Actual source code: mcrl.c
petsc-3.13.6 2020-09-29
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: {
21: Mat_AIJCRL *aijcrl = (Mat_AIJCRL*) A->spptr;
23: /* Free everything in the Mat_AIJCRL data structure. */
24: if (aijcrl) {
25: PetscFree2(aijcrl->acols,aijcrl->icols);
26: VecDestroy(&aijcrl->fwork);
27: VecDestroy(&aijcrl->xwork);
28: PetscFree(aijcrl->array);
29: }
30: PetscFree(A->spptr);
32: PetscObjectChangeTypeName((PetscObject)A, MATMPIAIJ);
33: MatDestroy_MPIAIJ(A);
34: return(0);
35: }
37: PetscErrorCode MatMPIAIJCRL_create_aijcrl(Mat A)
38: {
39: Mat_MPIAIJ *a = (Mat_MPIAIJ*)(A)->data;
40: Mat_SeqAIJ *Aij = (Mat_SeqAIJ*)(a->A->data), *Bij = (Mat_SeqAIJ*)(a->B->data);
41: Mat_AIJCRL *aijcrl = (Mat_AIJCRL*) A->spptr;
42: PetscInt m = A->rmap->n; /* Number of rows in the matrix. */
43: PetscInt nd = a->A->cmap->n; /* number of columns in diagonal portion */
44: PetscInt *aj = Aij->j,*bj = Bij->j; /* From the CSR representation; points to the beginning of each row. */
45: PetscInt i, j,rmax = 0,*icols, *ailen = Aij->ilen, *bilen = Bij->ilen;
46: PetscScalar *aa = Aij->a,*ba = Bij->a,*acols,*array;
50: /* determine the row with the most columns */
51: for (i=0; i<m; i++) {
52: rmax = PetscMax(rmax,ailen[i]+bilen[i]);
53: }
54: aijcrl->nz = Aij->nz+Bij->nz;
55: aijcrl->m = A->rmap->n;
56: aijcrl->rmax = rmax;
58: PetscFree2(aijcrl->acols,aijcrl->icols);
59: PetscMalloc2(rmax*m,&aijcrl->acols,rmax*m,&aijcrl->icols);
60: acols = aijcrl->acols;
61: icols = aijcrl->icols;
62: for (i=0; i<m; i++) {
63: for (j=0; j<ailen[i]; j++) {
64: acols[j*m+i] = *aa++;
65: icols[j*m+i] = *aj++;
66: }
67: for (; j<ailen[i]+bilen[i]; j++) {
68: acols[j*m+i] = *ba++;
69: icols[j*m+i] = nd + *bj++;
70: }
71: for (; j<rmax; j++) { /* empty column entries */
72: acols[j*m+i] = 0.0;
73: icols[j*m+i] = (j) ? icols[(j-1)*m+i] : 0; /* handle case where row is EMPTY */
74: }
75: }
76: PetscInfo1(A,"Percentage of 0's introduced for vectorized multiply %g\n",1.0-((double)(aijcrl->nz))/((double)(rmax*m)));
78: PetscFree(aijcrl->array);
79: PetscMalloc1(a->B->cmap->n+nd,&array);
80: /* xwork array is actually B->n+nd long, but we define xwork this length so can copy into it */
81: VecDestroy(&aijcrl->xwork);
82: VecCreateMPIWithArray(PetscObjectComm((PetscObject)A),1,nd,PETSC_DECIDE,array,&aijcrl->xwork);
83: VecDestroy(&aijcrl->fwork);
84: VecCreateSeqWithArray(PETSC_COMM_SELF,1,a->B->cmap->n,array+nd,&aijcrl->fwork);
86: aijcrl->array = array;
87: aijcrl->xscat = a->Mvctx;
88: return(0);
89: }
91: PetscErrorCode MatAssemblyEnd_MPIAIJCRL(Mat A, MatAssemblyType mode)
92: {
94: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
95: Mat_SeqAIJ *Aij = (Mat_SeqAIJ*)(a->A->data), *Bij = (Mat_SeqAIJ*)(a->A->data);
98: Aij->inode.use = PETSC_FALSE;
99: Bij->inode.use = PETSC_FALSE;
101: MatAssemblyEnd_MPIAIJ(A,mode);
102: if (mode == MAT_FLUSH_ASSEMBLY) return(0);
104: /* Now calculate the permutation and grouping information. */
105: MatMPIAIJCRL_create_aijcrl(A);
106: return(0);
107: }
109: extern PetscErrorCode MatMult_AIJCRL(Mat,Vec,Vec);
110: extern PetscErrorCode MatDuplicate_AIJCRL(Mat,MatDuplicateOption,Mat*);
112: /* MatConvert_MPIAIJ_MPIAIJCRL converts a MPIAIJ matrix into a
113: * MPIAIJCRL matrix. This routine is called by the MatCreate_MPIAIJCRL()
114: * routine, but can also be used to convert an assembled MPIAIJ matrix
115: * into a MPIAIJCRL one. */
117: PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJCRL(Mat A,MatType type,MatReuse reuse,Mat *newmat)
118: {
120: Mat B = *newmat;
121: Mat_AIJCRL *aijcrl;
124: if (reuse == MAT_INITIAL_MATRIX) {
125: MatDuplicate(A,MAT_COPY_VALUES,&B);
126: }
128: PetscNewLog(B,&aijcrl);
129: B->spptr = (void*) aijcrl;
131: /* Set function pointers for methods that we inherit from AIJ but override. */
132: B->ops->duplicate = MatDuplicate_AIJCRL;
133: B->ops->assemblyend = MatAssemblyEnd_MPIAIJCRL;
134: B->ops->destroy = MatDestroy_MPIAIJCRL;
135: B->ops->mult = MatMult_AIJCRL;
137: /* If A has already been assembled, compute the permutation. */
138: if (A->assembled) {
139: MatMPIAIJCRL_create_aijcrl(B);
140: }
141: PetscObjectChangeTypeName((PetscObject)B,MATMPIAIJCRL);
142: *newmat = B;
143: return(0);
144: }
146: /*@C
147: MatCreateMPIAIJCRL - Creates a sparse matrix of type MPIAIJCRL.
148: This type inherits from AIJ, but stores some additional
149: information that is used to allow better vectorization of
150: the matrix-vector product. At the cost of increased storage, the AIJ formatted
151: matrix can be copied to a format in which pieces of the matrix are
152: stored in ELLPACK format, allowing the vectorized matrix multiply
153: routine to use stride-1 memory accesses. As with the AIJ type, it is
154: important to preallocate matrix storage in order to get good assembly
155: performance.
157: Collective
159: Input Parameters:
160: + comm - MPI communicator, set to PETSC_COMM_SELF
161: . m - number of rows
162: . n - number of columns
163: . nz - number of nonzeros per row (same for all rows)
164: - nnz - array containing the number of nonzeros in the various rows
165: (possibly different for each row) or NULL
167: Output Parameter:
168: . A - the matrix
170: Notes:
171: If nnz is given then nz is ignored
173: Level: intermediate
175: .seealso: MatCreate(), MatCreateMPIAIJPERM(), MatSetValues()
176: @*/
177: PetscErrorCode MatCreateMPIAIJCRL(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt nz,const PetscInt nnz[],PetscInt onz,const PetscInt onnz[],Mat *A)
178: {
182: MatCreate(comm,A);
183: MatSetSizes(*A,m,n,m,n);
184: MatSetType(*A,MATMPIAIJCRL);
185: MatMPIAIJSetPreallocation_MPIAIJ(*A,nz,(PetscInt*)nnz,onz,(PetscInt*)onnz);
186: return(0);
187: }
189: PETSC_EXTERN PetscErrorCode MatCreate_MPIAIJCRL(Mat A)
190: {
194: MatSetType(A,MATMPIAIJ);
195: MatConvert_MPIAIJ_MPIAIJCRL(A,MATMPIAIJCRL,MAT_INPLACE_MATRIX,&A);
196: return(0);
197: }