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dbdsdc(3P)		    Sun Performance Library		    dbdsdc(3P)

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

SYNOPSIS
       SUBROUTINE DBDSDC(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(*)
       DOUBLE PRECISION D(*), E(*), U(LDU,*), VT(LDVT,*), Q(*), WORK(*)

       SUBROUTINE DBDSDC_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(*)
       DOUBLE PRECISION 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(8), DIMENSION(:) :: D, E, Q, WORK
       REAL(8), 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(8), DIMENSION(:) :: D, E, Q, WORK
       REAL(8), DIMENSION(:,:) :: U, VT

   C INTERFACE
       #include <sunperf.h>

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

       void dbdsdc_64(char uplo, char compq, long n,  double  *d,  double  *e,
		 double	 *u,  long ldu, double *vt, long ldvt, double *q, long
		 *iq, long *info);

PURPOSE
       dbdsdc 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 orthogo‐
       nal matrices of left and right singular vectors,	 respectively.	DBDSDC
       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 DLASD3 for details.

       The  code  currently  call  DLASDQ 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)
		 = 'U':	 B is upper bidiagonal.
		 = 'L':	 B is lower bidiagonal.

       COMPQ (input)
		 Specifies whether singular vectors are to be computed as fol‐
		 lows:
		 = 'N':	 Compute singular values only;
		 = 'P':	 Compute singular values and compute singular  vectors
		 in compact form; = 'I':  Compute singular values and singular
		 vectors.

       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 singu‐
		 lar vectors are desired, then LDVT >= max( 1, N ).

       Q (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,
		 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 >= (4 * N).  If COMPQ = 'P' then
		 LWORK >= (8 * N + (SMLSIZ+1) * (SMLSIZ+1) -2).	  If  COMPQ  =
		 'I' then LWORK >= (3 * N**2 + 4 * N).

       IWORK (workspace)
		 dimension(8*N)

       INFO (output)
		 = 0:  successful exit.
		 < 0:  if INFO = -i, the i-th argument had an illegal 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, University of
	  California at Berkeley, USA

				  6 Mar 2009			    dbdsdc(3P)
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