sbdsdc

NAME

sbdsdc - compute the singular value decomposition (SVD) of a real N-by-N (upper or lower) bidiagonal matrix B

SYNOPSIS

  SUBROUTINE SBDSDC( UPLO, COMPQ, N, D, E, U, LDU, VT, LDVT, Q, IQ, 
 *      WORK, IWORK, INFO)
  CHARACTER * 1 UPLO, COMPQ
  INTEGER N, LDU, LDVT, INFO
  INTEGER IQ(*), IWORK(*)
  REAL D(*), E(*), U(LDU,*), VT(LDVT,*), Q(*), WORK(*)
 
  SUBROUTINE SBDSDC_64( UPLO, COMPQ, N, D, E, U, LDU, VT, LDVT, Q, IQ, 
 *      WORK, IWORK, INFO)
  CHARACTER * 1 UPLO, COMPQ
  INTEGER*8 N, LDU, LDVT, INFO
  INTEGER*8 IQ(*), IWORK(*)
  REAL D(*), E(*), U(LDU,*), VT(LDVT,*), Q(*), WORK(*)

F95 INTERFACE

  SUBROUTINE BDSDC( UPLO, COMPQ, [N], D, E, U, [LDU], VT, [LDVT], Q, 
 *       IQ, [WORK], [IWORK], [INFO])
  CHARACTER(LEN=1) :: UPLO, COMPQ
  INTEGER :: N, LDU, LDVT, INFO
  INTEGER, DIMENSION(:) :: IQ, IWORK
  REAL, DIMENSION(:) :: D, E, Q, WORK
  REAL, DIMENSION(:,:) :: U, VT
 
  SUBROUTINE BDSDC_64( UPLO, COMPQ, [N], D, E, U, [LDU], VT, [LDVT], 
 *       Q, IQ, [WORK], [IWORK], [INFO])
  CHARACTER(LEN=1) :: UPLO, COMPQ
  INTEGER(8) :: N, LDU, LDVT, INFO
  INTEGER(8), DIMENSION(:) :: IQ, IWORK
  REAL, DIMENSION(:) :: D, E, Q, WORK
  REAL, DIMENSION(:,:) :: U, VT

C INTERFACE

#include <sunperf.h>

void sbdsdc(char uplo, char compq, int n, float *d, float *e, float *u, int ldu, float *vt, int ldvt, float *q, int *iq, int *info);

void sbdsdc_64(char uplo, char compq, long n, float *d, float *e, float *u, long ldu, float *vt, long ldvt, float *q, long *iq, long *info);

PURPOSE

sbdsdc computes the singular value decomposition (SVD) of a real N-by-N (upper or lower) bidiagonal matrix B: B = U * S * VT, using a divide and conquer method, where S is a diagonal matrix with non-negative diagonal elements (the singular values of B), and U and VT are orthogonal matrices of left and right singular vectors, respectively. SBDSDC can be used to compute all singular values, and optionally, singular vectors or singular vectors in compact form.

This code makes very mild assumptions about floating point arithmetic. It will work on machines with a guard digit in add/subtract, or on those binary machines without guard digits which subtract like the Cray X-MP, Cray Y-MP, Cray C-90, or Cray-2. It could conceivably fail on hexadecimal or decimal machines without guard digits, but we know of none. See SLASD3 for details.

The code currently call SLASDQ if singular values only are desired. However, it can be slightly modified to compute singular values using the divide and conquer method.

ARGUMENTS

* UPLO (input)
* COMPQ (input): Specifies whether singular vectors are to be computed as follows:
* N (input): The order of the matrix B. N >= 0.
* D (input/output): On entry, the n diagonal elements of the bidiagonal matrix B. On exit, if INFO=0, the singular values of B.
* E (input/output): On entry, the elements of E contain the offdiagonal elements of the bidiagonal matrix whose SVD is desired. On exit, E has been destroyed.
* U (output): If COMPQ = 'I', then: On exit, if INFO = 0, U contains the left singular vectors of the bidiagonal matrix. For other values of COMPQ, U is not referenced.
* LDU (input): The leading dimension of the array U. LDU >= 1. If singular vectors are desired, then LDU >= max( 1, N ).
* VT (output): If COMPQ = 'I', then: On exit, if INFO = 0, VT' contains the right singular vectors of the bidiagonal matrix. For other values of COMPQ, VT is not referenced.
* LDVT (input): The leading dimension of the array VT. LDVT >= 1. If singular vectors are desired, then LDVT >= max( 1, N ).
* Q (input): If COMPQ = 'P', then: On exit, if INFO = 0, Q and IQ contain the left and right singular vectors in a compact form, requiring O(N log N) space instead of 2*N**2. In particular, Q contains all the REAL data in LDQ >= N*(11 + 2*SMLSIZ + 8*INT(LOG_2(N/(SMLSIZ+1)))) words of memory, where SMLSIZ is returned by ILAENV and is equal to the maximum size of the subproblems at the bottom of the computation tree (usually about 25). For other values of COMPQ, Q is not referenced.
* IQ (output): If COMPQ = 'P', then: On exit, if INFO = 0, Q and IQ contain the left and right singular vectors in a compact form, requiring O(N log N) space instead of 2*N**2. In particular, IQ contains all INTEGER data in LDIQ >= N*(3 + 3*INT(LOG_2(N/(SMLSIZ+1)))) words of memory, where SMLSIZ is returned by ILAENV and is equal to the maximum size of the subproblems at the bottom of the computation tree (usually about 25). For other values of COMPQ, IQ is not referenced.
* WORK (workspace): If COMPQ = 'N' then LWORK >= (2 * N). If COMPQ = 'P' then LWORK >= (6 * N). If COMPQ = 'I' then LWORK >= (3 * N**2 + 4 * N).
* IWORK (workspace): dimension(8*N)
* INFO (output)