PDGEQRF(l)

πŸ“¦ version 1.5, in ubuntu jammy

πŸ’– PDGEQRF πŸ’–

okay bestie, we're doing this β€” this is a LAPACK routine page, and it's the one that does a QR factorization on a real distributed M-by-N matrix. Yes, distributed. Yes, parallel. Yes, she's that girl. 🌈

It computes sub( A ) = A(IA:IA+M-1,JA:JA+N-1) = Q * R. Periodt. πŸ’…


✨ NAME ✨

PDGEQRF β€” compute a QR factorization of a real distributed M-by-N matrix sub( A ) = A(IA:IA+M-1,JA:JA+N-1) = Q * R


πŸ¦‹ SYNOPSIS πŸ¦‹

SUBROUTINE PDGEQRF( M, N, A, IA, JA, DESCA, TAU, WORK, LWORK, INFO )

    INTEGER         IA, INFO, JA, LWORK, M, N

    INTEGER         DESCA( * )

    DOUBLE          PRECISION A( * ), TAU( * ), WORK( * )

🌸 PURPOSE 🌸

PDGEQRF computes a QR factorization of a real distributed M-by-N matrix

sub( A ) = A(IA:IA+M-1,JA:JA+N-1) = Q * R.

πŸ’« Notes πŸ’«

Every global data object is described by an associated description vector. That vector is lowkey the blueprint β€” it stores all 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".

  • 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. πŸ‘€
  • 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 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

πŸ‘‘ ARGUMENTS πŸ‘‘

  • M β€” (global input) INTEGER. The number of rows to be operated on, i.e. the number of rows of the distributed submatrix sub( A ). M >= 0. πŸ’–
  • N β€” (global input) INTEGER. The number of columns to be operated on, i.e. the number of columns of the distributed submatrix sub( A ). N >= 0. πŸ’–
  • A β€” (local input/local output) DOUBLE PRECISION 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 matrix sub( A ) which is to be factored. On exit, the elements on and above the diagonal of sub( A ) contain the min(M,N) by N upper trapezoidal matrix R (R is upper triangular if M >= N); the elements below the diagonal, with the array TAU, represent the orthogonal matrix Q as a product of elementary reflectors (see Further Details). πŸ”₯
  • IA β€” (global input) INTEGER. The row index in the global array A indicating the first row of sub( A ).
  • JA β€” (global input) INTEGER. 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) DOUBLE PRECISION, array, dimension LOCc(JA+MIN(M,N)-1). This array contains the scalar factors TAU of the elementary reflectors. TAU is tied to the distributed matrix A. πŸŽ€
  • WORK β€” (local workspace/local output) DOUBLE PRECISION array, dimension (LWORK). On exit, WORK(1) returns the minimal and optimal LWORK.
  • LWORK β€” (local or global input) INTEGER. The dimension of the array WORK. LWORK is local input and must be at least LWORK >= NB_A * ( Mp0 + Nq0 + NB_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. ✨

  • INFO β€” (global output) INTEGER.
    • = 0: successful exit πŸ₯³
    • < 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.

🧚 FURTHER DETAILS 🧚

The matrix Q is represented as a product of elementary reflectors

Q = H(ja) H(ja+1) . . . H(ja+k-1), where k = min(m,n).

Each H(i) has the form

H(j) = I - tau * v * v'

where tau is a real scalar, and v is a real vector with v(1:i-1) = 0 and v(i) = 1; v(i+1:m) is stored on exit in A(ia+i:ia+m-1,ja+i-1), and tau in TAU(ja+i-1). πŸ’œ


ngl bestie, that's the whole thing. QR factorization, distributed, iconic behaviour only. No cap. πŸ™ˆ

sending you off with the deets: this is LAPACK version 1.5, dated 12 May 1997. mwah πŸ’‹ slay, and go factor something. 🌟

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