Actual source code: mpiaijsell.c
1: #include <../src/mat/impls/aij/mpi/mpiaij.h>
2: /*@C
3: MatCreateMPIAIJSELL - Creates a sparse parallel matrix whose local
4: portions are stored as `MATSEQAIJSELL` matrices (a matrix class that inherits
5: from SEQAIJ but performs some operations in SELL format). The same
6: guidelines that apply to `MATMPIAIJ` matrices for preallocating the matrix
7: storage apply here as well.
9: Collective
11: Input Parameters:
12: + comm - MPI communicator
13: . m - number of local rows (or `PETSC_DECIDE` to have calculated if M is given)
14: This value should be the same as the local size used in creating the
15: y vector for the matrix-vector product y = Ax.
16: . n - This value should be the same as the local size used in creating the
17: x vector for the matrix-vector product y = Ax. (or `PETSC_DECIDE` to have
18: calculated if N is given) For square matrices n is almost always m.
19: . M - number of global rows (or `PETSC_DETERMINE` to have calculated if m is given)
20: . N - number of global columns (or `PETSC_DETERMINE` to have calculated if n is given)
21: . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix
22: (same value is used for all local rows)
23: . d_nnz - array containing the number of nonzeros in the various rows of the
24: DIAGONAL portion of the local submatrix (possibly different for each row)
25: or NULL, if d_nz is used to specify the nonzero structure.
26: The size of this array is equal to the number of local rows, i.e 'm'.
27: For matrices you plan to factor you must leave room for the diagonal entry and
28: put in the entry even if it is zero.
29: . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local
30: submatrix (same value is used for all local rows).
31: - o_nnz - array containing the number of nonzeros in the various rows of the
32: OFF-DIAGONAL portion of the local submatrix (possibly different for
33: each row) or NULL, if o_nz is used to specify the nonzero
34: structure. The size of this array is equal to the number
35: of local rows, i.e 'm'.
37: Output Parameter:
38: . A - the matrix
40: Notes:
41: If the *_nnz parameter is given then the *_nz parameter is ignored
43: m,n,M,N parameters specify the size of the matrix, and its partitioning across
44: processors, while d_nz,d_nnz,o_nz,o_nnz parameters specify the approximate
45: storage requirements for this matrix.
47: If `PETSC_DECIDE` or `PETSC_DETERMINE` is used for a particular argument on one
48: processor than it must be used on all processors that share the object for
49: that argument.
51: The user MUST specify either the local or global matrix dimensions
52: (possibly both).
54: The parallel matrix is partitioned such that the first m0 rows belong to
55: process 0, the next m1 rows belong to process 1, the next m2 rows belong
56: to process 2 etc.. where m0,m1,m2... are the input parameter 'm'.
58: The DIAGONAL portion of the local submatrix of a processor can be defined
59: as the submatrix which is obtained by extraction the part corresponding
60: to the rows r1-r2 and columns r1-r2 of the global matrix, where r1 is the
61: first row that belongs to the processor, and r2 is the last row belonging
62: to the this processor. This is a square mxm matrix. The remaining portion
63: of the local submatrix (mxN) constitute the OFF-DIAGONAL portion.
65: If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored.
67: When calling this routine with a single process communicator, a matrix of
68: type `MATSEQAIJSELL` is returned. If a matrix of type `MATMPIAIJSELL` is desired
69: for this type of communicator, use the construction mechanism:
70: `MatCreate`(...,&A); `MatSetType`(A,MPIAIJSELL); `MatMPIAIJSetPreallocation`(A,...);
72: Options Database Keys:
73: . -mat_aijsell_eager_shadow - Construct shadow matrix upon matrix assembly; default is to take a "lazy" approach, performing this step the first time the matrix is applied
75: Level: intermediate
77: .seealso: [Sparse Matrix Creation](sec_matsparse), `MATSEQAIJSELL`, `MATMPIAIJSELL`, `MATAIJSELL`, `MatCreate()`, `MatCreateSeqAIJSELL()`, `MatSetValues()`
78: @*/
79: PetscErrorCode MatCreateMPIAIJSELL(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)
80: {
81: PetscMPIInt size;
83: MatCreate(comm, A);
84: MatSetSizes(*A, m, n, M, N);
85: MPI_Comm_size(comm, &size);
86: if (size > 1) {
87: MatSetType(*A, MATMPIAIJSELL);
88: MatMPIAIJSetPreallocation(*A, d_nz, d_nnz, o_nz, o_nnz);
89: } else {
90: MatSetType(*A, MATSEQAIJSELL);
91: MatSeqAIJSetPreallocation(*A, d_nz, d_nnz);
92: }
93: return 0;
94: }
96: PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqAIJSELL(Mat, MatType, MatReuse, Mat *);
98: PetscErrorCode MatMPIAIJSetPreallocation_MPIAIJSELL(Mat B, PetscInt d_nz, const PetscInt d_nnz[], PetscInt o_nz, const PetscInt o_nnz[])
99: {
100: Mat_MPIAIJ *b = (Mat_MPIAIJ *)B->data;
102: MatMPIAIJSetPreallocation_MPIAIJ(B, d_nz, d_nnz, o_nz, o_nnz);
103: MatConvert_SeqAIJ_SeqAIJSELL(b->A, MATSEQAIJSELL, MAT_INPLACE_MATRIX, &b->A);
104: MatConvert_SeqAIJ_SeqAIJSELL(b->B, MATSEQAIJSELL, MAT_INPLACE_MATRIX, &b->B);
105: return 0;
106: }
108: PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJSELL(Mat A, MatType type, MatReuse reuse, Mat *newmat)
109: {
110: Mat B = *newmat;
112: if (reuse == MAT_INITIAL_MATRIX) MatDuplicate(A, MAT_COPY_VALUES, &B);
114: PetscObjectChangeTypeName((PetscObject)B, MATMPIAIJSELL);
115: PetscObjectComposeFunction((PetscObject)B, "MatMPIAIJSetPreallocation_C", MatMPIAIJSetPreallocation_MPIAIJSELL);
116: *newmat = B;
117: return 0;
118: }
120: PETSC_EXTERN PetscErrorCode MatCreate_MPIAIJSELL(Mat A)
121: {
122: MatSetType(A, MATMPIAIJ);
123: MatConvert_MPIAIJ_MPIAIJSELL(A, MATMPIAIJSELL, MAT_INPLACE_MATRIX, &A);
124: return 0;
125: }
127: /*MC
128: MATAIJSELL - MATAIJSELL = "AIJSELL" - A matrix type to be used for sparse matrices.
130: This matrix type is identical to `MATSEQAIJSELL` when constructed with a single process communicator,
131: and `MATMPIAIJSELL` otherwise. As a result, for single process communicators,
132: MatSeqAIJSetPreallocation() is supported, and similarly `MatMPIAIJSetPreallocation()` is supported
133: for communicators controlling multiple processes. It is recommended that you call both of
134: the above preallocation routines for simplicity.
136: Options Database Keys:
137: . -mat_type aijsell - sets the matrix type to `MATAIJSELL` during a call to `MatSetFromOptions()`
139: Level: beginner
141: .seealso: `MatCreateMPIAIJSELL()`, `MATSEQAIJSELL`, `MATMPIAIJSELL`, `MATSEQAIJ`, `MATMPIAIJ`, `MATSEQAIJPERM`, `MATMPIAIJPERM`, `MATSEQAIJMKL`, `MATMPIAIJMKL`
142: M*/