Date: 2025-03-29T05:58:32+00:00

Actual source code: basfactor.c

      1: #include <../src/mat/impls/aij/seq/aij.h>
      2: #include <../src/mat/impls/sbaij/seq/sbaij.h>
      3: #include <../src/mat/impls/aij/seq/bas/spbas.h>

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

     19:   PetscFunctionBegin;
     20:   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);
     21:   PetscCall(MatMissingDiagonal(A, &missing, &d));
     22:   PetscCheck(!missing, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONGSTATE, "Matrix is missing diagonal entry %" PetscInt_FMT, d);
     23:   PetscCall(ISIdentity(perm, &perm_identity));
     24:   PetscCall(ISInvertPermutation(perm, PETSC_DECIDE, &iperm));

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

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

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

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

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

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

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

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

     63:   b = (Mat_SeqSBAIJ *)fact->data;
     64:   PetscCall(PetscMalloc1(ui[am] + 1, &b->a));

     66:   b->j    = uj;
     67:   b->i    = ui;
     68:   b->diag = NULL;
     69:   b->ilen = NULL;
     70:   b->imax = NULL;
     71:   b->row  = perm;
     72:   b->col  = perm;

     74:   PetscCall(PetscObjectReference((PetscObject)perm));
     75:   PetscCall(PetscObjectReference((PetscObject)perm));

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

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

     95: static PetscErrorCode MatCholeskyFactorNumeric_SeqAIJ_Bas(Mat B, Mat A, const MatFactorInfo *info)
     96: {
     97:   Mat             C  = B;
     98:   Mat_SeqSBAIJ   *b  = (Mat_SeqSBAIJ *)C->data;
     99:   IS              ip = b->row, iip = b->icol;
    100:   const PetscInt *rip, *riip;
    101:   PetscInt        mbs = A->rmap->n, *bi = b->i, *bj = b->j;
    102:   MatScalar      *ba      = b->a;
    103:   PetscReal       shiftnz = info->shiftamount;
    104:   PetscReal       droptol = -1;
    105:   PetscBool       perm_identity;
    106:   spbas_matrix    Pattern, matrix_L, matrix_LT;
    107:   PetscReal       mem_reduction;

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

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

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

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

    125:   for (int ierr = NEGATIVE_DIAGONAL; ierr == NEGATIVE_DIAGONAL;) {
    126:     PetscBool success;

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

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

    139:   PetscCall(ISRestoreIndices(ip, &rip));
    140:   PetscCall(ISRestoreIndices(iip, &riip));

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

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

    165:   C->assembled    = PETSC_TRUE;
    166:   C->preallocated = PETSC_TRUE;

    168:   PetscCall(PetscLogFlops(C->rmap->n));
    169:   PetscFunctionReturn(PETSC_SUCCESS);
    170: }

    172: static PetscErrorCode MatFactorGetSolverType_seqaij_bas(Mat A, MatSolverType *type)
    173: {
    174:   PetscFunctionBegin;
    175:   *type = MATSOLVERBAS;
    176:   PetscFunctionReturn(PETSC_SUCCESS);
    177: }

    179: PETSC_INTERN PetscErrorCode MatGetFactor_seqaij_bas(Mat A, MatFactorType ftype, Mat *B)
    180: {
    181:   PetscInt n = A->rmap->n;

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

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

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