!>
!> ZGELSD computes the minimum-norm solution to a real linear least
!> squares problem:
!>     minimize 2-norm(| b - A*x |)
!> using the singular value decomposition (SVD) of A. A is an M-by-N
!> matrix which may be rank-deficient.
!>
!> Several right hand side vectors b and solution vectors x can be
!> handled in a single call; they are stored as the columns of the
!> M-by-NRHS right hand side matrix B and the N-by-NRHS solution
!> matrix X.
!>
!> The problem is solved in three steps:
!> (1) Reduce the coefficient matrix A to bidiagonal form with
!>     Householder transformations, reducing the original problem
!>     into a  (BLS)
!> (2) Solve the BLS using a divide and conquer approach.
!> (3) Apply back all the Householder transformations to solve
!>     the original least squares problem.
!>
!> The effective rank of A is determined by treating as zero those
!> singular values which are less than RCOND times the largest singular
!> value.
!>
!> 

M

!>          M is INTEGER
!>          The number of rows of the matrix A. M >= 0.
!> 

N

!>          N is INTEGER
!>          The number of columns of the matrix A. N >= 0.
!> 

NRHS

!>          NRHS is INTEGER
!>          The number of right hand sides, i.e., the number of columns
!>          of the matrices B and X. NRHS >= 0.
!> 

A

!>          A is COMPLEX*16 array, dimension (LDA,N)
!>          On entry, the M-by-N matrix A.
!>          On exit, A has been destroyed.
!> 

LDA

!>          LDA is INTEGER
!>          The leading dimension of the array A. LDA >= max(1,M).
!> 

B

!>          B is COMPLEX*16 array, dimension (LDB,NRHS)
!>          On entry, the M-by-NRHS right hand side matrix B.
!>          On exit, B is overwritten by the N-by-NRHS solution matrix X.
!>          If m >= n and RANK = n, the residual sum-of-squares for
!>          the solution in the i-th column is given by the sum of
!>          squares of the modulus of elements n+1:m in that column.
!> 

LDB

!>          LDB is INTEGER
!>          The leading dimension of the array B.  LDB >= max(1,M,N).
!> 

S

!>          S is DOUBLE PRECISION array, dimension (min(M,N))
!>          The singular values of A in decreasing order.
!>          The condition number of A in the 2-norm = S(1)/S(min(m,n)).
!> 

RCOND

!>          RCOND is DOUBLE PRECISION
!>          RCOND is used to determine the effective rank of A.
!>          Singular values S(i) <= RCOND*S(1) are treated as zero.
!>          If RCOND < 0, machine precision is used instead.
!> 

RANK

!>          RANK is INTEGER
!>          The effective rank of A, i.e., the number of singular values
!>          which are greater than RCOND*S(1).
!> 

WORK

!>          WORK is COMPLEX*16 array, dimension (MAX(1,LWORK))
!>          On exit, if INFO = 0, WORK(1) returns the optimal LWORK.
!> 

LWORK

!>          LWORK is INTEGER
!>          The dimension of the array WORK. LWORK must be at least 1.
!>          The exact minimum amount of workspace needed depends on M,
!>          N and NRHS. As long as LWORK is at least
!>              2*N + N*NRHS
!>          if M is greater than or equal to N or
!>              2*M + M*NRHS
!>          if M is less than N, the code will execute correctly.
!>          For good performance, LWORK should generally be larger.
!>
!>          If LWORK = -1, then a workspace query is assumed; the routine
!>          only calculates the optimal size of the array WORK and the
!>          minimum sizes of the arrays RWORK and IWORK, and returns
!>          these values as the first entries of the WORK, RWORK and
!>          IWORK arrays, and no error message related to LWORK is issued
!>          by XERBLA.
!> 

RWORK

!>          RWORK is DOUBLE PRECISION array, dimension (MAX(1,LRWORK))
!>          LRWORK >=
!>             10*N + 2*N*SMLSIZ + 8*N*NLVL + 3*SMLSIZ*NRHS +
!>             MAX( (SMLSIZ+1)**2, N*(1+NRHS) + 2*NRHS )
!>          if M is greater than or equal to N or
!>             10*M + 2*M*SMLSIZ + 8*M*NLVL + 3*SMLSIZ*NRHS +
!>             MAX( (SMLSIZ+1)**2, N*(1+NRHS) + 2*NRHS )
!>          if M is less than N, the code will execute correctly.
!>          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), and
!>             NLVL = MAX( 0, INT( LOG_2( MIN( M,N )/(SMLSIZ+1) ) ) + 1 )
!>          On exit, if INFO = 0, RWORK(1) returns the minimum LRWORK.
!> 

IWORK

!>          IWORK is INTEGER array, dimension (MAX(1,LIWORK))
!>          LIWORK >= max(1, 3*MINMN*NLVL + 11*MINMN),
!>          where MINMN = MIN( M,N ).
!>          On exit, if INFO = 0, IWORK(1) returns the minimum LIWORK.
!> 

INFO

!>          INFO is INTEGER
!>          = 0: successful exit
!>          < 0: if INFO = -i, the i-th argument had an illegal value.
!>          > 0:  the algorithm for computing the SVD failed to converge;
!>                if INFO = i, i off-diagonal elements of an intermediate
!>                bidiagonal form did not converge to zero.
!> 

Univ. of Tennessee

Univ. of California Berkeley

Univ. of Colorado Denver

NAG Ltd.

Ming Gu and Ren-Cang Li, Computer Science Division, University of California at Berkeley, USA
Osni Marques, LBNL/NERSC, USA