PZLATRZ(l)
β¨ NAME β¨
PZLATRZ β bestie, this is the one that reduces the M-by-N ( M<=N ) complex upper trapezoidal matrix sub( A ) = [A(IA:IA+M-1,JA:JA+M-1) A(IA:IA+M-1,JA+N-L:JA+N-1)] π
π¦ SYNOPSIS π¦
SUBROUTINE PZLATRZ( M, N, L, A, IA, JA, DESCA, TAU, WORK )
INTEGER IA, JA, L, M, N
INTEGER DESCA( * )
COMPLEX*16 A( * ), TAU( * ), WORK( * )
πΈ PURPOSE πΈ
Okay so PZLATRZ takes that M-by-N ( M<=N ) complex upper trapezoidal matrix
sub( A ) = [A(IA:IA+M-1,JA:JA+M-1) A(IA:IA+M-1,JA+N-L:JA+N-1)]
and reduces it to upper triangular form using unitary transformations. It's giving glow-up, honestly.
The upper trapezoidal matrix sub( A ) gets factored as
sub( A ) = ( R 0 ) * Z,
where Z is an N-by-N unitary matrix and R is an M-by-M upper triangular matrix. Iconic behavior fr fr. π
π Notes π
Every global data object is described by an associated description vector. This vector stores all the info you need to map an object element to its corresponding process and memory location. It's the group chat of metadata, iykyk.
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 just that.)
Here's the whole notation breakdown, no cap:
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 gridAis 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 arrayA.N_A(global) β stored inDESCA( N_ )β the number of columns in the global arrayA.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 arrayAis distributed.CSRC_A(global) β stored inDESCA( CSRC_ )β the process column over which the first column of the arrayAis 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
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.Lβ (global input) INTEGER. The columns of the distributed submatrixsub( A )containing the meaningful part of the Householder reflectors.L > 0.Aβ (local input/local output) COMPLEX*16 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 leading M-by-M upper triangular part ofsub( A )contains the upper triangular matrixR, and elementsN-L+1toNof the first M rows ofsub( A ), with the arrayTAU, represent the unitary matrixZas a product of M elementary reflectors. β¨IAβ (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*16, array, dimensionLOCr(IA+M-1). This array contains the scalar factors of the elementary reflectors.TAUis tied to the distributed matrixA.WORKβ (local workspace) COMPLEX*16 array, dimension(LWORK).
LWORK >= Nq0 + MAX( 1, Mp0 ), 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.
π₯ FURTHER DETAILS π₯
The factorization is obtained by Householder's method. The kth transformation matrix, Z( k ), whose conjugate transpose is used to introduce zeros into the (m - k + 1)th row of sub( A ), is given in the form
Z( k ) = ( I 0 ),
( 0 T( k ) )
where
T( k ) = I - tau*u( k )*u( k )', u( k ) = ( 1 ),
( 0 )
( z( k ) )
tau is a scalar and z( k ) is an ( n - m ) element vector. tau and z( k ) are chosen to annihilate the elements of the kth row of sub( A ). The way that this actually works?? Obsessed. π
The scalar tau is returned in the kth element of TAU and the vector u( k ) in the kth row of sub( A ), such that the elements of z( k ) are in a( k, m + 1 ), ..., a( k, n ). The elements of R are returned in the upper triangular part of sub( A ).
Z is given by
Z = Z( 1 ) * Z( 2 ) * ... * Z( m ).
And that's the whole page, bestie!! π This one's from LAPACK version 1.5, dated 12 May 1997 β yeah she's vintage, she's a classic, she ate and left no crumbs. πβ¨
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