PDGEHRD(l)
π PDGEHRD π
okay bestie, so this is a LAPACK routine, and it's giving distributed linear algebra in the most iconic way possible. It's a SUBROUTINE that lives in the PDGEHRD(l) page, and we're about to make it make sense. no cap. β¨
π NAME π
PDGEHRD β reduce a real general distributed matrix sub( A ) to upper Hessenberg form H by an orthogonal similarity transformation π¦
β¨ SYNOPSIS β¨
SUBROUTINE PDGEHRD( N, ILO, IHI, A, IA, JA, DESCA, TAU, WORK, LWORK,
INFO )
INTEGER IA, IHI, ILO, INFO, JA, LWORK, N
INTEGER DESCA( * )
DOUBLE PRECISION A( * ), TAU( * ), WORK( * )
π PURPOSE π
PDGEHRD reduces a real general distributed matrix sub( A ) to upper Hessenberg form H by an orthogonal similarity transformation, and the way that it does it is literally
Q' * sub( A ) * Q = H
where, and I need you to read this carefully because it's a whole thing,
sub( A ) = A(IA+N-1:IA+N-1,JA+N-1:JA+N-1)
(that's what the page says, character for character, and I'm not touching it π)
π Notes π
Every global data object is described by an associated description vector. This vector stores the info you need to establish the mapping between an object element and its corresponding process and memory location.
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".
so here's the whole notation breakdown, one glow-up at a time 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 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
πΈ ARGUMENTS πΈ
N(global input)INTEGERβ the number of rows and columns to be operated on, i.e. the order of the distributed submatrixsub( A ).N >= 0. bestie it's a size, it's giving "how big is this thing" energy π«ΆILO(global input)INTEGERIHI(global input)INTEGERβ 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,
(yes, that trailing "If N > 0," is literally how it's written on the page and I am not fixing it, that's the original's business π)
A(local input/local output)DOUBLE PRECISIONpointer 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 orthogonal matrixQas a product of elementary reflectors. See Further Details.IA(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.TAU(local output)DOUBLE PRECISIONarray, 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. πWORK(local workspace/local output)DOUBLE PRECISIONarray, dimension(LWORK). On exit,WORK( 1 )returns the minimal and optimalLWORK.LWORK(local or global input)INTEGERβ 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. π₯
INFO(global output)INTEGER= 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 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 real scalar, and v is a real 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
( a a a a a a a )
( a a a a a a )
( a a a a a a )
( a a a a a a )
( a a a a a a )
( a a a a a a )
( a )
on exit
( a a h h h h a )
( a h h h h a )
( h h h h h h )
( v2 h h h h h )
( v2 v3 h h h h )
( v2 v3 v4 h h h )
( 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). β¨
π§ Alignment requirements π§
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 )
fr fr, if that alignment vibe check fails, we're not doing this. π
that's the whole page, bestie β every flag, every formula, every little NUMROC call, untouched and thriving. now go reduce something to upper Hessenberg form, you main character. π
with love from LAPACK version 1.5, dated 12 May 1997, and originally signed off as PDGEHRD(l) β slay, periodt. 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