cggsvd(3P) Sun Performance Library cggsvd(3P)NAMEcggsvd - compute the generalized singular value decomposition (GSVD) of
an M-by-N complex matrix A and P-by-N complex matrix B
SYNOPSIS
SUBROUTINE CGGSVD(JOBU, JOBV, JOBQ, M, N, P, K, L, A, LDA, B, LDB,
ALPHA, BETA, U, LDU, V, LDV, Q, LDQ, WORK, WORK2, IWORK3, INFO)
CHARACTER * 1 JOBU, JOBV, JOBQ
COMPLEX A(LDA,*), B(LDB,*), U(LDU,*), V(LDV,*), Q(LDQ,*), WORK(*)
INTEGER M, N, P, K, L, LDA, LDB, LDU, LDV, LDQ, INFO
INTEGER IWORK3(*)
REAL ALPHA(*), BETA(*), WORK2(*)
SUBROUTINE CGGSVD_64(JOBU, JOBV, JOBQ, M, N, P, K, L, A, LDA, B, LDB,
ALPHA, BETA, U, LDU, V, LDV, Q, LDQ, WORK, WORK2, IWORK3, INFO)
CHARACTER * 1 JOBU, JOBV, JOBQ
COMPLEX A(LDA,*), B(LDB,*), U(LDU,*), V(LDV,*), Q(LDQ,*), WORK(*)
INTEGER*8 M, N, P, K, L, LDA, LDB, LDU, LDV, LDQ, INFO
INTEGER*8 IWORK3(*)
REAL ALPHA(*), BETA(*), WORK2(*)
F95 INTERFACE
SUBROUTINE GGSVD(JOBU, JOBV, JOBQ, [M], [N], [P], K, L, A, [LDA], B,
[LDB], ALPHA, BETA, U, [LDU], V, [LDV], Q, [LDQ], [WORK], [WORK2],
IWORK3, [INFO])
CHARACTER(LEN=1) :: JOBU, JOBV, JOBQ
COMPLEX, DIMENSION(:) :: WORK
COMPLEX, DIMENSION(:,:) :: A, B, U, V, Q
INTEGER :: M, N, P, K, L, LDA, LDB, LDU, LDV, LDQ, INFO
INTEGER, DIMENSION(:) :: IWORK3
REAL, DIMENSION(:) :: ALPHA, BETA, WORK2
SUBROUTINE GGSVD_64(JOBU, JOBV, JOBQ, [M], [N], [P], K, L, A, [LDA],
B, [LDB], ALPHA, BETA, U, [LDU], V, [LDV], Q, [LDQ], [WORK],
[WORK2], IWORK3, [INFO])
CHARACTER(LEN=1) :: JOBU, JOBV, JOBQ
COMPLEX, DIMENSION(:) :: WORK
COMPLEX, DIMENSION(:,:) :: A, B, U, V, Q
INTEGER(8) :: M, N, P, K, L, LDA, LDB, LDU, LDV, LDQ, INFO
INTEGER(8), DIMENSION(:) :: IWORK3
REAL, DIMENSION(:) :: ALPHA, BETA, WORK2
C INTERFACE
#include <sunperf.h>
void cggsvd(char jobu, char jobv, char jobq, int m, int n, int p, int
*k, int *l, complex *a, int lda, complex *b, int ldb, float
*alpha, float *beta, complex *u, int ldu, complex *v, int
ldv, complex *q, int ldq, int *iwork3, int *info);
void cggsvd_64(char jobu, char jobv, char jobq, long m, long n, long p,
long *k, long *l, complex *a, long lda, complex *b, long ldb,
float *alpha, float *beta, complex *u, long ldu, complex *v,
long ldv, complex *q, long ldq, long *iwork3, long *info);
PURPOSEcggsvd computes the generalized singular value decomposition (GSVD) of
an M-by-N complex matrix A and P-by-N complex matrix B:
U'*A*Q = D1*( 0 R ), V'*B*Q = D2*( 0 R )
where U, V and Q are unitary matrices, and Z' means the conjugate
transpose of Z. Let K+L = the effective numerical rank of the matrix
(A',B')', then R is a (K+L)-by-(K+L) nonsingular upper triangular
matrix, D1 and D2 are M-by-(K+L) and P-by-(K+L) "diagonal" matrices and
of the following structures, respectively:
If M-K-L >= 0,
K L
D1 = K ( I 0 )
L ( 0 C )
M-K-L ( 0 0 )
K L
D2 = L ( 0 S )
P-L ( 0 0 )
N-K-L K L
( 0 R ) = K ( 0 R11 R12 )
L ( 0 0 R22 )
where
C = diag( ALPHA(K+1), ... , ALPHA(K+L) ),
S = diag( BETA(K+1), ... , BETA(K+L) ),
C**2 + S**2 = I.
R is stored in A(1:K+L,N-K-L+1:N) on exit.
If M-K-L < 0,
K M-K K+L-M
D1 = K ( I 0 0 )
M-K ( 0 C 0 )
K M-K K+L-M
D2 = M-K ( 0 S 0 )
K+L-M ( 0 0 I )
P-L ( 0 0 0 )
N-K-L K M-K K+L-M
( 0 R ) = K ( 0 R11 R12 R13 )
M-K ( 0 0 R22 R23 )
K+L-M ( 0 0 0 R33 )
where
C = diag( ALPHA(K+1), ... , ALPHA(M) ),
S = diag( BETA(K+1), ... , BETA(M) ),
C**2 + S**2 = I.
(R11 R12 R13 ) is stored in A(1:M, N-K-L+1:N), and R33 is stored
( 0 R22 R23 )
in B(M-K+1:L,N+M-K-L+1:N) on exit.
The routine computes C, S, R, and optionally the unitary
transformation matrices U, V and Q.
In particular, if B is an N-by-N nonsingular matrix, then the GSVD of A
and B implicitly gives the SVD of A*inv(B):
A*inv(B) = U*(D1*inv(D2))*V'.
If ( A',B')' has orthnormal columns, then the GSVD of A and B is also
equal to the CS decomposition of A and B. Furthermore, the GSVD can be
used to derive the solution of the eigenvalue problem:
A'*A x = lambda* B'*B x.
In some literature, the GSVD of A and B is presented in the form
U'*A*X = ( 0 D1 ), V'*B*X = ( 0 D2 )
where U and V are orthogonal and X is nonsingular, and D1 and D2 are
``diagonal''. The former GSVD form can be converted to the latter form
by taking the nonsingular matrix X as
X = Q*( I 0 )
( 0 inv(R) )
ARGUMENTS
JOBU (input)
= 'U': Unitary matrix U is computed;
= 'N': U is not computed.
JOBV (input)
= 'V': Unitary matrix V is computed;
= 'N': V is not computed.
JOBQ (input)
= 'Q': Unitary matrix Q is computed;
= 'N': Q is not computed.
M (input) The number of rows of the matrix A. M >= 0.
N (input) The number of columns of the matrices A and B. N >= 0.
P (input) The number of rows of the matrix B. P >= 0.
K (output)
On exit, K and L specify the dimension of the subblocks
described in Purpose. K + L = effective numerical rank of
(A',B')'.
L (output)
On exit, K and L specify the dimension of the subblocks
described in Purpose. K + L = effective numerical rank of
(A',B')'.
A (input/output)
On entry, the M-by-N matrix A. On exit, A contains the tri‐
angular matrix R, or part of R. See Purpose for details.
LDA (input)
The leading dimension of the array A. LDA >= max(1,M).
B (input/output)
On entry, the P-by-N matrix B. On exit, B contains part of
the triangular matrix R if M-K-L < 0. See Purpose for
details.
LDB (input)
The leading dimension of the array B. LDB >= max(1,P).
ALPHA (output)
On exit, ALPHA and BETA contain the generalized singular
value pairs of A and B; ALPHA(1:K) = 1, ALPHA(1:K) = 1,
BETA(1:K) = 0, and if M-K-L >= 0, ALPHA(K+1:K+L) = C,
BETA(K+1:K+L) = S, or if M-K-L < 0, ALPHA(K+1:M)= C,
ALPHA(M+1:K+L)= 0
BETA(K+1:M) = S, BETA(M+1:K+L) = 1 and ALPHA(K+L+1:N) = 0
BETA(K+L+1:N) = 0
BETA (output)
See description of ALPHA.
U (output)
If JOBU = 'U', U contains the M-by-M unitary matrix U. If
JOBU = 'N', U is not referenced.
LDU (input)
The leading dimension of the array U. LDU >= max(1,M) if JOBU
= 'U'; LDU >= 1 otherwise.
V (output)
If JOBV = 'V', V contains the P-by-P unitary matrix V. If
JOBV = 'N', V is not referenced.
LDV (input)
The leading dimension of the array V. LDV >= max(1,P) if JOBV
= 'V'; LDV >= 1 otherwise.
Q (output)
If JOBQ = 'Q', Q contains the N-by-N unitary matrix Q. If
JOBQ = 'N', Q is not referenced.
LDQ (input)
The leading dimension of the array Q. LDQ >= max(1,N) if JOBQ
= 'Q'; LDQ >= 1 otherwise.
WORK (workspace)
dimension(MAX(3*N,M,P)+N)
WORK2 (workspace)
dimension(2*N)
IWORK3 (output)
dimension(N) On exit, IWORK3 stores the sorting information.
More precisely, the following loop will sort ALPHA for I =
K+1, min(M,K+L) swap ALPHA(I) and ALPHA(IWORK3(I)) endfor
such that ALPHA(1) >= ALPHA(2) >= ... >= ALPHA(N).
INFO (output)
= 0: successful exit.
< 0: if INFO = -i, the i-th argument had an illegal value.
> 0: if INFO = 1, the Jacobi-type procedure failed to con‐
verge. For further details, see subroutine CTGSJA.
6 Mar 2009 cggsvd(3P)
