dgesdd - N matrix A, optionally computing the left and right singular vectors
SUBROUTINE DGESDD(JOBZ, M, N, A, LDA, S, U, LDU, VT, LDVT, WORK, LWORK, IWORK, INFO) CHARACTER*1 JOBZ INTEGER M, N, LDA, LDU, LDVT, LWORK, INFO INTEGER IWORK(*) DOUBLE PRECISION A(LDA,*), S(*), U(LDU,*), VT(LDVT,*), WORK(*) SUBROUTINE DGESDD_64(JOBZ, M, N, A, LDA, S, U, LDU, VT, LDVT, WORK, LWORK, IWORK, INFO) CHARACTER*1 JOBZ INTEGER*8 M, N, LDA, LDU, LDVT, LWORK, INFO INTEGER*8 IWORK(*) DOUBLE PRECISION A(LDA,*), S(*), U(LDU,*), VT(LDVT,*), WORK(*) F95 INTERFACE SUBROUTINE GESDD(JOBZ, M, N, A, LDA, S, U, LDU, VT, LDVT, WORK, LWORK, IWORK, INFO) CHARACTER(LEN=1) :: JOBZ INTEGER :: M, N, LDA, LDU, LDVT, LWORK, INFO INTEGER, DIMENSION(:) :: IWORK REAL(8), DIMENSION(:) :: S, WORK REAL(8), DIMENSION(:,:) :: A, U, VT SUBROUTINE GESDD_64(JOBZ, M, N, A, LDA, S, U, LDU, VT, LDVT, WORK, LWORK, IWORK, INFO) CHARACTER(LEN=1) :: JOBZ INTEGER(8) :: M, N, LDA, LDU, LDVT, LWORK, INFO INTEGER(8), DIMENSION(:) :: IWORK REAL(8), DIMENSION(:) :: S, WORK REAL(8), DIMENSION(:,:) :: A, U, VT C INTERFACE #include <sunperf.h> void dgesdd(char jobz, int m, int n, double *a, int lda, double *s, double *u, int ldu, double *vt, int ldvt, int *info); void dgesdd_64(char jobz, long m, long n, double *a, long lda, double *s, double *u, long ldu, double *vt, long ldvt, long *info);
Oracle Solaris Studio Performance Library dgesdd(3P)
NAME
dgesdd - compute the singular value decomposition (SVD) of a real M-by-
N matrix A, optionally computing the left and right singular vectors
SYNOPSIS
SUBROUTINE DGESDD(JOBZ, M, N, A, LDA, S, U, LDU, VT, LDVT, WORK,
LWORK, IWORK, INFO)
CHARACTER*1 JOBZ
INTEGER M, N, LDA, LDU, LDVT, LWORK, INFO
INTEGER IWORK(*)
DOUBLE PRECISION A(LDA,*), S(*), U(LDU,*), VT(LDVT,*), WORK(*)
SUBROUTINE DGESDD_64(JOBZ, M, N, A, LDA, S, U, LDU, VT, LDVT, WORK,
LWORK, IWORK, INFO)
CHARACTER*1 JOBZ
INTEGER*8 M, N, LDA, LDU, LDVT, LWORK, INFO
INTEGER*8 IWORK(*)
DOUBLE PRECISION A(LDA,*), S(*), U(LDU,*), VT(LDVT,*), WORK(*)
F95 INTERFACE
SUBROUTINE GESDD(JOBZ, M, N, A, LDA, S, U, LDU, VT, LDVT,
WORK, LWORK, IWORK, INFO)
CHARACTER(LEN=1) :: JOBZ
INTEGER :: M, N, LDA, LDU, LDVT, LWORK, INFO
INTEGER, DIMENSION(:) :: IWORK
REAL(8), DIMENSION(:) :: S, WORK
REAL(8), DIMENSION(:,:) :: A, U, VT
SUBROUTINE GESDD_64(JOBZ, M, N, A, LDA, S, U, LDU, VT, LDVT,
WORK, LWORK, IWORK, INFO)
CHARACTER(LEN=1) :: JOBZ
INTEGER(8) :: M, N, LDA, LDU, LDVT, LWORK, INFO
INTEGER(8), DIMENSION(:) :: IWORK
REAL(8), DIMENSION(:) :: S, WORK
REAL(8), DIMENSION(:,:) :: A, U, VT
C INTERFACE
#include <sunperf.h>
void dgesdd(char jobz, int m, int n, double *a, int lda, double *s,
double *u, int ldu, double *vt, int ldvt, int *info);
void dgesdd_64(char jobz, long m, long n, double *a, long lda, double
*s, double *u, long ldu, double *vt, long ldvt, long *info);
PURPOSE
dgesdd computes the singular value decomposition (SVD) of a real M-by-N
matrix A, optionally computing the left and right singular vectors. If
singular vectors are desired, it uses a divide-and-conquer algorithm.
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 VT = V**T, not V.
The divide and conquer algorithm 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 dig-
its, but we know of none.
ARGUMENTS
JOBZ (input)
Specifies options for computing all or part of the matrix U:
= 'A': all M columns of U and all N rows of V**T are
returned in the arrays U and VT; = 'S': the first min(M,N)
columns of U and the first min(M,N) rows of V**T are returned
in the arrays U and VT; = 'O': If M >= N, the first N col-
umns of U are overwritten on the array A and all rows of V**T
are returned in the array VT; otherwise, all columns of U are
returned in the array U and the first M rows of V**T are
overwritten on the array A; = 'N': no columns of U or rows
of V**T are computed.
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 JOBZ = 'O', A is
overwritten with the first N columns of U (the left singular
vectors, stored columnwise) if M >= N; A is overwritten with
the first M rows of V**T (the right singular vectors, stored
rowwise) otherwise. if JOBZ .ne. 'O', the contents of A are
destroyed.
LDA (input)
The leading dimension of the array A. LDA >= max(1,M).
S (output)
The singular values of A, sorted so that S(i) >= S(i+1).
U (output)
UCOL = M if JOBZ = 'A' or JOBZ = 'O' and M < N; UCOL =
min(M,N) if JOBZ = 'S'. If JOBZ = 'A' or JOBZ = 'O' and M <
N, U contains the M-by-M orthogonal matrix U; if JOBZ = 'S',
U contains the first min(M,N) columns of U (the left singular
vectors, stored columnwise); if JOBZ = 'O' and M >= N, or
JOBZ = 'N', U is not referenced.
LDU (input)
The leading dimension of the array U. LDU >= 1; if JOBZ =
'S' or 'A' or JOBZ = 'O' and M < N, LDU >= M.
VT (output)
If JOBZ = 'A' or JOBZ = 'O' and M >= N, VT contains the N-by-
N orthogonal matrix V**T; if JOBZ = 'S', VT contains the
first min(M,N) rows of V**T (the right singular vectors,
stored rowwise); if JOBZ = 'O' and M < N, or JOBZ = 'N', VT
is not referenced.
LDVT (input)
The leading dimension of the array VT. LDVT >= 1; if JOBZ =
'A' or JOBZ = 'O' and M >= N, LDVT >= N; if JOBZ = 'S', LDVT
>= min(M,N).
WORK (workspace)
On exit, if INFO = 0, WORK(1) returns the optimal LWORK;
LWORK (input)
The dimension of the array WORK. LWORK >= 1. If LWORK = -1,
then a workspace query is assumed. In this case, 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. The minimum workspace
size requirement is as follows:
If M is much larger than N such that M >= (N * 11/6):
If JOBZ = 'N', LWORK >= 7*N + N
If JOBZ = 'O', LWORK >= 3*N*N + 4*N + 2*N*N + 3*N
If JOBZ = 'S', LWORK >= 3*N*N + 4*N + N*N + 3*N
If JOBZ = 'A', LWORK >= 3*N*N + 4*N + N*N + 3*N If M is at
least N but not much larger (N <= M < (N * 11/6)):
If JOBZ = 'N', LWORK >= 3*N + MAX(M, (7*N))
If JOBZ = 'O', LWORK >= 3*N + MAX(M, N*N + (3*N*N + 4*N))
If JOBZ = 'S', LWORK >= 3*N + MAX(M, (3*N*N + 4*N))
If JOBZ = 'A', LWORK >= 3*N + MAX( M, (3*N*N + 4*N)) If N
is much larger than M such that N >= (M * 11/6):
If JOBZ = 'N', LWORK >= 7*M + M
If JOBZ = 'O', LWORK >= 3*M*M + 4*M + 2*M*M + 3*M
If JOBZ = 'S', LWORK >= 3*M*M + 4*M + M*M + 3*M
If JOBZ = 'A', LWORK >= 3*M*M + 4*M + M*M + 3*M If N is at
least M but not much larger (M <= N < (M * 11/6):
If JOBZ = 'N', LWORK >= 3*M + MAX(N, 7*M)
If JOBZ = 'O', LWORK >= 3*M + MAX(N, M*M + (3*M*M + 4*M))
If JOBZ = 'S', LWORK >= 3*M + MAX(N, (3*M*M + 4*M))
If JOBZ = 'A', LWORK >= 3*M + MAX(N, (3*M*M + 4*M))
IWORK (workspace)
dimension(8*MIN(M,N))
INFO (output)
= 0: successful exit.
< 0: if INFO = -i, the i-th argument had an illegal value.
> 0: SBDSDC did not converge, updating process failed.
FURTHER DETAILS
Based on contributions by
Ming Gu and Huan Ren, Computer Science Division, University of
California at Berkeley, USA
7 Nov 2015 dgesdd(3P)