Actual source code: mcrl.c
2: /*
3: Defines a matrix-vector product for the MATMPIAIJCRL matrix class.
4: This class is derived from the MATMPIAIJ class and retains the
5: compressed row storage (aka Yale sparse matrix format) but augments
6: it with a column oriented storage that is more efficient for
7: matrix vector products on Vector machines.
9: CRL stands for constant row length (that is the same number of columns
10: is kept (padded with zeros) for each row of the sparse matrix.
12: See src/mat/impls/aij/seq/crl/crl.c for the sequential version
13: */
15: #include <../src/mat/impls/aij/mpi/mpiaij.h>
16: #include <../src/mat/impls/aij/seq/crl/crl.h>
18: PetscErrorCode MatDestroy_MPIAIJCRL(Mat A)
19: {
20: Mat_AIJCRL *aijcrl = (Mat_AIJCRL *)A->spptr;
22: PetscFunctionBegin;
23: if (aijcrl) {
24: PetscCall(PetscFree2(aijcrl->acols, aijcrl->icols));
25: PetscCall(VecDestroy(&aijcrl->fwork));
26: PetscCall(VecDestroy(&aijcrl->xwork));
27: PetscCall(PetscFree(aijcrl->array));
28: }
29: PetscCall(PetscFree(A->spptr));
31: PetscCall(PetscObjectChangeTypeName((PetscObject)A, MATMPIAIJ));
32: PetscCall(MatDestroy_MPIAIJ(A));
33: PetscFunctionReturn(PETSC_SUCCESS);
34: }
36: PetscErrorCode MatMPIAIJCRL_create_aijcrl(Mat A)
37: {
38: Mat_MPIAIJ *a = (Mat_MPIAIJ *)(A)->data;
39: Mat_SeqAIJ *Aij = (Mat_SeqAIJ *)(a->A->data), *Bij = (Mat_SeqAIJ *)(a->B->data);
40: Mat_AIJCRL *aijcrl = (Mat_AIJCRL *)A->spptr;
41: PetscInt m = A->rmap->n; /* Number of rows in the matrix. */
42: PetscInt nd = a->A->cmap->n; /* number of columns in diagonal portion */
43: PetscInt *aj = Aij->j, *bj = Bij->j; /* From the CSR representation; points to the beginning of each row. */
44: PetscInt i, j, rmax = 0, *icols, *ailen = Aij->ilen, *bilen = Bij->ilen;
45: PetscScalar *aa = Aij->a, *ba = Bij->a, *acols, *array;
47: PetscFunctionBegin;
48: /* determine the row with the most columns */
49: for (i = 0; i < m; i++) rmax = PetscMax(rmax, ailen[i] + bilen[i]);
50: aijcrl->nz = Aij->nz + Bij->nz;
51: aijcrl->m = A->rmap->n;
52: aijcrl->rmax = rmax;
54: PetscCall(PetscFree2(aijcrl->acols, aijcrl->icols));
55: PetscCall(PetscMalloc2(rmax * m, &aijcrl->acols, rmax * m, &aijcrl->icols));
56: acols = aijcrl->acols;
57: icols = aijcrl->icols;
58: for (i = 0; i < m; i++) {
59: for (j = 0; j < ailen[i]; j++) {
60: acols[j * m + i] = *aa++;
61: icols[j * m + i] = *aj++;
62: }
63: for (; j < ailen[i] + bilen[i]; j++) {
64: acols[j * m + i] = *ba++;
65: icols[j * m + i] = nd + *bj++;
66: }
67: for (; j < rmax; j++) { /* empty column entries */
68: acols[j * m + i] = 0.0;
69: icols[j * m + i] = (j) ? icols[(j - 1) * m + i] : 0; /* handle case where row is EMPTY */
70: }
71: }
72: PetscCall(PetscInfo(A, "Percentage of 0's introduced for vectorized multiply %g\n", 1.0 - ((double)(aijcrl->nz)) / ((double)(rmax * m))));
74: PetscCall(PetscFree(aijcrl->array));
75: PetscCall(PetscMalloc1(a->B->cmap->n + nd, &array));
76: /* xwork array is actually B->n+nd long, but we define xwork this length so can copy into it */
77: PetscCall(VecDestroy(&aijcrl->xwork));
78: PetscCall(VecCreateMPIWithArray(PetscObjectComm((PetscObject)A), 1, nd, PETSC_DECIDE, array, &aijcrl->xwork));
79: PetscCall(VecDestroy(&aijcrl->fwork));
80: PetscCall(VecCreateSeqWithArray(PETSC_COMM_SELF, 1, a->B->cmap->n, array + nd, &aijcrl->fwork));
82: aijcrl->array = array;
83: aijcrl->xscat = a->Mvctx;
84: PetscFunctionReturn(PETSC_SUCCESS);
85: }
87: PetscErrorCode MatAssemblyEnd_MPIAIJCRL(Mat A, MatAssemblyType mode)
88: {
89: Mat_MPIAIJ *a = (Mat_MPIAIJ *)A->data;
90: Mat_SeqAIJ *Aij = (Mat_SeqAIJ *)(a->A->data), *Bij = (Mat_SeqAIJ *)(a->A->data);
92: PetscFunctionBegin;
93: Aij->inode.use = PETSC_FALSE;
94: Bij->inode.use = PETSC_FALSE;
96: PetscCall(MatAssemblyEnd_MPIAIJ(A, mode));
97: if (mode == MAT_FLUSH_ASSEMBLY) PetscFunctionReturn(PETSC_SUCCESS);
99: /* Now calculate the permutation and grouping information. */
100: PetscCall(MatMPIAIJCRL_create_aijcrl(A));
101: PetscFunctionReturn(PETSC_SUCCESS);
102: }
104: extern PetscErrorCode MatMult_AIJCRL(Mat, Vec, Vec);
105: extern PetscErrorCode MatDuplicate_AIJCRL(Mat, MatDuplicateOption, Mat *);
107: /* MatConvert_MPIAIJ_MPIAIJCRL converts a MPIAIJ matrix into a
108: * MPIAIJCRL matrix. This routine is called by the MatCreate_MPIAIJCRL()
109: * routine, but can also be used to convert an assembled MPIAIJ matrix
110: * into a MPIAIJCRL one. */
112: PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJCRL(Mat A, MatType type, MatReuse reuse, Mat *newmat)
113: {
114: Mat B = *newmat;
115: Mat_AIJCRL *aijcrl;
117: PetscFunctionBegin;
118: if (reuse == MAT_INITIAL_MATRIX) PetscCall(MatDuplicate(A, MAT_COPY_VALUES, &B));
120: PetscCall(PetscNew(&aijcrl));
121: B->spptr = (void *)aijcrl;
123: /* Set function pointers for methods that we inherit from AIJ but override. */
124: B->ops->duplicate = MatDuplicate_AIJCRL;
125: B->ops->assemblyend = MatAssemblyEnd_MPIAIJCRL;
126: B->ops->destroy = MatDestroy_MPIAIJCRL;
127: B->ops->mult = MatMult_AIJCRL;
129: /* If A has already been assembled, compute the permutation. */
130: if (A->assembled) PetscCall(MatMPIAIJCRL_create_aijcrl(B));
131: PetscCall(PetscObjectChangeTypeName((PetscObject)B, MATMPIAIJCRL));
132: *newmat = B;
133: PetscFunctionReturn(PETSC_SUCCESS);
134: }
136: /*@C
137: MatCreateMPIAIJCRL - Creates a sparse matrix of type `MATMPIAIJCRL`.
138: This type inherits from `MATAIJ`, but stores some additional
139: information that is used to allow better vectorization of
140: the matrix-vector product. At the cost of increased storage, the AIJ formatted
141: matrix can be copied to a format in which pieces of the matrix are
142: stored in ELLPACK format, allowing the vectorized matrix multiply
143: routine to use stride-1 memory accesses.
145: Collective
147: Input Parameters:
148: + comm - MPI communicator, set to `PETSC_COMM_SELF`
149: . m - number of rows
150: . n - number of columns
151: . nz - number of nonzeros per row (same for all rows), for the "diagonal" submatrix
152: . nnz - array containing the number of nonzeros in the various rows (possibly different for each row) or `NULL`, for the "diagonal" submatrix
153: . onz - number of nonzeros per row (same for all rows), for the "off-diagonal" submatrix
154: - onnz - array containing the number of nonzeros in the various rows (possibly different for each row) or `NULL`, for the "off-diagonal" submatrix
156: Output Parameter:
157: . A - the matrix
159: Level: intermediate
161: Note:
162: If `nnz` is given then `nz` is ignored
164: .seealso: [](ch_matrices), `Mat`, [Sparse Matrix Creation](sec_matsparse), `MATAIJ`, `MATAIJSELL`, `MATAIJPERM`, `MATAIJMKL`, `MatCreate()`, `MatCreateMPIAIJPERM()`, `MatSetValues()`
165: @*/
166: PetscErrorCode MatCreateMPIAIJCRL(MPI_Comm comm, PetscInt m, PetscInt n, PetscInt nz, const PetscInt nnz[], PetscInt onz, const PetscInt onnz[], Mat *A)
167: {
168: PetscFunctionBegin;
169: PetscCall(MatCreate(comm, A));
170: PetscCall(MatSetSizes(*A, m, n, m, n));
171: PetscCall(MatSetType(*A, MATMPIAIJCRL));
172: PetscCall(MatMPIAIJSetPreallocation_MPIAIJ(*A, nz, (PetscInt *)nnz, onz, (PetscInt *)onnz));
173: PetscFunctionReturn(PETSC_SUCCESS);
174: }
176: PETSC_EXTERN PetscErrorCode MatCreate_MPIAIJCRL(Mat A)
177: {
178: PetscFunctionBegin;
179: PetscCall(MatSetType(A, MATMPIAIJ));
180: PetscCall(MatConvert_MPIAIJ_MPIAIJCRL(A, MATMPIAIJCRL, MAT_INPLACE_MATRIX, &A));
181: PetscFunctionReturn(PETSC_SUCCESS);
182: }