Actual source code: dscpack.c

  1: /*$Id: dscpack.c,v 1.10 2001/08/15 15:56:50 bsmith Exp $*/
  2: /* 
  3:         Provides an interface to the DSCPACK (Domain-Separator Codes) sparse direct solver
  4: */

 6:  #include src/mat/impls/baij/seq/baij.h
 7:  #include src/mat/impls/baij/mpi/mpibaij.h

  9: #if defined(PETSC_HAVE_DSCPACK) && !defined(PETSC_USE_SINGLE) && !defined(PETSC_USE_COMPLEX)

 11: EXTERN_C_BEGIN
 12: #include "dscmain.h"
 13: EXTERN_C_END

 15: typedef struct {
 16:   DSC_Solver        My_DSC_Solver;
 17:   int           num_local_strucs, *local_struc_old_num,
 18:                 num_local_cols, num_local_nonz,
 19:                 *global_struc_new_col_num,
 20:                 *global_struc_new_num, *global_struc_owner,
 21:                 dsc_id,bs,*local_cols_old_num,*replication;
 22:   int           order_code,scheme_code,factor_type, stat,
 23:                 LBLASLevel,DBLASLevel,max_mem_allowed;
 24:   MatStructure  flg;
 25:   IS            my_cols,iden,iden_dsc;
 26:   Vec           vec_dsc;
 27:   VecScatter    scat;
 28: } Mat_MPIBAIJ_DSC;

 30: extern int MatDestroy_MPIBAIJ(Mat);
 31: extern int MatDestroy_SeqBAIJ(Mat);

 33: /* DSC function */
 34: void isort2(int size, int *list, int *index)
 35: {
 36:                 /* in increasing order */
 37:                 /* index will contain indices such that */
 38:                 /* list can be accessed in sorted order */
 39:    int i, j, x, y;

 41:    for (i=0; i<size; i++) index[i] =i;

 43:    for (i=1; i<size; i++){
 44:       y= index[i];
 45:       x=list[index[i]];
 46:       for (j=i-1; ((j>=0) && (x<list[index[j]])); j--)
 47:                 index[j+1]=index[j];
 48:       index[j+1]=y;
 49:    }
 50: }/*end isort2*/

 52: int  BAIJtoMyANonz( int *AIndex, int *AStruct, int bs,
 53:                     RealNumberType *ANonz, int NumLocalStructs, 
 54:                     int NumLocalNonz,  int *GlobalStructNewColNum,                
 55:                     int *LocalStructOldNum,
 56:                     int *LocalStructLocalNum,
 57:                     RealNumberType **adr_MyANonz)
 58: /* 
 59:    Extract non-zero values of lower triangular part
 60:    of the permuted matrix that belong to this processor.

 62:    Only output parameter is adr_MyANonz -- is malloced and changed.
 63:    Rest are input parameters left unchanged.

 65:    When LocalStructLocalNum == PETSC_NULL,
 66:         AIndex, AStruct, and ANonz contain entire original matrix A 
 67:         in PETSc SeqBAIJ format,
 68:         otherwise,
 69:         AIndex, AStruct, and ANonz are indeces for the submatrix
 70:         of A whose colomns (in increasing order) belong to this processor.

 72:    Other variables supply information on ownership of columns
 73:    and the new numbering in a fill-reducing permutation

 75:    This information is used to setup lower half of A nonzeroes
 76:    for columns owned by this processor
 77:  */
 78: {
 79:   int            i, j, k, iold,inew, jj, kk,ierr, bs2=bs*bs,
 80:                  *idx, *NewColNum,
 81:                  MyANonz_last, max_struct=0, struct_size;
 82:   RealNumberType *MyANonz;


 86:   /* loop: to find maximum number of subscripts over columns
 87:      assigned to this processor */
 88:   for (i=0; i <NumLocalStructs; i++) {
 89:     /* for each struct i (local) assigned to this processor */
 90:     if (LocalStructLocalNum){
 91:       iold = LocalStructLocalNum[i];
 92:     } else {
 93:       iold = LocalStructOldNum[i];
 94:     }
 95: 
 96:     struct_size = AIndex[iold+1] - AIndex[iold];
 97:     if ( max_struct <= struct_size) max_struct = struct_size;
 98:   }

100:   /* allocate tmp arrays large enough to hold densest struct */
101:   PetscMalloc((2*max_struct+1)*sizeof(int),&NewColNum);
102:   idx = NewColNum + max_struct;
103: 
104:   PetscMalloc(NumLocalNonz*sizeof(RealNumberType),&MyANonz);
105:   *adr_MyANonz = MyANonz;

107:   /* loop to set up nonzeroes in MyANonz */
108:   MyANonz_last = 0 ; /* points to first empty space in MyANonz */
109:   for (i=0; i <NumLocalStructs; i++) {

111:     /* for each struct i (local) assigned to this processor */
112:     if (LocalStructLocalNum){
113:       iold = LocalStructLocalNum[i];
114:     } else {
115:       iold = LocalStructOldNum[i];
116:     }

118:     struct_size = AIndex[iold+1] - AIndex[iold];
119:     for (k=0, j=AIndex[iold]; j<AIndex[iold+1]; j++){
120:       NewColNum[k] = GlobalStructNewColNum[AStruct[j]];
121:       k++;
122:     }
123:     isort2(struct_size, NewColNum, idx);
124: 
125:     kk = AIndex[iold]*bs2; /* points to 1st element of iold block col in ANonz */
126:     inew = GlobalStructNewColNum[LocalStructOldNum[i]];

128:     for (jj = 0; jj < bs; jj++) {
129:       for (j=0; j<struct_size; j++){
130:         for ( k = 0; k<bs; k++){
131:           if (NewColNum[idx[j]] + k >= inew)
132:             MyANonz[MyANonz_last++] = ANonz[kk + idx[j]*bs2 + k*bs + jj];
133:         }
134:       }
135:       inew++;
136:     }
137:   } /* end outer loop for i */

139:   PetscFree(NewColNum);
140:   if (MyANonz_last != NumLocalNonz)
141:     SETERRQ2(1,"MyANonz_last %d != NumLocalNonz %dn",MyANonz_last, NumLocalNonz);
142:   return(0);
143: }

145: int MatDestroy_MPIBAIJ_DSCPACK(Mat A)
146: {
147:   Mat_MPIBAIJ_DSC     *lu=(Mat_MPIBAIJ_DSC*)A->spptr;
148:   int                 ierr, size;
149: 
151:   MPI_Comm_size(A->comm,&size);

153:   if (lu->dsc_id != -1) {
154:     if(lu->stat) DSC_DoStats(lu->My_DSC_Solver);
155:     DSC_FreeAll(lu->My_DSC_Solver);
156:     DSC_Close0(lu->My_DSC_Solver);

158:     PetscFree(lu->local_cols_old_num);
159:   }
160:   DSC_End(lu->My_DSC_Solver);
161: 
162:   ISDestroy(lu->my_cols);
163:   PetscFree(lu->replication);
164:   VecDestroy(lu->vec_dsc);
165:   ISDestroy(lu->iden_dsc);
166:   VecScatterDestroy(lu->scat);
167: 
168:   if (size >1) ISDestroy(lu->iden);
169:   PetscFree(lu);

171:   if (size == 1){
172:     MatDestroy_SeqBAIJ(A);
173:   } else {
174:     MatDestroy_MPIBAIJ(A);
175:   }
176: 
177:   return(0);
178: }

180: int MatSolve_MPIBAIJ_DSCPACK(Mat A,Vec b,Vec x)
181: {
182:   Mat_MPIBAIJ_DSC   *lu= (Mat_MPIBAIJ_DSC*)A->spptr;
183:   int               ierr;
184:   RealNumberType    *solution_vec, *rhs_vec;

187:   /* scatter b into seq vec_dsc */
188:   if ( !lu->scat ) {
189:     VecScatterCreate(b,lu->my_cols,lu->vec_dsc,lu->iden_dsc,&lu->scat);
190:   }
191:   VecScatterBegin(b,lu->vec_dsc,INSERT_VALUES,SCATTER_FORWARD,lu->scat);
192:   VecScatterEnd(b,lu->vec_dsc,INSERT_VALUES,SCATTER_FORWARD,lu->scat);

194:   if (lu->dsc_id != -1){
195:     VecGetArray(lu->vec_dsc,&rhs_vec);
196:     DSC_InputRhsLocalVec(lu->My_DSC_Solver, rhs_vec, lu->num_local_cols);
197:     VecRestoreArray(lu->vec_dsc,&rhs_vec);
198: 
199:     DSC_Solve(lu->My_DSC_Solver);
200:     if (ierr !=  DSC_NO_ERROR) {
201:       DSC_ErrorDisplay(lu->My_DSC_Solver);
202:       SETERRQ(1,"Error in calling DSC_Solve");
203:     }

205:     /* get the permuted local solution */
206:     VecGetArray(lu->vec_dsc,&solution_vec);
207:     DSC_GetLocalSolution(lu->My_DSC_Solver,solution_vec, lu->num_local_cols);
208:     VecRestoreArray(lu->vec_dsc,&solution_vec);

210:   } /* end of if (lu->dsc_id != -1) */

212:   /* put permuted local solution solution_vec into x in the original order */
213:   VecScatterBegin(lu->vec_dsc,x,INSERT_VALUES,SCATTER_REVERSE,lu->scat);
214:   VecScatterEnd(lu->vec_dsc,x,INSERT_VALUES,SCATTER_REVERSE,lu->scat);

216:   return(0);
217: }

219: int MatCholeskyFactorNumeric_MPIBAIJ_DSCPACK(Mat A,Mat *F)
220: {
221:   Mat_SeqBAIJ       *a_seq;
222:   Mat_MPIBAIJ_DSC   *lu=(Mat_MPIBAIJ_DSC*)(*F)->spptr;
223:   Mat               *tseq,A_seq;
224:   RealNumberType    *my_a_nonz;
225:   int               ierr, M=A->M, Mbs=M/lu->bs, size,
226:                     max_mem_estimate, max_single_malloc_blk,
227:                     number_of_procs,i,j,next,iold,
228:                     *idx,*iidx,*itmp;
229:   IS                my_cols_sorted;
230: 
232:   MPI_Comm_size(A->comm,&size);
233: 
234:   if ( lu->flg == DIFFERENT_NONZERO_PATTERN){ /* first numeric factorization */

236:     /* convert A to A_seq */
237:     if (size > 1) {
238:       ISCreateStride(PETSC_COMM_SELF,M,0,1,&lu->iden);
239:       MatGetSubMatrices(A,1,&lu->iden,&lu->iden,MAT_INITIAL_MATRIX,&tseq);
240: 
241:       A_seq = *tseq;
242:       PetscFree(tseq);
243:       a_seq = (Mat_SeqBAIJ*)A_seq->data;
244:     } else {
245:       a_seq = (Mat_SeqBAIJ*)A->data;
246:     }
247: 
248:     PetscMalloc(Mbs*sizeof(int),&lu->replication);
249:     for (i=0; i<Mbs; i++) lu->replication[i] = lu->bs;

251:     number_of_procs = DSC_Analyze(Mbs, a_seq->i, a_seq->j, lu->replication);
252: 
253:     i = size;
254:     if ( number_of_procs < i ) i = number_of_procs;
255:     number_of_procs = 1;
256:     while ( i > 1 ){
257:       number_of_procs  *= 2; i /= 2;
258:     }

260:     /* DSC_Solver starts */
261:     lu->My_DSC_Solver = DSC_Begin();
262:     DSC_Open0( lu->My_DSC_Solver, number_of_procs, &lu->dsc_id, PETSC_COMM_WORLD );

264:     if (lu->dsc_id != -1) {
265:       DSC_Order(lu->My_DSC_Solver,lu->order_code,Mbs,a_seq->i,a_seq->j,lu->replication,
266:                    &M,&lu->num_local_strucs,
267:                    &lu->num_local_cols, &lu->num_local_nonz,  &lu->global_struc_new_col_num,
268:                    &lu->global_struc_new_num, &lu->global_struc_owner,
269:                    &lu->local_struc_old_num);
270:       if (ierr !=  DSC_NO_ERROR) {
271:         DSC_ErrorDisplay(lu->My_DSC_Solver);
272:         SETERRQ(1,"Error when use DSC_Order()");
273:       }

275:       DSC_SFactor(lu->My_DSC_Solver,&max_mem_estimate,&max_single_malloc_blk,
276:                      lu->max_mem_allowed, lu->LBLASLevel, lu->DBLASLevel);
277:       if (ierr !=  DSC_NO_ERROR) {
278:         DSC_ErrorDisplay(lu->My_DSC_Solver);
279:         SETERRQ(1,"Error when use DSC_Order");
280:       }

282:       BAIJtoMyANonz(a_seq->i, a_seq->j, lu->bs, a_seq->a,
283:                        lu->num_local_strucs, lu->num_local_nonz,
284:                        lu->global_struc_new_col_num,
285:                        lu->local_struc_old_num,
286:                        PETSC_NULL,
287:                        &my_a_nonz);
288:       if (ierr <0) {
289:           DSC_ErrorDisplay(lu->My_DSC_Solver);
290:           SETERRQ1(1,"Error setting local nonzeroes at processor %d n", lu->dsc_id);
291:       }

293:       /* get local_cols_old_num and IS my_cols to be used later */
294:       PetscMalloc(lu->num_local_cols*sizeof(int),&lu->local_cols_old_num);
295:       for (next = 0, i=0; i<lu->num_local_strucs; i++){
296:         iold = lu->bs*lu->local_struc_old_num[i];
297:         for (j=0; j<lu->bs; j++)
298:           lu->local_cols_old_num[next++] = iold++;
299:       }
300:       ISCreateGeneral(PETSC_COMM_SELF,lu->num_local_cols,lu->local_cols_old_num,&lu->my_cols);
301: 
302:     } else {    /* lu->dsc_id == -1 */
303:       lu->num_local_cols = 0;
304:       lu->local_cols_old_num = 0;
305:       ISCreateGeneral(PETSC_COMM_SELF,lu->num_local_cols,lu->local_cols_old_num,&lu->my_cols);
306:     }
307:     /* generate vec_dsc and iden_dsc to be used later */
308:     VecCreateSeq(PETSC_COMM_SELF,lu->num_local_cols,&lu->vec_dsc);
309:     ISCreateStride(PETSC_COMM_SELF,lu->num_local_cols,0,1,&lu->iden_dsc);
310:     lu->scat = PETSC_NULL;

312:     if ( size>1 ) {MatDestroy(A_seq); }

314:   } else { /* use previously computed symbolic factor */
315:     /* convert A to my A_seq */
316:     if (size > 1) {
317:       if (lu->dsc_id == -1) {
318:         itmp = 0;
319:       } else {
320:         PetscMalloc(2*lu->num_local_strucs*sizeof(int),&idx);
321:         iidx = idx + lu->num_local_strucs;
322:         PetscMalloc(lu->num_local_cols*sizeof(int),&itmp);
323: 
324:         isort2(lu->num_local_strucs, lu->local_struc_old_num, idx);
325:         for (next=0, i=0; i< lu->num_local_strucs; i++) {
326:           iold = lu->bs*lu->local_struc_old_num[idx[i]];
327:           for (j=0; j<lu->bs; j++){
328:             itmp[next++] = iold++; /* sorted local_cols_old_num */
329:           }
330:         }
331:         for (i=0; i< lu->num_local_strucs; i++) {
332:           iidx[idx[i]] = i;       /* inverse of idx */
333:         }
334:       } /* end of (lu->dsc_id == -1) */
335:       ISCreateGeneral(PETSC_COMM_SELF,lu->num_local_cols,itmp,&my_cols_sorted);
336:       MatGetSubMatrices(A,1,&my_cols_sorted,&lu->iden,MAT_INITIAL_MATRIX,&tseq);
337:       ISDestroy(my_cols_sorted);
338: 
339:       A_seq = *tseq;
340:       PetscFree(tseq);
341: 
342:       if (lu->dsc_id != -1) {
343:         DSC_ReFactorInitialize(lu->My_DSC_Solver);

345:         a_seq = (Mat_SeqBAIJ*)A_seq->data;
346:         BAIJtoMyANonz(a_seq->i, a_seq->j, lu->bs, a_seq->a,
347:                        lu->num_local_strucs, lu->num_local_nonz,
348:                        lu->global_struc_new_col_num,
349:                        lu->local_struc_old_num,
350:                        iidx,
351:                        &my_a_nonz);
352:         if (ierr <0) {
353:           DSC_ErrorDisplay(lu->My_DSC_Solver);
354:           SETERRQ1(1,"Error setting local nonzeroes at processor %d n", lu->dsc_id);
355:         }
356: 
357:         PetscFree(idx);
358:         PetscFree(itmp);
359:       } /* end of if(lu->dsc_id != -1)  */
360:     } else { /* size == 1 */
361:       a_seq = (Mat_SeqBAIJ*)A->data;
362: 
363:       BAIJtoMyANonz(a_seq->i, a_seq->j, lu->bs, a_seq->a,
364:                        lu->num_local_strucs, lu->num_local_nonz,
365:                        lu->global_struc_new_col_num,
366:                        lu->local_struc_old_num,
367:                        PETSC_NULL,
368:                        &my_a_nonz);
369:       if (ierr <0) {
370:         DSC_ErrorDisplay(lu->My_DSC_Solver);
371:         SETERRQ1(1,"Error setting local nonzeroes at processor %d n", lu->dsc_id);
372:       }
373:     }
374:     if ( size>1 ) {MatDestroy(A_seq); }
375:   }
376: 
377:   if (lu->dsc_id != -1) {
378:     DSC_NFactor(lu->My_DSC_Solver, lu->scheme_code, my_a_nonz, lu->factor_type, lu->LBLASLevel, lu->DBLASLevel);
379:     PetscFree(my_a_nonz);
380:   }
381: 
382:   (*F)->assembled = PETSC_TRUE;
383:   lu->flg         = SAME_NONZERO_PATTERN;

385:   return(0);
386: }

388: /* Note the Petsc permutation r is ignored */
389: int MatCholeskyFactorSymbolic_MPIBAIJ_DSCPACK(Mat A,IS r,PetscReal f,Mat *F)
390: {
391:   Mat_MPIBAIJ_DSC         *lu;
392:   int                     ierr,M=A->M,size;
393:   PetscTruth              flg;
394:   char                    buff[32], *ftype[] = {"LLT","LDLT"},
395:                           *ltype[] = {"LBLAS1","LBLAS2","LBLAS3"},
396:                           *dtype[] = {"DBLAS1","DBLAS2"};

399:   PetscNew(Mat_MPIBAIJ_DSC,&lu);

401:   /* Create the factorization matrix F */
402:   MatGetBlockSize(A,&lu->bs);
403:   MatCreateMPIBAIJ(A->comm,lu->bs,PETSC_DECIDE,PETSC_DECIDE,M,M,0,PETSC_NULL,0,PETSC_NULL,F);
404: 
405:   (*F)->spptr                       = (Mat_MPIBAIJ_DSC*)lu;
406:   (*F)->ops->choleskyfactornumeric  = MatCholeskyFactorNumeric_MPIBAIJ_DSCPACK;
407:   (*F)->ops->solve                  = MatSolve_MPIBAIJ_DSCPACK;
408:   (*F)->ops->destroy                = MatDestroy_MPIBAIJ_DSCPACK;
409:   (*F)->factor                      = FACTOR_CHOLESKY;

411:   /* Set the default input options */
412:   lu->order_code  = 2;
413:   lu->scheme_code = 1;
414:   lu->factor_type = 1;
415:   lu->stat        = 0; /* do not display stats */
416:   lu->LBLASLevel  = DSC_LBLAS3;
417:   lu->DBLASLevel  = DSC_DBLAS2;
418:   lu->max_mem_allowed = 256;

420:   /* Get the runtime input options */
421:   PetscOptionsBegin(A->comm,A->prefix,"DSCPACK Options","Mat");

423:   PetscOptionsInt("-mat_dscpack_order","order_code: n
424:          1 = ND, 2 = Hybrid with Minimum Degree, 3 = Hybrid with Minimum Deficiency", 425:          "None",
426:          lu->order_code,&lu->order_code,PETSC_NULL);

428:   PetscOptionsInt("-mat_dscpack_scheme","scheme_code: n
429:          1 = standard factorization,  2 = factorization + selective inversion", 430:          "None",
431:          lu->scheme_code,&lu->scheme_code,PETSC_NULL);
432: 
433:   PetscOptionsEList("-mat_dscpack_factor","factor_type","None",
434:              ftype,2,ftype[0],buff,32,&flg);
435:   while (flg) {
436:     PetscStrcmp(buff,"LLT",&flg);
437:     if (flg) {
438:       lu->factor_type = DSC_LLT;
439:       break;
440:     }
441:     PetscStrcmp(buff,"LDLT",&flg);
442:     if (flg) {
443:       lu->factor_type = DSC_LDLT;
444:       break;
445:     }
446:     SETERRQ1(1,"Unknown factor type %s",buff);
447:   }
448:   PetscOptionsInt("-mat_dscpack_MaxMemAllowed","", 449:          "None",
450:          lu->max_mem_allowed,&lu->max_mem_allowed,PETSC_NULL);

452:   PetscOptionsInt("-mat_dscpack_stats","display stats: 0 = no display,  1 = display",
453:          "None", lu->stat,&lu->stat,PETSC_NULL);
454: 
455:   PetscOptionsEList("-mat_dscpack_LBLAS","BLAS level used in the local phase","None",
456:              ltype,3,ltype[2],buff,32,&flg);
457:   while (flg) {
458:     PetscStrcmp(buff,"LBLAS1",&flg);
459:     if (flg) {
460:       lu->LBLASLevel = DSC_LBLAS1;
461:       break;
462:     }
463:     PetscStrcmp(buff,"LBLAS2",&flg);
464:     if (flg) {
465:       lu->LBLASLevel = DSC_LBLAS2;
466:       break;
467:     }
468:     PetscStrcmp(buff,"LBLAS3",&flg);
469:     if (flg) {
470:       lu->LBLASLevel = DSC_LBLAS3;
471:       break;
472:     }
473:     SETERRQ1(1,"Unknown local phase BLAS level %s",buff);
474:   }

476:   PetscOptionsEList("-mat_dscpack_DBLAS","BLAS level used in the distributed phase","None",
477:              dtype,2,dtype[1],buff,32,&flg);
478:   while (flg) {
479:     PetscStrcmp(buff,"DBLAS1",&flg);
480:     if (flg) {
481:       lu->DBLASLevel = DSC_DBLAS1;
482:       break;
483:     }
484:     PetscStrcmp(buff,"DBLAS2",&flg);
485:     if (flg) {
486:       lu->DBLASLevel = DSC_DBLAS2;
487:       break;
488:     }
489:     SETERRQ1(1,"Unknown distributed phase BLAS level %s",buff);
490:   }

492:   PetscOptionsEnd();
493: 
494:   lu->flg = DIFFERENT_NONZERO_PATTERN;
495:   return(0);
496: }

498: int MatUseDSCPACK_MPIBAIJ(Mat A)
499: {
501:   A->ops->choleskyfactorsymbolic = MatCholeskyFactorSymbolic_MPIBAIJ_DSCPACK;
502:   return(0);
503: }

505: int MatMPIBAIJFactorInfo_DSCPACK(Mat A,PetscViewer viewer)
506: {
507:   Mat_MPIBAIJ_DSC         *lu=(Mat_MPIBAIJ_DSC*)A->spptr;
508:   int                     ierr;
509:   char                    *s;
510: 
512:   /* check if matrix is dscpack type */
513:   if (A->ops->solve != MatSolve_MPIBAIJ_DSCPACK) return(0);

515:   PetscViewerASCIIPrintf(viewer,"DSCPACK run parameters:n");

517:   switch (lu->order_code) {
518:   case 1: s = "ND"; break;
519:   case 2: s = "Hybrid with Minimum Degree"; break;
520:   case 3: s = "Hybrid with Minimum Deficiency"; break;
521:   }
522:   PetscViewerASCIIPrintf(viewer,"  order_code: %s n",s);

524:   switch (lu->scheme_code) {
525:   case 1: s = "standard factorization"; break;
526:   case 2: s = "factorization + selective inversion"; break;
527:   }
528:   PetscViewerASCIIPrintf(viewer,"  scheme_code: %s n",s);

530:   switch (lu->stat) {
531:   case 0: s = "NO"; break;
532:   case 1: s = "YES"; break;
533:   }
534:   PetscViewerASCIIPrintf(viewer,"  display stats: %s n",s);
535: 
536:   if ( lu->factor_type == DSC_LLT) {
537:     s = "LLT";
538:   } else if ( lu->factor_type == DSC_LDLT){
539:     s = "LDLT";
540:   } else {
541:     SETERRQ(1,"Unknown factor type");
542:   }
543:   PetscViewerASCIIPrintf(viewer,"  factor type: %s n",s);

545:   if ( lu->LBLASLevel == DSC_LBLAS1) {
546:     s = "BLAS1";
547:   } else if ( lu->LBLASLevel == DSC_LBLAS2){
548:     s = "BLAS2";
549:   } else if ( lu->LBLASLevel == DSC_LBLAS3){
550:     s = "BLAS3";
551:   } else {
552:     SETERRQ(1,"Unknown local phase BLAS level");
553:   }
554:   PetscViewerASCIIPrintf(viewer,"  local phase BLAS level: %s n",s);

556:   if ( lu->DBLASLevel == DSC_DBLAS1) {
557:     s = "BLAS1";
558:   } else if ( lu->DBLASLevel == DSC_DBLAS2){
559:     s = "BLAS2";
560:   } else {
561:     SETERRQ(1,"Unknown distributed phase BLAS level");
562:   }
563:   PetscViewerASCIIPrintf(viewer,"  distributed phase BLAS level: %s n",s);
564:   return(0);
565: }

567: #else

569: int MatUseDSCPACK_MPIBAIJ(Mat A)
570: {
572:   return(0);
573: }

575: #endif