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Updated: June 2017
 
 

sgesvd (3p)

Name

sgesvd - N matrix A, optionally computing the left and/or right singular vectors

Synopsis

SUBROUTINE SGESVD(JOBU, JOBVT, M, N, A, LDA, SING, U, LDU, VT, LDVT,
WORK, LDWORK, INFO)

CHARACTER*1 JOBU, JOBVT
INTEGER M, N, LDA, LDU, LDVT, LDWORK, INFO
REAL A(LDA,*), SING(*), U(LDU,*), VT(LDVT,*), WORK(*)

SUBROUTINE SGESVD_64(JOBU, JOBVT, M, N, A, LDA, SING, U, LDU, VT,
LDVT, WORK, LDWORK, INFO)

CHARACTER*1 JOBU, JOBVT
INTEGER*8 M, N, LDA, LDU, LDVT, LDWORK, INFO
REAL A(LDA,*), SING(*), U(LDU,*), VT(LDVT,*), WORK(*)




F95 INTERFACE
SUBROUTINE GESVD(JOBU, JOBVT, M, N, A, LDA, SING, U, LDU, VT,
LDVT, WORK, LDWORK, INFO)

CHARACTER(LEN=1) :: JOBU, JOBVT
INTEGER :: M, N, LDA, LDU, LDVT, LDWORK, INFO
REAL, DIMENSION(:) :: SING, WORK
REAL, DIMENSION(:,:) :: A, U, VT

SUBROUTINE GESVD_64(JOBU, JOBVT, M, N, A, LDA, SING, U, LDU,
VT, LDVT, WORK, LDWORK, INFO)

CHARACTER(LEN=1) :: JOBU, JOBVT
INTEGER(8) :: M, N, LDA, LDU, LDVT, LDWORK, INFO
REAL, DIMENSION(:) :: SING, WORK
REAL, DIMENSION(:,:) :: A, U, VT




C INTERFACE
#include <sunperf.h>

void  sgesvd(char  jobu,  char  jobvt, int m, int n, float *a, int lda,
float *sing, float *u, int ldu,  float  *vt,  int  ldvt,  int
*info);

void  sgesvd_64(char  jobu,  char jobvt, long m, long n, float *a, long
lda, float *sing, float *u, long ldu, float *vt,  long  ldvt,
long *info);

Description

Oracle Solaris Studio Performance Library                           sgesvd(3P)



NAME
       sgesvd - compute the singular value decomposition (SVD) of a real M-by-
       N matrix A, optionally computing the left and/or right singular vectors


SYNOPSIS
       SUBROUTINE SGESVD(JOBU, JOBVT, M, N, A, LDA, SING, U, LDU, VT, LDVT,
             WORK, LDWORK, INFO)

       CHARACTER*1 JOBU, JOBVT
       INTEGER M, N, LDA, LDU, LDVT, LDWORK, INFO
       REAL A(LDA,*), SING(*), U(LDU,*), VT(LDVT,*), WORK(*)

       SUBROUTINE SGESVD_64(JOBU, JOBVT, M, N, A, LDA, SING, U, LDU, VT,
             LDVT, WORK, LDWORK, INFO)

       CHARACTER*1 JOBU, JOBVT
       INTEGER*8 M, N, LDA, LDU, LDVT, LDWORK, INFO
       REAL A(LDA,*), SING(*), U(LDU,*), VT(LDVT,*), WORK(*)




   F95 INTERFACE
       SUBROUTINE GESVD(JOBU, JOBVT, M, N, A, LDA, SING, U, LDU, VT,
              LDVT, WORK, LDWORK, INFO)

       CHARACTER(LEN=1) :: JOBU, JOBVT
       INTEGER :: M, N, LDA, LDU, LDVT, LDWORK, INFO
       REAL, DIMENSION(:) :: SING, WORK
       REAL, DIMENSION(:,:) :: A, U, VT

       SUBROUTINE GESVD_64(JOBU, JOBVT, M, N, A, LDA, SING, U, LDU,
              VT, LDVT, WORK, LDWORK, INFO)

       CHARACTER(LEN=1) :: JOBU, JOBVT
       INTEGER(8) :: M, N, LDA, LDU, LDVT, LDWORK, INFO
       REAL, DIMENSION(:) :: SING, WORK
       REAL, DIMENSION(:,:) :: A, U, VT




   C INTERFACE
       #include <sunperf.h>

       void  sgesvd(char  jobu,  char  jobvt, int m, int n, float *a, int lda,
                 float *sing, float *u, int ldu,  float  *vt,  int  ldvt,  int
                 *info);

       void  sgesvd_64(char  jobu,  char jobvt, long m, long n, float *a, long
                 lda, float *sing, float *u, long ldu, float *vt,  long  ldvt,
                 long *info);



PURPOSE
       sgesvd computes the singular value decomposition (SVD) of a real M-by-N
       matrix A, optionally computing the left and/or right singular  vectors.
       The SVD is written
        = U * SIGMA * transpose(V)

       where  SIGMA  is an M-by-N matrix which is zero except for its min(m,n)
       diagonal elements, U is an M-by-M orthogonal matrix, and V is an N-by-N
       orthogonal  matrix.   The  diagonal  elements of SIGMA are the singular
       values of A; they are  real  and  non-negative,  and  are  returned  in
       descending  order.   The first min(m,n) columns of U and V are the left
       and right singular vectors of A.

       Note that the routine returns V**T, not V.


ARGUMENTS
       JOBU (input)
                 Specifies options for computing all or part of the matrix U:
                 = 'A':  all M columns of U are returned in array U:
                 = 'S':  the first min(m,n) columns of U  (the  left  singular
                 vectors)  are  returned  in  the  array  U; = 'O':  the first
                 min(m,n) columns of U (the left singular vectors)  are  over-
                 written on the array A; = 'N':  no columns of U (no left sin-
                 gular vectors) are computed.


       JOBVT (input)
                 Specifies options for computing all or  part  of  the  matrix
                 V**T:
                 = 'A':  all N rows of V**T are returned in the array VT;
                 =  'S':   the first min(m,n) rows of V**T (the right singular
                 vectors) are returned in the array  VT;  =  'O':   the  first
                 min(m,n)  rows of V**T (the right singular vectors) are over-
                 written on the array A; = 'N':  no rows  of  V**T  (no  right
                 singular vectors) are computed.

                 JOBVT and JOBU cannot both be 'O'.


       M (input) The number of rows of the input matrix A.  M >= 0.


       N (input) The number of columns of the input matrix A.  N >= 0.


       A (input/output)
                 On entry, the M-by-N matrix A.  On exit, if JOBU = 'O',  A is
                 overwritten with the first min(m,n) columns of  U  (the  left
                 singular  vectors,  stored  columnwise); if JOBVT = 'O', A is
                 overwritten with the first min(m,n) rows of V**T  (the  right
                 singular vectors, stored rowwise); if JOBU .ne. 'O' and JOBVT
                 .ne. 'O', the contents of A are destroyed.


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


       SING (output)
                 The  singular  values  of  A,  sorted  so  that  SING(i)   >=
                 SING(i+1).


       U (output)
                 (LDU,M)  if  JOBU  = 'A' or (LDU,min(M,N)) if JOBU = 'S'.  If
                 JOBU = 'A', U contains the M-by-M  orthogonal  matrix  U;  if
                 JOBU  =  'S', U contains the first min(m,n) columns of U (the
                 left singular vectors, stored columnwise); if JOBU =  'N'  or
                 'O', U is not referenced.


       LDU (input)
                 The  leading  dimension  of the array U.  LDU >= 1; if JOBU =
                 'S' or 'A', LDU >= M.


       VT (output)
                 If JOBVT = 'A', VT  contains  the  N-by-N  orthogonal  matrix
                 V**T;  if JOBVT = 'S', VT contains the first min(m,n) rows of
                 V**T (the right singular vectors, stored rowwise); if JOBVT =
                 'N' or 'O', VT is not referenced.


       LDVT (input)
                 The leading dimension of the array VT.  LDVT >= 1; if JOBVT =
                 'A', LDVT >= N; if JOBVT = 'S', LDVT >= min(M,N).


       WORK (workspace)
                 On exit, if INFO = 0, WORK(1) returns the optimal LDWORK;  if
                 INFO  >  0,  WORK(2:MIN(M,N)) contains the unconverged super-
                 diagonal elements of an upper bidiagonal matrix B whose diag-
                 onal is in SING (not necessarily sorted). B satisfies A = U *
                 B * VT, so it has the same singular values as A, and singular
                 vectors related by U and VT.


       LDWORK (input)
                 The  dimension  of  the  array  WORK. LDWORK >= 1.  LDWORK >=
                 MAX(3*MIN(M,N)+MAX(M,N),5*MIN(M,N)).  For  good  performance,
                 LDWORK should generally be larger.

                 If  LDWORK  = -1, then a workspace query is assumed; the rou-
                 tine 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 LDWORK is issued by XERBLA.


       INFO (output)
                 = 0:  successful exit.
                 < 0:  if INFO = -i, the i-th argument had an illegal value.
                 > 0:  if SBDSQR did not converge,  INFO  specifies  how  many
                 superdiagonals  of  an intermediate bidiagonal form B did not
                 converge to zero. See  the  description  of  WORK  above  for
                 details.




                                  7 Nov 2015                        sgesvd(3P)