Actual source code: mpicsrperm.c

petsc-3.8.3 2017-12-09
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  2:  #include <../src/mat/impls/aij/mpi/mpiaij.h>
  3: /*@C
  4:    MatCreateMPIAIJPERM - Creates a sparse parallel matrix whose local
  5:    portions are stored as SEQAIJPERM matrices (a matrix class that inherits
  6:    from SEQAIJ but includes some optimizations to allow more effective
  7:    vectorization).  The same guidelines that apply to MPIAIJ matrices for
  8:    preallocating the matrix storage apply here as well.

 10:       Collective on MPI_Comm

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

 38:    Output Parameter:
 39: .  A - the matrix

 41:    Notes:
 42:    If the *_nnz parameter is given then the *_nz parameter is ignored

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

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

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

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

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

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

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

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

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

 84:    Level: intermediate

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

 88: .seealso: MatCreate(), MatCreateSeqAIJPERM(), MatSetValues()
 89: @*/
 90: 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)
 91: {
 93:   PetscMPIInt    size;

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

109: PetscErrorCode  MatMPIAIJSetPreallocation_MPIAIJPERM(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[])
110: {
111:   Mat_MPIAIJ     *b = (Mat_MPIAIJ*)B->data;

115:   MatMPIAIJSetPreallocation_MPIAIJ(B,d_nz,d_nnz,o_nz,o_nnz);
116:   MatConvert_SeqAIJ_SeqAIJPERM(b->A, MATSEQAIJPERM, MAT_INPLACE_MATRIX, &b->A);
117:   MatConvert_SeqAIJ_SeqAIJPERM(b->B, MATSEQAIJPERM, MAT_INPLACE_MATRIX, &b->B);
118:   return(0);
119: }

121: PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJPERM(Mat A,MatType type,MatReuse reuse,Mat *newmat)
122: {
124:   Mat            B = *newmat;

127:   if (reuse == MAT_INITIAL_MATRIX) {
128:     MatDuplicate(A,MAT_COPY_VALUES,&B);
129:   }

131:   PetscObjectChangeTypeName((PetscObject) B, MATMPIAIJPERM);
132:   PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocation_C",MatMPIAIJSetPreallocation_MPIAIJPERM);
133:   *newmat = B;
134:   return(0);
135: }

137: PETSC_EXTERN PetscErrorCode MatCreate_MPIAIJPERM(Mat A)
138: {

142:   MatSetType(A,MATMPIAIJ);
143:   MatConvert_MPIAIJ_MPIAIJPERM(A,MATMPIAIJPERM,MAT_INPLACE_MATRIX,&A);
144:   return(0);
145: }

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

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

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

159:   Level: beginner

161: .seealso: MatCreateMPIAIJPERM(), MATSEQAIJPERM, MATMPIAIJPERM
162: M*/