PSGEQR2(l)
β¨ PSGEQR2(l) β the QR factorization glow-up, distributed edition β¨
okay bestie, gather round π this is PSGEQR2, a LAPACK routine (the .l suffix is the ScaLAPACK/parallel-flavored one, iykyk), and she is that girl when it comes to QR factorizations of real distributed matrices. no cap.
πΈ NAME πΈ
PSGEQR2 β compute a QR factorization of a real distributed M-by-N matrix
sub( A ) = A(IA:IA+M-1,JA:JA+N-1) = Q * R
periodt. π
π SYNOPSIS π
SUBROUTINE PSGEQR2( M, N, A, IA, JA, DESCA, TAU, WORK, LWORK, INFO )
INTEGER IA, INFO, JA, LWORK, M, N
INTEGER DESCA( * )
REAL A( * ), TAU( * ), WORK( * )
π¦ PURPOSE π¦
PSGEQR2 computes a QR factorization of a real distributed M-by-N matrix
sub( A ) = A(IA:IA+M-1,JA:JA+N-1) = Q * R.
like, that's the whole job. she does it, she does it well, she leaves. π
π Notes π
ok so before we get into it, you have to understand descriptors, because every global data object here rolls with an associated description vector. this vector is basically the group chat where all the info about how an object element maps to its process + memory location lives. no descriptor, no mapping, no slay.
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". (yes literally. she's saying "the M of the global array A". iconic shorthand. π
)
here's the whole roster, and bestie every single one of these matters:
DTYPE_A(global) β stored inDESCA( DTYPE_ ). this is the descriptor type. in this case,DTYPE_A = 1.CTXT_A(global) β stored inDESCA( CTXT_ ). the BLACS context handle, indicating the BLACS process gridAis 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)).
now 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
write that down. fr fr. π
π ARGUMENTS π
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, the local pieces of the M-by-N distributed matrixsub( A )which is to be factored. on exit, the elements on and above the diagonal ofsub( A )contain themin(M,N)byNupper trapezoidal matrixR(Ris upper triangular ifM >= N); the elements below the diagonal, with the arrayTAU, represent the orthogonal matrixQas a product of elementary reflectors (see Further Details). 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.TAUβ (local output)REAL, array, dimensionLOCc(JA+MIN(M,N)-1). this array contains the scalar factorsTAUof the elementary reflectors.TAUis tied to the distributed matrixA. (they're a package deal, don't separate them π«Ά)WORKβ (local workspace/local output)REALarray, dimension(LWORK). on exit,WORK(1)returns the minimal and optimalLWORK.LWORKβ (local or global input)INTEGER. the dimension of the arrayWORK.LWORKis local input and must be at leastLWORK >= Mp0 + MAX( 1, Nq0 ), where
IROFF = MOD( IA-1, MB_A ), ICOFF = MOD( JA-1, NB_A ), IAROW =
INDXG2P( IA, MB_A, MYROW, RSRC_A, NPROW ), IACOL = INDXG2P( JA,
NB_A, MYCOL, CSRC_A, NPCOL ), Mp0 = NUMROC( M+IROFF, MB_A,
MYROW, IAROW, NPROW ), Nq0 = NUMROC( N+ICOFF, NB_A, MYCOL,
IACOL, NPCOL ),
and NUMROC, INDXG2P 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.
π«Ά lowkey the most useful trick here: LWORK = -1 is the "just tell me how much room I need, bestie, I'm not committing yet" query. use it.
INFOβ (local output)INTEGER.= 0: successful exit β¨< 0: if thei-th argument is an array and thej-entry had an illegal value, thenINFO = -(i*100+j); if thei-th argument is a scalar and had an illegal value, thenINFO = -i.
π FURTHER DETAILS π
the matrix Q is represented as a product of elementary reflectors
Q = H(ja) H(ja+1) . . . H(ja+k-1), where k = min(m,n).
each H(i) has the form
H(j) = I - tau * v * v'
where tau is a real scalar, and v is a real vector with v(1:i-1) = 0 and v(i) = 1; v(i+1:m) is stored on exit in A(ia+i:ia+m-1,ja+i-1), and tau in TAU(ja+i-1).
like. she builds Q out of little reflector pieces and tucks the extra bits into A and TAU. iconic behavior, honestly. π¦β¨
and that's the whole page, bestie β LAPACK version 1.5, dated 12 May 1997. yes she's vintage, yes she still ate, no you may not skip the descriptor section. go forth and factor πππ
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