Actual source code: ispai.c

petsc-dev 2014-08-28
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  2: /*
  3:    3/99 Modified by Stephen Barnard to support SPAI version 3.0
  4: */

  6: /*
  7:       Provides an interface to the SPAI Sparse Approximate Inverse Preconditioner
  8:    Code written by Stephen Barnard.

 10:       Note: there is some BAD memory bleeding below!

 12:       This code needs work

 14:    1) get rid of all memory bleeding
 15:    2) fix PETSc/interface so that it gets if the matrix is symmetric from the matrix
 16:       rather than having the sp flag for PC_SPAI
 17:    3) fix to set the block size based on the matrix block size

 19: */
 20: #define PETSC_SKIP_COMPLEX /* since spai uses I which conflicts with some complex implementations */

 22: #include <petsc-private/pcimpl.h>        /*I "petscpc.h" I*/
 23: #include <../src/ksp/pc/impls/spai/petscspai.h>

 25: /*
 26:     These are the SPAI include files
 27: */
 28: EXTERN_C_BEGIN
 29: #define SPAI_USE_MPI /* required for setting SPAI_Comm correctly in basics.h */
 30: #include <spai.h>
 31: #include <matrix.h>
 32: EXTERN_C_END

 34: extern PetscErrorCode ConvertMatToMatrix(MPI_Comm,Mat,Mat,matrix**);
 35: extern PetscErrorCode ConvertMatrixToMat(MPI_Comm,matrix*,Mat*);
 36: extern PetscErrorCode ConvertVectorToVec(MPI_Comm,vector *v,Vec *Pv);
 37: extern PetscErrorCode MM_to_PETSC(char*,char*,char*);

 39: typedef struct {

 41:   matrix *B;                /* matrix in SPAI format */
 42:   matrix *BT;               /* transpose of matrix in SPAI format */
 43:   matrix *M;                /* the approximate inverse in SPAI format */

 45:   Mat PM;                   /* the approximate inverse PETSc format */

 47:   double epsilon;           /* tolerance */
 48:   int    nbsteps;           /* max number of "improvement" steps per line */
 49:   int    max;               /* max dimensions of is_I, q, etc. */
 50:   int    maxnew;            /* max number of new entries per step */
 51:   int    block_size;        /* constant block size */
 52:   int    cache_size;        /* one of (1,2,3,4,5,6) indicting size of cache */
 53:   int    verbose;           /* SPAI prints timing and statistics */

 55:   int      sp;              /* symmetric nonzero pattern */
 56:   MPI_Comm comm_spai;     /* communicator to be used with spai */
 57: } PC_SPAI;

 59: /**********************************************************************/

 63: static PetscErrorCode PCSetUp_SPAI(PC pc)
 64: {
 65:   PC_SPAI        *ispai = (PC_SPAI*)pc->data;
 67:   Mat            AT;

 70:   init_SPAI();

 72:   if (ispai->sp) {
 73:     ConvertMatToMatrix(ispai->comm_spai,pc->pmat,pc->pmat,&ispai->B);
 74:   } else {
 75:     /* Use the transpose to get the column nonzero structure. */
 76:     MatTranspose(pc->pmat,MAT_INITIAL_MATRIX,&AT);
 77:     ConvertMatToMatrix(ispai->comm_spai,pc->pmat,AT,&ispai->B);
 78:     MatDestroy(&AT);
 79:   }

 81:   /* Destroy the transpose */
 82:   /* Don't know how to do it. PETSc developers? */

 84:   /* construct SPAI preconditioner */
 85:   /* FILE *messages */     /* file for warning messages */
 86:   /* double epsilon */     /* tolerance */
 87:   /* int nbsteps */        /* max number of "improvement" steps per line */
 88:   /* int max */            /* max dimensions of is_I, q, etc. */
 89:   /* int maxnew */         /* max number of new entries per step */
 90:   /* int block_size */     /* block_size == 1 specifies scalar elments
 91:                               block_size == n specifies nxn constant-block elements
 92:                               block_size == 0 specifies variable-block elements */
 93:   /* int cache_size */     /* one of (1,2,3,4,5,6) indicting size of cache. cache_size == 0 indicates no caching */
 94:   /* int    verbose    */  /* verbose == 0 specifies that SPAI is silent
 95:                               verbose == 1 prints timing and matrix statistics */

 97:   bspai(ispai->B,&ispai->M,
 98:                stdout,
 99:                ispai->epsilon,
100:                ispai->nbsteps,
101:                ispai->max,
102:                ispai->maxnew,
103:                ispai->block_size,
104:                ispai->cache_size,
105:                ispai->verbose);

107:   ConvertMatrixToMat(PetscObjectComm((PetscObject)pc),ispai->M,&ispai->PM);

109:   /* free the SPAI matrices */
110:   sp_free_matrix(ispai->B);
111:   sp_free_matrix(ispai->M);
112:   return(0);
113: }

115: /**********************************************************************/

119: static PetscErrorCode PCApply_SPAI(PC pc,Vec xx,Vec y)
120: {
121:   PC_SPAI        *ispai = (PC_SPAI*)pc->data;

125:   /* Now using PETSc's multiply */
126:   MatMult(ispai->PM,xx,y);
127:   return(0);
128: }

130: /**********************************************************************/

134: static PetscErrorCode PCDestroy_SPAI(PC pc)
135: {
137:   PC_SPAI        *ispai = (PC_SPAI*)pc->data;

140:   MatDestroy(&ispai->PM);
141:   MPI_Comm_free(&(ispai->comm_spai));
142:   PetscFree(pc->data);
143:   return(0);
144: }

146: /**********************************************************************/

150: static PetscErrorCode PCView_SPAI(PC pc,PetscViewer viewer)
151: {
152:   PC_SPAI        *ispai = (PC_SPAI*)pc->data;
154:   PetscBool      iascii;

157:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
158:   if (iascii) {
159:     PetscViewerASCIIPrintf(viewer,"    SPAI preconditioner\n");
160:     PetscViewerASCIIPrintf(viewer,"    epsilon %g\n",   (double)ispai->epsilon);
161:     PetscViewerASCIIPrintf(viewer,"    nbsteps %d\n",   ispai->nbsteps);
162:     PetscViewerASCIIPrintf(viewer,"    max %d\n",       ispai->max);
163:     PetscViewerASCIIPrintf(viewer,"    maxnew %d\n",    ispai->maxnew);
164:     PetscViewerASCIIPrintf(viewer,"    block_size %d\n",ispai->block_size);
165:     PetscViewerASCIIPrintf(viewer,"    cache_size %d\n",ispai->cache_size);
166:     PetscViewerASCIIPrintf(viewer,"    verbose %d\n",   ispai->verbose);
167:     PetscViewerASCIIPrintf(viewer,"    sp %d\n",        ispai->sp);
168:   }
169:   return(0);
170: }

174: static PetscErrorCode  PCSPAISetEpsilon_SPAI(PC pc,double epsilon1)
175: {
176:   PC_SPAI *ispai = (PC_SPAI*)pc->data;

179:   ispai->epsilon = epsilon1;
180:   return(0);
181: }

183: /**********************************************************************/

187: static PetscErrorCode  PCSPAISetNBSteps_SPAI(PC pc,int nbsteps1)
188: {
189:   PC_SPAI *ispai = (PC_SPAI*)pc->data;

192:   ispai->nbsteps = nbsteps1;
193:   return(0);
194: }

196: /**********************************************************************/

198: /* added 1/7/99 g.h. */
201: static PetscErrorCode  PCSPAISetMax_SPAI(PC pc,int max1)
202: {
203:   PC_SPAI *ispai = (PC_SPAI*)pc->data;

206:   ispai->max = max1;
207:   return(0);
208: }

210: /**********************************************************************/

214: static PetscErrorCode  PCSPAISetMaxNew_SPAI(PC pc,int maxnew1)
215: {
216:   PC_SPAI *ispai = (PC_SPAI*)pc->data;

219:   ispai->maxnew = maxnew1;
220:   return(0);
221: }

223: /**********************************************************************/

227: static PetscErrorCode  PCSPAISetBlockSize_SPAI(PC pc,int block_size1)
228: {
229:   PC_SPAI *ispai = (PC_SPAI*)pc->data;

232:   ispai->block_size = block_size1;
233:   return(0);
234: }

236: /**********************************************************************/

240: static PetscErrorCode  PCSPAISetCacheSize_SPAI(PC pc,int cache_size)
241: {
242:   PC_SPAI *ispai = (PC_SPAI*)pc->data;

245:   ispai->cache_size = cache_size;
246:   return(0);
247: }

249: /**********************************************************************/

253: static PetscErrorCode  PCSPAISetVerbose_SPAI(PC pc,int verbose)
254: {
255:   PC_SPAI *ispai = (PC_SPAI*)pc->data;

258:   ispai->verbose = verbose;
259:   return(0);
260: }

262: /**********************************************************************/

266: static PetscErrorCode  PCSPAISetSp_SPAI(PC pc,int sp)
267: {
268:   PC_SPAI *ispai = (PC_SPAI*)pc->data;

271:   ispai->sp = sp;
272:   return(0);
273: }

275: /* -------------------------------------------------------------------*/

279: /*@
280:   PCSPAISetEpsilon -- Set the tolerance for the SPAI preconditioner

282:   Input Parameters:
283: + pc - the preconditioner
284: - eps - epsilon (default .4)

286:   Notes:  Espilon must be between 0 and 1. It controls the
287:                  quality of the approximation of M to the inverse of
288:                  A. Higher values of epsilon lead to more work, more
289:                  fill, and usually better preconditioners. In many
290:                  cases the best choice of epsilon is the one that
291:                  divides the total solution time equally between the
292:                  preconditioner and the solver.

294:   Level: intermediate

296: .seealso: PCSPAI, PCSetType()
297:   @*/
298: PetscErrorCode  PCSPAISetEpsilon(PC pc,double epsilon1)
299: {

303:   PetscTryMethod(pc,"PCSPAISetEpsilon_C",(PC,double),(pc,epsilon1));
304:   return(0);
305: }

307: /**********************************************************************/

311: /*@
312:   PCSPAISetNBSteps - set maximum number of improvement steps per row in
313:         the SPAI preconditioner

315:   Input Parameters:
316: + pc - the preconditioner
317: - n - number of steps (default 5)

319:   Notes:  SPAI constructs to approximation to every column of
320:                  the exact inverse of A in a series of improvement
321:                  steps. The quality of the approximation is determined
322:                  by epsilon. If an approximation achieving an accuracy
323:                  of epsilon is not obtained after ns steps, SPAI simply
324:                  uses the best approximation constructed so far.

326:   Level: intermediate

328: .seealso: PCSPAI, PCSetType(), PCSPAISetMaxNew()
329: @*/
330: PetscErrorCode  PCSPAISetNBSteps(PC pc,int nbsteps1)
331: {

335:   PetscTryMethod(pc,"PCSPAISetNBSteps_C",(PC,int),(pc,nbsteps1));
336:   return(0);
337: }

339: /**********************************************************************/

341: /* added 1/7/99 g.h. */
344: /*@
345:   PCSPAISetMax - set the size of various working buffers in
346:         the SPAI preconditioner

348:   Input Parameters:
349: + pc - the preconditioner
350: - n - size (default is 5000)

352:   Level: intermediate

354: .seealso: PCSPAI, PCSetType()
355: @*/
356: PetscErrorCode  PCSPAISetMax(PC pc,int max1)
357: {

361:   PetscTryMethod(pc,"PCSPAISetMax_C",(PC,int),(pc,max1));
362:   return(0);
363: }

365: /**********************************************************************/

369: /*@
370:   PCSPAISetMaxNew - set maximum number of new nonzero candidates per step
371:    in SPAI preconditioner

373:   Input Parameters:
374: + pc - the preconditioner
375: - n - maximum number (default 5)

377:   Level: intermediate

379: .seealso: PCSPAI, PCSetType(), PCSPAISetNBSteps()
380: @*/
381: PetscErrorCode  PCSPAISetMaxNew(PC pc,int maxnew1)
382: {

386:   PetscTryMethod(pc,"PCSPAISetMaxNew_C",(PC,int),(pc,maxnew1));
387:   return(0);
388: }

390: /**********************************************************************/

394: /*@
395:   PCSPAISetBlockSize - set the block size for the SPAI preconditioner

397:   Input Parameters:
398: + pc - the preconditioner
399: - n - block size (default 1)

401:   Notes: A block
402:                  size of 1 treats A as a matrix of scalar elements. A
403:                  block size of s > 1 treats A as a matrix of sxs
404:                  blocks. A block size of 0 treats A as a matrix with
405:                  variable sized blocks, which are determined by
406:                  searching for dense square diagonal blocks in A.
407:                  This can be very effective for finite-element
408:                  matrices.

410:                  SPAI will convert A to block form, use a block
411:                  version of the preconditioner algorithm, and then
412:                  convert the result back to scalar form.

414:                  In many cases the a block-size parameter other than 1
415:                  can lead to very significant improvement in
416:                  performance.


419:   Level: intermediate

421: .seealso: PCSPAI, PCSetType()
422: @*/
423: PetscErrorCode  PCSPAISetBlockSize(PC pc,int block_size1)
424: {

428:   PetscTryMethod(pc,"PCSPAISetBlockSize_C",(PC,int),(pc,block_size1));
429:   return(0);
430: }

432: /**********************************************************************/

436: /*@
437:   PCSPAISetCacheSize - specify cache size in the SPAI preconditioner

439:   Input Parameters:
440: + pc - the preconditioner
441: - n -  cache size {0,1,2,3,4,5} (default 5)

443:   Notes:    SPAI uses a hash table to cache messages and avoid
444:                  redundant communication. If suggest always using
445:                  5. This parameter is irrelevant in the serial
446:                  version.

448:   Level: intermediate

450: .seealso: PCSPAI, PCSetType()
451: @*/
452: PetscErrorCode  PCSPAISetCacheSize(PC pc,int cache_size)
453: {

457:   PetscTryMethod(pc,"PCSPAISetCacheSize_C",(PC,int),(pc,cache_size));
458:   return(0);
459: }

461: /**********************************************************************/

465: /*@
466:   PCSPAISetVerbose - verbosity level for the SPAI preconditioner

468:   Input Parameters:
469: + pc - the preconditioner
470: - n - level (default 1)

472:   Notes: print parameters, timings and matrix statistics

474:   Level: intermediate

476: .seealso: PCSPAI, PCSetType()
477: @*/
478: PetscErrorCode  PCSPAISetVerbose(PC pc,int verbose)
479: {

483:   PetscTryMethod(pc,"PCSPAISetVerbose_C",(PC,int),(pc,verbose));
484:   return(0);
485: }

487: /**********************************************************************/

491: /*@
492:   PCSPAISetSp - specify a symmetric matrix sparsity pattern in the SPAI preconditioner

494:   Input Parameters:
495: + pc - the preconditioner
496: - n - 0 or 1

498:   Notes: If A has a symmetric nonzero pattern use -sp 1 to
499:                  improve performance by eliminating some communication
500:                  in the parallel version. Even if A does not have a
501:                  symmetric nonzero pattern -sp 1 may well lead to good
502:                  results, but the code will not follow the published
503:                  SPAI algorithm exactly.


506:   Level: intermediate

508: .seealso: PCSPAI, PCSetType()
509: @*/
510: PetscErrorCode  PCSPAISetSp(PC pc,int sp)
511: {

515:   PetscTryMethod(pc,"PCSPAISetSp_C",(PC,int),(pc,sp));
516:   return(0);
517: }

519: /**********************************************************************/

521: /**********************************************************************/

525: static PetscErrorCode PCSetFromOptions_SPAI(PC pc)
526: {
527:   PC_SPAI        *ispai = (PC_SPAI*)pc->data;
529:   int            nbsteps1,max1,maxnew1,block_size1,cache_size,verbose,sp;
530:   double         epsilon1;
531:   PetscBool      flg;

534:   PetscOptionsHead("SPAI options");
535:   PetscOptionsReal("-pc_spai_epsilon","","PCSPAISetEpsilon",ispai->epsilon,&epsilon1,&flg);
536:   if (flg) {
537:     PCSPAISetEpsilon(pc,epsilon1);
538:   }
539:   PetscOptionsInt("-pc_spai_nbsteps","","PCSPAISetNBSteps",ispai->nbsteps,&nbsteps1,&flg);
540:   if (flg) {
541:     PCSPAISetNBSteps(pc,nbsteps1);
542:   }
543:   /* added 1/7/99 g.h. */
544:   PetscOptionsInt("-pc_spai_max","","PCSPAISetMax",ispai->max,&max1,&flg);
545:   if (flg) {
546:     PCSPAISetMax(pc,max1);
547:   }
548:   PetscOptionsInt("-pc_spai_maxnew","","PCSPAISetMaxNew",ispai->maxnew,&maxnew1,&flg);
549:   if (flg) {
550:     PCSPAISetMaxNew(pc,maxnew1);
551:   }
552:   PetscOptionsInt("-pc_spai_block_size","","PCSPAISetBlockSize",ispai->block_size,&block_size1,&flg);
553:   if (flg) {
554:     PCSPAISetBlockSize(pc,block_size1);
555:   }
556:   PetscOptionsInt("-pc_spai_cache_size","","PCSPAISetCacheSize",ispai->cache_size,&cache_size,&flg);
557:   if (flg) {
558:     PCSPAISetCacheSize(pc,cache_size);
559:   }
560:   PetscOptionsInt("-pc_spai_verbose","","PCSPAISetVerbose",ispai->verbose,&verbose,&flg);
561:   if (flg) {
562:     PCSPAISetVerbose(pc,verbose);
563:   }
564:   PetscOptionsInt("-pc_spai_sp","","PCSPAISetSp",ispai->sp,&sp,&flg);
565:   if (flg) {
566:     PCSPAISetSp(pc,sp);
567:   }
568:   PetscOptionsTail();
569:   return(0);
570: }

572: /**********************************************************************/

574: /*MC
575:    PCSPAI - Use the Sparse Approximate Inverse method of Grote and Barnard
576:      as a preconditioner (SIAM J. Sci. Comput.; vol 18, nr 3)

578:    Options Database Keys:
579: +  -pc_spai_epsilon <eps> - set tolerance
580: .  -pc_spai_nbstep <n> - set nbsteps
581: .  -pc_spai_max <m> - set max
582: .  -pc_spai_max_new <m> - set maxnew
583: .  -pc_spai_block_size <n> - set block size
584: .  -pc_spai_cache_size <n> - set cache size
585: .  -pc_spai_sp <m> - set sp
586: -  -pc_spai_set_verbose <true,false> - verbose output

588:    Notes: This only works with AIJ matrices.

590:    Level: beginner

592:    Concepts: approximate inverse

594: .seealso:  PCCreate(), PCSetType(), PCType (for list of available types), PC,
595:     PCSPAISetEpsilon(), PCSPAISetMax(), PCSPAISetMaxNew(), PCSPAISetBlockSize(),
596:     PCSPAISetVerbose(), PCSPAISetSp()
597: M*/

601: PETSC_EXTERN PetscErrorCode PCCreate_SPAI(PC pc)
602: {
603:   PC_SPAI        *ispai;

607:   PetscNewLog(pc,&ispai);
608:   pc->data = ispai;

610:   pc->ops->destroy         = PCDestroy_SPAI;
611:   pc->ops->apply           = PCApply_SPAI;
612:   pc->ops->applyrichardson = 0;
613:   pc->ops->setup           = PCSetUp_SPAI;
614:   pc->ops->view            = PCView_SPAI;
615:   pc->ops->setfromoptions  = PCSetFromOptions_SPAI;

617:   ispai->epsilon    = .4;
618:   ispai->nbsteps    = 5;
619:   ispai->max        = 5000;
620:   ispai->maxnew     = 5;
621:   ispai->block_size = 1;
622:   ispai->cache_size = 5;
623:   ispai->verbose    = 0;

625:   ispai->sp = 1;
626:   MPI_Comm_dup(PetscObjectComm((PetscObject)pc),&(ispai->comm_spai));

628:   PetscObjectComposeFunction((PetscObject)pc,"PCSPAISetEpsilon_C",PCSPAISetEpsilon_SPAI);
629:   PetscObjectComposeFunction((PetscObject)pc,"PCSPAISetNBSteps_C",PCSPAISetNBSteps_SPAI);
630:   PetscObjectComposeFunction((PetscObject)pc,"PCSPAISetMax_C",PCSPAISetMax_SPAI);
631:   PetscObjectComposeFunction((PetscObject)pc,"PCSPAISetMaxNew_C",PCSPAISetMaxNew_SPAI);
632:   PetscObjectComposeFunction((PetscObject)pc,"PCSPAISetBlockSize_C",PCSPAISetBlockSize_SPAI);
633:   PetscObjectComposeFunction((PetscObject)pc,"PCSPAISetCacheSize_C",PCSPAISetCacheSize_SPAI);
634:   PetscObjectComposeFunction((PetscObject)pc,"PCSPAISetVerbose_C",PCSPAISetVerbose_SPAI);
635:   PetscObjectComposeFunction((PetscObject)pc,"PCSPAISetSp_C",PCSPAISetSp_SPAI);
636:   return(0);
637: }

639: /**********************************************************************/

641: /*
642:    Converts from a PETSc matrix to an SPAI matrix
643: */
646: PetscErrorCode ConvertMatToMatrix(MPI_Comm comm, Mat A,Mat AT,matrix **B)
647: {
648:   matrix                  *M;
649:   int                     i,j,col;
650:   int                     row_indx;
651:   int                     len,pe,local_indx,start_indx;
652:   int                     *mapping;
653:   PetscErrorCode          ierr;
654:   const int               *cols;
655:   const double            *vals;
656:   int                     n,mnl,nnl,nz,rstart,rend;
657:   PetscMPIInt             size,rank;
658:   struct compressed_lines *rows;

661:   MPI_Comm_size(comm,&size);
662:   MPI_Comm_rank(comm,&rank);
663:   MatGetSize(A,&n,&n);
664:   MatGetLocalSize(A,&mnl,&nnl);

666:   /*
667:     not sure why a barrier is required. commenting out
668:   MPI_Barrier(comm);
669:   */

671:   M = new_matrix((SPAI_Comm)comm);

673:   M->n              = n;
674:   M->bs             = 1;
675:   M->max_block_size = 1;

677:   M->mnls          = (int*)malloc(sizeof(int)*size);
678:   M->start_indices = (int*)malloc(sizeof(int)*size);
679:   M->pe            = (int*)malloc(sizeof(int)*n);
680:   M->block_sizes   = (int*)malloc(sizeof(int)*n);
681:   for (i=0; i<n; i++) M->block_sizes[i] = 1;

683:   MPI_Allgather(&mnl,1,MPI_INT,M->mnls,1,MPI_INT,comm);

685:   M->start_indices[0] = 0;
686:   for (i=1; i<size; i++) M->start_indices[i] = M->start_indices[i-1] + M->mnls[i-1];

688:   M->mnl            = M->mnls[M->myid];
689:   M->my_start_index = M->start_indices[M->myid];

691:   for (i=0; i<size; i++) {
692:     start_indx = M->start_indices[i];
693:     for (j=0; j<M->mnls[i]; j++) M->pe[start_indx+j] = i;
694:   }

696:   if (AT) {
697:     M->lines = new_compressed_lines(M->mnls[rank],1);
698:   } else {
699:     M->lines = new_compressed_lines(M->mnls[rank],0);
700:   }

702:   rows = M->lines;

704:   /* Determine the mapping from global indices to pointers */
705:   PetscMalloc1(M->n,&mapping);
706:   pe         = 0;
707:   local_indx = 0;
708:   for (i=0; i<M->n; i++) {
709:     if (local_indx >= M->mnls[pe]) {
710:       pe++;
711:       local_indx = 0;
712:     }
713:     mapping[i] = local_indx + M->start_indices[pe];
714:     local_indx++;
715:   }

717:   /*********************************************************/
718:   /************** Set up the row structure *****************/
719:   /*********************************************************/

721:   MatGetOwnershipRange(A,&rstart,&rend);
722:   for (i=rstart; i<rend; i++) {
723:     row_indx = i - rstart;
724:     MatGetRow(A,i,&nz,&cols,&vals);
725:     /* allocate buffers */
726:     rows->ptrs[row_indx] = (int*)malloc(nz*sizeof(int));
727:     rows->A[row_indx]    = (double*)malloc(nz*sizeof(double));
728:     /* copy the matrix */
729:     for (j=0; j<nz; j++) {
730:       col = cols[j];
731:       len = rows->len[row_indx]++;

733:       rows->ptrs[row_indx][len] = mapping[col];
734:       rows->A[row_indx][len]    = vals[j];
735:     }
736:     rows->slen[row_indx] = rows->len[row_indx];

738:     MatRestoreRow(A,i,&nz,&cols,&vals);
739:   }


742:   /************************************************************/
743:   /************** Set up the column structure *****************/
744:   /*********************************************************/

746:   if (AT) {

748:     for (i=rstart; i<rend; i++) {
749:       row_indx = i - rstart;
750:       MatGetRow(AT,i,&nz,&cols,&vals);
751:       /* allocate buffers */
752:       rows->rptrs[row_indx] = (int*)malloc(nz*sizeof(int));
753:       /* copy the matrix (i.e., the structure) */
754:       for (j=0; j<nz; j++) {
755:         col = cols[j];
756:         len = rows->rlen[row_indx]++;

758:         rows->rptrs[row_indx][len] = mapping[col];
759:       }
760:       MatRestoreRow(AT,i,&nz,&cols,&vals);
761:     }
762:   }

764:   PetscFree(mapping);

766:   order_pointers(M);
767:   M->maxnz = calc_maxnz(M);
768:   *B       = M;
769:   return(0);
770: }

772: /**********************************************************************/

774: /*
775:    Converts from an SPAI matrix B  to a PETSc matrix PB.
776:    This assumes that the SPAI matrix B is stored in
777:    COMPRESSED-ROW format.
778: */
781: PetscErrorCode ConvertMatrixToMat(MPI_Comm comm,matrix *B,Mat *PB)
782: {
783:   PetscMPIInt    size,rank;
785:   int            m,n,M,N;
786:   int            d_nz,o_nz;
787:   int            *d_nnz,*o_nnz;
788:   int            i,k,global_row,global_col,first_diag_col,last_diag_col;
789:   PetscScalar    val;

792:   MPI_Comm_size(comm,&size);
793:   MPI_Comm_rank(comm,&rank);

795:   m    = n = B->mnls[rank];
796:   d_nz = o_nz = 0;

798:   /* Determine preallocation for MatCreateMPIAIJ */
799:   PetscMalloc1(m,&d_nnz);
800:   PetscMalloc1(m,&o_nnz);
801:   for (i=0; i<m; i++) d_nnz[i] = o_nnz[i] = 0;
802:   first_diag_col = B->start_indices[rank];
803:   last_diag_col  = first_diag_col + B->mnls[rank];
804:   for (i=0; i<B->mnls[rank]; i++) {
805:     for (k=0; k<B->lines->len[i]; k++) {
806:       global_col = B->lines->ptrs[i][k];
807:       if ((global_col >= first_diag_col) && (global_col < last_diag_col)) d_nnz[i]++;
808:       else o_nnz[i]++;
809:     }
810:   }

812:   M = N = B->n;
813:   /* Here we only know how to create AIJ format */
814:   MatCreate(comm,PB);
815:   MatSetSizes(*PB,m,n,M,N);
816:   MatSetType(*PB,MATAIJ);
817:   MatSeqAIJSetPreallocation(*PB,d_nz,d_nnz);
818:   MatMPIAIJSetPreallocation(*PB,d_nz,d_nnz,o_nz,o_nnz);

820:   for (i=0; i<B->mnls[rank]; i++) {
821:     global_row = B->start_indices[rank]+i;
822:     for (k=0; k<B->lines->len[i]; k++) {
823:       global_col = B->lines->ptrs[i][k];

825:       val  = B->lines->A[i][k];
826:       MatSetValues(*PB,1,&global_row,1,&global_col,&val,ADD_VALUES);
827:     }
828:   }

830:   PetscFree(d_nnz);
831:   PetscFree(o_nnz);

833:   MatAssemblyBegin(*PB,MAT_FINAL_ASSEMBLY);
834:   MatAssemblyEnd(*PB,MAT_FINAL_ASSEMBLY);
835:   return(0);
836: }

838: /**********************************************************************/

840: /*
841:    Converts from an SPAI vector v  to a PETSc vec Pv.
842: */
845: PetscErrorCode ConvertVectorToVec(MPI_Comm comm,vector *v,Vec *Pv)
846: {
848:   PetscMPIInt    size,rank;
849:   int            m,M,i,*mnls,*start_indices,*global_indices;

852:   MPI_Comm_size(comm,&size);
853:   MPI_Comm_rank(comm,&rank);

855:   m = v->mnl;
856:   M = v->n;


859:   VecCreateMPI(comm,m,M,Pv);

861:   PetscMalloc1(size,&mnls);
862:   MPI_Allgather(&v->mnl,1,MPI_INT,mnls,1,MPI_INT,comm);

864:   PetscMalloc1(size,&start_indices);

866:   start_indices[0] = 0;
867:   for (i=1; i<size; i++) start_indices[i] = start_indices[i-1] +mnls[i-1];

869:   PetscMalloc1(v->mnl,&global_indices);
870:   for (i=0; i<v->mnl; i++) global_indices[i] = start_indices[rank] + i;

872:   PetscFree(mnls);
873:   PetscFree(start_indices);

875:   VecSetValues(*Pv,v->mnl,global_indices,v->v,INSERT_VALUES);
876:   VecAssemblyBegin(*Pv);
877:   VecAssemblyEnd(*Pv);

879:   PetscFree(global_indices);
880:   return(0);
881: }