PCGEQR2(l)
π PCGEQR2 π
okay bestie, welcome to the PCGEQR2(l) page π she's a LAPACK routine, version 1.5, and she does QR factorization on a complex distributed matrix. buckle up, it's giving linear algebra but make it cute β¨
πΈ NAME πΈ
PCGEQR2 β compute a QR factorization of a complex distributed M-by-N matrix sub( A ) = A(IA:IA+M-1,JA:JA+N-1) = Q * R π
π¦ SYNOPSIS π¦
SUBROUTINE PCGEQR2( M, N, A, IA, JA, DESCA, TAU, WORK, LWORK, INFO )
INTEGER IA, INFO, JA, LWORK, M, N
INTEGER DESCA( * )
COMPLEX A( * ), TAU( * ), WORK( * )
β¨ PURPOSE β¨
PCGEQR2 computes a QR factorization of a complex distributed M-by-N matrix sub( A ) = A(IA:IA+M-1,JA:JA+N-1) = Q * R. that's the whole assignment, and she ate π₯
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. (translation: the descriptor is the group chat that tells everyone where their pieces live π«Ά)
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". iykyk π
Here's the whole cast, no cap:
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«Ά ARGUMENTS π«Ά
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) COMPLEX pointer 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)by N upper trapezoidal matrixR(Ris upper triangular ifM >= N); the elements below the diagonal, with the arrayTAU, represent the unitary matrixQas a product of elementary reflectors (see Further Details). she really said "input AND output", versatile queen 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) INTEGER array of dimensionDLEN_. The array descriptor for the distributed matrixA.TAUβ (local output) COMPLEX, array, dimensionLOCc(JA+MIN(M,N)-1). This array contains the scalar factorsTAUof the elementary reflectors.TAUis tied to the distributed matrixA. πWORKβ (local workspace/local output) COMPLEX array, 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. (yes bestie, the -1 thing is the classic "just tell me how much space you need, no drama" move π)
INFOβ (local output) INTEGER.= 0: successful exit π< 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 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 complex scalar, and v is a complex 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).
real talk: the reflector storage is the thing to remember here, bestie.vlives below the diagonal,taulives inTAU, and that's the whole recipe. no cap π§
and that's the page!! this iconic LAPACK routine is version 1.5, dated 12 May 1997 β old enough to be a period piece but she still slays π mwah, go factor something gorgeous πΈβ¨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