PZTZRZF(l)
β¨ PZTZRZF β¨
okay bestie, sit down, hydrate, because today we're talking about PZTZRZF from the LAPACK family (version 1.5, the ScaLAPACK girlies know π
). this is a routine page from manual section l, and it's about taking a complex upper trapezoidal matrix and making it upper triangular with unitary transformations. glow-up of the century tbh π¦
πΈ NAME πΈ
PZTZRZF β reduce the M-by-N ( M<=N ) complex upper trapezoidal matrix sub( A ) = A(IA:IA+M-1,JA:JA+N-1) to upper triangular form by means of unitary transformations
like. that's the whole job. that's her main character arc. β¨
π SYNOPSIS π
SUBROUTINE PZTZRZF( M, N, A, IA, JA, DESCA, TAU, WORK, LWORK, INFO )
INTEGER IA, INFO, JA, LWORK, M, N
INTEGER DESCA( * )
COMPLEX*16 A( * ), TAU( * ), WORK( * )
no cap, that's the whole signature. memorize it or keep it in your notes app π
π PURPOSE π
PZTZRZF reduces the M-by-N ( M<=N ) complex upper trapezoidal matrix sub( A ) = A(IA:IA+M-1,JA:JA+N-1) to upper triangular form by means of unitary transformations.
the upper trapezoidal matrix sub( A ) is 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.
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. it's giving β¨bookkeepingβ¨ but make it distributed.
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".
okay so here's the lore, one bullet per entry because tables aren't the vibe here π«Ά:
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 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)).
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.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 elements M+1 to N of the first M rows ofsub( A ), with the arrayTAU, represent the unitary matrixZas a product of M elementary reflectors. (she contains multitudes fr fr π)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/local output) COMPLEX*16 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 >= 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. (yes queen, give us nothing and everything at once π
)
INFOβ (global 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 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 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 ).
ok bestie one (1) tiny reminder: this is a real LAPACK/ScaLAPACK routine, so respect the descriptor, respect LWORK, and read the argument constraints before you go wild. the math is not playing around, even if i am π«Ά
and that's the page!! π this was PZTZRZF(l) from LAPACK version 1.5, dated 12 May 1997 β yes she's an elder icon and she's still serving upper triangular realness. periodt. πβ¨πΈππ¦
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