PCUNMHR(l)
π PCUNMHR π
okay bestie, sit down, hydrate, because we're doing a LAPACK routine today. this is PCUNMHR from LAPACK, version 1.5, and it is so much. it's giving distributed linear algebra, it's giving block cyclic realness, it's giving "I apply elementary reflectors to your matrix and you say thank you." no cap. π¦
β¨ NAME β¨
PCUNMHR β overwrite the general complex 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 PCUNMHR( SIDE, TRANS, M, N, ILO, IHI, A, IA, JA, DESCA, TAU,
C, IC, JC, DESCC, WORK, LWORK, INFO )
CHARACTER SIDE, TRANS
INTEGER IA, IC, IHI, ILO, INFO, JA, JC, LWORK, M, N
INTEGER DESCA( * ), DESCC( * )
COMPLEX A( * ), C( * ), TAU( * ), WORK( * )
πΈ PURPOSE πΈ
PCUNMHR overwrites the general complex M-by-N distributed matrix sub( C ) = C(IC:IC+M-1,JC:JC+N-1) with
TRANS = 'C': Q**H * sub( C )
sub( C ) * Q**H
where Q is a complex unitary distributed matrix of order nq, with nq = m if SIDE = 'L' and nq = n if SIDE = 'R'. Q is defined as the product of IHI-ILO elementary reflectors, as returned by PCGEHRD:
Q = H(ilo) H(ilo+1) . . . H(ihi-1).
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".
so here's the whole little glossary, bestie, in bullet form because we're not doing table vibes today:
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₯
every single one of them, no skipping, we're eating the whole plate π
SIDE(global input)CHARACTERβ= 'L': apply Q or QH from the Left;= 'R': apply Q or QH from the Right.TRANS(global input)CHARACTERβ= 'N': No transpose, apply Q;= 'C': Conjugate transpose, apply Q**H.M(global input)INTEGERβ the number of rows to be operated on i.e the number of rows of the distributed submatrix sub( C ).M >= 0.N(global input)INTEGERβ the number of columns to be operated on i.e the number of columns of the distributed submatrix sub( C ).N >= 0.ILO(global input)INTEGERandIHI(global input)INTEGERβ ILO and IHI must have the same values as in the previous call ofPCGEHRD. Q is equal to the unit matrix except in the distributed submatrixQ(ia+ilo:ia+ihi-1,ia+ilo:ja+ihi-1). IfSIDE = 'L',1 <= ILO <= IHI <= max(1,M); ifSIDE = 'R',1 <= ILO <= IHI <= max(1,N); ILO and IHI are relative indexes.A(local input)COMPLEXpointer 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'. The vectors which define the elementary reflectors, as returned byPCGEHRD.IA(global input)INTEGERβ the row index in the global array A indicating the first row of sub( A ).JA(global input)INTEGERβ the column index in the global array A indicating the first column of sub( A ).DESCA(global and local input)INTEGERarray of dimensionDLEN_. The array descriptor for the distributed matrix A.TAU(local input)COMPLEX, array, dimensionLOCc(JA+M-2)ifSIDE = 'L', andLOCc(JA+N-2)ifSIDE = 'R'. This array contains the scalar factorsTAU(j)of the elementary reflectorsH(j)as returned byPCGEHRD. TAU is tied to the distributed matrix A.C(local input/local output)COMPLEXpointer into the local memory to an array of dimension(LLD_C,LOCc(JC+N-1)). On entry, the local pieces of the distributed matrix sub(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 of sub( C ).JC(global input)INTEGERβ the column index in the global array C indicating the first column of sub( C ).DESCC(global and local input)INTEGERarray of dimensionDLEN_. The array descriptor for the distributed matrix C.WORK(local workspace/local output)COMPLEXarray, dimension(LWORK). On exit,WORK(1)returns the minimal and optimal LWORK.LWORK(local or global input)INTEGERβ the dimension of the array WORK. LWORK is local input and must be at least
IAA = IA + ILO; JAA = JA+ILO-1; If SIDE = 'L', MI = IHI-ILO; NI
= N; ICC = IC + ILO; JCC = JC; LWORK >= MAX( (NB_A*(NB_A-1))/2,
(NqC0 + MpC0)*NB_A ) + NB_A * NB_A else if SIDE = 'R', MI = M;
NI = IHI-ILO; ICC = IC; JCC = JC + ILO; LWORK >= MAX(
(NB_A*(NB_A-1))/2, ( NqC0 + MAX( NpA0 + NUMROC( NUMROC(
NI+ICOFFC, NB_A, 0, 0, NPCOL ), NB_A, 0, 0, LCMQ ), MpC0 )
)*NB_A ) + NB_A * NB_A end if
where LCMQ = LCM / NPCOL with LCM = ICLM( NPROW, NPCOL ),
IROFFA = MOD( IAA-1, MB_A ), ICOFFA = MOD( JAA-1, NB_A ), IAROW
= INDXG2P( IAA, MB_A, MYROW, RSRC_A, NPROW ), NpA0 = NUMROC(
NI+IROFFA, MB_A, MYROW, IAROW, NPROW ),
IROFFC = MOD( ICC-1, MB_C ), ICOFFC = MOD( JCC-1, NB_C ), ICROW
= INDXG2P( ICC, MB_C, MYROW, RSRC_C, NPROW ), ICCOL = INDXG2P(
JCC, NB_C, MYCOL, CSRC_C, NPCOL ), MpC0 = NUMROC( MI+IROFFC,
MB_C, MYROW, ICROW, NPROW ), NqC0 = NUMROC( NI+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', ( MB_A.EQ.MB_C .AND. IROFFA.EQ.IROFFC .AND. IAROW.EQ.ICROW )
If SIDE = 'R', ( MB_A.EQ.NB_C .AND. IROFFA.EQ.ICOFFC )
bestie please actually check these alignment conditions, I am begging. the routine will not hold your hand and it will not be cute about it. π
and that's the whole page, mwah. π this was LAPACK, version 1.5, dated 12 May 1997 β yes she's an elder icon and she still serves. go forth, call your PCUNMHR, and stay aligned. periodt. β¨π¦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