PSLARF(l)
β¨ NAME β¨
PSLARF applies a real elementary reflector Q (or Q**T) to a real M-by-N distributed matrix sub( C ) = C(IC:IC+M-1,JC:JC+N-1), from either the left or the right. π
πΈ SYNOPSIS πΈ
SUBROUTINE PSLARF( SIDE, M, N, V, IV, JV, DESCV, INCV, TAU, C, IC, JC,
DESCC, WORK )
CHARACTER SIDE
INTEGER IC, INCV, IV, JC, JV, M, N
INTEGER DESCC( * ), DESCV( * )
REAL C( * ), TAU( * ), V( * ), WORK( * )
π PURPOSE π
So PSLARF takes a real elementary reflector Q (or Q**T) and applies it to a real M-by-N distributed matrix sub( C ) = C(IC:IC+M-1,JC:JC+N-1), either from the left or from the right. Iconic behavior, no notes.
Q is represented in the form
Q = I - tau * v * v'
where tau is a real scalar and v is a real vector. π¦
If tau = 0, then Q is taken to be the unit matrix. The math said "no thoughts, identity only."
π Notes
Every global data object is described by an associated description vector. This vector stores the info you need to establish the mapping between an object element and its corresponding process and memory location. Bestie, it's the group chat roster of your array. π
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".
Here's the whole lore drop:
DTYPE_A(global) βDESCA( DTYPE_ )β the descriptor type. In this case,DTYPE_A = 1.CTXT_A(global) βDESCA( 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) βDESCA( M_ )β the number of rows in the global arrayA.N_A(global) βDESCA( N_ )β the number of columns in the global arrayA.MB_A(global) βDESCA( MB_ )β the blocking factor used to distribute the rows of the array.NB_A(global) βDESCA( NB_ )β the blocking factor used to distribute the columns of the array.RSRC_A(global) βDESCA( RSRC_ )β the process row over which the first row of the arrayAis distributed.CSRC_A(global) βDESCA( CSRC_ )β the process column over which the first column of the arrayAis distributed.LLD_A(local) βDESCA( 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
Because vectors may be viewed as a subclass of matrices, a distributed vector is considered to be a distributed matrix. Yes, a vector is a matrix in a little outfit. Slay. π
π¨ Restrictions
Pay attention, this is the part where it gets picky. π«Ά
If SIDE = 'Left' and INCV = 1, then the row process having the first entry V(IV,JV) must also have the first row of sub( C ). Moreover, MOD(IV-1,MB_V) must be equal to MOD(IC-1,MB_C), if INCV=M_V, only the last equality must be satisfied.
If SIDE = 'Right' and INCV = M_V then the column process having the first entry V(IV,JV) must also have the first column of sub( C ) and MOD(JV-1,NB_V) must be equal to MOD(JC-1,NB_C), if INCV = 1 only the last equality must be satisfied.
These are not vibes-based suggestions. If your alignment is off, the routine will simply not have a good time. π
π ARGUMENTS π
SIDEβ (global input)CHARACTER= 'L': formQ * sub( C ),= 'R': formsub( C ) * Q,Q = Q**T.
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.Vβ (local input)REALpointer into the local memory to an array of dimension(LLD_V,*)containing the local pieces of the distributed vectorsVrepresenting the Householder transformationQ,
V(IV:IV+M-1,JV) if SIDE = 'L' and INCV = 1,
V(IV,JV:JV+M-1) if SIDE = 'L' and INCV = M_V,
V(IV:IV+N-1,JV) if SIDE = 'R' and INCV = 1,
V(IV,JV:JV+N-1) if SIDE = 'R' and INCV = M_V,
The vector v in the representation of Q. V is not used if TAU = 0.
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.INCVβ (global input)INTEGERThe global increment for the elements ofV. Only two values ofINCVare supported in this version, namely1andM_V.INCVmust not be zero.TAUβ (local input)REAL, array, dimensionLOCc(JV)ifINCV = 1, andLOCr(IV)otherwise. This array contains the Householder scalars related to the Householder vectors.TAUis tied to the distributed matrixV.Cβ (local input/local output)REALpointer into the local memory to an array of dimension(LLD_C, LOCc(JC+N-1) ), containing the local pieces ofsub( C ). On exit,sub( C )is overwritten by theQ * sub( C )ifSIDE = 'L', orsub( C ) * QifSIDE = 'R'.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)REALarray, dimension(LWORK)
If INCV = 1, if SIDE = 'L', if IVCOL = ICCOL, LWORK >= NqC0 else
LWORK >= MpC0 + MAX( 1, NqC0 ) end if else if SIDE = 'R', LWORK
>= NqC0 + MAX( MAX( 1, MpC0 ), NUMROC( NUMROC(
N+ICOFFC,NB_V,0,0,NPCOL ),NB_V,0,0,LCMQ ) ) end if else if INCV
= M_V, if SIDE = 'L', LWORK >= MpC0 + MAX( MAX( 1, NqC0 ),
NUMROC( NUMROC( M+IROFFC,MB_V,0,0,NPROW ),MB_V,0,0,LCMP ) ) else
if SIDE = 'R', if IVROW = ICROW, LWORK >= MpC0 else LWORK >=
NqC0 + MAX( 1, MpC0 ) end if end if end if
where:
LCMis the least common multiple ofNPROWandNPCOLandLCM = ILCM( NPROW, NPCOL ),LCMP = LCM / NPROW,LCMQ = LCM / 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,INDXG2PandNUMROCare ScaLAPACK tool functions;MYROW,MYCOL,NPROWandNPCOLcan be determined by calling the subroutineBLACS_GRIDINFO.
π Alignment requirements
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:
MB_V = NB_V,
If INCV = 1, If SIDE = 'Left', ( MB_V.EQ.MB_C .AND.
IROFFV.EQ.IROFFC .AND. IVROW.EQ.ICROW ) If SIDE = 'Right', (
MB_V.EQ.NB_A .AND. MB_V.EQ.NB_C .AND. IROFFV.EQ.ICOFFC ) else if
INCV = M_V, If SIDE = 'Left', ( MB_V.EQ.NB_V .AND. MB_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
And that's the whole page, bestie!! π PSLARF(l) came straight out of LAPACK version 1.5, dated 12 May 1997 β yes she's an elder icon and she still eats. Go forth and distribute your reflectors responsibly. πβ¨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