PDTZRZF(l)
π PDTZRZF π
okay so bestie, welcome to PDTZRZF, a LAPACK routine, version 1.5, sitting in the l manual section (that's the LAPACK corner of the man pages, iykyk) β¨ this one is a whole distributed-memory moment and she's iconic, let's get into it πΈ
π NAME π
PDTZRZF β reduce the M-by-N ( M<=N ) real upper trapezoidal matrix sub( A ) = A(IA:IA+M-1,JA:JA+N-1) to upper triangular form by means of orthogonal transformations π¦
β SYNOPSIS β
SUBROUTINE PDTZRZF( M, N, A, IA, JA, DESCA, TAU, WORK, LWORK, INFO )
INTEGER IA, INFO, JA, LWORK, M, N
INTEGER DESCA( * )
DOUBLE PRECISION A( * ), TAU( * ), WORK( * )
π PURPOSE π
PDTZRZF reduces the M-by-N ( M<=N ) real upper trapezoidal matrix sub( A ) = A(IA:IA+M-1,JA:JA+N-1) to upper triangular form by means of orthogonal transformations. periodt π
The upper trapezoidal matrix sub( A ) is factored as
sub( A ) = ( R 0 ) * Z,
where Z is an N-by-N orthogonal matrix and R is an M-by-M upper triangular matrix. no cap, that's the whole glow-up 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. she's the group chat admin of the whole grid fr fr 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
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
M(global input)INTEGERβ the number of rows to be operated on, i.e. the number of rows of the distributed submatrixsub( A ).M >= 0. β¨N(global input)INTEGERβ the number of columns to be operated on, i.e. the number of columns of the distributed submatrixsub( A ).N >= 0. β¨A(local input/local output)DOUBLE PRECISIONpointer 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 elementsM+1toNof the firstMrows ofsub( A ), with the arrayTAU, represent the orthogonal matrixZas a product ofMelementary reflectors. she does double duty, main character energy fr πIA(global input)INTEGERβ the row index in the global arrayAindicating the first row ofsub( A ).JA(global input)INTEGERβ the column index in the global arrayAindicating the first column ofsub( A ).DESCA(global and local input)INTEGERarray of dimensionDLEN_. The array descriptor for the distributed matrixA. πTAU(local output)DOUBLE PRECISION, array, dimensionLOCr(IA+M-1). This array contains the scalar factors of the elementary reflectors.TAUis tied to the distributed matrixA.WORK(local workspace/local output)DOUBLE PRECISIONarray, dimension(LWORK). On exit,WORK(1)returns the minimal and optimalLWORK. π«ΆLWORK(local or global input)INTEGERβ the dimension of the arrayWORK.LWORKis local input and must be at least
LWORK >= MB_A * ( Mp0 + Nq0 + MB_A ),
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 (no yelling at you, that's the point)
INFO(global output)INTEGERβ= 0: successful exit π< 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 factorization is obtained by Householder's method. The kth transformation matrix, Z( k ), which 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 ). like, she's literally zeroing out the whole row, it's giving precision πΈ
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 ). π
Z is given by
Z = Z( 1 ) * Z( 2 ) * ... * Z( m ).
and that's the whole page bestie, you ate π
β¨ this was LAPACK version 1.5, dated 12 May 1997 β yeah she's a classic, an icon, a legend, and she IS the moment ππ bye pookie, go call PDTZRZF responsibly 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