Actual source code: mpidense.c

petsc-master 2017-10-19
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  2: /*
  3:    Basic functions for basic parallel dense matrices.
  4: */


  7:  #include <../src/mat/impls/dense/mpi/mpidense.h>
  8:  #include <../src/mat/impls/aij/mpi/mpiaij.h>
  9:  #include <petscblaslapack.h>

 11: /*@

 13:       MatDenseGetLocalMatrix - For a MATMPIDENSE or MATSEQDENSE matrix returns the sequential
 14:               matrix that represents the operator. For sequential matrices it returns itself.

 16:     Input Parameter:
 17: .      A - the Seq or MPI dense matrix

 19:     Output Parameter:
 20: .      B - the inner matrix

 22:     Level: intermediate

 24: @*/
 25: PetscErrorCode MatDenseGetLocalMatrix(Mat A,Mat *B)
 26: {
 27:   Mat_MPIDense   *mat = (Mat_MPIDense*)A->data;
 29:   PetscBool      flg;

 32:   PetscObjectTypeCompare((PetscObject)A,MATMPIDENSE,&flg);
 33:   if (flg) *B = mat->A;
 34:   else *B = A;
 35:   return(0);
 36: }

 38: PetscErrorCode MatGetRow_MPIDense(Mat A,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
 39: {
 40:   Mat_MPIDense   *mat = (Mat_MPIDense*)A->data;
 42:   PetscInt       lrow,rstart = A->rmap->rstart,rend = A->rmap->rend;

 45:   if (row < rstart || row >= rend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"only local rows");
 46:   lrow = row - rstart;
 47:   MatGetRow(mat->A,lrow,nz,(const PetscInt**)idx,(const PetscScalar**)v);
 48:   return(0);
 49: }

 51: PetscErrorCode MatRestoreRow_MPIDense(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
 52: {

 56:   if (idx) {PetscFree(*idx);}
 57:   if (v) {PetscFree(*v);}
 58:   return(0);
 59: }

 61: PetscErrorCode  MatGetDiagonalBlock_MPIDense(Mat A,Mat *a)
 62: {
 63:   Mat_MPIDense   *mdn = (Mat_MPIDense*)A->data;
 65:   PetscInt       m = A->rmap->n,rstart = A->rmap->rstart;
 66:   PetscScalar    *array;
 67:   MPI_Comm       comm;
 68:   Mat            B;

 71:   if (A->rmap->N != A->cmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only square matrices supported.");

 73:   PetscObjectQuery((PetscObject)A,"DiagonalBlock",(PetscObject*)&B);
 74:   if (!B) {
 75:     PetscObjectGetComm((PetscObject)(mdn->A),&comm);
 76:     MatCreate(comm,&B);
 77:     MatSetSizes(B,m,m,m,m);
 78:     MatSetType(B,((PetscObject)mdn->A)->type_name);
 79:     MatDenseGetArray(mdn->A,&array);
 80:     MatSeqDenseSetPreallocation(B,array+m*rstart);
 81:     MatDenseRestoreArray(mdn->A,&array);
 82:     MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
 83:     MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);
 84:     PetscObjectCompose((PetscObject)A,"DiagonalBlock",(PetscObject)B);
 85:     *a   = B;
 86:     MatDestroy(&B);
 87:   } else *a = B;
 88:   return(0);
 89: }

 91: PetscErrorCode MatSetValues_MPIDense(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],const PetscScalar v[],InsertMode addv)
 92: {
 93:   Mat_MPIDense   *A = (Mat_MPIDense*)mat->data;
 95:   PetscInt       i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend,row;
 96:   PetscBool      roworiented = A->roworiented;

 99:   for (i=0; i<m; i++) {
100:     if (idxm[i] < 0) continue;
101:     if (idxm[i] >= mat->rmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large");
102:     if (idxm[i] >= rstart && idxm[i] < rend) {
103:       row = idxm[i] - rstart;
104:       if (roworiented) {
105:         MatSetValues(A->A,1,&row,n,idxn,v+i*n,addv);
106:       } else {
107:         for (j=0; j<n; j++) {
108:           if (idxn[j] < 0) continue;
109:           if (idxn[j] >= mat->cmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large");
110:           MatSetValues(A->A,1,&row,1,&idxn[j],v+i+j*m,addv);
111:         }
112:       }
113:     } else if (!A->donotstash) {
114:       mat->assembled = PETSC_FALSE;
115:       if (roworiented) {
116:         MatStashValuesRow_Private(&mat->stash,idxm[i],n,idxn,v+i*n,PETSC_FALSE);
117:       } else {
118:         MatStashValuesCol_Private(&mat->stash,idxm[i],n,idxn,v+i,m,PETSC_FALSE);
119:       }
120:     }
121:   }
122:   return(0);
123: }

125: PetscErrorCode MatGetValues_MPIDense(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[])
126: {
127:   Mat_MPIDense   *mdn = (Mat_MPIDense*)mat->data;
129:   PetscInt       i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend,row;

132:   for (i=0; i<m; i++) {
133:     if (idxm[i] < 0) continue; /* SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row"); */
134:     if (idxm[i] >= mat->rmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large");
135:     if (idxm[i] >= rstart && idxm[i] < rend) {
136:       row = idxm[i] - rstart;
137:       for (j=0; j<n; j++) {
138:         if (idxn[j] < 0) continue; /* SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column"); */
139:         if (idxn[j] >= mat->cmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large");
140:         MatGetValues(mdn->A,1,&row,1,&idxn[j],v+i*n+j);
141:       }
142:     } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local values currently supported");
143:   }
144:   return(0);
145: }

147: static PetscErrorCode MatDenseGetArray_MPIDense(Mat A,PetscScalar *array[])
148: {
149:   Mat_MPIDense   *a = (Mat_MPIDense*)A->data;

153:   MatDenseGetArray(a->A,array);
154:   return(0);
155: }

157: static PetscErrorCode MatDensePlaceArray_MPIDense(Mat A,const PetscScalar array[])
158: {
159:   Mat_MPIDense   *a = (Mat_MPIDense*)A->data;

163:   MatDensePlaceArray(a->A,array);
164:   return(0);
165: }

167: static PetscErrorCode MatDenseResetArray_MPIDense(Mat A)
168: {
169:   Mat_MPIDense   *a = (Mat_MPIDense*)A->data;

173:   MatDenseResetArray(a->A);
174:   return(0);
175: }

177: static PetscErrorCode MatCreateSubMatrix_MPIDense(Mat A,IS isrow,IS iscol,MatReuse scall,Mat *B)
178: {
179:   Mat_MPIDense   *mat  = (Mat_MPIDense*)A->data,*newmatd;
180:   Mat_SeqDense   *lmat = (Mat_SeqDense*)mat->A->data;
182:   PetscInt       i,j,rstart,rend,nrows,ncols,Ncols,nlrows,nlcols;
183:   const PetscInt *irow,*icol;
184:   PetscScalar    *av,*bv,*v = lmat->v;
185:   Mat            newmat;
186:   IS             iscol_local;

189:   ISAllGather(iscol,&iscol_local);
190:   ISGetIndices(isrow,&irow);
191:   ISGetIndices(iscol_local,&icol);
192:   ISGetLocalSize(isrow,&nrows);
193:   ISGetLocalSize(iscol,&ncols);
194:   ISGetSize(iscol,&Ncols); /* global number of columns, size of iscol_local */

196:   /* No parallel redistribution currently supported! Should really check each index set
197:      to comfirm that it is OK.  ... Currently supports only submatrix same partitioning as
198:      original matrix! */

200:   MatGetLocalSize(A,&nlrows,&nlcols);
201:   MatGetOwnershipRange(A,&rstart,&rend);

203:   /* Check submatrix call */
204:   if (scall == MAT_REUSE_MATRIX) {
205:     /* SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Reused submatrix wrong size"); */
206:     /* Really need to test rows and column sizes! */
207:     newmat = *B;
208:   } else {
209:     /* Create and fill new matrix */
210:     MatCreate(PetscObjectComm((PetscObject)A),&newmat);
211:     MatSetSizes(newmat,nrows,ncols,PETSC_DECIDE,Ncols);
212:     MatSetType(newmat,((PetscObject)A)->type_name);
213:     MatMPIDenseSetPreallocation(newmat,NULL);
214:   }

216:   /* Now extract the data pointers and do the copy, column at a time */
217:   newmatd = (Mat_MPIDense*)newmat->data;
218:   bv      = ((Mat_SeqDense*)newmatd->A->data)->v;

220:   for (i=0; i<Ncols; i++) {
221:     av = v + ((Mat_SeqDense*)mat->A->data)->lda*icol[i];
222:     for (j=0; j<nrows; j++) {
223:       *bv++ = av[irow[j] - rstart];
224:     }
225:   }

227:   /* Assemble the matrices so that the correct flags are set */
228:   MatAssemblyBegin(newmat,MAT_FINAL_ASSEMBLY);
229:   MatAssemblyEnd(newmat,MAT_FINAL_ASSEMBLY);

231:   /* Free work space */
232:   ISRestoreIndices(isrow,&irow);
233:   ISRestoreIndices(iscol_local,&icol);
234:   ISDestroy(&iscol_local);
235:   *B   = newmat;
236:   return(0);
237: }

239: PetscErrorCode MatDenseRestoreArray_MPIDense(Mat A,PetscScalar *array[])
240: {
241:   Mat_MPIDense   *a = (Mat_MPIDense*)A->data;

245:   MatDenseRestoreArray(a->A,array);
246:   return(0);
247: }

249: PetscErrorCode MatAssemblyBegin_MPIDense(Mat mat,MatAssemblyType mode)
250: {
251:   Mat_MPIDense   *mdn = (Mat_MPIDense*)mat->data;
252:   MPI_Comm       comm;
254:   PetscInt       nstash,reallocs;
255:   InsertMode     addv;

258:   PetscObjectGetComm((PetscObject)mat,&comm);
259:   /* make sure all processors are either in INSERTMODE or ADDMODE */
260:   MPIU_Allreduce((PetscEnum*)&mat->insertmode,(PetscEnum*)&addv,1,MPIU_ENUM,MPI_BOR,comm);
261:   if (addv == (ADD_VALUES|INSERT_VALUES)) SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_ARG_WRONGSTATE,"Cannot mix adds/inserts on different procs");
262:   mat->insertmode = addv; /* in case this processor had no cache */

264:   MatStashScatterBegin_Private(mat,&mat->stash,mat->rmap->range);
265:   MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);
266:   PetscInfo2(mdn->A,"Stash has %D entries, uses %D mallocs.\n",nstash,reallocs);
267:   return(0);
268: }

270: PetscErrorCode MatAssemblyEnd_MPIDense(Mat mat,MatAssemblyType mode)
271: {
272:   Mat_MPIDense   *mdn=(Mat_MPIDense*)mat->data;
274:   PetscInt       i,*row,*col,flg,j,rstart,ncols;
275:   PetscMPIInt    n;
276:   PetscScalar    *val;

279:   /*  wait on receives */
280:   while (1) {
281:     MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);
282:     if (!flg) break;

284:     for (i=0; i<n;) {
285:       /* Now identify the consecutive vals belonging to the same row */
286:       for (j=i,rstart=row[j]; j<n; j++) {
287:         if (row[j] != rstart) break;
288:       }
289:       if (j < n) ncols = j-i;
290:       else       ncols = n-i;
291:       /* Now assemble all these values with a single function call */
292:       MatSetValues_MPIDense(mat,1,row+i,ncols,col+i,val+i,mat->insertmode);
293:       i    = j;
294:     }
295:   }
296:   MatStashScatterEnd_Private(&mat->stash);

298:   MatAssemblyBegin(mdn->A,mode);
299:   MatAssemblyEnd(mdn->A,mode);

301:   if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) {
302:     MatSetUpMultiply_MPIDense(mat);
303:   }
304:   return(0);
305: }

307: PetscErrorCode MatZeroEntries_MPIDense(Mat A)
308: {
310:   Mat_MPIDense   *l = (Mat_MPIDense*)A->data;

313:   MatZeroEntries(l->A);
314:   return(0);
315: }

317: /* the code does not do the diagonal entries correctly unless the
318:    matrix is square and the column and row owerships are identical.
319:    This is a BUG. The only way to fix it seems to be to access
320:    mdn->A and mdn->B directly and not through the MatZeroRows()
321:    routine.
322: */
323: PetscErrorCode MatZeroRows_MPIDense(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b)
324: {
325:   Mat_MPIDense      *l = (Mat_MPIDense*)A->data;
326:   PetscErrorCode    ierr;
327:   PetscInt          i,*owners = A->rmap->range;
328:   PetscInt          *sizes,j,idx,nsends;
329:   PetscInt          nmax,*svalues,*starts,*owner,nrecvs;
330:   PetscInt          *rvalues,tag = ((PetscObject)A)->tag,count,base,slen,*source;
331:   PetscInt          *lens,*lrows,*values;
332:   PetscMPIInt       n,imdex,rank = l->rank,size = l->size;
333:   MPI_Comm          comm;
334:   MPI_Request       *send_waits,*recv_waits;
335:   MPI_Status        recv_status,*send_status;
336:   PetscBool         found;
337:   const PetscScalar *xx;
338:   PetscScalar       *bb;

341:   PetscObjectGetComm((PetscObject)A,&comm);
342:   if (A->rmap->N != A->cmap->N) SETERRQ(comm,PETSC_ERR_SUP,"Only handles square matrices");
343:   if (A->rmap->n != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only handles matrices with identical column and row ownership");
344:   /*  first count number of contributors to each processor */
345:   PetscCalloc1(2*size,&sizes);
346:   PetscMalloc1(N+1,&owner);  /* see note*/
347:   for (i=0; i<N; i++) {
348:     idx   = rows[i];
349:     found = PETSC_FALSE;
350:     for (j=0; j<size; j++) {
351:       if (idx >= owners[j] && idx < owners[j+1]) {
352:         sizes[2*j]++; sizes[2*j+1] = 1; owner[i] = j; found = PETSC_TRUE; break;
353:       }
354:     }
355:     if (!found) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Index out of range");
356:   }
357:   nsends = 0;
358:   for (i=0; i<size; i++) nsends += sizes[2*i+1];

360:   /* inform other processors of number of messages and max length*/
361:   PetscMaxSum(comm,sizes,&nmax,&nrecvs);

363:   /* post receives:   */
364:   PetscMalloc1((nrecvs+1)*(nmax+1),&rvalues);
365:   PetscMalloc1(nrecvs+1,&recv_waits);
366:   for (i=0; i<nrecvs; i++) {
367:     MPI_Irecv(rvalues+nmax*i,nmax,MPIU_INT,MPI_ANY_SOURCE,tag,comm,recv_waits+i);
368:   }

370:   /* do sends:
371:       1) starts[i] gives the starting index in svalues for stuff going to
372:          the ith processor
373:   */
374:   PetscMalloc1(N+1,&svalues);
375:   PetscMalloc1(nsends+1,&send_waits);
376:   PetscMalloc1(size+1,&starts);

378:   starts[0] = 0;
379:   for (i=1; i<size; i++) starts[i] = starts[i-1] + sizes[2*i-2];
380:   for (i=0; i<N; i++) svalues[starts[owner[i]]++] = rows[i];

382:   starts[0] = 0;
383:   for (i=1; i<size+1; i++) starts[i] = starts[i-1] + sizes[2*i-2];
384:   count = 0;
385:   for (i=0; i<size; i++) {
386:     if (sizes[2*i+1]) {
387:       MPI_Isend(svalues+starts[i],sizes[2*i],MPIU_INT,i,tag,comm,send_waits+count++);
388:     }
389:   }
390:   PetscFree(starts);

392:   base = owners[rank];

394:   /*  wait on receives */
395:   PetscMalloc2(nrecvs,&lens,nrecvs,&source);
396:   count = nrecvs;
397:   slen  = 0;
398:   while (count) {
399:     MPI_Waitany(nrecvs,recv_waits,&imdex,&recv_status);
400:     /* unpack receives into our local space */
401:     MPI_Get_count(&recv_status,MPIU_INT,&n);

403:     source[imdex] = recv_status.MPI_SOURCE;
404:     lens[imdex]   = n;
405:     slen += n;
406:     count--;
407:   }
408:   PetscFree(recv_waits);

410:   /* move the data into the send scatter */
411:   PetscMalloc1(slen+1,&lrows);
412:   count = 0;
413:   for (i=0; i<nrecvs; i++) {
414:     values = rvalues + i*nmax;
415:     for (j=0; j<lens[i]; j++) {
416:       lrows[count++] = values[j] - base;
417:     }
418:   }
419:   PetscFree(rvalues);
420:   PetscFree2(lens,source);
421:   PetscFree(owner);
422:   PetscFree(sizes);

424:   /* fix right hand side if needed */
425:   if (x && b) {
426:     VecGetArrayRead(x,&xx);
427:     VecGetArray(b,&bb);
428:     for (i=0; i<slen; i++) {
429:       bb[lrows[i]] = diag*xx[lrows[i]];
430:     }
431:     VecRestoreArrayRead(x,&xx);
432:     VecRestoreArray(b,&bb);
433:   }

435:   /* actually zap the local rows */
436:   MatZeroRows(l->A,slen,lrows,0.0,0,0);
437:   if (diag != 0.0) {
438:     Mat_SeqDense *ll = (Mat_SeqDense*)l->A->data;
439:     PetscInt     m   = ll->lda, i;

441:     for (i=0; i<slen; i++) {
442:       ll->v[lrows[i] + m*(A->cmap->rstart + lrows[i])] = diag;
443:     }
444:   }
445:   PetscFree(lrows);

447:   /* wait on sends */
448:   if (nsends) {
449:     PetscMalloc1(nsends,&send_status);
450:     MPI_Waitall(nsends,send_waits,send_status);
451:     PetscFree(send_status);
452:   }
453:   PetscFree(send_waits);
454:   PetscFree(svalues);
455:   return(0);
456: }

458: PETSC_INTERN PetscErrorCode MatMult_SeqDense(Mat,Vec,Vec);
459: PETSC_INTERN PetscErrorCode MatMultAdd_SeqDense(Mat,Vec,Vec,Vec);
460: PETSC_INTERN PetscErrorCode MatMultTranspose_SeqDense(Mat,Vec,Vec);
461: PETSC_INTERN PetscErrorCode MatMultTransposeAdd_SeqDense(Mat,Vec,Vec,Vec);

463: PetscErrorCode MatMult_MPIDense(Mat mat,Vec xx,Vec yy)
464: {
465:   Mat_MPIDense   *mdn = (Mat_MPIDense*)mat->data;

469:   VecScatterBegin(mdn->Mvctx,xx,mdn->lvec,INSERT_VALUES,SCATTER_FORWARD);
470:   VecScatterEnd(mdn->Mvctx,xx,mdn->lvec,INSERT_VALUES,SCATTER_FORWARD);
471:   MatMult_SeqDense(mdn->A,mdn->lvec,yy);
472:   return(0);
473: }

475: PetscErrorCode MatMultAdd_MPIDense(Mat mat,Vec xx,Vec yy,Vec zz)
476: {
477:   Mat_MPIDense   *mdn = (Mat_MPIDense*)mat->data;

481:   VecScatterBegin(mdn->Mvctx,xx,mdn->lvec,INSERT_VALUES,SCATTER_FORWARD);
482:   VecScatterEnd(mdn->Mvctx,xx,mdn->lvec,INSERT_VALUES,SCATTER_FORWARD);
483:   MatMultAdd_SeqDense(mdn->A,mdn->lvec,yy,zz);
484:   return(0);
485: }

487: PetscErrorCode MatMultTranspose_MPIDense(Mat A,Vec xx,Vec yy)
488: {
489:   Mat_MPIDense   *a = (Mat_MPIDense*)A->data;
491:   PetscScalar    zero = 0.0;

494:   VecSet(yy,zero);
495:   MatMultTranspose_SeqDense(a->A,xx,a->lvec);
496:   VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
497:   VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
498:   return(0);
499: }

501: PetscErrorCode MatMultTransposeAdd_MPIDense(Mat A,Vec xx,Vec yy,Vec zz)
502: {
503:   Mat_MPIDense   *a = (Mat_MPIDense*)A->data;

507:   VecCopy(yy,zz);
508:   MatMultTranspose_SeqDense(a->A,xx,a->lvec);
509:   VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);
510:   VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);
511:   return(0);
512: }

514: PetscErrorCode MatGetDiagonal_MPIDense(Mat A,Vec v)
515: {
516:   Mat_MPIDense   *a    = (Mat_MPIDense*)A->data;
517:   Mat_SeqDense   *aloc = (Mat_SeqDense*)a->A->data;
519:   PetscInt       len,i,n,m = A->rmap->n,radd;
520:   PetscScalar    *x,zero = 0.0;

523:   VecSet(v,zero);
524:   VecGetArray(v,&x);
525:   VecGetSize(v,&n);
526:   if (n != A->rmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming mat and vec");
527:   len  = PetscMin(a->A->rmap->n,a->A->cmap->n);
528:   radd = A->rmap->rstart*m;
529:   for (i=0; i<len; i++) {
530:     x[i] = aloc->v[radd + i*m + i];
531:   }
532:   VecRestoreArray(v,&x);
533:   return(0);
534: }

536: PetscErrorCode MatDestroy_MPIDense(Mat mat)
537: {
538:   Mat_MPIDense   *mdn = (Mat_MPIDense*)mat->data;

542: #if defined(PETSC_USE_LOG)
543:   PetscLogObjectState((PetscObject)mat,"Rows=%D, Cols=%D",mat->rmap->N,mat->cmap->N);
544: #endif
545:   MatStashDestroy_Private(&mat->stash);
546:   MatDestroy(&mdn->A);
547:   VecDestroy(&mdn->lvec);
548:   VecScatterDestroy(&mdn->Mvctx);

550:   PetscFree(mat->data);
551:   PetscObjectChangeTypeName((PetscObject)mat,0);

553:   PetscObjectComposeFunction((PetscObject)mat,"MatDenseGetArray_C",NULL);
554:   PetscObjectComposeFunction((PetscObject)mat,"MatDensePlaceArray_C",NULL);
555:   PetscObjectComposeFunction((PetscObject)mat,"MatDenseResetArray_C",NULL);

557:   PetscObjectComposeFunction((PetscObject)mat,"MatDenseRestoreArray_C",NULL);
558: #if defined(PETSC_HAVE_ELEMENTAL)
559:   PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpidense_elemental_C",NULL);
560: #endif
561:   PetscObjectComposeFunction((PetscObject)mat,"MatMPIDenseSetPreallocation_C",NULL);
562:   PetscObjectComposeFunction((PetscObject)mat,"MatMatMult_mpiaij_mpidense_C",NULL);
563:   PetscObjectComposeFunction((PetscObject)mat,"MatMatMultSymbolic_mpiaij_mpidense_C",NULL);
564:   PetscObjectComposeFunction((PetscObject)mat,"MatMatMultNumeric_mpiaij_mpidense_C",NULL);
565:   PetscObjectComposeFunction((PetscObject)mat,"MatTransposeMatMult_mpiaij_mpidense_C",NULL);
566:   PetscObjectComposeFunction((PetscObject)mat,"MatTransposeMatMultSymbolic_mpiaij_mpidense_C",NULL);
567:   PetscObjectComposeFunction((PetscObject)mat,"MatTransposeMatMultNumeric_mpiaij_mpidense_C",NULL);
568:   return(0);
569: }

571: static PetscErrorCode MatView_MPIDense_Binary(Mat mat,PetscViewer viewer)
572: {
573:   Mat_MPIDense      *mdn = (Mat_MPIDense*)mat->data;
574:   PetscErrorCode    ierr;
575:   PetscViewerFormat format;
576:   int               fd;
577:   PetscInt          header[4],mmax,N = mat->cmap->N,i,j,m,k;
578:   PetscMPIInt       rank,tag  = ((PetscObject)viewer)->tag,size;
579:   PetscScalar       *work,*v,*vv;
580:   Mat_SeqDense      *a = (Mat_SeqDense*)mdn->A->data;

583:   if (mdn->size == 1) {
584:     MatView(mdn->A,viewer);
585:   } else {
586:     PetscViewerBinaryGetDescriptor(viewer,&fd);
587:     MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);
588:     MPI_Comm_size(PetscObjectComm((PetscObject)mat),&size);

590:     PetscViewerGetFormat(viewer,&format);
591:     if (format == PETSC_VIEWER_NATIVE) {

593:       if (!rank) {
594:         /* store the matrix as a dense matrix */
595:         header[0] = MAT_FILE_CLASSID;
596:         header[1] = mat->rmap->N;
597:         header[2] = N;
598:         header[3] = MATRIX_BINARY_FORMAT_DENSE;
599:         PetscBinaryWrite(fd,header,4,PETSC_INT,PETSC_TRUE);

601:         /* get largest work array needed for transposing array */
602:         mmax = mat->rmap->n;
603:         for (i=1; i<size; i++) {
604:           mmax = PetscMax(mmax,mat->rmap->range[i+1] - mat->rmap->range[i]);
605:         }
606:         PetscMalloc1(mmax*N,&work);

608:         /* write out local array, by rows */
609:         m = mat->rmap->n;
610:         v = a->v;
611:         for (j=0; j<N; j++) {
612:           for (i=0; i<m; i++) {
613:             work[j + i*N] = *v++;
614:           }
615:         }
616:         PetscBinaryWrite(fd,work,m*N,PETSC_SCALAR,PETSC_FALSE);
617:         /* get largest work array to receive messages from other processes, excludes process zero */
618:         mmax = 0;
619:         for (i=1; i<size; i++) {
620:           mmax = PetscMax(mmax,mat->rmap->range[i+1] - mat->rmap->range[i]);
621:         }
622:         PetscMalloc1(mmax*N,&vv);
623:         for (k = 1; k < size; k++) {
624:           v    = vv;
625:           m    = mat->rmap->range[k+1] - mat->rmap->range[k];
626:           MPIULong_Recv(v,m*N,MPIU_SCALAR,k,tag,PetscObjectComm((PetscObject)mat));

628:           for (j = 0; j < N; j++) {
629:             for (i = 0; i < m; i++) {
630:               work[j + i*N] = *v++;
631:             }
632:           }
633:           PetscBinaryWrite(fd,work,m*N,PETSC_SCALAR,PETSC_FALSE);
634:         }
635:         PetscFree(work);
636:         PetscFree(vv);
637:       } else {
638:         MPIULong_Send(a->v,mat->rmap->n*mat->cmap->N,MPIU_SCALAR,0,tag,PetscObjectComm((PetscObject)mat));
639:       }
640:     } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"To store a parallel dense matrix you must first call PetscViewerPushFormat(viewer,PETSC_VIEWER_NATIVE)");
641:   }
642:   return(0);
643: }

645: extern PetscErrorCode MatView_SeqDense(Mat,PetscViewer);
646:  #include <petscdraw.h>
647: static PetscErrorCode MatView_MPIDense_ASCIIorDraworSocket(Mat mat,PetscViewer viewer)
648: {
649:   Mat_MPIDense      *mdn = (Mat_MPIDense*)mat->data;
650:   PetscErrorCode    ierr;
651:   PetscMPIInt       rank = mdn->rank;
652:   PetscViewerType   vtype;
653:   PetscBool         iascii,isdraw;
654:   PetscViewer       sviewer;
655:   PetscViewerFormat format;

658:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
659:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);
660:   if (iascii) {
661:     PetscViewerGetType(viewer,&vtype);
662:     PetscViewerGetFormat(viewer,&format);
663:     if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) {
664:       MatInfo info;
665:       MatGetInfo(mat,MAT_LOCAL,&info);
666:       PetscViewerASCIIPushSynchronized(viewer);
667:       PetscViewerASCIISynchronizedPrintf(viewer,"  [%d] local rows %D nz %D nz alloced %D mem %D \n",rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(PetscInt)info.memory);
668:       PetscViewerFlush(viewer);
669:       PetscViewerASCIIPopSynchronized(viewer);
670:       VecScatterView(mdn->Mvctx,viewer);
671:       return(0);
672:     } else if (format == PETSC_VIEWER_ASCII_INFO) {
673:       return(0);
674:     }
675:   } else if (isdraw) {
676:     PetscDraw draw;
677:     PetscBool isnull;

679:     PetscViewerDrawGetDraw(viewer,0,&draw);
680:     PetscDrawIsNull(draw,&isnull);
681:     if (isnull) return(0);
682:   }

684:   {
685:     /* assemble the entire matrix onto first processor. */
686:     Mat         A;
687:     PetscInt    M = mat->rmap->N,N = mat->cmap->N,m,row,i,nz;
688:     PetscInt    *cols;
689:     PetscScalar *vals;

691:     MatCreate(PetscObjectComm((PetscObject)mat),&A);
692:     if (!rank) {
693:       MatSetSizes(A,M,N,M,N);
694:     } else {
695:       MatSetSizes(A,0,0,M,N);
696:     }
697:     /* Since this is a temporary matrix, MATMPIDENSE instead of ((PetscObject)A)->type_name here is probably acceptable. */
698:     MatSetType(A,MATMPIDENSE);
699:     MatMPIDenseSetPreallocation(A,NULL);
700:     PetscLogObjectParent((PetscObject)mat,(PetscObject)A);

702:     /* Copy the matrix ... This isn't the most efficient means,
703:        but it's quick for now */
704:     A->insertmode = INSERT_VALUES;

706:     row = mat->rmap->rstart;
707:     m   = mdn->A->rmap->n;
708:     for (i=0; i<m; i++) {
709:       MatGetRow_MPIDense(mat,row,&nz,&cols,&vals);
710:       MatSetValues_MPIDense(A,1,&row,nz,cols,vals,INSERT_VALUES);
711:       MatRestoreRow_MPIDense(mat,row,&nz,&cols,&vals);
712:       row++;
713:     }

715:     MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);
716:     MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);
717:     PetscViewerGetSubViewer(viewer,PETSC_COMM_SELF,&sviewer);
718:     if (!rank) {
719:       PetscObjectSetName((PetscObject)((Mat_MPIDense*)(A->data))->A,((PetscObject)mat)->name);
720:       MatView_SeqDense(((Mat_MPIDense*)(A->data))->A,sviewer);
721:     }
722:     PetscViewerRestoreSubViewer(viewer,PETSC_COMM_SELF,&sviewer);
723:     PetscViewerFlush(viewer);
724:     MatDestroy(&A);
725:   }
726:   return(0);
727: }

729: PetscErrorCode MatView_MPIDense(Mat mat,PetscViewer viewer)
730: {
732:   PetscBool      iascii,isbinary,isdraw,issocket;

735:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
736:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);
737:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSOCKET,&issocket);
738:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);

740:   if (iascii || issocket || isdraw) {
741:     MatView_MPIDense_ASCIIorDraworSocket(mat,viewer);
742:   } else if (isbinary) {
743:     MatView_MPIDense_Binary(mat,viewer);
744:   }
745:   return(0);
746: }

748: PetscErrorCode MatGetInfo_MPIDense(Mat A,MatInfoType flag,MatInfo *info)
749: {
750:   Mat_MPIDense   *mat = (Mat_MPIDense*)A->data;
751:   Mat            mdn  = mat->A;
753:   PetscReal      isend[5],irecv[5];

756:   info->block_size = 1.0;

758:   MatGetInfo(mdn,MAT_LOCAL,info);

760:   isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded;
761:   isend[3] = info->memory;  isend[4] = info->mallocs;
762:   if (flag == MAT_LOCAL) {
763:     info->nz_used      = isend[0];
764:     info->nz_allocated = isend[1];
765:     info->nz_unneeded  = isend[2];
766:     info->memory       = isend[3];
767:     info->mallocs      = isend[4];
768:   } else if (flag == MAT_GLOBAL_MAX) {
769:     MPIU_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)A));

771:     info->nz_used      = irecv[0];
772:     info->nz_allocated = irecv[1];
773:     info->nz_unneeded  = irecv[2];
774:     info->memory       = irecv[3];
775:     info->mallocs      = irecv[4];
776:   } else if (flag == MAT_GLOBAL_SUM) {
777:     MPIU_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)A));

779:     info->nz_used      = irecv[0];
780:     info->nz_allocated = irecv[1];
781:     info->nz_unneeded  = irecv[2];
782:     info->memory       = irecv[3];
783:     info->mallocs      = irecv[4];
784:   }
785:   info->fill_ratio_given  = 0; /* no parallel LU/ILU/Cholesky */
786:   info->fill_ratio_needed = 0;
787:   info->factor_mallocs    = 0;
788:   return(0);
789: }

791: PetscErrorCode MatSetOption_MPIDense(Mat A,MatOption op,PetscBool flg)
792: {
793:   Mat_MPIDense   *a = (Mat_MPIDense*)A->data;

797:   switch (op) {
798:   case MAT_NEW_NONZERO_LOCATIONS:
799:   case MAT_NEW_NONZERO_LOCATION_ERR:
800:   case MAT_NEW_NONZERO_ALLOCATION_ERR:
801:     MatCheckPreallocated(A,1);
802:     MatSetOption(a->A,op,flg);
803:     break;
804:   case MAT_ROW_ORIENTED:
805:     MatCheckPreallocated(A,1);
806:     a->roworiented = flg;
807:     MatSetOption(a->A,op,flg);
808:     break;
809:   case MAT_NEW_DIAGONALS:
810:   case MAT_KEEP_NONZERO_PATTERN:
811:   case MAT_USE_HASH_TABLE:
812:     PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);
813:     break;
814:   case MAT_IGNORE_OFF_PROC_ENTRIES:
815:     a->donotstash = flg;
816:     break;
817:   case MAT_SYMMETRIC:
818:   case MAT_STRUCTURALLY_SYMMETRIC:
819:   case MAT_HERMITIAN:
820:   case MAT_SYMMETRY_ETERNAL:
821:   case MAT_IGNORE_LOWER_TRIANGULAR:
822:     PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);
823:     break;
824:   default:
825:     SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %s",MatOptions[op]);
826:   }
827:   return(0);
828: }


831: PetscErrorCode MatDiagonalScale_MPIDense(Mat A,Vec ll,Vec rr)
832: {
833:   Mat_MPIDense      *mdn = (Mat_MPIDense*)A->data;
834:   Mat_SeqDense      *mat = (Mat_SeqDense*)mdn->A->data;
835:   const PetscScalar *l,*r;
836:   PetscScalar       x,*v;
837:   PetscErrorCode    ierr;
838:   PetscInt          i,j,s2a,s3a,s2,s3,m=mdn->A->rmap->n,n=mdn->A->cmap->n;

841:   MatGetLocalSize(A,&s2,&s3);
842:   if (ll) {
843:     VecGetLocalSize(ll,&s2a);
844:     if (s2a != s2) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Left scaling vector non-conforming local size, %d != %d.", s2a, s2);
845:     VecGetArrayRead(ll,&l);
846:     for (i=0; i<m; i++) {
847:       x = l[i];
848:       v = mat->v + i;
849:       for (j=0; j<n; j++) { (*v) *= x; v+= m;}
850:     }
851:     VecRestoreArrayRead(ll,&l);
852:     PetscLogFlops(n*m);
853:   }
854:   if (rr) {
855:     VecGetLocalSize(rr,&s3a);
856:     if (s3a != s3) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Right scaling vec non-conforming local size, %d != %d.", s3a, s3);
857:     VecScatterBegin(mdn->Mvctx,rr,mdn->lvec,INSERT_VALUES,SCATTER_FORWARD);
858:     VecScatterEnd(mdn->Mvctx,rr,mdn->lvec,INSERT_VALUES,SCATTER_FORWARD);
859:     VecGetArrayRead(mdn->lvec,&r);
860:     for (i=0; i<n; i++) {
861:       x = r[i];
862:       v = mat->v + i*m;
863:       for (j=0; j<m; j++) (*v++) *= x;
864:     }
865:     VecRestoreArrayRead(mdn->lvec,&r);
866:     PetscLogFlops(n*m);
867:   }
868:   return(0);
869: }

871: PetscErrorCode MatNorm_MPIDense(Mat A,NormType type,PetscReal *nrm)
872: {
873:   Mat_MPIDense   *mdn = (Mat_MPIDense*)A->data;
874:   Mat_SeqDense   *mat = (Mat_SeqDense*)mdn->A->data;
876:   PetscInt       i,j;
877:   PetscReal      sum = 0.0;
878:   PetscScalar    *v  = mat->v;

881:   if (mdn->size == 1) {
882:      MatNorm(mdn->A,type,nrm);
883:   } else {
884:     if (type == NORM_FROBENIUS) {
885:       for (i=0; i<mdn->A->cmap->n*mdn->A->rmap->n; i++) {
886:         sum += PetscRealPart(PetscConj(*v)*(*v)); v++;
887:       }
888:       MPIU_Allreduce(&sum,nrm,1,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)A));
889:       *nrm = PetscSqrtReal(*nrm);
890:       PetscLogFlops(2.0*mdn->A->cmap->n*mdn->A->rmap->n);
891:     } else if (type == NORM_1) {
892:       PetscReal *tmp,*tmp2;
893:       PetscMalloc2(A->cmap->N,&tmp,A->cmap->N,&tmp2);
894:       PetscMemzero(tmp,A->cmap->N*sizeof(PetscReal));
895:       PetscMemzero(tmp2,A->cmap->N*sizeof(PetscReal));
896:       *nrm = 0.0;
897:       v    = mat->v;
898:       for (j=0; j<mdn->A->cmap->n; j++) {
899:         for (i=0; i<mdn->A->rmap->n; i++) {
900:           tmp[j] += PetscAbsScalar(*v);  v++;
901:         }
902:       }
903:       MPIU_Allreduce(tmp,tmp2,A->cmap->N,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)A));
904:       for (j=0; j<A->cmap->N; j++) {
905:         if (tmp2[j] > *nrm) *nrm = tmp2[j];
906:       }
907:       PetscFree2(tmp,tmp2);
908:       PetscLogFlops(A->cmap->n*A->rmap->n);
909:     } else if (type == NORM_INFINITY) { /* max row norm */
910:       PetscReal ntemp;
911:       MatNorm(mdn->A,type,&ntemp);
912:       MPIU_Allreduce(&ntemp,nrm,1,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)A));
913:     } else SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"No support for two norm");
914:   }
915:   return(0);
916: }

918: PetscErrorCode MatTranspose_MPIDense(Mat A,MatReuse reuse,Mat *matout)
919: {
920:   Mat_MPIDense   *a    = (Mat_MPIDense*)A->data;
921:   Mat_SeqDense   *Aloc = (Mat_SeqDense*)a->A->data;
922:   Mat            B;
923:   PetscInt       M = A->rmap->N,N = A->cmap->N,m,n,*rwork,rstart = A->rmap->rstart;
925:   PetscInt       j,i;
926:   PetscScalar    *v;

929:   if (reuse == MAT_INPLACE_MATRIX  && M != N) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Supports square matrix only in-place");
930:   if (reuse == MAT_INITIAL_MATRIX || reuse == MAT_INPLACE_MATRIX) {
931:     MatCreate(PetscObjectComm((PetscObject)A),&B);
932:     MatSetSizes(B,A->cmap->n,A->rmap->n,N,M);
933:     MatSetType(B,((PetscObject)A)->type_name);
934:     MatMPIDenseSetPreallocation(B,NULL);
935:   } else {
936:     B = *matout;
937:   }

939:   m    = a->A->rmap->n; n = a->A->cmap->n; v = Aloc->v;
940:   PetscMalloc1(m,&rwork);
941:   for (i=0; i<m; i++) rwork[i] = rstart + i;
942:   for (j=0; j<n; j++) {
943:     MatSetValues(B,1,&j,m,rwork,v,INSERT_VALUES);
944:     v   += m;
945:   }
946:   PetscFree(rwork);
947:   MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
948:   MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);
949:   if (reuse == MAT_INITIAL_MATRIX || reuse == MAT_REUSE_MATRIX) {
950:     *matout = B;
951:   } else {
952:     MatHeaderMerge(A,&B);
953:   }
954:   return(0);
955: }


958: static PetscErrorCode MatDuplicate_MPIDense(Mat,MatDuplicateOption,Mat*);
959: extern PetscErrorCode MatScale_MPIDense(Mat,PetscScalar);

961: PetscErrorCode MatSetUp_MPIDense(Mat A)
962: {

966:    MatMPIDenseSetPreallocation(A,0);
967:   return(0);
968: }

970: PetscErrorCode MatAXPY_MPIDense(Mat Y,PetscScalar alpha,Mat X,MatStructure str)
971: {
973:   Mat_MPIDense   *A = (Mat_MPIDense*)Y->data, *B = (Mat_MPIDense*)X->data;

976:   MatAXPY(A->A,alpha,B->A,str);
977:   PetscObjectStateIncrease((PetscObject)Y);
978:   return(0);
979: }

981: PetscErrorCode  MatConjugate_MPIDense(Mat mat)
982: {
983:   Mat_MPIDense   *a = (Mat_MPIDense*)mat->data;

987:   MatConjugate(a->A);
988:   return(0);
989: }

991: PetscErrorCode MatRealPart_MPIDense(Mat A)
992: {
993:   Mat_MPIDense   *a = (Mat_MPIDense*)A->data;

997:   MatRealPart(a->A);
998:   return(0);
999: }

1001: PetscErrorCode MatImaginaryPart_MPIDense(Mat A)
1002: {
1003:   Mat_MPIDense   *a = (Mat_MPIDense*)A->data;

1007:   MatImaginaryPart(a->A);
1008:   return(0);
1009: }

1011: extern PetscErrorCode MatGetColumnNorms_SeqDense(Mat,NormType,PetscReal*);
1012: PetscErrorCode MatGetColumnNorms_MPIDense(Mat A,NormType type,PetscReal *norms)
1013: {
1015:   PetscInt       i,n;
1016:   Mat_MPIDense   *a = (Mat_MPIDense*) A->data;
1017:   PetscReal      *work;

1020:   MatGetSize(A,NULL,&n);
1021:   PetscMalloc1(n,&work);
1022:   MatGetColumnNorms_SeqDense(a->A,type,work);
1023:   if (type == NORM_2) {
1024:     for (i=0; i<n; i++) work[i] *= work[i];
1025:   }
1026:   if (type == NORM_INFINITY) {
1027:     MPIU_Allreduce(work,norms,n,MPIU_REAL,MPIU_MAX,A->hdr.comm);
1028:   } else {
1029:     MPIU_Allreduce(work,norms,n,MPIU_REAL,MPIU_SUM,A->hdr.comm);
1030:   }
1031:   PetscFree(work);
1032:   if (type == NORM_2) {
1033:     for (i=0; i<n; i++) norms[i] = PetscSqrtReal(norms[i]);
1034:   }
1035:   return(0);
1036: }

1038: static PetscErrorCode  MatSetRandom_MPIDense(Mat x,PetscRandom rctx)
1039: {
1040:   Mat_MPIDense   *d = (Mat_MPIDense*)x->data;
1042:   PetscScalar    *a;
1043:   PetscInt       m,n,i;

1046:   MatGetSize(d->A,&m,&n);
1047:   MatDenseGetArray(d->A,&a);
1048:   for (i=0; i<m*n; i++) {
1049:     PetscRandomGetValue(rctx,a+i);
1050:   }
1051:   MatDenseRestoreArray(d->A,&a);
1052:   return(0);
1053: }

1055: extern PetscErrorCode MatMatMultNumeric_MPIDense(Mat A,Mat,Mat);

1057: static PetscErrorCode MatMissingDiagonal_MPIDense(Mat A,PetscBool  *missing,PetscInt *d)
1058: {
1060:   *missing = PETSC_FALSE;
1061:   return(0);
1062: }

1064: /* -------------------------------------------------------------------*/
1065: static struct _MatOps MatOps_Values = { MatSetValues_MPIDense,
1066:                                         MatGetRow_MPIDense,
1067:                                         MatRestoreRow_MPIDense,
1068:                                         MatMult_MPIDense,
1069:                                 /*  4*/ MatMultAdd_MPIDense,
1070:                                         MatMultTranspose_MPIDense,
1071:                                         MatMultTransposeAdd_MPIDense,
1072:                                         0,
1073:                                         0,
1074:                                         0,
1075:                                 /* 10*/ 0,
1076:                                         0,
1077:                                         0,
1078:                                         0,
1079:                                         MatTranspose_MPIDense,
1080:                                 /* 15*/ MatGetInfo_MPIDense,
1081:                                         MatEqual_MPIDense,
1082:                                         MatGetDiagonal_MPIDense,
1083:                                         MatDiagonalScale_MPIDense,
1084:                                         MatNorm_MPIDense,
1085:                                 /* 20*/ MatAssemblyBegin_MPIDense,
1086:                                         MatAssemblyEnd_MPIDense,
1087:                                         MatSetOption_MPIDense,
1088:                                         MatZeroEntries_MPIDense,
1089:                                 /* 24*/ MatZeroRows_MPIDense,
1090:                                         0,
1091:                                         0,
1092:                                         0,
1093:                                         0,
1094:                                 /* 29*/ MatSetUp_MPIDense,
1095:                                         0,
1096:                                         0,
1097:                                         MatGetDiagonalBlock_MPIDense,
1098:                                         0,
1099:                                 /* 34*/ MatDuplicate_MPIDense,
1100:                                         0,
1101:                                         0,
1102:                                         0,
1103:                                         0,
1104:                                 /* 39*/ MatAXPY_MPIDense,
1105:                                         MatCreateSubMatrices_MPIDense,
1106:                                         0,
1107:                                         MatGetValues_MPIDense,
1108:                                         0,
1109:                                 /* 44*/ 0,
1110:                                         MatScale_MPIDense,
1111:                                         MatShift_Basic,
1112:                                         0,
1113:                                         0,
1114:                                 /* 49*/ MatSetRandom_MPIDense,
1115:                                         0,
1116:                                         0,
1117:                                         0,
1118:                                         0,
1119:                                 /* 54*/ 0,
1120:                                         0,
1121:                                         0,
1122:                                         0,
1123:                                         0,
1124:                                 /* 59*/ MatCreateSubMatrix_MPIDense,
1125:                                         MatDestroy_MPIDense,
1126:                                         MatView_MPIDense,
1127:                                         0,
1128:                                         0,
1129:                                 /* 64*/ 0,
1130:                                         0,
1131:                                         0,
1132:                                         0,
1133:                                         0,
1134:                                 /* 69*/ 0,
1135:                                         0,
1136:                                         0,
1137:                                         0,
1138:                                         0,
1139:                                 /* 74*/ 0,
1140:                                         0,
1141:                                         0,
1142:                                         0,
1143:                                         0,
1144:                                 /* 79*/ 0,
1145:                                         0,
1146:                                         0,
1147:                                         0,
1148:                                 /* 83*/ MatLoad_MPIDense,
1149:                                         0,
1150:                                         0,
1151:                                         0,
1152:                                         0,
1153:                                         0,
1154: #if defined(PETSC_HAVE_ELEMENTAL)
1155:                                 /* 89*/ MatMatMult_MPIDense_MPIDense,
1156:                                         MatMatMultSymbolic_MPIDense_MPIDense,
1157: #else
1158:                                 /* 89*/ 0,
1159:                                         0,
1160: #endif
1161:                                         MatMatMultNumeric_MPIDense,
1162:                                         0,
1163:                                         0,
1164:                                 /* 94*/ 0,
1165:                                         0,
1166:                                         0,
1167:                                         0,
1168:                                         0,
1169:                                 /* 99*/ 0,
1170:                                         0,
1171:                                         0,
1172:                                         MatConjugate_MPIDense,
1173:                                         0,
1174:                                 /*104*/ 0,
1175:                                         MatRealPart_MPIDense,
1176:                                         MatImaginaryPart_MPIDense,
1177:                                         0,
1178:                                         0,
1179:                                 /*109*/ 0,
1180:                                         0,
1181:                                         0,
1182:                                         0,
1183:                                         MatMissingDiagonal_MPIDense,
1184:                                 /*114*/ 0,
1185:                                         0,
1186:                                         0,
1187:                                         0,
1188:                                         0,
1189:                                 /*119*/ 0,
1190:                                         0,
1191:                                         0,
1192:                                         0,
1193:                                         0,
1194:                                 /*124*/ 0,
1195:                                         MatGetColumnNorms_MPIDense,
1196:                                         0,
1197:                                         0,
1198:                                         0,
1199:                                 /*129*/ 0,
1200:                                         MatTransposeMatMult_MPIDense_MPIDense,
1201:                                         MatTransposeMatMultSymbolic_MPIDense_MPIDense,
1202:                                         MatTransposeMatMultNumeric_MPIDense_MPIDense,
1203:                                         0,
1204:                                 /*134*/ 0,
1205:                                         0,
1206:                                         0,
1207:                                         0,
1208:                                         0,
1209:                                 /*139*/ 0,
1210:                                         0,
1211:                                         0
1212: };

1214: PetscErrorCode  MatMPIDenseSetPreallocation_MPIDense(Mat mat,PetscScalar *data)
1215: {
1216:   Mat_MPIDense   *a;

1220:   mat->preallocated = PETSC_TRUE;
1221:   /* Note:  For now, when data is specified above, this assumes the user correctly
1222:    allocates the local dense storage space.  We should add error checking. */

1224:   a       = (Mat_MPIDense*)mat->data;
1225:   PetscLayoutSetUp(mat->rmap);
1226:   PetscLayoutSetUp(mat->cmap);
1227:   a->nvec = mat->cmap->n;

1229:   MatCreate(PETSC_COMM_SELF,&a->A);
1230:   MatSetSizes(a->A,mat->rmap->n,mat->cmap->N,mat->rmap->n,mat->cmap->N);
1231:   MatSetType(a->A,MATSEQDENSE);
1232:   MatSeqDenseSetPreallocation(a->A,data);
1233:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->A);
1234:   return(0);
1235: }

1237: #if defined(PETSC_HAVE_ELEMENTAL)
1238: PETSC_INTERN PetscErrorCode MatConvert_MPIDense_Elemental(Mat A, MatType newtype,MatReuse reuse,Mat *newmat)
1239: {
1240:   Mat            mat_elemental;
1242:   PetscScalar    *v;
1243:   PetscInt       m=A->rmap->n,N=A->cmap->N,rstart=A->rmap->rstart,i,*rows,*cols;
1244: 
1246:   if (reuse == MAT_REUSE_MATRIX) {
1247:     mat_elemental = *newmat;
1248:     MatZeroEntries(*newmat);
1249:   } else {
1250:     MatCreate(PetscObjectComm((PetscObject)A), &mat_elemental);
1251:     MatSetSizes(mat_elemental,PETSC_DECIDE,PETSC_DECIDE,A->rmap->N,A->cmap->N);
1252:     MatSetType(mat_elemental,MATELEMENTAL);
1253:     MatSetUp(mat_elemental);
1254:     MatSetOption(mat_elemental,MAT_ROW_ORIENTED,PETSC_FALSE);
1255:   }

1257:   PetscMalloc2(m,&rows,N,&cols);
1258:   for (i=0; i<N; i++) cols[i] = i;
1259:   for (i=0; i<m; i++) rows[i] = rstart + i;
1260: 
1261:   /* PETSc-Elemental interaface uses axpy for setting off-processor entries, only ADD_VALUES is allowed */
1262:   MatDenseGetArray(A,&v);
1263:   MatSetValues(mat_elemental,m,rows,N,cols,v,ADD_VALUES);
1264:   MatAssemblyBegin(mat_elemental, MAT_FINAL_ASSEMBLY);
1265:   MatAssemblyEnd(mat_elemental, MAT_FINAL_ASSEMBLY);
1266:   MatDenseRestoreArray(A,&v);
1267:   PetscFree2(rows,cols);

1269:   if (reuse == MAT_INPLACE_MATRIX) {
1270:     MatHeaderReplace(A,&mat_elemental);
1271:   } else {
1272:     *newmat = mat_elemental;
1273:   }
1274:   return(0);
1275: }
1276: #endif

1278: PETSC_EXTERN PetscErrorCode MatCreate_MPIDense(Mat mat)
1279: {
1280:   Mat_MPIDense   *a;

1284:   PetscNewLog(mat,&a);
1285:   mat->data = (void*)a;
1286:   PetscMemcpy(mat->ops,&MatOps_Values,sizeof(struct _MatOps));

1288:   mat->insertmode = NOT_SET_VALUES;
1289:   MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&a->rank);
1290:   MPI_Comm_size(PetscObjectComm((PetscObject)mat),&a->size);

1292:   /* build cache for off array entries formed */
1293:   a->donotstash = PETSC_FALSE;

1295:   MatStashCreate_Private(PetscObjectComm((PetscObject)mat),1,&mat->stash);

1297:   /* stuff used for matrix vector multiply */
1298:   a->lvec        = 0;
1299:   a->Mvctx       = 0;
1300:   a->roworiented = PETSC_TRUE;

1302:   PetscObjectComposeFunction((PetscObject)mat,"MatDenseGetArray_C",MatDenseGetArray_MPIDense);
1303:   PetscObjectComposeFunction((PetscObject)mat,"MatDensePlaceArray_C",MatDensePlaceArray_MPIDense);
1304:   PetscObjectComposeFunction((PetscObject)mat,"MatDenseResetArray_C",MatDenseResetArray_MPIDense);
1305:   PetscObjectComposeFunction((PetscObject)mat,"MatDenseRestoreArray_C",MatDenseRestoreArray_MPIDense);
1306: #if defined(PETSC_HAVE_ELEMENTAL)
1307:   PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpidense_elemental_C",MatConvert_MPIDense_Elemental);
1308: #endif
1309:   PetscObjectComposeFunction((PetscObject)mat,"MatMPIDenseSetPreallocation_C",MatMPIDenseSetPreallocation_MPIDense);
1310:   PetscObjectComposeFunction((PetscObject)mat,"MatMatMult_mpiaij_mpidense_C",MatMatMult_MPIAIJ_MPIDense);
1311:   PetscObjectComposeFunction((PetscObject)mat,"MatMatMultSymbolic_mpiaij_mpidense_C",MatMatMultSymbolic_MPIAIJ_MPIDense);
1312:   PetscObjectComposeFunction((PetscObject)mat,"MatMatMultNumeric_mpiaij_mpidense_C",MatMatMultNumeric_MPIAIJ_MPIDense);

1314:   PetscObjectComposeFunction((PetscObject)mat,"MatTransposeMatMult_mpiaij_mpidense_C",MatTransposeMatMult_MPIAIJ_MPIDense);
1315:   PetscObjectComposeFunction((PetscObject)mat,"MatTransposeMatMultSymbolic_mpiaij_mpidense_C",MatTransposeMatMultSymbolic_MPIAIJ_MPIDense);
1316:   PetscObjectComposeFunction((PetscObject)mat,"MatTransposeMatMultNumeric_mpiaij_mpidense_C",MatTransposeMatMultNumeric_MPIAIJ_MPIDense);
1317:   PetscObjectChangeTypeName((PetscObject)mat,MATMPIDENSE);
1318:   return(0);
1319: }

1321: /*MC
1322:    MATDENSE - MATDENSE = "dense" - A matrix type to be used for dense matrices.

1324:    This matrix type is identical to MATSEQDENSE when constructed with a single process communicator,
1325:    and MATMPIDENSE otherwise.

1327:    Options Database Keys:
1328: . -mat_type dense - sets the matrix type to "dense" during a call to MatSetFromOptions()

1330:   Level: beginner


1333: .seealso: MatCreateMPIDense,MATSEQDENSE,MATMPIDENSE
1334: M*/

1336: /*@C
1337:    MatMPIDenseSetPreallocation - Sets the array used to store the matrix entries

1339:    Not collective

1341:    Input Parameters:
1342: .  B - the matrix
1343: -  data - optional location of matrix data.  Set data=NULL for PETSc
1344:    to control all matrix memory allocation.

1346:    Notes:
1347:    The dense format is fully compatible with standard Fortran 77
1348:    storage by columns.

1350:    The data input variable is intended primarily for Fortran programmers
1351:    who wish to allocate their own matrix memory space.  Most users should
1352:    set data=NULL.

1354:    Level: intermediate

1356: .keywords: matrix,dense, parallel

1358: .seealso: MatCreate(), MatCreateSeqDense(), MatSetValues()
1359: @*/
1360: PetscErrorCode  MatMPIDenseSetPreallocation(Mat B,PetscScalar *data)
1361: {

1365:   PetscTryMethod(B,"MatMPIDenseSetPreallocation_C",(Mat,PetscScalar*),(B,data));
1366:   return(0);
1367: }

1369: /*@
1370:    MatDensePlaceArray - Allows one to replace the array in a dense array with an
1371:    array provided by the user. This is useful to avoid copying an array
1372:    into a matrix

1374:    Not Collective

1376:    Input Parameters:
1377: +  mat - the matrix
1378: -  array - the array in column major order

1380:    Notes:
1381:    You can return to the original array with a call to MatDenseResetArray(). The user is responsible for freeing this array; it will not be
1382:    freed when the matrix is destroyed.

1384:    Level: developer

1386: .seealso: MatDenseGetArray(), MatDenseResetArray(), VecPlaceArray(), VecGetArray(), VecRestoreArray(), VecReplaceArray(), VecResetArray()

1388: @*/
1389: PetscErrorCode  MatDensePlaceArray(Mat mat,const PetscScalar array[])
1390: {
1393:   PetscUseMethod(mat,"MatDensePlaceArray_C",(Mat,const PetscScalar*),(mat,array));
1394:   PetscObjectStateIncrease((PetscObject)mat);
1395:   return(0);
1396: }

1398: /*@
1399:    MatDenseResetArray - Resets the matrix array to that it previously had before the call to MatDensePlaceArray()

1401:    Not Collective

1403:    Input Parameters:
1404: .  mat - the matrix

1406:    Notes:
1407:    You can only call this after a call to MatDensePlaceArray()

1409:    Level: developer

1411: .seealso: MatDenseGetArray(), MatDensePlaceArray(), VecPlaceArray(), VecGetArray(), VecRestoreArray(), VecReplaceArray(), VecResetArray()

1413: @*/
1414: PetscErrorCode  MatDenseResetArray(Mat mat)
1415: {
1418:   PetscUseMethod(mat,"MatDenseResetArray_C",(Mat),(mat));
1419:   PetscObjectStateIncrease((PetscObject)mat);
1420:   return(0);
1421: }

1423: /*@C
1424:    MatCreateDense - Creates a parallel matrix in dense format.

1426:    Collective on MPI_Comm

1428:    Input Parameters:
1429: +  comm - MPI communicator
1430: .  m - number of local rows (or PETSC_DECIDE to have calculated if M is given)
1431: .  n - number of local columns (or PETSC_DECIDE to have calculated if N is given)
1432: .  M - number of global rows (or PETSC_DECIDE to have calculated if m is given)
1433: .  N - number of global columns (or PETSC_DECIDE to have calculated if n is given)
1434: -  data - optional location of matrix data.  Set data=NULL (PETSC_NULL_SCALAR for Fortran users) for PETSc
1435:    to control all matrix memory allocation.

1437:    Output Parameter:
1438: .  A - the matrix

1440:    Notes:
1441:    The dense format is fully compatible with standard Fortran 77
1442:    storage by columns.

1444:    The data input variable is intended primarily for Fortran programmers
1445:    who wish to allocate their own matrix memory space.  Most users should
1446:    set data=NULL (PETSC_NULL_SCALAR for Fortran users).

1448:    The user MUST specify either the local or global matrix dimensions
1449:    (possibly both).

1451:    Level: intermediate

1453: .keywords: matrix,dense, parallel

1455: .seealso: MatCreate(), MatCreateSeqDense(), MatSetValues()
1456: @*/
1457: PetscErrorCode  MatCreateDense(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,PetscScalar *data,Mat *A)
1458: {
1460:   PetscMPIInt    size;

1463:   MatCreate(comm,A);
1464:   MatSetSizes(*A,m,n,M,N);
1465:   MPI_Comm_size(comm,&size);
1466:   if (size > 1) {
1467:     MatSetType(*A,MATMPIDENSE);
1468:     MatMPIDenseSetPreallocation(*A,data);
1469:     if (data) {  /* user provided data array, so no need to assemble */
1470:       MatSetUpMultiply_MPIDense(*A);
1471:       (*A)->assembled = PETSC_TRUE;
1472:     }
1473:   } else {
1474:     MatSetType(*A,MATSEQDENSE);
1475:     MatSeqDenseSetPreallocation(*A,data);
1476:   }
1477:   return(0);
1478: }

1480: static PetscErrorCode MatDuplicate_MPIDense(Mat A,MatDuplicateOption cpvalues,Mat *newmat)
1481: {
1482:   Mat            mat;
1483:   Mat_MPIDense   *a,*oldmat = (Mat_MPIDense*)A->data;

1487:   *newmat = 0;
1488:   MatCreate(PetscObjectComm((PetscObject)A),&mat);
1489:   MatSetSizes(mat,A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N);
1490:   MatSetType(mat,((PetscObject)A)->type_name);
1491:   a       = (Mat_MPIDense*)mat->data;
1492:   PetscMemcpy(mat->ops,A->ops,sizeof(struct _MatOps));

1494:   mat->factortype   = A->factortype;
1495:   mat->assembled    = PETSC_TRUE;
1496:   mat->preallocated = PETSC_TRUE;

1498:   a->size         = oldmat->size;
1499:   a->rank         = oldmat->rank;
1500:   mat->insertmode = NOT_SET_VALUES;
1501:   a->nvec         = oldmat->nvec;
1502:   a->donotstash   = oldmat->donotstash;

1504:   PetscLayoutReference(A->rmap,&mat->rmap);
1505:   PetscLayoutReference(A->cmap,&mat->cmap);

1507:   MatSetUpMultiply_MPIDense(mat);
1508:   MatDuplicate(oldmat->A,cpvalues,&a->A);
1509:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->A);

1511:   *newmat = mat;
1512:   return(0);
1513: }

1515: PetscErrorCode MatLoad_MPIDense_DenseInFile(MPI_Comm comm,PetscInt fd,PetscInt M,PetscInt N,Mat newmat)
1516: {
1518:   PetscMPIInt    rank,size;
1519:   const PetscInt *rowners;
1520:   PetscInt       i,m,n,nz,j,mMax;
1521:   PetscScalar    *array,*vals,*vals_ptr;
1522:   Mat_MPIDense   *a = (Mat_MPIDense*)newmat->data;

1525:   MPI_Comm_rank(comm,&rank);
1526:   MPI_Comm_size(comm,&size);

1528:   /* determine ownership of rows and columns */
1529:   m = (newmat->rmap->n < 0) ? PETSC_DECIDE : newmat->rmap->n;
1530:   n = (newmat->cmap->n < 0) ? PETSC_DECIDE : newmat->cmap->n;

1532:   MatSetSizes(newmat,m,n,M,N);
1533:   if (!a->A || !((Mat_SeqDense*)(a->A->data))->user_alloc) {
1534:     MatMPIDenseSetPreallocation(newmat,NULL);
1535:   }
1536:   MatDenseGetArray(newmat,&array);
1537:   MatGetLocalSize(newmat,&m,NULL);
1538:   MatGetOwnershipRanges(newmat,&rowners);
1539:   MPI_Reduce(&m,&mMax,1,MPIU_INT,MPI_MAX,0,comm);
1540:   if (!rank) {
1541:     PetscMalloc1(mMax*N,&vals);

1543:     /* read in my part of the matrix numerical values  */
1544:     PetscBinaryRead(fd,vals,m*N,PETSC_SCALAR);

1546:     /* insert into matrix-by row (this is why cannot directly read into array */
1547:     vals_ptr = vals;
1548:     for (i=0; i<m; i++) {
1549:       for (j=0; j<N; j++) {
1550:         array[i + j*m] = *vals_ptr++;
1551:       }
1552:     }

1554:     /* read in other processors and ship out */
1555:     for (i=1; i<size; i++) {
1556:       nz   = (rowners[i+1] - rowners[i])*N;
1557:       PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);
1558:       MPIULong_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)(newmat))->tag,comm);
1559:     }
1560:   } else {
1561:     /* receive numeric values */
1562:     PetscMalloc1(m*N,&vals);

1564:     /* receive message of values*/
1565:     MPIULong_Recv(vals,m*N,MPIU_SCALAR,0,((PetscObject)(newmat))->tag,comm);

1567:     /* insert into matrix-by row (this is why cannot directly read into array */
1568:     vals_ptr = vals;
1569:     for (i=0; i<m; i++) {
1570:       for (j=0; j<N; j++) {
1571:         array[i + j*m] = *vals_ptr++;
1572:       }
1573:     }
1574:   }
1575:   MatDenseRestoreArray(newmat,&array);
1576:   PetscFree(vals);
1577:   MatAssemblyBegin(newmat,MAT_FINAL_ASSEMBLY);
1578:   MatAssemblyEnd(newmat,MAT_FINAL_ASSEMBLY);
1579:   return(0);
1580: }

1582: PetscErrorCode MatLoad_MPIDense(Mat newmat,PetscViewer viewer)
1583: {
1584:   Mat_MPIDense   *a;
1585:   PetscScalar    *vals,*svals;
1586:   MPI_Comm       comm;
1587:   MPI_Status     status;
1588:   PetscMPIInt    rank,size,tag = ((PetscObject)viewer)->tag,*rowners,*sndcounts,m,n,maxnz;
1589:   PetscInt       header[4],*rowlengths = 0,M,N,*cols;
1590:   PetscInt       *ourlens,*procsnz = 0,jj,*mycols,*smycols;
1591:   PetscInt       i,nz,j,rstart,rend;
1592:   int            fd;

1596:   /* force binary viewer to load .info file if it has not yet done so */
1597:   PetscViewerSetUp(viewer);
1598:   PetscObjectGetComm((PetscObject)viewer,&comm);
1599:   MPI_Comm_size(comm,&size);
1600:   MPI_Comm_rank(comm,&rank);
1601:   PetscViewerBinaryGetDescriptor(viewer,&fd);
1602:   if (!rank) {
1603:     PetscBinaryRead(fd,(char*)header,4,PETSC_INT);
1604:     if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object");
1605:   }
1606:   MPI_Bcast(header+1,3,MPIU_INT,0,comm);
1607:   M    = header[1]; N = header[2]; nz = header[3];

1609:   /* If global rows/cols are set to PETSC_DECIDE, set it to the sizes given in the file */
1610:   if (newmat->rmap->N < 0) newmat->rmap->N = M;
1611:   if (newmat->cmap->N < 0) newmat->cmap->N = N;

1613:   if (newmat->rmap->N != M) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED, "Inconsistent # of rows:Matrix in file has (%D) and input matrix has (%D)",M,newmat->rmap->N);
1614:   if (newmat->cmap->N != N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED, "Inconsistent # of cols:Matrix in file has (%D) and input matrix has (%D)",N,newmat->cmap->N);

1616:   /*
1617:        Handle case where matrix is stored on disk as a dense matrix
1618:   */
1619:   if (nz == MATRIX_BINARY_FORMAT_DENSE) {
1620:     MatLoad_MPIDense_DenseInFile(comm,fd,M,N,newmat);
1621:     return(0);
1622:   }

1624:   /* determine ownership of all rows */
1625:   if (newmat->rmap->n < 0) {
1626:     PetscMPIIntCast(M/size + ((M % size) > rank),&m);
1627:   } else {
1628:     PetscMPIIntCast(newmat->rmap->n,&m);
1629:   }
1630:   if (newmat->cmap->n < 0) {
1631:     n = PETSC_DECIDE;
1632:   } else {
1633:     PetscMPIIntCast(newmat->cmap->n,&n);
1634:   }

1636:   PetscMalloc1(size+2,&rowners);
1637:   MPI_Allgather(&m,1,MPI_INT,rowners+1,1,MPI_INT,comm);
1638:   rowners[0] = 0;
1639:   for (i=2; i<=size; i++) {
1640:     rowners[i] += rowners[i-1];
1641:   }
1642:   rstart = rowners[rank];
1643:   rend   = rowners[rank+1];

1645:   /* distribute row lengths to all processors */
1646:   PetscMalloc1(rend-rstart,&ourlens);
1647:   if (!rank) {
1648:     PetscMalloc1(M,&rowlengths);
1649:     PetscBinaryRead(fd,rowlengths,M,PETSC_INT);
1650:     PetscMalloc1(size,&sndcounts);
1651:     for (i=0; i<size; i++) sndcounts[i] = rowners[i+1] - rowners[i];
1652:     MPI_Scatterv(rowlengths,sndcounts,rowners,MPIU_INT,ourlens,rend-rstart,MPIU_INT,0,comm);
1653:     PetscFree(sndcounts);
1654:   } else {
1655:     MPI_Scatterv(0,0,0,MPIU_INT,ourlens,rend-rstart,MPIU_INT,0,comm);
1656:   }

1658:   if (!rank) {
1659:     /* calculate the number of nonzeros on each processor */
1660:     PetscMalloc1(size,&procsnz);
1661:     PetscMemzero(procsnz,size*sizeof(PetscInt));
1662:     for (i=0; i<size; i++) {
1663:       for (j=rowners[i]; j< rowners[i+1]; j++) {
1664:         procsnz[i] += rowlengths[j];
1665:       }
1666:     }
1667:     PetscFree(rowlengths);

1669:     /* determine max buffer needed and allocate it */
1670:     maxnz = 0;
1671:     for (i=0; i<size; i++) {
1672:       maxnz = PetscMax(maxnz,procsnz[i]);
1673:     }
1674:     PetscMalloc1(maxnz,&cols);

1676:     /* read in my part of the matrix column indices  */
1677:     nz   = procsnz[0];
1678:     PetscMalloc1(nz,&mycols);
1679:     PetscBinaryRead(fd,mycols,nz,PETSC_INT);

1681:     /* read in every one elses and ship off */
1682:     for (i=1; i<size; i++) {
1683:       nz   = procsnz[i];
1684:       PetscBinaryRead(fd,cols,nz,PETSC_INT);
1685:       MPI_Send(cols,nz,MPIU_INT,i,tag,comm);
1686:     }
1687:     PetscFree(cols);
1688:   } else {
1689:     /* determine buffer space needed for message */
1690:     nz = 0;
1691:     for (i=0; i<m; i++) {
1692:       nz += ourlens[i];
1693:     }
1694:     PetscMalloc1(nz+1,&mycols);

1696:     /* receive message of column indices*/
1697:     MPI_Recv(mycols,nz,MPIU_INT,0,tag,comm,&status);
1698:     MPI_Get_count(&status,MPIU_INT,&maxnz);
1699:     if (maxnz != nz) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file");
1700:   }

1702:   MatSetSizes(newmat,m,n,M,N);
1703:   a = (Mat_MPIDense*)newmat->data;
1704:   if (!a->A || !((Mat_SeqDense*)(a->A->data))->user_alloc) {
1705:     MatMPIDenseSetPreallocation(newmat,NULL);
1706:   }

1708:   if (!rank) {
1709:     PetscMalloc1(maxnz,&vals);

1711:     /* read in my part of the matrix numerical values  */
1712:     nz   = procsnz[0];
1713:     PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);

1715:     /* insert into matrix */
1716:     jj      = rstart;
1717:     smycols = mycols;
1718:     svals   = vals;
1719:     for (i=0; i<m; i++) {
1720:       MatSetValues(newmat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);
1721:       smycols += ourlens[i];
1722:       svals   += ourlens[i];
1723:       jj++;
1724:     }

1726:     /* read in other processors and ship out */
1727:     for (i=1; i<size; i++) {
1728:       nz   = procsnz[i];
1729:       PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);
1730:       MPI_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newmat)->tag,comm);
1731:     }
1732:     PetscFree(procsnz);
1733:   } else {
1734:     /* receive numeric values */
1735:     PetscMalloc1(nz+1,&vals);

1737:     /* receive message of values*/
1738:     MPI_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newmat)->tag,comm,&status);
1739:     MPI_Get_count(&status,MPIU_SCALAR,&maxnz);
1740:     if (maxnz != nz) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file");

1742:     /* insert into matrix */
1743:     jj      = rstart;
1744:     smycols = mycols;
1745:     svals   = vals;
1746:     for (i=0; i<m; i++) {
1747:       MatSetValues(newmat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);
1748:       smycols += ourlens[i];
1749:       svals   += ourlens[i];
1750:       jj++;
1751:     }
1752:   }
1753:   PetscFree(ourlens);
1754:   PetscFree(vals);
1755:   PetscFree(mycols);
1756:   PetscFree(rowners);

1758:   MatAssemblyBegin(newmat,MAT_FINAL_ASSEMBLY);
1759:   MatAssemblyEnd(newmat,MAT_FINAL_ASSEMBLY);
1760:   return(0);
1761: }

1763: PetscErrorCode MatEqual_MPIDense(Mat A,Mat B,PetscBool  *flag)
1764: {
1765:   Mat_MPIDense   *matB = (Mat_MPIDense*)B->data,*matA = (Mat_MPIDense*)A->data;
1766:   Mat            a,b;
1767:   PetscBool      flg;

1771:   a    = matA->A;
1772:   b    = matB->A;
1773:   MatEqual(a,b,&flg);
1774:   MPIU_Allreduce(&flg,flag,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)A));
1775:   return(0);
1776: }

1778: PetscErrorCode MatDestroy_MatTransMatMult_MPIDense_MPIDense(Mat A)
1779: {
1780:   PetscErrorCode        ierr;
1781:   Mat_MPIDense          *a = (Mat_MPIDense*)A->data;
1782:   Mat_TransMatMultDense *atb = a->atbdense;

1785:   PetscFree3(atb->sendbuf,atb->atbarray,atb->recvcounts);
1786:   (atb->destroy)(A);
1787:   PetscFree(atb);
1788:   return(0);
1789: }

1791: PetscErrorCode MatTransposeMatMultNumeric_MPIDense_MPIDense(Mat A,Mat B,Mat C)
1792: {
1793:   Mat_MPIDense   *a=(Mat_MPIDense*)A->data, *b=(Mat_MPIDense*)B->data, *c=(Mat_MPIDense*)C->data;
1794:   Mat_SeqDense   *aseq=(Mat_SeqDense*)(a->A)->data, *bseq=(Mat_SeqDense*)(b->A)->data;
1795:   Mat_TransMatMultDense *atb = c->atbdense;
1797:   MPI_Comm       comm;
1798:   PetscMPIInt    rank,size,*recvcounts=atb->recvcounts;
1799:   PetscScalar    *carray,*atbarray=atb->atbarray,*sendbuf=atb->sendbuf;
1800:   PetscInt       i,cN=C->cmap->N,cM=C->rmap->N,proc,k,j;
1801:   PetscScalar    _DOne=1.0,_DZero=0.0;
1802:   PetscBLASInt   am,an,bn,aN;
1803:   const PetscInt *ranges;

1806:   PetscObjectGetComm((PetscObject)A,&comm);
1807:   MPI_Comm_rank(comm,&rank);
1808:   MPI_Comm_size(comm,&size);

1810:   /* compute atbarray = aseq^T * bseq */
1811:   PetscBLASIntCast(a->A->cmap->n,&an);
1812:   PetscBLASIntCast(b->A->cmap->n,&bn);
1813:   PetscBLASIntCast(a->A->rmap->n,&am);
1814:   PetscBLASIntCast(A->cmap->N,&aN);
1815:   PetscStackCallBLAS("BLASgemm",BLASgemm_("T","N",&an,&bn,&am,&_DOne,aseq->v,&aseq->lda,bseq->v,&bseq->lda,&_DZero,atbarray,&aN));
1816: 
1817:   MatGetOwnershipRanges(C,&ranges);
1818:   for (i=0; i<size; i++) recvcounts[i] = (ranges[i+1] - ranges[i])*cN;
1819: 
1820:   /* arrange atbarray into sendbuf */
1821:   k = 0;
1822:   for (proc=0; proc<size; proc++) {
1823:     for (j=0; j<cN; j++) {
1824:       for (i=ranges[proc]; i<ranges[proc+1]; i++) sendbuf[k++] = atbarray[i+j*cM];
1825:     }
1826:   }
1827:   /* sum all atbarray to local values of C */
1828:   MatDenseGetArray(c->A,&carray);
1829:   MPI_Reduce_scatter(sendbuf,carray,recvcounts,MPIU_SCALAR,MPIU_SUM,comm);
1830:   MatDenseRestoreArray(c->A,&carray);
1831:   return(0);
1832: }

1834: PetscErrorCode MatTransposeMatMultSymbolic_MPIDense_MPIDense(Mat A,Mat B,PetscReal fill,Mat *C)
1835: {
1836:   PetscErrorCode        ierr;
1837:   Mat                   Cdense;
1838:   MPI_Comm              comm;
1839:   PetscMPIInt           size;
1840:   PetscInt              cm=A->cmap->n,cM,cN=B->cmap->N;
1841:   Mat_MPIDense          *c;
1842:   Mat_TransMatMultDense *atb;

1845:   PetscObjectGetComm((PetscObject)A,&comm);
1846:   if (A->rmap->rstart != B->rmap->rstart || A->rmap->rend != B->rmap->rend) {
1847:     SETERRQ4(comm,PETSC_ERR_ARG_SIZ,"Matrix local dimensions are incompatible, A (%D, %D) != B (%D,%D)",A->rmap->rstart,A->rmap->rend,B->rmap->rstart,B->rmap->rend);
1848:   }

1850:   /* create matrix product Cdense */
1851:   MatCreate(comm,&Cdense);
1852:   MatSetSizes(Cdense,cm,B->cmap->n,PETSC_DECIDE,PETSC_DECIDE);
1853:   MatSetType(Cdense,MATMPIDENSE);
1854:   MatMPIDenseSetPreallocation(Cdense,NULL);
1855:   MatAssemblyBegin(Cdense,MAT_FINAL_ASSEMBLY);
1856:   MatAssemblyEnd(Cdense,MAT_FINAL_ASSEMBLY);
1857:   *C   = Cdense;

1859:   /* create data structure for reuse Cdense */
1860:   MPI_Comm_size(comm,&size);
1861:   PetscNew(&atb);
1862:   cM = Cdense->rmap->N;
1863:   PetscMalloc3(cM*cN,&atb->sendbuf,cM*cN,&atb->atbarray,size,&atb->recvcounts);
1864: 
1865:   c                    = (Mat_MPIDense*)Cdense->data;
1866:   c->atbdense          = atb;
1867:   atb->destroy         = Cdense->ops->destroy;
1868:   Cdense->ops->destroy = MatDestroy_MatTransMatMult_MPIDense_MPIDense;
1869:   return(0);
1870: }

1872: PetscErrorCode MatTransposeMatMult_MPIDense_MPIDense(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C)
1873: {

1877:   if (scall == MAT_INITIAL_MATRIX) {
1878:     MatTransposeMatMultSymbolic_MPIDense_MPIDense(A,B,fill,C);
1879:   }
1880:   MatTransposeMatMultNumeric_MPIDense_MPIDense(A,B,*C);
1881:   return(0);
1882: }

1884: PetscErrorCode MatDestroy_MatMatMult_MPIDense_MPIDense(Mat A)
1885: {
1886:   PetscErrorCode   ierr;
1887:   Mat_MPIDense     *a = (Mat_MPIDense*)A->data;
1888:   Mat_MatMultDense *ab = a->abdense;

1891:   MatDestroy(&ab->Ce);
1892:   MatDestroy(&ab->Ae);
1893:   MatDestroy(&ab->Be);

1895:   (ab->destroy)(A);
1896:   PetscFree(ab);
1897:   return(0);
1898: }

1900: #if defined(PETSC_HAVE_ELEMENTAL)
1901: PetscErrorCode MatMatMultNumeric_MPIDense_MPIDense(Mat A,Mat B,Mat C)
1902: {
1903:   PetscErrorCode   ierr;
1904:   Mat_MPIDense     *c=(Mat_MPIDense*)C->data;
1905:   Mat_MatMultDense *ab=c->abdense;

1908:   MatConvert_MPIDense_Elemental(A,MATELEMENTAL,MAT_REUSE_MATRIX, &ab->Ae);
1909:   MatConvert_MPIDense_Elemental(B,MATELEMENTAL,MAT_REUSE_MATRIX, &ab->Be);
1910:   MatMatMultNumeric(ab->Ae,ab->Be,ab->Ce);
1911:   MatConvert(ab->Ce,MATMPIDENSE,MAT_REUSE_MATRIX,&C);
1912:   return(0);
1913: }

1915: PetscErrorCode MatMatMultSymbolic_MPIDense_MPIDense(Mat A,Mat B,PetscReal fill,Mat *C)
1916: {
1917:   PetscErrorCode   ierr;
1918:   Mat              Ae,Be,Ce;
1919:   Mat_MPIDense     *c;
1920:   Mat_MatMultDense *ab;

1923:   if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) {
1924:     SETERRQ4(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_SIZ,"Matrix local dimensions are incompatible, A (%D, %D) != B (%D,%D)",A->rmap->rstart,A->rmap->rend,B->rmap->rstart,B->rmap->rend);
1925:   }

1927:   /* convert A and B to Elemental matrices Ae and Be */
1928:   MatConvert(A,MATELEMENTAL,MAT_INITIAL_MATRIX, &Ae);
1929:   MatConvert(B,MATELEMENTAL,MAT_INITIAL_MATRIX, &Be);

1931:   /* Ce = Ae*Be */
1932:   MatMatMultSymbolic(Ae,Be,fill,&Ce);
1933:   MatMatMultNumeric(Ae,Be,Ce);
1934: 
1935:   /* convert Ce to C */
1936:   MatConvert(Ce,MATMPIDENSE,MAT_INITIAL_MATRIX,C);

1938:   /* create data structure for reuse Cdense */
1939:   PetscNew(&ab);
1940:   c                  = (Mat_MPIDense*)(*C)->data;
1941:   c->abdense         = ab;

1943:   ab->Ae             = Ae;
1944:   ab->Be             = Be;
1945:   ab->Ce             = Ce;
1946:   ab->destroy        = (*C)->ops->destroy;
1947:   (*C)->ops->destroy        = MatDestroy_MatMatMult_MPIDense_MPIDense;
1948:   (*C)->ops->matmultnumeric = MatMatMultNumeric_MPIDense_MPIDense;
1949:   return(0);
1950: }

1952: PETSC_INTERN PetscErrorCode MatMatMult_MPIDense_MPIDense(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C)
1953: {

1957:   if (scall == MAT_INITIAL_MATRIX) { /* simbolic product includes numeric product */
1958:     PetscLogEventBegin(MAT_MatMultSymbolic,A,B,0,0);
1959:     MatMatMultSymbolic_MPIDense_MPIDense(A,B,fill,C);
1960:     PetscLogEventEnd(MAT_MatMultSymbolic,A,B,0,0);
1961:   } else {
1962:     PetscLogEventBegin(MAT_MatMultNumeric,A,B,0,0);
1963:     MatMatMultNumeric_MPIDense_MPIDense(A,B,*C);
1964:     PetscLogEventEnd(MAT_MatMultNumeric,A,B,0,0);
1965:   }
1966:   return(0);
1967: }
1968: #endif