Actual source code: mpiaijperm.c
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 `MATSEQAIJPERM` 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 `MATMPIAIJ` matrices for
8: preallocating the matrix storage apply here as well.
10: Collective
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 `MATSEQAIJPERM` is returned. If a matrix of type `MATMPIAIJPERM` 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)
81: Level: intermediate
83: .seealso: [Sparse Matrix Creation](sec_matsparse), `MATMPIAIJPERM`, `MatCreate()`, `MatCreateSeqAIJPERM()`, `MatSetValues()`
84: @*/
85: 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)
86: {
87: PetscMPIInt size;
89: MatCreate(comm, A);
90: MatSetSizes(*A, m, n, M, N);
91: MPI_Comm_size(comm, &size);
92: if (size > 1) {
93: MatSetType(*A, MATMPIAIJPERM);
94: MatMPIAIJSetPreallocation(*A, d_nz, d_nnz, o_nz, o_nnz);
95: } else {
96: MatSetType(*A, MATSEQAIJPERM);
97: MatSeqAIJSetPreallocation(*A, d_nz, d_nnz);
98: }
99: return 0;
100: }
102: PetscErrorCode MatMPIAIJSetPreallocation_MPIAIJPERM(Mat B, PetscInt d_nz, const PetscInt d_nnz[], PetscInt o_nz, const PetscInt o_nnz[])
103: {
104: Mat_MPIAIJ *b = (Mat_MPIAIJ *)B->data;
106: MatMPIAIJSetPreallocation_MPIAIJ(B, d_nz, d_nnz, o_nz, o_nnz);
107: MatConvert_SeqAIJ_SeqAIJPERM(b->A, MATSEQAIJPERM, MAT_INPLACE_MATRIX, &b->A);
108: MatConvert_SeqAIJ_SeqAIJPERM(b->B, MATSEQAIJPERM, MAT_INPLACE_MATRIX, &b->B);
109: return 0;
110: }
112: PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJPERM(Mat A, MatType type, MatReuse reuse, Mat *newmat)
113: {
114: Mat B = *newmat;
116: if (reuse == MAT_INITIAL_MATRIX) MatDuplicate(A, MAT_COPY_VALUES, &B);
118: PetscObjectChangeTypeName((PetscObject)B, MATMPIAIJPERM);
119: PetscObjectComposeFunction((PetscObject)B, "MatMPIAIJSetPreallocation_C", MatMPIAIJSetPreallocation_MPIAIJPERM);
120: *newmat = B;
121: return 0;
122: }
124: PETSC_EXTERN PetscErrorCode MatCreate_MPIAIJPERM(Mat A)
125: {
126: MatSetType(A, MATMPIAIJ);
127: MatConvert_MPIAIJ_MPIAIJPERM(A, MATMPIAIJPERM, MAT_INPLACE_MATRIX, &A);
128: return 0;
129: }
131: /*MC
132: MATAIJPERM - MATAIJPERM = "AIJPERM" - A matrix type to be used for sparse matrices.
134: This matrix type is identical to `MATSEQAIJPERM` when constructed with a single process communicator,
135: and `MATMPIAIJPERM` otherwise. As a result, for single process communicators,
136: `MatSeqAIJSetPreallocation()` is supported, and similarly `MatMPIAIJSetPreallocation()` is supported
137: for communicators controlling multiple processes. It is recommended that you call both of
138: the above preallocation routines for simplicity.
140: Options Database Keys:
141: . -mat_type aijperm - sets the matrix type to `MATAIJPERM` during a call to `MatSetFromOptions()`
143: Level: beginner
145: .seealso: `MatCreateMPIAIJPERM()`, `MATSEQAIJPERM`, `MATMPIAIJPERM`, `MATSEQAIJ`, `MATMPIAIJ`, `MATSEQAIJMKL`, `MATMPIAIJMKL`, `MATSEQAIJSELL`, `MATMPIAIJSELL`
146: M*/