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dlaswlq.f(3) LAPACK dlaswlq.f(3)

NAME

dlaswlq.f

SYNOPSIS

Functions/Subroutines


subroutine dlaswlq (M, N, MB, NB, A, LDA, T, LDT, WORK, LWORK, INFO)

Function/Subroutine Documentation

subroutine dlaswlq (integer M, integer N, integer MB, integer NB, double precision, dimension( lda, * ) A, integer LDA, double precision, dimension( ldt, *) T, integer LDT, double precision, dimension( * ) WORK, integer LWORK, integer INFO)

Purpose:

DLASWLQ computes a blocked Short-Wide LQ factorization of a M-by-N matrix A, where N >= M: A = L * Q

Parameters:

M


M is INTEGER
The number of rows of the matrix A. M >= 0.

N


N is INTEGER
The number of columns of the matrix A. N >= M >= 0.

MB


MB is INTEGER
The row block size to be used in the blocked QR.
M >= MB >= 1

NB


NB is INTEGER
The column block size to be used in the blocked QR.
NB > M.

A


A is DOUBLE PRECISION array, dimension (LDA,N)
On entry, the M-by-N matrix A.
On exit, the elements on and bleow the diagonal
of the array contain the N-by-N lower triangular matrix L;
the elements above the diagonal represent Q by the rows
of blocked V (see Further Details).

LDA


LDA is INTEGER
The leading dimension of the array A. LDA >= max(1,M).

T


T is DOUBLE PRECISION array,
dimension (LDT, N * Number_of_row_blocks)
where Number_of_row_blocks = CEIL((N-M)/(NB-M))
The blocked upper triangular block reflectors stored in compact form
as a sequence of upper triangular blocks.
See Further Details below.

LDT


LDT is INTEGER
The leading dimension of the array T. LDT >= MB.

WORK


(workspace) DOUBLE PRECISION array, dimension (MAX(1,LWORK))

LWORK


The dimension of the array WORK. LWORK >= MB*M.
If LWORK = -1, then a workspace query is assumed; the routine
only calculates the optimal size of the WORK array, returns
this value as the first entry of the WORK array, and no error
message related to LWORK is issued by XERBLA.

INFO


INFO is INTEGER
= 0: successful exit
< 0: if INFO = -i, the i-th argument had an illegal value

Author:

Univ. of Tennessee

Univ. of California Berkeley

Univ. of Colorado Denver

NAG Ltd.

Further Details:

Short-Wide LQ (SWLQ) performs LQ by a sequence of orthogonal transformations, representing Q as a product of other orthogonal matrices Q = Q(1) * Q(2) * . . . * Q(k) where each Q(i) zeros out upper diagonal entries of a block of NB rows of A: Q(1) zeros out the upper diagonal entries of rows 1:NB of A Q(2) zeros out the bottom MB-N rows of rows [1:M,NB+1:2*NB-M] of A Q(3) zeros out the bottom MB-N rows of rows [1:M,2*NB-M+1:3*NB-2*M] of A . . .

Q(1) is computed by GELQT, which represents Q(1) by Householder vectors stored under the diagonal of rows 1:MB of A, and by upper triangular block reflectors, stored in array T(1:LDT,1:N). For more information see Further Details in GELQT.

Q(i) for i>1 is computed by TPLQT, which represents Q(i) by Householder vectors stored in columns [(i-1)*(NB-M)+M+1:i*(NB-M)+M] of A, and by upper triangular block reflectors, stored in array T(1:LDT,(i-1)*M+1:i*M). The last Q(k) may use fewer rows. For more information see Further Details in TPQRT.

For more details of the overall algorithm, see the description of Sequential TSQR in Section 2.2 of [1].

[1] “Communication-Optimal Parallel and Sequential QR and LU Factorizations,” J. Demmel, L. Grigori, M. Hoemmen, J. Langou, SIAM J. Sci. Comput, vol. 34, no. 1, 2012

Author

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