NAME

bdism, sbdism, dbdism, cbdism, zbdism - block diagonal format triangular solve


SYNOPSIS

  SUBROUTINE SBDISM( TRANSA, MB, N, UNITD, DV, ALPHA, DESCRA,
 *           VAL, BLDA, IBDIAG, NBDIAG, LB,
 *           B, LDB, BETA, C, LDC, WORK, LWORK )
  INTEGER*4  TRANSA, MB, N, UNITD, DESCRA(5), BLDA, NBDIAG, LB,
 *           LDB, LDC, LWORK
  INTEGER*4  IBDIAG(NBDIAG)
  REAL*4     ALPHA, BETA
  REAL*4     DV(MB*LB*LB), VAL(LB*LB*BLDA, NBDIAG), B(LDB,*), C(LDC,*),
 *           WORK(LWORK)
  SUBROUTINE DBDISM( TRANSA, MB, N, UNITD, DV, ALPHA, DESCRA,
 *           VAL, BLDA, IBDIAG, NBDIAG, LB,
 *           B, LDB, BETA, C, LDC, WORK, LWORK)
  INTEGER*4  TRANSA, MB, N, UNITD, DESCRA(5), BLDA, NBDIAG, LB,
 *           LDB, LDC, LWORK
  INTEGER*4  IBDIAG(NBDIAG)
  REAL*8     ALPHA, BETA
  REAL*8     DV(MB*LB*LB), VAL(LB*LB*BLDA, NBDIAG), B(LDB,*), C(LDC,*),
 *           WORK(LWORK)
  SUBROUTINE CBDISM( TRANSA, MB, N, UNITD, DV, ALPHA, DESCRA,
 *           VAL, BLDA, IBDIAG, NBDIAG, LB,
 *           B, LDB, BETA, C, LDC, WORK, LWORK )
  INTEGER*4  TRANSA, MB, N, UNITD, DESCRA(5), BLDA, NBDIAG, LB,
 *           LDB, LDC, LWORK
  INTEGER*4  IBDIAG(NBDIAG)
  COMPLEX*8  ALPHA, BETA
  COMPLEX*8  DV(MB*LB*LB), VAL(LB*LB*BLDA, NBDIAG), B(LDB,*), C(LDC,*),
 *           WORK(LWORK)
  SUBROUTINE ZBDISM( TRANSA, MB, N, UNITD, DV, ALPHA, DESCRA,
 *           VAL, BLDA, IBDIAG, NBDIAG, LB,
 *           B, LDB, BETA, C, LDC, WORK, LWORK)
  INTEGER*4  TRANSA, MB, N, UNITD, DESCRA(5), BLDA, NBDIAG, LB,
 *           LDB, LDC, LWORK
  INTEGER*4  IBDIAG(NBDIAG)
  COMPLEX*16 ALPHA, BETA
  COMPLEX*16 DV(MB*LB*LB), VAL(LB*LB*BLDA, NBDIAG), B(LDB,*), C(LDC,*),
 *           WORK(LWORK)


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 block  diagonal matrix,  A is a unit, or non-unit, upper or 
 lower triangular matrix represented in block diagonal 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)
 All blocks of A on the main diagonal MUST be triangular matrices.


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.
 MB            Number of block 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)
 DV()          Array of length MB*LB*LB containing the elements of
               the diagonal blocks of the matrix D.  The size of each
               square block is LB-by-LB and each block 
               is stored in standard column-major form.
 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, DESCRA(1)=3 is only supported.

               DESCRA(2) upper/lower triangular indicator
                 1 : lower
                 2 : upper
               DESCRA(3) main diagonal type
                 0 : non-identity blocks on the main diagonal
                 1 : identity diagonal block
               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 LB*LB*BLDA-by-NBDIAG scalar array
               consisting of the NBDIAG non-zero block diagonal.
               Each dense block is stored in standard column-major form.

 BLDA          Leading block dimension of VAL().  Should be greater
               than or equal to MB.
 IBDIAG()      integer array of length NBDIAG consisting of the
               corresponding diagonal offsets of the non-zero block 
               diagonals of A in VAL.  Lower triangular block diagonals 
               have negative offsets, the main block diagonal has offset
               0, and upper triangular block diagonals have positive offset. 
               Elements of IBDIAG  MUST be sorted in  increasing order.
 NBDIAG        The number of non-zero block diagonals in A.
 LB            Dimension of dense blocks composing A.
 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  size
               of LWORK.

 LWORK        length of WORK array. LWORK should be at least
              MB*LB.

              For good performance, LWORK should generally be larger. 
              For optimum performance on multiple processors, LWORK 
              >=MB*LB*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/


NOTES/BUGS

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