Date: 2015-10-02T22:07:27+00:00

Actual source code: pastix.c
petsc-3.6.2 2015-10-02
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      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: #define PASTIX_CHECKMATRIX c_pastix_checkMatrix
     21: #else
     22: #define PASTIX_CALL z_pastix
     23: #define PASTIX_CHECKMATRIX z_pastix_checkMatrix
     24: #endif

     26: #else /* PETSC_USE_COMPLEX */

     28: #if defined(PETSC_USE_REAL_SINGLE)
     29: #define PASTIX_CALL s_pastix
     30: #define PASTIX_CHECKMATRIX s_pastix_checkMatrix
     31: #else
     32: #define PASTIX_CALL d_pastix
     33: #define PASTIX_CHECKMATRIX d_pastix_checkMatrix
     34: #endif

     36: #endif /* PETSC_USE_COMPLEX */

     38: typedef PetscScalar PastixScalar;

     40: typedef struct Mat_Pastix_ {
     41:   pastix_data_t *pastix_data;    /* Pastix data storage structure                        */
     42:   MatStructure  matstruc;
     43:   PetscInt      n;               /* Number of columns in the matrix                      */
     44:   PetscInt      *colptr;         /* Index of first element of each column in row and val */
     45:   PetscInt      *row;            /* Row of each element of the matrix                    */
     46:   PetscScalar   *val;            /* Value of each element of the matrix                  */
     47:   PetscInt      *perm;           /* Permutation tabular                                  */
     48:   PetscInt      *invp;           /* Reverse permutation tabular                          */
     49:   PetscScalar   *rhs;            /* Rhight-hand-side member                              */
     50:   PetscInt      rhsnbr;          /* Rhight-hand-side number (must be 1)                  */
     51:   PetscInt      iparm[64];       /* Integer parameters                                   */
     52:   double        dparm[64];       /* Floating point parameters                            */
     53:   MPI_Comm      pastix_comm;     /* PaStiX MPI communicator                              */
     54:   PetscMPIInt   commRank;        /* MPI rank                                             */
     55:   PetscMPIInt   commSize;        /* MPI communicator size                                */
     56:   PetscBool     CleanUpPastix;   /* Boolean indicating if we call PaStiX clean step      */
     57:   VecScatter    scat_rhs;
     58:   VecScatter    scat_sol;
     59:   Vec           b_seq;
     60:   PetscBool     isAIJ;
     61:   PetscErrorCode (*Destroy)(Mat);
     62: } Mat_Pastix;

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

     68: /*
     69:    convert Petsc seqaij matrix to CSC: colptr[n], row[nz], val[nz]

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

    105:   MatIsSymmetric(A,0.0,&isSym);
    106:   PetscObjectTypeCompare((PetscObject)A,MATSBAIJ,&isSBAIJ);
    107:   PetscObjectTypeCompare((PetscObject)A,MATSEQSBAIJ,&isSeqSBAIJ);
    108:   PetscObjectTypeCompare((PetscObject)A,MATMPISBAIJ,&isMpiSBAIJ);

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

    112:   /* PaStiX only needs triangular matrix if matrix is symmetric
    113:    */
    114:   if (isSym && !(isSBAIJ || isSeqSBAIJ || isMpiSBAIJ)) nnz = (aa->nz - *n)/2 + *n;
    115:   else nnz = aa->nz;

    117:   if (!valOnly) {
    118:     PetscMalloc1((*n)+1,colptr);
    119:     PetscMalloc1(nnz,row);
    120:     PetscMalloc1(nnz,values);

    122:     if (isSBAIJ || isSeqSBAIJ || isMpiSBAIJ) {
    123:       PetscMemcpy (*colptr, rowptr, ((*n)+1)*sizeof(PetscInt));
    124:       for (i = 0; i < *n+1; i++) (*colptr)[i] += base;
    125:       PetscMemcpy (*row, col, (nnz)*sizeof(PetscInt));
    126:       for (i = 0; i < nnz; i++) (*row)[i] += base;
    127:       PetscMemcpy (*values, rvalues, (nnz)*sizeof(PetscScalar));
    128:     } else {
    129:       PetscMalloc1(*n,&colcount);

    131:       for (i = 0; i < m; i++) colcount[i] = 0;
    132:       /* Fill-in colptr */
    133:       for (i = 0; i < m; i++) {
    134:         for (j = rowptr[i]; j < rowptr[i+1]; j++) {
    135:           if (!isSym || col[j] <= i)  colcount[col[j]]++;
    136:         }
    137:       }

    139:       (*colptr)[0] = base;
    140:       for (j = 0; j < *n; j++) {
    141:         (*colptr)[j+1] = (*colptr)[j] + colcount[j];
    142:         /* in next loop we fill starting from (*colptr)[colidx] - base */
    143:         colcount[j] = -base;
    144:       }

    146:       /* Fill-in rows and values */
    147:       for (i = 0; i < m; i++) {
    148:         for (j = rowptr[i]; j < rowptr[i+1]; j++) {
    149:           if (!isSym || col[j] <= i) {
    150:             colidx         = col[j];
    151:             idx            = (*colptr)[colidx] + colcount[colidx];
    152:             (*row)[idx]    = i + base;
    153:             (*values)[idx] = rvalues[j];
    154:             colcount[colidx]++;
    155:           }
    156:         }
    157:       }
    158:       PetscFree(colcount);
    159:     }
    160:   } else {
    161:     /* Fill-in only values */
    162:     for (i = 0; i < m; i++) {
    163:       for (j = rowptr[i]; j < rowptr[i+1]; j++) {
    164:         colidx = col[j];
    165:         if ((isSBAIJ || isSeqSBAIJ || isMpiSBAIJ) ||!isSym || col[j] <= i) {
    166:           /* look for the value to fill */
    167:           for (k = (*colptr)[colidx] - base; k < (*colptr)[colidx + 1] - base; k++) {
    168:             if (((*row)[k]-base) == i) {
    169:               (*values)[k] = rvalues[j];
    170:               break;
    171:             }
    172:           }
    173:           /* data structure of sparse matrix has changed */
    174:           if (k == (*colptr)[colidx + 1] - base) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_PLIB,"overflow on k %D",k);
    175:         }
    176:       }
    177:     }
    178:   }

    180:   icntl =-1;
    181:   check = 0;
    182:   PetscOptionsGetInt(((PetscObject) A)->prefix, "-mat_pastix_check", &icntl, &flg);
    183:   if ((flg && icntl >= 0) || PetscLogPrintInfo) check =  icntl;

    185:   if (check == 1) {
    186:     PetscScalar *tmpvalues;
    187:     PetscInt    *tmprows,*tmpcolptr;
    188:     tmpvalues = (PetscScalar*)malloc(nnz*sizeof(PetscScalar));    if (!tmpvalues) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_MEM,"Unable to allocate memory");
    189:     tmprows   = (PetscInt*)   malloc(nnz*sizeof(PetscInt));       if (!tmprows)   SETERRQ(PETSC_COMM_SELF,PETSC_ERR_MEM,"Unable to allocate memory");
    190:     tmpcolptr = (PetscInt*)   malloc((*n+1)*sizeof(PetscInt));    if (!tmpcolptr) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_MEM,"Unable to allocate memory");

    192:     PetscMemcpy(tmpcolptr,*colptr,(*n+1)*sizeof(PetscInt));
    193:     PetscMemcpy(tmprows,*row,nnz*sizeof(PetscInt));
    194:     PetscMemcpy(tmpvalues,*values,nnz*sizeof(PetscScalar));
    195:     PetscFree(*row);
    196:     PetscFree(*values);

    198:     icntl=-1;
    199:     verb = API_VERBOSE_NOT;
    200:     /* "iparm[IPARM_VERBOSE] : level of printing (0 to 2)" */
    201:     PetscOptionsGetInt(((PetscObject) A)->prefix, "-mat_pastix_verbose", &icntl, &flg);
    202:     if ((flg && icntl >= 0) || PetscLogPrintInfo) verb =  icntl;
    203:     PASTIX_CHECKMATRIX(MPI_COMM_WORLD,verb,((isSym != 0) ? API_SYM_YES : API_SYM_NO),API_YES,*n,&tmpcolptr,&tmprows,(PastixScalar**)&tmpvalues,NULL,1);

    205:     PetscMemcpy(*colptr,tmpcolptr,(*n+1)*sizeof(PetscInt));
    206:     PetscMalloc1(((*colptr)[*n]-1),row);
    207:     PetscMemcpy(*row,tmprows,((*colptr)[*n]-1)*sizeof(PetscInt));
    208:     PetscMalloc1(((*colptr)[*n]-1),values);
    209:     PetscMemcpy(*values,tmpvalues,((*colptr)[*n]-1)*sizeof(PetscScalar));
    210:     free(tmpvalues);
    211:     free(tmprows);
    212:     free(tmpcolptr);

    214:   }
    215:   return(0);
    216: }

    220: PetscErrorCode MatGetDiagonal_Pastix(Mat A,Vec v)
    221: {
    223:   SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Mat type: Pastix factor");
    224:   return(0);
    225: }

    229: /*
    230:   Call clean step of PaStiX if lu->CleanUpPastix == true.
    231:   Free the CSC matrix.
    232:  */
    233: PetscErrorCode MatDestroy_Pastix(Mat A)
    234: {
    235:   Mat_Pastix     *lu=(Mat_Pastix*)A->spptr;
    237:   PetscMPIInt    size=lu->commSize;

    240:   if (lu && lu->CleanUpPastix) {
    241:     /* Terminate instance, deallocate memories */
    242:     if (size > 1) {
    243:       VecScatterDestroy(&lu->scat_rhs);
    244:       VecDestroy(&lu->b_seq);
    245:       VecScatterDestroy(&lu->scat_sol);
    246:     }

    248:     lu->iparm[IPARM_START_TASK]=API_TASK_CLEAN;
    249:     lu->iparm[IPARM_END_TASK]  =API_TASK_CLEAN;

    251:     PASTIX_CALL(&(lu->pastix_data),
    252:                 lu->pastix_comm,
    253:                 lu->n,
    254:                 lu->colptr,
    255:                 lu->row,
    256:                 (PastixScalar*)lu->val,
    257:                 lu->perm,
    258:                 lu->invp,
    259:                 (PastixScalar*)lu->rhs,
    260:                 lu->rhsnbr,
    261:                 lu->iparm,
    262:                 lu->dparm);

    264:     PetscFree(lu->colptr);
    265:     PetscFree(lu->row);
    266:     PetscFree(lu->val);
    267:     PetscFree(lu->perm);
    268:     PetscFree(lu->invp);
    269:     MPI_Comm_free(&(lu->pastix_comm));
    270:   }
    271:   if (lu && lu->Destroy) {
    272:     (lu->Destroy)(A);
    273:   }
    274:   PetscFree(A->spptr);
    275:   return(0);
    276: }

    280: /*
    281:   Gather right-hand-side.
    282:   Call for Solve step.
    283:   Scatter solution.
    284:  */
    285: PetscErrorCode MatSolve_PaStiX(Mat A,Vec b,Vec x)
    286: {
    287:   Mat_Pastix     *lu=(Mat_Pastix*)A->spptr;
    288:   PetscScalar    *array;
    289:   Vec            x_seq;

    293:   lu->rhsnbr = 1;
    294:   x_seq      = lu->b_seq;
    295:   if (lu->commSize > 1) {
    296:     /* PaStiX only supports centralized rhs. Scatter b into a seqential rhs vector */
    297:     VecScatterBegin(lu->scat_rhs,b,x_seq,INSERT_VALUES,SCATTER_FORWARD);
    298:     VecScatterEnd(lu->scat_rhs,b,x_seq,INSERT_VALUES,SCATTER_FORWARD);
    299:     VecGetArray(x_seq,&array);
    300:   } else {  /* size == 1 */
    301:     VecCopy(b,x);
    302:     VecGetArray(x,&array);
    303:   }
    304:   lu->rhs = array;
    305:   if (lu->commSize == 1) {
    306:     VecRestoreArray(x,&array);
    307:   } else {
    308:     VecRestoreArray(x_seq,&array);
    309:   }

    311:   /* solve phase */
    312:   /*-------------*/
    313:   lu->iparm[IPARM_START_TASK] = API_TASK_SOLVE;
    314:   lu->iparm[IPARM_END_TASK]   = API_TASK_REFINE;
    315:   lu->iparm[IPARM_RHS_MAKING] = API_RHS_B;

    317:   PASTIX_CALL(&(lu->pastix_data),
    318:               lu->pastix_comm,
    319:               lu->n,
    320:               lu->colptr,
    321:               lu->row,
    322:               (PastixScalar*)lu->val,
    323:               lu->perm,
    324:               lu->invp,
    325:               (PastixScalar*)lu->rhs,
    326:               lu->rhsnbr,
    327:               lu->iparm,
    328:               lu->dparm);

    330:   if (lu->iparm[IPARM_ERROR_NUMBER] < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error reported by PaStiX in solve phase: lu->iparm[IPARM_ERROR_NUMBER] = %d\n",lu->iparm[IPARM_ERROR_NUMBER]);

    332:   if (lu->commSize == 1) {
    333:     VecRestoreArray(x,&(lu->rhs));
    334:   } else {
    335:     VecRestoreArray(x_seq,&(lu->rhs));
    336:   }

    338:   if (lu->commSize > 1) { /* convert PaStiX centralized solution to petsc mpi x */
    339:     VecScatterBegin(lu->scat_sol,x_seq,x,INSERT_VALUES,SCATTER_FORWARD);
    340:     VecScatterEnd(lu->scat_sol,x_seq,x,INSERT_VALUES,SCATTER_FORWARD);
    341:   }
    342:   return(0);
    343: }

    345: /*
    346:   Numeric factorisation using PaStiX solver.

    348:  */
    351: PetscErrorCode MatFactorNumeric_PaStiX(Mat F,Mat A,const MatFactorInfo *info)
    352: {
    353:   Mat_Pastix     *lu =(Mat_Pastix*)(F)->spptr;
    354:   Mat            *tseq;
    355:   PetscErrorCode 0;
    356:   PetscInt       icntl;
    357:   PetscInt       M=A->rmap->N;
    358:   PetscBool      valOnly,flg, isSym;
    359:   Mat            F_diag;
    360:   IS             is_iden;
    361:   Vec            b;
    362:   IS             isrow;
    363:   PetscBool      isSeqAIJ,isSeqSBAIJ,isMPIAIJ;

    366:   PetscObjectTypeCompare((PetscObject)A,MATSEQAIJ,&isSeqAIJ);
    367:   PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&isMPIAIJ);
    368:   PetscObjectTypeCompare((PetscObject)A,MATSEQSBAIJ,&isSeqSBAIJ);
    369:   if (lu->matstruc == DIFFERENT_NONZERO_PATTERN) {
    370:     (F)->ops->solve = MatSolve_PaStiX;

    372:     /* Initialize a PASTIX instance */
    373:     MPI_Comm_dup(PetscObjectComm((PetscObject)A),&(lu->pastix_comm));
    374:     MPI_Comm_rank(lu->pastix_comm, &lu->commRank);
    375:     MPI_Comm_size(lu->pastix_comm, &lu->commSize);

    377:     /* Set pastix options */
    378:     lu->iparm[IPARM_MODIFY_PARAMETER] = API_NO;
    379:     lu->iparm[IPARM_START_TASK]       = API_TASK_INIT;
    380:     lu->iparm[IPARM_END_TASK]         = API_TASK_INIT;

    382:     lu->rhsnbr = 1;

    384:     /* Call to set default pastix options */
    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:     PetscOptionsBegin(PetscObjectComm((PetscObject)A),((PetscObject)A)->prefix,"PaStiX Options","Mat");

    400:     icntl = -1;

    402:     lu->iparm[IPARM_VERBOSE] = API_VERBOSE_NOT;

    404:     PetscOptionsInt("-mat_pastix_verbose","iparm[IPARM_VERBOSE] : level of printing (0 to 2)","None",lu->iparm[IPARM_VERBOSE],&icntl,&flg);
    405:     if ((flg && icntl >= 0) || PetscLogPrintInfo) {
    406:       lu->iparm[IPARM_VERBOSE] =  icntl;
    407:     }
    408:     icntl=-1;
    409:     PetscOptionsInt("-mat_pastix_threadnbr","iparm[IPARM_THREAD_NBR] : Number of thread by MPI node","None",lu->iparm[IPARM_THREAD_NBR],&icntl,&flg);
    410:     if ((flg && icntl > 0)) {
    411:       lu->iparm[IPARM_THREAD_NBR] = icntl;
    412:     }
    413:     PetscOptionsEnd();
    414:     valOnly = PETSC_FALSE;
    415:   } else {
    416:     if (isSeqAIJ || isMPIAIJ) {
    417:       PetscFree(lu->colptr);
    418:       PetscFree(lu->row);
    419:       PetscFree(lu->val);
    420:       valOnly = PETSC_FALSE;
    421:     } else valOnly = PETSC_TRUE;
    422:   }

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

    426:   /* convert mpi A to seq mat A */
    427:   ISCreateStride(PETSC_COMM_SELF,M,0,1,&isrow);
    428:   MatGetSubMatrices(A,1,&isrow,&isrow,MAT_INITIAL_MATRIX,&tseq);
    429:   ISDestroy(&isrow);

    431:   MatConvertToCSC(*tseq,valOnly, &lu->n, &lu->colptr, &lu->row, &lu->val);
    432:   MatIsSymmetric(*tseq,0.0,&isSym);
    433:   MatDestroyMatrices(1,&tseq);

    435:   if (!lu->perm) {
    436:     PetscMalloc1(lu->n,&(lu->perm));
    437:     PetscMalloc1(lu->n,&(lu->invp));
    438:   }

    440:   if (isSym) {
    441:     /* On symmetric matrix, LLT */
    442:     lu->iparm[IPARM_SYM]           = API_SYM_YES;
    443:     lu->iparm[IPARM_FACTORIZATION] = API_FACT_LDLT;
    444:   } else {
    445:     /* On unsymmetric matrix, LU */
    446:     lu->iparm[IPARM_SYM]           = API_SYM_NO;
    447:     lu->iparm[IPARM_FACTORIZATION] = API_FACT_LU;
    448:   }

    450:   /*----------------*/
    451:   if (lu->matstruc == DIFFERENT_NONZERO_PATTERN) {
    452:     if (!(isSeqAIJ || isSeqSBAIJ)) {
    453:       /* PaStiX only supports centralized rhs. Create scatter scat_rhs for repeated use in MatSolve() */
    454:       VecCreateSeq(PETSC_COMM_SELF,A->cmap->N,&lu->b_seq);
    455:       ISCreateStride(PETSC_COMM_SELF,A->cmap->N,0,1,&is_iden);
    456:       MatCreateVecs(A,NULL,&b);
    457:       VecScatterCreate(b,is_iden,lu->b_seq,is_iden,&lu->scat_rhs);
    458:       VecScatterCreate(lu->b_seq,is_iden,b,is_iden,&lu->scat_sol);
    459:       ISDestroy(&is_iden);
    460:       VecDestroy(&b);
    461:     }
    462:     lu->iparm[IPARM_START_TASK] = API_TASK_ORDERING;
    463:     lu->iparm[IPARM_END_TASK]   = API_TASK_NUMFACT;

    465:     PASTIX_CALL(&(lu->pastix_data),
    466:                 lu->pastix_comm,
    467:                 lu->n,
    468:                 lu->colptr,
    469:                 lu->row,
    470:                 (PastixScalar*)lu->val,
    471:                 lu->perm,
    472:                 lu->invp,
    473:                 (PastixScalar*)lu->rhs,
    474:                 lu->rhsnbr,
    475:                 lu->iparm,
    476:                 lu->dparm);
    477:     if (lu->iparm[IPARM_ERROR_NUMBER] < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error reported by PaStiX in analysis phase: iparm(IPARM_ERROR_NUMBER)=%d\n",lu->iparm[IPARM_ERROR_NUMBER]);
    478:   } else {
    479:     lu->iparm[IPARM_START_TASK] = API_TASK_NUMFACT;
    480:     lu->iparm[IPARM_END_TASK]   = API_TASK_NUMFACT;
    481:     PASTIX_CALL(&(lu->pastix_data),
    482:                 lu->pastix_comm,
    483:                 lu->n,
    484:                 lu->colptr,
    485:                 lu->row,
    486:                 (PastixScalar*)lu->val,
    487:                 lu->perm,
    488:                 lu->invp,
    489:                 (PastixScalar*)lu->rhs,
    490:                 lu->rhsnbr,
    491:                 lu->iparm,
    492:                 lu->dparm);

    494:     if (lu->iparm[IPARM_ERROR_NUMBER] < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error reported by PaStiX in analysis phase: iparm(IPARM_ERROR_NUMBER)=%d\n",lu->iparm[IPARM_ERROR_NUMBER]);
    495:   }

    497:   if (lu->commSize > 1) {
    498:     if ((F)->factortype == MAT_FACTOR_LU) {
    499:       F_diag = ((Mat_MPIAIJ*)(F)->data)->A;
    500:     } else {
    501:       F_diag = ((Mat_MPISBAIJ*)(F)->data)->A;
    502:     }
    503:     F_diag->assembled = PETSC_TRUE;
    504:   }
    505:   (F)->assembled    = PETSC_TRUE;
    506:   lu->matstruc      = SAME_NONZERO_PATTERN;
    507:   lu->CleanUpPastix = PETSC_TRUE;
    508:   return(0);
    509: }

    511: /* Note the Petsc r and c permutations are ignored */
    514: PetscErrorCode MatLUFactorSymbolic_AIJPASTIX(Mat F,Mat A,IS r,IS c,const MatFactorInfo *info)
    515: {
    516:   Mat_Pastix *lu = (Mat_Pastix*)F->spptr;

    519:   lu->iparm[IPARM_FACTORIZATION] = API_FACT_LU;
    520:   lu->iparm[IPARM_SYM]           = API_SYM_YES;
    521:   lu->matstruc                   = DIFFERENT_NONZERO_PATTERN;
    522:   F->ops->lufactornumeric        = MatFactorNumeric_PaStiX;
    523:   return(0);
    524: }

    527: /* Note the Petsc r permutation is ignored */
    530: PetscErrorCode MatCholeskyFactorSymbolic_SBAIJPASTIX(Mat F,Mat A,IS r,const MatFactorInfo *info)
    531: {
    532:   Mat_Pastix *lu = (Mat_Pastix*)(F)->spptr;

    535:   lu->iparm[IPARM_FACTORIZATION]  = API_FACT_LLT;
    536:   lu->iparm[IPARM_SYM]            = API_SYM_NO;
    537:   lu->matstruc                    = DIFFERENT_NONZERO_PATTERN;
    538:   (F)->ops->choleskyfactornumeric = MatFactorNumeric_PaStiX;
    539:   return(0);
    540: }

    544: PetscErrorCode MatView_PaStiX(Mat A,PetscViewer viewer)
    545: {
    546:   PetscErrorCode    ierr;
    547:   PetscBool         iascii;
    548:   PetscViewerFormat format;

    551:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
    552:   if (iascii) {
    553:     PetscViewerGetFormat(viewer,&format);
    554:     if (format == PETSC_VIEWER_ASCII_INFO) {
    555:       Mat_Pastix *lu=(Mat_Pastix*)A->spptr;

    557:       PetscViewerASCIIPrintf(viewer,"PaStiX run parameters:\n");
    558:       PetscViewerASCIIPrintf(viewer,"  Matrix type :                      %s \n",((lu->iparm[IPARM_SYM] == API_SYM_YES) ? "Symmetric" : "Unsymmetric"));
    559:       PetscViewerASCIIPrintf(viewer,"  Level of printing (0,1,2):         %d \n",lu->iparm[IPARM_VERBOSE]);
    560:       PetscViewerASCIIPrintf(viewer,"  Number of refinements iterations : %d \n",lu->iparm[IPARM_NBITER]);
    561:       PetscPrintf(PETSC_COMM_SELF,"  Error :                        %g \n",lu->dparm[DPARM_RELATIVE_ERROR]);
    562:     }
    563:   }
    564:   return(0);
    565: }

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

    572:   Use ./configure --download-pastix --download-parmetis --download-metis --download-ptscotch  to have PETSc installed with PasTiX

    574:   Use -pc_type lu -pc_factor_mat_solver_package pastix to us this direct solver

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

    580:   Level: beginner

    582: .seealso: PCFactorSetMatSolverPackage(), MatSolverPackage

    584: M*/

    589: PetscErrorCode MatGetInfo_PaStiX(Mat A,MatInfoType flag,MatInfo *info)
    590: {
    591:   Mat_Pastix *lu =(Mat_Pastix*)A->spptr;

    594:   info->block_size        = 1.0;
    595:   info->nz_allocated      = lu->iparm[IPARM_NNZEROS];
    596:   info->nz_used           = lu->iparm[IPARM_NNZEROS];
    597:   info->nz_unneeded       = 0.0;
    598:   info->assemblies        = 0.0;
    599:   info->mallocs           = 0.0;
    600:   info->memory            = 0.0;
    601:   info->fill_ratio_given  = 0;
    602:   info->fill_ratio_needed = 0;
    603:   info->factor_mallocs    = 0;
    604:   return(0);
    605: }

    609: PetscErrorCode MatFactorGetSolverPackage_pastix(Mat A,const MatSolverPackage *type)
    610: {
    612:   *type = MATSOLVERPASTIX;
    613:   return(0);
    614: }

    616: /*
    617:     The seq and mpi versions of this function are the same
    618: */
    621: PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_pastix(Mat A,MatFactorType ftype,Mat *F)
    622: {
    623:   Mat            B;
    625:   Mat_Pastix     *pastix;

    628:   if (ftype != MAT_FACTOR_LU) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Cannot use PETSc AIJ matrices with PaStiX Cholesky, use SBAIJ matrix");
    629:   /* Create the factorization matrix */
    630:   MatCreate(PetscObjectComm((PetscObject)A),&B);
    631:   MatSetSizes(B,A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N);
    632:   MatSetType(B,((PetscObject)A)->type_name);
    633:   MatSeqAIJSetPreallocation(B,0,NULL);

    635:   B->ops->lufactorsymbolic = MatLUFactorSymbolic_AIJPASTIX;
    636:   B->ops->view             = MatView_PaStiX;
    637:   B->ops->getinfo          = MatGetInfo_PaStiX;
    638:   B->ops->getdiagonal      = MatGetDiagonal_Pastix;

    640:   PetscObjectComposeFunction((PetscObject)B,"MatFactorGetSolverPackage_C",MatFactorGetSolverPackage_pastix);

    642:   B->factortype = MAT_FACTOR_LU;

    644:   PetscNewLog(B,&pastix);

    646:   pastix->CleanUpPastix = PETSC_FALSE;
    647:   pastix->isAIJ         = PETSC_TRUE;
    648:   pastix->scat_rhs      = NULL;
    649:   pastix->scat_sol      = NULL;
    650:   pastix->Destroy       = B->ops->destroy;
    651:   B->ops->destroy       = MatDestroy_Pastix;
    652:   B->spptr              = (void*)pastix;

    654:   *F = B;
    655:   return(0);
    656: }

    660: PETSC_EXTERN PetscErrorCode MatGetFactor_mpiaij_pastix(Mat A,MatFactorType ftype,Mat *F)
    661: {
    662:   Mat            B;
    664:   Mat_Pastix     *pastix;

    667:   if (ftype != MAT_FACTOR_LU) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Cannot use PETSc AIJ matrices with PaStiX Cholesky, use SBAIJ matrix");
    668:   /* Create the factorization matrix */
    669:   MatCreate(PetscObjectComm((PetscObject)A),&B);
    670:   MatSetSizes(B,A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N);
    671:   MatSetType(B,((PetscObject)A)->type_name);
    672:   MatSeqAIJSetPreallocation(B,0,NULL);
    673:   MatMPIAIJSetPreallocation(B,0,NULL,0,NULL);

    675:   B->ops->lufactorsymbolic = MatLUFactorSymbolic_AIJPASTIX;
    676:   B->ops->view             = MatView_PaStiX;
    677:   B->ops->getdiagonal      = MatGetDiagonal_Pastix;

    679:   PetscObjectComposeFunction((PetscObject)B,"MatFactorGetSolverPackage_C",MatFactorGetSolverPackage_pastix);

    681:   B->factortype = MAT_FACTOR_LU;

    683:   PetscNewLog(B,&pastix);

    685:   pastix->CleanUpPastix = PETSC_FALSE;
    686:   pastix->isAIJ         = PETSC_TRUE;
    687:   pastix->scat_rhs      = NULL;
    688:   pastix->scat_sol      = NULL;
    689:   pastix->Destroy       = B->ops->destroy;
    690:   B->ops->destroy       = MatDestroy_Pastix;
    691:   B->spptr              = (void*)pastix;

    693:   *F = B;
    694:   return(0);
    695: }

    699: PETSC_EXTERN PetscErrorCode MatGetFactor_seqsbaij_pastix(Mat A,MatFactorType ftype,Mat *F)
    700: {
    701:   Mat            B;
    703:   Mat_Pastix     *pastix;

    706:   if (ftype != MAT_FACTOR_CHOLESKY) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Cannot use PETSc SBAIJ matrices with PaStiX LU, use AIJ matrix");
    707:   /* Create the factorization matrix */
    708:   MatCreate(PetscObjectComm((PetscObject)A),&B);
    709:   MatSetSizes(B,A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N);
    710:   MatSetType(B,((PetscObject)A)->type_name);
    711:   MatSeqSBAIJSetPreallocation(B,1,0,NULL);
    712:   MatMPISBAIJSetPreallocation(B,1,0,NULL,0,NULL);

    714:   B->ops->choleskyfactorsymbolic = MatCholeskyFactorSymbolic_SBAIJPASTIX;
    715:   B->ops->view                   = MatView_PaStiX;
    716:   B->ops->getdiagonal            = MatGetDiagonal_Pastix;

    718:   PetscObjectComposeFunction((PetscObject)B,"MatFactorGetSolverPackage_C",MatFactorGetSolverPackage_pastix);

    720:   B->factortype = MAT_FACTOR_CHOLESKY;

    722:   PetscNewLog(B,&pastix);

    724:   pastix->CleanUpPastix = PETSC_FALSE;
    725:   pastix->isAIJ         = PETSC_TRUE;
    726:   pastix->scat_rhs      = NULL;
    727:   pastix->scat_sol      = NULL;
    728:   pastix->Destroy       = B->ops->destroy;
    729:   B->ops->destroy       = MatDestroy_Pastix;
    730:   B->spptr              = (void*)pastix;

    732:   *F = B;
    733:   return(0);
    734: }

    738: PETSC_EXTERN PetscErrorCode MatGetFactor_mpisbaij_pastix(Mat A,MatFactorType ftype,Mat *F)
    739: {
    740:   Mat            B;
    742:   Mat_Pastix     *pastix;

    745:   if (ftype != MAT_FACTOR_CHOLESKY) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Cannot use PETSc SBAIJ matrices with PaStiX LU, use AIJ matrix");

    747:   /* Create the factorization matrix */
    748:   MatCreate(PetscObjectComm((PetscObject)A),&B);
    749:   MatSetSizes(B,A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N);
    750:   MatSetType(B,((PetscObject)A)->type_name);
    751:   MatSeqSBAIJSetPreallocation(B,1,0,NULL);
    752:   MatMPISBAIJSetPreallocation(B,1,0,NULL,0,NULL);

    754:   B->ops->choleskyfactorsymbolic = MatCholeskyFactorSymbolic_SBAIJPASTIX;
    755:   B->ops->view                   = MatView_PaStiX;
    756:   B->ops->getdiagonal            = MatGetDiagonal_Pastix;

    758:   PetscObjectComposeFunction((PetscObject)B,"MatFactorGetSolverPackage_C",MatFactorGetSolverPackage_pastix);

    760:   B->factortype = MAT_FACTOR_CHOLESKY;

    762:   PetscNewLog(B,&pastix);

    764:   pastix->CleanUpPastix = PETSC_FALSE;
    765:   pastix->isAIJ         = PETSC_TRUE;
    766:   pastix->scat_rhs      = NULL;
    767:   pastix->scat_sol      = NULL;
    768:   pastix->Destroy       = B->ops->destroy;
    769:   B->ops->destroy       = MatDestroy_Pastix;
    770:   B->spptr              = (void*)pastix;

    772:   *F = B;
    773:   return(0);
    774: }

    778: PETSC_EXTERN PetscErrorCode MatSolverPackageRegister_Pastix(void)
    779: {

    783:   MatSolverPackageRegister(MATSOLVERPASTIX,MATMPIAIJ,        MAT_FACTOR_LU,MatGetFactor_mpiaij_pastix);
    784:   MatSolverPackageRegister(MATSOLVERPASTIX,MATSEQAIJ,        MAT_FACTOR_LU,MatGetFactor_seqaij_pastix);
    785:   MatSolverPackageRegister(MATSOLVERPASTIX,MATMPISBAIJ,      MAT_FACTOR_CHOLESKY,MatGetFactor_mpisbaij_pastix);
    786:   MatSolverPackageRegister(MATSOLVERPASTIX,MATSEQSBAIJ,      MAT_FACTOR_CHOLESKY,MatGetFactor_seqsbaij_pastix);
    787:   return(0);
    788: }