PDLARFB(l)
π PDLARFB(l) π
okay bestie, welcome to the glow-up zone β¨ this is a page from the LAPACK auxiliary routine collection, version 1.5, and we're about to make block reflectors feel like a group chat π«Ά
β¨ NAME β¨
PDLARFB β applie a real block reflector Q or its transpose Q**T to a real distributed M-by-N matrix sub( C ) = C(IC:IC+M-1,JC:JC+N-1)
(yes, "applie", we don't judge, we stan a vintage typo π )
π¦ SYNOPSIS π¦
SUBROUTINE PDLARFB( SIDE, TRANS, DIRECT, STOREV, M, N, K, V, IV, JV,
DESCV, T, C, IC, JC, DESCC, WORK )
CHARACTER SIDE, TRANS, DIRECT, STOREV
INTEGER IC, IV, JC, JV, K, M, N
INTEGER DESCC( * ), DESCV( * )
DOUBLE PRECISION C( * ), T( * ), V( * ), WORK( * )
π₯ PURPOSE π₯
So like. PDLARFB applies a real block reflector Q or its transpose Q**T to a real distributed M-by-N matrix sub( C ) = C(IC:IC+M-1,JC:JC+N-1) β from the left or from the right. Left or right, it's giving main character energy either way π
π Notes
okay this is the part where you sit down and pay attention because the notation is a whole vibe and it's important, fr fr π«Ά
Every 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_ ): the descriptor type. In this case,DTYPE_A = 1.CTXT_A(global) β stored inDESCA( CTXT_ ): 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_ ): the number of rows in the global arrayA.N_A(global) β stored inDESCA( N_ ): the number of columns in the global arrayA.MB_A(global) β stored inDESCA( MB_ ): the blocking factor used to distribute the rows of the array.NB_A(global) β stored inDESCA( NB_ ): the blocking factor used to distribute the columns of the array.RSRC_A(global) β stored inDESCA( RSRC_ ): the process row over which the first row of the arrayAis distributed.CSRC_A(global) β stored inDESCA( CSRC_ ): the process column over which the first column of the arrayAis distributed.LLD_A(local) β stored inDESCA( LLD_ ): 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
okay here comes the whole cast, everybody gets a moment π
SIDEβ (global input)CHARACTER= 'L': applyQorQ**Tfrom the Left;= 'R': applyQorQ**Tfrom the Right.
TRANSβ (global input)CHARACTER= 'N': No transpose, applyQ;= 'T': Transpose, applyQ**T.
DIRECTβ (global input)CHARACTERIndicates howQis formed from a product of elementary reflectors= 'F':Q = H(1) H(2) . . . H(k)(Forward)= 'B':Q = H(k) . . . H(2) H(1)(Backward)
STOREVβ (global input)CHARACTERIndicates how the vectors which define the elementary reflectors are stored:= 'C': Columnwise= 'R': Rowwise
Mβ (global input)INTEGERThe number of rows to be operated on i.e the number of rows of the distributed submatrixsub( C ).M >= 0.Nβ (global input)INTEGERThe number of columns to be operated on i.e the number of columns of the distributed submatrixsub( C ).N >= 0.Kβ (global input)INTEGERThe order of the matrixT(= the number of elementary reflectors whose product defines the block reflector).Vβ (local input)DOUBLE PRECISIONpointer into the local memory to an array of dimension( LLD_V, LOCc(JV+K-1) )ifSTOREV = 'C',( LLD_V, LOCc(JV+M-1))ifSTOREV = 'R'andSIDE = 'L',( LLD_V, LOCc(JV+N-1) )ifSTOREV = 'R'andSIDE = 'R'. It contains the local pieces of the distributed vectorsVrepresenting the Householder transformation. See further details. IfSTOREV = 'C'andSIDE = 'L',LLD_V >= MAX(1,LOCr(IV+M-1)); ifSTOREV = 'C'andSIDE = 'R',LLD_V >= MAX(1,LOCr(IV+N-1)); ifSTOREV = 'R',LLD_V >= LOCr(IV+K-1).IVβ (global input)INTEGERThe row index in the global arrayVindicating the first row ofsub( V ).JVβ (global input)INTEGERThe column index in the global arrayVindicating the first column ofsub( V ).DESCVβ (global and local input)INTEGERarray of dimensionDLEN_. The array descriptor for the distributed matrixV.Tβ (local input)DOUBLE PRECISIONarray, dimensionMB_VbyMB_VifSTOREV = 'R'andNB_VbyNB_VifSTOREV = 'C'. The triangular matrixTin the representation of the block reflector.Cβ (local input/local output)DOUBLE PRECISIONpointer into the local memory to an array of dimension(LLD_C,LOCc(JC+N-1)). On entry, the M-by-N distributed matrixsub( C ). On exit,sub( C )is overwritten byQ*sub( C )orQ'*sub( C )orsub( C )*Qorsub( C )*Q'.ICβ (global input)INTEGERThe row index in the global arrayCindicating the first row ofsub( C ).JCβ (global input)INTEGERThe column index in the global arrayCindicating the first column ofsub( C ).DESCCβ (global and local input)INTEGERarray of dimensionDLEN_. The array descriptor for the distributed matrixC.WORKβ (local workspace)DOUBLE PRECISIONarray, dimension(LWORK)
If STOREV = 'C',
if SIDE = 'L', LWORK >= ( NqC0 + MpC0 ) * K
else if SIDE = 'R', LWORK >= ( NqC0 + MAX( NpV0 + NUMROC(
NUMROC( N+ICOFFC, NB_V, 0, 0, NPCOL ), NB_V, 0, 0, LCMQ ),
MpC0 ) ) * K
end if
else if STOREV = 'R',
if SIDE = 'L', LWORK >= ( MpC0 + MAX( MqV0 + NUMROC( NUMROC(
M+IROFFC, MB_V, 0, 0, NPROW ), MB_V, 0, 0, LCMP ), NqC0 ) ) * K
else if SIDE = 'R', LWORK >= ( MpC0 + NqC0 ) * K
end if
end if
where LCMQ = LCM / NPCOL with LCM = ICLM( NPROW, NPCOL ),
IROFFV = MOD( IV-1, MB_V ), ICOFFV = MOD( JV-1, NB_V ),
IVROW = INDXG2P( IV, MB_V, MYROW, RSRC_V, NPROW ),
IVCOL = INDXG2P( JV, NB_V, MYCOL, CSRC_V, NPCOL ),
MqV0 = NUMROC( M+ICOFFV, NB_V, MYCOL, IVCOL, NPCOL ),
NpV0 = NUMROC( N+IROFFV, MB_V, MYROW, IVROW, NPROW ),
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 ),
NpC0 = NUMROC( N+ICOFFC, 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.
π Alignment requirements π
The distributed submatrices V(IV:*, JV:*) and C(IC:IC+M-1,JC:JC+N-1) must verify some alignment properties, namely the following expressions should be true:
If STOREV = 'Columnwise'
If SIDE = 'Left', ( MB_V.EQ.MB_C .AND. IROFFV.EQ.IROFFC .AND. IVROW.EQ.ICROW )
If SIDE = 'Right', ( MB_V.EQ.NB_C .AND. IROFFV.EQ.ICOFFC )
else if STOREV = 'Rowwise'
If SIDE = 'Left', ( NB_V.EQ.MB_C .AND. ICOFFV.EQ.IROFFC )
If SIDE = 'Right', ( NB_V.EQ.NB_C .AND. ICOFFV.EQ.ICOFFC .AND. IVCOL.EQ.ICCOL )
end if
bestie if those alignment expressions aren't true, that's not a vibe check you're gonna pass π double check them before you ship, no cap.
πΈ and that's the whole page!! πΈ
This one's from LAPACK version 1.5, dated 12 May 1997 β an absolute icon, a legend, a piece of history, and it ate. periodt ππ¦β¨
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