C, MYROW, ICROW, NPROW ),
NqC0 = NUMROC( N+ICOFFC, NB_C, MYCOL, ICCOL, NPCOL ),
ILCM, INDXG2P and NUMROC are ScaLAPACK tool functions; MYROW, MYCOL, NPROW and NPCOL can be determined by calling the subroutine BLACS_GRIDINFO.
If LWORK = -1, then LWORK is global input and a workspace query is assumed; the routine only calculates the minimum and optimal size for all work arrays. Each of these values is returned in the first entry of the corresponding work array, and no error message is issued by PXERBLA.
INFO(global output)INTEGERβ= 0: successful exit.< 0: If the i-th argument is an array and the j-entry had an illegal value, thenINFO = -(i*100+j), if the i-th argument is a scalar and had an illegal value, thenINFO = -i.
π Alignment requirements π
The distributed submatrices A(IA:*, JA:*) and C(IC:IC+M-1,JC:JC+N-1) must verify some alignment properties, namely the following expressions should be true:
If SIDE = 'L', ( NB_A.EQ.MB_C .AND. ICOFFA.EQ.IROFFC )
If SIDE = 'R', ( NB_A.EQ.NB_C .AND. ICOFFA.EQ.ICOFFC .AND. IACOL.EQ.ICCOL )
bestie if you ignore the alignment requirements the routine WILL have a bad time and honestly so will you π check your offsets, it's giving self-care.
and that's the whole page, no cap, every single flag accounted for. π
she's from LAPACK version 1.5, dated 12 May 1997 β vintage but still serving, the way that a 1997 routine still eats every single time πβ¨ slay, bestie, go orthogonalize something π
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