SRC/clatsqr.f(3)

πŸ’– SRC/clatsqr.f πŸ’–

okay bestie, this is the SRC/clatsqr.f(3) page from the Library Functions Manual β€” and it’s all about the CLATSQR subroutine. No cap, we’re doing a whole blocked Tall-Skinny QR situation here. πŸ¦‹


✨ NAME ✨

SRC/clatsqr.f


✨ SYNOPSIS ✨

Functions/Subroutines

  • subroutine clatsqr (m, n, mb, nb, a, lda, t, ldt, work, lwork, info) β€” CLATSQR

πŸŽ€ Function/Subroutine Documentation πŸŽ€

πŸ’… Subroutine Signature πŸ’…

   subroutine clatsqr (integer m, integer n, integer mb, integer nb, complex,
       dimension( lda, * ) a, integer lda, complex, dimension( ldt, * ) t,
       integer ldt, complex, dimension( * ) work, integer lwork, integer info)
       CLATSQR

🎯 Purpose 🎯

okay so CLATSQR computes a blocked Tall-Skinny QR factorization of a complex M-by-N matrix A for M >= N. The whole glow-up is:

A = Q * ( R ),
         ( 0 )

where:

  • Q is a M-by-M orthogonal matrix, stored on exit in an implicit form in the elements below the diagonal of the array A and in the elements of the array T;
  • R is an upper-triangular N-by-N matrix, stored on exit in the elements on and above the diagonal of the array A;
  • 0 is a (M-N)-by-N zero matrix, and is not stored. πŸ’€

🌸 Parameters 🌸

  • M β€” M is INTEGER. It’s the number of rows of the matrix A. Constraint: M >= 0. πŸ‘‘
  • N β€” N is INTEGER. It’s the number of columns of the matrix A. Constraint: M >= N >= 0. ✨
  • MB β€” MB is INTEGER. The row block size to be used in the blocked QR. Constraint: MB > N. 🧱
  • NB β€” NB is INTEGER. The column block size to be used in the blocked QR. Constraint: N >= NB >= 1. πŸŽ€
  • A β€” A is COMPLEX array, dimension (LDA,N). On entry, it’s the M-by-N matrix A. On exit, the elements on and above the diagonal of the array contain the N-by-N upper triangular matrix R; the elements below the diagonal represent Q by the columns of blocked V (see Further Details). πŸ¦‹
  • LDA β€” LDA is INTEGER. The leading dimension of the array A. Constraint: LDA >= max(1,M). βœ…
  • T β€” T is COMPLEX array, dimension (LDT, N * Number_of_row_blocks) where Number_of_row_blocks = CEIL((M-N)/(MB-N)). The blocked upper triangular block reflectors stored in compact form as a sequence of upper triangular blocks. See Further Details below. 🎁
  • LDT β€” LDT is INTEGER. The leading dimension of the array T. Constraint: LDT >= NB. πŸ’…
  • WORK β€” (workspace) COMPLEX array, dimension (MAX(1,LWORK)). On exit, if INFO = 0, WORK(1) returns the minimal LWORK. πŸ› οΈ
  • LWORK β€” LWORK is INTEGER. The dimension of the array WORK. LWORK >= 1, if MIN(M,N) = 0, and LWORK >= NB*N, otherwise. If LWORK = -1, then a workspace query is assumed; the routine only calculates the minimal 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. πŸ”
  • INFO β€” INFO is INTEGER. = 0: successful exit. < 0: if INFO = -i, the i-th argument had an illegal value. 🚨

πŸ’… Author πŸ’…

  • Univ. of Tennessee
  • Univ. of California Berkeley
  • Univ. of Colorado Denver
  • NAG Ltd.

πŸ¦‹ Further Details πŸ¦‹

Tall-Skinny QR (TSQR) performs QR 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 subdiagonal entries of a block of MB rows of A:

  • Q(1) zeros out the subdiagonal entries of rows 1:MB of A
  • Q(2) zeros out the bottom MB-N rows of rows [1:N,MB+1:2*MB-N] of A
  • Q(3) zeros out the bottom MB-N rows of rows [1:N,2*MB-N+1:3*MB-2*N] of A
  • . . .

Q(1) is computed by GEQRT, 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 GEQRT.

Q(i) for i>1 is computed by TPQRT, which represents Q(i) by Householder vectors stored in rows [(i-1)*(MB-N)+N+1:i*(MB-N)+N] of A, and by upper triangular block reflectors, stored in array T(1:LDT,(i-1)*N+1:i*N). 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] β€œCommunication-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

Definition at line 170 of file clatsqr.f.


πŸ€– Author πŸ€–

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πŸ’– that’s the whole page, bestie. cute sign-off: this is LAPACK, Version 3.12.0, and the source file is SRC/clatsqr.f(3). periodt. πŸ’–

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