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CLALSD(1)		 LAPACK routine (version 3.2)		     CLALSD(1)

NAME
       CLALSD  - 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

SYNOPSIS
       SUBROUTINE CLALSD( UPLO, SMLSIZ, N, NRHS, D, E, B,  LDB,	 RCOND,	 RANK,
			  WORK, RWORK, IWORK, INFO )

	   CHARACTER	  UPLO

	   INTEGER	  INFO, LDB, N, NRHS, RANK, SMLSIZ

	   REAL		  RCOND

	   INTEGER	  IWORK( * )

	   REAL		  D( * ), E( * ), RWORK( * )

	   COMPLEX	  B( LDB, * ), WORK( * )

PURPOSE
       CLALSD  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/sub‐
       tract, or on those binary machines without guard digits which  subtract
       like  the  Cray XMP, Cray YMP, Cray C 90, or Cray 2.  It could conceiv‐
       ably fail on hexadecimal or decimal machines without guard digits,  but
       we know of none.

ARGUMENTS
       UPLO   (input) CHARACTER*1
	      = 'U': D and E define an upper bidiagonal matrix.
	      =	 'L':  D  and  E  define  a   lower bidiagonal matrix.	SMLSIZ
	      (input) INTEGER The maximum size of the subproblems at the  bot‐
	      tom of the computation tree.

       N      (input) INTEGER
	      The dimension of the  bidiagonal matrix.	N >= 0.

       NRHS   (input) INTEGER
	      The number of columns of B. NRHS must be at least 1.

       D      (input/output) 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.

       E      (input/output) REAL array, dimension (N-1)
	      Contains the super-diagonal entries of  the  bidiagonal  matrix.
	      On exit, E has been destroyed.

       B      (input/output) COMPLEX array, dimension (LDB,NRHS)
	      On  input,  B contains the right hand sides of the least squares
	      problem. On output, B contains the solution X.

       LDB    (input) INTEGER
	      The leading dimension of B in the calling subprogram.  LDB  must
	      be at least max(1,N).

       RCOND  (input) 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).

       RANK   (output) INTEGER
	      The number of singular values of A greater than RCOND times  the
	      largest singular value.

       WORK   (workspace) COMPLEX array, dimension (N * NRHS).

       RWORK  (workspace) REAL array, dimension at least
	      (9*N  +  2*N*SMLSIZ + 8*N*NLVL + 3*SMLSIZ*NRHS + (SMLSIZ+1)**2),
	      where NLVL = MAX( 0, INT( LOG_2( MIN( M,N )/(SMLSIZ+1) ) ) + 1 )

       IWORK  (workspace) INTEGER array, dimension (3*N*NLVL + 11*N).

       INFO   (output) INTEGER
	      = 0:  successful exit.
	      < 0:  if INFO = -i, the i-th argument had an illegal value.
	      > 0:  The algorithm failed to compute an	singular  value	 while
	      working  on  the	submatrix lying in rows and columns INFO/(N+1)
	      through MOD(INFO,N+1).

FURTHER DETAILS
       Based on contributions by
	  Ming Gu and Ren-Cang Li, Computer Science Division, University of
	    California at Berkeley, USA
	  Osni Marques, LBNL/NERSC, USA

 LAPACK routine (version 3.2)	 November 2008			     CLALSD(1)
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