Contents


NAME

     cellsm - Ellpack format triangular solve

SYNOPSIS

       SUBROUTINE CELLSM( TRANSA, M, N, UNITD, DV, ALPHA, DESCRA,
      *           VAL, INDX, LDA, MAXNZ,
      *           B, LDB, BETA, C, LDC, WORK, LWORK )
       INTEGER    TRANSA, M, N, UNITD, DESCRA(5), LDA, MAXNZ,
      *           LDB, LDC, LWORK
       INTEGER    INDX(LDA,MAXNZ)
       COMPLEX    ALPHA, BETA
       COMPLEX    DV(M), VAL(LDA,MAXNZ), B(LDB,*), C(LDC,*), WORK(LWORK)

       SUBROUTINE CELLSM_64( TRANSA, M, N, UNITD, DV, ALPHA, DESCRA,
      *           VAL, INDX, LDA, MAXNZ,
      *           B, LDB, BETA, C, LDC, WORK, LWORK )
       INTEGER*8  TRANSA, M, N, UNITD, DESCRA(5), LDA, MAXNZ,
      *           LDB, LDC, LWORK
       INTEGER*8  INDX(LDA,MAXNZ)
       COMPLEX    ALPHA, BETA
       COMPLEX    DV(M), VAL(LDA,MAXNZ), B(LDB,*), C(LDC,*), WORK(LWORK)

     F95 INTERFACE

       SUBROUTINE ELLSM( TRANSA, M, [N], UNITD, DV, ALPHA, DESCRA, VAL,
      *    INDX, [LDA], MAXNZ, B, [LDB], BETA, C, [LDC], [WORK], [LWORK])
       INTEGER    TRANSA, M,  MAXNZ
       INTEGER, DIMENSION(:) ::  DESCRA
       INTEGER, DIMENSION(:, :) ::    INDX
       COMPLEX    ALPHA, BETA
       COMPLEX, DIMENSION(:) ::  DV
       COMPLEX, DIMENSION(:, :) ::  VAL, B, C

       SUBROUTINE ELLSM_64( TRANSA, M, [N], UNITD, DV, ALPHA, DESCRA, VAL,
      *    INDX, [LDA], MAXNZ, B, [LDB], BETA, C, [LDC], [WORK], [LWORK])
       INTEGER*8    TRANSA, M,  MAXNZ
       INTEGER*8, DIMENSION(:) ::  DESCRA
       INTEGER*8, DIMENSION(:, :) ::    INDX
       COMPLEX    ALPHA, BETA
       COMPLEX, DIMENSION(:) ::  DV
       COMPLEX, DIMENSION(:, :) ::  VAL, B, C

DESCRIPTION

        C <- ALPHA  op(A) B + BETA C     C <- ALPHA D op(A) B + BETA C
        C <- ALPHA op(A) D B + BETA C

      where ALPHA and BETA are scalar, C and B are m by n dense matrices,
      D is a diagonal scaling matrix,  A is a unit, or non-unit, upper or
      lower triangular matrix represented in Ellpack format and
      op( A )  is one  of
       op( A ) = inv(A) or  op( A ) = inv(A')  or  op( A ) =inv(conjg( A' ))
       (inv denotes matrix inverse,  ' indicates matrix transpose)

ARGUMENTS

      TRANSA        Indicates how to operate with the sparse matrix
                      0 : operate with matrix
                      1 : operate with transpose matrix
                      2 : operate with the conjugate transpose of matrix.
                          2 is equivalent to 1 if matrix is real.

      M             Number of rows in matrix A

      N             Number of columns in matrix C

      UNITD         Type of scaling:
                      1 : Identity matrix (argument DV[] is ignored)
                      2 : Scale on left (row scaling)
                      3 : Scale on right (column scaling)
                      4 : Automatic row scaling (see section NOTES for
                          further details)

      DV()          Array of length M containing the diagonal entries of the
                    scaling diagonal matrix D.

      ALPHA         Scalar parameter

      DESCRA()      Descriptor argument.  Five element integer array
                    DESCRA(1) matrix structure
                      0 : general
                      1 : symmetric (A=A')
                      2 : Hermitian (A= CONJG(A'))
                      3 : Triangular
                      4 : Skew(Anti)-Symmetric (A=-A')
                      5 : Diagonal
                      6 : Skew-Hermitian (A= -CONJG(A'))

                    Note: For the routine, only DESCRA(1)=3 is supported.

                    DESCRA(2) upper/lower triangular indicator
                      1 : lower
                      2 : upper
                    DESCRA(3) main diagonal type
                      0 : non-unit
                      1 : unit
                    DESCRA(4) Array base  (NOT IMPLEMENTED)
                      0 : C/C++ compatible
                      1 : Fortran compatible
                    DESCRA(5) repeated indices? (NOT IMPLEMENTED)
                      0 : unknown
                      1 : no repeated indices
      VAL()         two-dimensional LDA-by-MAXNZ array such that VAL(I,:)
                    consists of non-zero elements in row I of A, padded by
                    zero values if the row contains less than MAXNZ.

      INDX()        two-dimensional integer LDA-by-MAXNZ array such
                    INDX(I,:) consists of the column indices of the
                    nonzero elements in row I, padded by the integer
                    value I if the number of nonzeros is less than MAXNZ.
                    The column indices MUST be sorted in increasing order
                    for each row.

      LDA           leading dimension of VAL and INDX.

      MAXNZ         max number of nonzeros elements per row.

      B()           rectangular array with first dimension LDB.

      LDB           leading dimension of B

      BETA          Scalar parameter

      C()           rectangular array with first dimension LDC.

      LDC           leading dimension of C

      WORK()        scratch array of length LWORK.

                    On exit,  if LWORK = -1, WORK(1) returns the optimum LWORK.

      LWORK         length of WORK array.  LWORK should be at least M.

                   For good performance, LWORK should generally be larger.
                   For optimum performance on multiple processors, LWORK
                   >=M*N_CPUS where N_CPUS is the maximum number of
                   processors available to the program.

                   If LWORK=0, the routine is to allocate workspace needed.

                   If LWORK = -1, then a workspace query is assumed; the
                   routine only calculates the optimum size of the WORK
                   array, returns this value as the first entry of the WORK
                   array, and no error message related to LWORK is issued
                   by XERBLA.

SEE ALSO

     NIST FORTRAN Sparse Blas User's Guide available at:

     http://math.nist.gov/mcsd/Staff/KRemington/fspblas/

     "Document for the Basic Linear Algebra Subprograms (BLAS)
     Standard", University of Tennessee, Knoxville, Tennessee,
     1996:

     http://www.netlib.org/utk/papers/sparse.ps

NOTES/BUGS
     1. No test for singularity or near-singularity is included
     in this routine. Such tests must be performed before calling
     this routine.

     2. If UNITD =4, the routine scales the rows of A such that
     their 2-norms are one. The scaling may improve the accuracy
     of the computed solution. Corresponding entries of VAL are
     changed only in the particular case. On return DV matrix
     stored as a vector contains the diagonal matrix by which the
     rows have been scaled. UNITD=2 should be used for the next
     calls to the routine with overwritten VAL and DV.

     WORK(1)=0 on return if the scaling has been completed
     successfully, otherwise WORK(1) = -i where i is the row
     number which 2-norm is exactly zero.

     3. If DESCRA(3)=1 and  UNITD < 4, the unit diagonal elements
     might or might not be referenced in the ELL representation
     of a sparse matrix. They are not used anyway in these cases.
     But if UNITD=4, the unit diagonal elements MUST be
     referenced in the ELL representation.

     4. The routine can be applied for solving triangular systems
     when the upper or lower triangle of the general sparse
     matrix A is used. However DESCRA(1) must be equal to 3 in
     this case.