LAPACK  3.4.2
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slalsd.f File Reference

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Functions/Subroutines

subroutine slalsd (UPLO, SMLSIZ, N, NRHS, D, E, B, LDB, RCOND, RANK, WORK, IWORK, INFO)
 SLALSD uses the singular value decomposition of A to solve the least squares problem.

Function/Subroutine Documentation

subroutine slalsd ( character  UPLO,
integer  SMLSIZ,
integer  N,
integer  NRHS,
real, dimension( * )  D,
real, dimension( * )  E,
real, dimension( ldb, * )  B,
integer  LDB,
real  RCOND,
integer  RANK,
real, dimension( * )  WORK,
integer, dimension( * )  IWORK,
integer  INFO 
)

SLALSD uses the singular value decomposition of A to solve the least squares problem.

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Purpose:
 SLALSD uses the singular value decomposition of A to solve the least
 squares problem of finding X to minimize the Euclidean norm of each
 column of A*X-B, where A is N-by-N upper bidiagonal, and X and B
 are N-by-NRHS. The solution X overwrites B.

 The singular values of A smaller than RCOND times the largest
 singular value are treated as zero in solving the least squares
 problem; in this case a minimum norm solution is returned.
 The actual singular values are returned in D in ascending order.

 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 XMP, Cray YMP, Cray C 90, or Cray 2.
 It could conceivably fail on hexadecimal or decimal machines
 without guard digits, but we know of none.
Parameters:
[in]UPLO
          UPLO is CHARACTER*1
         = 'U': D and E define an upper bidiagonal matrix.
         = 'L': D and E define a  lower bidiagonal matrix.
[in]SMLSIZ
          SMLSIZ is INTEGER
         The maximum size of the subproblems at the bottom of the
         computation tree.
[in]N
          N is INTEGER
         The dimension of the  bidiagonal matrix.  N >= 0.
[in]NRHS
          NRHS is INTEGER
         The number of columns of B. NRHS must be at least 1.
[in,out]D
          D is REAL array, dimension (N)
         On entry D contains the main diagonal of the bidiagonal
         matrix. On exit, if INFO = 0, D contains its singular values.
[in,out]E
          E is REAL array, dimension (N-1)
         Contains the super-diagonal entries of the bidiagonal matrix.
         On exit, E has been destroyed.
[in,out]B
          B is REAL array, dimension (LDB,NRHS)
         On input, B contains the right hand sides of the least
         squares problem. On output, B contains the solution X.
[in]LDB
          LDB is INTEGER
         The leading dimension of B in the calling subprogram.
         LDB must be at least max(1,N).
[in]RCOND
          RCOND is REAL
         The singular values of A less than or equal to RCOND times
         the largest singular value are treated as zero in solving
         the least squares problem. If RCOND is negative,
         machine precision is used instead.
         For example, if diag(S)*X=B were the least squares problem,
         where diag(S) is a diagonal matrix of singular values, the
         solution would be X(i) = B(i) / S(i) if S(i) is greater than
         RCOND*max(S), and X(i) = 0 if S(i) is less than or equal to
         RCOND*max(S).
[out]RANK
          RANK is INTEGER
         The number of singular values of A greater than RCOND times
         the largest singular value.
[out]WORK
          WORK is REAL array, dimension at least
         (9*N + 2*N*SMLSIZ + 8*N*NLVL + N*NRHS + (SMLSIZ+1)**2),
         where NLVL = max(0, INT(log_2 (N/(SMLSIZ+1))) + 1).
[out]IWORK
          IWORK is INTEGER array, dimension at least
         (3*N*NLVL + 11*N)
[out]INFO
          INFO is INTEGER
         = 0:  successful exit.
         < 0:  if INFO = -i, the i-th argument had an illegal value.
         > 0:  The algorithm failed to compute a singular value while
               working on the submatrix lying in rows and columns
               INFO/(N+1) through MOD(INFO,N+1).
Author:
Univ. of Tennessee
Univ. of California Berkeley
Univ. of Colorado Denver
NAG Ltd.
Date:
September 2012
Contributors:
Ming Gu and Ren-Cang Li, Computer Science Division, University of California at Berkeley, USA
Osni Marques, LBNL/NERSC, USA

Definition at line 179 of file slalsd.f.

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