Actual source code: mpibdiag.c

  1: #define PETSCMAT_DLL

  3: /*
  4:    The basic matrix operations for the Block diagonal parallel 
  5:   matrices.
  6: */
 7:  #include src/mat/impls/bdiag/mpi/mpibdiag.h

 11: PetscErrorCode MatSetValues_MPIBDiag(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],const PetscScalar v[],InsertMode addv)
 12: {
 13:   Mat_MPIBDiag   *mbd = (Mat_MPIBDiag*)mat->data;
 15:   PetscInt       i,j,row,rstart = mat->rmap.rstart,rend = mat->rmap.rend;
 16:   PetscTruth     roworiented = mbd->roworiented;

 19:   for (i=0; i<m; i++) {
 20:     if (idxm[i] < 0) continue;
 21:     if (idxm[i] >= mat->rmap.N) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Row too large");
 22:     if (idxm[i] >= rstart && idxm[i] < rend) {
 23:       row = idxm[i] - rstart;
 24:       for (j=0; j<n; j++) {
 25:         if (idxn[j] < 0) continue;
 26:         if (idxn[j] >= mat->cmap.N) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Column too large");
 27:         if (roworiented) {
 28:           MatSetValues(mbd->A,1,&row,1,&idxn[j],v+i*n+j,addv);
 29:         } else {
 30:           MatSetValues(mbd->A,1,&row,1,&idxn[j],v+i+j*m,addv);
 31:         }
 32:       }
 33:     } else {
 34:       if (!mbd->donotstash) {
 35:         if (roworiented) {
 36:           MatStashValuesRow_Private(&mat->stash,idxm[i],n,idxn,v+i*n);
 37:         } else {
 38:           MatStashValuesCol_Private(&mat->stash,idxm[i],n,idxn,v+i,m);
 39:         }
 40:       }
 41:     }
 42:   }
 43:   return(0);
 44: }

 48: PetscErrorCode MatGetValues_MPIBDiag(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[])
 49: {
 50:   Mat_MPIBDiag   *mbd = (Mat_MPIBDiag*)mat->data;
 52:   PetscInt       i,j,row,rstart = mat->rmap.rstart,rend = mat->rmap.rend;

 55:   for (i=0; i<m; i++) {
 56:     if (idxm[i] < 0) continue; /* SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Negative row"); */
 57:     if (idxm[i] >= mat->rmap.N) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Row too large");
 58:     if (idxm[i] >= rstart && idxm[i] < rend) {
 59:       row = idxm[i] - rstart;
 60:       for (j=0; j<n; j++) {
 61:         if (idxn[j] < 0) continue; /* SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Negative column"); */
 62:         if (idxn[j] >= mat->cmap.N) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Column too large");
 63:         MatGetValues(mbd->A,1,&row,1,&idxn[j],v+i*n+j);
 64:       }
 65:     } else {
 66:       SETERRQ(PETSC_ERR_SUP,"Only local values currently supported");
 67:     }
 68:   }
 69:   return(0);
 70: }

 74: PetscErrorCode MatAssemblyBegin_MPIBDiag(Mat mat,MatAssemblyType mode)
 75: {
 76:   MPI_Comm       comm = ((PetscObject)mat)->comm;
 78:   PetscInt       nstash,reallocs;
 79:   InsertMode     addv;

 82:   MPI_Allreduce(&mat->insertmode,&addv,1,MPI_INT,MPI_BOR,comm);
 83:   if (addv == (ADD_VALUES|INSERT_VALUES)) {
 84:     SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Cannot mix adds/inserts on different procs");
 85:   }
 86:   mat->insertmode = addv; /* in case this processor had no cache */
 87:   MatStashScatterBegin_Private(mat,&mat->stash,mat->rmap.range);
 88:   MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);
 89:   PetscInfo2(mat,"Stash has %D entries,uses %D mallocs.\n",nstash,reallocs);
 90:   return(0);
 91: }

 95: PetscErrorCode MatAssemblyEnd_MPIBDiag(Mat mat,MatAssemblyType mode)
 96: {
 97:   Mat_MPIBDiag   *mbd = (Mat_MPIBDiag*)mat->data;
 98:   Mat_SeqBDiag   *mlocal;
100:   PetscMPIInt    n;
101:   PetscInt       i,*row,*col;
102:   PetscInt       *tmp1,*tmp2,len,ict,Mblock,Nblock,flg,j,rstart,ncols;
103:   PetscScalar    *val;
104:   InsertMode     addv = mat->insertmode;


108:   while (1) {
109:     MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);
110:     if (!flg) break;
111: 
112:     for (i=0; i<n;) {
113:       /* Now identify the consecutive vals belonging to the same row */
114:       for (j=i,rstart=row[j]; j<n; j++) { if (row[j] != rstart) break; }
115:       if (j < n) ncols = j-i;
116:       else       ncols = n-i;
117:       /* Now assemble all these values with a single function call */
118:       MatSetValues_MPIBDiag(mat,1,row+i,ncols,col+i,val+i,addv);
119:       i = j;
120:     }
121:   }
122:   MatStashScatterEnd_Private(&mat->stash);

124:   MatAssemblyBegin(mbd->A,mode);
125:   MatAssemblyEnd(mbd->A,mode);

127:   /* Fix main diagonal location and determine global diagonals */
128:   mlocal         = (Mat_SeqBDiag*)mbd->A->data;
129:   Mblock         = mat->rmap.N/mat->rmap.bs; Nblock = mat->cmap.N/mat->rmap.bs;
130:   len            = Mblock + Nblock + 1; /* add 1 to prevent 0 malloc */
131:   PetscMalloc(2*len*sizeof(PetscInt),&tmp1);
132:   tmp2           = tmp1 + len;
133:   PetscMemzero(tmp1,2*len*sizeof(PetscInt));
134:   mlocal->mainbd = -1;
135:   for (i=0; i<mlocal->nd; i++) {
136:     if (mlocal->diag[i] + mbd->brstart == 0) mlocal->mainbd = i;
137:     tmp1[mlocal->diag[i] + mbd->brstart + Mblock] = 1;
138:   }
139:   MPI_Allreduce(tmp1,tmp2,len,MPIU_INT,MPI_SUM,((PetscObject)mat)->comm);
140:   ict  = 0;
141:   for (i=0; i<len; i++) {
142:     if (tmp2[i]) {
143:       mbd->gdiag[ict] = i - Mblock;
144:       ict++;
145:     }
146:   }
147:   mbd->gnd = ict;
148:   PetscFree(tmp1);

150:   if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) {
151:     MatSetUpMultiply_MPIBDiag(mat);
152:   }
153:   return(0);
154: }

158: PetscErrorCode MatZeroEntries_MPIBDiag(Mat A)
159: {
160:   Mat_MPIBDiag   *l = (Mat_MPIBDiag*)A->data;

164:   MatZeroEntries(l->A);
165:   return(0);
166: }

168: /* again this uses the same basic stratagy as in the assembly and 
169:    scatter create routines, we should try to do it systematically 
170:    if we can figure out the proper level of generality. */

172: /* the code does not do the diagonal entries correctly unless the 
173:    matrix is square and the column and row owerships are identical.
174:    This is a BUG. The only way to fix it seems to be to access 
175:    aij->A and aij->B directly and not through the MatZeroRows() 
176:    routine. 
177: */

181: PetscErrorCode MatZeroRows_MPIBDiag(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag)
182: {
183:   Mat_MPIBDiag   *l = (Mat_MPIBDiag*)A->data;
185:   PetscMPIInt    n,imdex,size = l->size,rank = l->rank,tag = ((PetscObject)A)->tag;
186:   PetscInt       i,*owners = A->rmap.range;
187:   PetscInt       *nprocs,j,idx,nsends;
188:   PetscInt       nmax,*svalues,*starts,*owner,nrecvs;
189:   PetscInt       *rvalues,count,base,slen,*source;
190:   PetscInt       *lens,*lrows,*values;
191:   MPI_Comm       comm = ((PetscObject)A)->comm;
192:   MPI_Request    *send_waits,*recv_waits;
193:   MPI_Status     recv_status,*send_status;
194:   PetscTruth     found;

197:   /*  first count number of contributors to each processor */
198:   PetscMalloc(2*size*sizeof(PetscInt),&nprocs);
199:   PetscMemzero(nprocs,2*size*sizeof(PetscInt));
200:   PetscMalloc((N+1)*sizeof(PetscInt),&owner); /* see note*/
201:   for (i=0; i<N; i++) {
202:     idx = rows[i];
203:     found = PETSC_FALSE;
204:     for (j=0; j<size; j++) {
205:       if (idx >= owners[j] && idx < owners[j+1]) {
206:         nprocs[2*j]++; nprocs[2*j+1] = 1; owner[i] = j; found = PETSC_TRUE; break;
207:       }
208:     }
209:     if (!found) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"row out of range");
210:   }
211:   nsends = 0;  for (i=0; i<size; i++) {nsends += nprocs[2*i+1];}

213:   /* inform other processors of number of messages and max length*/
214:   PetscMaxSum(comm,nprocs,&nmax,&nrecvs);

216:   /* post receives:   */
217:   PetscMalloc((nrecvs+1)*(nmax+1)*sizeof(PetscInt),&rvalues);
218:   PetscMalloc((nrecvs+1)*sizeof(MPI_Request),&recv_waits);
219:   for (i=0; i<nrecvs; i++) {
220:     MPI_Irecv(rvalues+nmax*i,nmax,MPIU_INT,MPI_ANY_SOURCE,tag,comm,recv_waits+i);
221:   }

223:   /* do sends:
224:       1) starts[i] gives the starting index in svalues for stuff going to 
225:          the ith processor
226:   */
227:   PetscMalloc((N+1)*sizeof(PetscInt),&svalues);
228:   PetscMalloc((nsends+1)*sizeof(MPI_Request),&send_waits);
229:   PetscMalloc((size+1)*sizeof(PetscInt),&starts);
230:   starts[0] = 0;
231:   for (i=1; i<size; i++) { starts[i] = starts[i-1] + nprocs[2*i-2];}
232:   for (i=0; i<N; i++) {
233:     svalues[starts[owner[i]]++] = rows[i];
234:   }

236:   starts[0] = 0;
237:   for (i=1; i<size+1; i++) { starts[i] = starts[i-1] + nprocs[2*i-2];}
238:   count = 0;
239:   for (i=0; i<size; i++) {
240:     if (nprocs[2*i+1]) {
241:       MPI_Isend(svalues+starts[i],nprocs[2*i],MPIU_INT,i,tag,comm,send_waits+count++);
242:     }
243:   }
244:   PetscFree(starts);

246:   base = owners[rank];

248:   /*  wait on receives */
249:   PetscMalloc(2*(nrecvs+1)*sizeof(PetscInt),&lens);
250:   source = lens + nrecvs;
251:   count  = nrecvs;
252:   slen   = 0;
253:   while (count) {
254:     MPI_Waitany(nrecvs,recv_waits,&imdex,&recv_status);
255:     /* unpack receives into our local space */
256:     MPI_Get_count(&recv_status,MPIU_INT,&n);
257:     source[imdex]  = recv_status.MPI_SOURCE;
258:     lens[imdex]  = n;
259:     slen += n;
260:     count--;
261:   }
262:   PetscFree(recv_waits);
263: 
264:   /* move the data into the send scatter */
265:   PetscMalloc((slen+1)*sizeof(PetscInt),&lrows);
266:   count = 0;
267:   for (i=0; i<nrecvs; i++) {
268:     values = rvalues + i*nmax;
269:     for (j=0; j<lens[i]; j++) {
270:       lrows[count++] = values[j] - base;
271:     }
272:   }
273:   PetscFree(rvalues);
274:   PetscFree(lens);
275:   PetscFree(owner);
276:   PetscFree(nprocs);
277: 
278:   /* actually zap the local rows */
279:   MatZeroRows(l->A,slen,lrows,diag);
280:   PetscFree(lrows);

282:   /* wait on sends */
283:   if (nsends) {
284:     PetscMalloc(nsends*sizeof(MPI_Status),&send_status);
285:     MPI_Waitall(nsends,send_waits,send_status);
286:     PetscFree(send_status);
287:   }
288:   PetscFree(send_waits);
289:   PetscFree(svalues);

291:   return(0);
292: }

296: PetscErrorCode MatMult_MPIBDiag(Mat mat,Vec xx,Vec yy)
297: {
298:   Mat_MPIBDiag   *mbd = (Mat_MPIBDiag*)mat->data;

302:   VecScatterBegin(mbd->Mvctx,xx,mbd->lvec,INSERT_VALUES,SCATTER_FORWARD);
303:   VecScatterEnd(mbd->Mvctx,xx,mbd->lvec,INSERT_VALUES,SCATTER_FORWARD);
304:   (*mbd->A->ops->mult)(mbd->A,mbd->lvec,yy);
305:   return(0);
306: }

310: PetscErrorCode MatMultAdd_MPIBDiag(Mat mat,Vec xx,Vec yy,Vec zz)
311: {
312:   Mat_MPIBDiag   *mbd = (Mat_MPIBDiag*)mat->data;

316:   VecScatterBegin(mbd->Mvctx,xx,mbd->lvec,INSERT_VALUES,SCATTER_FORWARD);
317:   VecScatterEnd(mbd->Mvctx,xx,mbd->lvec,INSERT_VALUES,SCATTER_FORWARD);
318:   (*mbd->A->ops->multadd)(mbd->A,mbd->lvec,yy,zz);
319:   return(0);
320: }

324: PetscErrorCode MatMultTranspose_MPIBDiag(Mat A,Vec xx,Vec yy)
325: {
326:   Mat_MPIBDiag   *a = (Mat_MPIBDiag*)A->data;
328:   PetscScalar    zero = 0.0;

331:   VecSet(yy,zero);
332:   (*a->A->ops->multtranspose)(a->A,xx,a->lvec);
333:   VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
334:   VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
335:   return(0);
336: }

340: PetscErrorCode MatMultTransposeAdd_MPIBDiag(Mat A,Vec xx,Vec yy,Vec zz)
341: {
342:   Mat_MPIBDiag   *a = (Mat_MPIBDiag*)A->data;

346:   VecCopy(yy,zz);
347:   (*a->A->ops->multtranspose)(a->A,xx,a->lvec);
348:   VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);
349:   VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);
350:   return(0);
351: }

355: PetscErrorCode MatGetInfo_MPIBDiag(Mat matin,MatInfoType flag,MatInfo *info)
356: {
357:   Mat_MPIBDiag   *mat = (Mat_MPIBDiag*)matin->data;
359:   PetscReal      isend[5],irecv[5];

362:   info->block_size     = (PetscReal)mat->A->rmap.bs;
363:   MatGetInfo(mat->A,MAT_LOCAL,info);
364:   isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded;
365:   isend[3] = info->memory;  isend[4] = info->mallocs;
366:   if (flag == MAT_LOCAL) {
367:     info->nz_used      = isend[0];
368:     info->nz_allocated = isend[1];
369:     info->nz_unneeded  = isend[2];
370:     info->memory       = isend[3];
371:     info->mallocs      = isend[4];
372:   } else if (flag == MAT_GLOBAL_MAX) {
373:     MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPI_MAX,((PetscObject)matin)->comm);
374:     info->nz_used      = irecv[0];
375:     info->nz_allocated = irecv[1];
376:     info->nz_unneeded  = irecv[2];
377:     info->memory       = irecv[3];
378:     info->mallocs      = irecv[4];
379:   } else if (flag == MAT_GLOBAL_SUM) {
380:     MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPI_SUM,((PetscObject)matin)->comm);
381:     info->nz_used      = irecv[0];
382:     info->nz_allocated = irecv[1];
383:     info->nz_unneeded  = irecv[2];
384:     info->memory       = irecv[3];
385:     info->mallocs      = irecv[4];
386:   }
387:   info->rows_global    = (double)matin->rmap.N;
388:   info->columns_global = (double)matin->cmap.N;
389:   info->rows_local     = (double)matin->rmap.n;
390:   info->columns_local  = (double)matin->cmap.N;
391:   return(0);
392: }

396: PetscErrorCode MatGetDiagonal_MPIBDiag(Mat mat,Vec v)
397: {
399:   Mat_MPIBDiag   *A = (Mat_MPIBDiag*)mat->data;

402:   MatGetDiagonal(A->A,v);
403:   return(0);
404: }

408: PetscErrorCode MatDestroy_MPIBDiag(Mat mat)
409: {
410:   Mat_MPIBDiag   *mbd = (Mat_MPIBDiag*)mat->data;
412: #if defined(PETSC_USE_LOG)
413:   Mat_SeqBDiag   *ms = (Mat_SeqBDiag*)mbd->A->data;

416:   PetscLogObjectState((PetscObject)mat,"Rows=%D, Cols=%D, BSize=%D, NDiag=%D",mat->rmap.N,mat->cmap.N,mat->rmap.bs,ms->nd);
417: #else
419: #endif
420:   MatStashDestroy_Private(&mat->stash);
421:   PetscFree(mbd->gdiag);
422:   MatDestroy(mbd->A);
423:   if (mbd->lvec) {VecDestroy(mbd->lvec);}
424:   if (mbd->Mvctx) {VecScatterDestroy(mbd->Mvctx);}
425:   PetscFree(mbd);

427:   PetscObjectChangeTypeName((PetscObject)mat,0);
428:   PetscObjectComposeFunction((PetscObject)mat,"MatGetDiagonalBlock_C","",PETSC_NULL);
429:   PetscObjectComposeFunction((PetscObject)mat,"MatMPIBDiagSetPreallocation_C","",PETSC_NULL);
430:   return(0);
431: }


436: static PetscErrorCode MatView_MPIBDiag_Binary(Mat mat,PetscViewer viewer)
437: {
438:   Mat_MPIBDiag   *mbd = (Mat_MPIBDiag*)mat->data;

442:   if (mbd->size == 1) {
443:     MatView(mbd->A,viewer);
444:   } else SETERRQ(PETSC_ERR_SUP,"Only uniprocessor output supported");
445:   return(0);
446: }

450: static PetscErrorCode MatView_MPIBDiag_ASCIIorDraw(Mat mat,PetscViewer viewer)
451: {
452:   Mat_MPIBDiag      *mbd = (Mat_MPIBDiag*)mat->data;
453:   PetscErrorCode    ierr;
454:   PetscMPIInt       size = mbd->size,rank = mbd->rank;
455:   PetscInt          i;
456:   PetscTruth        iascii,isdraw;
457:   PetscViewer       sviewer;
458:   PetscViewerFormat format;

461:   PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&iascii);
462:   PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_DRAW,&isdraw);
463:   if (iascii) {
464:     PetscViewerGetFormat(viewer,&format);
465:     if (format == PETSC_VIEWER_ASCII_INFO || format == PETSC_VIEWER_ASCII_INFO_DETAIL) {
466:       PetscInt nline = PetscMin(10,mbd->gnd),k,nk,np;
467:       PetscViewerASCIIPrintf(viewer,"  block size=%D, total number of diagonals=%D\n",mat->rmap.bs,mbd->gnd);
468:       nk = (mbd->gnd-1)/nline + 1;
469:       for (k=0; k<nk; k++) {
470:         PetscViewerASCIIPrintf(viewer,"  global diag numbers:");
471:         np = PetscMin(nline,mbd->gnd - nline*k);
472:         for (i=0; i<np; i++) {
473:           PetscViewerASCIIPrintf(viewer,"  %D",mbd->gdiag[i+nline*k]);
474:         }
475:         PetscViewerASCIIPrintf(viewer,"\n");
476:       }
477:       if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) {
478:         MatInfo info;
479:         MPI_Comm_rank(((PetscObject)mat)->comm,&rank);
480:         MatGetInfo(mat,MAT_LOCAL,&info);
481:         PetscViewerASCIISynchronizedPrintf(viewer,"[%d] local rows %D nz %D nz alloced %D mem %D \n",rank,mat->rmap.N,
482:             (PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(PetscInt)info.memory);
483:         PetscViewerFlush(viewer);
484:         VecScatterView(mbd->Mvctx,viewer);
485:       }
486:       return(0);
487:     }
488:   }

490:   if (isdraw) {
491:     PetscDraw       draw;
492:     PetscTruth isnull;
493:     PetscViewerDrawGetDraw(viewer,0,&draw);
494:     PetscDrawIsNull(draw,&isnull); if (isnull) return(0);
495:   }

497:   if (size == 1) {
498:     MatView(mbd->A,viewer);
499:   } else {
500:     /* assemble the entire matrix onto first processor. */
501:     Mat          A;
502:     PetscInt     M = mat->rmap.N,N = mat->cmap.N,m,row,nz,*cols;
503:     PetscScalar  *vals;

505:     /* Here we are constructing a temporary matrix, so we will explicitly set the type to MPIBDiag */
506:     MatCreate(((PetscObject)mat)->comm,&A);
507:     if (!rank) {
508:       MatSetSizes(A,M,N,M,N);
509:       MatSetType(A,MATMPIBDIAG);
510:       MatMPIBDiagSetPreallocation(A,mbd->gnd,mbd->A->rmap.bs,mbd->gdiag,PETSC_NULL);
511:     } else {
512:       MatSetSizes(A,0,0,M,N);
513:       MatSetType(A,MATMPIBDIAG);
514:       MatMPIBDiagSetPreallocation(A,0,mbd->A->rmap.bs,PETSC_NULL,PETSC_NULL);
515:     }
516:     PetscLogObjectParent(mat,A);

518:     /* Copy the matrix ... This isn't the most efficient means,
519:        but it's quick for now */
520:     row = mat->rmap.rstart;
521:     m = mbd->A->rmap.N;
522:     for (i=0; i<m; i++) {
523:       MatGetRow_MPIBDiag(mat,row,&nz,&cols,&vals);
524:       MatSetValues(A,1,&row,nz,cols,vals,INSERT_VALUES);
525:       MatRestoreRow_MPIBDiag(mat,row,&nz,&cols,&vals);
526:       row++;
527:     }
528:     MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);
529:     MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);
530:     PetscViewerGetSingleton(viewer,&sviewer);
531:     if (!rank) {
532:       MatView(((Mat_MPIBDiag*)(A->data))->A,sviewer);
533:     }
534:     PetscViewerRestoreSingleton(viewer,&sviewer);
535:     PetscViewerFlush(viewer);
536:     MatDestroy(A);
537:   }
538:   return(0);
539: }

543: PetscErrorCode MatView_MPIBDiag(Mat mat,PetscViewer viewer)
544: {
546:   PetscTruth     iascii,isdraw,isbinary;

549:   PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&iascii);
550:   PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_DRAW,&isdraw);
551:   PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_BINARY,&isbinary);
552:   if (iascii || isdraw) {
553:     MatView_MPIBDiag_ASCIIorDraw(mat,viewer);
554:   } else if (isbinary) {
555:     MatView_MPIBDiag_Binary(mat,viewer);
556:   } else {
557:     SETERRQ1(PETSC_ERR_SUP,"Viewer type %s not supported by MPIBdiag matrices",((PetscObject)viewer)->type_name);
558:   }
559:   return(0);
560: }

564: PetscErrorCode MatSetOption_MPIBDiag(Mat A,MatOption op,PetscTruth flg)
565: {
566:   Mat_MPIBDiag   *mbd = (Mat_MPIBDiag*)A->data;

569:   switch (op) {
570:   case MAT_NEW_NONZERO_LOCATIONS:
571:   case MAT_NEW_NONZERO_LOCATION_ERR:
572:   case MAT_NEW_NONZERO_ALLOCATION_ERR:
573:   case MAT_NEW_DIAGONALS:
574:     MatSetOption(mbd->A,op,flg);
575:     break;
576:   case MAT_ROW_ORIENTED:
577:     mbd->roworiented = flg;
578:     MatSetOption(mbd->A,op,flg);
579:     break;
580:   case MAT_IGNORE_OFF_PROC_ENTRIES:
581:     mbd->donotstash = flg;
582:     break;
583:   case MAT_SYMMETRIC:
584:   case MAT_STRUCTURALLY_SYMMETRIC:
585:   case MAT_HERMITIAN:
586:   case MAT_SYMMETRY_ETERNAL:
587:     PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);
588:     break;
589:   default:
590:     SETERRQ1(PETSC_ERR_SUP,"unknown option %d",op);
591:   }
592:   return(0);
593: }


598: PetscErrorCode MatGetRow_MPIBDiag(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
599: {
600:   Mat_MPIBDiag   *mat = (Mat_MPIBDiag*)matin->data;
602:   PetscInt       lrow;

605:   if (row < matin->rmap.rstart || row >= matin->rmap.rend) SETERRQ(PETSC_ERR_SUP,"only for local rows")
606:   lrow = row - matin->rmap.rstart;
607:   MatGetRow_SeqBDiag(mat->A,lrow,nz,idx,v);
608:   return(0);
609: }

613: PetscErrorCode MatRestoreRow_MPIBDiag(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
614: {
615:   Mat_MPIBDiag   *mat = (Mat_MPIBDiag*)matin->data;
617:   PetscInt       lrow;

620:   lrow = row - matin->rmap.rstart;
621:   MatRestoreRow_SeqBDiag(mat->A,lrow,nz,idx,v);
622:   return(0);
623: }


628: PetscErrorCode MatNorm_MPIBDiag(Mat A,NormType type,PetscReal *nrm)
629: {
630:   Mat_MPIBDiag   *mbd = (Mat_MPIBDiag*)A->data;
631:   Mat_SeqBDiag   *a = (Mat_SeqBDiag*)mbd->A->data;
632:   PetscReal      sum = 0.0;
634:   PetscInt       d,i,nd = a->nd,bs = A->rmap.bs,len;
635:   PetscScalar    *dv;

638:   if (type == NORM_FROBENIUS) {
639:     for (d=0; d<nd; d++) {
640:       dv   = a->diagv[d];
641:       len  = a->bdlen[d]*bs*bs;
642:       for (i=0; i<len; i++) {
643: #if defined(PETSC_USE_COMPLEX)
644:         sum += PetscRealPart(PetscConj(dv[i])*dv[i]);
645: #else
646:         sum += dv[i]*dv[i];
647: #endif
648:       }
649:     }
650:     MPI_Allreduce(&sum,nrm,1,MPIU_REAL,MPI_SUM,((PetscObject)A)->comm);
651:     *nrm = sqrt(*nrm);
652:     PetscLogFlops(2*A->rmap.n*A->rmap.N);
653:   } else if (type == NORM_1) { /* max column norm */
654:     PetscReal *tmp,*tmp2;
655:     PetscInt    j;
656:     PetscMalloc((mbd->A->cmap.n+1)*sizeof(PetscReal),&tmp);
657:     PetscMalloc((mbd->A->cmap.n+1)*sizeof(PetscReal),&tmp2);
658:     MatNorm_SeqBDiag_Columns(mbd->A,tmp,mbd->A->cmap.n);
659:     *nrm = 0.0;
660:     MPI_Allreduce(tmp,tmp2,mbd->A->cmap.n,MPIU_REAL,MPI_SUM,((PetscObject)A)->comm);
661:     for (j=0; j<mbd->A->cmap.n; j++) {
662:       if (tmp2[j] > *nrm) *nrm = tmp2[j];
663:     }
664:     PetscFree(tmp);
665:     PetscFree(tmp2);
666:   } else if (type == NORM_INFINITY) { /* max row norm */
667:     PetscReal normtemp;
668:     MatNorm(mbd->A,type,&normtemp);
669:     MPI_Allreduce(&normtemp,nrm,1,MPIU_REAL,MPI_MAX,((PetscObject)A)->comm);
670:   }
671:   return(0);
672: }

676: PetscErrorCode MatScale_MPIBDiag(Mat A,PetscScalar alpha)
677: {
679:   Mat_MPIBDiag   *a = (Mat_MPIBDiag*)A->data;

682:   MatScale_SeqBDiag(a->A,alpha);
683:   return(0);
684: }

688: PetscErrorCode MatSetUpPreallocation_MPIBDiag(Mat A)
689: {

693:    MatMPIBDiagSetPreallocation(A,PETSC_DEFAULT,PETSC_DEFAULT,0,0);
694:   return(0);
695: }

697: /* -------------------------------------------------------------------*/

699: static struct _MatOps MatOps_Values = {MatSetValues_MPIBDiag,
700:        MatGetRow_MPIBDiag,
701:        MatRestoreRow_MPIBDiag,
702:        MatMult_MPIBDiag,
703: /* 4*/ MatMultAdd_MPIBDiag,
704:        MatMultTranspose_MPIBDiag,
705:        MatMultTransposeAdd_MPIBDiag,
706:        0,
707:        0,
708:        0,
709: /*10*/ 0,
710:        0,
711:        0,
712:        0,
713:        0,
714: /*15*/ MatGetInfo_MPIBDiag,
715:        0,
716:        MatGetDiagonal_MPIBDiag,
717:        0,
718:        MatNorm_MPIBDiag,
719: /*20*/ MatAssemblyBegin_MPIBDiag,
720:        MatAssemblyEnd_MPIBDiag,
721:        0,
722:        MatSetOption_MPIBDiag,
723:        MatZeroEntries_MPIBDiag,
724: /*25*/ MatZeroRows_MPIBDiag,
725:        0,
726:        0,
727:        0,
728:        0,
729: /*30*/ MatSetUpPreallocation_MPIBDiag,
730:        0,
731:        0,
732:        0,
733:        0,
734: /*35*/ 0,
735:        0,
736:        0,
737:        0,
738:        0,
739: /*40*/ 0,
740:        0,
741:        0,
742:        MatGetValues_MPIBDiag,
743:        0,
744: /*45*/ 0,
745:        MatScale_MPIBDiag,
746:        0,
747:        0,
748:        0,
749: /*50*/ 0,
750:        0,
751:        0,
752:        0,
753:        0,
754: /*55*/ 0,
755:        0,
756:        0,
757:        0,
758:        0,
759: /*60*/ 0,
760:        MatDestroy_MPIBDiag,
761:        MatView_MPIBDiag,
762:        0,
763:        0,
764: /*65*/ 0,
765:        0,
766:        0,
767:        0,
768:        0,
769: /*70*/ 0,
770:        0,
771:        0,
772:        0,
773:        0,
774: /*75*/ 0,
775:        0,
776:        0,
777:        0,
778:        0,
779: /*80*/ 0,
780:        0,
781:        0,
782:        0,
783:        MatLoad_MPIBDiag,
784: /*85*/ 0,
785:        0,
786:        0,
787:        0,
788:        0,
789: /*90*/ 0,
790:        0,
791:        0,
792:        0,
793:        0,
794: /*95*/ 0,
795:        0,
796:        0,
797:        0};

802: PetscErrorCode  MatGetDiagonalBlock_MPIBDiag(Mat A,PetscTruth *iscopy,MatReuse reuse,Mat *a)
803: {
804:   Mat_MPIBDiag   *matin = (Mat_MPIBDiag *)A->data;
806:   PetscInt       lrows,lcols,rstart,rend;
807:   IS             localc,localr;

810:   MatGetLocalSize(A,&lrows,&lcols);
811:   MatGetOwnershipRange(A,&rstart,&rend);
812:   ISCreateStride(PETSC_COMM_SELF,lrows,rstart,1,&localc);
813:   ISCreateStride(PETSC_COMM_SELF,lrows,0,1,&localr);
814:   MatGetSubMatrix(matin->A,localr,localc,PETSC_DECIDE,reuse,a);
815:   ISDestroy(localr);
816:   ISDestroy(localc);

818:   *iscopy = PETSC_TRUE;
819:   return(0);
820: }

826: PetscErrorCode  MatMPIBDiagSetPreallocation_MPIBDiag(Mat B,PetscInt nd,PetscInt bs,PetscInt *diag,PetscScalar **diagv)
827: {
828:   Mat_MPIBDiag   *b;
830:   PetscInt       i,k,*ldiag,len,nd2;
831:   PetscScalar    **ldiagv = 0;
832:   PetscTruth     flg2;

835:   B->preallocated = PETSC_TRUE;
836:   if (bs == PETSC_DEFAULT) bs = 1;
837:   if (nd == PETSC_DEFAULT) nd = 0;
838:   PetscOptionsGetInt(PETSC_NULL,"-mat_block_size",&bs,PETSC_NULL);
839:   PetscOptionsGetInt(PETSC_NULL,"-mat_bdiag_ndiag",&nd,PETSC_NULL);
840:   PetscOptionsHasName(PETSC_NULL,"-mat_bdiag_diags",&flg2);
841:   if (nd && !diag) {
842:     PetscMalloc(nd*sizeof(PetscInt),&diag);
843:     nd2  = nd;
844:     PetscOptionsGetIntArray(PETSC_NULL,"-mat_bdiag_dvals",diag,&nd2,PETSC_NULL);
845:     if (nd2 != nd) {
846:       SETERRQ(PETSC_ERR_ARG_INCOMP,"Incompatible number of diags and diagonal vals");
847:     }
848:   } else if (flg2) {
849:     SETERRQ(PETSC_ERR_ARG_WRONG,"Must specify number of diagonals with -mat_bdiag_ndiag");
850:   }

852:   if (bs <= 0) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Blocksize must be positive");

854:   B->rmap.bs = B->cmap.bs = bs;

856:   PetscMapSetUp(&B->rmap);
857:   PetscMapSetUp(&B->cmap);

859:   if ((B->cmap.N%bs)) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Invalid block size - bad column number");
860:   if ((B->rmap.N%bs)) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Invalid block size - bad local row number");
861:   if ((B->rmap.N%bs)) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Invalid block size - bad global row number");


864:   b          = (Mat_MPIBDiag*)B->data;
865:   b->gnd     = nd;
866:   b->brstart = (B->rmap.rstart)/bs;
867:   b->brend   = (B->rmap.rend)/bs;


870:   /* Determine local diagonals; for now, assume global rows = global cols */
871:   /* These are sorted in MatCreateSeqBDiag */
872:   PetscMalloc((nd+1)*sizeof(PetscInt),&ldiag);
873:   len  = B->rmap.N/bs + B->cmap.N/bs + 1;
874:   PetscMalloc(len*sizeof(PetscInt),&b->gdiag);
875:   k    = 0;
876:   if (diagv) {
877:     PetscMalloc((nd+1)*sizeof(PetscScalar*),&ldiagv);
878:   }
879:   for (i=0; i<nd; i++) {
880:     b->gdiag[i] = diag[i];
881:     if (diag[i] > 0) { /* lower triangular */
882:       if (diag[i] < b->brend) {
883:         ldiag[k] = diag[i] - b->brstart;
884:         if (diagv) ldiagv[k] = diagv[i];
885:         k++;
886:       }
887:     } else { /* upper triangular */
888:       if (B->rmap.N/bs - diag[i] > B->cmap.N/bs) {
889:         if (B->rmap.N/bs + diag[i] > b->brstart) {
890:           ldiag[k] = diag[i] - b->brstart;
891:           if (diagv) ldiagv[k] = diagv[i];
892:           k++;
893:         }
894:       } else {
895:         if (B->rmap.N/bs > b->brstart) {
896:           ldiag[k] = diag[i] - b->brstart;
897:           if (diagv) ldiagv[k] = diagv[i];
898:           k++;
899:         }
900:       }
901:     }
902:   }

904:   /* Form local matrix */
905:   MatCreate(PETSC_COMM_SELF,&b->A);
906:   MatSetSizes(b->A,B->rmap.n,B->cmap.N,B->rmap.n,B->cmap.N);
907:   MatSetType(b->A,MATSEQBDIAG);
908:   MatSeqBDiagSetPreallocation(b->A,k,bs,ldiag,ldiagv);
909:   PetscLogObjectParent(B,b->A);
910:   PetscFree(ldiag);
911:   PetscFree(ldiagv);

913:   return(0);
914: }

917: /*MC
918:    MATMPIBDIAG - MATMPIBDIAG = "mpibdiag" - A matrix type to be used for distributed block diagonal matrices.

920:    Options Database Keys:
921: . -mat_type mpibdiag - sets the matrix type to "mpibdiag" during a call to MatSetFromOptions()

923:   Level: beginner

925: .seealso: MatCreateMPIBDiag
926: M*/

931: PetscErrorCode  MatCreate_MPIBDiag(Mat B)
932: {
933:   Mat_MPIBDiag   *b;

937:   PetscNewLog(B,Mat_MPIBDiag,&b);
938:   B->data         = (void*)b;
939:   PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));
940:   B->factor       = 0;
941:   B->mapping      = 0;

943:   B->insertmode = NOT_SET_VALUES;
944:   MPI_Comm_rank(((PetscObject)B)->comm,&b->rank);
945:   MPI_Comm_size(((PetscObject)B)->comm,&b->size);

947:   /* build cache for off array entries formed */
948:   MatStashCreate_Private(((PetscObject)B)->comm,1,&B->stash);
949:   b->donotstash = PETSC_FALSE;

951:   /* stuff used for matrix-vector multiply */
952:   b->lvec        = 0;
953:   b->Mvctx       = 0;

955:   /* used for MatSetValues() input */
956:   b->roworiented = PETSC_TRUE;

958:   PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetDiagonalBlock_C",
959:                                      "MatGetDiagonalBlock_MPIBDiag",
960:                                       MatGetDiagonalBlock_MPIBDiag);
961:   PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMPIBDiagSetPreallocation_C",
962:                                      "MatMPIBDiagSetPreallocation_MPIBDiag",
963:                                       MatMPIBDiagSetPreallocation_MPIBDiag);
964:   PetscObjectChangeTypeName((PetscObject)B,MATMPIBDIAG);
965:   return(0);
966: }

969: /*MC
970:    MATBDIAG - MATBDIAG = "bdiag" - A matrix type to be used for block diagonal matrices.

972:    This matrix type is identical to MATSEQBDIAG when constructed with a single process communicator,
973:    and MATMPIBDIAG otherwise.

975:    Options Database Keys:
976: . -mat_type bdiag - sets the matrix type to "bdiag" during a call to MatSetFromOptions()

978:   Level: beginner

980: .seealso: MatCreateMPIBDiag,MATSEQBDIAG,MATMPIBDIAG
981: M*/

986: PetscErrorCode  MatCreate_BDiag(Mat A)
987: {
989:   PetscMPIInt   size;

992:   MPI_Comm_size(((PetscObject)A)->comm,&size);
993:   if (size == 1) {
994:     MatSetType(A,MATSEQBDIAG);
995:   } else {
996:     MatSetType(A,MATMPIBDIAG);
997:   }
998:   return(0);
999: }

1004: /*@C
1005:    MatMPIBDiagSetPreallocation - 

1007:    Collective on Mat

1009:    Input Parameters:
1010: +  A - the matrix 
1011: .  nd - number of block diagonals (global) (optional)
1012: .  bs - each element of a diagonal is an bs x bs dense matrix
1013: .  diag - optional array of block diagonal numbers (length nd).
1014:    For a matrix element A[i,j], where i=row and j=column, the
1015:    diagonal number is
1016: $     diag = i/bs - j/bs  (integer division)
1017:    Set diag=PETSC_NULL on input for PETSc to dynamically allocate memory as 
1018:    needed (expensive).
1019: -  diagv  - pointer to actual diagonals (in same order as diag array), 
1020:    if allocated by user. Otherwise, set diagv=PETSC_NULL on input for PETSc
1021:    to control memory allocation.


1024:    Options Database Keys:
1025: .  -mat_block_size <bs> - Sets blocksize
1026: .  -mat_bdiag_diags <s1,s2,s3,...> - Sets diagonal numbers

1028:    Notes:
1029:    If PETSC_DECIDE or  PETSC_DETERMINE is used for a particular argument on one processor
1030:    than it must be used on all processors that share the object for that argument.

1032:    The parallel matrix is partitioned across the processors by rows, where
1033:    each local rectangular matrix is stored in the uniprocessor block 
1034:    diagonal format.  See the users manual for further details.

1036:    The user MUST specify either the local or global numbers of rows
1037:    (possibly both).

1039:    The case bs=1 (conventional diagonal storage) is implemented as
1040:    a special case.

1042:    Fortran Notes:
1043:    Fortran programmers cannot set diagv; this variable is ignored.

1045:    Level: intermediate

1047: .keywords: matrix, block, diagonal, parallel, sparse

1049: .seealso: MatCreate(), MatCreateSeqBDiag(), MatSetValues()
1050: @*/
1051: PetscErrorCode  MatMPIBDiagSetPreallocation(Mat B,PetscInt nd,PetscInt bs,const PetscInt diag[],PetscScalar *diagv[])
1052: {
1053:   PetscErrorCode ierr,(*f)(Mat,PetscInt,PetscInt,const PetscInt[],PetscScalar*[]);

1056:   PetscObjectQueryFunction((PetscObject)B,"MatMPIBDiagSetPreallocation_C",(void (**)(void))&f);
1057:   if (f) {
1058:     (*f)(B,nd,bs,diag,diagv);
1059:   }
1060:   return(0);
1061: }

1065: /*@C
1066:    MatCreateMPIBDiag - Creates a sparse parallel matrix in MPIBDiag format.

1068:    Collective on MPI_Comm

1070:    Input Parameters:
1071: +  comm - MPI communicator
1072: .  m - number of local rows (or PETSC_DECIDE to have calculated if M is given)
1073: .  M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
1074: .  N - number of columns (local and global)
1075: .  nd - number of block diagonals (global) (optional)
1076: .  bs - each element of a diagonal is an bs x bs dense matrix
1077: .  diag - optional array of block diagonal numbers (length nd).
1078:    For a matrix element A[i,j], where i=row and j=column, the
1079:    diagonal number is
1080: $     diag = i/bs - j/bs  (integer division)
1081:    Set diag=PETSC_NULL on input for PETSc to dynamically allocate memory as 
1082:    needed (expensive).
1083: -  diagv  - pointer to actual diagonals (in same order as diag array), 
1084:    if allocated by user. Otherwise, set diagv=PETSC_NULL on input for PETSc
1085:    to control memory allocation.

1087:    Output Parameter:
1088: .  A - the matrix 

1090:    Options Database Keys:
1091: .  -mat_block_size <bs> - Sets blocksize
1092: .  -mat_bdiag_diags <s1,s2,s3,...> - Sets diagonal numbers

1094:    Notes:
1095:    If PETSC_DECIDE or  PETSC_DETERMINE is used for a particular argument on one processor
1096:    than it must be used on all processors that share the object for that argument.

1098:    The parallel matrix is partitioned across the processors by rows, where
1099:    each local rectangular matrix is stored in the uniprocessor block 
1100:    diagonal format.  See the users manual for further details.

1102:    The user MUST specify either the local or global numbers of rows
1103:    (possibly both).

1105:    The case bs=1 (conventional diagonal storage) is implemented as
1106:    a special case.

1108:    Fortran Notes:
1109:    Fortran programmers cannot set diagv; this variable is ignored.

1111:    Level: intermediate

1113: .keywords: matrix, block, diagonal, parallel, sparse

1115: .seealso: MatCreate(), MatCreateSeqBDiag(), MatSetValues()
1116: @*/
1117: PetscErrorCode  MatCreateMPIBDiag(MPI_Comm comm,PetscInt m,PetscInt M,PetscInt N,PetscInt nd,PetscInt bs,const PetscInt diag[],PetscScalar *diagv[],Mat *A)
1118: {
1120:   PetscMPIInt    size;

1123:   MatCreate(comm,A);
1124:   MatSetSizes(*A,m,m,M,N);
1125:   MPI_Comm_size(comm,&size);
1126:   if (size > 1) {
1127:     MatSetType(*A,MATMPIBDIAG);
1128:     MatMPIBDiagSetPreallocation(*A,nd,bs,diag,diagv);
1129:   } else {
1130:     MatSetType(*A,MATSEQBDIAG);
1131:     MatSeqBDiagSetPreallocation(*A,nd,bs,diag,diagv);
1132:   }
1133:   return(0);
1134: }

1138: /*@C
1139:    MatBDiagGetData - Gets the data for the block diagonal matrix format.
1140:    For the parallel case, this returns information for the local submatrix.

1142:    Input Parameters:
1143: .  mat - the matrix, stored in block diagonal format.

1145:    Not Collective

1147:    Output Parameters:
1148: +  m - number of rows
1149: .  n - number of columns
1150: .  nd - number of block diagonals
1151: .  bs - each element of a diagonal is an bs x bs dense matrix
1152: .  bdlen - array of total block lengths of block diagonals
1153: .  diag - optional array of block diagonal numbers (length nd).
1154:    For a matrix element A[i,j], where i=row and j=column, the
1155:    diagonal number is
1156: $     diag = i/bs - j/bs  (integer division)
1157:    Set diag=PETSC_NULL on input for PETSc to dynamically allocate memory as 
1158:    needed (expensive).
1159: -  diagv - pointer to actual diagonals (in same order as diag array), 

1161:    Level: advanced

1163:    Notes:
1164:    See the users manual for further details regarding this storage format.

1166: .keywords: matrix, block, diagonal, get, data

1168: .seealso: MatCreateSeqBDiag(), MatCreateMPIBDiag()
1169: @*/
1170: PetscErrorCode  MatBDiagGetData(Mat mat,PetscInt *nd,PetscInt *bs,PetscInt *diag[],PetscInt *bdlen[],PetscScalar ***diagv)
1171: {
1172:   Mat_MPIBDiag   *pdmat;
1173:   Mat_SeqBDiag   *dmat = 0;
1174:   PetscTruth     isseq,ismpi;

1179:   PetscTypeCompare((PetscObject)mat,MATSEQBDIAG,&isseq);
1180:   PetscTypeCompare((PetscObject)mat,MATMPIBDIAG,&ismpi);
1181:   if (isseq) {
1182:     dmat = (Mat_SeqBDiag*)mat->data;
1183:   } else if (ismpi) {
1184:     pdmat = (Mat_MPIBDiag*)mat->data;
1185:     dmat = (Mat_SeqBDiag*)pdmat->A->data;
1186:   } else SETERRQ(PETSC_ERR_SUP,"Valid only for MATSEQBDIAG and MATMPIBDIAG formats");
1187:   *nd    = dmat->nd;
1188:   *bs    = mat->rmap.bs;
1189:   *diag  = dmat->diag;
1190:   *bdlen = dmat->bdlen;
1191:   *diagv = dmat->diagv;
1192:   return(0);
1193: }

1195:  #include petscsys.h

1199: PetscErrorCode MatLoad_MPIBDiag(PetscViewer viewer, MatType type,Mat *newmat)
1200: {
1201:   Mat            A;
1202:   PetscScalar    *vals,*svals;
1203:   MPI_Comm       comm = ((PetscObject)viewer)->comm;
1204:   MPI_Status     status;
1206:   int            fd;
1207:   PetscMPIInt    tag = ((PetscObject)viewer)->tag,rank,size,*sndcounts = 0,*rowners,maxnz,mm;
1208:   PetscInt       bs,i,nz,j,rstart,rend,*cols;
1209:   PetscInt       header[4],*rowlengths = 0,M,N,m,Mbs;
1210:   PetscInt       *ourlens,*procsnz = 0,jj,*mycols,*smycols;
1211:   PetscInt       extra_rows;

1214:   MPI_Comm_size(comm,&size);
1215:   MPI_Comm_rank(comm,&rank);
1216:   if (!rank) {
1217:     PetscViewerBinaryGetDescriptor(viewer,&fd);
1218:     PetscBinaryRead(fd,(char *)header,4,PETSC_INT);
1219:     if (header[0] != MAT_FILE_COOKIE) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"not matrix object");
1220:     if (header[3] < 0) {
1221:       SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format,cannot load as MPIBDiag");
1222:     }
1223:   }
1224:   MPI_Bcast(header+1,3,MPIU_INT,0,comm);
1225:   M = header[1]; N = header[2];

1227:   bs = 1;   /* uses a block size of 1 by default; */
1228:   PetscOptionsGetInt(PETSC_NULL,"-matload_block_size",&bs,PETSC_NULL);

1230:   /* 
1231:      This code adds extra rows to make sure the number of rows is 
1232:      divisible by the blocksize
1233:   */
1234:   Mbs        = M/bs;
1235:   extra_rows = bs - M + bs*(Mbs);
1236:   if (extra_rows == bs) extra_rows = 0;
1237:   else                  Mbs++;
1238:   if (extra_rows && !rank) {
1239:     PetscInfo(viewer,"Padding loaded matrix to match blocksize\n");
1240:   }

1242:   /* determine ownership of all rows */
1243:   m          = bs*(Mbs/size + ((Mbs % size) > rank));
1244:   PetscMalloc((size+2)*sizeof(PetscInt),&rowners);
1245:   mm         = (PetscMPIInt)m;
1246:   MPI_Allgather(&mm,1,MPI_INT,rowners+1,1,MPI_INT,comm);
1247:   rowners[0] = 0;
1248:   for (i=2; i<=size; i++) {
1249:     rowners[i] += rowners[i-1];
1250:   }
1251:   rstart = rowners[rank];
1252:   rend   = rowners[rank+1];

1254:   /* distribute row lengths to all processors */
1255:   PetscMalloc((rend-rstart)*sizeof(PetscInt),&ourlens);
1256:   if (!rank) {
1257:     PetscMalloc((M+extra_rows)*sizeof(PetscInt),&rowlengths);
1258:     PetscBinaryRead(fd,rowlengths,M,PETSC_INT);
1259:     for (i=0; i<extra_rows; i++) rowlengths[M+i] = 1;
1260:     PetscMalloc(size*sizeof(PetscMPIInt),&sndcounts);
1261:     for (i=0; i<size; i++) sndcounts[i] = rowners[i+1] - rowners[i];
1262:     MPI_Scatterv(rowlengths,sndcounts,rowners,MPIU_INT,ourlens,rend-rstart,MPIU_INT,0,comm);
1263:     PetscFree(sndcounts);
1264:   } else {
1265:     MPI_Scatterv(0,0,0,MPIU_INT,ourlens,rend-rstart,MPIU_INT,0,comm);
1266:   }

1268:   if (!rank) {
1269:     /* calculate the number of nonzeros on each processor */
1270:     PetscMalloc(size*sizeof(PetscInt),&procsnz);
1271:     PetscMemzero(procsnz,size*sizeof(PetscInt));
1272:     for (i=0; i<size; i++) {
1273:       for (j=rowners[i]; j<rowners[i+1]; j++) {
1274:         procsnz[i] += rowlengths[j];
1275:       }
1276:     }
1277:     PetscFree(rowlengths);

1279:     /* determine max buffer needed and allocate it */
1280:     maxnz = 0;
1281:     for (i=0; i<size; i++) {
1282:       maxnz = PetscMax(maxnz,procsnz[i]);
1283:     }
1284:     PetscMalloc(maxnz*sizeof(PetscInt),&cols);

1286:     /* read in my part of the matrix column indices  */
1287:     nz   = procsnz[0];
1288:     PetscMalloc(nz*sizeof(PetscInt),&mycols);
1289:     if (size == 1)  nz -= extra_rows;
1290:     PetscBinaryRead(fd,mycols,nz,PETSC_INT);
1291:     if (size == 1)  for (i=0; i<extra_rows; i++) { mycols[nz+i] = M+i; }

1293:     /* read in every one elses and ship off */
1294:     for (i=1; i<size-1; i++) {
1295:       nz   = procsnz[i];
1296:       PetscBinaryRead(fd,cols,nz,PETSC_INT);
1297:       MPI_Send(cols,nz,MPIU_INT,i,tag,comm);
1298:     }
1299:     /* read in the stuff for the last proc */
1300:     if (size != 1) {
1301:       nz   = procsnz[size-1] - extra_rows;  /* the extra rows are not on the disk */
1302:       PetscBinaryRead(fd,cols,nz,PETSC_INT);
1303:       for (i=0; i<extra_rows; i++) cols[nz+i] = M+i;
1304:       MPI_Send(cols,nz+extra_rows,MPIU_INT,size-1,tag,comm);
1305:     }
1306:     PetscFree(cols);
1307:   } else {
1308:     /* determine buffer space needed for message */
1309:     nz = 0;
1310:     for (i=0; i<m; i++) {
1311:       nz += ourlens[i];
1312:     }
1313:     PetscMalloc(nz*sizeof(PetscInt),&mycols);

1315:     /* receive message of column indices*/
1316:     MPI_Recv(mycols,nz,MPIU_INT,0,tag,comm,&status);
1317:     MPI_Get_count(&status,MPIU_INT,&maxnz);
1318:     if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file");
1319:   }

1321:   MatCreate(comm,newmat);
1322:   MatSetSizes(*newmat,m,m,M+extra_rows,N+extra_rows);
1323:   MatSetType(*newmat,type);
1324:   MatMPIBDiagSetPreallocation(*newmat,0,bs,PETSC_NULL,PETSC_NULL);
1325:   A = *newmat;

1327:   if (!rank) {
1328:     PetscMalloc(maxnz*sizeof(PetscScalar),&vals);

1330:     /* read in my part of the matrix numerical values  */
1331:     nz = procsnz[0];
1332:     if (size == 1)  nz -= extra_rows;
1333:     PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);
1334:     if (size == 1)  for (i=0; i<extra_rows; i++) { vals[nz+i] = 1.0; }

1336:     /* insert into matrix */
1337:     jj      = rstart;
1338:     smycols = mycols;
1339:     svals   = vals;
1340:     for (i=0; i<m; i++) {
1341:       MatSetValues(A,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);
1342:       smycols += ourlens[i];
1343:       svals   += ourlens[i];
1344:       jj++;
1345:     }

1347:     /* read in other processors (except the last one) and ship out */
1348:     for (i=1; i<size-1; i++) {
1349:       nz   = procsnz[i];
1350:       PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);
1351:       MPI_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)A)->tag,comm);
1352:     }
1353:     /* the last proc */
1354:     if (size != 1){
1355:       nz   = procsnz[i] - extra_rows;
1356:       PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);
1357:       for (i=0; i<extra_rows; i++) vals[nz+i] = 1.0;
1358:       MPI_Send(vals,nz+extra_rows,MPIU_SCALAR,size-1,((PetscObject)A)->tag,comm);
1359:     }
1360:     PetscFree(procsnz);
1361:   } else {
1362:     /* receive numeric values */
1363:     PetscMalloc(nz*sizeof(PetscScalar),&vals);

1365:     /* receive message of values*/
1366:     MPI_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)A)->tag,comm,&status);
1367:     MPI_Get_count(&status,MPIU_SCALAR,&maxnz);
1368:     if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file");

1370:     /* insert into matrix */
1371:     jj      = rstart;
1372:     smycols = mycols;
1373:     svals   = vals;
1374:     for (i=0; i<m; i++) {
1375:       MatSetValues(A,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);
1376:       smycols += ourlens[i];
1377:       svals   += ourlens[i];
1378:       jj++;
1379:     }
1380:   }
1381:   PetscFree(ourlens);
1382:   PetscFree(vals);
1383:   PetscFree(mycols);
1384:   PetscFree(rowners);

1386:   MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);
1387:   MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);
1388:   return(0);
1389: }