Actual source code: basfactor.c
petsc-3.6.1 2015-08-06
2: #include <../src/mat/impls/aij/seq/aij.h>
3: #include <../src/mat/impls/sbaij/seq/sbaij.h>
4: #include <../src/mat/impls/aij/seq/bas/spbas.h>
8: PetscErrorCode MatICCFactorSymbolic_SeqAIJ_Bas(Mat fact,Mat A,IS perm,const MatFactorInfo *info)
9: {
10: Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data;
11: Mat_SeqSBAIJ *b;
13: PetscBool perm_identity,missing;
14: PetscInt reallocs=0,i,*ai=a->i,*aj=a->j,am=A->rmap->n,*ui;
15: const PetscInt *rip,*riip;
16: PetscInt j;
17: PetscInt d;
18: PetscInt ncols,*cols,*uj;
19: PetscReal fill=info->fill,levels=info->levels;
20: IS iperm;
21: spbas_matrix Pattern_0, Pattern_P;
24: if (A->rmap->n != A->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Must be square matrix, rows %D columns %D",A->rmap->n,A->cmap->n);
25: MatMissingDiagonal(A,&missing,&d);
26: if (missing) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Matrix is missing diagonal entry %D",d);
27: ISIdentity(perm,&perm_identity);
28: ISInvertPermutation(perm,PETSC_DECIDE,&iperm);
30: /* ICC(0) without matrix ordering: simply copies fill pattern */
31: if (!levels && perm_identity) {
32: PetscMalloc1(am+1,&ui);
33: ui[0] = 0;
35: for (i=0; i<am; i++) {
36: ui[i+1] = ui[i] + ai[i+1] - a->diag[i];
37: }
38: PetscMalloc1(ui[am]+1,&uj);
39: cols = uj;
40: for (i=0; i<am; i++) {
41: aj = a->j + a->diag[i];
42: ncols = ui[i+1] - ui[i];
43: for (j=0; j<ncols; j++) *cols++ = *aj++;
44: }
45: } else { /* case: levels>0 || (levels=0 && !perm_identity) */
46: ISGetIndices(iperm,&riip);
47: ISGetIndices(perm,&rip);
49: /* Create spbas_matrix for pattern */
50: spbas_pattern_only(am, am, ai, aj, &Pattern_0);
52: /* Apply the permutation */
53: spbas_apply_reordering(&Pattern_0, rip, riip);
55: /* Raise the power */
56: spbas_power(Pattern_0, (int) levels+1, &Pattern_P);
57: spbas_delete(Pattern_0);
59: /* Keep only upper triangle of pattern */
60: spbas_keep_upper(&Pattern_P);
62: /* Convert to Sparse Row Storage */
63: spbas_matrix_to_crs(Pattern_P, NULL, &ui, &uj);
64: spbas_delete(Pattern_P);
65: } /* end of case: levels>0 || (levels=0 && !perm_identity) */
67: /* put together the new matrix in MATSEQSBAIJ format */
69: b = (Mat_SeqSBAIJ*)(fact)->data;
70: b->singlemalloc = PETSC_FALSE;
72: PetscMalloc1(ui[am]+1,&b->a);
74: b->j = uj;
75: b->i = ui;
76: b->diag = 0;
77: b->ilen = 0;
78: b->imax = 0;
79: b->row = perm;
80: b->col = perm;
82: PetscObjectReference((PetscObject)perm);
83: PetscObjectReference((PetscObject)perm);
85: b->icol = iperm;
86: b->pivotinblocks = PETSC_FALSE; /* need to get from MatFactorInfo */
87: PetscMalloc1(am+1,&b->solve_work);
88: PetscLogObjectMemory((PetscObject)(fact),(ui[am]-am)*(sizeof(PetscInt)+sizeof(MatScalar)));
89: b->maxnz = b->nz = ui[am];
90: b->free_a = PETSC_TRUE;
91: b->free_ij = PETSC_TRUE;
93: (fact)->info.factor_mallocs = reallocs;
94: (fact)->info.fill_ratio_given = fill;
95: if (ai[am] != 0) {
96: (fact)->info.fill_ratio_needed = ((PetscReal)ui[am])/((PetscReal)ai[am]);
97: } else {
98: (fact)->info.fill_ratio_needed = 0.0;
99: }
100: /* (fact)->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqAIJ_inplace; */
101: return(0);
102: }
107: PetscErrorCode MatCholeskyFactorNumeric_SeqAIJ_Bas(Mat B,Mat A,const MatFactorInfo *info)
108: {
109: Mat C = B;
110: Mat_SeqSBAIJ *b=(Mat_SeqSBAIJ*)C->data;
111: IS ip=b->row,iip = b->icol;
113: const PetscInt *rip,*riip;
114: PetscInt mbs=A->rmap->n,*bi=b->i,*bj=b->j;
116: MatScalar *ba = b->a;
117: PetscReal shiftnz = info->shiftamount;
118: PetscReal droptol = -1;
119: PetscBool perm_identity;
120: spbas_matrix Pattern, matrix_L,matrix_LT;
121: PetscReal mem_reduction;
124: /* Reduce memory requirements: erase values of B-matrix */
125: PetscFree(ba);
126: /* Compress (maximum) sparseness pattern of B-matrix */
127: spbas_compress_pattern(bi, bj, mbs, mbs, SPBAS_DIAGONAL_OFFSETS,&Pattern, &mem_reduction);
128: PetscFree(bi);
129: PetscFree(bj);
131: PetscInfo1(NULL," compression rate for spbas_compress_pattern %g \n",(double)mem_reduction);
133: /* Make Cholesky decompositions with larger Manteuffel shifts until no more negative diagonals are found. */
134: ISGetIndices(ip,&rip);
135: ISGetIndices(iip,&riip);
137: if (info->usedt) {
138: droptol = info->dt;
139: }
140: for (NEGATIVE_DIAGONAL; ierr == NEGATIVE_DIAGONAL;)
141: {
142: spbas_incomplete_cholesky(A, rip, riip, Pattern, droptol, shiftnz,&matrix_LT);
143: if (ierr == NEGATIVE_DIAGONAL) {
144: shiftnz *= 1.5;
145: if (shiftnz < 1e-5) shiftnz=1e-5;
146: PetscInfo1(NULL,"spbas_incomplete_cholesky found a negative diagonal. Trying again with Manteuffel shift=%g\n",(double)shiftnz);
147: }
148: }
149: spbas_delete(Pattern);
151: PetscInfo1(NULL," memory_usage for spbas_incomplete_cholesky %g bytes per row\n", (double)(PetscReal) (spbas_memory_requirement(matrix_LT)/ (PetscReal) mbs));
153: ISRestoreIndices(ip,&rip);
154: ISRestoreIndices(iip,&riip);
156: /* Convert spbas_matrix to compressed row storage */
157: spbas_transpose(matrix_LT, &matrix_L);
158: spbas_delete(matrix_LT);
159: spbas_matrix_to_crs(matrix_L, &ba, &bi, &bj);
160: b->i =bi; b->j=bj; b->a=ba;
161: spbas_delete(matrix_L);
163: /* Set the appropriate solution functions */
164: ISIdentity(ip,&perm_identity);
165: if (perm_identity) {
166: (B)->ops->solve = MatSolve_SeqSBAIJ_1_NaturalOrdering_inplace;
167: (B)->ops->solvetranspose = MatSolve_SeqSBAIJ_1_NaturalOrdering_inplace;
168: (B)->ops->forwardsolve = MatForwardSolve_SeqSBAIJ_1_NaturalOrdering_inplace;
169: (B)->ops->backwardsolve = MatBackwardSolve_SeqSBAIJ_1_NaturalOrdering_inplace;
170: } else {
171: (B)->ops->solve = MatSolve_SeqSBAIJ_1_inplace;
172: (B)->ops->solvetranspose = MatSolve_SeqSBAIJ_1_inplace;
173: (B)->ops->forwardsolve = MatForwardSolve_SeqSBAIJ_1_inplace;
174: (B)->ops->backwardsolve = MatBackwardSolve_SeqSBAIJ_1_inplace;
175: }
177: C->assembled = PETSC_TRUE;
178: C->preallocated = PETSC_TRUE;
180: PetscLogFlops(C->rmap->n);
181: return(0);
182: }
186: PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_bas(Mat A,MatFactorType ftype,Mat *B)
187: {
188: PetscInt n = A->rmap->n;
192: MatCreate(PetscObjectComm((PetscObject)A),B);
193: MatSetSizes(*B,n,n,n,n);
194: if (ftype == MAT_FACTOR_ICC) {
195: MatSetType(*B,MATSEQSBAIJ);
196: MatSeqSBAIJSetPreallocation(*B,1,MAT_SKIP_ALLOCATION,NULL);
198: (*B)->ops->iccfactorsymbolic = MatICCFactorSymbolic_SeqAIJ_Bas;
199: (*B)->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqAIJ_Bas;
200: } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Factor type not supported");
201: (*B)->factortype = ftype;
202: return(0);
203: }