Date: 2021-03-03T22:26:13+00:00

Actual source code: basfactor.c
petsc-3.14.5 2021-03-03
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      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;
     11:   PetscBool      perm_identity,missing;
     12:   PetscInt       reallocs=0,i,*ai=a->i,*aj=a->j,am=A->rmap->n,*ui;
     13:   const PetscInt *rip,*riip;
     14:   PetscInt       j;
     15:   PetscInt       d;
     16:   PetscInt       ncols,*cols,*uj;
     17:   PetscReal      fill=info->fill,levels=info->levels;
     18:   IS             iperm;
     19:   spbas_matrix   Pattern_0, Pattern_P;

     22:   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);
     23:   MatMissingDiagonal(A,&missing,&d);
     24:   if (missing) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Matrix is missing diagonal entry %D",d);
     25:   ISIdentity(perm,&perm_identity);
     26:   ISInvertPermutation(perm,PETSC_DECIDE,&iperm);

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

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

     47:     /* Create spbas_matrix for pattern */
     48:     spbas_pattern_only(am, am, ai, aj, &Pattern_0);

     50:     /* Apply the permutation */
     51:     spbas_apply_reordering(&Pattern_0, rip, riip);

     53:     /* Raise the power */
     54:     spbas_power(Pattern_0, (int) levels+1, &Pattern_P);
     55:     spbas_delete(Pattern_0);

     57:     /* Keep only upper triangle of pattern */
     58:     spbas_keep_upper(&Pattern_P);

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

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

     67:   b               = (Mat_SeqSBAIJ*)(fact)->data;
     68:   b->singlemalloc = PETSC_FALSE;

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

     72:   b->j    = uj;
     73:   b->i    = ui;
     74:   b->diag = NULL;
     75:   b->ilen = NULL;
     76:   b->imax = NULL;
     77:   b->row  = perm;
     78:   b->col  = perm;

     80:   PetscObjectReference((PetscObject)perm);
     81:   PetscObjectReference((PetscObject)perm);

     83:   b->icol          = iperm;
     84:   b->pivotinblocks = PETSC_FALSE; /* need to get from MatFactorInfo */
     85:   PetscMalloc1(am+1,&b->solve_work);
     86:   PetscLogObjectMemory((PetscObject)(fact),(ui[am]-am)*(sizeof(PetscInt)+sizeof(MatScalar)));
     87:   b->maxnz         = b->nz = ui[am];
     88:   b->free_a        = PETSC_TRUE;
     89:   b->free_ij       = PETSC_TRUE;

     91:   (fact)->info.factor_mallocs   = reallocs;
     92:   (fact)->info.fill_ratio_given = fill;
     93:   if (ai[am] != 0) {
     94:     (fact)->info.fill_ratio_needed = ((PetscReal)ui[am])/((PetscReal)ai[am]);
     95:   } else {
     96:     (fact)->info.fill_ratio_needed = 0.0;
     97:   }
     98:   /*  (fact)->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqAIJ_inplace; */
     99:   return(0);
    100: }

    103: PetscErrorCode MatCholeskyFactorNumeric_SeqAIJ_Bas(Mat B,Mat A,const MatFactorInfo *info)
    104: {
    105:   Mat            C = B;
    106:   Mat_SeqSBAIJ   *b=(Mat_SeqSBAIJ*)C->data;
    107:   IS             ip=b->row,iip = b->icol;
    109:   const PetscInt *rip,*riip;
    110:   PetscInt       mbs=A->rmap->n,*bi=b->i,*bj=b->j;

    112:   MatScalar    *ba     = b->a;
    113:   PetscReal    shiftnz = info->shiftamount;
    114:   PetscReal    droptol = -1;
    115:   PetscBool    perm_identity;
    116:   spbas_matrix Pattern, matrix_L,matrix_LT;
    117:   PetscReal    mem_reduction;

    120:   /* Reduce memory requirements:   erase values of B-matrix */
    121:   PetscFree(ba);
    122:   /*   Compress (maximum) sparseness pattern of B-matrix */
    123:   spbas_compress_pattern(bi, bj, mbs, mbs, SPBAS_DIAGONAL_OFFSETS,&Pattern, &mem_reduction);
    124:   PetscFree(bi);
    125:   PetscFree(bj);

    127:   PetscInfo1(NULL,"    compression rate for spbas_compress_pattern %g \n",(double)mem_reduction);

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

    133:   if (info->usedt) {
    134:     droptol = info->dt;
    135:   }
    136:   for (NEGATIVE_DIAGONAL; ierr == NEGATIVE_DIAGONAL;)
    137:   {
    138:     spbas_incomplete_cholesky(A, rip, riip, Pattern, droptol, shiftnz,&matrix_LT);
    139:     if (ierr == NEGATIVE_DIAGONAL) {
    140:       shiftnz *= 1.5;
    141:       if (shiftnz < 1e-5) shiftnz=1e-5;
    142:       PetscInfo1(NULL,"spbas_incomplete_cholesky found a negative diagonal. Trying again with Manteuffel shift=%g\n",(double)shiftnz);
    143:     }
    144:   }
    145:   spbas_delete(Pattern);

    147:   PetscInfo1(NULL,"    memory_usage for  spbas_incomplete_cholesky  %g bytes per row\n", (double)(PetscReal) (spbas_memory_requirement(matrix_LT)/ (PetscReal) mbs));

    149:   ISRestoreIndices(ip,&rip);
    150:   ISRestoreIndices(iip,&riip);

    152:   /* Convert spbas_matrix to compressed row storage */
    153:   spbas_transpose(matrix_LT, &matrix_L);
    154:   spbas_delete(matrix_LT);
    155:   spbas_matrix_to_crs(matrix_L, &ba, &bi, &bj);
    156:   b->i =bi; b->j=bj; b->a=ba;
    157:   spbas_delete(matrix_L);

    159:   /* Set the appropriate solution functions */
    160:   ISIdentity(ip,&perm_identity);
    161:   if (perm_identity) {
    162:     (B)->ops->solve          = MatSolve_SeqSBAIJ_1_NaturalOrdering_inplace;
    163:     (B)->ops->solvetranspose = MatSolve_SeqSBAIJ_1_NaturalOrdering_inplace;
    164:     (B)->ops->forwardsolve   = MatForwardSolve_SeqSBAIJ_1_NaturalOrdering_inplace;
    165:     (B)->ops->backwardsolve  = MatBackwardSolve_SeqSBAIJ_1_NaturalOrdering_inplace;
    166:   } else {
    167:     (B)->ops->solve          = MatSolve_SeqSBAIJ_1_inplace;
    168:     (B)->ops->solvetranspose = MatSolve_SeqSBAIJ_1_inplace;
    169:     (B)->ops->forwardsolve   = MatForwardSolve_SeqSBAIJ_1_inplace;
    170:     (B)->ops->backwardsolve  = MatBackwardSolve_SeqSBAIJ_1_inplace;
    171:   }

    173:   C->assembled    = PETSC_TRUE;
    174:   C->preallocated = PETSC_TRUE;

    176:   PetscLogFlops(C->rmap->n);
    177:   return(0);
    178: }

    180: PetscErrorCode MatFactorGetSolverType_seqaij_bas(Mat A,MatSolverType *type)
    181: {
    183:   *type = MATSOLVERBAS;
    184:   return(0);
    185: }

    187: PETSC_INTERN PetscErrorCode MatGetFactor_seqaij_bas(Mat A,MatFactorType ftype,Mat *B)
    188: {
    189:   PetscInt       n = A->rmap->n;

    193:   MatCreate(PetscObjectComm((PetscObject)A),B);
    194:   MatSetSizes(*B,n,n,n,n);
    195:   if (ftype == MAT_FACTOR_ICC) {
    196:     MatSetType(*B,MATSEQSBAIJ);
    197:     MatSeqSBAIJSetPreallocation(*B,1,MAT_SKIP_ALLOCATION,NULL);

    199:     (*B)->ops->iccfactorsymbolic     = MatICCFactorSymbolic_SeqAIJ_Bas;
    200:     (*B)->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqAIJ_Bas;
    201:      PetscObjectComposeFunction((PetscObject)*B,"MatFactorGetSolverType_C",MatFactorGetSolverType_seqaij_bas);
    202:   } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Factor type not supported");
    203:   (*B)->factortype = ftype;

    205:   PetscFree((*B)->solvertype);
    206:   PetscStrallocpy(MATSOLVERBAS,&(*B)->solvertype);
    207:   (*B)->useordering = PETSC_TRUE;
    208:   return(0);
    209: }