Actual source code: pastix.c

      1: /*
      2:  Provides an interface to the PaStiX sparse solver
      3:  */
      4: #include <../src/mat/impls/aij/seq/aij.h>
      5: #include <../src/mat/impls/aij/mpi/mpiaij.h>
      6: #include <../src/mat/impls/sbaij/seq/sbaij.h>
      7: #include <../src/mat/impls/sbaij/mpi/mpisbaij.h>

      9: #if defined(PETSC_USE_COMPLEX)
     10: #define _H_COMPLEX
     11: #endif

     13: EXTERN_C_BEGIN
     14: #include <pastix.h>
     15: EXTERN_C_END

     17: #if defined(PETSC_USE_COMPLEX)
     18: #if defined(PETSC_USE_REAL_SINGLE)
     19: #define PASTIX_CALL c_pastix
     20: #else
     21: #define PASTIX_CALL z_pastix
     22: #endif

     24: #else /* PETSC_USE_COMPLEX */

     26: #if defined(PETSC_USE_REAL_SINGLE)
     27: #define PASTIX_CALL s_pastix
     28: #else
     29: #define PASTIX_CALL d_pastix
     30: #endif

     32: #endif /* PETSC_USE_COMPLEX */

     34: typedef PetscScalar PastixScalar;

     36: typedef struct Mat_Pastix_ {
     37:   pastix_data_t *pastix_data;    /* Pastix data storage structure                        */
     38:   MatStructure  matstruc;
     39:   PetscInt      n;               /* Number of columns in the matrix                      */
     40:   PetscInt      *colptr;         /* Index of first element of each column in row and val */
     41:   PetscInt      *row;            /* Row of each element of the matrix                    */
     42:   PetscScalar   *val;            /* Value of each element of the matrix                  */
     43:   PetscInt      *perm;           /* Permutation tabular                                  */
     44:   PetscInt      *invp;           /* Reverse permutation tabular                          */
     45:   PetscScalar   *rhs;            /* Rhight-hand-side member                              */
     46:   PetscInt      rhsnbr;          /* Rhight-hand-side number (must be 1)                  */
     47:   PetscInt      iparm[IPARM_SIZE];       /* Integer parameters                                   */
     48:   double        dparm[DPARM_SIZE];       /* Floating point parameters                            */
     49:   MPI_Comm      pastix_comm;     /* PaStiX MPI communicator                              */
     50:   PetscMPIInt   commRank;        /* MPI rank                                             */
     51:   PetscMPIInt   commSize;        /* MPI communicator size                                */
     52:   PetscBool     CleanUpPastix;   /* Boolean indicating if we call PaStiX clean step      */
     53:   VecScatter    scat_rhs;
     54:   VecScatter    scat_sol;
     55:   Vec           b_seq;
     56: } Mat_Pastix;

     58: extern PetscErrorCode MatDuplicate_Pastix(Mat,MatDuplicateOption,Mat*);

     60: /*
     61:    convert Petsc seqaij matrix to CSC: colptr[n], row[nz], val[nz]

     63:   input:
     64:     A       - matrix in seqaij or mpisbaij (bs=1) format
     65:     valOnly - FALSE: spaces are allocated and values are set for the CSC
     66:               TRUE:  Only fill values
     67:   output:
     68:     n       - Size of the matrix
     69:     colptr  - Index of first element of each column in row and val
     70:     row     - Row of each element of the matrix
     71:     values  - Value of each element of the matrix
     72:  */
     73: PetscErrorCode MatConvertToCSC(Mat A,PetscBool valOnly,PetscInt *n,PetscInt **colptr,PetscInt **row,PetscScalar **values)
     74: {
     75:   Mat_SeqAIJ  *aa      = (Mat_SeqAIJ*)A->data;
     76:   PetscInt    *rowptr  = aa->i;
     77:   PetscInt    *col     = aa->j;
     78:   PetscScalar *rvalues = aa->a;
     79:   PetscInt     m       = A->rmap->N;
     80:   PetscInt     nnz;
     81:   PetscInt     i,j, k;
     82:   PetscInt     base    = 1;
     83:   PetscInt     idx;
     84:   PetscInt     colidx;
     85:   PetscInt    *colcount;
     86:   PetscBool    isSBAIJ;
     87:   PetscBool    isSeqSBAIJ;
     88:   PetscBool    isMpiSBAIJ;
     89:   PetscBool    isSym;

     91:   MatIsSymmetric(A,0.0,&isSym);
     92:   PetscObjectTypeCompare((PetscObject)A,MATSBAIJ,&isSBAIJ);
     93:   PetscObjectTypeCompare((PetscObject)A,MATSEQSBAIJ,&isSeqSBAIJ);
     94:   PetscObjectTypeCompare((PetscObject)A,MATMPISBAIJ,&isMpiSBAIJ);

     96:   *n = A->cmap->N;

     98:   /* PaStiX only needs triangular matrix if matrix is symmetric
     99:    */
    100:   if (isSym && !(isSBAIJ || isSeqSBAIJ || isMpiSBAIJ)) nnz = (aa->nz - *n)/2 + *n;
    101:   else nnz = aa->nz;

    103:   if (!valOnly) {
    104:     PetscMalloc1((*n)+1,colptr);
    105:     PetscMalloc1(nnz,row);
    106:     PetscMalloc1(nnz,values);

    108:     if (isSBAIJ || isSeqSBAIJ || isMpiSBAIJ) {
    109:       PetscArraycpy (*colptr, rowptr, (*n)+1);
    110:       for (i = 0; i < *n+1; i++) (*colptr)[i] += base;
    111:       PetscArraycpy (*row, col, nnz);
    112:       for (i = 0; i < nnz; i++) (*row)[i] += base;
    113:       PetscArraycpy (*values, rvalues, nnz);
    114:     } else {
    115:       PetscMalloc1(*n,&colcount);

    117:       for (i = 0; i < m; i++) colcount[i] = 0;
    118:       /* Fill-in colptr */
    119:       for (i = 0; i < m; i++) {
    120:         for (j = rowptr[i]; j < rowptr[i+1]; j++) {
    121:           if (!isSym || col[j] <= i)  colcount[col[j]]++;
    122:         }
    123:       }

    125:       (*colptr)[0] = base;
    126:       for (j = 0; j < *n; j++) {
    127:         (*colptr)[j+1] = (*colptr)[j] + colcount[j];
    128:         /* in next loop we fill starting from (*colptr)[colidx] - base */
    129:         colcount[j] = -base;
    130:       }

    132:       /* Fill-in rows and values */
    133:       for (i = 0; i < m; i++) {
    134:         for (j = rowptr[i]; j < rowptr[i+1]; j++) {
    135:           if (!isSym || col[j] <= i) {
    136:             colidx         = col[j];
    137:             idx            = (*colptr)[colidx] + colcount[colidx];
    138:             (*row)[idx]    = i + base;
    139:             (*values)[idx] = rvalues[j];
    140:             colcount[colidx]++;
    141:           }
    142:         }
    143:       }
    144:       PetscFree(colcount);
    145:     }
    146:   } else {
    147:     /* Fill-in only values */
    148:     for (i = 0; i < m; i++) {
    149:       for (j = rowptr[i]; j < rowptr[i+1]; j++) {
    150:         colidx = col[j];
    151:         if ((isSBAIJ || isSeqSBAIJ || isMpiSBAIJ) ||!isSym || col[j] <= i) {
    152:           /* look for the value to fill */
    153:           for (k = (*colptr)[colidx] - base; k < (*colptr)[colidx + 1] - base; k++) {
    154:             if (((*row)[k]-base) == i) {
    155:               (*values)[k] = rvalues[j];
    156:               break;
    157:             }
    158:           }
    159:           /* data structure of sparse matrix has changed */
    161:         }
    162:       }
    163:     }
    164:   }
    165:   return 0;
    166: }

    168: /*
    169:   Call clean step of PaStiX if lu->CleanUpPastix == true.
    170:   Free the CSC matrix.
    171:  */
    172: PetscErrorCode MatDestroy_Pastix(Mat A)
    173: {
    174:   Mat_Pastix *lu = (Mat_Pastix*)A->data;

    176:   if (lu->CleanUpPastix) {
    177:     /* Terminate instance, deallocate memories */
    178:     VecScatterDestroy(&lu->scat_rhs);
    179:     VecDestroy(&lu->b_seq);
    180:     VecScatterDestroy(&lu->scat_sol);

    182:     lu->iparm[IPARM_START_TASK]=API_TASK_CLEAN;
    183:     lu->iparm[IPARM_END_TASK]  =API_TASK_CLEAN;

    185:     PASTIX_CALL(&(lu->pastix_data),
    186:                 lu->pastix_comm,
    187:                 lu->n,
    188:                 lu->colptr,
    189:                 lu->row,
    190:                 (PastixScalar*)lu->val,
    191:                 lu->perm,
    192:                 lu->invp,
    193:                 (PastixScalar*)lu->rhs,
    194:                 lu->rhsnbr,
    195:                 lu->iparm,
    196:                 lu->dparm);
    198:     PetscFree(lu->colptr);
    199:     PetscFree(lu->row);
    200:     PetscFree(lu->val);
    201:     PetscFree(lu->perm);
    202:     PetscFree(lu->invp);
    203:     MPI_Comm_free(&(lu->pastix_comm));
    204:   }
    205:   PetscFree(A->data);
    206:   return 0;
    207: }

    209: /*
    210:   Gather right-hand-side.
    211:   Call for Solve step.
    212:   Scatter solution.
    213:  */
    214: PetscErrorCode MatSolve_PaStiX(Mat A,Vec b,Vec x)
    215: {
    216:   Mat_Pastix  *lu = (Mat_Pastix*)A->data;
    217:   PetscScalar *array;
    218:   Vec          x_seq;

    220:   lu->rhsnbr = 1;
    221:   x_seq      = lu->b_seq;
    222:   if (lu->commSize > 1) {
    223:     /* PaStiX only supports centralized rhs. Scatter b into a sequential rhs vector */
    224:     VecScatterBegin(lu->scat_rhs,b,x_seq,INSERT_VALUES,SCATTER_FORWARD);
    225:     VecScatterEnd(lu->scat_rhs,b,x_seq,INSERT_VALUES,SCATTER_FORWARD);
    226:     VecGetArray(x_seq,&array);
    227:   } else {  /* size == 1 */
    228:     VecCopy(b,x);
    229:     VecGetArray(x,&array);
    230:   }
    231:   lu->rhs = array;
    232:   if (lu->commSize == 1) {
    233:     VecRestoreArray(x,&array);
    234:   } else {
    235:     VecRestoreArray(x_seq,&array);
    236:   }

    238:   /* solve phase */
    239:   /*-------------*/
    240:   lu->iparm[IPARM_START_TASK] = API_TASK_SOLVE;
    241:   lu->iparm[IPARM_END_TASK]   = API_TASK_REFINE;
    242:   lu->iparm[IPARM_RHS_MAKING] = API_RHS_B;

    244:   PASTIX_CALL(&(lu->pastix_data),
    245:               lu->pastix_comm,
    246:               lu->n,
    247:               lu->colptr,
    248:               lu->row,
    249:               (PastixScalar*)lu->val,
    250:               lu->perm,
    251:               lu->invp,
    252:               (PastixScalar*)lu->rhs,
    253:               lu->rhsnbr,
    254:               lu->iparm,
    255:               lu->dparm);

    258:   if (lu->commSize == 1) {
    259:     VecRestoreArray(x,&(lu->rhs));
    260:   } else {
    261:     VecRestoreArray(x_seq,&(lu->rhs));
    262:   }

    264:   if (lu->commSize > 1) { /* convert PaStiX centralized solution to petsc mpi x */
    265:     VecScatterBegin(lu->scat_sol,x_seq,x,INSERT_VALUES,SCATTER_FORWARD);
    266:     VecScatterEnd(lu->scat_sol,x_seq,x,INSERT_VALUES,SCATTER_FORWARD);
    267:   }
    268:   return 0;
    269: }

    271: /*
    272:   Numeric factorisation using PaStiX solver.

    274:  */
    275: PetscErrorCode MatFactorNumeric_PaStiX(Mat F,Mat A,const MatFactorInfo *info)
    276: {
    277:   Mat_Pastix     *lu =(Mat_Pastix*)(F)->data;
    278:   Mat            *tseq;
    280:   PetscInt       icntl;
    281:   PetscInt       M=A->rmap->N;
    282:   PetscBool      valOnly,flg, isSym;
    283:   IS             is_iden;
    284:   Vec            b;
    285:   IS             isrow;
    286:   PetscBool      isSeqAIJ,isSeqSBAIJ,isMPIAIJ;

    288:   PetscObjectTypeCompare((PetscObject)A,MATSEQAIJ,&isSeqAIJ);
    289:   PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&isMPIAIJ);
    290:   PetscObjectTypeCompare((PetscObject)A,MATSEQSBAIJ,&isSeqSBAIJ);
    291:   if (lu->matstruc == DIFFERENT_NONZERO_PATTERN) {
    292:     (F)->ops->solve = MatSolve_PaStiX;

    294:     /* Initialize a PASTIX instance */
    295:     MPI_Comm_dup(PetscObjectComm((PetscObject)A),&(lu->pastix_comm));
    296:     MPI_Comm_rank(lu->pastix_comm, &lu->commRank);
    297:     MPI_Comm_size(lu->pastix_comm, &lu->commSize);

    299:     /* Set pastix options */
    300:     lu->iparm[IPARM_MODIFY_PARAMETER] = API_NO;
    301:     lu->iparm[IPARM_START_TASK]       = API_TASK_INIT;
    302:     lu->iparm[IPARM_END_TASK]         = API_TASK_INIT;

    304:     lu->rhsnbr = 1;

    306:     /* Call to set default pastix options */
    307:     PASTIX_CALL(&(lu->pastix_data),
    308:                 lu->pastix_comm,
    309:                 lu->n,
    310:                 lu->colptr,
    311:                 lu->row,
    312:                 (PastixScalar*)lu->val,
    313:                 lu->perm,
    314:                 lu->invp,
    315:                 (PastixScalar*)lu->rhs,
    316:                 lu->rhsnbr,
    317:                 lu->iparm,
    318:                 lu->dparm);

    321:     PetscOptionsBegin(PetscObjectComm((PetscObject)A),((PetscObject)A)->prefix,"PaStiX Options","Mat");
    322:     icntl = -1;
    323:     lu->iparm[IPARM_VERBOSE] = API_VERBOSE_NOT;
    324:     PetscOptionsInt("-mat_pastix_verbose","iparm[IPARM_VERBOSE] : level of printing (0 to 2)","None",lu->iparm[IPARM_VERBOSE],&icntl,&flg);
    325:     if ((flg && icntl >= 0) || PetscLogPrintInfo) {
    326:       lu->iparm[IPARM_VERBOSE] =  icntl;
    327:     }
    328:     icntl=-1;
    329:     PetscOptionsInt("-mat_pastix_threadnbr","iparm[IPARM_THREAD_NBR] : Number of thread by MPI node","None",lu->iparm[IPARM_THREAD_NBR],&icntl,&flg);
    330:     if ((flg && icntl > 0)) {
    331:       lu->iparm[IPARM_THREAD_NBR] = icntl;
    332:     }
    333:     PetscOptionsEnd();
    334:     valOnly = PETSC_FALSE;
    335:   } else {
    336:     if (isSeqAIJ || isMPIAIJ) {
    337:       PetscFree(lu->colptr);
    338:       PetscFree(lu->row);
    339:       PetscFree(lu->val);
    340:       valOnly = PETSC_FALSE;
    341:     } else valOnly = PETSC_TRUE;
    342:   }

    344:   lu->iparm[IPARM_MATRIX_VERIFICATION] = API_YES;

    346:   /* convert mpi A to seq mat A */
    347:   ISCreateStride(PETSC_COMM_SELF,M,0,1,&isrow);
    348:   MatCreateSubMatrices(A,1,&isrow,&isrow,MAT_INITIAL_MATRIX,&tseq);
    349:   ISDestroy(&isrow);

    351:   MatConvertToCSC(*tseq,valOnly, &lu->n, &lu->colptr, &lu->row, &lu->val);
    352:   MatIsSymmetric(*tseq,0.0,&isSym);
    353:   MatDestroyMatrices(1,&tseq);

    355:   if (!lu->perm) {
    356:     PetscMalloc1(lu->n,&(lu->perm));
    357:     PetscMalloc1(lu->n,&(lu->invp));
    358:   }

    360:   if (isSym) {
    361:     /* On symmetric matrix, LLT */
    362:     lu->iparm[IPARM_SYM]           = API_SYM_YES;
    363:     lu->iparm[IPARM_FACTORIZATION] = API_FACT_LDLT;
    364:   } else {
    365:     /* On unsymmetric matrix, LU */
    366:     lu->iparm[IPARM_SYM]           = API_SYM_NO;
    367:     lu->iparm[IPARM_FACTORIZATION] = API_FACT_LU;
    368:   }

    370:   /*----------------*/
    371:   if (lu->matstruc == DIFFERENT_NONZERO_PATTERN) {
    372:     if (!(isSeqAIJ || isSeqSBAIJ) && !lu->b_seq) {
    373:       /* PaStiX only supports centralized rhs. Create scatter scat_rhs for repeated use in MatSolve() */
    374:       VecCreateSeq(PETSC_COMM_SELF,A->cmap->N,&lu->b_seq);
    375:       ISCreateStride(PETSC_COMM_SELF,A->cmap->N,0,1,&is_iden);
    376:       MatCreateVecs(A,NULL,&b);
    377:       VecScatterCreate(b,is_iden,lu->b_seq,is_iden,&lu->scat_rhs);
    378:       VecScatterCreate(lu->b_seq,is_iden,b,is_iden,&lu->scat_sol);
    379:       ISDestroy(&is_iden);
    380:       VecDestroy(&b);
    381:     }
    382:     lu->iparm[IPARM_START_TASK] = API_TASK_ORDERING;
    383:     lu->iparm[IPARM_END_TASK]   = API_TASK_NUMFACT;

    385:     PASTIX_CALL(&(lu->pastix_data),
    386:                 lu->pastix_comm,
    387:                 lu->n,
    388:                 lu->colptr,
    389:                 lu->row,
    390:                 (PastixScalar*)lu->val,
    391:                 lu->perm,
    392:                 lu->invp,
    393:                 (PastixScalar*)lu->rhs,
    394:                 lu->rhsnbr,
    395:                 lu->iparm,
    396:                 lu->dparm);
    398:   } else {
    399:     lu->iparm[IPARM_START_TASK] = API_TASK_NUMFACT;
    400:     lu->iparm[IPARM_END_TASK]   = API_TASK_NUMFACT;
    401:     PASTIX_CALL(&(lu->pastix_data),
    402:                 lu->pastix_comm,
    403:                 lu->n,
    404:                 lu->colptr,
    405:                 lu->row,
    406:                 (PastixScalar*)lu->val,
    407:                 lu->perm,
    408:                 lu->invp,
    409:                 (PastixScalar*)lu->rhs,
    410:                 lu->rhsnbr,
    411:                 lu->iparm,
    412:                 lu->dparm);
    414:   }

    416:   (F)->assembled    = PETSC_TRUE;
    417:   lu->matstruc      = SAME_NONZERO_PATTERN;
    418:   lu->CleanUpPastix = PETSC_TRUE;
    419:   return 0;
    420: }

    422: /* Note the Petsc r and c permutations are ignored */
    423: PetscErrorCode MatLUFactorSymbolic_AIJPASTIX(Mat F,Mat A,IS r,IS c,const MatFactorInfo *info)
    424: {
    425:   Mat_Pastix *lu = (Mat_Pastix*)F->data;

    427:   lu->iparm[IPARM_FACTORIZATION] = API_FACT_LU;
    428:   lu->iparm[IPARM_SYM]           = API_SYM_YES;
    429:   lu->matstruc                   = DIFFERENT_NONZERO_PATTERN;
    430:   F->ops->lufactornumeric        = MatFactorNumeric_PaStiX;
    431:   return 0;
    432: }

    434: PetscErrorCode MatCholeskyFactorSymbolic_SBAIJPASTIX(Mat F,Mat A,IS r,const MatFactorInfo *info)
    435: {
    436:   Mat_Pastix *lu = (Mat_Pastix*)(F)->data;

    438:   lu->iparm[IPARM_FACTORIZATION]  = API_FACT_LLT;
    439:   lu->iparm[IPARM_SYM]            = API_SYM_NO;
    440:   lu->matstruc                    = DIFFERENT_NONZERO_PATTERN;
    441:   (F)->ops->choleskyfactornumeric = MatFactorNumeric_PaStiX;
    442:   return 0;
    443: }

    445: PetscErrorCode MatView_PaStiX(Mat A,PetscViewer viewer)
    446: {
    447:   PetscBool         iascii;
    448:   PetscViewerFormat format;

    450:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
    451:   if (iascii) {
    452:     PetscViewerGetFormat(viewer,&format);
    453:     if (format == PETSC_VIEWER_ASCII_INFO) {
    454:       Mat_Pastix *lu=(Mat_Pastix*)A->data;

    456:       PetscViewerASCIIPrintf(viewer,"PaStiX run parameters:\n");
    457:       PetscViewerASCIIPrintf(viewer,"  Matrix type :                      %s \n",((lu->iparm[IPARM_SYM] == API_SYM_YES) ? "Symmetric" : "Unsymmetric"));
    458:       PetscViewerASCIIPrintf(viewer,"  Level of printing (0,1,2):         %" PetscInt_FMT " \n",lu->iparm[IPARM_VERBOSE]);
    459:       PetscViewerASCIIPrintf(viewer,"  Number of refinements iterations : %" PetscInt_FMT " \n",lu->iparm[IPARM_NBITER]);
    460:       PetscPrintf(PETSC_COMM_SELF,"  Error :                        %g \n",lu->dparm[DPARM_RELATIVE_ERROR]);
    461:     }
    462:   }
    463:   return 0;
    464: }

    466: /*MC
    467:      MATSOLVERPASTIX  - A solver package providing direct solvers (LU) for distributed
    468:   and sequential matrices via the external package PaStiX.

    470:   Use ./configure --download-pastix --download-ptscotch  to have PETSc installed with PasTiX

    472:   Use -pc_type lu -pc_factor_mat_solver_type pastix to use this direct solver

    474:   Options Database Keys:
    475: + -mat_pastix_verbose   <0,1,2>   - print level
    476: - -mat_pastix_threadnbr <integer> - Set the thread number by MPI task.

    478:   Notes:
    479:     This only works for matrices with symmetric nonzero structure, if you pass it a matrix with
    480:    nonsymmetric structure PasTiX and hence PETSc return with an error.

    482:   Level: beginner

    484: .seealso: PCFactorSetMatSolverType(), MatSolverType

    486: M*/

    488: PetscErrorCode MatGetInfo_PaStiX(Mat A,MatInfoType flag,MatInfo *info)
    489: {
    490:   Mat_Pastix *lu =(Mat_Pastix*)A->data;

    492:   info->block_size        = 1.0;
    493:   info->nz_allocated      = lu->iparm[IPARM_NNZEROS];
    494:   info->nz_used           = lu->iparm[IPARM_NNZEROS];
    495:   info->nz_unneeded       = 0.0;
    496:   info->assemblies        = 0.0;
    497:   info->mallocs           = 0.0;
    498:   info->memory            = 0.0;
    499:   info->fill_ratio_given  = 0;
    500:   info->fill_ratio_needed = 0;
    501:   info->factor_mallocs    = 0;
    502:   return 0;
    503: }

    505: static PetscErrorCode MatFactorGetSolverType_pastix(Mat A,MatSolverType *type)
    506: {
    507:   *type = MATSOLVERPASTIX;
    508:   return 0;
    509: }

    511: /*
    512:     The seq and mpi versions of this function are the same
    513: */
    514: static PetscErrorCode MatGetFactor_seqaij_pastix(Mat A,MatFactorType ftype,Mat *F)
    515: {
    516:   Mat         B;
    517:   Mat_Pastix *pastix;

    520:   /* Create the factorization matrix */
    521:   MatCreate(PetscObjectComm((PetscObject)A),&B);
    522:   MatSetSizes(B,A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N);
    523:   PetscStrallocpy("pastix",&((PetscObject)B)->type_name);
    524:   MatSetUp(B);

    526:   B->trivialsymbolic       = PETSC_TRUE;
    527:   B->ops->lufactorsymbolic = MatLUFactorSymbolic_AIJPASTIX;
    528:   B->ops->view             = MatView_PaStiX;
    529:   B->ops->getinfo          = MatGetInfo_PaStiX;

    531:   PetscObjectComposeFunction((PetscObject)B,"MatFactorGetSolverType_C",MatFactorGetSolverType_pastix);

    533:   B->factortype = MAT_FACTOR_LU;

    535:   /* set solvertype */
    536:   PetscFree(B->solvertype);
    537:   PetscStrallocpy(MATSOLVERPASTIX,&B->solvertype);

    539:   PetscNewLog(B,&pastix);

    541:   pastix->CleanUpPastix = PETSC_FALSE;
    542:   pastix->scat_rhs      = NULL;
    543:   pastix->scat_sol      = NULL;
    544:   B->ops->getinfo       = MatGetInfo_External;
    545:   B->ops->destroy       = MatDestroy_Pastix;
    546:   B->data               = (void*)pastix;

    548:   *F = B;
    549:   return 0;
    550: }

    552: static PetscErrorCode MatGetFactor_mpiaij_pastix(Mat A,MatFactorType ftype,Mat *F)
    553: {
    554:   Mat         B;
    555:   Mat_Pastix *pastix;

    558:   /* Create the factorization matrix */
    559:   MatCreate(PetscObjectComm((PetscObject)A),&B);
    560:   MatSetSizes(B,A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N);
    561:   PetscStrallocpy("pastix",&((PetscObject)B)->type_name);
    562:   MatSetUp(B);

    564:   B->trivialsymbolic       = PETSC_TRUE;
    565:   B->ops->lufactorsymbolic = MatLUFactorSymbolic_AIJPASTIX;
    566:   B->ops->view             = MatView_PaStiX;
    567:   B->ops->getinfo          = MatGetInfo_PaStiX;
    568:   PetscObjectComposeFunction((PetscObject)B,"MatFactorGetSolverType_C",MatFactorGetSolverType_pastix);

    570:   B->factortype = MAT_FACTOR_LU;

    572:   /* set solvertype */
    573:   PetscFree(B->solvertype);
    574:   PetscStrallocpy(MATSOLVERPASTIX,&B->solvertype);

    576:   PetscNewLog(B,&pastix);

    578:   pastix->CleanUpPastix = PETSC_FALSE;
    579:   pastix->scat_rhs      = NULL;
    580:   pastix->scat_sol      = NULL;
    581:   B->ops->getinfo       = MatGetInfo_External;
    582:   B->ops->destroy       = MatDestroy_Pastix;
    583:   B->data               = (void*)pastix;

    585:   *F = B;
    586:   return 0;
    587: }

    589: static PetscErrorCode MatGetFactor_seqsbaij_pastix(Mat A,MatFactorType ftype,Mat *F)
    590: {
    591:   Mat         B;
    592:   Mat_Pastix *pastix;

    595:   /* Create the factorization matrix */
    596:   MatCreate(PetscObjectComm((PetscObject)A),&B);
    597:   MatSetSizes(B,A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N);
    598:   PetscStrallocpy("pastix",&((PetscObject)B)->type_name);
    599:   MatSetUp(B);

    601:   B->trivialsymbolic             = PETSC_TRUE;
    602:   B->ops->choleskyfactorsymbolic = MatCholeskyFactorSymbolic_SBAIJPASTIX;
    603:   B->ops->view                   = MatView_PaStiX;
    604:   B->ops->getinfo                = MatGetInfo_PaStiX;
    605:   PetscObjectComposeFunction((PetscObject)B,"MatFactorGetSolverType_C",MatFactorGetSolverType_pastix);

    607:   B->factortype = MAT_FACTOR_CHOLESKY;

    609:   /* set solvertype */
    610:   PetscFree(B->solvertype);
    611:   PetscStrallocpy(MATSOLVERPASTIX,&B->solvertype);

    613:   PetscNewLog(B,&pastix);

    615:   pastix->CleanUpPastix = PETSC_FALSE;
    616:   pastix->scat_rhs      = NULL;
    617:   pastix->scat_sol      = NULL;
    618:   B->ops->getinfo       = MatGetInfo_External;
    619:   B->ops->destroy       = MatDestroy_Pastix;
    620:   B->data               = (void*)pastix;
    621:   *F = B;
    622:   return 0;
    623: }

    625: static PetscErrorCode MatGetFactor_mpisbaij_pastix(Mat A,MatFactorType ftype,Mat *F)
    626: {
    627:   Mat         B;
    628:   Mat_Pastix *pastix;

    632:   /* Create the factorization matrix */
    633:   MatCreate(PetscObjectComm((PetscObject)A),&B);
    634:   MatSetSizes(B,A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N);
    635:   PetscStrallocpy("pastix",&((PetscObject)B)->type_name);
    636:   MatSetUp(B);

    638:   B->ops->choleskyfactorsymbolic = MatCholeskyFactorSymbolic_SBAIJPASTIX;
    639:   B->ops->view                   = MatView_PaStiX;
    640:   B->ops->getinfo                = MatGetInfo_PaStiX;
    641:   B->ops->destroy                = MatDestroy_Pastix;
    642:   PetscObjectComposeFunction((PetscObject)B,"MatFactorGetSolverType_C",MatFactorGetSolverType_pastix);

    644:   B->factortype = MAT_FACTOR_CHOLESKY;

    646:   /* set solvertype */
    647:   PetscFree(B->solvertype);
    648:   PetscStrallocpy(MATSOLVERPASTIX,&B->solvertype);

    650:   PetscNewLog(B,&pastix);

    652:   pastix->CleanUpPastix = PETSC_FALSE;
    653:   pastix->scat_rhs      = NULL;
    654:   pastix->scat_sol      = NULL;
    655:   B->data               = (void*)pastix;

    657:   *F = B;
    658:   return 0;
    659: }

    661: PETSC_EXTERN PetscErrorCode MatSolverTypeRegister_Pastix(void)
    662: {
    663:   MatSolverTypeRegister(MATSOLVERPASTIX,MATMPIAIJ,        MAT_FACTOR_LU,MatGetFactor_mpiaij_pastix);
    664:   MatSolverTypeRegister(MATSOLVERPASTIX,MATSEQAIJ,        MAT_FACTOR_LU,MatGetFactor_seqaij_pastix);
    665:   MatSolverTypeRegister(MATSOLVERPASTIX,MATMPISBAIJ,      MAT_FACTOR_CHOLESKY,MatGetFactor_mpisbaij_pastix);
    666:   MatSolverTypeRegister(MATSOLVERPASTIX,MATSEQSBAIJ,      MAT_FACTOR_CHOLESKY,MatGetFactor_seqsbaij_pastix);
    667:   return 0;
    668: }