sbdsdc(3)

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      COMPQ, UPLO
    INTEGER        INFO, LDU, LDVT, N
    INTEGER        IQ( * ), IWORK( * )
    REAL           D( * ), E( * ), Q( * ), U(  LDU,  *  ),
VT( LDVT, * ), WORK( * )

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 ma
trix with non-negative diagonal elements (the singular values of
B), and U and VT are orthogonal matrices of left and right singu
lar vectors, respectively. SBDSDC can be used to compute all sin
gular values, and optionally, singular vectors or singular vec
tors 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 ma
chines 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 singu
lar values using the divide and conquer method.

ARGUMENTS

UPLO (input) CHARACTER*1
= 'U': B is upper bidiagonal.
= 'L': B is lower bidiagonal.
COMPQ (input) CHARACTER*1
Specifies whether singular vectors are to be com
puted as follows:
= 'N': Compute singular values only;
= 'P': Compute singular values and compute singu
lar vectors in compact form; = 'I': Compute singular values and
singular vectors.
N (input) INTEGER
The order of the matrix B. N >= 0.
D (input/output) REAL array, dimension (N)
On entry, the n diagonal elements of the bidiago
nal matrix B. On exit, if INFO=0, the singular values of B.
E (input/output) REAL array, dimension (N)
On entry, the elements of E contain the offdiago
nal elements of the bidiagonal matrix whose SVD is desired. On
exit, E has been destroyed.
U (output) REAL array, dimension (LDU,N)
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) INTEGER
The leading dimension of the array U. LDU >= 1.
If singular vectors are desired, then LDU >= max( 1, N ).
VT (output) REAL array, dimension (LDVT,N)
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) INTEGER
The leading dimension of the array VT. LDVT >= 1.
If singular vectors are desired, then LDVT >= max( 1, N ).
Q (output) REAL array, dimension (LDQ)
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 re
turned by ILAENV and is equal to the maximum size of the subprob
lems at the bottom of the computation tree (usually about 25).
For other values of COMPQ, Q is not referenced.
IQ (output) INTEGER array, dimension (LDIQ)
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/(SML
SIZ+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) REAL array, dimension (LWORK)
If COMPQ = 'N' then LWORK >= (4 * N). If COMPQ =
'P' then LWORK >= (6 * N). If COMPQ = 'I' then LWORK >= (3 *
N**2 + 4 * N).
IWORK (workspace) INTEGER array, dimension (8*N)
INFO (output) INTEGER
= 0: successful exit.
< 0: if INFO = -i, the i-th argument had an ille
gal value.
> 0: The algorithm failed to compute an singular
value. The update process of divide and conquer failed.

FURTHER DETAILS

Based on contributions by
Ming Gu and Huan Ren, Computer Science Division, Uni
versity of
California at Berkeley, USA
LAPACK version 3.0 15 June 2000
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