PZGEHD2(l)

πŸ“¦ version 1.5, in ubuntu jammy

πŸ’– PZGEHD2 πŸ’– β€” it's giving LAPACK auxiliary routine, bestie (version 1.5, she's an icon, she's from the l manual)

okay so like. hi. you're here because you need to take a complex general distributed matrix sub( A ) and glow it up into upper Hessenberg form H using a unitary similarity transformation. slay. let's go πŸ¦‹


✨ NAME ✨

PZGEHD2 β€” reduces a complex general distributed matrix sub( A ) to upper Hessenberg form H by an unitary similarity transformation. periodt. πŸ’…


🌸 SYNOPSIS 🌸

SUBROUTINE PZGEHD2( 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( * )

πŸ‘‘ PURPOSE πŸ‘‘

PZGEHD2 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).

🧚 Notes 🧚

Every global data object has a little bestie called a description vector. That vector holds all the info you need to map an element of the object to its process and its memory location. no cap.

Let A be a generic term for any 2D block cyclicly distributed array. That global array has an associated description vector DESCA. And in the comments below, read the character _ as "of the global array". iykyk.

Here's the whole vibe, stored in the descriptor:

  • DTYPE_A (global) β€” stored in DESCA( DTYPE_ ) β€” the descriptor type. In this case, DTYPE_A = 1.
  • CTXT_A (global) β€” stored in DESCA( 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 in DESCA( M_ ) β€” the number of rows in the global array A.
  • N_A (global) β€” stored in DESCA( N_ ) β€” the number of columns in the global array A.
  • MB_A (global) β€” stored in DESCA( MB_ ) β€” the blocking factor used to distribute the rows of the array.
  • NB_A (global) β€” stored in DESCA( NB_ ) β€” the blocking factor used to distribute the columns of the array.
  • RSRC_A (global) β€” stored in DESCA( RSRC_ ) β€” the process row over which the first row of the array A is distributed.
  • CSRC_A (global) β€” stored in DESCA( CSRC_ ) β€” the process column over which the first column of the array A is distributed.
  • LLD_A (local) β€” stored in DESCA( 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 ) is 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 ) is the number of elements of K that a process would receive if K were distributed over the q processes of its process row.

You can get the values of LOCr() and LOCc() by calling 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

πŸŽ€ ARGUMENTS πŸŽ€

  • N β€” (global input) INTEGER β€” the number of rows and columns to be operated on, i.e. the order of the distributed submatrix sub( A ). N >= 0.
  • ILO β€” (global input) INTEGER
  • IHI β€” (global input) INTEGER β€” it is assumed that sub( A ) is already upper triangular in rows IA:IA+ILO-2 and IA+IHI:IA+N-1 and columns JA:JA+JLO-2 and JA:JHI:JA+N-1. See Further Details. If N > 0,
  • A β€” (local input/local output) COMPLEX*16 pointer into the local memory to an array of dimension (LLD_A,LOCc(JA+N-1)). On entry, this array contains the local pieces of the N-by-N general distributed matrix sub( A ) to be reduced. On exit, the upper triangle and the first subdiagonal of sub( A ) are overwritten with the upper Hessenberg matrix H, and the elements below the first subdiagonal, with the array TAU, represent the unitary matrix Q as a product of elementary reflectors. See Further Details.
  • IA β€” (global input) INTEGER β€” the row index in the global array A indicating the first row of sub( A ).
  • JA β€” (global input) INTEGER β€” the column index in the global array A indicating the first column of sub( A ).
  • DESCA β€” (global and local input) INTEGER array of dimension DLEN_. The array descriptor for the distributed matrix A.
  • TAU β€” (local output) COMPLEX*16 array, dimension LOCc(JA+N-2) β€” the scalar factors of the elementary reflectors (see Further Details). Elements JA:JA+ILO-2 and JA+IHI:JA+N-2 of TAU are set to zero. TAU is tied to the distributed matrix A. πŸ”—
  • WORK β€” (local workspace/local output) COMPLEX*16 array, dimension (LWORK). On exit, WORK( 1 ) returns the minimal and optimal LWORK.
  • LWORK β€” (local or global input) INTEGER β€” the dimension of the array WORK. LWORK is local input and must be at least
LWORK >= NB + MAX( NpA0, NB )

where

NB = MB_A = NB_A,
IROFFA = MOD( IA-1, NB ),
IAROW = INDXG2P( IA, NB, MYROW, RSRC_A, NPROW ),
NpA0 = NUMROC( IHI+IROFFA, NB, MYROW, IAROW, NPROW ),

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.

  • INFO β€” (local output) INTEGER
    • = 0: successful exit πŸŽ‰
    • < 0: If the i-th argument is an array and the j-entry had an illegal value, then INFO = -(i*100+j), if the i-th argument is a scalar and had an illegal value, then INFO = -i.

πŸ”₯ FURTHER DETAILS πŸ”₯

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:

( 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 )
(          v2  h   h   h   h )
(          v2  v3  h   h   h )
(          v2  v3  v4  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).

🌈 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, do not pass go, do not collect $200. fix your alignment first fr fr. 😭

and that's the whole page, you ate that πŸ’… go forth and Hessenberg-ify responsibly.

this was LAPACK version 1.5, dated 12 May 1997 β€” yeah she's vintage, she's an old-money icon, and she still slays πŸŽ€βœ¨

πŸ“¦ where this page comes from