Date: 2013-07-02T14:42:16+00:00

Actual source code: mpicsrperm.c
petsc-3.4.2 2013-07-02

      2: #include <../src/mat/impls/aij/mpi/mpiaij.h>
      5: /*@C
      6:    MatCreateMPIAIJPERM - Creates a sparse parallel matrix whose local
      7:    portions are stored as SEQAIJPERM matrices (a matrix class that inherits
      8:    from SEQAIJ but includes some optimizations to allow more effective
      9:    vectorization).  The same guidelines that apply to MPIAIJ matrices for
     10:    preallocating the matrix storage apply here as well.

     12:       Collective on MPI_Comm

     14:    Input Parameters:
     15: +  comm - MPI communicator
     16: .  m - number of local rows (or PETSC_DECIDE to have calculated if M is given)
     17:            This value should be the same as the local size used in creating the
     18:            y vector for the matrix-vector product y = Ax.
     19: .  n - This value should be the same as the local size used in creating the
     20:        x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have
     21:        calculated if N is given) For square matrices n is almost always m.
     22: .  M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
     23: .  N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
     24: .  d_nz  - number of nonzeros per row in DIAGONAL portion of local submatrix
     25:            (same value is used for all local rows)
     26: .  d_nnz - array containing the number of nonzeros in the various rows of the
     27:            DIAGONAL portion of the local submatrix (possibly different for each row)
     28:            or NULL, if d_nz is used to specify the nonzero structure.
     29:            The size of this array is equal to the number of local rows, i.e 'm'.
     30:            For matrices you plan to factor you must leave room for the diagonal entry and
     31:            put in the entry even if it is zero.
     32: .  o_nz  - number of nonzeros per row in the OFF-DIAGONAL portion of local
     33:            submatrix (same value is used for all local rows).
     34: -  o_nnz - array containing the number of nonzeros in the various rows of the
     35:            OFF-DIAGONAL portion of the local submatrix (possibly different for
     36:            each row) or NULL, if o_nz is used to specify the nonzero
     37:            structure. The size of this array is equal to the number
     38:            of local rows, i.e 'm'.

     40:    Output Parameter:
     41: .  A - the matrix

     43:    Notes:
     44:    If the *_nnz parameter is given then the *_nz parameter is ignored

     46:    m,n,M,N parameters specify the size of the matrix, and its partitioning across
     47:    processors, while d_nz,d_nnz,o_nz,o_nnz parameters specify the approximate
     48:    storage requirements for this matrix.

     50:    If PETSC_DECIDE or  PETSC_DETERMINE is used for a particular argument on one
     51:    processor than it must be used on all processors that share the object for
     52:    that argument.

     54:    The user MUST specify either the local or global matrix dimensions
     55:    (possibly both).

     57:    The parallel matrix is partitioned such that the first m0 rows belong to
     58:    process 0, the next m1 rows belong to process 1, the next m2 rows belong
     59:    to process 2 etc.. where m0,m1,m2... are the input parameter 'm'.

     61:    The DIAGONAL portion of the local submatrix of a processor can be defined
     62:    as the submatrix which is obtained by extraction the part corresponding
     63:    to the rows r1-r2 and columns r1-r2 of the global matrix, where r1 is the
     64:    first row that belongs to the processor, and r2 is the last row belonging
     65:    to the this processor. This is a square mxm matrix. The remaining portion
     66:    of the local submatrix (mxN) constitute the OFF-DIAGONAL portion.

     68:    If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored.

     70:    When calling this routine with a single process communicator, a matrix of
     71:    type SEQAIJPERM is returned.  If a matrix of type MPIAIJPERM is desired
     72:    for this type of communicator, use the construction mechanism:
     73:      MatCreate(...,&A); MatSetType(A,MPIAIJ); MatMPIAIJSetPreallocation(A,...);

     75:    By default, this format uses inodes (identical nodes) when possible.
     76:    We search for consecutive rows with the same nonzero structure, thereby
     77:    reusing matrix information to achieve increased efficiency.

     79:    Options Database Keys:
     80: +  -mat_no_inode  - Do not use inodes
     81: .  -mat_inode_limit <limit> - Sets inode limit (max limit=5)
     82: -  -mat_aij_oneindex - Internally use indexing starting at 1
     83:         rather than 0.  Note that when calling MatSetValues(),
     84:         the user still MUST index entries starting at 0!

     86:    Level: intermediate

     88: .keywords: matrix, cray, sparse, parallel

     90: .seealso: MatCreate(), MatCreateSeqAIJPERM(), MatSetValues()
     91: @*/
     92: PetscErrorCode  MatCreateMPIAIJPERM(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[],Mat *A)
     93: {
     95:   PetscMPIInt    size;

     98:   MatCreate(comm,A);
     99:   MatSetSizes(*A,m,n,M,N);
    100:   MPI_Comm_size(comm,&size);
    101:   if (size > 1) {
    102:     MatSetType(*A,MATMPIAIJPERM);
    103:     MatMPIAIJSetPreallocation(*A,d_nz,d_nnz,o_nz,o_nnz);
    104:   } else {
    105:     MatSetType(*A,MATSEQAIJPERM);
    106:     MatSeqAIJSetPreallocation(*A,d_nz,d_nnz);
    107:   }
    108:   return(0);
    109: }

    111: extern PetscErrorCode MatConvert_SeqAIJ_SeqAIJPERM(Mat,MatType,MatReuse,Mat*);

    115: PetscErrorCode  MatMPIAIJSetPreallocation_MPIAIJPERM(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[])
    116: {
    117:   Mat_MPIAIJ     *b = (Mat_MPIAIJ*)B->data;

    121:   MatMPIAIJSetPreallocation_MPIAIJ(B,d_nz,d_nnz,o_nz,o_nnz);
    122:   MatConvert_SeqAIJ_SeqAIJPERM(b->A, MATSEQAIJPERM, MAT_REUSE_MATRIX, &b->A);
    123:   MatConvert_SeqAIJ_SeqAIJPERM(b->B, MATSEQAIJPERM, MAT_REUSE_MATRIX, &b->B);
    124:   return(0);
    125: }

    129: PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJPERM(Mat A,MatType type,MatReuse reuse,Mat *newmat)
    130: {
    132:   Mat            B = *newmat;

    135:   if (reuse == MAT_INITIAL_MATRIX) {
    136:     MatDuplicate(A,MAT_COPY_VALUES,&B);
    137:   }

    139:   PetscObjectChangeTypeName((PetscObject) B, MATMPIAIJPERM);
    140:   PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocation_C",MatMPIAIJSetPreallocation_MPIAIJPERM);
    141:   *newmat = B;
    142:   return(0);
    143: }

    147: PETSC_EXTERN PetscErrorCode MatCreate_MPIAIJPERM(Mat A)
    148: {

    152:   MatSetType(A,MATMPIAIJ);
    153:   MatConvert_MPIAIJ_MPIAIJPERM(A,MATMPIAIJPERM,MAT_REUSE_MATRIX,&A);
    154:   return(0);
    155: }

    157: /*MC
    158:    MATAIJPERM - MATAIJPERM = "AIJPERM" - A matrix type to be used for sparse matrices.

    160:    This matrix type is identical to MATSEQAIJPERM when constructed with a single process communicator,
    161:    and MATMPIAIJPERM otherwise.  As a result, for single process communicators,
    162:   MatSeqAIJSetPreallocation() is supported, and similarly MatMPIAIJSetPreallocation() is supported
    163:   for communicators controlling multiple processes.  It is recommended that you call both of
    164:   the above preallocation routines for simplicity.

    166:    Options Database Keys:
    167: . -mat_type aijperm - sets the matrix type to "AIJPERM" during a call to MatSetFromOptions()

    169:   Level: beginner

    171: .seealso: MatCreateMPIAIJPERM(), MATSEQAIJPERM, MATMPIAIJPERM
    172: M*/