PZGEHRD(l)
π NAME π
PZGEHRD β bestie, this is a LAPACK routine (version 1.5, we love her) and what she does is reduce a complex general distributed matrix sub( A ) to upper Hessenberg form H by a unitary similarity transformation. That's the whole vibe. Periodt.
β¨ SYNOPSIS β¨
SUBROUTINE PZGEHRD( N, ILO, IHI, A, IA, JA, DESCA, TAU, WORK, LWORK,
INFO )
INTEGER IA, IHI, ILO, INFO, JA, LWORK, N
INTEGER DESCA( * )
COMPLEX*16 A( * ), TAU( * ), WORK( * )
π¦ PURPOSE π¦
Okay so PZGEHRD reduces a complex general distributed matrix sub( A ) to upper Hessenberg form H by an unitary similarity transformation: Q' * sub( A ) * Q = H, where
sub( A ) = A(IA+N-1:IA+N-1,JA+N-1:JA+N-1).
π Notes
Every global data object out here is described by an associated description vector. That vector is literally storing the info you need to build the mapping between an element of the object and the process + memory location it lives in. It's giving very organized, very demure.
Let A be a generic term for any 2D block cyclicly distributed array. An array like that has an associated description vector DESCA. And in the comments below, the character _ should be read as "of the global array". Iykyk, it's just shorthand.
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 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_ )β the number of rows in the global array A.N_A(global) β stored inDESCA( N_ )β the number of columns in the global array A.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 array A is distributed.CSRC_A(global) β stored inDESCA( CSRC_ )β the process column over which the first column of the array A is 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 its process grid has dimension p x q.
LOCr( K )= the number of elements ofKthat a process would receive ifKwere distributed over thepprocesses of its process column.LOCc( K )= the number of elements ofKthat a process would receive ifKwere distributed over theqprocesses 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
πΈ ARGUMENTS πΈ
Nβ (global input)INTEGER. The number of rows and columns to be operated on, i.e. the order of the distributed submatrixsub( A ).N >= 0.ILOβ (global input)INTEGER.IHIβ (global input)INTEGER. It is assumed thatsub( A )is already upper triangular in rowsIA:IA+ILO-2andIA+IHI:IA+N-1and columnsJA:JA+ILO-2andJA+IHI:JA+N-1. See Further Details. IfN > 0,Aβ (local input/local output)COMPLEX*16pointer into the local memory to an array of dimension(LLD_A,LOCc(JA+N-1)). On entry, this array contains the local pieces of theN-by-Ngeneral distributed matrixsub( A )to be reduced. On exit, the upper triangle and the first subdiagonal ofsub( A )are overwritten with the upper Hessenberg matrixH, and the elements below the first subdiagonal, with the arrayTAU, represent the unitary matrixQas a product of elementary reflectors. See Further Details.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)INTEGERarray of dimensionDLEN_. The array descriptor for the distributed matrixA.TAUβ (local output)COMPLEX*16array, dimensionLOCc(JA+N-2). The scalar factors of the elementary reflectors (see Further Details). ElementsJA:JA+ILO-2andJA+IHI:JA+N-2ofTAUare set to zero.TAUis tied to the distributed matrixA.WORKβ (local workspace/local output)COMPLEX*16array, 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 least
LWORK >= NB*NB + NB*MAX( IHIP+1, IHLP+INLQ )
where
NB = MB_A = NB_A,
IROFFA = MOD( IA-1, NB ),
ICOFFA = MOD( JA-1, NB ),
IOFF = MOD( IA+ILO-2, NB ),
IAROW = INDXG2P( IA, NB, MYROW, RSRC_A, NPROW ),
IHIP = NUMROC( IHI+IROFFA, NB, MYROW, IAROW, NPROW ),
ILROW = INDXG2P( IA+ILO-1, NB, MYROW, RSRC_A, NPROW ),
IHLP = NUMROC( IHI-ILO+IOFF+1, NB, MYROW, ILROW, NPROW ),
ILCOL = INDXG2P( JA+ILO-1, NB, MYCOL, CSRC_A, NPCOL ),
INLQ = NUMROC( N-ILO+IOFF+1, NB, MYCOL, ILCOL, NPCOL ),
INDXG2P and NUMROC 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.
INFOβ (global output)INTEGER.= 0: successful exit. slay 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 (ihi-ilo) elementary reflectors
Q = H(ilo) H(ilo+1) . . . H(ihi-1).
Each H(i) has the form
H(i) = I - tau * v * v'
where tau is a complex scalar, and v is a complex vector with v(1:I) = 0, v(I+1) = 1 and v(IHI+1:N) = 0; v(I+2:IHI) is stored on exit in A(IA+ILO+I:IA+IHI-1,JA+ILO+I-2), and tau in TAU(JA+ILO+I-2).
The contents of A(IA:IA+N-1,JA:JA+N-1) are illustrated by the following example, with N = 7, ILO = 2 and IHI = 6:
on entry on exit
( a a a a a a a ) ( a a h h h h a )
( a a a a a a a ) ( a h h h h a )
( a a a a a a a ) ( h h h h h h )
( a a a a a a a ) ( v2 h h h h h )
( a a a a a a a ) ( v2 v3 h h h h )
( a a a a a a a ) ( v2 v3 v4 h h h )
( a a a a a a a ) ( a )
where a denotes an element of the original matrix sub( A ), H denotes a modified element of the upper Hessenberg matrix H, and vi denotes an element of the vector defining H(JA+ILO+I-2).
π Alignment requirements
The distributed submatrix sub( A ) must verify some alignment properties, namely the following expression should be true:
( MB_A.EQ.NB_A .AND. IROFFA.EQ.ICOFFA )
bestie if that expression is not true, we have a problem. check your alignment, fr fr π
okay that's the whole page, you ate it, you understood it, I'm obsessed. go reduce something to Hessenberg form, main character energy only π
This has been LAPACK version 1.5, dated 12 May 1997, page PZGEHRD(l) β signing off, mwah πβ¨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