Actual source code: mcrl.c
1: #define PETSCMAT_DLL
3: /*
4: Defines a matrix-vector product for the MATMPIAIJCRL matrix class.
5: This class is derived from the MATMPIAIJ class and retains the
6: compressed row storage (aka Yale sparse matrix format) but augments
7: it with a column oriented storage that is more efficient for
8: matrix vector products on Vector machines.
10: CRL stands for constant row length (that is the same number of columns
11: is kept (padded with zeros) for each row of the sparse matrix.
13: See src/mat/impls/aij/seq/crl/crl.c for the sequential version
14: */
16: #include ../src/mat/impls/aij/mpi/mpiaij.h
17: #include ../src/mat/impls/aij/seq/crl/crl.h
21: PetscErrorCode MatDestroy_MPICRL(Mat A)
22: {
24: Mat_CRL *crl = (Mat_CRL *) A->spptr;
26: /* We are going to convert A back into a MPIAIJ matrix, since we are
27: * eventually going to use MatDestroy_MPIAIJ() to destroy everything
28: * that is not specific to CRL.
29: * In preparation for this, reset the operations pointers in A to
30: * their MPIAIJ versions. */
31: A->ops->assemblyend = crl->AssemblyEnd;
32: A->ops->destroy = crl->MatDestroy;
33: A->ops->duplicate = crl->MatDuplicate;
35: /* Free everything in the Mat_CRL data structure. */
36: PetscFree2(crl->acols,crl->icols);
37: if (crl->fwork) {
38: VecDestroy(crl->fwork);
39: }
40: if (crl->xwork) {
41: VecDestroy(crl->xwork);
42: }
43: PetscFree(crl->array);
44: PetscFree(crl);
45: A->spptr = 0;
47: /* Change the type of A back to MPIAIJ and use MatDestroy_MPIAIJ()
48: * to destroy everything that remains. */
49: PetscObjectChangeTypeName( (PetscObject)A, MATMPIAIJ);
50: /* Note that I don't call MatSetType(). I believe this is because that
51: * is only to be called when *building* a matrix. */
52: (*A->ops->destroy)(A);
53: return(0);
54: }
58: PetscErrorCode MPICRL_create_crl(Mat A)
59: {
60: Mat_MPIAIJ *a = (Mat_MPIAIJ *)(A)->data;
61: Mat_SeqAIJ *Aij = (Mat_SeqAIJ*)(a->A->data), *Bij = (Mat_SeqAIJ*)(a->B->data);
62: Mat_CRL *crl = (Mat_CRL*) A->spptr;
63: PetscInt m = A->rmap->n; /* Number of rows in the matrix. */
64: PetscInt nd = a->A->cmap->n; /* number of columns in diagonal portion */
65: PetscInt *aj = Aij->j,*bj = Bij->j; /* From the CSR representation; points to the beginning of each row. */
66: PetscInt i, j,rmax = 0,*icols, *ailen = Aij->ilen, *bilen = Bij->ilen;
67: PetscScalar *aa = Aij->a,*ba = Bij->a,*acols,*array;
71: /* determine the row with the most columns */
72: for (i=0; i<m; i++) {
73: rmax = PetscMax(rmax,ailen[i]+bilen[i]);
74: }
75: crl->nz = Aij->nz+Bij->nz;
76: crl->m = A->rmap->n;
77: crl->rmax = rmax;
78: PetscMalloc2(rmax*m,PetscScalar,&crl->acols,rmax*m,PetscInt,&crl->icols);
79: acols = crl->acols;
80: icols = crl->icols;
81: for (i=0; i<m; i++) {
82: for (j=0; j<ailen[i]; j++) {
83: acols[j*m+i] = *aa++;
84: icols[j*m+i] = *aj++;
85: }
86: for (;j<ailen[i]+bilen[i]; j++) {
87: acols[j*m+i] = *ba++;
88: icols[j*m+i] = nd + *bj++;
89: }
90: for (;j<rmax; j++) { /* empty column entries */
91: acols[j*m+i] = 0.0;
92: icols[j*m+i] = (j) ? icols[(j-1)*m+i] : 0; /* handle case where row is EMPTY */
93: }
94: }
95: PetscInfo1(A,"Percentage of 0's introduced for vectorized multiply %g\n",1.0-((double)(crl->nz))/((double)(rmax*m)));
97: PetscMalloc((a->B->cmap->n+nd)*sizeof(PetscScalar),&array);
98: /* xwork array is actually B->n+nd long, but we define xwork this length so can copy into it */
99: VecCreateMPIWithArray(((PetscObject)A)->comm,nd,PETSC_DECIDE,array,&crl->xwork);
100: VecCreateSeqWithArray(PETSC_COMM_SELF,a->B->cmap->n,array+nd,&crl->fwork);
101: crl->array = array;
102: crl->xscat = a->Mvctx;
103: return(0);
104: }
108: PetscErrorCode MatAssemblyEnd_MPICRL(Mat A, MatAssemblyType mode)
109: {
111: Mat_CRL *crl = (Mat_CRL*) A->spptr;
112: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
113: Mat_SeqAIJ *Aij = (Mat_SeqAIJ*)(a->A->data), *Bij = (Mat_SeqAIJ*)(a->A->data);
116: if (mode == MAT_FLUSH_ASSEMBLY) return(0);
117:
118: /* Since a MATMPICRL matrix is really just a MATMPIAIJ with some
119: * extra information, call the AssemblyEnd routine for a MATMPIAIJ.
120: * I'm not sure if this is the best way to do this, but it avoids
121: * a lot of code duplication.
122: * I also note that currently MATMPICRL doesn't know anything about
123: * the Mat_CompressedRow data structure that MPIAIJ now uses when there
124: * are many zero rows. If the MPIAIJ assembly end routine decides to use
125: * this, this may break things. (Don't know... haven't looked at it.) */
126: Aij->inode.use = PETSC_FALSE;
127: Bij->inode.use = PETSC_FALSE;
128: (*crl->AssemblyEnd)(A, mode);
130: /* Now calculate the permutation and grouping information. */
131: MPICRL_create_crl(A);
132: return(0);
133: }
138: /* MatConvert_MPIAIJ_MPICRL converts a MPIAIJ matrix into a
139: * MPICRL matrix. This routine is called by the MatCreate_MPICRL()
140: * routine, but can also be used to convert an assembled MPIAIJ matrix
141: * into a MPICRL one. */
145: PetscErrorCode MatConvert_MPIAIJ_MPICRL(Mat A,const MatType type,MatReuse reuse,Mat *newmat)
146: {
148: Mat B = *newmat;
149: Mat_CRL *crl;
152: if (reuse == MAT_INITIAL_MATRIX) {
153: MatDuplicate(A,MAT_COPY_VALUES,&B);
154: }
156: PetscNewLog(B,Mat_CRL,&crl);
157: B->spptr = (void *) crl;
159: crl->AssemblyEnd = A->ops->assemblyend;
160: crl->MatDestroy = A->ops->destroy;
161: crl->MatDuplicate = A->ops->duplicate;
163: /* Set function pointers for methods that we inherit from AIJ but override. */
164: B->ops->duplicate = MatDuplicate_CRL;
165: B->ops->assemblyend = MatAssemblyEnd_MPICRL;
166: B->ops->destroy = MatDestroy_MPICRL;
167: B->ops->mult = MatMult_CRL;
169: /* If A has already been assembled, compute the permutation. */
170: if (A->assembled == PETSC_TRUE) {
171: MPICRL_create_crl(B);
172: }
173: PetscObjectChangeTypeName((PetscObject)B,MATMPICRL);
174: *newmat = B;
175: return(0);
176: }
182: /*@C
183: MatCreateMPICRL - Creates a sparse matrix of type MPICRL.
184: This type inherits from AIJ, but stores some additional
185: information that is used to allow better vectorization of
186: the matrix-vector product. At the cost of increased storage, the AIJ formatted
187: matrix can be copied to a format in which pieces of the matrix are
188: stored in ELLPACK format, allowing the vectorized matrix multiply
189: routine to use stride-1 memory accesses. As with the AIJ type, it is
190: important to preallocate matrix storage in order to get good assembly
191: performance.
192:
193: Collective on MPI_Comm
195: Input Parameters:
196: + comm - MPI communicator, set to PETSC_COMM_SELF
197: . m - number of rows
198: . n - number of columns
199: . nz - number of nonzeros per row (same for all rows)
200: - nnz - array containing the number of nonzeros in the various rows
201: (possibly different for each row) or PETSC_NULL
203: Output Parameter:
204: . A - the matrix
206: Notes:
207: If nnz is given then nz is ignored
209: Level: intermediate
211: .keywords: matrix, cray, sparse, parallel
213: .seealso: MatCreate(), MatCreateMPICSRPERM(), MatSetValues()
214: @*/
215: PetscErrorCode MatCreateMPICRL(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt nz,const PetscInt nnz[],PetscInt onz,const PetscInt onnz[],Mat *A)
216: {
220: MatCreate(comm,A);
221: MatSetSizes(*A,m,n,m,n);
222: MatSetType(*A,MATMPICRL);
223: MatMPIAIJSetPreallocation_MPIAIJ(*A,nz,(PetscInt*)nnz,onz,(PetscInt*)onnz);
224: return(0);
225: }
231: PetscErrorCode MatCreate_MPICRL(Mat A)
232: {
236: MatSetType(A,MATMPIAIJ);
237: MatConvert_MPIAIJ_MPICRL(A,MATMPICRL,MAT_REUSE_MATRIX,&A);
238: return(0);
239: }