Actual source code: basfactor.c


  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>

  6: PetscErrorCode MatICCFactorSymbolic_SeqAIJ_Bas(Mat fact, Mat A, IS perm, const MatFactorInfo *info)
  7: {
  8:   Mat_SeqAIJ     *a = (Mat_SeqAIJ *)A->data;
  9:   Mat_SeqSBAIJ   *b;
 10:   PetscBool       perm_identity, missing;
 11:   PetscInt        reallocs = 0, i, *ai = a->i, *aj = a->j, am = A->rmap->n, *ui;
 12:   const PetscInt *rip, *riip;
 13:   PetscInt        j;
 14:   PetscInt        d;
 15:   PetscInt        ncols, *cols, *uj;
 16:   PetscReal       fill = info->fill, levels = info->levels;
 17:   IS              iperm;
 18:   spbas_matrix    Pattern_0, Pattern_P;

 20:   PetscFunctionBegin;
 21:   PetscCheck(A->rmap->n == A->cmap->n, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONG, "Must be square matrix, rows %" PetscInt_FMT " columns %" PetscInt_FMT, A->rmap->n, A->cmap->n);
 22:   PetscCall(MatMissingDiagonal(A, &missing, &d));
 23:   PetscCheck(!missing, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONGSTATE, "Matrix is missing diagonal entry %" PetscInt_FMT, d);
 24:   PetscCall(ISIdentity(perm, &perm_identity));
 25:   PetscCall(ISInvertPermutation(perm, PETSC_DECIDE, &iperm));

 27:   /* ICC(0) without matrix ordering: simply copies fill pattern */
 28:   if (!levels && perm_identity) {
 29:     PetscCall(PetscMalloc1(am + 1, &ui));
 30:     ui[0] = 0;

 32:     for (i = 0; i < am; i++) ui[i + 1] = ui[i] + ai[i + 1] - a->diag[i];
 33:     PetscCall(PetscMalloc1(ui[am] + 1, &uj));
 34:     cols = uj;
 35:     for (i = 0; i < am; i++) {
 36:       aj    = a->j + a->diag[i];
 37:       ncols = ui[i + 1] - ui[i];
 38:       for (j = 0; j < ncols; j++) *cols++ = *aj++;
 39:     }
 40:   } else { /* case: levels>0 || (levels=0 && !perm_identity) */
 41:     PetscCall(ISGetIndices(iperm, &riip));
 42:     PetscCall(ISGetIndices(perm, &rip));

 44:     /* Create spbas_matrix for pattern */
 45:     PetscCall(spbas_pattern_only(am, am, ai, aj, &Pattern_0));

 47:     /* Apply the permutation */
 48:     PetscCall(spbas_apply_reordering(&Pattern_0, rip, riip));

 50:     /* Raise the power */
 51:     PetscCall(spbas_power(Pattern_0, (int)levels + 1, &Pattern_P));
 52:     PetscCall(spbas_delete(Pattern_0));

 54:     /* Keep only upper triangle of pattern */
 55:     PetscCall(spbas_keep_upper(&Pattern_P));

 57:     /* Convert to Sparse Row Storage  */
 58:     PetscCall(spbas_matrix_to_crs(Pattern_P, NULL, &ui, &uj));
 59:     PetscCall(spbas_delete(Pattern_P));
 60:   } /* end of case: levels>0 || (levels=0 && !perm_identity) */

 62:   /* put together the new matrix in MATSEQSBAIJ format */

 64:   b               = (Mat_SeqSBAIJ *)(fact)->data;
 65:   b->singlemalloc = PETSC_FALSE;

 67:   PetscCall(PetscMalloc1(ui[am] + 1, &b->a));

 69:   b->j    = uj;
 70:   b->i    = ui;
 71:   b->diag = NULL;
 72:   b->ilen = NULL;
 73:   b->imax = NULL;
 74:   b->row  = perm;
 75:   b->col  = perm;

 77:   PetscCall(PetscObjectReference((PetscObject)perm));
 78:   PetscCall(PetscObjectReference((PetscObject)perm));

 80:   b->icol          = iperm;
 81:   b->pivotinblocks = PETSC_FALSE; /* need to get from MatFactorInfo */
 82:   PetscCall(PetscMalloc1(am + 1, &b->solve_work));
 83:   b->maxnz = b->nz = ui[am];
 84:   b->free_a        = PETSC_TRUE;
 85:   b->free_ij       = PETSC_TRUE;

 87:   (fact)->info.factor_mallocs   = reallocs;
 88:   (fact)->info.fill_ratio_given = fill;
 89:   if (ai[am] != 0) {
 90:     (fact)->info.fill_ratio_needed = ((PetscReal)ui[am]) / ((PetscReal)ai[am]);
 91:   } else {
 92:     (fact)->info.fill_ratio_needed = 0.0;
 93:   }
 94:   /*  (fact)->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqAIJ_inplace; */
 95:   PetscFunctionReturn(PETSC_SUCCESS);
 96: }

 98: PetscErrorCode MatCholeskyFactorNumeric_SeqAIJ_Bas(Mat B, Mat A, const MatFactorInfo *info)
 99: {
100:   Mat             C  = B;
101:   Mat_SeqSBAIJ   *b  = (Mat_SeqSBAIJ *)C->data;
102:   IS              ip = b->row, iip = b->icol;
103:   const PetscInt *rip, *riip;
104:   PetscInt        mbs = A->rmap->n, *bi = b->i, *bj = b->j;
105:   MatScalar      *ba      = b->a;
106:   PetscReal       shiftnz = info->shiftamount;
107:   PetscReal       droptol = -1;
108:   PetscBool       perm_identity;
109:   spbas_matrix    Pattern, matrix_L, matrix_LT;
110:   PetscReal       mem_reduction;

112:   PetscFunctionBegin;
113:   /* Reduce memory requirements:   erase values of B-matrix */
114:   PetscCall(PetscFree(ba));
115:   /*   Compress (maximum) sparseness pattern of B-matrix */
116:   PetscCall(spbas_compress_pattern(bi, bj, mbs, mbs, SPBAS_DIAGONAL_OFFSETS, &Pattern, &mem_reduction));
117:   PetscCall(PetscFree(bi));
118:   PetscCall(PetscFree(bj));

120:   PetscCall(PetscInfo(NULL, "    compression rate for spbas_compress_pattern %g \n", (double)mem_reduction));

122:   /* Make Cholesky decompositions with larger Manteuffel shifts until no more    negative diagonals are found. */
123:   PetscCall(ISGetIndices(ip, &rip));
124:   PetscCall(ISGetIndices(iip, &riip));

126:   if (info->usedt) droptol = info->dt;

128:   for (int ierr = NEGATIVE_DIAGONAL; ierr == NEGATIVE_DIAGONAL;) {
129:     PetscBool success;

131:     ierr = (int)spbas_incomplete_cholesky(A, rip, riip, Pattern, droptol, shiftnz, &matrix_LT, &success);
132:     if (!success) {
133:       shiftnz *= 1.5;
134:       if (shiftnz < 1e-5) shiftnz = 1e-5;
135:       PetscCall(PetscInfo(NULL, "spbas_incomplete_cholesky found a negative diagonal. Trying again with Manteuffel shift=%g\n", (double)shiftnz));
136:     }
137:   }
138:   PetscCall(spbas_delete(Pattern));

140:   PetscCall(PetscInfo(NULL, "    memory_usage for  spbas_incomplete_cholesky  %g bytes per row\n", (double)(PetscReal)(spbas_memory_requirement(matrix_LT) / (PetscReal)mbs)));

142:   PetscCall(ISRestoreIndices(ip, &rip));
143:   PetscCall(ISRestoreIndices(iip, &riip));

145:   /* Convert spbas_matrix to compressed row storage */
146:   PetscCall(spbas_transpose(matrix_LT, &matrix_L));
147:   PetscCall(spbas_delete(matrix_LT));
148:   PetscCall(spbas_matrix_to_crs(matrix_L, &ba, &bi, &bj));
149:   b->i = bi;
150:   b->j = bj;
151:   b->a = ba;
152:   PetscCall(spbas_delete(matrix_L));

154:   /* Set the appropriate solution functions */
155:   PetscCall(ISIdentity(ip, &perm_identity));
156:   if (perm_identity) {
157:     (B)->ops->solve          = MatSolve_SeqSBAIJ_1_NaturalOrdering_inplace;
158:     (B)->ops->solvetranspose = MatSolve_SeqSBAIJ_1_NaturalOrdering_inplace;
159:     (B)->ops->forwardsolve   = MatForwardSolve_SeqSBAIJ_1_NaturalOrdering_inplace;
160:     (B)->ops->backwardsolve  = MatBackwardSolve_SeqSBAIJ_1_NaturalOrdering_inplace;
161:   } else {
162:     (B)->ops->solve          = MatSolve_SeqSBAIJ_1_inplace;
163:     (B)->ops->solvetranspose = MatSolve_SeqSBAIJ_1_inplace;
164:     (B)->ops->forwardsolve   = MatForwardSolve_SeqSBAIJ_1_inplace;
165:     (B)->ops->backwardsolve  = MatBackwardSolve_SeqSBAIJ_1_inplace;
166:   }

168:   C->assembled    = PETSC_TRUE;
169:   C->preallocated = PETSC_TRUE;

171:   PetscCall(PetscLogFlops(C->rmap->n));
172:   PetscFunctionReturn(PETSC_SUCCESS);
173: }

175: PetscErrorCode MatFactorGetSolverType_seqaij_bas(Mat A, MatSolverType *type)
176: {
177:   PetscFunctionBegin;
178:   *type = MATSOLVERBAS;
179:   PetscFunctionReturn(PETSC_SUCCESS);
180: }

182: PETSC_INTERN PetscErrorCode MatGetFactor_seqaij_bas(Mat A, MatFactorType ftype, Mat *B)
183: {
184:   PetscInt n = A->rmap->n;

186:   PetscFunctionBegin;
187:   PetscCall(MatCreate(PetscObjectComm((PetscObject)A), B));
188:   PetscCall(MatSetSizes(*B, n, n, n, n));
189:   if (ftype == MAT_FACTOR_ICC) {
190:     PetscCall(MatSetType(*B, MATSEQSBAIJ));
191:     PetscCall(MatSeqSBAIJSetPreallocation(*B, 1, MAT_SKIP_ALLOCATION, NULL));

193:     (*B)->ops->iccfactorsymbolic     = MatICCFactorSymbolic_SeqAIJ_Bas;
194:     (*B)->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqAIJ_Bas;
195:     PetscCall(PetscObjectComposeFunction((PetscObject)*B, "MatFactorGetSolverType_C", MatFactorGetSolverType_seqaij_bas));
196:     PetscCall(PetscStrallocpy(MATORDERINGND, (char **)&(*B)->preferredordering[MAT_FACTOR_LU]));
197:     PetscCall(PetscStrallocpy(MATORDERINGND, (char **)&(*B)->preferredordering[MAT_FACTOR_CHOLESKY]));
198:   } else SETERRQ(PETSC_COMM_SELF, PETSC_ERR_SUP, "Factor type not supported");
199:   (*B)->factortype = ftype;

201:   PetscCall(PetscFree((*B)->solvertype));
202:   PetscCall(PetscStrallocpy(MATSOLVERBAS, &(*B)->solvertype));
203:   (*B)->canuseordering = PETSC_TRUE;
204:   PetscCall(PetscStrallocpy(MATORDERINGNATURAL, (char **)&(*B)->preferredordering[MAT_FACTOR_ICC]));
205:   PetscFunctionReturn(PETSC_SUCCESS);
206: }