Actual source code: mpiaij.c

petsc-3.10.2 2018-10-09
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  3:  #include <../src/mat/impls/aij/mpi/mpiaij.h>
  4:  #include <petsc/private/vecimpl.h>
  5:  #include <petsc/private/isimpl.h>
  6:  #include <petscblaslapack.h>
  7:  #include <petscsf.h>

  9: /*MC
 10:    MATAIJ - MATAIJ = "aij" - A matrix type to be used for sparse matrices.

 12:    This matrix type is identical to MATSEQAIJ when constructed with a single process communicator,
 13:    and MATMPIAIJ otherwise.  As a result, for single process communicators,
 14:   MatSeqAIJSetPreallocation is supported, and similarly MatMPIAIJSetPreallocation is supported
 15:   for communicators controlling multiple processes.  It is recommended that you call both of
 16:   the above preallocation routines for simplicity.

 18:    Options Database Keys:
 19: . -mat_type aij - sets the matrix type to "aij" during a call to MatSetFromOptions()

 21:   Developer Notes:
 22:     Subclasses include MATAIJCUSP, MATAIJCUSPARSE, MATAIJPERM, MATAIJSELL, MATAIJMKL, MATAIJCRL, and also automatically switches over to use inodes when
 23:    enough exist.

 25:   Level: beginner

 27: .seealso: MatCreateAIJ(), MatCreateSeqAIJ(), MATSEQAIJ, MATMPIAIJ
 28: M*/

 30: /*MC
 31:    MATAIJCRL - MATAIJCRL = "aijcrl" - A matrix type to be used for sparse matrices.

 33:    This matrix type is identical to MATSEQAIJCRL when constructed with a single process communicator,
 34:    and MATMPIAIJCRL otherwise.  As a result, for single process communicators,
 35:    MatSeqAIJSetPreallocation() is supported, and similarly MatMPIAIJSetPreallocation() is supported
 36:   for communicators controlling multiple processes.  It is recommended that you call both of
 37:   the above preallocation routines for simplicity.

 39:    Options Database Keys:
 40: . -mat_type aijcrl - sets the matrix type to "aijcrl" during a call to MatSetFromOptions()

 42:   Level: beginner

 44: .seealso: MatCreateMPIAIJCRL,MATSEQAIJCRL,MATMPIAIJCRL, MATSEQAIJCRL, MATMPIAIJCRL
 45: M*/

 47: PetscErrorCode MatSetBlockSizes_MPIAIJ(Mat M, PetscInt rbs, PetscInt cbs)
 48: {
 50:   Mat_MPIAIJ     *mat = (Mat_MPIAIJ*)M->data;

 53:   if (mat->A) {
 54:     MatSetBlockSizes(mat->A,rbs,cbs);
 55:     MatSetBlockSizes(mat->B,rbs,1);
 56:   }
 57:   return(0);
 58: }

 60: PetscErrorCode MatFindNonzeroRows_MPIAIJ(Mat M,IS *keptrows)
 61: {
 62:   PetscErrorCode  ierr;
 63:   Mat_MPIAIJ      *mat = (Mat_MPIAIJ*)M->data;
 64:   Mat_SeqAIJ      *a   = (Mat_SeqAIJ*)mat->A->data;
 65:   Mat_SeqAIJ      *b   = (Mat_SeqAIJ*)mat->B->data;
 66:   const PetscInt  *ia,*ib;
 67:   const MatScalar *aa,*bb;
 68:   PetscInt        na,nb,i,j,*rows,cnt=0,n0rows;
 69:   PetscInt        m = M->rmap->n,rstart = M->rmap->rstart;

 72:   *keptrows = 0;
 73:   ia        = a->i;
 74:   ib        = b->i;
 75:   for (i=0; i<m; i++) {
 76:     na = ia[i+1] - ia[i];
 77:     nb = ib[i+1] - ib[i];
 78:     if (!na && !nb) {
 79:       cnt++;
 80:       goto ok1;
 81:     }
 82:     aa = a->a + ia[i];
 83:     for (j=0; j<na; j++) {
 84:       if (aa[j] != 0.0) goto ok1;
 85:     }
 86:     bb = b->a + ib[i];
 87:     for (j=0; j <nb; j++) {
 88:       if (bb[j] != 0.0) goto ok1;
 89:     }
 90:     cnt++;
 91: ok1:;
 92:   }
 93:   MPIU_Allreduce(&cnt,&n0rows,1,MPIU_INT,MPI_SUM,PetscObjectComm((PetscObject)M));
 94:   if (!n0rows) return(0);
 95:   PetscMalloc1(M->rmap->n-cnt,&rows);
 96:   cnt  = 0;
 97:   for (i=0; i<m; i++) {
 98:     na = ia[i+1] - ia[i];
 99:     nb = ib[i+1] - ib[i];
100:     if (!na && !nb) continue;
101:     aa = a->a + ia[i];
102:     for (j=0; j<na;j++) {
103:       if (aa[j] != 0.0) {
104:         rows[cnt++] = rstart + i;
105:         goto ok2;
106:       }
107:     }
108:     bb = b->a + ib[i];
109:     for (j=0; j<nb; j++) {
110:       if (bb[j] != 0.0) {
111:         rows[cnt++] = rstart + i;
112:         goto ok2;
113:       }
114:     }
115: ok2:;
116:   }
117:   ISCreateGeneral(PetscObjectComm((PetscObject)M),cnt,rows,PETSC_OWN_POINTER,keptrows);
118:   return(0);
119: }

121: PetscErrorCode  MatDiagonalSet_MPIAIJ(Mat Y,Vec D,InsertMode is)
122: {
123:   PetscErrorCode    ierr;
124:   Mat_MPIAIJ        *aij = (Mat_MPIAIJ*) Y->data;
125:   PetscBool         cong;

128:   MatHasCongruentLayouts(Y,&cong);
129:   if (Y->assembled && cong) {
130:     MatDiagonalSet(aij->A,D,is);
131:   } else {
132:     MatDiagonalSet_Default(Y,D,is);
133:   }
134:   return(0);
135: }

137: PetscErrorCode MatFindZeroDiagonals_MPIAIJ(Mat M,IS *zrows)
138: {
139:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)M->data;
141:   PetscInt       i,rstart,nrows,*rows;

144:   *zrows = NULL;
145:   MatFindZeroDiagonals_SeqAIJ_Private(aij->A,&nrows,&rows);
146:   MatGetOwnershipRange(M,&rstart,NULL);
147:   for (i=0; i<nrows; i++) rows[i] += rstart;
148:   ISCreateGeneral(PetscObjectComm((PetscObject)M),nrows,rows,PETSC_OWN_POINTER,zrows);
149:   return(0);
150: }

152: PetscErrorCode MatGetColumnNorms_MPIAIJ(Mat A,NormType type,PetscReal *norms)
153: {
155:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)A->data;
156:   PetscInt       i,n,*garray = aij->garray;
157:   Mat_SeqAIJ     *a_aij = (Mat_SeqAIJ*) aij->A->data;
158:   Mat_SeqAIJ     *b_aij = (Mat_SeqAIJ*) aij->B->data;
159:   PetscReal      *work;

162:   MatGetSize(A,NULL,&n);
163:   PetscCalloc1(n,&work);
164:   if (type == NORM_2) {
165:     for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) {
166:       work[A->cmap->rstart + a_aij->j[i]] += PetscAbsScalar(a_aij->a[i]*a_aij->a[i]);
167:     }
168:     for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) {
169:       work[garray[b_aij->j[i]]] += PetscAbsScalar(b_aij->a[i]*b_aij->a[i]);
170:     }
171:   } else if (type == NORM_1) {
172:     for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) {
173:       work[A->cmap->rstart + a_aij->j[i]] += PetscAbsScalar(a_aij->a[i]);
174:     }
175:     for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) {
176:       work[garray[b_aij->j[i]]] += PetscAbsScalar(b_aij->a[i]);
177:     }
178:   } else if (type == NORM_INFINITY) {
179:     for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) {
180:       work[A->cmap->rstart + a_aij->j[i]] = PetscMax(PetscAbsScalar(a_aij->a[i]), work[A->cmap->rstart + a_aij->j[i]]);
181:     }
182:     for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) {
183:       work[garray[b_aij->j[i]]] = PetscMax(PetscAbsScalar(b_aij->a[i]),work[garray[b_aij->j[i]]]);
184:     }

186:   } else SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Unknown NormType");
187:   if (type == NORM_INFINITY) {
188:     MPIU_Allreduce(work,norms,n,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)A));
189:   } else {
190:     MPIU_Allreduce(work,norms,n,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)A));
191:   }
192:   PetscFree(work);
193:   if (type == NORM_2) {
194:     for (i=0; i<n; i++) norms[i] = PetscSqrtReal(norms[i]);
195:   }
196:   return(0);
197: }

199: PetscErrorCode MatFindOffBlockDiagonalEntries_MPIAIJ(Mat A,IS *is)
200: {
201:   Mat_MPIAIJ      *a  = (Mat_MPIAIJ*)A->data;
202:   IS              sis,gis;
203:   PetscErrorCode  ierr;
204:   const PetscInt  *isis,*igis;
205:   PetscInt        n,*iis,nsis,ngis,rstart,i;

208:   MatFindOffBlockDiagonalEntries(a->A,&sis);
209:   MatFindNonzeroRows(a->B,&gis);
210:   ISGetSize(gis,&ngis);
211:   ISGetSize(sis,&nsis);
212:   ISGetIndices(sis,&isis);
213:   ISGetIndices(gis,&igis);

215:   PetscMalloc1(ngis+nsis,&iis);
216:   PetscMemcpy(iis,igis,ngis*sizeof(PetscInt));
217:   PetscMemcpy(iis+ngis,isis,nsis*sizeof(PetscInt));
218:   n    = ngis + nsis;
219:   PetscSortRemoveDupsInt(&n,iis);
220:   MatGetOwnershipRange(A,&rstart,NULL);
221:   for (i=0; i<n; i++) iis[i] += rstart;
222:   ISCreateGeneral(PetscObjectComm((PetscObject)A),n,iis,PETSC_OWN_POINTER,is);

224:   ISRestoreIndices(sis,&isis);
225:   ISRestoreIndices(gis,&igis);
226:   ISDestroy(&sis);
227:   ISDestroy(&gis);
228:   return(0);
229: }

231: /*
232:     Distributes a SeqAIJ matrix across a set of processes. Code stolen from
233:     MatLoad_MPIAIJ(). Horrible lack of reuse. Should be a routine for each matrix type.

235:     Only for square matrices

237:     Used by a preconditioner, hence PETSC_EXTERN
238: */
239: PETSC_EXTERN PetscErrorCode MatDistribute_MPIAIJ(MPI_Comm comm,Mat gmat,PetscInt m,MatReuse reuse,Mat *inmat)
240: {
241:   PetscMPIInt    rank,size;
242:   PetscInt       *rowners,*dlens,*olens,i,rstart,rend,j,jj,nz = 0,*gmataj,cnt,row,*ld,bses[2];
244:   Mat            mat;
245:   Mat_SeqAIJ     *gmata;
246:   PetscMPIInt    tag;
247:   MPI_Status     status;
248:   PetscBool      aij;
249:   MatScalar      *gmataa,*ao,*ad,*gmataarestore=0;

252:   MPI_Comm_rank(comm,&rank);
253:   MPI_Comm_size(comm,&size);
254:   if (!rank) {
255:     PetscObjectTypeCompare((PetscObject)gmat,MATSEQAIJ,&aij);
256:     if (!aij) SETERRQ1(PetscObjectComm((PetscObject)gmat),PETSC_ERR_SUP,"Currently no support for input matrix of type %s\n",((PetscObject)gmat)->type_name);
257:   }
258:   if (reuse == MAT_INITIAL_MATRIX) {
259:     MatCreate(comm,&mat);
260:     MatSetSizes(mat,m,m,PETSC_DETERMINE,PETSC_DETERMINE);
261:     MatGetBlockSizes(gmat,&bses[0],&bses[1]);
262:     MPI_Bcast(bses,2,MPIU_INT,0,comm);
263:     MatSetBlockSizes(mat,bses[0],bses[1]);
264:     MatSetType(mat,MATAIJ);
265:     PetscMalloc1(size+1,&rowners);
266:     PetscMalloc2(m,&dlens,m,&olens);
267:     MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);

269:     rowners[0] = 0;
270:     for (i=2; i<=size; i++) rowners[i] += rowners[i-1];
271:     rstart = rowners[rank];
272:     rend   = rowners[rank+1];
273:     PetscObjectGetNewTag((PetscObject)mat,&tag);
274:     if (!rank) {
275:       gmata = (Mat_SeqAIJ*) gmat->data;
276:       /* send row lengths to all processors */
277:       for (i=0; i<m; i++) dlens[i] = gmata->ilen[i];
278:       for (i=1; i<size; i++) {
279:         MPI_Send(gmata->ilen + rowners[i],rowners[i+1]-rowners[i],MPIU_INT,i,tag,comm);
280:       }
281:       /* determine number diagonal and off-diagonal counts */
282:       PetscMemzero(olens,m*sizeof(PetscInt));
283:       PetscCalloc1(m,&ld);
284:       jj   = 0;
285:       for (i=0; i<m; i++) {
286:         for (j=0; j<dlens[i]; j++) {
287:           if (gmata->j[jj] < rstart) ld[i]++;
288:           if (gmata->j[jj] < rstart || gmata->j[jj] >= rend) olens[i]++;
289:           jj++;
290:         }
291:       }
292:       /* send column indices to other processes */
293:       for (i=1; i<size; i++) {
294:         nz   = gmata->i[rowners[i+1]]-gmata->i[rowners[i]];
295:         MPI_Send(&nz,1,MPIU_INT,i,tag,comm);
296:         MPI_Send(gmata->j + gmata->i[rowners[i]],nz,MPIU_INT,i,tag,comm);
297:       }

299:       /* send numerical values to other processes */
300:       for (i=1; i<size; i++) {
301:         nz   = gmata->i[rowners[i+1]]-gmata->i[rowners[i]];
302:         MPI_Send(gmata->a + gmata->i[rowners[i]],nz,MPIU_SCALAR,i,tag,comm);
303:       }
304:       gmataa = gmata->a;
305:       gmataj = gmata->j;

307:     } else {
308:       /* receive row lengths */
309:       MPI_Recv(dlens,m,MPIU_INT,0,tag,comm,&status);
310:       /* receive column indices */
311:       MPI_Recv(&nz,1,MPIU_INT,0,tag,comm,&status);
312:       PetscMalloc2(nz,&gmataa,nz,&gmataj);
313:       MPI_Recv(gmataj,nz,MPIU_INT,0,tag,comm,&status);
314:       /* determine number diagonal and off-diagonal counts */
315:       PetscMemzero(olens,m*sizeof(PetscInt));
316:       PetscCalloc1(m,&ld);
317:       jj   = 0;
318:       for (i=0; i<m; i++) {
319:         for (j=0; j<dlens[i]; j++) {
320:           if (gmataj[jj] < rstart) ld[i]++;
321:           if (gmataj[jj] < rstart || gmataj[jj] >= rend) olens[i]++;
322:           jj++;
323:         }
324:       }
325:       /* receive numerical values */
326:       PetscMemzero(gmataa,nz*sizeof(PetscScalar));
327:       MPI_Recv(gmataa,nz,MPIU_SCALAR,0,tag,comm,&status);
328:     }
329:     /* set preallocation */
330:     for (i=0; i<m; i++) {
331:       dlens[i] -= olens[i];
332:     }
333:     MatSeqAIJSetPreallocation(mat,0,dlens);
334:     MatMPIAIJSetPreallocation(mat,0,dlens,0,olens);

336:     for (i=0; i<m; i++) {
337:       dlens[i] += olens[i];
338:     }
339:     cnt = 0;
340:     for (i=0; i<m; i++) {
341:       row  = rstart + i;
342:       MatSetValues(mat,1,&row,dlens[i],gmataj+cnt,gmataa+cnt,INSERT_VALUES);
343:       cnt += dlens[i];
344:     }
345:     if (rank) {
346:       PetscFree2(gmataa,gmataj);
347:     }
348:     PetscFree2(dlens,olens);
349:     PetscFree(rowners);

351:     ((Mat_MPIAIJ*)(mat->data))->ld = ld;

353:     *inmat = mat;
354:   } else {   /* column indices are already set; only need to move over numerical values from process 0 */
355:     Mat_SeqAIJ *Ad = (Mat_SeqAIJ*)((Mat_MPIAIJ*)((*inmat)->data))->A->data;
356:     Mat_SeqAIJ *Ao = (Mat_SeqAIJ*)((Mat_MPIAIJ*)((*inmat)->data))->B->data;
357:     mat  = *inmat;
358:     PetscObjectGetNewTag((PetscObject)mat,&tag);
359:     if (!rank) {
360:       /* send numerical values to other processes */
361:       gmata  = (Mat_SeqAIJ*) gmat->data;
362:       MatGetOwnershipRanges(mat,(const PetscInt**)&rowners);
363:       gmataa = gmata->a;
364:       for (i=1; i<size; i++) {
365:         nz   = gmata->i[rowners[i+1]]-gmata->i[rowners[i]];
366:         MPI_Send(gmataa + gmata->i[rowners[i]],nz,MPIU_SCALAR,i,tag,comm);
367:       }
368:       nz = gmata->i[rowners[1]]-gmata->i[rowners[0]];
369:     } else {
370:       /* receive numerical values from process 0*/
371:       nz   = Ad->nz + Ao->nz;
372:       PetscMalloc1(nz,&gmataa); gmataarestore = gmataa;
373:       MPI_Recv(gmataa,nz,MPIU_SCALAR,0,tag,comm,&status);
374:     }
375:     /* transfer numerical values into the diagonal A and off diagonal B parts of mat */
376:     ld = ((Mat_MPIAIJ*)(mat->data))->ld;
377:     ad = Ad->a;
378:     ao = Ao->a;
379:     if (mat->rmap->n) {
380:       i  = 0;
381:       nz = ld[i];                                   PetscMemcpy(ao,gmataa,nz*sizeof(PetscScalar)); ao += nz; gmataa += nz;
382:       nz = Ad->i[i+1] - Ad->i[i];                   PetscMemcpy(ad,gmataa,nz*sizeof(PetscScalar)); ad += nz; gmataa += nz;
383:     }
384:     for (i=1; i<mat->rmap->n; i++) {
385:       nz = Ao->i[i] - Ao->i[i-1] - ld[i-1] + ld[i]; PetscMemcpy(ao,gmataa,nz*sizeof(PetscScalar)); ao += nz; gmataa += nz;
386:       nz = Ad->i[i+1] - Ad->i[i];                   PetscMemcpy(ad,gmataa,nz*sizeof(PetscScalar)); ad += nz; gmataa += nz;
387:     }
388:     i--;
389:     if (mat->rmap->n) {
390:       nz = Ao->i[i+1] - Ao->i[i] - ld[i];           PetscMemcpy(ao,gmataa,nz*sizeof(PetscScalar));
391:     }
392:     if (rank) {
393:       PetscFree(gmataarestore);
394:     }
395:   }
396:   MatAssemblyBegin(mat,MAT_FINAL_ASSEMBLY);
397:   MatAssemblyEnd(mat,MAT_FINAL_ASSEMBLY);
398:   return(0);
399: }

401: /*
402:   Local utility routine that creates a mapping from the global column
403: number to the local number in the off-diagonal part of the local
404: storage of the matrix.  When PETSC_USE_CTABLE is used this is scalable at
405: a slightly higher hash table cost; without it it is not scalable (each processor
406: has an order N integer array but is fast to acess.
407: */
408: PetscErrorCode MatCreateColmap_MPIAIJ_Private(Mat mat)
409: {
410:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)mat->data;
412:   PetscInt       n = aij->B->cmap->n,i;

415:   if (!aij->garray) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"MPIAIJ Matrix was assembled but is missing garray");
416: #if defined(PETSC_USE_CTABLE)
417:   PetscTableCreate(n,mat->cmap->N+1,&aij->colmap);
418:   for (i=0; i<n; i++) {
419:     PetscTableAdd(aij->colmap,aij->garray[i]+1,i+1,INSERT_VALUES);
420:   }
421: #else
422:   PetscCalloc1(mat->cmap->N+1,&aij->colmap);
423:   PetscLogObjectMemory((PetscObject)mat,(mat->cmap->N+1)*sizeof(PetscInt));
424:   for (i=0; i<n; i++) aij->colmap[aij->garray[i]] = i+1;
425: #endif
426:   return(0);
427: }

429: #define MatSetValues_SeqAIJ_A_Private(row,col,value,addv,orow,ocol)     \
430: { \
431:     if (col <= lastcol1)  low1 = 0;     \
432:     else                 high1 = nrow1; \
433:     lastcol1 = col;\
434:     while (high1-low1 > 5) { \
435:       t = (low1+high1)/2; \
436:       if (rp1[t] > col) high1 = t; \
437:       else              low1  = t; \
438:     } \
439:       for (_i=low1; _i<high1; _i++) { \
440:         if (rp1[_i] > col) break; \
441:         if (rp1[_i] == col) { \
442:           if (addv == ADD_VALUES) ap1[_i] += value;   \
443:           else                    ap1[_i] = value; \
444:           goto a_noinsert; \
445:         } \
446:       }  \
447:       if (value == 0.0 && ignorezeroentries && row != col) {low1 = 0; high1 = nrow1;goto a_noinsert;} \
448:       if (nonew == 1) {low1 = 0; high1 = nrow1; goto a_noinsert;}                \
449:       if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero at global row/column (%D, %D) into matrix", orow, ocol); \
450:       MatSeqXAIJReallocateAIJ(A,am,1,nrow1,row,col,rmax1,aa,ai,aj,rp1,ap1,aimax,nonew,MatScalar); \
451:       N = nrow1++ - 1; a->nz++; high1++; \
452:       /* shift up all the later entries in this row */ \
453:       for (ii=N; ii>=_i; ii--) { \
454:         rp1[ii+1] = rp1[ii]; \
455:         ap1[ii+1] = ap1[ii]; \
456:       } \
457:       rp1[_i] = col;  \
458:       ap1[_i] = value;  \
459:       A->nonzerostate++;\
460:       a_noinsert: ; \
461:       ailen[row] = nrow1; \
462: }

464: #define MatSetValues_SeqAIJ_B_Private(row,col,value,addv,orow,ocol) \
465:   { \
466:     if (col <= lastcol2) low2 = 0;                        \
467:     else high2 = nrow2;                                   \
468:     lastcol2 = col;                                       \
469:     while (high2-low2 > 5) {                              \
470:       t = (low2+high2)/2;                                 \
471:       if (rp2[t] > col) high2 = t;                        \
472:       else             low2  = t;                         \
473:     }                                                     \
474:     for (_i=low2; _i<high2; _i++) {                       \
475:       if (rp2[_i] > col) break;                           \
476:       if (rp2[_i] == col) {                               \
477:         if (addv == ADD_VALUES) ap2[_i] += value;         \
478:         else                    ap2[_i] = value;          \
479:         goto b_noinsert;                                  \
480:       }                                                   \
481:     }                                                     \
482:     if (value == 0.0 && ignorezeroentries) {low2 = 0; high2 = nrow2; goto b_noinsert;} \
483:     if (nonew == 1) {low2 = 0; high2 = nrow2; goto b_noinsert;}                        \
484:     if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero at global row/column (%D, %D) into matrix", orow, ocol); \
485:     MatSeqXAIJReallocateAIJ(B,bm,1,nrow2,row,col,rmax2,ba,bi,bj,rp2,ap2,bimax,nonew,MatScalar); \
486:     N = nrow2++ - 1; b->nz++; high2++;                    \
487:     /* shift up all the later entries in this row */      \
488:     for (ii=N; ii>=_i; ii--) {                            \
489:       rp2[ii+1] = rp2[ii];                                \
490:       ap2[ii+1] = ap2[ii];                                \
491:     }                                                     \
492:     rp2[_i] = col;                                        \
493:     ap2[_i] = value;                                      \
494:     B->nonzerostate++;                                    \
495:     b_noinsert: ;                                         \
496:     bilen[row] = nrow2;                                   \
497:   }

499: PetscErrorCode MatSetValuesRow_MPIAIJ(Mat A,PetscInt row,const PetscScalar v[])
500: {
501:   Mat_MPIAIJ     *mat = (Mat_MPIAIJ*)A->data;
502:   Mat_SeqAIJ     *a   = (Mat_SeqAIJ*)mat->A->data,*b = (Mat_SeqAIJ*)mat->B->data;
504:   PetscInt       l,*garray = mat->garray,diag;

507:   /* code only works for square matrices A */

509:   /* find size of row to the left of the diagonal part */
510:   MatGetOwnershipRange(A,&diag,0);
511:   row  = row - diag;
512:   for (l=0; l<b->i[row+1]-b->i[row]; l++) {
513:     if (garray[b->j[b->i[row]+l]] > diag) break;
514:   }
515:   PetscMemcpy(b->a+b->i[row],v,l*sizeof(PetscScalar));

517:   /* diagonal part */
518:   PetscMemcpy(a->a+a->i[row],v+l,(a->i[row+1]-a->i[row])*sizeof(PetscScalar));

520:   /* right of diagonal part */
521:   PetscMemcpy(b->a+b->i[row]+l,v+l+a->i[row+1]-a->i[row],(b->i[row+1]-b->i[row]-l)*sizeof(PetscScalar));
522:   return(0);
523: }

525: PetscErrorCode MatSetValues_MPIAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv)
526: {
527:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)mat->data;
528:   PetscScalar    value;
530:   PetscInt       i,j,rstart  = mat->rmap->rstart,rend = mat->rmap->rend;
531:   PetscInt       cstart      = mat->cmap->rstart,cend = mat->cmap->rend,row,col;
532:   PetscBool      roworiented = aij->roworiented;

534:   /* Some Variables required in the macro */
535:   Mat        A                 = aij->A;
536:   Mat_SeqAIJ *a                = (Mat_SeqAIJ*)A->data;
537:   PetscInt   *aimax            = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j;
538:   MatScalar  *aa               = a->a;
539:   PetscBool  ignorezeroentries = a->ignorezeroentries;
540:   Mat        B                 = aij->B;
541:   Mat_SeqAIJ *b                = (Mat_SeqAIJ*)B->data;
542:   PetscInt   *bimax            = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n;
543:   MatScalar  *ba               = b->a;

545:   PetscInt  *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2;
546:   PetscInt  nonew;
547:   MatScalar *ap1,*ap2;

550:   for (i=0; i<m; i++) {
551:     if (im[i] < 0) continue;
552: #if defined(PETSC_USE_DEBUG)
553:     if (im[i] >= mat->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],mat->rmap->N-1);
554: #endif
555:     if (im[i] >= rstart && im[i] < rend) {
556:       row      = im[i] - rstart;
557:       lastcol1 = -1;
558:       rp1      = aj + ai[row];
559:       ap1      = aa + ai[row];
560:       rmax1    = aimax[row];
561:       nrow1    = ailen[row];
562:       low1     = 0;
563:       high1    = nrow1;
564:       lastcol2 = -1;
565:       rp2      = bj + bi[row];
566:       ap2      = ba + bi[row];
567:       rmax2    = bimax[row];
568:       nrow2    = bilen[row];
569:       low2     = 0;
570:       high2    = nrow2;

572:       for (j=0; j<n; j++) {
573:         if (roworiented) value = v[i*n+j];
574:         else             value = v[i+j*m];
575:         if (in[j] >= cstart && in[j] < cend) {
576:           col   = in[j] - cstart;
577:           nonew = a->nonew;
578:           if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES) && row != col) continue;
579:           MatSetValues_SeqAIJ_A_Private(row,col,value,addv,im[i],in[j]);
580:         } else if (in[j] < 0) continue;
581: #if defined(PETSC_USE_DEBUG)
582:         else if (in[j] >= mat->cmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",in[j],mat->cmap->N-1);
583: #endif
584:         else {
585:           if (mat->was_assembled) {
586:             if (!aij->colmap) {
587:               MatCreateColmap_MPIAIJ_Private(mat);
588:             }
589: #if defined(PETSC_USE_CTABLE)
590:             PetscTableFind(aij->colmap,in[j]+1,&col);
591:             col--;
592: #else
593:             col = aij->colmap[in[j]] - 1;
594: #endif
595:             if (col < 0 && !((Mat_SeqAIJ*)(aij->B->data))->nonew) {
596:               MatDisAssemble_MPIAIJ(mat);
597:               col  =  in[j];
598:               /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */
599:               B     = aij->B;
600:               b     = (Mat_SeqAIJ*)B->data;
601:               bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j; ba = b->a;
602:               rp2   = bj + bi[row];
603:               ap2   = ba + bi[row];
604:               rmax2 = bimax[row];
605:               nrow2 = bilen[row];
606:               low2  = 0;
607:               high2 = nrow2;
608:               bm    = aij->B->rmap->n;
609:               ba    = b->a;
610:             } else if (col < 0) {
611:               if (1 == ((Mat_SeqAIJ*)(aij->B->data))->nonew) {
612:                 PetscInfo3(mat,"Skipping of insertion of new nonzero location in off-diagonal portion of matrix %g(%D,%D)\n",(double)PetscRealPart(value),im[i],in[j]);
613:               } else SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero at global row/column (%D, %D) into matrix", im[i], in[j]);
614:             }
615:           } else col = in[j];
616:           nonew = b->nonew;
617:           MatSetValues_SeqAIJ_B_Private(row,col,value,addv,im[i],in[j]);
618:         }
619:       }
620:     } else {
621:       if (mat->nooffprocentries) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Setting off process row %D even though MatSetOption(,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE) was set",im[i]);
622:       if (!aij->donotstash) {
623:         mat->assembled = PETSC_FALSE;
624:         if (roworiented) {
625:           MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));
626:         } else {
627:           MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));
628:         }
629:       }
630:     }
631:   }
632:   return(0);
633: }

635: /*
636:     This function sets the j and ilen arrays (of the diagonal and off-diagonal part) of an MPIAIJ-matrix.
637:     The values in mat_i have to be sorted and the values in mat_j have to be sorted for each row (CSR-like).
638:     No off-processor parts off the matrix are allowed here and mat->was_assembled has to be PETSC_FALSE.
639: */
640: PetscErrorCode MatSetValues_MPIAIJ_CopyFromCSRFormat_Symbolic(Mat mat,const PetscInt mat_j[],const PetscInt mat_i[])
641: {
642:   Mat_MPIAIJ     *aij        = (Mat_MPIAIJ*)mat->data;
643:   Mat            A           = aij->A; /* diagonal part of the matrix */
644:   Mat            B           = aij->B; /* offdiagonal part of the matrix */
645:   Mat_SeqAIJ     *a          = (Mat_SeqAIJ*)A->data;
646:   Mat_SeqAIJ     *b          = (Mat_SeqAIJ*)B->data;
647:   PetscInt       cstart      = mat->cmap->rstart,cend = mat->cmap->rend,col;
648:   PetscInt       *ailen      = a->ilen,*aj = a->j;
649:   PetscInt       *bilen      = b->ilen,*bj = b->j;
650:   PetscInt       am          = aij->A->rmap->n,j;
651:   PetscInt       diag_so_far = 0,dnz;
652:   PetscInt       offd_so_far = 0,onz;

655:   /* Iterate over all rows of the matrix */
656:   for (j=0; j<am; j++) {
657:     dnz = onz = 0;
658:     /*  Iterate over all non-zero columns of the current row */
659:     for (col=mat_i[j]; col<mat_i[j+1]; col++) {
660:       /* If column is in the diagonal */
661:       if (mat_j[col] >= cstart && mat_j[col] < cend) {
662:         aj[diag_so_far++] = mat_j[col] - cstart;
663:         dnz++;
664:       } else { /* off-diagonal entries */
665:         bj[offd_so_far++] = mat_j[col];
666:         onz++;
667:       }
668:     }
669:     ailen[j] = dnz;
670:     bilen[j] = onz;
671:   }
672:   return(0);
673: }

675: /*
676:     This function sets the local j, a and ilen arrays (of the diagonal and off-diagonal part) of an MPIAIJ-matrix.
677:     The values in mat_i have to be sorted and the values in mat_j have to be sorted for each row (CSR-like).
678:     No off-processor parts off the matrix are allowed here, they are set at a later point by MatSetValues_MPIAIJ.
679:     Also, mat->was_assembled has to be false, otherwise the statement aj[rowstart_diag+dnz_row] = mat_j[col] - cstart;
680:     would not be true and the more complex MatSetValues_MPIAIJ has to be used.
681: */
682: PetscErrorCode MatSetValues_MPIAIJ_CopyFromCSRFormat(Mat mat,const PetscInt mat_j[],const PetscInt mat_i[],const PetscScalar mat_a[])
683: {
684:   Mat_MPIAIJ     *aij   = (Mat_MPIAIJ*)mat->data;
685:   Mat            A      = aij->A; /* diagonal part of the matrix */
686:   Mat            B      = aij->B; /* offdiagonal part of the matrix */
687:   Mat_SeqAIJ     *aijd  =(Mat_SeqAIJ*)(aij->A)->data,*aijo=(Mat_SeqAIJ*)(aij->B)->data;
688:   Mat_SeqAIJ     *a     = (Mat_SeqAIJ*)A->data;
689:   Mat_SeqAIJ     *b     = (Mat_SeqAIJ*)B->data;
690:   PetscInt       cstart = mat->cmap->rstart,cend = mat->cmap->rend;
691:   PetscInt       *ailen = a->ilen,*aj = a->j;
692:   PetscInt       *bilen = b->ilen,*bj = b->j;
693:   PetscInt       am     = aij->A->rmap->n,j;
694:   PetscInt       *full_diag_i=aijd->i,*full_offd_i=aijo->i; /* These variables can also include non-local elements, which are set at a later point. */
695:   PetscInt       col,dnz_row,onz_row,rowstart_diag,rowstart_offd;
696:   PetscScalar    *aa = a->a,*ba = b->a;

699:   /* Iterate over all rows of the matrix */
700:   for (j=0; j<am; j++) {
701:     dnz_row = onz_row = 0;
702:     rowstart_offd = full_offd_i[j];
703:     rowstart_diag = full_diag_i[j];
704:     /*  Iterate over all non-zero columns of the current row */
705:     for (col=mat_i[j]; col<mat_i[j+1]; col++) {
706:       /* If column is in the diagonal */
707:       if (mat_j[col] >= cstart && mat_j[col] < cend) {
708:         aj[rowstart_diag+dnz_row] = mat_j[col] - cstart;
709:         aa[rowstart_diag+dnz_row] = mat_a[col];
710:         dnz_row++;
711:       } else { /* off-diagonal entries */
712:         bj[rowstart_offd+onz_row] = mat_j[col];
713:         ba[rowstart_offd+onz_row] = mat_a[col];
714:         onz_row++;
715:       }
716:     }
717:     ailen[j] = dnz_row;
718:     bilen[j] = onz_row;
719:   }
720:   return(0);
721: }

723: PetscErrorCode MatGetValues_MPIAIJ(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[])
724: {
725:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)mat->data;
727:   PetscInt       i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend;
728:   PetscInt       cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col;

731:   for (i=0; i<m; i++) {
732:     if (idxm[i] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",idxm[i]);*/
733:     if (idxm[i] >= mat->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",idxm[i],mat->rmap->N-1);
734:     if (idxm[i] >= rstart && idxm[i] < rend) {
735:       row = idxm[i] - rstart;
736:       for (j=0; j<n; j++) {
737:         if (idxn[j] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column: %D",idxn[j]); */
738:         if (idxn[j] >= mat->cmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",idxn[j],mat->cmap->N-1);
739:         if (idxn[j] >= cstart && idxn[j] < cend) {
740:           col  = idxn[j] - cstart;
741:           MatGetValues(aij->A,1,&row,1,&col,v+i*n+j);
742:         } else {
743:           if (!aij->colmap) {
744:             MatCreateColmap_MPIAIJ_Private(mat);
745:           }
746: #if defined(PETSC_USE_CTABLE)
747:           PetscTableFind(aij->colmap,idxn[j]+1,&col);
748:           col--;
749: #else
750:           col = aij->colmap[idxn[j]] - 1;
751: #endif
752:           if ((col < 0) || (aij->garray[col] != idxn[j])) *(v+i*n+j) = 0.0;
753:           else {
754:             MatGetValues(aij->B,1,&row,1,&col,v+i*n+j);
755:           }
756:         }
757:       }
758:     } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local values currently supported");
759:   }
760:   return(0);
761: }

763: extern PetscErrorCode MatMultDiagonalBlock_MPIAIJ(Mat,Vec,Vec);

765: PetscErrorCode MatAssemblyBegin_MPIAIJ(Mat mat,MatAssemblyType mode)
766: {
767:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)mat->data;
769:   PetscInt       nstash,reallocs;

772:   if (aij->donotstash || mat->nooffprocentries) return(0);

774:   MatStashScatterBegin_Private(mat,&mat->stash,mat->rmap->range);
775:   MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);
776:   PetscInfo2(aij->A,"Stash has %D entries, uses %D mallocs.\n",nstash,reallocs);
777:   return(0);
778: }

780: PetscErrorCode MatAssemblyEnd_MPIAIJ(Mat mat,MatAssemblyType mode)
781: {
782:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)mat->data;
783:   Mat_SeqAIJ     *a   = (Mat_SeqAIJ*)aij->A->data;
785:   PetscMPIInt    n;
786:   PetscInt       i,j,rstart,ncols,flg;
787:   PetscInt       *row,*col;
788:   PetscBool      other_disassembled;
789:   PetscScalar    *val;

791:   /* do not use 'b = (Mat_SeqAIJ*)aij->B->data' as B can be reset in disassembly */

794:   if (!aij->donotstash && !mat->nooffprocentries) {
795:     while (1) {
796:       MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);
797:       if (!flg) break;

799:       for (i=0; i<n; ) {
800:         /* Now identify the consecutive vals belonging to the same row */
801:         for (j=i,rstart=row[j]; j<n; j++) {
802:           if (row[j] != rstart) break;
803:         }
804:         if (j < n) ncols = j-i;
805:         else       ncols = n-i;
806:         /* Now assemble all these values with a single function call */
807:         MatSetValues_MPIAIJ(mat,1,row+i,ncols,col+i,val+i,mat->insertmode);

809:         i = j;
810:       }
811:     }
812:     MatStashScatterEnd_Private(&mat->stash);
813:   }
814:   MatAssemblyBegin(aij->A,mode);
815:   MatAssemblyEnd(aij->A,mode);

817:   /* determine if any processor has disassembled, if so we must
818:      also disassemble ourselfs, in order that we may reassemble. */
819:   /*
820:      if nonzero structure of submatrix B cannot change then we know that
821:      no processor disassembled thus we can skip this stuff
822:   */
823:   if (!((Mat_SeqAIJ*)aij->B->data)->nonew) {
824:     MPIU_Allreduce(&mat->was_assembled,&other_disassembled,1,MPIU_BOOL,MPI_PROD,PetscObjectComm((PetscObject)mat));
825:     if (mat->was_assembled && !other_disassembled) {
826:       MatDisAssemble_MPIAIJ(mat);
827:     }
828:   }
829:   if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) {
830:     MatSetUpMultiply_MPIAIJ(mat);
831:   }
832:   MatSetOption(aij->B,MAT_USE_INODES,PETSC_FALSE);
833:   MatAssemblyBegin(aij->B,mode);
834:   MatAssemblyEnd(aij->B,mode);

836:   PetscFree2(aij->rowvalues,aij->rowindices);

838:   aij->rowvalues = 0;

840:   VecDestroy(&aij->diag);
841:   if (a->inode.size) mat->ops->multdiagonalblock = MatMultDiagonalBlock_MPIAIJ;

843:   /* if no new nonzero locations are allowed in matrix then only set the matrix state the first time through */
844:   if ((!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) || !((Mat_SeqAIJ*)(aij->A->data))->nonew) {
845:     PetscObjectState state = aij->A->nonzerostate + aij->B->nonzerostate;
846:     MPIU_Allreduce(&state,&mat->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)mat));
847:   }
848:   return(0);
849: }

851: PetscErrorCode MatZeroEntries_MPIAIJ(Mat A)
852: {
853:   Mat_MPIAIJ     *l = (Mat_MPIAIJ*)A->data;

857:   MatZeroEntries(l->A);
858:   MatZeroEntries(l->B);
859:   return(0);
860: }

862: PetscErrorCode MatZeroRows_MPIAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b)
863: {
864:   Mat_MPIAIJ    *mat    = (Mat_MPIAIJ *) A->data;
865:   PetscInt      *lrows;
866:   PetscInt       r, len;
867:   PetscBool      cong;

871:   /* get locally owned rows */
872:   MatZeroRowsMapLocal_Private(A,N,rows,&len,&lrows);
873:   /* fix right hand side if needed */
874:   if (x && b) {
875:     const PetscScalar *xx;
876:     PetscScalar       *bb;

878:     VecGetArrayRead(x, &xx);
879:     VecGetArray(b, &bb);
880:     for (r = 0; r < len; ++r) bb[lrows[r]] = diag*xx[lrows[r]];
881:     VecRestoreArrayRead(x, &xx);
882:     VecRestoreArray(b, &bb);
883:   }
884:   /* Must zero l->B before l->A because the (diag) case below may put values into l->B*/
885:   MatZeroRows(mat->B, len, lrows, 0.0, NULL, NULL);
886:   MatHasCongruentLayouts(A,&cong);
887:   if ((diag != 0.0) && cong) {
888:     MatZeroRows(mat->A, len, lrows, diag, NULL, NULL);
889:   } else if (diag != 0.0) {
890:     MatZeroRows(mat->A, len, lrows, 0.0, NULL, NULL);
891:     if (((Mat_SeqAIJ *) mat->A->data)->nonew) SETERRQ(PETSC_COMM_SELF, PETSC_ERR_SUP, "MatZeroRows() on rectangular matrices cannot be used with the Mat options\nMAT_NEW_NONZERO_LOCATIONS,MAT_NEW_NONZERO_LOCATION_ERR,MAT_NEW_NONZERO_ALLOCATION_ERR");
892:     for (r = 0; r < len; ++r) {
893:       const PetscInt row = lrows[r] + A->rmap->rstart;
894:       MatSetValues(A, 1, &row, 1, &row, &diag, INSERT_VALUES);
895:     }
896:     MatAssemblyBegin(A, MAT_FINAL_ASSEMBLY);
897:     MatAssemblyEnd(A, MAT_FINAL_ASSEMBLY);
898:   } else {
899:     MatZeroRows(mat->A, len, lrows, 0.0, NULL, NULL);
900:   }
901:   PetscFree(lrows);

903:   /* only change matrix nonzero state if pattern was allowed to be changed */
904:   if (!((Mat_SeqAIJ*)(mat->A->data))->keepnonzeropattern) {
905:     PetscObjectState state = mat->A->nonzerostate + mat->B->nonzerostate;
906:     MPIU_Allreduce(&state,&A->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)A));
907:   }
908:   return(0);
909: }

911: PetscErrorCode MatZeroRowsColumns_MPIAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b)
912: {
913:   Mat_MPIAIJ        *l = (Mat_MPIAIJ*)A->data;
914:   PetscErrorCode    ierr;
915:   PetscMPIInt       n = A->rmap->n;
916:   PetscInt          i,j,r,m,p = 0,len = 0;
917:   PetscInt          *lrows,*owners = A->rmap->range;
918:   PetscSFNode       *rrows;
919:   PetscSF           sf;
920:   const PetscScalar *xx;
921:   PetscScalar       *bb,*mask;
922:   Vec               xmask,lmask;
923:   Mat_SeqAIJ        *aij = (Mat_SeqAIJ*)l->B->data;
924:   const PetscInt    *aj, *ii,*ridx;
925:   PetscScalar       *aa;

928:   /* Create SF where leaves are input rows and roots are owned rows */
929:   PetscMalloc1(n, &lrows);
930:   for (r = 0; r < n; ++r) lrows[r] = -1;
931:   PetscMalloc1(N, &rrows);
932:   for (r = 0; r < N; ++r) {
933:     const PetscInt idx   = rows[r];
934:     if (idx < 0 || A->rmap->N <= idx) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row %D out of range [0,%D)",idx,A->rmap->N);
935:     if (idx < owners[p] || owners[p+1] <= idx) { /* short-circuit the search if the last p owns this row too */
936:       PetscLayoutFindOwner(A->rmap,idx,&p);
937:     }
938:     rrows[r].rank  = p;
939:     rrows[r].index = rows[r] - owners[p];
940:   }
941:   PetscSFCreate(PetscObjectComm((PetscObject) A), &sf);
942:   PetscSFSetGraph(sf, n, N, NULL, PETSC_OWN_POINTER, rrows, PETSC_OWN_POINTER);
943:   /* Collect flags for rows to be zeroed */
944:   PetscSFReduceBegin(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);
945:   PetscSFReduceEnd(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);
946:   PetscSFDestroy(&sf);
947:   /* Compress and put in row numbers */
948:   for (r = 0; r < n; ++r) if (lrows[r] >= 0) lrows[len++] = r;
949:   /* zero diagonal part of matrix */
950:   MatZeroRowsColumns(l->A,len,lrows,diag,x,b);
951:   /* handle off diagonal part of matrix */
952:   MatCreateVecs(A,&xmask,NULL);
953:   VecDuplicate(l->lvec,&lmask);
954:   VecGetArray(xmask,&bb);
955:   for (i=0; i<len; i++) bb[lrows[i]] = 1;
956:   VecRestoreArray(xmask,&bb);
957:   VecScatterBegin(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);
958:   VecScatterEnd(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);
959:   VecDestroy(&xmask);
960:   if (x) {
961:     VecScatterBegin(l->Mvctx,x,l->lvec,INSERT_VALUES,SCATTER_FORWARD);
962:     VecScatterEnd(l->Mvctx,x,l->lvec,INSERT_VALUES,SCATTER_FORWARD);
963:     VecGetArrayRead(l->lvec,&xx);
964:     VecGetArray(b,&bb);
965:   }
966:   VecGetArray(lmask,&mask);
967:   /* remove zeroed rows of off diagonal matrix */
968:   ii = aij->i;
969:   for (i=0; i<len; i++) {
970:     PetscMemzero(aij->a + ii[lrows[i]],(ii[lrows[i]+1] - ii[lrows[i]])*sizeof(PetscScalar));
971:   }
972:   /* loop over all elements of off process part of matrix zeroing removed columns*/
973:   if (aij->compressedrow.use) {
974:     m    = aij->compressedrow.nrows;
975:     ii   = aij->compressedrow.i;
976:     ridx = aij->compressedrow.rindex;
977:     for (i=0; i<m; i++) {
978:       n  = ii[i+1] - ii[i];
979:       aj = aij->j + ii[i];
980:       aa = aij->a + ii[i];

982:       for (j=0; j<n; j++) {
983:         if (PetscAbsScalar(mask[*aj])) {
984:           if (b) bb[*ridx] -= *aa*xx[*aj];
985:           *aa = 0.0;
986:         }
987:         aa++;
988:         aj++;
989:       }
990:       ridx++;
991:     }
992:   } else { /* do not use compressed row format */
993:     m = l->B->rmap->n;
994:     for (i=0; i<m; i++) {
995:       n  = ii[i+1] - ii[i];
996:       aj = aij->j + ii[i];
997:       aa = aij->a + ii[i];
998:       for (j=0; j<n; j++) {
999:         if (PetscAbsScalar(mask[*aj])) {
1000:           if (b) bb[i] -= *aa*xx[*aj];
1001:           *aa = 0.0;
1002:         }
1003:         aa++;
1004:         aj++;
1005:       }
1006:     }
1007:   }
1008:   if (x) {
1009:     VecRestoreArray(b,&bb);
1010:     VecRestoreArrayRead(l->lvec,&xx);
1011:   }
1012:   VecRestoreArray(lmask,&mask);
1013:   VecDestroy(&lmask);
1014:   PetscFree(lrows);

1016:   /* only change matrix nonzero state if pattern was allowed to be changed */
1017:   if (!((Mat_SeqAIJ*)(l->A->data))->keepnonzeropattern) {
1018:     PetscObjectState state = l->A->nonzerostate + l->B->nonzerostate;
1019:     MPIU_Allreduce(&state,&A->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)A));
1020:   }
1021:   return(0);
1022: }

1024: PetscErrorCode MatMult_MPIAIJ(Mat A,Vec xx,Vec yy)
1025: {
1026:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;
1028:   PetscInt       nt;
1029:   VecScatter     Mvctx = a->Mvctx;

1032:   VecGetLocalSize(xx,&nt);
1033:   if (nt != A->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible partition of A (%D) and xx (%D)",A->cmap->n,nt);

1035:   VecScatterBegin(Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
1036:   (*a->A->ops->mult)(a->A,xx,yy);
1037:   VecScatterEnd(Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
1038:   (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);
1039:   return(0);
1040: }

1042: PetscErrorCode MatMultDiagonalBlock_MPIAIJ(Mat A,Vec bb,Vec xx)
1043: {
1044:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;

1048:   MatMultDiagonalBlock(a->A,bb,xx);
1049:   return(0);
1050: }

1052: PetscErrorCode MatMultAdd_MPIAIJ(Mat A,Vec xx,Vec yy,Vec zz)
1053: {
1054:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;
1056:   VecScatter     Mvctx = a->Mvctx;

1059:   if (a->Mvctx_mpi1_flg) Mvctx = a->Mvctx_mpi1;
1060:   VecScatterBegin(Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
1061:   (*a->A->ops->multadd)(a->A,xx,yy,zz);
1062:   VecScatterEnd(Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
1063:   (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);
1064:   return(0);
1065: }

1067: PetscErrorCode MatMultTranspose_MPIAIJ(Mat A,Vec xx,Vec yy)
1068: {
1069:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;
1071:   PetscBool      merged;

1074:   VecScatterGetMerged(a->Mvctx,&merged);
1075:   /* do nondiagonal part */
1076:   (*a->B->ops->multtranspose)(a->B,xx,a->lvec);
1077:   if (!merged) {
1078:     /* send it on its way */
1079:     VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
1080:     /* do local part */
1081:     (*a->A->ops->multtranspose)(a->A,xx,yy);
1082:     /* receive remote parts: note this assumes the values are not actually */
1083:     /* added in yy until the next line, */
1084:     VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
1085:   } else {
1086:     /* do local part */
1087:     (*a->A->ops->multtranspose)(a->A,xx,yy);
1088:     /* send it on its way */
1089:     VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
1090:     /* values actually were received in the Begin() but we need to call this nop */
1091:     VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
1092:   }
1093:   return(0);
1094: }

1096: PetscErrorCode MatIsTranspose_MPIAIJ(Mat Amat,Mat Bmat,PetscReal tol,PetscBool  *f)
1097: {
1098:   MPI_Comm       comm;
1099:   Mat_MPIAIJ     *Aij = (Mat_MPIAIJ*) Amat->data, *Bij;
1100:   Mat            Adia = Aij->A, Bdia, Aoff,Boff,*Aoffs,*Boffs;
1101:   IS             Me,Notme;
1103:   PetscInt       M,N,first,last,*notme,i;
1104:   PetscBool      lf;
1105:   PetscMPIInt    size;

1108:   /* Easy test: symmetric diagonal block */
1109:   Bij  = (Mat_MPIAIJ*) Bmat->data; Bdia = Bij->A;
1110:   MatIsTranspose(Adia,Bdia,tol,&lf);
1111:   MPIU_Allreduce(&lf,f,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)Amat));
1112:   if (!*f) return(0);
1113:   PetscObjectGetComm((PetscObject)Amat,&comm);
1114:   MPI_Comm_size(comm,&size);
1115:   if (size == 1) return(0);

1117:   /* Hard test: off-diagonal block. This takes a MatCreateSubMatrix. */
1118:   MatGetSize(Amat,&M,&N);
1119:   MatGetOwnershipRange(Amat,&first,&last);
1120:   PetscMalloc1(N-last+first,&notme);
1121:   for (i=0; i<first; i++) notme[i] = i;
1122:   for (i=last; i<M; i++) notme[i-last+first] = i;
1123:   ISCreateGeneral(MPI_COMM_SELF,N-last+first,notme,PETSC_COPY_VALUES,&Notme);
1124:   ISCreateStride(MPI_COMM_SELF,last-first,first,1,&Me);
1125:   MatCreateSubMatrices(Amat,1,&Me,&Notme,MAT_INITIAL_MATRIX,&Aoffs);
1126:   Aoff = Aoffs[0];
1127:   MatCreateSubMatrices(Bmat,1,&Notme,&Me,MAT_INITIAL_MATRIX,&Boffs);
1128:   Boff = Boffs[0];
1129:   MatIsTranspose(Aoff,Boff,tol,f);
1130:   MatDestroyMatrices(1,&Aoffs);
1131:   MatDestroyMatrices(1,&Boffs);
1132:   ISDestroy(&Me);
1133:   ISDestroy(&Notme);
1134:   PetscFree(notme);
1135:   return(0);
1136: }

1138: PetscErrorCode MatIsSymmetric_MPIAIJ(Mat A,PetscReal tol,PetscBool  *f)
1139: {

1143:   MatIsTranspose_MPIAIJ(A,A,tol,f);
1144:   return(0);
1145: }

1147: PetscErrorCode MatMultTransposeAdd_MPIAIJ(Mat A,Vec xx,Vec yy,Vec zz)
1148: {
1149:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;

1153:   /* do nondiagonal part */
1154:   (*a->B->ops->multtranspose)(a->B,xx,a->lvec);
1155:   /* send it on its way */
1156:   VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);
1157:   /* do local part */
1158:   (*a->A->ops->multtransposeadd)(a->A,xx,yy,zz);
1159:   /* receive remote parts */
1160:   VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);
1161:   return(0);
1162: }

1164: /*
1165:   This only works correctly for square matrices where the subblock A->A is the
1166:    diagonal block
1167: */
1168: PetscErrorCode MatGetDiagonal_MPIAIJ(Mat A,Vec v)
1169: {
1171:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;

1174:   if (A->rmap->N != A->cmap->N) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block");
1175:   if (A->rmap->rstart != A->cmap->rstart || A->rmap->rend != A->cmap->rend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"row partition must equal col partition");
1176:   MatGetDiagonal(a->A,v);
1177:   return(0);
1178: }

1180: PetscErrorCode MatScale_MPIAIJ(Mat A,PetscScalar aa)
1181: {
1182:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;

1186:   MatScale(a->A,aa);
1187:   MatScale(a->B,aa);
1188:   return(0);
1189: }

1191: PetscErrorCode MatDestroy_MPIAIJ(Mat mat)
1192: {
1193:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)mat->data;

1197: #if defined(PETSC_USE_LOG)
1198:   PetscLogObjectState((PetscObject)mat,"Rows=%D, Cols=%D",mat->rmap->N,mat->cmap->N);
1199: #endif
1200:   MatStashDestroy_Private(&mat->stash);
1201:   VecDestroy(&aij->diag);
1202:   MatDestroy(&aij->A);
1203:   MatDestroy(&aij->B);
1204: #if defined(PETSC_USE_CTABLE)
1205:   PetscTableDestroy(&aij->colmap);
1206: #else
1207:   PetscFree(aij->colmap);
1208: #endif
1209:   PetscFree(aij->garray);
1210:   VecDestroy(&aij->lvec);
1211:   VecScatterDestroy(&aij->Mvctx);
1212:   if (aij->Mvctx_mpi1) {VecScatterDestroy(&aij->Mvctx_mpi1);}
1213:   PetscFree2(aij->rowvalues,aij->rowindices);
1214:   PetscFree(aij->ld);
1215:   PetscFree(mat->data);

1217:   PetscObjectChangeTypeName((PetscObject)mat,0);
1218:   PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C",NULL);
1219:   PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C",NULL);
1220:   PetscObjectComposeFunction((PetscObject)mat,"MatIsTranspose_C",NULL);
1221:   PetscObjectComposeFunction((PetscObject)mat,"MatMPIAIJSetPreallocation_C",NULL);
1222:   PetscObjectComposeFunction((PetscObject)mat,"MatResetPreallocation_C",NULL);
1223:   PetscObjectComposeFunction((PetscObject)mat,"MatMPIAIJSetPreallocationCSR_C",NULL);
1224:   PetscObjectComposeFunction((PetscObject)mat,"MatDiagonalScaleLocal_C",NULL);
1225:   PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpiaij_mpisbaij_C",NULL);
1226: #if defined(PETSC_HAVE_ELEMENTAL)
1227:   PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpiaij_elemental_C",NULL);
1228: #endif
1229: #if defined(PETSC_HAVE_HYPRE)
1230:   PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpiaij_hypre_C",NULL);
1231:   PetscObjectComposeFunction((PetscObject)mat,"MatMatMatMult_transpose_mpiaij_mpiaij_C",NULL);
1232: #endif
1233:   PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpiaij_is_C",NULL);
1234:   PetscObjectComposeFunction((PetscObject)mat,"MatPtAP_is_mpiaij_C",NULL);
1235:   return(0);
1236: }

1238: PetscErrorCode MatView_MPIAIJ_Binary(Mat mat,PetscViewer viewer)
1239: {
1240:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)mat->data;
1241:   Mat_SeqAIJ     *A   = (Mat_SeqAIJ*)aij->A->data;
1242:   Mat_SeqAIJ     *B   = (Mat_SeqAIJ*)aij->B->data;
1244:   PetscMPIInt    rank,size,tag = ((PetscObject)viewer)->tag;
1245:   int            fd;
1246:   PetscInt       nz,header[4],*row_lengths,*range=0,rlen,i;
1247:   PetscInt       nzmax,*column_indices,j,k,col,*garray = aij->garray,cnt,cstart = mat->cmap->rstart,rnz = 0;
1248:   PetscScalar    *column_values;
1249:   PetscInt       message_count,flowcontrolcount;
1250:   FILE           *file;

1253:   MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);
1254:   MPI_Comm_size(PetscObjectComm((PetscObject)mat),&size);
1255:   nz   = A->nz + B->nz;
1256:   PetscViewerBinaryGetDescriptor(viewer,&fd);
1257:   if (!rank) {
1258:     header[0] = MAT_FILE_CLASSID;
1259:     header[1] = mat->rmap->N;
1260:     header[2] = mat->cmap->N;

1262:     MPI_Reduce(&nz,&header[3],1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));
1263:     PetscBinaryWrite(fd,header,4,PETSC_INT,PETSC_TRUE);
1264:     /* get largest number of rows any processor has */
1265:     rlen  = mat->rmap->n;
1266:     range = mat->rmap->range;
1267:     for (i=1; i<size; i++) rlen = PetscMax(rlen,range[i+1] - range[i]);
1268:   } else {
1269:     MPI_Reduce(&nz,0,1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));
1270:     rlen = mat->rmap->n;
1271:   }

1273:   /* load up the local row counts */
1274:   PetscMalloc1(rlen+1,&row_lengths);
1275:   for (i=0; i<mat->rmap->n; i++) row_lengths[i] = A->i[i+1] - A->i[i] + B->i[i+1] - B->i[i];

1277:   /* store the row lengths to the file */
1278:   PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);
1279:   if (!rank) {
1280:     PetscBinaryWrite(fd,row_lengths,mat->rmap->n,PETSC_INT,PETSC_TRUE);
1281:     for (i=1; i<size; i++) {
1282:       PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);
1283:       rlen = range[i+1] - range[i];
1284:       MPIULong_Recv(row_lengths,rlen,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat));
1285:       PetscBinaryWrite(fd,row_lengths,rlen,PETSC_INT,PETSC_TRUE);
1286:     }
1287:     PetscViewerFlowControlEndMaster(viewer,&message_count);
1288:   } else {
1289:     PetscViewerFlowControlStepWorker(viewer,rank,&message_count);
1290:     MPIULong_Send(row_lengths,mat->rmap->n,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));
1291:     PetscViewerFlowControlEndWorker(viewer,&message_count);
1292:   }
1293:   PetscFree(row_lengths);

1295:   /* load up the local column indices */
1296:   nzmax = nz; /* th processor needs space a largest processor needs */
1297:   MPI_Reduce(&nz,&nzmax,1,MPIU_INT,MPI_MAX,0,PetscObjectComm((PetscObject)mat));
1298:   PetscMalloc1(nzmax+1,&column_indices);
1299:   cnt   = 0;
1300:   for (i=0; i<mat->rmap->n; i++) {
1301:     for (j=B->i[i]; j<B->i[i+1]; j++) {
1302:       if ((col = garray[B->j[j]]) > cstart) break;
1303:       column_indices[cnt++] = col;
1304:     }
1305:     for (k=A->i[i]; k<A->i[i+1]; k++) column_indices[cnt++] = A->j[k] + cstart;
1306:     for (; j<B->i[i+1]; j++) column_indices[cnt++] = garray[B->j[j]];
1307:   }
1308:   if (cnt != A->nz + B->nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: cnt = %D nz = %D",cnt,A->nz+B->nz);

1310:   /* store the column indices to the file */
1311:   PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);
1312:   if (!rank) {
1313:     MPI_Status status;
1314:     PetscBinaryWrite(fd,column_indices,nz,PETSC_INT,PETSC_TRUE);
1315:     for (i=1; i<size; i++) {
1316:       PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);
1317:       MPI_Recv(&rnz,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);
1318:       if (rnz > nzmax) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: nz = %D nzmax = %D",nz,nzmax);
1319:       MPIULong_Recv(column_indices,rnz,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat));
1320:       PetscBinaryWrite(fd,column_indices,rnz,PETSC_INT,PETSC_TRUE);
1321:     }
1322:     PetscViewerFlowControlEndMaster(viewer,&message_count);
1323:   } else {
1324:     PetscViewerFlowControlStepWorker(viewer,rank,&message_count);
1325:     MPI_Send(&nz,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));
1326:     MPIULong_Send(column_indices,nz,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));
1327:     PetscViewerFlowControlEndWorker(viewer,&message_count);
1328:   }
1329:   PetscFree(column_indices);

1331:   /* load up the local column values */
1332:   PetscMalloc1(nzmax+1,&column_values);
1333:   cnt  = 0;
1334:   for (i=0; i<mat->rmap->n; i++) {
1335:     for (j=B->i[i]; j<B->i[i+1]; j++) {
1336:       if (garray[B->j[j]] > cstart) break;
1337:       column_values[cnt++] = B->a[j];
1338:     }
1339:     for (k=A->i[i]; k<A->i[i+1]; k++) column_values[cnt++] = A->a[k];
1340:     for (; j<B->i[i+1]; j++) column_values[cnt++] = B->a[j];
1341:   }
1342:   if (cnt != A->nz + B->nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Internal PETSc error: cnt = %D nz = %D",cnt,A->nz+B->nz);

1344:   /* store the column values to the file */
1345:   PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);
1346:   if (!rank) {
1347:     MPI_Status status;
1348:     PetscBinaryWrite(fd,column_values,nz,PETSC_SCALAR,PETSC_TRUE);
1349:     for (i=1; i<size; i++) {
1350:       PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);
1351:       MPI_Recv(&rnz,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);
1352:       if (rnz > nzmax) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: nz = %D nzmax = %D",nz,nzmax);
1353:       MPIULong_Recv(column_values,rnz,MPIU_SCALAR,i,tag,PetscObjectComm((PetscObject)mat));
1354:       PetscBinaryWrite(fd,column_values,rnz,PETSC_SCALAR,PETSC_TRUE);
1355:     }
1356:     PetscViewerFlowControlEndMaster(viewer,&message_count);
1357:   } else {
1358:     PetscViewerFlowControlStepWorker(viewer,rank,&message_count);
1359:     MPI_Send(&nz,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));
1360:     MPIULong_Send(column_values,nz,MPIU_SCALAR,0,tag,PetscObjectComm((PetscObject)mat));
1361:     PetscViewerFlowControlEndWorker(viewer,&message_count);
1362:   }
1363:   PetscFree(column_values);

1365:   PetscViewerBinaryGetInfoPointer(viewer,&file);
1366:   if (file) fprintf(file,"-matload_block_size %d\n",(int)PetscAbs(mat->rmap->bs));
1367:   return(0);
1368: }

1370:  #include <petscdraw.h>
1371: PetscErrorCode MatView_MPIAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer)
1372: {
1373:   Mat_MPIAIJ        *aij = (Mat_MPIAIJ*)mat->data;
1374:   PetscErrorCode    ierr;
1375:   PetscMPIInt       rank = aij->rank,size = aij->size;
1376:   PetscBool         isdraw,iascii,isbinary;
1377:   PetscViewer       sviewer;
1378:   PetscViewerFormat format;

1381:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);
1382:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
1383:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);
1384:   if (iascii) {
1385:     PetscViewerGetFormat(viewer,&format);
1386:     if (format == PETSC_VIEWER_LOAD_BALANCE) {
1387:       PetscInt i,nmax = 0,nmin = PETSC_MAX_INT,navg = 0,*nz,nzlocal = ((Mat_SeqAIJ*) (aij->A->data))->nz + ((Mat_SeqAIJ*) (aij->B->data))->nz;
1388:       PetscMalloc1(size,&nz);
1389:       MPI_Allgather(&nzlocal,1,MPIU_INT,nz,1,MPIU_INT,PetscObjectComm((PetscObject)mat));
1390:       for (i=0; i<(PetscInt)size; i++) {
1391:         nmax = PetscMax(nmax,nz[i]);
1392:         nmin = PetscMin(nmin,nz[i]);
1393:         navg += nz[i];
1394:       }
1395:       PetscFree(nz);
1396:       navg = navg/size;
1397:       PetscViewerASCIIPrintf(viewer,"Load Balance - Nonzeros: Min %D  avg %D  max %D\n",nmin,navg,nmax);
1398:       return(0);
1399:     }
1400:     PetscViewerGetFormat(viewer,&format);
1401:     if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) {
1402:       MatInfo   info;
1403:       PetscBool inodes;

1405:       MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);
1406:       MatGetInfo(mat,MAT_LOCAL,&info);
1407:       MatInodeGetInodeSizes(aij->A,NULL,(PetscInt**)&inodes,NULL);
1408:       PetscViewerASCIIPushSynchronized(viewer);
1409:       if (!inodes) {
1410:         PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D mem %g, not using I-node routines\n",
1411:                                                   rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(double)info.memory);
1412:       } else {
1413:         PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D mem %g, using I-node routines\n",
1414:                                                   rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(double)info.memory);
1415:       }
1416:       MatGetInfo(aij->A,MAT_LOCAL,&info);
1417:       PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);
1418:       MatGetInfo(aij->B,MAT_LOCAL,&info);
1419:       PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);
1420:       PetscViewerFlush(viewer);
1421:       PetscViewerASCIIPopSynchronized(viewer);
1422:       PetscViewerASCIIPrintf(viewer,"Information on VecScatter used in matrix-vector product: \n");
1423:       VecScatterView(aij->Mvctx,viewer);
1424:       return(0);
1425:     } else if (format == PETSC_VIEWER_ASCII_INFO) {
1426:       PetscInt inodecount,inodelimit,*inodes;
1427:       MatInodeGetInodeSizes(aij->A,&inodecount,&inodes,&inodelimit);
1428:       if (inodes) {
1429:         PetscViewerASCIIPrintf(viewer,"using I-node (on process 0) routines: found %D nodes, limit used is %D\n",inodecount,inodelimit);
1430:       } else {
1431:         PetscViewerASCIIPrintf(viewer,"not using I-node (on process 0) routines\n");
1432:       }
1433:       return(0);
1434:     } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) {
1435:       return(0);
1436:     }
1437:   } else if (isbinary) {
1438:     if (size == 1) {
1439:       PetscObjectSetName((PetscObject)aij->A,((PetscObject)mat)->name);
1440:       MatView(aij->A,viewer);
1441:     } else {
1442:       MatView_MPIAIJ_Binary(mat,viewer);
1443:     }
1444:     return(0);
1445:   } else if (isdraw) {
1446:     PetscDraw draw;
1447:     PetscBool isnull;
1448:     PetscViewerDrawGetDraw(viewer,0,&draw);
1449:     PetscDrawIsNull(draw,&isnull);
1450:     if (isnull) return(0);
1451:   }

1453:   {
1454:     /* assemble the entire matrix onto first processor. */
1455:     Mat        A;
1456:     Mat_SeqAIJ *Aloc;
1457:     PetscInt   M = mat->rmap->N,N = mat->cmap->N,m,*ai,*aj,row,*cols,i,*ct;
1458:     MatScalar  *a;

1460:     MatCreate(PetscObjectComm((PetscObject)mat),&A);
1461:     if (!rank) {
1462:       MatSetSizes(A,M,N,M,N);
1463:     } else {
1464:       MatSetSizes(A,0,0,M,N);
1465:     }
1466:     /* This is just a temporary matrix, so explicitly using MATMPIAIJ is probably best */
1467:     MatSetType(A,MATMPIAIJ);
1468:     MatMPIAIJSetPreallocation(A,0,NULL,0,NULL);
1469:     MatSetOption(A,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_FALSE);
1470:     PetscLogObjectParent((PetscObject)mat,(PetscObject)A);

1472:     /* copy over the A part */
1473:     Aloc = (Mat_SeqAIJ*)aij->A->data;
1474:     m    = aij->A->rmap->n; ai = Aloc->i; aj = Aloc->j; a = Aloc->a;
1475:     row  = mat->rmap->rstart;
1476:     for (i=0; i<ai[m]; i++) aj[i] += mat->cmap->rstart;
1477:     for (i=0; i<m; i++) {
1478:       MatSetValues(A,1,&row,ai[i+1]-ai[i],aj,a,INSERT_VALUES);
1479:       row++;
1480:       a += ai[i+1]-ai[i]; aj += ai[i+1]-ai[i];
1481:     }
1482:     aj = Aloc->j;
1483:     for (i=0; i<ai[m]; i++) aj[i] -= mat->cmap->rstart;

1485:     /* copy over the B part */
1486:     Aloc = (Mat_SeqAIJ*)aij->B->data;
1487:     m    = aij->B->rmap->n;  ai = Aloc->i; aj = Aloc->j; a = Aloc->a;
1488:     row  = mat->rmap->rstart;
1489:     PetscMalloc1(ai[m]+1,&cols);
1490:     ct   = cols;
1491:     for (i=0; i<ai[m]; i++) cols[i] = aij->garray[aj[i]];
1492:     for (i=0; i<m; i++) {
1493:       MatSetValues(A,1,&row,ai[i+1]-ai[i],cols,a,INSERT_VALUES);
1494:       row++;
1495:       a += ai[i+1]-ai[i]; cols += ai[i+1]-ai[i];
1496:     }
1497:     PetscFree(ct);
1498:     MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);
1499:     MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);
1500:     /*
1501:        Everyone has to call to draw the matrix since the graphics waits are
1502:        synchronized across all processors that share the PetscDraw object
1503:     */
1504:     PetscViewerGetSubViewer(viewer,PETSC_COMM_SELF,&sviewer);
1505:     if (!rank) {
1506:       PetscObjectSetName((PetscObject)((Mat_MPIAIJ*)(A->data))->A,((PetscObject)mat)->name);
1507:       MatView_SeqAIJ(((Mat_MPIAIJ*)(A->data))->A,sviewer);
1508:     }
1509:     PetscViewerRestoreSubViewer(viewer,PETSC_COMM_SELF,&sviewer);
1510:     PetscViewerFlush(viewer);
1511:     MatDestroy(&A);
1512:   }
1513:   return(0);
1514: }

1516: PetscErrorCode MatView_MPIAIJ(Mat mat,PetscViewer viewer)
1517: {
1519:   PetscBool      iascii,isdraw,issocket,isbinary;

1522:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
1523:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);
1524:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);
1525:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSOCKET,&issocket);
1526:   if (iascii || isdraw || isbinary || issocket) {
1527:     MatView_MPIAIJ_ASCIIorDraworSocket(mat,viewer);
1528:   }
1529:   return(0);
1530: }

1532: PetscErrorCode MatSOR_MPIAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx)
1533: {
1534:   Mat_MPIAIJ     *mat = (Mat_MPIAIJ*)matin->data;
1536:   Vec            bb1 = 0;
1537:   PetscBool      hasop;

1540:   if (flag == SOR_APPLY_UPPER) {
1541:     (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
1542:     return(0);
1543:   }

1545:   if (its > 1 || ~flag & SOR_ZERO_INITIAL_GUESS || flag & SOR_EISENSTAT) {
1546:     VecDuplicate(bb,&bb1);
1547:   }

1549:   if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) {
1550:     if (flag & SOR_ZERO_INITIAL_GUESS) {
1551:       (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
1552:       its--;
1553:     }

1555:     while (its--) {
1556:       VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
1557:       VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);

1559:       /* update rhs: bb1 = bb - B*x */
1560:       VecScale(mat->lvec,-1.0);
1561:       (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);

1563:       /* local sweep */
1564:       (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,1,xx);
1565:     }
1566:   } else if (flag & SOR_LOCAL_FORWARD_SWEEP) {
1567:     if (flag & SOR_ZERO_INITIAL_GUESS) {
1568:       (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
1569:       its--;
1570:     }
1571:     while (its--) {
1572:       VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
1573:       VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);

1575:       /* update rhs: bb1 = bb - B*x */
1576:       VecScale(mat->lvec,-1.0);
1577:       (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);

1579:       /* local sweep */
1580:       (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_FORWARD_SWEEP,fshift,lits,1,xx);
1581:     }
1582:   } else if (flag & SOR_LOCAL_BACKWARD_SWEEP) {
1583:     if (flag & SOR_ZERO_INITIAL_GUESS) {
1584:       (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
1585:       its--;
1586:     }
1587:     while (its--) {
1588:       VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
1589:       VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);

1591:       /* update rhs: bb1 = bb - B*x */
1592:       VecScale(mat->lvec,-1.0);
1593:       (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);

1595:       /* local sweep */
1596:       (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_BACKWARD_SWEEP,fshift,lits,1,xx);
1597:     }
1598:   } else if (flag & SOR_EISENSTAT) {
1599:     Vec xx1;

1601:     VecDuplicate(bb,&xx1);
1602:     (*mat->A->ops->sor)(mat->A,bb,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_BACKWARD_SWEEP),fshift,lits,1,xx);

1604:     VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
1605:     VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
1606:     if (!mat->diag) {
1607:       MatCreateVecs(matin,&mat->diag,NULL);
1608:       MatGetDiagonal(matin,mat->diag);
1609:     }
1610:     MatHasOperation(matin,MATOP_MULT_DIAGONAL_BLOCK,&hasop);
1611:     if (hasop) {
1612:       MatMultDiagonalBlock(matin,xx,bb1);
1613:     } else {
1614:       VecPointwiseMult(bb1,mat->diag,xx);
1615:     }
1616:     VecAYPX(bb1,(omega-2.0)/omega,bb);

1618:     MatMultAdd(mat->B,mat->lvec,bb1,bb1);

1620:     /* local sweep */
1621:     (*mat->A->ops->sor)(mat->A,bb1,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_FORWARD_SWEEP),fshift,lits,1,xx1);
1622:     VecAXPY(xx,1.0,xx1);
1623:     VecDestroy(&xx1);
1624:   } else SETERRQ(PetscObjectComm((PetscObject)matin),PETSC_ERR_SUP,"Parallel SOR not supported");

1626:   VecDestroy(&bb1);

1628:   matin->factorerrortype = mat->A->factorerrortype;
1629:   return(0);
1630: }

1632: PetscErrorCode MatPermute_MPIAIJ(Mat A,IS rowp,IS colp,Mat *B)
1633: {
1634:   Mat            aA,aB,Aperm;
1635:   const PetscInt *rwant,*cwant,*gcols,*ai,*bi,*aj,*bj;
1636:   PetscScalar    *aa,*ba;
1637:   PetscInt       i,j,m,n,ng,anz,bnz,*dnnz,*onnz,*tdnnz,*tonnz,*rdest,*cdest,*work,*gcdest;
1638:   PetscSF        rowsf,sf;
1639:   IS             parcolp = NULL;
1640:   PetscBool      done;

1644:   MatGetLocalSize(A,&m,&n);
1645:   ISGetIndices(rowp,&rwant);
1646:   ISGetIndices(colp,&cwant);
1647:   PetscMalloc3(PetscMax(m,n),&work,m,&rdest,n,&cdest);

1649:   /* Invert row permutation to find out where my rows should go */
1650:   PetscSFCreate(PetscObjectComm((PetscObject)A),&rowsf);
1651:   PetscSFSetGraphLayout(rowsf,A->rmap,A->rmap->n,NULL,PETSC_OWN_POINTER,rwant);
1652:   PetscSFSetFromOptions(rowsf);
1653:   for (i=0; i<m; i++) work[i] = A->rmap->rstart + i;
1654:   PetscSFReduceBegin(rowsf,MPIU_INT,work,rdest,MPIU_REPLACE);
1655:   PetscSFReduceEnd(rowsf,MPIU_INT,work,rdest,MPIU_REPLACE);

1657:   /* Invert column permutation to find out where my columns should go */
1658:   PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);
1659:   PetscSFSetGraphLayout(sf,A->cmap,A->cmap->n,NULL,PETSC_OWN_POINTER,cwant);
1660:   PetscSFSetFromOptions(sf);
1661:   for (i=0; i<n; i++) work[i] = A->cmap->rstart + i;
1662:   PetscSFReduceBegin(sf,MPIU_INT,work,cdest,MPIU_REPLACE);
1663:   PetscSFReduceEnd(sf,MPIU_INT,work,cdest,MPIU_REPLACE);
1664:   PetscSFDestroy(&sf);

1666:   ISRestoreIndices(rowp,&rwant);
1667:   ISRestoreIndices(colp,&cwant);
1668:   MatMPIAIJGetSeqAIJ(A,&aA,&aB,&gcols);

1670:   /* Find out where my gcols should go */
1671:   MatGetSize(aB,NULL,&ng);
1672:   PetscMalloc1(ng,&gcdest);
1673:   PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);
1674:   PetscSFSetGraphLayout(sf,A->cmap,ng,NULL,PETSC_OWN_POINTER,gcols);
1675:   PetscSFSetFromOptions(sf);
1676:   PetscSFBcastBegin(sf,MPIU_INT,cdest,gcdest);
1677:   PetscSFBcastEnd(sf,MPIU_INT,cdest,gcdest);
1678:   PetscSFDestroy(&sf);

1680:   PetscCalloc4(m,&dnnz,m,&onnz,m,&tdnnz,m,&tonnz);
1681:   MatGetRowIJ(aA,0,PETSC_FALSE,PETSC_FALSE,&anz,&ai,&aj,&done);
1682:   MatGetRowIJ(aB,0,PETSC_FALSE,PETSC_FALSE,&bnz,&bi,&bj,&done);
1683:   for (i=0; i<m; i++) {
1684:     PetscInt row = rdest[i],rowner;
1685:     PetscLayoutFindOwner(A->rmap,row,&rowner);
1686:     for (j=ai[i]; j<ai[i+1]; j++) {
1687:       PetscInt cowner,col = cdest[aj[j]];
1688:       PetscLayoutFindOwner(A->cmap,col,&cowner); /* Could build an index for the columns to eliminate this search */
1689:       if (rowner == cowner) dnnz[i]++;
1690:       else onnz[i]++;
1691:     }
1692:     for (j=bi[i]; j<bi[i+1]; j++) {
1693:       PetscInt cowner,col = gcdest[bj[j]];
1694:       PetscLayoutFindOwner(A->cmap,col,&cowner);
1695:       if (rowner == cowner) dnnz[i]++;
1696:       else onnz[i]++;
1697:     }
1698:   }
1699:   PetscSFBcastBegin(rowsf,MPIU_INT,dnnz,tdnnz);
1700:   PetscSFBcastEnd(rowsf,MPIU_INT,dnnz,tdnnz);
1701:   PetscSFBcastBegin(rowsf,MPIU_INT,onnz,tonnz);
1702:   PetscSFBcastEnd(rowsf,MPIU_INT,onnz,tonnz);
1703:   PetscSFDestroy(&rowsf);

1705:   MatCreateAIJ(PetscObjectComm((PetscObject)A),A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N,0,tdnnz,0,tonnz,&Aperm);
1706:   MatSeqAIJGetArray(aA,&aa);
1707:   MatSeqAIJGetArray(aB,&ba);
1708:   for (i=0; i<m; i++) {
1709:     PetscInt *acols = dnnz,*bcols = onnz; /* Repurpose now-unneeded arrays */
1710:     PetscInt j0,rowlen;
1711:     rowlen = ai[i+1] - ai[i];
1712:     for (j0=j=0; j<rowlen; j0=j) { /* rowlen could be larger than number of rows m, so sum in batches */
1713:       for ( ; j<PetscMin(rowlen,j0+m); j++) acols[j-j0] = cdest[aj[ai[i]+j]];
1714:       MatSetValues(Aperm,1,&rdest[i],j-j0,acols,aa+ai[i]+j0,INSERT_VALUES);
1715:     }
1716:     rowlen = bi[i+1] - bi[i];
1717:     for (j0=j=0; j<rowlen; j0=j) {
1718:       for ( ; j<PetscMin(rowlen,j0+m); j++) bcols[j-j0] = gcdest[bj[bi[i]+j]];
1719:       MatSetValues(Aperm,1,&rdest[i],j-j0,bcols,ba+bi[i]+j0,INSERT_VALUES);
1720:     }
1721:   }
1722:   MatAssemblyBegin(Aperm,MAT_FINAL_ASSEMBLY);
1723:   MatAssemblyEnd(Aperm,MAT_FINAL_ASSEMBLY);
1724:   MatRestoreRowIJ(aA,0,PETSC_FALSE,PETSC_FALSE,&anz,&ai,&aj,&done);
1725:   MatRestoreRowIJ(aB,0,PETSC_FALSE,PETSC_FALSE,&bnz,&bi,&bj,&done);
1726:   MatSeqAIJRestoreArray(aA,&aa);
1727:   MatSeqAIJRestoreArray(aB,&ba);
1728:   PetscFree4(dnnz,onnz,tdnnz,tonnz);
1729:   PetscFree3(work,rdest,cdest);
1730:   PetscFree(gcdest);
1731:   if (parcolp) {ISDestroy(&colp);}
1732:   *B = Aperm;
1733:   return(0);
1734: }

1736: PetscErrorCode  MatGetGhosts_MPIAIJ(Mat mat,PetscInt *nghosts,const PetscInt *ghosts[])
1737: {
1738:   Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;

1742:   MatGetSize(aij->B,NULL,nghosts);
1743:   if (ghosts) *ghosts = aij->garray;
1744:   return(0);
1745: }

1747: PetscErrorCode MatGetInfo_MPIAIJ(Mat matin,MatInfoType flag,MatInfo *info)
1748: {
1749:   Mat_MPIAIJ     *mat = (Mat_MPIAIJ*)matin->data;
1750:   Mat            A    = mat->A,B = mat->B;
1752:   PetscReal      isend[5],irecv[5];

1755:   info->block_size = 1.0;
1756:   MatGetInfo(A,MAT_LOCAL,info);

1758:   isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded;
1759:   isend[3] = info->memory;  isend[4] = info->mallocs;

1761:   MatGetInfo(B,MAT_LOCAL,info);

1763:   isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded;
1764:   isend[3] += info->memory;  isend[4] += info->mallocs;
1765:   if (flag == MAT_LOCAL) {
1766:     info->nz_used      = isend[0];
1767:     info->nz_allocated = isend[1];
1768:     info->nz_unneeded  = isend[2];
1769:     info->memory       = isend[3];
1770:     info->mallocs      = isend[4];
1771:   } else if (flag == MAT_GLOBAL_MAX) {
1772:     MPIU_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)matin));

1774:     info->nz_used      = irecv[0];
1775:     info->nz_allocated = irecv[1];
1776:     info->nz_unneeded  = irecv[2];
1777:     info->memory       = irecv[3];
1778:     info->mallocs      = irecv[4];
1779:   } else if (flag == MAT_GLOBAL_SUM) {
1780:     MPIU_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)matin));

1782:     info->nz_used      = irecv[0];
1783:     info->nz_allocated = irecv[1];
1784:     info->nz_unneeded  = irecv[2];
1785:     info->memory       = irecv[3];
1786:     info->mallocs      = irecv[4];
1787:   }
1788:   info->fill_ratio_given  = 0; /* no parallel LU/ILU/Cholesky */
1789:   info->fill_ratio_needed = 0;
1790:   info->factor_mallocs    = 0;
1791:   return(0);
1792: }

1794: PetscErrorCode MatSetOption_MPIAIJ(Mat A,MatOption op,PetscBool flg)
1795: {
1796:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;

1800:   switch (op) {
1801:   case MAT_NEW_NONZERO_LOCATIONS:
1802:   case MAT_NEW_NONZERO_ALLOCATION_ERR:
1803:   case MAT_UNUSED_NONZERO_LOCATION_ERR:
1804:   case MAT_KEEP_NONZERO_PATTERN:
1805:   case MAT_NEW_NONZERO_LOCATION_ERR:
1806:   case MAT_USE_INODES:
1807:   case MAT_IGNORE_ZERO_ENTRIES:
1808:     MatCheckPreallocated(A,1);
1809:     MatSetOption(a->A,op,flg);
1810:     MatSetOption(a->B,op,flg);
1811:     break;
1812:   case MAT_ROW_ORIENTED:
1813:     MatCheckPreallocated(A,1);
1814:     a->roworiented = flg;

1816:     MatSetOption(a->A,op,flg);
1817:     MatSetOption(a->B,op,flg);
1818:     break;
1819:   case MAT_NEW_DIAGONALS:
1820:     PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);
1821:     break;
1822:   case MAT_IGNORE_OFF_PROC_ENTRIES:
1823:     a->donotstash = flg;
1824:     break;
1825:   case MAT_SPD:
1826:     A->spd_set = PETSC_TRUE;
1827:     A->spd     = flg;
1828:     if (flg) {
1829:       A->symmetric                  = PETSC_TRUE;
1830:       A->structurally_symmetric     = PETSC_TRUE;
1831:       A->symmetric_set              = PETSC_TRUE;
1832:       A->structurally_symmetric_set = PETSC_TRUE;
1833:     }
1834:     break;
1835:   case MAT_SYMMETRIC:
1836:     MatCheckPreallocated(A,1);
1837:     MatSetOption(a->A,op,flg);
1838:     break;
1839:   case MAT_STRUCTURALLY_SYMMETRIC:
1840:     MatCheckPreallocated(A,1);
1841:     MatSetOption(a->A,op,flg);
1842:     break;
1843:   case MAT_HERMITIAN:
1844:     MatCheckPreallocated(A,1);
1845:     MatSetOption(a->A,op,flg);
1846:     break;
1847:   case MAT_SYMMETRY_ETERNAL:
1848:     MatCheckPreallocated(A,1);
1849:     MatSetOption(a->A,op,flg);
1850:     break;
1851:   case MAT_SUBMAT_SINGLEIS:
1852:     A->submat_singleis = flg;
1853:     break;
1854:   case MAT_STRUCTURE_ONLY:
1855:     /* The option is handled directly by MatSetOption() */
1856:     break;
1857:   default:
1858:     SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %d",op);
1859:   }
1860:   return(0);
1861: }

1863: PetscErrorCode MatGetRow_MPIAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
1864: {
1865:   Mat_MPIAIJ     *mat = (Mat_MPIAIJ*)matin->data;
1866:   PetscScalar    *vworkA,*vworkB,**pvA,**pvB,*v_p;
1868:   PetscInt       i,*cworkA,*cworkB,**pcA,**pcB,cstart = matin->cmap->rstart;
1869:   PetscInt       nztot,nzA,nzB,lrow,rstart = matin->rmap->rstart,rend = matin->rmap->rend;
1870:   PetscInt       *cmap,*idx_p;

1873:   if (mat->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Already active");
1874:   mat->getrowactive = PETSC_TRUE;

1876:   if (!mat->rowvalues && (idx || v)) {
1877:     /*
1878:         allocate enough space to hold information from the longest row.
1879:     */
1880:     Mat_SeqAIJ *Aa = (Mat_SeqAIJ*)mat->A->data,*Ba = (Mat_SeqAIJ*)mat->B->data;
1881:     PetscInt   max = 1,tmp;
1882:     for (i=0; i<matin->rmap->n; i++) {
1883:       tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i];
1884:       if (max < tmp) max = tmp;
1885:     }
1886:     PetscMalloc2(max,&mat->rowvalues,max,&mat->rowindices);
1887:   }

1889:   if (row < rstart || row >= rend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Only local rows");
1890:   lrow = row - rstart;

1892:   pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB;
1893:   if (!v)   {pvA = 0; pvB = 0;}
1894:   if (!idx) {pcA = 0; if (!v) pcB = 0;}
1895:   (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);
1896:   (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);
1897:   nztot = nzA + nzB;

1899:   cmap = mat->garray;
1900:   if (v  || idx) {
1901:     if (nztot) {
1902:       /* Sort by increasing column numbers, assuming A and B already sorted */
1903:       PetscInt imark = -1;
1904:       if (v) {
1905:         *v = v_p = mat->rowvalues;
1906:         for (i=0; i<nzB; i++) {
1907:           if (cmap[cworkB[i]] < cstart) v_p[i] = vworkB[i];
1908:           else break;
1909:         }
1910:         imark = i;
1911:         for (i=0; i<nzA; i++)     v_p[imark+i] = vworkA[i];
1912:         for (i=imark; i<nzB; i++) v_p[nzA+i]   = vworkB[i];
1913:       }
1914:       if (idx) {
1915:         *idx = idx_p = mat->rowindices;
1916:         if (imark > -1) {
1917:           for (i=0; i<imark; i++) {
1918:             idx_p[i] = cmap[cworkB[i]];
1919:           }
1920:         } else {
1921:           for (i=0; i<nzB; i++) {
1922:             if (cmap[cworkB[i]] < cstart) idx_p[i] = cmap[cworkB[i]];
1923:             else break;
1924:           }
1925:           imark = i;
1926:         }
1927:         for (i=0; i<nzA; i++)     idx_p[imark+i] = cstart + cworkA[i];
1928:         for (i=imark; i<nzB; i++) idx_p[nzA+i]   = cmap[cworkB[i]];
1929:       }
1930:     } else {
1931:       if (idx) *idx = 0;
1932:       if (v)   *v   = 0;
1933:     }
1934:   }
1935:   *nz  = nztot;
1936:   (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);
1937:   (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);
1938:   return(0);
1939: }

1941: PetscErrorCode MatRestoreRow_MPIAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
1942: {
1943:   Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;

1946:   if (!aij->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"MatGetRow() must be called first");
1947:   aij->getrowactive = PETSC_FALSE;
1948:   return(0);
1949: }

1951: PetscErrorCode MatNorm_MPIAIJ(Mat mat,NormType type,PetscReal *norm)
1952: {
1953:   Mat_MPIAIJ     *aij  = (Mat_MPIAIJ*)mat->data;
1954:   Mat_SeqAIJ     *amat = (Mat_SeqAIJ*)aij->A->data,*bmat = (Mat_SeqAIJ*)aij->B->data;
1956:   PetscInt       i,j,cstart = mat->cmap->rstart;
1957:   PetscReal      sum = 0.0;
1958:   MatScalar      *v;

1961:   if (aij->size == 1) {
1962:      MatNorm(aij->A,type,norm);
1963:   } else {
1964:     if (type == NORM_FROBENIUS) {
1965:       v = amat->a;
1966:       for (i=0; i<amat->nz; i++) {
1967:         sum += PetscRealPart(PetscConj(*v)*(*v)); v++;
1968:       }
1969:       v = bmat->a;
1970:       for (i=0; i<bmat->nz; i++) {
1971:         sum += PetscRealPart(PetscConj(*v)*(*v)); v++;
1972:       }
1973:       MPIU_Allreduce(&sum,norm,1,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));
1974:       *norm = PetscSqrtReal(*norm);
1975:       PetscLogFlops(2*amat->nz+2*bmat->nz);
1976:     } else if (type == NORM_1) { /* max column norm */
1977:       PetscReal *tmp,*tmp2;
1978:       PetscInt  *jj,*garray = aij->garray;
1979:       PetscCalloc1(mat->cmap->N+1,&tmp);
1980:       PetscMalloc1(mat->cmap->N+1,&tmp2);
1981:       *norm = 0.0;
1982:       v     = amat->a; jj = amat->j;
1983:       for (j=0; j<amat->nz; j++) {
1984:         tmp[cstart + *jj++] += PetscAbsScalar(*v);  v++;
1985:       }
1986:       v = bmat->a; jj = bmat->j;
1987:       for (j=0; j<bmat->nz; j++) {
1988:         tmp[garray[*jj++]] += PetscAbsScalar(*v); v++;
1989:       }
1990:       MPIU_Allreduce(tmp,tmp2,mat->cmap->N,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));
1991:       for (j=0; j<mat->cmap->N; j++) {
1992:         if (tmp2[j] > *norm) *norm = tmp2[j];
1993:       }
1994:       PetscFree(tmp);
1995:       PetscFree(tmp2);
1996:       PetscLogFlops(PetscMax(amat->nz+bmat->nz-1,0));
1997:     } else if (type == NORM_INFINITY) { /* max row norm */
1998:       PetscReal ntemp = 0.0;
1999:       for (j=0; j<aij->A->rmap->n; j++) {
2000:         v   = amat->a + amat->i[j];
2001:         sum = 0.0;
2002:         for (i=0; i<amat->i[j+1]-amat->i[j]; i++) {
2003:           sum += PetscAbsScalar(*v); v++;
2004:         }
2005:         v = bmat->a + bmat->i[j];
2006:         for (i=0; i<bmat->i[j+1]-bmat->i[j]; i++) {
2007:           sum += PetscAbsScalar(*v); v++;
2008:         }
2009:         if (sum > ntemp) ntemp = sum;
2010:       }
2011:       MPIU_Allreduce(&ntemp,norm,1,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)mat));
2012:       PetscLogFlops(PetscMax(amat->nz+bmat->nz-1,0));
2013:     } else SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_SUP,"No support for two norm");
2014:   }
2015:   return(0);
2016: }

2018: PetscErrorCode MatTranspose_MPIAIJ(Mat A,MatReuse reuse,Mat *matout)
2019: {
2020:   Mat_MPIAIJ     *a    =(Mat_MPIAIJ*)A->data,*b;
2021:   Mat_SeqAIJ     *Aloc =(Mat_SeqAIJ*)a->A->data,*Bloc=(Mat_SeqAIJ*)a->B->data,*sub_B_diag;
2022:   PetscInt       M     = A->rmap->N,N=A->cmap->N,ma,na,mb,nb,*ai,*aj,*bi,*bj,row,*cols,*cols_tmp,*B_diag_ilen,*B_diag_i,i,ncol,A_diag_ncol;
2024:   Mat            B,A_diag,*B_diag;
2025:   MatScalar      *array;

2028:   ma = A->rmap->n; na = A->cmap->n; mb = a->B->rmap->n; nb = a->B->cmap->n;
2029:   ai = Aloc->i; aj = Aloc->j;
2030:   bi = Bloc->i; bj = Bloc->j;
2031:   if (reuse == MAT_INITIAL_MATRIX || *matout == A) {
2032:     PetscInt             *d_nnz,*g_nnz,*o_nnz;
2033:     PetscSFNode          *oloc;
2034:     PETSC_UNUSED PetscSF sf;

2036:     PetscMalloc4(na,&d_nnz,na,&o_nnz,nb,&g_nnz,nb,&oloc);
2037:     /* compute d_nnz for preallocation */
2038:     PetscMemzero(d_nnz,na*sizeof(PetscInt));
2039:     for (i=0; i<ai[ma]; i++) {
2040:       d_nnz[aj[i]]++;
2041:     }
2042:     /* compute local off-diagonal contributions */
2043:     PetscMemzero(g_nnz,nb*sizeof(PetscInt));
2044:     for (i=0; i<bi[ma]; i++) g_nnz[bj[i]]++;
2045:     /* map those to global */
2046:     PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);
2047:     PetscSFSetGraphLayout(sf,A->cmap,nb,NULL,PETSC_USE_POINTER,a->garray);
2048:     PetscSFSetFromOptions(sf);
2049:     PetscMemzero(o_nnz,na*sizeof(PetscInt));
2050:     PetscSFReduceBegin(sf,MPIU_INT,g_nnz,o_nnz,MPIU_SUM);
2051:     PetscSFReduceEnd(sf,MPIU_INT,g_nnz,o_nnz,MPIU_SUM);
2052:     PetscSFDestroy(&sf);

2054:     MatCreate(PetscObjectComm((PetscObject)A),&B);
2055:     MatSetSizes(B,A->cmap->n,A->rmap->n,N,M);
2056:     MatSetBlockSizes(B,PetscAbs(A->cmap->bs),PetscAbs(A->rmap->bs));
2057:     MatSetType(B,((PetscObject)A)->type_name);
2058:     MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);
2059:     PetscFree4(d_nnz,o_nnz,g_nnz,oloc);
2060:   } else {
2061:     B    = *matout;
2062:     MatSetOption(B,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_TRUE);
2063:   }

2065:   b           = (Mat_MPIAIJ*)B->data;
2066:   A_diag      = a->A;
2067:   B_diag      = &b->A;
2068:   sub_B_diag  = (Mat_SeqAIJ*)(*B_diag)->data;
2069:   A_diag_ncol = A_diag->cmap->N;
2070:   B_diag_ilen = sub_B_diag->ilen;
2071:   B_diag_i    = sub_B_diag->i;

2073:   /* Set ilen for diagonal of B */
2074:   for (i=0; i<A_diag_ncol; i++) {
2075:     B_diag_ilen[i] = B_diag_i[i+1] - B_diag_i[i];
2076:   }

2078:   /* Transpose the diagonal part of the matrix. In contrast to the offdiagonal part, this can be done
2079:   very quickly (=without using MatSetValues), because all writes are local. */
2080:   MatTranspose(A_diag,MAT_REUSE_MATRIX,B_diag);

2082:   /* copy over the B part */
2083:   PetscCalloc1(bi[mb],&cols);
2084:   array = Bloc->a;
2085:   row   = A->rmap->rstart;
2086:   for (i=0; i<bi[mb]; i++) cols[i] = a->garray[bj[i]];
2087:   cols_tmp = cols;
2088:   for (i=0; i<mb; i++) {
2089:     ncol = bi[i+1]-bi[i];
2090:     MatSetValues(B,ncol,cols_tmp,1,&row,array,INSERT_VALUES);
2091:     row++;
2092:     array += ncol; cols_tmp += ncol;
2093:   }
2094:   PetscFree(cols);

2096:   MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
2097:   MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);
2098:   if (reuse == MAT_INITIAL_MATRIX || reuse == MAT_REUSE_MATRIX) {
2099:     *matout = B;
2100:   } else {
2101:     MatHeaderMerge(A,&B);
2102:   }
2103:   return(0);
2104: }

2106: PetscErrorCode MatDiagonalScale_MPIAIJ(Mat mat,Vec ll,Vec rr)
2107: {
2108:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)mat->data;
2109:   Mat            a    = aij->A,b = aij->B;
2111:   PetscInt       s1,s2,s3;

2114:   MatGetLocalSize(mat,&s2,&s3);
2115:   if (rr) {
2116:     VecGetLocalSize(rr,&s1);
2117:     if (s1!=s3) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"right vector non-conforming local size");
2118:     /* Overlap communication with computation. */
2119:     VecScatterBegin(aij->Mvctx,rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD);
2120:   }
2121:   if (ll) {
2122:     VecGetLocalSize(ll,&s1);
2123:     if (s1!=s2) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"left vector non-conforming local size");
2124:     (*b->ops->diagonalscale)(b,ll,0);
2125:   }
2126:   /* scale  the diagonal block */
2127:   (*a->ops->diagonalscale)(a,ll,rr);

2129:   if (rr) {
2130:     /* Do a scatter end and then right scale the off-diagonal block */
2131:     VecScatterEnd(aij->Mvctx,rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD);
2132:     (*b->ops->diagonalscale)(b,0,aij->lvec);
2133:   }
2134:   return(0);
2135: }

2137: PetscErrorCode MatSetUnfactored_MPIAIJ(Mat A)
2138: {
2139:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;

2143:   MatSetUnfactored(a->A);
2144:   return(0);
2145: }

2147: PetscErrorCode MatEqual_MPIAIJ(Mat A,Mat B,PetscBool  *flag)
2148: {
2149:   Mat_MPIAIJ     *matB = (Mat_MPIAIJ*)B->data,*matA = (Mat_MPIAIJ*)A->data;
2150:   Mat            a,b,c,d;
2151:   PetscBool      flg;

2155:   a = matA->A; b = matA->B;
2156:   c = matB->A; d = matB->B;

2158:   MatEqual(a,c,&flg);
2159:   if (flg) {
2160:     MatEqual(b,d,&flg);
2161:   }
2162:   MPIU_Allreduce(&flg,flag,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)A));
2163:   return(0);
2164: }

2166: PetscErrorCode MatCopy_MPIAIJ(Mat A,Mat B,MatStructure str)
2167: {
2169:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;
2170:   Mat_MPIAIJ     *b = (Mat_MPIAIJ*)B->data;

2173:   /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */
2174:   if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) {
2175:     /* because of the column compression in the off-processor part of the matrix a->B,
2176:        the number of columns in a->B and b->B may be different, hence we cannot call
2177:        the MatCopy() directly on the two parts. If need be, we can provide a more
2178:        efficient copy than the MatCopy_Basic() by first uncompressing the a->B matrices
2179:        then copying the submatrices */
2180:     MatCopy_Basic(A,B,str);
2181:   } else {
2182:     MatCopy(a->A,b->A,str);
2183:     MatCopy(a->B,b->B,str);
2184:   }
2185:   PetscObjectStateIncrease((PetscObject)B);
2186:   return(0);
2187: }

2189: PetscErrorCode MatSetUp_MPIAIJ(Mat A)
2190: {

2194:    MatMPIAIJSetPreallocation(A,PETSC_DEFAULT,0,PETSC_DEFAULT,0);
2195:   return(0);
2196: }

2198: /*
2199:    Computes the number of nonzeros per row needed for preallocation when X and Y
2200:    have different nonzero structure.
2201: */
2202: PetscErrorCode MatAXPYGetPreallocation_MPIX_private(PetscInt m,const PetscInt *xi,const PetscInt *xj,const PetscInt *xltog,const PetscInt *yi,const PetscInt *yj,const PetscInt *yltog,PetscInt *nnz)
2203: {
2204:   PetscInt       i,j,k,nzx,nzy;

2207:   /* Set the number of nonzeros in the new matrix */
2208:   for (i=0; i<m; i++) {
2209:     const PetscInt *xjj = xj+xi[i],*yjj = yj+yi[i];
2210:     nzx = xi[i+1] - xi[i];
2211:     nzy = yi[i+1] - yi[i];
2212:     nnz[i] = 0;
2213:     for (j=0,k=0; j<nzx; j++) {                   /* Point in X */
2214:       for (; k<nzy && yltog[yjj[k]]<xltog[xjj[j]]; k++) nnz[i]++; /* Catch up to X */
2215:       if (k<nzy && yltog[yjj[k]]==xltog[xjj[j]]) k++;             /* Skip duplicate */
2216:       nnz[i]++;
2217:     }
2218:     for (; k<nzy; k++) nnz[i]++;
2219:   }
2220:   return(0);
2221: }

2223: /* This is the same as MatAXPYGetPreallocation_SeqAIJ, except that the local-to-global map is provided */
2224: static PetscErrorCode MatAXPYGetPreallocation_MPIAIJ(Mat Y,const PetscInt *yltog,Mat X,const PetscInt *xltog,PetscInt *nnz)
2225: {
2227:   PetscInt       m = Y->rmap->N;
2228:   Mat_SeqAIJ     *x = (Mat_SeqAIJ*)X->data;
2229:   Mat_SeqAIJ     *y = (Mat_SeqAIJ*)Y->data;

2232:   MatAXPYGetPreallocation_MPIX_private(m,x->i,x->j,xltog,y->i,y->j,yltog,nnz);
2233:   return(0);
2234: }

2236: PetscErrorCode MatAXPY_MPIAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str)
2237: {
2239:   Mat_MPIAIJ     *xx = (Mat_MPIAIJ*)X->data,*yy = (Mat_MPIAIJ*)Y->data;
2240:   PetscBLASInt   bnz,one=1;
2241:   Mat_SeqAIJ     *x,*y;

2244:   if (str == SAME_NONZERO_PATTERN) {
2245:     PetscScalar alpha = a;
2246:     x    = (Mat_SeqAIJ*)xx->A->data;
2247:     PetscBLASIntCast(x->nz,&bnz);
2248:     y    = (Mat_SeqAIJ*)yy->A->data;
2249:     PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one));
2250:     x    = (Mat_SeqAIJ*)xx->B->data;
2251:     y    = (Mat_SeqAIJ*)yy->B->data;
2252:     PetscBLASIntCast(x->nz,&bnz);
2253:     PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one));
2254:     PetscObjectStateIncrease((PetscObject)Y);
2255:   } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */
2256:     MatAXPY_Basic(Y,a,X,str);
2257:   } else {
2258:     Mat      B;
2259:     PetscInt *nnz_d,*nnz_o;
2260:     PetscMalloc1(yy->A->rmap->N,&nnz_d);
2261:     PetscMalloc1(yy->B->rmap->N,&nnz_o);
2262:     MatCreate(PetscObjectComm((PetscObject)Y),&B);
2263:     PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);
2264:     MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);
2265:     MatSetBlockSizesFromMats(B,Y,Y);
2266:     MatSetType(B,MATMPIAIJ);
2267:     MatAXPYGetPreallocation_SeqAIJ(yy->A,xx->A,nnz_d);
2268:     MatAXPYGetPreallocation_MPIAIJ(yy->B,yy->garray,xx->B,xx->garray,nnz_o);
2269:     MatMPIAIJSetPreallocation(B,0,nnz_d,0,nnz_o);
2270:     MatAXPY_BasicWithPreallocation(B,Y,a,X,str);
2271:     MatHeaderReplace(Y,&B);
2272:     PetscFree(nnz_d);
2273:     PetscFree(nnz_o);
2274:   }
2275:   return(0);
2276: }

2278: extern PetscErrorCode  MatConjugate_SeqAIJ(Mat);

2280: PetscErrorCode  MatConjugate_MPIAIJ(Mat mat)
2281: {
2282: #if defined(PETSC_USE_COMPLEX)
2284:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)mat->data;

2287:   MatConjugate_SeqAIJ(aij->A);
2288:   MatConjugate_SeqAIJ(aij->B);
2289: #else
2291: #endif
2292:   return(0);
2293: }

2295: PetscErrorCode MatRealPart_MPIAIJ(Mat A)
2296: {
2297:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;

2301:   MatRealPart(a->A);
2302:   MatRealPart(a->B);
2303:   return(0);
2304: }

2306: PetscErrorCode MatImaginaryPart_MPIAIJ(Mat A)
2307: {
2308:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;

2312:   MatImaginaryPart(a->A);
2313:   MatImaginaryPart(a->B);
2314:   return(0);
2315: }

2317: PetscErrorCode MatGetRowMaxAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[])
2318: {
2319:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;
2321:   PetscInt       i,*idxb = 0;
2322:   PetscScalar    *va,*vb;
2323:   Vec            vtmp;

2326:   MatGetRowMaxAbs(a->A,v,idx);
2327:   VecGetArray(v,&va);
2328:   if (idx) {
2329:     for (i=0; i<A->rmap->n; i++) {
2330:       if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart;
2331:     }
2332:   }

2334:   VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);
2335:   if (idx) {
2336:     PetscMalloc1(A->rmap->n,&idxb);
2337:   }
2338:   MatGetRowMaxAbs(a->B,vtmp,idxb);
2339:   VecGetArray(vtmp,&vb);

2341:   for (i=0; i<A->rmap->n; i++) {
2342:     if (PetscAbsScalar(va[i]) < PetscAbsScalar(vb[i])) {
2343:       va[i] = vb[i];
2344:       if (idx) idx[i] = a->garray[idxb[i]];
2345:     }
2346:   }

2348:   VecRestoreArray(v,&va);
2349:   VecRestoreArray(vtmp,&vb);
2350:   PetscFree(idxb);
2351:   VecDestroy(&vtmp);
2352:   return(0);
2353: }

2355: PetscErrorCode MatGetRowMinAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[])
2356: {
2357:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;
2359:   PetscInt       i,*idxb = 0;
2360:   PetscScalar    *va,*vb;
2361:   Vec            vtmp;

2364:   MatGetRowMinAbs(a->A,v,idx);
2365:   VecGetArray(v,&va);
2366:   if (idx) {
2367:     for (i=0; i<A->cmap->n; i++) {
2368:       if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart;
2369:     }
2370:   }

2372:   VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);
2373:   if (idx) {
2374:     PetscMalloc1(A->rmap->n,&idxb);
2375:   }
2376:   MatGetRowMinAbs(a->B,vtmp,idxb);
2377:   VecGetArray(vtmp,&vb);

2379:   for (i=0; i<A->rmap->n; i++) {
2380:     if (PetscAbsScalar(va[i]) > PetscAbsScalar(vb[i])) {
2381:       va[i] = vb[i];
2382:       if (idx) idx[i] = a->garray[idxb[i]];
2383:     }
2384:   }

2386:   VecRestoreArray(v,&va);
2387:   VecRestoreArray(vtmp,&vb);
2388:   PetscFree(idxb);
2389:   VecDestroy(&vtmp);
2390:   return(0);
2391: }

2393: PetscErrorCode MatGetRowMin_MPIAIJ(Mat A, Vec v, PetscInt idx[])
2394: {
2395:   Mat_MPIAIJ     *mat   = (Mat_MPIAIJ*) A->data;
2396:   PetscInt       n      = A->rmap->n;
2397:   PetscInt       cstart = A->cmap->rstart;
2398:   PetscInt       *cmap  = mat->garray;
2399:   PetscInt       *diagIdx, *offdiagIdx;
2400:   Vec            diagV, offdiagV;
2401:   PetscScalar    *a, *diagA, *offdiagA;
2402:   PetscInt       r;

2406:   PetscMalloc2(n,&diagIdx,n,&offdiagIdx);
2407:   VecCreateSeq(PetscObjectComm((PetscObject)A), n, &diagV);
2408:   VecCreateSeq(PetscObjectComm((PetscObject)A), n, &offdiagV);
2409:   MatGetRowMin(mat->A, diagV,    diagIdx);
2410:   MatGetRowMin(mat->B, offdiagV, offdiagIdx);
2411:   VecGetArray(v,        &a);
2412:   VecGetArray(diagV,    &diagA);
2413:   VecGetArray(offdiagV, &offdiagA);
2414:   for (r = 0; r < n; ++r) {
2415:     if (PetscAbsScalar(diagA[r]) <= PetscAbsScalar(offdiagA[r])) {
2416:       a[r]   = diagA[r];
2417:       idx[r] = cstart + diagIdx[r];
2418:     } else {
2419:       a[r]   = offdiagA[r];
2420:       idx[r] = cmap[offdiagIdx[r]];
2421:     }
2422:   }
2423:   VecRestoreArray(v,        &a);
2424:   VecRestoreArray(diagV,    &diagA);
2425:   VecRestoreArray(offdiagV, &offdiagA);
2426:   VecDestroy(&diagV);
2427:   VecDestroy(&offdiagV);
2428:   PetscFree2(diagIdx, offdiagIdx);
2429:   return(0);
2430: }

2432: PetscErrorCode MatGetRowMax_MPIAIJ(Mat A, Vec v, PetscInt idx[])
2433: {
2434:   Mat_MPIAIJ     *mat   = (Mat_MPIAIJ*) A->data;
2435:   PetscInt       n      = A->rmap->n;
2436:   PetscInt       cstart = A->cmap->rstart;
2437:   PetscInt       *cmap  = mat->garray;
2438:   PetscInt       *diagIdx, *offdiagIdx;
2439:   Vec            diagV, offdiagV;
2440:   PetscScalar    *a, *diagA, *offdiagA;
2441:   PetscInt       r;

2445:   PetscMalloc2(n,&diagIdx,n,&offdiagIdx);
2446:   VecCreateSeq(PETSC_COMM_SELF, n, &diagV);
2447:   VecCreateSeq(PETSC_COMM_SELF, n, &offdiagV);
2448:   MatGetRowMax(mat->A, diagV,    diagIdx);
2449:   MatGetRowMax(mat->B, offdiagV, offdiagIdx);
2450:   VecGetArray(v,        &a);
2451:   VecGetArray(diagV,    &diagA);
2452:   VecGetArray(offdiagV, &offdiagA);
2453:   for (r = 0; r < n; ++r) {
2454:     if (PetscAbsScalar(diagA[r]) >= PetscAbsScalar(offdiagA[r])) {
2455:       a[r]   = diagA[r];
2456:       idx[r] = cstart + diagIdx[r];
2457:     } else {
2458:       a[r]   = offdiagA[r];
2459:       idx[r] = cmap[offdiagIdx[r]];
2460:     }
2461:   }
2462:   VecRestoreArray(v,        &a);
2463:   VecRestoreArray(diagV,    &diagA);
2464:   VecRestoreArray(offdiagV, &offdiagA);
2465:   VecDestroy(&diagV);
2466:   VecDestroy(&offdiagV);
2467:   PetscFree2(diagIdx, offdiagIdx);
2468:   return(0);
2469: }

2471: PetscErrorCode MatGetSeqNonzeroStructure_MPIAIJ(Mat mat,Mat *newmat)
2472: {
2474:   Mat            *dummy;

2477:   MatCreateSubMatrix_MPIAIJ_All(mat,MAT_DO_NOT_GET_VALUES,MAT_INITIAL_MATRIX,&dummy);
2478:   *newmat = *dummy;
2479:   PetscFree(dummy);
2480:   return(0);
2481: }

2483: PetscErrorCode  MatInvertBlockDiagonal_MPIAIJ(Mat A,const PetscScalar **values)
2484: {
2485:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*) A->data;

2489:   MatInvertBlockDiagonal(a->A,values);
2490:   A->factorerrortype = a->A->factorerrortype;
2491:   return(0);
2492: }

2494: static PetscErrorCode  MatSetRandom_MPIAIJ(Mat x,PetscRandom rctx)
2495: {
2497:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)x->data;

2500:   MatSetRandom(aij->A,rctx);
2501:   MatSetRandom(aij->B,rctx);
2502:   MatAssemblyBegin(x,MAT_FINAL_ASSEMBLY);
2503:   MatAssemblyEnd(x,MAT_FINAL_ASSEMBLY);
2504:   return(0);
2505: }

2507: PetscErrorCode MatMPIAIJSetUseScalableIncreaseOverlap_MPIAIJ(Mat A,PetscBool sc)
2508: {
2510:   if (sc) A->ops->increaseoverlap = MatIncreaseOverlap_MPIAIJ_Scalable;
2511:   else A->ops->increaseoverlap    = MatIncreaseOverlap_MPIAIJ;
2512:   return(0);
2513: }

2515: /*@
2516:    MatMPIAIJSetUseScalableIncreaseOverlap - Determine if the matrix uses a scalable algorithm to compute the overlap

2518:    Collective on Mat

2520:    Input Parameters:
2521: +    A - the matrix
2522: -    sc - PETSC_TRUE indicates use the scalable algorithm (default is not to use the scalable algorithm)

2524:  Level: advanced

2526: @*/
2527: PetscErrorCode MatMPIAIJSetUseScalableIncreaseOverlap(Mat A,PetscBool sc)
2528: {
2529:   PetscErrorCode       ierr;

2532:   PetscTryMethod(A,"MatMPIAIJSetUseScalableIncreaseOverlap_C",(Mat,PetscBool),(A,sc));
2533:   return(0);
2534: }

2536: PetscErrorCode MatSetFromOptions_MPIAIJ(PetscOptionItems *PetscOptionsObject,Mat A)
2537: {
2538:   PetscErrorCode       ierr;
2539:   PetscBool            sc = PETSC_FALSE,flg;

2542:   PetscOptionsHead(PetscOptionsObject,"MPIAIJ options");
2543:   if (A->ops->increaseoverlap == MatIncreaseOverlap_MPIAIJ_Scalable) sc = PETSC_TRUE;
2544:   PetscOptionsBool("-mat_increase_overlap_scalable","Use a scalable algorithm to compute the overlap","MatIncreaseOverlap",sc,&sc,&flg);
2545:   if (flg) {
2546:     MatMPIAIJSetUseScalableIncreaseOverlap(A,sc);
2547:   }
2548:   PetscOptionsTail();
2549:   return(0);
2550: }

2552: PetscErrorCode MatShift_MPIAIJ(Mat Y,PetscScalar a)
2553: {
2555:   Mat_MPIAIJ     *maij = (Mat_MPIAIJ*)Y->data;
2556:   Mat_SeqAIJ     *aij = (Mat_SeqAIJ*)maij->A->data;

2559:   if (!Y->preallocated) {
2560:     MatMPIAIJSetPreallocation(Y,1,NULL,0,NULL);
2561:   } else if (!aij->nz) {
2562:     PetscInt nonew = aij->nonew;
2563:     MatSeqAIJSetPreallocation(maij->A,1,NULL);
2564:     aij->nonew = nonew;
2565:   }
2566:   MatShift_Basic(Y,a);
2567:   return(0);
2568: }

2570: PetscErrorCode MatMissingDiagonal_MPIAIJ(Mat A,PetscBool  *missing,PetscInt *d)
2571: {
2572:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;

2576:   if (A->rmap->n != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only works for square matrices");
2577:   MatMissingDiagonal(a->A,missing,d);
2578:   if (d) {
2579:     PetscInt rstart;
2580:     MatGetOwnershipRange(A,&rstart,NULL);
2581:     *d += rstart;

2583:   }
2584:   return(0);
2585: }

2587: PetscErrorCode MatInvertVariableBlockDiagonal_MPIAIJ(Mat A,PetscInt nblocks,const PetscInt *bsizes,PetscScalar *diag)
2588: {
2589:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;

2593:   MatInvertVariableBlockDiagonal(a->A,nblocks,bsizes,diag);
2594:   return(0);
2595: }

2597: /* -------------------------------------------------------------------*/
2598: static struct _MatOps MatOps_Values = {MatSetValues_MPIAIJ,
2599:                                        MatGetRow_MPIAIJ,
2600:                                        MatRestoreRow_MPIAIJ,
2601:                                        MatMult_MPIAIJ,
2602:                                 /* 4*/ MatMultAdd_MPIAIJ,
2603:                                        MatMultTranspose_MPIAIJ,
2604:                                        MatMultTransposeAdd_MPIAIJ,
2605:                                        0,
2606:                                        0,
2607:                                        0,
2608:                                 /*10*/ 0,
2609:                                        0,
2610:                                        0,
2611:                                        MatSOR_MPIAIJ,
2612:                                        MatTranspose_MPIAIJ,
2613:                                 /*15*/ MatGetInfo_MPIAIJ,
2614:                                        MatEqual_MPIAIJ,
2615:                                        MatGetDiagonal_MPIAIJ,
2616:                                        MatDiagonalScale_MPIAIJ,
2617:                                        MatNorm_MPIAIJ,
2618:                                 /*20*/ MatAssemblyBegin_MPIAIJ,
2619:                                        MatAssemblyEnd_MPIAIJ,
2620:                                        MatSetOption_MPIAIJ,
2621:                                        MatZeroEntries_MPIAIJ,
2622:                                 /*24*/ MatZeroRows_MPIAIJ,
2623:                                        0,
2624:                                        0,
2625:                                        0,
2626:                                        0,
2627:                                 /*29*/ MatSetUp_MPIAIJ,
2628:                                        0,
2629:                                        0,
2630:                                        MatGetDiagonalBlock_MPIAIJ,
2631:                                        0,
2632:                                 /*34*/ MatDuplicate_MPIAIJ,
2633:                                        0,
2634:                                        0,
2635:                                        0,
2636:                                        0,
2637:                                 /*39*/ MatAXPY_MPIAIJ,
2638:                                        MatCreateSubMatrices_MPIAIJ,
2639:                                        MatIncreaseOverlap_MPIAIJ,
2640:                                        MatGetValues_MPIAIJ,
2641:                                        MatCopy_MPIAIJ,
2642:                                 /*44*/ MatGetRowMax_MPIAIJ,
2643:                                        MatScale_MPIAIJ,
2644:                                        MatShift_MPIAIJ,
2645:                                        MatDiagonalSet_MPIAIJ,
2646:                                        MatZeroRowsColumns_MPIAIJ,
2647:                                 /*49*/ MatSetRandom_MPIAIJ,
2648:                                        0,
2649:                                        0,
2650:                                        0,
2651:                                        0,
2652:                                 /*54*/ MatFDColoringCreate_MPIXAIJ,
2653:                                        0,
2654:                                        MatSetUnfactored_MPIAIJ,
2655:                                        MatPermute_MPIAIJ,
2656:                                        0,
2657:                                 /*59*/ MatCreateSubMatrix_MPIAIJ,
2658:                                        MatDestroy_MPIAIJ,
2659:                                        MatView_MPIAIJ,
2660:                                        0,
2661:                                        MatMatMatMult_MPIAIJ_MPIAIJ_MPIAIJ,
2662:                                 /*64*/ MatMatMatMultSymbolic_MPIAIJ_MPIAIJ_MPIAIJ,
2663:                                        MatMatMatMultNumeric_MPIAIJ_MPIAIJ_MPIAIJ,
2664:                                        0,
2665:                                        0,
2666:                                        0,
2667:                                 /*69*/ MatGetRowMaxAbs_MPIAIJ,
2668:                                        MatGetRowMinAbs_MPIAIJ,
2669:                                        0,
2670:                                        0,
2671:                                        0,
2672:                                        0,
2673:                                 /*75*/ MatFDColoringApply_AIJ,
2674:                                        MatSetFromOptions_MPIAIJ,
2675:                                        0,
2676:                                        0,
2677:                                        MatFindZeroDiagonals_MPIAIJ,
2678:                                 /*80*/ 0,
2679:                                        0,
2680:                                        0,
2681:                                 /*83*/ MatLoad_MPIAIJ,
2682:                                        MatIsSymmetric_MPIAIJ,
2683:                                        0,
2684:                                        0,
2685:                                        0,
2686:                                        0,
2687:                                 /*89*/ MatMatMult_MPIAIJ_MPIAIJ,
2688:                                        MatMatMultSymbolic_MPIAIJ_MPIAIJ,
2689:                                        MatMatMultNumeric_MPIAIJ_MPIAIJ,
2690:                                        MatPtAP_MPIAIJ_MPIAIJ,
2691:                                        MatPtAPSymbolic_MPIAIJ_MPIAIJ,
2692:                                 /*94*/ MatPtAPNumeric_MPIAIJ_MPIAIJ,
2693:                                        0,
2694:                                        0,
2695:                                        0,
2696:                                        0,
2697:                                 /*99*/ 0,
2698:                                        0,
2699:                                        0,
2700:                                        MatConjugate_MPIAIJ,
2701:                                        0,
2702:                                 /*104*/MatSetValuesRow_MPIAIJ,
2703:                                        MatRealPart_MPIAIJ,
2704:                                        MatImaginaryPart_MPIAIJ,
2705:                                        0,
2706:                                        0,
2707:                                 /*109*/0,
2708:                                        0,
2709:                                        MatGetRowMin_MPIAIJ,
2710:                                        0,
2711:                                        MatMissingDiagonal_MPIAIJ,
2712:                                 /*114*/MatGetSeqNonzeroStructure_MPIAIJ,
2713:                                        0,
2714:                                        MatGetGhosts_MPIAIJ,
2715:                                        0,
2716:                                        0,
2717:                                 /*119*/0,
2718:                                        0,
2719:                                        0,
2720:                                        0,
2721:                                        MatGetMultiProcBlock_MPIAIJ,
2722:                                 /*124*/MatFindNonzeroRows_MPIAIJ,
2723:                                        MatGetColumnNorms_MPIAIJ,
2724:                                        MatInvertBlockDiagonal_MPIAIJ,
2725:                                        MatInvertVariableBlockDiagonal_MPIAIJ,
2726:                                        MatCreateSubMatricesMPI_MPIAIJ,
2727:                                 /*129*/0,
2728:                                        MatTransposeMatMult_MPIAIJ_MPIAIJ,
2729:                                        MatTransposeMatMultSymbolic_MPIAIJ_MPIAIJ,
2730:                                        MatTransposeMatMultNumeric_MPIAIJ_MPIAIJ,
2731:                                        0,
2732:                                 /*134*/0,
2733:                                        0,
2734:                                        MatRARt_MPIAIJ_MPIAIJ,
2735:                                        0,
2736:                                        0,
2737:                                 /*139*/MatSetBlockSizes_MPIAIJ,
2738:                                        0,
2739:                                        0,
2740:                                        MatFDColoringSetUp_MPIXAIJ,
2741:                                        MatFindOffBlockDiagonalEntries_MPIAIJ,
2742:                                 /*144*/MatCreateMPIMatConcatenateSeqMat_MPIAIJ
2743: };

2745: /* ----------------------------------------------------------------------------------------*/

2747: PetscErrorCode  MatStoreValues_MPIAIJ(Mat mat)
2748: {
2749:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)mat->data;

2753:   MatStoreValues(aij->A);
2754:   MatStoreValues(aij->B);
2755:   return(0);
2756: }

2758: PetscErrorCode  MatRetrieveValues_MPIAIJ(Mat mat)
2759: {
2760:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)mat->data;

2764:   MatRetrieveValues(aij->A);
2765:   MatRetrieveValues(aij->B);
2766:   return(0);
2767: }

2769: PetscErrorCode  MatMPIAIJSetPreallocation_MPIAIJ(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[])
2770: {
2771:   Mat_MPIAIJ     *b;

2775:   PetscLayoutSetUp(B->rmap);
2776:   PetscLayoutSetUp(B->cmap);
2777:   b = (Mat_MPIAIJ*)B->data;

2779: #if defined(PETSC_USE_CTABLE)
2780:   PetscTableDestroy(&b->colmap);
2781: #else
2782:   PetscFree(b->colmap);
2783: #endif
2784:   PetscFree(b->garray);
2785:   VecDestroy(&b->lvec);
2786:   VecScatterDestroy(&b->Mvctx);

2788:   /* Because the B will have been resized we simply destroy it and create a new one each time */
2789:   MatDestroy(&b->B);
2790:   MatCreate(PETSC_COMM_SELF,&b->B);
2791:   MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);
2792:   MatSetBlockSizesFromMats(b->B,B,B);
2793:   MatSetType(b->B,MATSEQAIJ);
2794:   PetscLogObjectParent((PetscObject)B,(PetscObject)b->B);

2796:   if (!B->preallocated) {
2797:     MatCreate(PETSC_COMM_SELF,&b->A);
2798:     MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);
2799:     MatSetBlockSizesFromMats(b->A,B,B);
2800:     MatSetType(b->A,MATSEQAIJ);
2801:     PetscLogObjectParent((PetscObject)B,(PetscObject)b->A);
2802:   }

2804:   MatSeqAIJSetPreallocation(b->A,d_nz,d_nnz);
2805:   MatSeqAIJSetPreallocation(b->B,o_nz,o_nnz);
2806:   B->preallocated  = PETSC_TRUE;
2807:   B->was_assembled = PETSC_FALSE;
2808:   B->assembled     = PETSC_FALSE;;
2809:   return(0);
2810: }

2812: PetscErrorCode MatResetPreallocation_MPIAIJ(Mat B)
2813: {
2814:   Mat_MPIAIJ     *b;

2819:   PetscLayoutSetUp(B->rmap);
2820:   PetscLayoutSetUp(B->cmap);
2821:   b = (Mat_MPIAIJ*)B->data;

2823: #if defined(PETSC_USE_CTABLE)
2824:   PetscTableDestroy(&b->colmap);
2825: #else
2826:   PetscFree(b->colmap);
2827: #endif
2828:   PetscFree(b->garray);
2829:   VecDestroy(&b->lvec);
2830:   VecScatterDestroy(&b->Mvctx);

2832:   MatResetPreallocation(b->A);
2833:   MatResetPreallocation(b->B);
2834:   B->preallocated  = PETSC_TRUE;
2835:   B->was_assembled = PETSC_FALSE;
2836:   B->assembled = PETSC_FALSE;
2837:   return(0);
2838: }

2840: PetscErrorCode MatDuplicate_MPIAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat)
2841: {
2842:   Mat            mat;
2843:   Mat_MPIAIJ     *a,*oldmat = (Mat_MPIAIJ*)matin->data;

2847:   *newmat = 0;
2848:   MatCreate(PetscObjectComm((PetscObject)matin),&mat);
2849:   MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);
2850:   MatSetBlockSizesFromMats(mat,matin,matin);
2851:   MatSetType(mat,((PetscObject)matin)->type_name);
2852:   PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));
2853:   a       = (Mat_MPIAIJ*)mat->data;

2855:   mat->factortype   = matin->factortype;
2856:   mat->assembled    = PETSC_TRUE;
2857:   mat->insertmode   = NOT_SET_VALUES;
2858:   mat->preallocated = PETSC_TRUE;

2860:   a->size         = oldmat->size;
2861:   a->rank         = oldmat->rank;
2862:   a->donotstash   = oldmat->donotstash;
2863:   a->roworiented  = oldmat->roworiented;
2864:   a->rowindices   = 0;
2865:   a->rowvalues    = 0;
2866:   a->getrowactive = PETSC_FALSE;

2868:   PetscLayoutReference(matin->rmap,&mat->rmap);
2869:   PetscLayoutReference(matin->cmap,&mat->cmap);

2871:   if (oldmat->colmap) {
2872: #if defined(PETSC_USE_CTABLE)
2873:     PetscTableCreateCopy(oldmat->colmap,&a->colmap);
2874: #else
2875:     PetscMalloc1(mat->cmap->N,&a->colmap);
2876:     PetscLogObjectMemory((PetscObject)mat,(mat->cmap->N)*sizeof(PetscInt));
2877:     PetscMemcpy(a->colmap,oldmat->colmap,(mat->cmap->N)*sizeof(PetscInt));
2878: #endif
2879:   } else a->colmap = 0;
2880:   if (oldmat->garray) {
2881:     PetscInt len;
2882:     len  = oldmat->B->cmap->n;
2883:     PetscMalloc1(len+1,&a->garray);
2884:     PetscLogObjectMemory((PetscObject)mat,len*sizeof(PetscInt));
2885:     if (len) { PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt)); }
2886:   } else a->garray = 0;

2888:   VecDuplicate(oldmat->lvec,&a->lvec);
2889:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->lvec);
2890:   VecScatterCopy(oldmat->Mvctx,&a->Mvctx);
2891:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->Mvctx);

2893:   if (oldmat->Mvctx_mpi1) {
2894:     VecScatterCopy(oldmat->Mvctx_mpi1,&a->Mvctx_mpi1);
2895:     PetscLogObjectParent((PetscObject)mat,(PetscObject)a->Mvctx_mpi1);
2896:   }

2898:   MatDuplicate(oldmat->A,cpvalues,&a->A);
2899:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->A);
2900:   MatDuplicate(oldmat->B,cpvalues,&a->B);
2901:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->B);
2902:   PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);
2903:   *newmat = mat;
2904:   return(0);
2905: }

2907: PetscErrorCode MatLoad_MPIAIJ(Mat newMat, PetscViewer viewer)
2908: {
2909:   PetscScalar    *vals,*svals;
2910:   MPI_Comm       comm;
2912:   PetscMPIInt    rank,size,tag = ((PetscObject)viewer)->tag;
2913:   PetscInt       i,nz,j,rstart,rend,mmax,maxnz = 0;
2914:   PetscInt       header[4],*rowlengths = 0,M,N,m,*cols;
2915:   PetscInt       *ourlens = NULL,*procsnz = NULL,*offlens = NULL,jj,*mycols,*smycols;
2916:   PetscInt       cend,cstart,n,*rowners;
2917:   int            fd;
2918:   PetscInt       bs = newMat->rmap->bs;

2921:   /* force binary viewer to load .info file if it has not yet done so */
2922:   PetscViewerSetUp(viewer);
2923:   PetscObjectGetComm((PetscObject)viewer,&comm);
2924:   MPI_Comm_size(comm,&size);
2925:   MPI_Comm_rank(comm,&rank);
2926:   PetscViewerBinaryGetDescriptor(viewer,&fd);
2927:   if (!rank) {
2928:     PetscBinaryRead(fd,(char*)header,4,PETSC_INT);
2929:     if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object");
2930:     if (header[3] < 0) SETERRQ(PetscObjectComm((PetscObject)newMat),PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format on disk,cannot load as MATMPIAIJ");
2931:   }

2933:   PetscOptionsBegin(comm,NULL,"Options for loading MATMPIAIJ matrix","Mat");
2934:   PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);
2935:   PetscOptionsEnd();
2936:   if (bs < 0) bs = 1;

2938:   MPI_Bcast(header+1,3,MPIU_INT,0,comm);
2939:   M    = header[1]; N = header[2];

2941:   /* If global sizes are set, check if they are consistent with that given in the file */
2942:   if (newMat->rmap->N >= 0 && 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)",newMat->rmap->N,M);
2943:   if (newMat->cmap->N >=0 && 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)",newMat->cmap->N,N);

2945:   /* determine ownership of all (block) rows */
2946:   if (M%bs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED, "Inconsistent # of rows (%d) and block size (%d)",M,bs);
2947:   if (newMat->rmap->n < 0) m = bs*((M/bs)/size + (((M/bs) % size) > rank));    /* PETSC_DECIDE */
2948:   else m = newMat->rmap->n; /* Set by user */

2950:   PetscMalloc1(size+1,&rowners);
2951:   MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);

2953:   /* First process needs enough room for process with most rows */
2954:   if (!rank) {
2955:     mmax = rowners[1];
2956:     for (i=2; i<=size; i++) {
2957:       mmax = PetscMax(mmax, rowners[i]);
2958:     }
2959:   } else mmax = -1;             /* unused, but compilers complain */

2961:   rowners[0] = 0;
2962:   for (i=2; i<=size; i++) {
2963:     rowners[i] += rowners[i-1];
2964:   }
2965:   rstart = rowners[rank];
2966:   rend   = rowners[rank+1];

2968:   /* distribute row lengths to all processors */
2969:   PetscMalloc2(m,&ourlens,m,&offlens);
2970:   if (!rank) {
2971:     PetscBinaryRead(fd,ourlens,m,PETSC_INT);
2972:     PetscMalloc1(mmax,&rowlengths);
2973:     PetscCalloc1(size,&procsnz);
2974:     for (j=0; j<m; j++) {
2975:       procsnz[0] += ourlens[j];
2976:     }
2977:     for (i=1; i<size; i++) {
2978:       PetscBinaryRead(fd,rowlengths,rowners[i+1]-rowners[i],PETSC_INT);
2979:       /* calculate the number of nonzeros on each processor */
2980:       for (j=0; j<rowners[i+1]-rowners[i]; j++) {
2981:         procsnz[i] += rowlengths[j];
2982:       }
2983:       MPIULong_Send(rowlengths,rowners[i+1]-rowners[i],MPIU_INT,i,tag,comm);
2984:     }
2985:     PetscFree(rowlengths);
2986:   } else {
2987:     MPIULong_Recv(ourlens,m,MPIU_INT,0,tag,comm);
2988:   }

2990:   if (!rank) {
2991:     /* determine max buffer needed and allocate it */
2992:     maxnz = 0;
2993:     for (i=0; i<size; i++) {
2994:       maxnz = PetscMax(maxnz,procsnz[i]);
2995:     }
2996:     PetscMalloc1(maxnz,&cols);

2998:     /* read in my part of the matrix column indices  */
2999:     nz   = procsnz[0];
3000:     PetscMalloc1(nz,&mycols);
3001:     PetscBinaryRead(fd,mycols,nz,PETSC_INT);

3003:     /* read in every one elses and ship off */
3004:     for (i=1; i<size; i++) {
3005:       nz   = procsnz[i];
3006:       PetscBinaryRead(fd,cols,nz,PETSC_INT);
3007:       MPIULong_Send(cols,nz,MPIU_INT,i,tag,comm);
3008:     }
3009:     PetscFree(cols);
3010:   } else {
3011:     /* determine buffer space needed for message */
3012:     nz = 0;
3013:     for (i=0; i<m; i++) {
3014:       nz += ourlens[i];
3015:     }
3016:     PetscMalloc1(nz,&mycols);

3018:     /* receive message of column indices*/
3019:     MPIULong_Recv(mycols,nz,MPIU_INT,0,tag,comm);
3020:   }

3022:   /* determine column ownership if matrix is not square */
3023:   if (N != M) {
3024:     if (newMat->cmap->n < 0) n = N/size + ((N % size) > rank);
3025:     else n = newMat->cmap->n;
3026:     MPI_Scan(&n,&cend,1,MPIU_INT,MPI_SUM,comm);
3027:     cstart = cend - n;
3028:   } else {
3029:     cstart = rstart;
3030:     cend   = rend;
3031:     n      = cend - cstart;
3032:   }

3034:   /* loop over local rows, determining number of off diagonal entries */
3035:   PetscMemzero(offlens,m*sizeof(PetscInt));
3036:   jj   = 0;
3037:   for (i=0; i<m; i++) {
3038:     for (j=0; j<ourlens[i]; j++) {
3039:       if (mycols[jj] < cstart || mycols[jj] >= cend) offlens[i]++;
3040:       jj++;
3041:     }
3042:   }

3044:   for (i=0; i<m; i++) {
3045:     ourlens[i] -= offlens[i];
3046:   }
3047:   MatSetSizes(newMat,m,n,M,N);

3049:   if (bs > 1) {MatSetBlockSize(newMat,bs);}

3051:   MatMPIAIJSetPreallocation(newMat,0,ourlens,0,offlens);

3053:   for (i=0; i<m; i++) {
3054:     ourlens[i] += offlens[i];
3055:   }

3057:   if (!rank) {
3058:     PetscMalloc1(maxnz+1,&vals);

3060:     /* read in my part of the matrix numerical values  */
3061:     nz   = procsnz[0];
3062:     PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);

3064:     /* insert into matrix */
3065:     jj      = rstart;
3066:     smycols = mycols;
3067:     svals   = vals;
3068:     for (i=0; i<m; i++) {
3069:       MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);
3070:       smycols += ourlens[i];
3071:       svals   += ourlens[i];
3072:       jj++;
3073:     }

3075:     /* read in other processors and ship out */
3076:     for (i=1; i<size; i++) {
3077:       nz   = procsnz[i];
3078:       PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);
3079:       MPIULong_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newMat)->tag,comm);
3080:     }
3081:     PetscFree(procsnz);
3082:   } else {
3083:     /* receive numeric values */
3084:     PetscMalloc1(nz+1,&vals);

3086:     /* receive message of values*/
3087:     MPIULong_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newMat)->tag,comm);

3089:     /* insert into matrix */
3090:     jj      = rstart;
3091:     smycols = mycols;
3092:     svals   = vals;
3093:     for (i=0; i<m; i++) {
3094:       MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);
3095:       smycols += ourlens[i];
3096:       svals   += ourlens[i];
3097:       jj++;
3098:     }
3099:   }
3100:   PetscFree2(ourlens,offlens);
3101:   PetscFree(vals);
3102:   PetscFree(mycols);
3103:   PetscFree(rowners);
3104:   MatAssemblyBegin(newMat,MAT_FINAL_ASSEMBLY);
3105:   MatAssemblyEnd(newMat,MAT_FINAL_ASSEMBLY);
3106:   return(0);
3107: }

3109: /* Not scalable because of ISAllGather() unless getting all columns. */
3110: PetscErrorCode ISGetSeqIS_Private(Mat mat,IS iscol,IS *isseq)
3111: {
3113:   IS             iscol_local;
3114:   PetscBool      isstride;
3115:   PetscMPIInt    lisstride=0,gisstride;

3118:   /* check if we are grabbing all columns*/
3119:   PetscObjectTypeCompare((PetscObject)iscol,ISSTRIDE,&isstride);

3121:   if (isstride) {
3122:     PetscInt  start,len,mstart,mlen;
3123:     ISStrideGetInfo(iscol,&start,NULL);
3124:     ISGetLocalSize(iscol,&len);
3125:     MatGetOwnershipRangeColumn(mat,&mstart,&mlen);
3126:     if (mstart == start && mlen-mstart == len) lisstride = 1;
3127:   }

3129:   MPIU_Allreduce(&lisstride,&gisstride,1,MPI_INT,MPI_MIN,PetscObjectComm((PetscObject)mat));
3130:   if (gisstride) {
3131:     PetscInt N;
3132:     MatGetSize(mat,NULL,&N);
3133:     ISCreateStride(PetscObjectComm((PetscObject)mat),N,0,1,&iscol_local);
3134:     ISSetIdentity(iscol_local);
3135:     PetscInfo(mat,"Optimizing for obtaining all columns of the matrix; skipping ISAllGather()\n");
3136:   } else {
3137:     PetscInt cbs;
3138:     ISGetBlockSize(iscol,&cbs);
3139:     ISAllGather(iscol,&iscol_local);
3140:     ISSetBlockSize(iscol_local,cbs);
3141:   }

3143:   *isseq = iscol_local;
3144:   return(0);
3145: }

3147: /*
3148:  Used by MatCreateSubMatrix_MPIAIJ_SameRowColDist() to avoid ISAllGather() and global size of iscol_local
3149:  (see MatCreateSubMatrix_MPIAIJ_nonscalable)

3151:  Input Parameters:
3152:    mat - matrix
3153:    isrow - parallel row index set; its local indices are a subset of local columns of mat,
3154:            i.e., mat->rstart <= isrow[i] < mat->rend
3155:    iscol - parallel column index set; its local indices are a subset of local columns of mat,
3156:            i.e., mat->cstart <= iscol[i] < mat->cend
3157:  Output Parameter:
3158:    isrow_d,iscol_d - sequential row and column index sets for retrieving mat->A
3159:    iscol_o - sequential column index set for retrieving mat->B
3160:    garray - column map; garray[i] indicates global location of iscol_o[i] in iscol
3161:  */
3162: PetscErrorCode ISGetSeqIS_SameColDist_Private(Mat mat,IS isrow,IS iscol,IS *isrow_d,IS *iscol_d,IS *iscol_o,const PetscInt *garray[])
3163: {
3165:   Vec            x,cmap;
3166:   const PetscInt *is_idx;
3167:   PetscScalar    *xarray,*cmaparray;
3168:   PetscInt       ncols,isstart,*idx,m,rstart,*cmap1,count;
3169:   Mat_MPIAIJ     *a=(Mat_MPIAIJ*)mat->data;
3170:   Mat            B=a->B;
3171:   Vec            lvec=a->lvec,lcmap;
3172:   PetscInt       i,cstart,cend,Bn=B->cmap->N;
3173:   MPI_Comm       comm;
3174:   VecScatter     Mvctx=a->Mvctx;

3177:   PetscObjectGetComm((PetscObject)mat,&comm);
3178:   ISGetLocalSize(iscol,&ncols);

3180:   /* (1) iscol is a sub-column vector of mat, pad it with '-1.' to form a full vector x */
3181:   MatCreateVecs(mat,&x,NULL);
3182:   VecSet(x,-1.0);
3183:   VecDuplicate(x,&cmap);
3184:   VecSet(cmap,-1.0);

3186:   /* Get start indices */
3187:   MPI_Scan(&ncols,&isstart,1,MPIU_INT,MPI_SUM,comm);
3188:   isstart -= ncols;
3189:   MatGetOwnershipRangeColumn(mat,&cstart,&cend);

3191:   ISGetIndices(iscol,&is_idx);
3192:   VecGetArray(x,&xarray);
3193:   VecGetArray(cmap,&cmaparray);
3194:   PetscMalloc1(ncols,&idx);
3195:   for (i=0; i<ncols; i++) {
3196:     xarray[is_idx[i]-cstart]    = (PetscScalar)is_idx[i];
3197:     cmaparray[is_idx[i]-cstart] = i + isstart;      /* global index of iscol[i] */
3198:     idx[i]                      = is_idx[i]-cstart; /* local index of iscol[i]  */
3199:   }
3200:   VecRestoreArray(x,&xarray);
3201:   VecRestoreArray(cmap,&cmaparray);
3202:   ISRestoreIndices(iscol,&is_idx);

3204:   /* Get iscol_d */
3205:   ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,iscol_d);
3206:   ISGetBlockSize(iscol,&i);
3207:   ISSetBlockSize(*iscol_d,i);

3209:   /* Get isrow_d */
3210:   ISGetLocalSize(isrow,&m);
3211:   rstart = mat->rmap->rstart;
3212:   PetscMalloc1(m,&idx);
3213:   ISGetIndices(isrow,&is_idx);
3214:   for (i=0; i<m; i++) idx[i] = is_idx[i]-rstart;
3215:   ISRestoreIndices(isrow,&is_idx);

3217:   ISCreateGeneral(PETSC_COMM_SELF,m,idx,PETSC_OWN_POINTER,isrow_d);
3218:   ISGetBlockSize(isrow,&i);
3219:   ISSetBlockSize(*isrow_d,i);

3221:   /* (2) Scatter x and cmap using aij->Mvctx to get their off-process portions (see MatMult_MPIAIJ) */
3222:   VecScatterBegin(Mvctx,x,lvec,INSERT_VALUES,SCATTER_FORWARD);
3223:   VecScatterEnd(Mvctx,x,lvec,INSERT_VALUES,SCATTER_FORWARD);

3225:   VecDuplicate(lvec,&lcmap);

3227:   VecScatterBegin(Mvctx,cmap,lcmap,INSERT_VALUES,SCATTER_FORWARD);
3228:   VecScatterEnd(Mvctx,cmap,lcmap,INSERT_VALUES,SCATTER_FORWARD);

3230:   /* (3) create sequential iscol_o (a subset of iscol) and isgarray */
3231:   /* off-process column indices */
3232:   count = 0;
3233:   PetscMalloc1(Bn,&idx);
3234:   PetscMalloc1(Bn,&cmap1);

3236:   VecGetArray(lvec,&xarray);
3237:   VecGetArray(lcmap,&cmaparray);
3238:   for (i=0; i<Bn; i++) {
3239:     if (PetscRealPart(xarray[i]) > -1.0) {
3240:       idx[count]     = i;                   /* local column index in off-diagonal part B */
3241:       cmap1[count] = (PetscInt)PetscRealPart(cmaparray[i]);  /* column index in submat */
3242:       count++;
3243:     }
3244:   }
3245:   VecRestoreArray(lvec,&xarray);
3246:   VecRestoreArray(lcmap,&cmaparray);

3248:   ISCreateGeneral(PETSC_COMM_SELF,count,idx,PETSC_COPY_VALUES,iscol_o);
3249:   /* cannot ensure iscol_o has same blocksize as iscol! */

3251:   PetscFree(idx);
3252:   *garray = cmap1;

3254:   VecDestroy(&x);
3255:   VecDestroy(&cmap);
3256:   VecDestroy(&lcmap);
3257:   return(0);
3258: }

3260: /* isrow and iscol have same processor distribution as mat, output *submat is a submatrix of local mat */
3261: PetscErrorCode MatCreateSubMatrix_MPIAIJ_SameRowColDist(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *submat)
3262: {
3264:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)mat->data,*asub;
3265:   Mat            M = NULL;
3266:   MPI_Comm       comm;
3267:   IS             iscol_d,isrow_d,iscol_o;
3268:   Mat            Asub = NULL,Bsub = NULL;
3269:   PetscInt       n;

3272:   PetscObjectGetComm((PetscObject)mat,&comm);

3274:   if (call == MAT_REUSE_MATRIX) {
3275:     /* Retrieve isrow_d, iscol_d and iscol_o from submat */
3276:     PetscObjectQuery((PetscObject)*submat,"isrow_d",(PetscObject*)&isrow_d);
3277:     if (!isrow_d) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"isrow_d passed in was not used before, cannot reuse");

3279:     PetscObjectQuery((PetscObject)*submat,"iscol_d",(PetscObject*)&iscol_d);
3280:     if (!iscol_d) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"iscol_d passed in was not used before, cannot reuse");

3282:     PetscObjectQuery((PetscObject)*submat,"iscol_o",(PetscObject*)&iscol_o);
3283:     if (!iscol_o) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"iscol_o passed in was not used before, cannot reuse");

3285:     /* Update diagonal and off-diagonal portions of submat */
3286:     asub = (Mat_MPIAIJ*)(*submat)->data;
3287:     MatCreateSubMatrix_SeqAIJ(a->A,isrow_d,iscol_d,PETSC_DECIDE,MAT_REUSE_MATRIX,&asub->A);
3288:     ISGetLocalSize(iscol_o,&n);
3289:     if (n) {
3290:       MatCreateSubMatrix_SeqAIJ(a->B,isrow_d,iscol_o,PETSC_DECIDE,MAT_REUSE_MATRIX,&asub->B);
3291:     }
3292:     MatAssemblyBegin(*submat,MAT_FINAL_ASSEMBLY);
3293:     MatAssemblyEnd(*submat,MAT_FINAL_ASSEMBLY);

3295:   } else { /* call == MAT_INITIAL_MATRIX) */
3296:     const PetscInt *garray;
3297:     PetscInt        BsubN;

3299:     /* Create isrow_d, iscol_d, iscol_o and isgarray (replace isgarray with array?) */
3300:     ISGetSeqIS_SameColDist_Private(mat,isrow,iscol,&isrow_d,&iscol_d,&iscol_o,&garray);

3302:     /* Create local submatrices Asub and Bsub */
3303:     MatCreateSubMatrix_SeqAIJ(a->A,isrow_d,iscol_d,PETSC_DECIDE,MAT_INITIAL_MATRIX,&Asub);
3304:     MatCreateSubMatrix_SeqAIJ(a->B,isrow_d,iscol_o,PETSC_DECIDE,MAT_INITIAL_MATRIX,&Bsub);

3306:     /* Create submatrix M */
3307:     MatCreateMPIAIJWithSeqAIJ(comm,Asub,Bsub,garray,&M);

3309:     /* If Bsub has empty columns, compress iscol_o such that it will retrieve condensed Bsub from a->B during reuse */
3310:     asub = (Mat_MPIAIJ*)M->data;

3312:     ISGetLocalSize(iscol_o,&BsubN);
3313:     n = asub->B->cmap->N;
3314:     if (BsubN > n) {
3315:       /* This case can be tested using ~petsc/src/tao/bound/examples/tutorials/runplate2_3 */
3316:       const PetscInt *idx;
3317:       PetscInt       i,j,*idx_new,*subgarray = asub->garray;
3318:       PetscInfo2(M,"submatrix Bn %D != BsubN %D, update iscol_o\n",n,BsubN);

3320:       PetscMalloc1(n,&idx_new);
3321:       j = 0;
3322:       ISGetIndices(iscol_o,&idx);
3323:       for (i=0; i<n; i++) {
3324:         if (j >= BsubN) break;
3325:         while (subgarray[i] > garray[j]) j++;

3327:         if (subgarray[i] == garray[j]) {
3328:           idx_new[i] = idx[j++];
3329:         } else SETERRQ4(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"subgarray[%D]=%D cannot < garray[%D]=%D",i,subgarray[i],j,garray[j]);
3330:       }
3331:       ISRestoreIndices(iscol_o,&idx);

3333:       ISDestroy(&iscol_o);
3334:       ISCreateGeneral(PETSC_COMM_SELF,n,idx_new,PETSC_OWN_POINTER,&iscol_o);

3336:     } else if (BsubN < n) {
3337:       SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Columns of Bsub cannot be smaller than B's",BsubN,asub->B->cmap->N);
3338:     }

3340:     PetscFree(garray);
3341:     *submat = M;

3343:     /* Save isrow_d, iscol_d and iscol_o used in processor for next request */
3344:     PetscObjectCompose((PetscObject)M,"isrow_d",(PetscObject)isrow_d);
3345:     ISDestroy(&isrow_d);

3347:     PetscObjectCompose((PetscObject)M,"iscol_d",(PetscObject)iscol_d);
3348:     ISDestroy(&iscol_d);

3350:     PetscObjectCompose((PetscObject)M,"iscol_o",(PetscObject)iscol_o);
3351:     ISDestroy(&iscol_o);
3352:   }
3353:   return(0);
3354: }

3356: PetscErrorCode MatCreateSubMatrix_MPIAIJ(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat)
3357: {
3359:   IS             iscol_local=NULL,isrow_d;
3360:   PetscInt       csize;
3361:   PetscInt       n,i,j,start,end;
3362:   PetscBool      sameRowDist=PETSC_FALSE,sameDist[2],tsameDist[2];
3363:   MPI_Comm       comm;

3366:   /* If isrow has same processor distribution as mat,
3367:      call MatCreateSubMatrix_MPIAIJ_SameRowDist() to avoid using a hash table with global size of iscol */
3368:   if (call == MAT_REUSE_MATRIX) {
3369:     PetscObjectQuery((PetscObject)*newmat,"isrow_d",(PetscObject*)&isrow_d);
3370:     if (isrow_d) {
3371:       sameRowDist  = PETSC_TRUE;
3372:       tsameDist[1] = PETSC_TRUE; /* sameColDist */
3373:     } else {
3374:       PetscObjectQuery((PetscObject)*newmat,"SubIScol",(PetscObject*)&iscol_local);
3375:       if (iscol_local) {
3376:         sameRowDist  = PETSC_TRUE;
3377:         tsameDist[1] = PETSC_FALSE; /* !sameColDist */
3378:       }
3379:     }
3380:   } else {
3381:     /* Check if isrow has same processor distribution as mat */
3382:     sameDist[0] = PETSC_FALSE;
3383:     ISGetLocalSize(isrow,&n);
3384:     if (!n) {
3385:       sameDist[0] = PETSC_TRUE;
3386:     } else {
3387:       ISGetMinMax(isrow,&i,&j);
3388:       MatGetOwnershipRange(mat,&start,&end);
3389:       if (i >= start && j < end) {
3390:         sameDist[0] = PETSC_TRUE;
3391:       }
3392:     }

3394:     /* Check if iscol has same processor distribution as mat */
3395:     sameDist[1] = PETSC_FALSE;
3396:     ISGetLocalSize(iscol,&n);
3397:     if (!n) {
3398:       sameDist[1] = PETSC_TRUE;
3399:     } else {
3400:       ISGetMinMax(iscol,&i,&j);
3401:       MatGetOwnershipRangeColumn(mat,&start,&end);
3402:       if (i >= start && j < end) sameDist[1] = PETSC_TRUE;
3403:     }

3405:     PetscObjectGetComm((PetscObject)mat,&comm);
3406:     MPIU_Allreduce(&sameDist,&tsameDist,2,MPIU_BOOL,MPI_LAND,comm);
3407:     sameRowDist = tsameDist[0];
3408:   }

3410:   if (sameRowDist) {
3411:     if (tsameDist[1]) { /* sameRowDist & sameColDist */
3412:       /* isrow and iscol have same processor distribution as mat */
3413:       MatCreateSubMatrix_MPIAIJ_SameRowColDist(mat,isrow,iscol,call,newmat);
3414:       return(0);
3415:     } else { /* sameRowDist */
3416:       /* isrow has same processor distribution as mat */
3417:       if (call == MAT_INITIAL_MATRIX) {
3418:         PetscBool sorted;
3419:         ISGetSeqIS_Private(mat,iscol,&iscol_local);
3420:         ISGetLocalSize(iscol_local,&n); /* local size of iscol_local = global columns of newmat */
3421:         ISGetSize(iscol,&i);
3422:         if (n != i) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"n %d != size of iscol %d",n,i);

3424:         ISSorted(iscol_local,&sorted);
3425:         if (sorted) {
3426:           /* MatCreateSubMatrix_MPIAIJ_SameRowDist() requires iscol_local be sorted; it can have duplicate indices */
3427:           MatCreateSubMatrix_MPIAIJ_SameRowDist(mat,isrow,iscol,iscol_local,MAT_INITIAL_MATRIX,newmat);
3428:           return(0);
3429:         }
3430:       } else { /* call == MAT_REUSE_MATRIX */
3431:         IS    iscol_sub;
3432:         PetscObjectQuery((PetscObject)*newmat,"SubIScol",(PetscObject*)&iscol_sub);
3433:         if (iscol_sub) {
3434:           MatCreateSubMatrix_MPIAIJ_SameRowDist(mat,isrow,iscol,NULL,call,newmat);
3435:           return(0);
3436:         }
3437:       }
3438:     }
3439:   }

3441:   /* General case: iscol -> iscol_local which has global size of iscol */
3442:   if (call == MAT_REUSE_MATRIX) {
3443:     PetscObjectQuery((PetscObject)*newmat,"ISAllGather",(PetscObject*)&iscol_local);
3444:     if (!iscol_local) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse");
3445:   } else {
3446:     if (!iscol_local) {
3447:       ISGetSeqIS_Private(mat,iscol,&iscol_local);
3448:     }
3449:   }

3451:   ISGetLocalSize(iscol,&csize);
3452:   MatCreateSubMatrix_MPIAIJ_nonscalable(mat,isrow,iscol_local,csize,call,newmat);

3454:   if (call == MAT_INITIAL_MATRIX) {
3455:     PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);
3456:     ISDestroy(&iscol_local);
3457:   }
3458:   return(0);
3459: }

3461: /*@C
3462:      MatCreateMPIAIJWithSeqAIJ - creates a MPIAIJ matrix using SeqAIJ matrices that contain the "diagonal"
3463:          and "off-diagonal" part of the matrix in CSR format.

3465:    Collective on MPI_Comm

3467:    Input Parameters:
3468: +  comm - MPI communicator
3469: .  A - "diagonal" portion of matrix
3470: .  B - "off-diagonal" portion of matrix, may have empty columns, will be destroyed by this routine
3471: -  garray - global index of B columns

3473:    Output Parameter:
3474: .   mat - the matrix, with input A as its local diagonal matrix
3475:    Level: advanced

3477:    Notes:
3478:        See MatCreateAIJ() for the definition of "diagonal" and "off-diagonal" portion of the matrix.
3479:        A becomes part of output mat, B is destroyed by this routine. The user cannot use A and B anymore.

3481: .seealso: MatCreateMPIAIJWithSplitArrays()
3482: @*/
3483: PetscErrorCode MatCreateMPIAIJWithSeqAIJ(MPI_Comm comm,Mat A,Mat B,const PetscInt garray[],Mat *mat)
3484: {
3486:   Mat_MPIAIJ     *maij;
3487:   Mat_SeqAIJ     *b=(Mat_SeqAIJ*)B->data,*bnew;
3488:   PetscInt       *oi=b->i,*oj=b->j,i,nz,col;
3489:   PetscScalar    *oa=b->a;
3490:   Mat            Bnew;
3491:   PetscInt       m,n,N;

3494:   MatCreate(comm,mat);
3495:   MatGetSize(A,&m,&n);
3496:   if (m != B->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Am %D != Bm %D",m,B->rmap->N);
3497:   if (A->rmap->bs != B->rmap->bs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"A row bs %D != B row bs %D",A->rmap->bs,B->rmap->bs);
3498:   /* remove check below; When B is created using iscol_o from ISGetSeqIS_SameColDist_Private(), its bs may not be same as A */
3499:   /* if (A->cmap->bs != B->cmap->bs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"A column bs %D != B column bs %D",A->cmap->bs,B->cmap->bs); */

3501:   /* Get global columns of mat */
3502:   MPIU_Allreduce(&n,&N,1,MPIU_INT,MPI_SUM,comm);

3504:   MatSetSizes(*mat,m,n,PETSC_DECIDE,N);
3505:   MatSetType(*mat,MATMPIAIJ);
3506:   MatSetBlockSizes(*mat,A->rmap->bs,A->cmap->bs);
3507:   maij = (Mat_MPIAIJ*)(*mat)->data;

3509:   (*mat)->preallocated = PETSC_TRUE;

3511:   PetscLayoutSetUp((*mat)->rmap);
3512:   PetscLayoutSetUp((*mat)->cmap);

3514:   /* Set A as diagonal portion of *mat */
3515:   maij->A = A;

3517:   nz = oi[m];
3518:   for (i=0; i<nz; i++) {
3519:     col   = oj[i];
3520:     oj[i] = garray[col];
3521:   }

3523:    /* Set Bnew as off-diagonal portion of *mat */
3524:   MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,N,oi,oj,oa,&Bnew);
3525:   bnew        = (Mat_SeqAIJ*)Bnew->data;
3526:   bnew->maxnz = b->maxnz; /* allocated nonzeros of B */
3527:   maij->B     = Bnew;

3529:   if (B->rmap->N != Bnew->rmap->N) SETERRQ2(PETSC_COMM_SELF,0,"BN %d != BnewN %d",B->rmap->N,Bnew->rmap->N);

3531:   b->singlemalloc = PETSC_FALSE; /* B arrays are shared by Bnew */
3532:   b->free_a       = PETSC_FALSE;
3533:   b->free_ij      = PETSC_FALSE;
3534:   MatDestroy(&B);

3536:   bnew->singlemalloc = PETSC_TRUE; /* arrays will be freed by MatDestroy(&Bnew) */
3537:   bnew->free_a       = PETSC_TRUE;
3538:   bnew->free_ij      = PETSC_TRUE;

3540:   /* condense columns of maij->B */
3541:   MatSetOption(*mat,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE);
3542:   MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);
3543:   MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);
3544:   MatSetOption(*mat,MAT_NO_OFF_PROC_ENTRIES,PETSC_FALSE);
3545:   MatSetOption(*mat,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);
3546:   return(0);
3547: }

3549: extern PetscErrorCode MatCreateSubMatrices_MPIAIJ_SingleIS_Local(Mat,PetscInt,const IS[],const IS[],MatReuse,PetscBool,Mat*);

3551: PetscErrorCode MatCreateSubMatrix_MPIAIJ_SameRowDist(Mat mat,IS isrow,IS iscol,IS iscol_local,MatReuse call,Mat *newmat)
3552: {
3554:   PetscInt       i,m,n,rstart,row,rend,nz,j,bs,cbs;
3555:   PetscInt       *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal;
3556:   Mat_MPIAIJ     *a=(Mat_MPIAIJ*)mat->data;
3557:   Mat            M,Msub,B=a->B;
3558:   MatScalar      *aa;
3559:   Mat_SeqAIJ     *aij;
3560:   PetscInt       *garray = a->garray,*colsub,Ncols;
3561:   PetscInt       count,Bn=B->cmap->N,cstart=mat->cmap->rstart,cend=mat->cmap->rend;
3562:   IS             iscol_sub,iscmap;
3563:   const PetscInt *is_idx,*cmap;
3564:   PetscBool      allcolumns=PETSC_FALSE;
3565:   MPI_Comm       comm;

3568:   PetscObjectGetComm((PetscObject)mat,&comm);

3570:   if (call == MAT_REUSE_MATRIX) {
3571:     PetscObjectQuery((PetscObject)*newmat,"SubIScol",(PetscObject*)&iscol_sub);
3572:     if (!iscol_sub) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"SubIScol passed in was not used before, cannot reuse");
3573:     ISGetLocalSize(iscol_sub,&count);

3575:     PetscObjectQuery((PetscObject)*newmat,"Subcmap",(PetscObject*)&iscmap);
3576:     if (!iscmap) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Subcmap passed in was not used before, cannot reuse");

3578:     PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject*)&Msub);
3579:     if (!Msub) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse");

3581:     MatCreateSubMatrices_MPIAIJ_SingleIS_Local(mat,1,&isrow,&iscol_sub,MAT_REUSE_MATRIX,PETSC_FALSE,&Msub);

3583:   } else { /* call == MAT_INITIAL_MATRIX) */
3584:     PetscBool flg;

3586:     ISGetLocalSize(iscol,&n);
3587:     ISGetSize(iscol,&Ncols);

3589:     /* (1) iscol -> nonscalable iscol_local */
3590:     /* Check for special case: each processor gets entire matrix columns */
3591:     ISIdentity(iscol_local,&flg);
3592:     if (flg && n == mat->cmap->N) allcolumns = PETSC_TRUE;
3593:     if (allcolumns) {
3594:       iscol_sub = iscol_local;
3595:       PetscObjectReference((PetscObject)iscol_local);
3596:       ISCreateStride(PETSC_COMM_SELF,n,0,1,&iscmap);

3598:     } else {
3599:       /* (2) iscol_local -> iscol_sub and iscmap. Implementation below requires iscol_local be sorted, it can have duplicate indices */
3600:       PetscInt *idx,*cmap1,k;
3601:       PetscMalloc1(Ncols,&idx);
3602:       PetscMalloc1(Ncols,&cmap1);
3603:       ISGetIndices(iscol_local,&is_idx);
3604:       count = 0;
3605:       k     = 0;
3606:       for (i=0; i<Ncols; i++) {
3607:         j = is_idx[i];
3608:         if (j >= cstart && j < cend) {
3609:           /* diagonal part of mat */
3610:           idx[count]     = j;
3611:           cmap1[count++] = i; /* column index in submat */
3612:         } else if (Bn) {
3613:           /* off-diagonal part of mat */
3614:           if (j == garray[k]) {
3615:             idx[count]     = j;
3616:             cmap1[count++] = i;  /* column index in submat */
3617:           } else if (j > garray[k]) {
3618:             while (j > garray[k] && k < Bn-1) k++;
3619:             if (j == garray[k]) {
3620:               idx[count]     = j;
3621:               cmap1[count++] = i; /* column index in submat */
3622:             }
3623:           }
3624:         }
3625:       }
3626:       ISRestoreIndices(iscol_local,&is_idx);

3628:       ISCreateGeneral(PETSC_COMM_SELF,count,idx,PETSC_OWN_POINTER,&iscol_sub);
3629:       ISGetBlockSize(iscol,&cbs);
3630:       ISSetBlockSize(iscol_sub,cbs);

3632:       ISCreateGeneral(PetscObjectComm((PetscObject)iscol_local),count,cmap1,PETSC_OWN_POINTER,&iscmap);
3633:     }

3635:     /* (3) Create sequential Msub */
3636:     MatCreateSubMatrices_MPIAIJ_SingleIS_Local(mat,1,&isrow,&iscol_sub,MAT_INITIAL_MATRIX,allcolumns,&Msub);
3637:   }

3639:   ISGetLocalSize(iscol_sub,&count);
3640:   aij  = (Mat_SeqAIJ*)(Msub)->data;
3641:   ii   = aij->i;
3642:   ISGetIndices(iscmap,&cmap);

3644:   /*
3645:       m - number of local rows
3646:       Ncols - number of columns (same on all processors)
3647:       rstart - first row in new global matrix generated
3648:   */
3649:   MatGetSize(Msub,&m,NULL);

3651:   if (call == MAT_INITIAL_MATRIX) {
3652:     /* (4) Create parallel newmat */
3653:     PetscMPIInt    rank,size;
3654:     PetscInt       csize;

3656:     MPI_Comm_size(comm,&size);
3657:     MPI_Comm_rank(comm,&rank);

3659:     /*
3660:         Determine the number of non-zeros in the diagonal and off-diagonal
3661:         portions of the matrix in order to do correct preallocation
3662:     */

3664:     /* first get start and end of "diagonal" columns */
3665:     ISGetLocalSize(iscol,&csize);
3666:     if (csize == PETSC_DECIDE) {
3667:       ISGetSize(isrow,&mglobal);
3668:       if (mglobal == Ncols) { /* square matrix */
3669:         nlocal = m;
3670:       } else {
3671:         nlocal = Ncols/size + ((Ncols % size) > rank);
3672:       }
3673:     } else {
3674:       nlocal = csize;
3675:     }
3676:     MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);
3677:     rstart = rend - nlocal;
3678:     if (rank == size - 1 && rend != Ncols) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Local column sizes %D do not add up to total number of columns %D",rend,Ncols);

3680:     /* next, compute all the lengths */
3681:     jj    = aij->j;
3682:     PetscMalloc1(2*m+1,&dlens);
3683:     olens = dlens + m;
3684:     for (i=0; i<m; i++) {
3685:       jend = ii[i+1] - ii[i];
3686:       olen = 0;
3687:       dlen = 0;
3688:       for (j=0; j<jend; j++) {
3689:         if (cmap[*jj] < rstart || cmap[*jj] >= rend) olen++;
3690:         else dlen++;
3691:         jj++;
3692:       }
3693:       olens[i] = olen;
3694:       dlens[i] = dlen;
3695:     }

3697:     ISGetBlockSize(isrow,&bs);
3698:     ISGetBlockSize(iscol,&cbs);

3700:     MatCreate(comm,&M);
3701:     MatSetSizes(M,m,nlocal,PETSC_DECIDE,Ncols);
3702:     MatSetBlockSizes(M,bs,cbs);
3703:     MatSetType(M,((PetscObject)mat)->type_name);
3704:     MatMPIAIJSetPreallocation(M,0,dlens,0,olens);
3705:     PetscFree(dlens);

3707:   } else { /* call == MAT_REUSE_MATRIX */
3708:     M    = *newmat;
3709:     MatGetLocalSize(M,&i,NULL);
3710:     if (i != m) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request");
3711:     MatZeroEntries(M);
3712:     /*
3713:          The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly,
3714:        rather than the slower MatSetValues().
3715:     */
3716:     M->was_assembled = PETSC_TRUE;
3717:     M->assembled     = PETSC_FALSE;
3718:   }

3720:   /* (5) Set values of Msub to *newmat */
3721:   PetscMalloc1(count,&colsub);
3722:   MatGetOwnershipRange(M,&rstart,NULL);

3724:   jj   = aij->j;
3725:   aa   = aij->a;
3726:   for (i=0; i<m; i++) {
3727:     row = rstart + i;
3728:     nz  = ii[i+1] - ii[i];
3729:     for (j=0; j<nz; j++) colsub[j] = cmap[jj[j]];
3730:     MatSetValues_MPIAIJ(M,1,&row,nz,colsub,aa,INSERT_VALUES);
3731:     jj += nz; aa += nz;
3732:   }
3733:   ISRestoreIndices(iscmap,&cmap);

3735:   MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);
3736:   MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);

3738:   PetscFree(colsub);

3740:   /* save Msub, iscol_sub and iscmap used in processor for next request */
3741:   if (call ==  MAT_INITIAL_MATRIX) {
3742:     *newmat = M;
3743:     PetscObjectCompose((PetscObject)(*newmat),"SubMatrix",(PetscObject)Msub);
3744:     MatDestroy(&Msub);

3746:     PetscObjectCompose((PetscObject)(*newmat),"SubIScol",(PetscObject)iscol_sub);
3747:     ISDestroy(&iscol_sub);

3749:     PetscObjectCompose((PetscObject)(*newmat),"Subcmap",(PetscObject)iscmap);
3750:     ISDestroy(&iscmap);

3752:     if (iscol_local) {
3753:       PetscObjectCompose((PetscObject)(*newmat),"ISAllGather",(PetscObject)iscol_local);
3754:       ISDestroy(&iscol_local);
3755:     }
3756:   }
3757:   return(0);
3758: }

3760: /*
3761:     Not great since it makes two copies of the submatrix, first an SeqAIJ
3762:   in local and then by concatenating the local matrices the end result.
3763:   Writing it directly would be much like MatCreateSubMatrices_MPIAIJ()

3765:   Note: This requires a sequential iscol with all indices.
3766: */
3767: PetscErrorCode MatCreateSubMatrix_MPIAIJ_nonscalable(Mat mat,IS isrow,IS iscol,PetscInt csize,MatReuse call,Mat *newmat)
3768: {
3770:   PetscMPIInt    rank,size;
3771:   PetscInt       i,m,n,rstart,row,rend,nz,*cwork,j,bs,cbs;
3772:   PetscInt       *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal;
3773:   Mat            M,Mreuse;
3774:   MatScalar      *aa,*vwork;
3775:   MPI_Comm       comm;
3776:   Mat_SeqAIJ     *aij;
3777:   PetscBool      colflag,allcolumns=PETSC_FALSE;

3780:   PetscObjectGetComm((PetscObject)mat,&comm);
3781:   MPI_Comm_rank(comm,&rank);
3782:   MPI_Comm_size(comm,&size);

3784:   /* Check for special case: each processor gets entire matrix columns */
3785:   ISIdentity(iscol,&colflag);
3786:   ISGetLocalSize(iscol,&n);
3787:   if (colflag && n == mat->cmap->N) allcolumns = PETSC_TRUE;

3789:   if (call ==  MAT_REUSE_MATRIX) {
3790:     PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject*)&Mreuse);
3791:     if (!Mreuse) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse");
3792:     MatCreateSubMatrices_MPIAIJ_SingleIS_Local(mat,1,&isrow,&iscol,MAT_REUSE_MATRIX,allcolumns,&Mreuse);
3793:   } else {
3794:     MatCreateSubMatrices_MPIAIJ_SingleIS_Local(mat,1,&isrow,&iscol,MAT_INITIAL_MATRIX,allcolumns,&Mreuse);
3795:   }

3797:   /*
3798:       m - number of local rows
3799:       n - number of columns (same on all processors)
3800:       rstart - first row in new global matrix generated
3801:   */
3802:   MatGetSize(Mreuse,&m,&n);
3803:   MatGetBlockSizes(Mreuse,&bs,&cbs);
3804:   if (call == MAT_INITIAL_MATRIX) {
3805:     aij = (Mat_SeqAIJ*)(Mreuse)->data;
3806:     ii  = aij->i;
3807:     jj  = aij->j;

3809:     /*
3810:         Determine the number of non-zeros in the diagonal and off-diagonal
3811:         portions of the matrix in order to do correct preallocation
3812:     */

3814:     /* first get start and end of "diagonal" columns */
3815:     if (csize == PETSC_DECIDE) {
3816:       ISGetSize(isrow,&mglobal);
3817:       if (mglobal == n) { /* square matrix */
3818:         nlocal = m;
3819:       } else {
3820:         nlocal = n/size + ((n % size) > rank);
3821:       }
3822:     } else {
3823:       nlocal = csize;
3824:     }
3825:     MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);
3826:     rstart = rend - nlocal;
3827:     if (rank == size - 1 && rend != n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Local column sizes %D do not add up to total number of columns %D",rend,n);

3829:     /* next, compute all the lengths */
3830:     PetscMalloc1(2*m+1,&dlens);
3831:     olens = dlens + m;
3832:     for (i=0; i<m; i++) {
3833:       jend = ii[i+1] - ii[i];
3834:       olen = 0;
3835:       dlen = 0;
3836:       for (j=0; j<jend; j++) {
3837:         if (*jj < rstart || *jj >= rend) olen++;
3838:         else dlen++;
3839:         jj++;
3840:       }
3841:       olens[i] = olen;
3842:       dlens[i] = dlen;
3843:     }
3844:     MatCreate(comm,&M);
3845:     MatSetSizes(M,m,nlocal,PETSC_DECIDE,n);
3846:     MatSetBlockSizes(M,bs,cbs);
3847:     MatSetType(M,((PetscObject)mat)->type_name);
3848:     MatMPIAIJSetPreallocation(M,0,dlens,0,olens);
3849:     PetscFree(dlens);
3850:   } else {
3851:     PetscInt ml,nl;

3853:     M    = *newmat;
3854:     MatGetLocalSize(M,&ml,&nl);
3855:     if (ml != m) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request");
3856:     MatZeroEntries(M);
3857:     /*
3858:          The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly,
3859:        rather than the slower MatSetValues().
3860:     */
3861:     M->was_assembled = PETSC_TRUE;
3862:     M->assembled     = PETSC_FALSE;
3863:   }
3864:   MatGetOwnershipRange(M,&rstart,&rend);
3865:   aij  = (Mat_SeqAIJ*)(Mreuse)->data;
3866:   ii   = aij->i;
3867:   jj   = aij->j;
3868:   aa   = aij->a;
3869:   for (i=0; i<m; i++) {
3870:     row   = rstart + i;
3871:     nz    = ii[i+1] - ii[i];
3872:     cwork = jj;     jj += nz;
3873:     vwork = aa;     aa += nz;
3874:     MatSetValues_MPIAIJ(M,1,&row,nz,cwork,vwork,INSERT_VALUES);
3875:   }

3877:   MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);
3878:   MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);
3879:   *newmat = M;

3881:   /* save submatrix used in processor for next request */
3882:   if (call ==  MAT_INITIAL_MATRIX) {
3883:     PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Mreuse);
3884:     MatDestroy(&Mreuse);
3885:   }
3886:   return(0);
3887: }

3889: PetscErrorCode MatMPIAIJSetPreallocationCSR_MPIAIJ(Mat B,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[])
3890: {
3891:   PetscInt       m,cstart, cend,j,nnz,i,d;
3892:   PetscInt       *d_nnz,*o_nnz,nnz_max = 0,rstart,ii;
3893:   const PetscInt *JJ;
3894:   PetscScalar    *values;
3896:   PetscBool      nooffprocentries;

3899:   if (Ii && Ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Ii[0] must be 0 it is %D",Ii[0]);

3901:   PetscLayoutSetUp(B->rmap);
3902:   PetscLayoutSetUp(B->cmap);
3903:   m      = B->rmap->n;
3904:   cstart = B->cmap->rstart;
3905:   cend   = B->cmap->rend;
3906:   rstart = B->rmap->rstart;

3908:   PetscMalloc2(m,&d_nnz,m,&o_nnz);

3910: #if defined(PETSC_USE_DEBUG)
3911:   for (i=0; i<m; i++) {
3912:     nnz = Ii[i+1]- Ii[i];
3913:     JJ  = J + Ii[i];
3914:     if (nnz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative %D number of columns",i,nnz);
3915:     if (nnz && (JJ[0] < 0)) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Row %D starts with negative column index",i,JJ[0]);
3916:     if (nnz && (JJ[nnz-1] >= B->cmap->N)) SETERRQ3(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Row %D ends with too large a column index %D (max allowed %D)",i,JJ[nnz-1],B->cmap->N);
3917:   }
3918: #endif

3920:   for (i=0; i<m; i++) {
3921:     nnz     = Ii[i+1]- Ii[i];
3922:     JJ      = J + Ii[i];
3923:     nnz_max = PetscMax(nnz_max,nnz);
3924:     d       = 0;
3925:     for (j=0; j<nnz; j++) {
3926:       if (cstart <= JJ[j] && JJ[j] < cend) d++;
3927:     }
3928:     d_nnz[i] = d;
3929:     o_nnz[i] = nnz - d;
3930:   }
3931:   MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);
3932:   PetscFree2(d_nnz,o_nnz);

3934:   if (v) values = (PetscScalar*)v;
3935:   else {
3936:     PetscCalloc1(nnz_max+1,&values);
3937:   }

3939:   for (i=0; i<m; i++) {
3940:     ii   = i + rstart;
3941:     nnz  = Ii[i+1]- Ii[i];
3942:     MatSetValues_MPIAIJ(B,1,&ii,nnz,J+Ii[i],values+(v ? Ii[i] : 0),INSERT_VALUES);
3943:   }
3944:   nooffprocentries    = B->nooffprocentries;
3945:   B->nooffprocentries = PETSC_TRUE;
3946:   MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
3947:   MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);
3948:   B->nooffprocentries = nooffprocentries;

3950:   if (!v) {
3951:     PetscFree(values);
3952:   }
3953:   MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);
3954:   return(0);
3955: }

3957: /*@
3958:    MatMPIAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in AIJ format
3959:    (the default parallel PETSc format).

3961:    Collective on MPI_Comm

3963:    Input Parameters:
3964: +  B - the matrix
3965: .  i - the indices into j for the start of each local row (starts with zero)
3966: .  j - the column indices for each local row (starts with zero)
3967: -  v - optional values in the matrix

3969:    Level: developer

3971:    Notes:
3972:        The i, j, and v arrays ARE copied by this routine into the internal format used by PETSc;
3973:      thus you CANNOT change the matrix entries by changing the values of v[] after you have
3974:      called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays.

3976:        The i and j indices are 0 based, and i indices are indices corresponding to the local j array.

3978:        The format which is used for the sparse matrix input, is equivalent to a
3979:     row-major ordering.. i.e for the following matrix, the input data expected is
3980:     as shown

3982: $        1 0 0
3983: $        2 0 3     P0
3984: $       -------
3985: $        4 5 6     P1
3986: $
3987: $     Process0 [P0]: rows_owned=[0,1]
3988: $        i =  {0,1,3}  [size = nrow+1  = 2+1]
3989: $        j =  {0,0,2}  [size = 3]
3990: $        v =  {1,2,3}  [size = 3]
3991: $
3992: $     Process1 [P1]: rows_owned=[2]
3993: $        i =  {0,3}    [size = nrow+1  = 1+1]
3994: $        j =  {0,1,2}  [size = 3]
3995: $        v =  {4,5,6}  [size = 3]

3997: .keywords: matrix, aij, compressed row, sparse, parallel

3999: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatCreateAIJ(), MATMPIAIJ,
4000:           MatCreateSeqAIJWithArrays(), MatCreateMPIAIJWithSplitArrays()
4001: @*/
4002: PetscErrorCode  MatMPIAIJSetPreallocationCSR(Mat B,const PetscInt i[],const PetscInt j[], const PetscScalar v[])
4003: {

4007:   PetscTryMethod(B,"MatMPIAIJSetPreallocationCSR_C",(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,i,j,v));
4008:   return(0);
4009: }

4011: /*@C
4012:    MatMPIAIJSetPreallocation - Preallocates memory for a sparse parallel matrix in AIJ format
4013:    (the default parallel PETSc format).  For good matrix assembly performance
4014:    the user should preallocate the matrix storage by setting the parameters
4015:    d_nz (or d_nnz) and o_nz (or o_nnz).  By setting these parameters accurately,
4016:    performance can be increased by more than a factor of 50.

4018:    Collective on MPI_Comm

4020:    Input Parameters:
4021: +  B - the matrix
4022: .  d_nz  - number of nonzeros per row in DIAGONAL portion of local submatrix
4023:            (same value is used for all local rows)
4024: .  d_nnz - array containing the number of nonzeros in the various rows of the
4025:            DIAGONAL portion of the local submatrix (possibly different for each row)
4026:            or NULL (PETSC_NULL_INTEGER in Fortran), if d_nz is used to specify the nonzero structure.
4027:            The size of this array is equal to the number of local rows, i.e 'm'.
4028:            For matrices that will be factored, you must leave room for (and set)
4029:            the diagonal entry even if it is zero.
4030: .  o_nz  - number of nonzeros per row in the OFF-DIAGONAL portion of local
4031:            submatrix (same value is used for all local rows).
4032: -  o_nnz - array containing the number of nonzeros in the various rows of the
4033:            OFF-DIAGONAL portion of the local submatrix (possibly different for
4034:            each row) or NULL (PETSC_NULL_INTEGER in Fortran), if o_nz is used to specify the nonzero
4035:            structure. The size of this array is equal to the number
4036:            of local rows, i.e 'm'.

4038:    If the *_nnz parameter is given then the *_nz parameter is ignored

4040:    The AIJ format (also called the Yale sparse matrix format or
4041:    compressed row storage (CSR)), is fully compatible with standard Fortran 77
4042:    storage.  The stored row and column indices begin with zero.
4043:    See Users-Manual: ch_mat for details.

4045:    The parallel matrix is partitioned such that the first m0 rows belong to
4046:    process 0, the next m1 rows belong to process 1, the next m2 rows belong
4047:    to process 2 etc.. where m0,m1,m2... are the input parameter 'm'.

4049:    The DIAGONAL portion of the local submatrix of a processor can be defined
4050:    as the submatrix which is obtained by extraction the part corresponding to
4051:    the rows r1-r2 and columns c1-c2 of the global matrix, where r1 is the
4052:    first row that belongs to the processor, r2 is the last row belonging to
4053:    the this processor, and c1-c2 is range of indices of the local part of a
4054:    vector suitable for applying the matrix to.  This is an mxn matrix.  In the
4055:    common case of a square matrix, the row and column ranges are the same and
4056:    the DIAGONAL part is also square. The remaining portion of the local
4057:    submatrix (mxN) constitute the OFF-DIAGONAL portion.

4059:    If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored.

4061:    You can call MatGetInfo() to get information on how effective the preallocation was;
4062:    for example the fields mallocs,nz_allocated,nz_used,nz_unneeded;
4063:    You can also run with the option -info and look for messages with the string
4064:    malloc in them to see if additional memory allocation was needed.

4066:    Example usage:

4068:    Consider the following 8x8 matrix with 34 non-zero values, that is
4069:    assembled across 3 processors. Lets assume that proc0 owns 3 rows,
4070:    proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown
4071:    as follows:

4073: .vb
4074:             1  2  0  |  0  3  0  |  0  4
4075:     Proc0   0  5  6  |  7  0  0  |  8  0
4076:             9  0 10  | 11  0  0  | 12  0
4077:     -------------------------------------
4078:            13  0 14  | 15 16 17  |  0  0
4079:     Proc1   0 18  0  | 19 20 21  |  0  0
4080:             0  0  0  | 22 23  0  | 24  0
4081:     -------------------------------------
4082:     Proc2  25 26 27  |  0  0 28  | 29  0
4083:            30  0  0  | 31 32 33  |  0 34
4084: .ve

4086:    This can be represented as a collection of submatrices as:

4088: .vb
4089:       A B C
4090:       D E F
4091:       G H I
4092: .ve

4094:    Where the submatrices A,B,C are owned by proc0, D,E,F are
4095:    owned by proc1, G,H,I are owned by proc2.

4097:    The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively.
4098:    The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively.
4099:    The 'M','N' parameters are 8,8, and have the same values on all procs.

4101:    The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are
4102:    submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices
4103:    corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively.
4104:    Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL
4105:    part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ
4106:    matrix, ans [DF] as another SeqAIJ matrix.

4108:    When d_nz, o_nz parameters are specified, d_nz storage elements are
4109:    allocated for every row of the local diagonal submatrix, and o_nz
4110:    storage locations are allocated for every row of the OFF-DIAGONAL submat.
4111:    One way to choose d_nz and o_nz is to use the max nonzerors per local
4112:    rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices.
4113:    In this case, the values of d_nz,o_nz are:
4114: .vb
4115:      proc0 : dnz = 2, o_nz = 2
4116:      proc1 : dnz = 3, o_nz = 2
4117:      proc2 : dnz = 1, o_nz = 4
4118: .ve
4119:    We are allocating m*(d_nz+o_nz) storage locations for every proc. This
4120:    translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10
4121:    for proc3. i.e we are using 12+15+10=37 storage locations to store
4122:    34 values.

4124:    When d_nnz, o_nnz parameters are specified, the storage is specified
4125:    for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices.
4126:    In the above case the values for d_nnz,o_nnz are:
4127: .vb
4128:      proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2]
4129:      proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1]
4130:      proc2: d_nnz = [1,1]   and o_nnz = [4,4]
4131: .ve
4132:    Here the space allocated is sum of all the above values i.e 34, and
4133:    hence pre-allocation is perfect.

4135:    Level: intermediate

4137: .keywords: matrix, aij, compressed row, sparse, parallel

4139: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateAIJ(), MatMPIAIJSetPreallocationCSR(),
4140:           MATMPIAIJ, MatGetInfo(), PetscSplitOwnership()
4141: @*/
4142: PetscErrorCode MatMPIAIJSetPreallocation(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[])
4143: {

4149:   PetscTryMethod(B,"MatMPIAIJSetPreallocation_C",(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[]),(B,d_nz,d_nnz,o_nz,o_nnz));
4150:   return(0);
4151: }

4153: /*@
4154:      MatCreateMPIAIJWithArrays - creates a MPI AIJ matrix using arrays that contain in standard
4155:          CSR format the local rows.

4157:    Collective on MPI_Comm

4159:    Input Parameters:
4160: +  comm - MPI communicator
4161: .  m - number of local rows (Cannot be PETSC_DECIDE)
4162: .  n - This value should be the same as the local size used in creating the
4163:        x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have
4164:        calculated if N is given) For square matrices n is almost always m.
4165: .  M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
4166: .  N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
4167: .   i - row indices
4168: .   j - column indices
4169: -   a - matrix values

4171:    Output Parameter:
4172: .   mat - the matrix

4174:    Level: intermediate

4176:    Notes:
4177:        The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc;
4178:      thus you CANNOT change the matrix entries by changing the values of a[] after you have
4179:      called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays.

4181:        The i and j indices are 0 based, and i indices are indices corresponding to the local j array.

4183:        The format which is used for the sparse matrix input, is equivalent to a
4184:     row-major ordering.. i.e for the following matrix, the input data expected is
4185:     as shown

4187: $        1 0 0
4188: $        2 0 3     P0
4189: $       -------
4190: $        4 5 6     P1
4191: $
4192: $     Process0 [P0]: rows_owned=[0,1]
4193: $        i =  {0,1,3}  [size = nrow+1  = 2+1]
4194: $        j =  {0,0,2}  [size = 3]
4195: $        v =  {1,2,3}  [size = 3]
4196: $
4197: $     Process1 [P1]: rows_owned=[2]
4198: $        i =  {0,3}    [size = nrow+1  = 1+1]
4199: $        j =  {0,1,2}  [size = 3]
4200: $        v =  {4,5,6}  [size = 3]

4202: .keywords: matrix, aij, compressed row, sparse, parallel

4204: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(),
4205:           MATMPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays()
4206: @*/
4207: PetscErrorCode MatCreateMPIAIJWithArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,const PetscInt i[],const PetscInt j[],const PetscScalar a[],Mat *mat)
4208: {

4212:   if (i && i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0");
4213:   if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative");
4214:   MatCreate(comm,mat);
4215:   MatSetSizes(*mat,m,n,M,N);
4216:   /* MatSetBlockSizes(M,bs,cbs); */
4217:   MatSetType(*mat,MATMPIAIJ);
4218:   MatMPIAIJSetPreallocationCSR(*mat,i,j,a);
4219:   return(0);
4220: }

4222: /*@C
4223:    MatCreateAIJ - Creates a sparse parallel matrix in AIJ format
4224:    (the default parallel PETSc format).  For good matrix assembly performance
4225:    the user should preallocate the matrix storage by setting the parameters
4226:    d_nz (or d_nnz) and o_nz (or o_nnz).  By setting these parameters accurately,
4227:    performance can be increased by more than a factor of 50.

4229:    Collective on MPI_Comm

4231:    Input Parameters:
4232: +  comm - MPI communicator
4233: .  m - number of local rows (or PETSC_DECIDE to have calculated if M is given)
4234:            This value should be the same as the local size used in creating the
4235:            y vector for the matrix-vector product y = Ax.
4236: .  n - This value should be the same as the local size used in creating the
4237:        x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have
4238:        calculated if N is given) For square matrices n is almost always m.
4239: .  M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
4240: .  N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
4241: .  d_nz  - number of nonzeros per row in DIAGONAL portion of local submatrix
4242:            (same value is used for all local rows)
4243: .  d_nnz - array containing the number of nonzeros in the various rows of the
4244:            DIAGONAL portion of the local submatrix (possibly different for each row)
4245:            or NULL, if d_nz is used to specify the nonzero structure.
4246:            The size of this array is equal to the number of local rows, i.e 'm'.
4247: .  o_nz  - number of nonzeros per row in the OFF-DIAGONAL portion of local
4248:            submatrix (same value is used for all local rows).
4249: -  o_nnz - array containing the number of nonzeros in the various rows of the
4250:            OFF-DIAGONAL portion of the local submatrix (possibly different for
4251:            each row) or NULL, if o_nz is used to specify the nonzero
4252:            structure. The size of this array is equal to the number
4253:            of local rows, i.e 'm'.

4255:    Output Parameter:
4256: .  A - the matrix

4258:    It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(),
4259:    MatXXXXSetPreallocation() paradgm instead of this routine directly.
4260:    [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation]

4262:    Notes:
4263:    If the *_nnz parameter is given then the *_nz parameter is ignored

4265:    m,n,M,N parameters specify the size of the matrix, and its partitioning across
4266:    processors, while d_nz,d_nnz,o_nz,o_nnz parameters specify the approximate
4267:    storage requirements for this matrix.

4269:    If PETSC_DECIDE or  PETSC_DETERMINE is used for a particular argument on one
4270:    processor than it must be used on all processors that share the object for
4271:    that argument.

4273:    The user MUST specify either the local or global matrix dimensions
4274:    (possibly both).

4276:    The parallel matrix is partitioned across processors such that the
4277:    first m0 rows belong to process 0, the next m1 rows belong to
4278:    process 1, the next m2 rows belong to process 2 etc.. where
4279:    m0,m1,m2,.. are the input parameter 'm'. i.e each processor stores
4280:    values corresponding to [m x N] submatrix.

4282:    The columns are logically partitioned with the n0 columns belonging
4283:    to 0th partition, the next n1 columns belonging to the next
4284:    partition etc.. where n0,n1,n2... are the input parameter 'n'.

4286:    The DIAGONAL portion of the local submatrix on any given processor
4287:    is the submatrix corresponding to the rows and columns m,n
4288:    corresponding to the given processor. i.e diagonal matrix on
4289:    process 0 is [m0 x n0], diagonal matrix on process 1 is [m1 x n1]
4290:    etc. The remaining portion of the local submatrix [m x (N-n)]
4291:    constitute the OFF-DIAGONAL portion. The example below better
4292:    illustrates this concept.

4294:    For a square global matrix we define each processor's diagonal portion
4295:    to be its local rows and the corresponding columns (a square submatrix);
4296:    each processor's off-diagonal portion encompasses the remainder of the
4297:    local matrix (a rectangular submatrix).

4299:    If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored.

4301:    When calling this routine with a single process communicator, a matrix of
4302:    type SEQAIJ is returned.  If a matrix of type MPIAIJ is desired for this
4303:    type of communicator, use the construction mechanism
4304: .vb
4305:      MatCreate(...,&A); MatSetType(A,MATMPIAIJ); MatSetSizes(A, m,n,M,N); MatMPIAIJSetPreallocation(A,...);
4306: .ve

4308: $     MatCreate(...,&A);
4309: $     MatSetType(A,MATMPIAIJ);
4310: $     MatSetSizes(A, m,n,M,N);
4311: $     MatMPIAIJSetPreallocation(A,...);

4313:    By default, this format uses inodes (identical nodes) when possible.
4314:    We search for consecutive rows with the same nonzero structure, thereby
4315:    reusing matrix information to achieve increased efficiency.

4317:    Options Database Keys:
4318: +  -mat_no_inode  - Do not use inodes
4319: -  -mat_inode_limit <limit> - Sets inode limit (max limit=5)



4323:    Example usage:

4325:    Consider the following 8x8 matrix with 34 non-zero values, that is
4326:    assembled across 3 processors. Lets assume that proc0 owns 3 rows,
4327:    proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown
4328:    as follows

4330: .vb
4331:             1  2  0  |  0  3  0  |  0  4
4332:     Proc0   0  5  6  |  7  0  0  |  8  0
4333:             9  0 10  | 11  0  0  | 12  0
4334:     -------------------------------------
4335:            13  0 14  | 15 16 17  |  0  0
4336:     Proc1   0 18  0  | 19 20 21  |  0  0
4337:             0  0  0  | 22 23  0  | 24  0
4338:     -------------------------------------
4339:     Proc2  25 26 27  |  0  0 28  | 29  0
4340:            30  0  0  | 31 32 33  |  0 34
4341: .ve

4343:    This can be represented as a collection of submatrices as

4345: .vb
4346:       A B C
4347:       D E F
4348:       G H I
4349: .ve

4351:    Where the submatrices A,B,C are owned by proc0, D,E,F are
4352:    owned by proc1, G,H,I are owned by proc2.

4354:    The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively.
4355:    The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively.
4356:    The 'M','N' parameters are 8,8, and have the same values on all procs.

4358:    The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are
4359:    submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices
4360:    corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively.
4361:    Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL
4362:    part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ
4363:    matrix, ans [DF] as another SeqAIJ matrix.

4365:    When d_nz, o_nz parameters are specified, d_nz storage elements are
4366:    allocated for every row of the local diagonal submatrix, and o_nz
4367:    storage locations are allocated for every row of the OFF-DIAGONAL submat.
4368:    One way to choose d_nz and o_nz is to use the max nonzerors per local
4369:    rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices.
4370:    In this case, the values of d_nz,o_nz are
4371: .vb
4372:      proc0 : dnz = 2, o_nz = 2
4373:      proc1 : dnz = 3, o_nz = 2
4374:      proc2 : dnz = 1, o_nz = 4
4375: .ve
4376:    We are allocating m*(d_nz+o_nz) storage locations for every proc. This
4377:    translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10
4378:    for proc3. i.e we are using 12+15+10=37 storage locations to store
4379:    34 values.

4381:    When d_nnz, o_nnz parameters are specified, the storage is specified
4382:    for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices.
4383:    In the above case the values for d_nnz,o_nnz are
4384: .vb
4385:      proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2]
4386:      proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1]
4387:      proc2: d_nnz = [1,1]   and o_nnz = [4,4]
4388: .ve
4389:    Here the space allocated is sum of all the above values i.e 34, and
4390:    hence pre-allocation is perfect.

4392:    Level: intermediate

4394: .keywords: matrix, aij, compressed row, sparse, parallel

4396: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(),
4397:           MATMPIAIJ, MatCreateMPIAIJWithArrays()
4398: @*/
4399: PetscErrorCode  MatCreateAIJ(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[],Mat *A)
4400: {
4402:   PetscMPIInt    size;

4405:   MatCreate(comm,A);
4406:   MatSetSizes(*A,m,n,M,N);
4407:   MPI_Comm_size(comm,&size);
4408:   if (size > 1) {
4409:     MatSetType(*A,MATMPIAIJ);
4410:     MatMPIAIJSetPreallocation(*A,d_nz,d_nnz,o_nz,o_nnz);
4411:   } else {
4412:     MatSetType(*A,MATSEQAIJ);
4413:     MatSeqAIJSetPreallocation(*A,d_nz,d_nnz);
4414:   }
4415:   return(0);
4416: }

4418: PetscErrorCode MatMPIAIJGetSeqAIJ(Mat A,Mat *Ad,Mat *Ao,const PetscInt *colmap[])
4419: {
4420:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;
4421:   PetscBool      flg;

4425:   PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&flg);
4426:   if (!flg) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"This function requires a MATMPIAIJ matrix as input");
4427:   if (Ad)     *Ad     = a->A;
4428:   if (Ao)     *Ao     = a->B;
4429:   if (colmap) *colmap = a->garray;
4430:   return(0);
4431: }

4433: PetscErrorCode MatCreateMPIMatConcatenateSeqMat_MPIAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat)
4434: {
4436:   PetscInt       m,N,i,rstart,nnz,Ii;
4437:   PetscInt       *indx;
4438:   PetscScalar    *values;

4441:   MatGetSize(inmat,&m,&N);
4442:   if (scall == MAT_INITIAL_MATRIX) { /* symbolic phase */
4443:     PetscInt       *dnz,*onz,sum,bs,cbs;

4445:     if (n == PETSC_DECIDE) {
4446:       PetscSplitOwnership(comm,&n,&N);
4447:     }
4448:     /* Check sum(n) = N */
4449:     MPIU_Allreduce(&n,&sum,1,MPIU_INT,MPI_SUM,comm);
4450:     if (sum != N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Sum of local columns %D != global columns %D",sum,N);

4452:     MPI_Scan(&m, &rstart,1,MPIU_INT,MPI_SUM,comm);
4453:     rstart -= m;

4455:     MatPreallocateInitialize(comm,m,n,dnz,onz);
4456:     for (i=0; i<m; i++) {
4457:       MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);
4458:       MatPreallocateSet(i+rstart,nnz,indx,dnz,onz);
4459:       MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);
4460:     }

4462:     MatCreate(comm,outmat);
4463:     MatSetSizes(*outmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);
4464:     MatGetBlockSizes(inmat,&bs,&cbs);
4465:     MatSetBlockSizes(*outmat,bs,cbs);
4466:     MatSetType(*outmat,MATAIJ);
4467:     MatSeqAIJSetPreallocation(*outmat,0,dnz);
4468:     MatMPIAIJSetPreallocation(*outmat,0,dnz,0,onz);
4469:     MatPreallocateFinalize(dnz,onz);
4470:   }

4472:   /* numeric phase */
4473:   MatGetOwnershipRange(*outmat,&rstart,NULL);
4474:   for (i=0; i<m; i++) {
4475:     MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,&values);
4476:     Ii   = i + rstart;
4477:     MatSetValues(*outmat,1,&Ii,nnz,indx,values,INSERT_VALUES);
4478:     MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,&values);
4479:   }
4480:   MatAssemblyBegin(*outmat,MAT_FINAL_ASSEMBLY);
4481:   MatAssemblyEnd(*outmat,MAT_FINAL_ASSEMBLY);
4482:   return(0);
4483: }

4485: PetscErrorCode MatFileSplit(Mat A,char *outfile)
4486: {
4487:   PetscErrorCode    ierr;
4488:   PetscMPIInt       rank;
4489:   PetscInt          m,N,i,rstart,nnz;
4490:   size_t            len;
4491:   const PetscInt    *indx;
4492:   PetscViewer       out;
4493:   char              *name;
4494:   Mat               B;
4495:   const PetscScalar *values;

4498:   MatGetLocalSize(A,&m,0);
4499:   MatGetSize(A,0,&N);
4500:   /* Should this be the type of the diagonal block of A? */
4501:   MatCreate(PETSC_COMM_SELF,&B);
4502:   MatSetSizes(B,m,N,m,N);
4503:   MatSetBlockSizesFromMats(B,A,A);
4504:   MatSetType(B,MATSEQAIJ);
4505:   MatSeqAIJSetPreallocation(B,0,NULL);
4506:   MatGetOwnershipRange(A,&rstart,0);
4507:   for (i=0; i<m; i++) {
4508:     MatGetRow(A,i+rstart,&nnz,&indx,&values);
4509:     MatSetValues(B,1,&i,nnz,indx,values,INSERT_VALUES);
4510:     MatRestoreRow(A,i+rstart,&nnz,&indx,&values);
4511:   }
4512:   MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
4513:   MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);

4515:   MPI_Comm_rank(PetscObjectComm((PetscObject)A),&rank);
4516:   PetscStrlen(outfile,&len);
4517:   PetscMalloc1(len+5,&name);
4518:   sprintf(name,"%s.%d",outfile,rank);
4519:   PetscViewerBinaryOpen(PETSC_COMM_SELF,name,FILE_MODE_APPEND,&out);
4520:   PetscFree(name);
4521:   MatView(B,out);
4522:   PetscViewerDestroy(&out);
4523:   MatDestroy(&B);
4524:   return(0);
4525: }

4527: PetscErrorCode MatDestroy_MPIAIJ_SeqsToMPI(Mat A)
4528: {
4529:   PetscErrorCode      ierr;
4530:   Mat_Merge_SeqsToMPI *merge;
4531:   PetscContainer      container;

4534:   PetscObjectQuery((PetscObject)A,"MatMergeSeqsToMPI",(PetscObject*)&container);
4535:   if (container) {
4536:     PetscContainerGetPointer(container,(void**)&merge);
4537:     PetscFree(merge->id_r);
4538:     PetscFree(merge->len_s);
4539:     PetscFree(merge->len_r);
4540:     PetscFree(merge->bi);
4541:     PetscFree(merge->bj);
4542:     PetscFree(merge->buf_ri[0]);
4543:     PetscFree(merge->buf_ri);
4544:     PetscFree(merge->buf_rj[0]);
4545:     PetscFree(merge->buf_rj);
4546:     PetscFree(merge->coi);
4547:     PetscFree(merge->coj);
4548:     PetscFree(merge->owners_co);
4549:     PetscLayoutDestroy(&merge->rowmap);
4550:     PetscFree(merge);
4551:     PetscObjectCompose((PetscObject)A,"MatMergeSeqsToMPI",0);
4552:   }
4553:   MatDestroy_MPIAIJ(A);
4554:   return(0);
4555: }

4557:  #include <../src/mat/utils/freespace.h>
4558:  #include <petscbt.h>

4560: PetscErrorCode MatCreateMPIAIJSumSeqAIJNumeric(Mat seqmat,Mat mpimat)
4561: {
4562:   PetscErrorCode      ierr;
4563:   MPI_Comm            comm;
4564:   Mat_SeqAIJ          *a  =(Mat_SeqAIJ*)seqmat->data;
4565:   PetscMPIInt         size,rank,taga,*len_s;
4566:   PetscInt            N=mpimat->cmap->N,i,j,*owners,*ai=a->i,*aj;
4567:   PetscInt            proc,m;
4568:   PetscInt            **buf_ri,**buf_rj;
4569:   PetscInt            k,anzi,*bj_i,*bi,*bj,arow,bnzi,nextaj;
4570:   PetscInt            nrows,**buf_ri_k,**nextrow,**nextai;
4571:   MPI_Request         *s_waits,*r_waits;
4572:   MPI_Status          *status;
4573:   MatScalar           *aa=a->a;
4574:   MatScalar           **abuf_r,*ba_i;
4575:   Mat_Merge_SeqsToMPI *merge;
4576:   PetscContainer      container;

4579:   PetscObjectGetComm((PetscObject)mpimat,&comm);
4580:   PetscLogEventBegin(MAT_Seqstompinum,seqmat,0,0,0);

4582:   MPI_Comm_size(comm,&size);
4583:   MPI_Comm_rank(comm,&rank);

4585:   PetscObjectQuery((PetscObject)mpimat,"MatMergeSeqsToMPI",(PetscObject*)&container);
4586:   PetscContainerGetPointer(container,(void**)&merge);

4588:   bi     = merge->bi;
4589:   bj     = merge->bj;
4590:   buf_ri = merge->buf_ri;
4591:   buf_rj = merge->buf_rj;

4593:   PetscMalloc1(size,&status);
4594:   owners = merge->rowmap->range;
4595:   len_s  = merge->len_s;

4597:   /* send and recv matrix values */
4598:   /*-----------------------------*/
4599:   PetscObjectGetNewTag((PetscObject)mpimat,&taga);
4600:   PetscPostIrecvScalar(comm,taga,merge->nrecv,merge->id_r,merge->len_r,&abuf_r,&r_waits);

4602:   PetscMalloc1(merge->nsend+1,&s_waits);
4603:   for (proc=0,k=0; proc<size; proc++) {
4604:     if (!len_s[proc]) continue;
4605:     i    = owners[proc];
4606:     MPI_Isend(aa+ai[i],len_s[proc],MPIU_MATSCALAR,proc,taga,comm,s_waits+k);
4607:     k++;
4608:   }

4610:   if (merge->nrecv) {MPI_Waitall(merge->nrecv,r_waits,status);}
4611:   if (merge->nsend) {MPI_Waitall(merge->nsend,s_waits,status);}
4612:   PetscFree(status);

4614:   PetscFree(s_waits);
4615:   PetscFree(r_waits);

4617:   /* insert mat values of mpimat */
4618:   /*----------------------------*/
4619:   PetscMalloc1(N,&ba_i);
4620:   PetscMalloc3(merge->nrecv,&buf_ri_k,merge->nrecv,&nextrow,merge->nrecv,&nextai);

4622:   for (k=0; k<merge->nrecv; k++) {
4623:     buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */
4624:     nrows       = *(buf_ri_k[k]);
4625:     nextrow[k]  = buf_ri_k[k]+1;  /* next row number of k-th recved i-structure */
4626:     nextai[k]   = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure  */
4627:   }

4629:   /* set values of ba */
4630:   m = merge->rowmap->n;
4631:   for (i=0; i<m; i++) {
4632:     arow = owners[rank] + i;
4633:     bj_i = bj+bi[i];  /* col indices of the i-th row of mpimat */
4634:     bnzi = bi[i+1] - bi[i];
4635:     PetscMemzero(ba_i,bnzi*sizeof(PetscScalar));

4637:     /* add local non-zero vals of this proc's seqmat into ba */
4638:     anzi   = ai[arow+1] - ai[arow];
4639:     aj     = a->j + ai[arow];
4640:     aa     = a->a + ai[arow];
4641:     nextaj = 0;
4642:     for (j=0; nextaj<anzi; j++) {
4643:       if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */
4644:         ba_i[j] += aa[nextaj++];
4645:       }
4646:     }

4648:     /* add received vals into ba */
4649:     for (k=0; k<merge->nrecv; k++) { /* k-th received message */
4650:       /* i-th row */
4651:       if (i == *nextrow[k]) {
4652:         anzi   = *(nextai[k]+1) - *nextai[k];
4653:         aj     = buf_rj[k] + *(nextai[k]);
4654:         aa     = abuf_r[k] + *(nextai[k]);
4655:         nextaj = 0;
4656:         for (j=0; nextaj<anzi; j++) {
4657:           if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */
4658:             ba_i[j] += aa[nextaj++];
4659:           }
4660:         }
4661:         nextrow[k]++; nextai[k]++;
4662:       }
4663:     }
4664:     MatSetValues(mpimat,1,&arow,bnzi,bj_i,ba_i,INSERT_VALUES);
4665:   }
4666:   MatAssemblyBegin(mpimat,MAT_FINAL_ASSEMBLY);
4667:   MatAssemblyEnd(mpimat,MAT_FINAL_ASSEMBLY);

4669:   PetscFree(abuf_r[0]);
4670:   PetscFree(abuf_r);
4671:   PetscFree(ba_i);
4672:   PetscFree3(buf_ri_k,nextrow,nextai);
4673:   PetscLogEventEnd(MAT_Seqstompinum,seqmat,0,0,0);
4674:   return(0);
4675: }

4677: PetscErrorCode  MatCreateMPIAIJSumSeqAIJSymbolic(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,Mat *mpimat)
4678: {
4679:   PetscErrorCode      ierr;
4680:   Mat                 B_mpi;
4681:   Mat_SeqAIJ          *a=(Mat_SeqAIJ*)seqmat->data;
4682:   PetscMPIInt         size,rank,tagi,tagj,*len_s,*len_si,*len_ri;
4683:   PetscInt            **buf_rj,**buf_ri,**buf_ri_k;
4684:   PetscInt            M=seqmat->rmap->n,N=seqmat->cmap->n,i,*owners,*ai=a->i,*aj=a->j;
4685:   PetscInt            len,proc,*dnz,*onz,bs,cbs;
4686:   PetscInt            k,anzi,*bi,*bj,*lnk,nlnk,arow,bnzi,nspacedouble=0;
4687:   PetscInt            nrows,*buf_s,*buf_si,*buf_si_i,**nextrow,**nextai;
4688:   MPI_Request         *si_waits,*sj_waits,*ri_waits,*rj_waits;
4689:   MPI_Status          *status;
4690:   PetscFreeSpaceList  free_space=NULL,current_space=NULL;
4691:   PetscBT             lnkbt;
4692:   Mat_Merge_SeqsToMPI *merge;
4693:   PetscContainer      container;

4696:   PetscLogEventBegin(MAT_Seqstompisym,seqmat,0,0,0);

4698:   /* make sure it is a PETSc comm */
4699:   PetscCommDuplicate(comm,&comm,NULL);
4700:   MPI_Comm_size(comm,&size);
4701:   MPI_Comm_rank(comm,&rank);

4703:   PetscNew(&merge);
4704:   PetscMalloc1(size,&status);

4706:   /* determine row ownership */
4707:   /*---------------------------------------------------------*/
4708:   PetscLayoutCreate(comm,&merge->rowmap);
4709:   PetscLayoutSetLocalSize(merge->rowmap,m);
4710:   PetscLayoutSetSize(merge->rowmap,M);
4711:   PetscLayoutSetBlockSize(merge->rowmap,1);
4712:   PetscLayoutSetUp(merge->rowmap);
4713:   PetscMalloc1(size,&len_si);
4714:   PetscMalloc1(size,&merge->len_s);

4716:   m      = merge->rowmap->n;
4717:   owners = merge->rowmap->range;

4719:   /* determine the number of messages to send, their lengths */
4720:   /*---------------------------------------------------------*/
4721:   len_s = merge->len_s;

4723:   len          = 0; /* length of buf_si[] */
4724:   merge->nsend = 0;
4725:   for (proc=0; proc<size; proc++) {
4726:     len_si[proc] = 0;
4727:     if (proc == rank) {
4728:       len_s[proc] = 0;
4729:     } else {
4730:       len_si[proc] = owners[proc+1] - owners[proc] + 1;
4731:       len_s[proc]  = ai[owners[proc+1]] - ai[owners[proc]]; /* num of rows to be sent to [proc] */
4732:     }
4733:     if (len_s[proc]) {
4734:       merge->nsend++;
4735:       nrows = 0;
4736:       for (i=owners[proc]; i<owners[proc+1]; i++) {
4737:         if (ai[i+1] > ai[i]) nrows++;
4738:       }
4739:       len_si[proc] = 2*(nrows+1);
4740:       len         += len_si[proc];
4741:     }
4742:   }

4744:   /* determine the number and length of messages to receive for ij-structure */
4745:   /*-------------------------------------------------------------------------*/
4746:   PetscGatherNumberOfMessages(comm,NULL,len_s,&merge->nrecv);
4747:   PetscGatherMessageLengths2(comm,merge->nsend,merge->nrecv,len_s,len_si,&merge->id_r,&merge->len_r,&len_ri);

4749:   /* post the Irecv of j-structure */
4750:   /*-------------------------------*/
4751:   PetscCommGetNewTag(comm,&tagj);
4752:   PetscPostIrecvInt(comm,tagj,merge->nrecv,merge->id_r,merge->len_r,&buf_rj,&rj_waits);

4754:   /* post the Isend of j-structure */
4755:   /*--------------------------------*/
4756:   PetscMalloc2(merge->nsend,&si_waits,merge->nsend,&sj_waits);

4758:   for (proc=0, k=0; proc<size; proc++) {
4759:     if (!len_s[proc]) continue;
4760:     i    = owners[proc];
4761:     MPI_Isend(aj+ai[i],len_s[proc],MPIU_INT,proc,tagj,comm,sj_waits+k);
4762:     k++;
4763:   }

4765:   /* receives and sends of j-structure are complete */
4766:   /*------------------------------------------------*/
4767:   if (merge->nrecv) {MPI_Waitall(merge->nrecv,rj_waits,status);}
4768:   if (merge->nsend) {MPI_Waitall(merge->nsend,sj_waits,status);}

4770:   /* send and recv i-structure */
4771:   /*---------------------------*/
4772:   PetscCommGetNewTag(comm,&tagi);
4773:   PetscPostIrecvInt(comm,tagi,merge->nrecv,merge->id_r,len_ri,&buf_ri,&ri_waits);

4775:   PetscMalloc1(len+1,&buf_s);
4776:   buf_si = buf_s;  /* points to the beginning of k-th msg to be sent */
4777:   for (proc=0,k=0; proc<size; proc++) {
4778:     if (!len_s[proc]) continue;
4779:     /* form outgoing message for i-structure:
4780:          buf_si[0]:                 nrows to be sent
4781:                [1:nrows]:           row index (global)
4782:                [nrows+1:2*nrows+1]: i-structure index
4783:     */
4784:     /*-------------------------------------------*/
4785:     nrows       = len_si[proc]/2 - 1;
4786:     buf_si_i    = buf_si + nrows+1;
4787:     buf_si[0]   = nrows;
4788:     buf_si_i[0] = 0;
4789:     nrows       = 0;
4790:     for (i=owners[proc]; i<owners[proc+1]; i++) {
4791:       anzi = ai[i+1] - ai[i];
4792:       if (anzi) {
4793:         buf_si_i[nrows+1] = buf_si_i[nrows] + anzi; /* i-structure */
4794:         buf_si[nrows+1]   = i-owners[proc]; /* local row index */
4795:         nrows++;
4796:       }
4797:     }
4798:     MPI_Isend(buf_si,len_si[proc],MPIU_INT,proc,tagi,comm,si_waits+k);
4799:     k++;
4800:     buf_si += len_si[proc];
4801:   }

4803:   if (merge->nrecv) {MPI_Waitall(merge->nrecv,ri_waits,status);}
4804:   if (merge->nsend) {MPI_Waitall(merge->nsend,si_waits,status);}

4806:   PetscInfo2(seqmat,"nsend: %D, nrecv: %D\n",merge->nsend,merge->nrecv);
4807:   for (i=0; i<merge->nrecv; i++) {
4808:     PetscInfo3(seqmat,"recv len_ri=%D, len_rj=%D from [%D]\n",len_ri[i],merge->len_r[i],merge->id_r[i]);
4809:   }

4811:   PetscFree(len_si);
4812:   PetscFree(len_ri);
4813:   PetscFree(rj_waits);
4814:   PetscFree2(si_waits,sj_waits);
4815:   PetscFree(ri_waits);
4816:   PetscFree(buf_s);
4817:   PetscFree(status);

4819:   /* compute a local seq matrix in each processor */
4820:   /*----------------------------------------------*/
4821:   /* allocate bi array and free space for accumulating nonzero column info */
4822:   PetscMalloc1(m+1,&bi);
4823:   bi[0] = 0;

4825:   /* create and initialize a linked list */
4826:   nlnk = N+1;
4827:   PetscLLCreate(N,N,nlnk,lnk,lnkbt);

4829:   /* initial FreeSpace size is 2*(num of local nnz(seqmat)) */
4830:   len  = ai[owners[rank+1]] - ai[owners[rank]];
4831:   PetscFreeSpaceGet(PetscIntMultTruncate(2,len)+1,&free_space);

4833:   current_space = free_space;

4835:   /* determine symbolic info for each local row */
4836:   PetscMalloc3(merge->nrecv,&buf_ri_k,merge->nrecv,&nextrow,merge->nrecv,&nextai);

4838:   for (k=0; k<merge->nrecv; k++) {
4839:     buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */
4840:     nrows       = *buf_ri_k[k];
4841:     nextrow[k]  = buf_ri_k[k] + 1;  /* next row number of k-th recved i-structure */
4842:     nextai[k]   = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure  */
4843:   }

4845:   MatPreallocateInitialize(comm,m,n,dnz,onz);
4846:   len  = 0;
4847:   for (i=0; i<m; i++) {
4848:     bnzi = 0;
4849:     /* add local non-zero cols of this proc's seqmat into lnk */
4850:     arow  = owners[rank] + i;
4851:     anzi  = ai[arow+1] - ai[arow];
4852:     aj    = a->j + ai[arow];
4853:     PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);
4854:     bnzi += nlnk;
4855:     /* add received col data into lnk */
4856:     for (k=0; k<merge->nrecv; k++) { /* k-th received message */
4857:       if (i == *nextrow[k]) { /* i-th row */
4858:         anzi  = *(nextai[k]+1) - *nextai[k];
4859:         aj    = buf_rj[k] + *nextai[k];
4860:         PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);
4861:         bnzi += nlnk;
4862:         nextrow[k]++; nextai[k]++;
4863:       }
4864:     }
4865:     if (len < bnzi) len = bnzi;  /* =max(bnzi) */

4867:     /* if free space is not available, make more free space */
4868:     if (current_space->local_remaining<bnzi) {
4869:       PetscFreeSpaceGet(PetscIntSumTruncate(bnzi,current_space->total_array_size),&current_space);
4870:       nspacedouble++;
4871:     }
4872:     /* copy data into free space, then initialize lnk */
4873:     PetscLLClean(N,N,bnzi,lnk,current_space->array,lnkbt);
4874:     MatPreallocateSet(i+owners[rank],bnzi,current_space->array,dnz,onz);

4876:     current_space->array           += bnzi;
4877:     current_space->local_used      += bnzi;
4878:     current_space->local_remaining -= bnzi;

4880:     bi[i+1] = bi[i] + bnzi;
4881:   }

4883:   PetscFree3(buf_ri_k,nextrow,nextai);

4885:   PetscMalloc1(bi[m]+1,&bj);
4886:   PetscFreeSpaceContiguous(&free_space,bj);
4887:   PetscLLDestroy(lnk,lnkbt);

4889:   /* create symbolic parallel matrix B_mpi */
4890:   /*---------------------------------------*/
4891:   MatGetBlockSizes(seqmat,&bs,&cbs);
4892:   MatCreate(comm,&B_mpi);
4893:   if (n==PETSC_DECIDE) {
4894:     MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,N);
4895:   } else {
4896:     MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,PETSC_DETERMINE);
4897:   }
4898:   MatSetBlockSizes(B_mpi,bs,cbs);
4899:   MatSetType(B_mpi,MATMPIAIJ);
4900:   MatMPIAIJSetPreallocation(B_mpi,0,dnz,0,onz);
4901:   MatPreallocateFinalize(dnz,onz);
4902:   MatSetOption(B_mpi,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_FALSE);

4904:   /* B_mpi is not ready for use - assembly will be done by MatCreateMPIAIJSumSeqAIJNumeric() */
4905:   B_mpi->assembled    = PETSC_FALSE;
4906:   B_mpi->ops->destroy = MatDestroy_MPIAIJ_SeqsToMPI;
4907:   merge->bi           = bi;
4908:   merge->bj           = bj;
4909:   merge->buf_ri       = buf_ri;
4910:   merge->buf_rj       = buf_rj;
4911:   merge->coi          = NULL;
4912:   merge->coj          = NULL;
4913:   merge->owners_co    = NULL;

4915:   PetscCommDestroy(&comm);

4917:   /* attach the supporting struct to B_mpi for reuse */
4918:   PetscContainerCreate(PETSC_COMM_SELF,&container);
4919:   PetscContainerSetPointer(container,merge);
4920:   PetscObjectCompose((PetscObject)B_mpi,"MatMergeSeqsToMPI",(PetscObject)container);
4921:   PetscContainerDestroy(&container);
4922:   *mpimat = B_mpi;

4924:   PetscLogEventEnd(MAT_Seqstompisym,seqmat,0,0,0);
4925:   return(0);
4926: }

4928: /*@C
4929:       MatCreateMPIAIJSumSeqAIJ - Creates a MATMPIAIJ matrix by adding sequential
4930:                  matrices from each processor

4932:     Collective on MPI_Comm

4934:    Input Parameters:
4935: +    comm - the communicators the parallel matrix will live on
4936: .    seqmat - the input sequential matrices
4937: .    m - number of local rows (or PETSC_DECIDE)
4938: .    n - number of local columns (or PETSC_DECIDE)
4939: -    scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX

4941:    Output Parameter:
4942: .    mpimat - the parallel matrix generated

4944:     Level: advanced

4946:    Notes:
4947:      The dimensions of the sequential matrix in each processor MUST be the same.
4948:      The input seqmat is included into the container "Mat_Merge_SeqsToMPI", and will be
4949:      destroyed when mpimat is destroyed. Call PetscObjectQuery() to access seqmat.
4950: @*/
4951: PetscErrorCode MatCreateMPIAIJSumSeqAIJ(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,MatReuse scall,Mat *mpimat)
4952: {
4954:   PetscMPIInt    size;

4957:   MPI_Comm_size(comm,&size);
4958:   if (size == 1) {
4959:     PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);
4960:     if (scall == MAT_INITIAL_MATRIX) {
4961:       MatDuplicate(seqmat,MAT_COPY_VALUES,mpimat);
4962:     } else {
4963:       MatCopy(seqmat,*mpimat,SAME_NONZERO_PATTERN);
4964:     }
4965:     PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);
4966:     return(0);
4967:   }
4968:   PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);
4969:   if (scall == MAT_INITIAL_MATRIX) {
4970:     MatCreateMPIAIJSumSeqAIJSymbolic(comm,seqmat,m,n,mpimat);
4971:   }
4972:   MatCreateMPIAIJSumSeqAIJNumeric(seqmat,*mpimat);
4973:   PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);
4974:   return(0);
4975: }

4977: /*@
4978:      MatMPIAIJGetLocalMat - Creates a SeqAIJ from a MATMPIAIJ matrix by taking all its local rows and putting them into a sequential matrix with
4979:           mlocal rows and n columns. Where mlocal is the row count obtained with MatGetLocalSize() and n is the global column count obtained
4980:           with MatGetSize()

4982:     Not Collective

4984:    Input Parameters:
4985: +    A - the matrix
4986: .    scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX

4988:    Output Parameter:
4989: .    A_loc - the local sequential matrix generated

4991:     Level: developer

4993: .seealso: MatGetOwnerShipRange(), MatMPIAIJGetLocalMatCondensed()

4995: @*/
4996: PetscErrorCode MatMPIAIJGetLocalMat(Mat A,MatReuse scall,Mat *A_loc)
4997: {
4999:   Mat_MPIAIJ     *mpimat=(Mat_MPIAIJ*)A->data;
5000:   Mat_SeqAIJ     *mat,*a,*b;
5001:   PetscInt       *ai,*aj,*bi,*bj,*cmap=mpimat->garray;
5002:   MatScalar      *aa,*ba,*cam;
5003:   PetscScalar    *ca;
5004:   PetscInt       am=A->rmap->n,i,j,k,cstart=A->cmap->rstart;
5005:   PetscInt       *ci,*cj,col,ncols_d,ncols_o,jo;
5006:   PetscBool      match;
5007:   MPI_Comm       comm;
5008:   PetscMPIInt    size;

5011:   PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);
5012:   if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MATMPIAIJ matrix as input");
5013:   PetscObjectGetComm((PetscObject)A,&comm);
5014:   MPI_Comm_size(comm,&size);
5015:   if (size == 1 && scall == MAT_REUSE_MATRIX) return(0);

5017:   PetscLogEventBegin(MAT_Getlocalmat,A,0,0,0);
5018:   a = (Mat_SeqAIJ*)(mpimat->A)->data;
5019:   b = (Mat_SeqAIJ*)(mpimat->B)->data;
5020:   ai = a->i; aj = a->j; bi = b->i; bj = b->j;
5021:   aa = a->a; ba = b->a;
5022:   if (scall == MAT_INITIAL_MATRIX) {
5023:     if (size == 1) {
5024:       MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ai,aj,aa,A_loc);
5025:       return(0);
5026:     }

5028:     PetscMalloc1(1+am,&ci);
5029:     ci[0] = 0;
5030:     for (i=0; i<am; i++) {
5031:       ci[i+1] = ci[i] + (ai[i+1] - ai[i]) + (bi[i+1] - bi[i]);
5032:     }
5033:     PetscMalloc1(1+ci[am],&cj);
5034:     PetscMalloc1(1+ci[am],&ca);
5035:     k    = 0;
5036:     for (i=0; i<am; i++) {
5037:       ncols_o = bi[i+1] - bi[i];
5038:       ncols_d = ai[i+1] - ai[i];
5039:       /* off-diagonal portion of A */
5040:       for (jo=0; jo<ncols_o; jo++) {
5041:         col = cmap[*bj];
5042:         if (col >= cstart) break;
5043:         cj[k]   = col; bj++;
5044:         ca[k++] = *ba++;
5045:       }
5046:       /* diagonal portion of A */
5047:       for (j=0; j<ncols_d; j++) {
5048:         cj[k]   = cstart + *aj++;
5049:         ca[k++] = *aa++;
5050:       }
5051:       /* off-diagonal portion of A */
5052:       for (j=jo; j<ncols_o; j++) {
5053:         cj[k]   = cmap[*bj++];
5054:         ca[k++] = *ba++;
5055:       }
5056:     }
5057:     /* put together the new matrix */
5058:     MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ci,cj,ca,A_loc);
5059:     /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */
5060:     /* Since these are PETSc arrays, change flags to free them as necessary. */
5061:     mat          = (Mat_SeqAIJ*)(*A_loc)->data;
5062:     mat->free_a  = PETSC_TRUE;
5063:     mat->free_ij = PETSC_TRUE;
5064:     mat->nonew   = 0;
5065:   } else if (scall == MAT_REUSE_MATRIX) {
5066:     mat=(Mat_SeqAIJ*)(*A_loc)->data;
5067:     ci = mat->i; cj = mat->j; cam = mat->a;
5068:     for (i=0; i<am; i++) {
5069:       /* off-diagonal portion of A */
5070:       ncols_o = bi[i+1] - bi[i];
5071:       for (jo=0; jo<ncols_o; jo++) {
5072:         col = cmap[*bj];
5073:         if (col >= cstart) break;
5074:         *cam++ = *ba++; bj++;
5075:       }
5076:       /* diagonal portion of A */
5077:       ncols_d = ai[i+1] - ai[i];
5078:       for (j=0; j<ncols_d; j++) *cam++ = *aa++;
5079:       /* off-diagonal portion of A */
5080:       for (j=jo; j<ncols_o; j++) {
5081:         *cam++ = *ba++; bj++;
5082:       }
5083:     }
5084:   } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Invalid MatReuse %d",(int)scall);
5085:   PetscLogEventEnd(MAT_Getlocalmat,A,0,0,0);
5086:   return(0);
5087: }

5089: /*@C
5090:      MatMPIAIJGetLocalMatCondensed - Creates a SeqAIJ matrix from an MATMPIAIJ matrix by taking all its local rows and NON-ZERO columns

5092:     Not Collective

5094:    Input Parameters:
5095: +    A - the matrix
5096: .    scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX
5097: -    row, col - index sets of rows and columns to extract (or NULL)

5099:    Output Parameter:
5100: .    A_loc - the local sequential matrix generated

5102:     Level: developer

5104: .seealso: MatGetOwnershipRange(), MatMPIAIJGetLocalMat()

5106: @*/
5107: PetscErrorCode MatMPIAIJGetLocalMatCondensed(Mat A,MatReuse scall,IS *row,IS *col,Mat *A_loc)
5108: {
5109:   Mat_MPIAIJ     *a=(Mat_MPIAIJ*)A->data;
5111:   PetscInt       i,start,end,ncols,nzA,nzB,*cmap,imark,*idx;
5112:   IS             isrowa,iscola;
5113:   Mat            *aloc;
5114:   PetscBool      match;

5117:   PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);
5118:   if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MATMPIAIJ matrix as input");
5119:   PetscLogEventBegin(MAT_Getlocalmatcondensed,A,0,0,0);
5120:   if (!row) {
5121:     start = A->rmap->rstart; end = A->rmap->rend;
5122:     ISCreateStride(PETSC_COMM_SELF,end-start,start,1,&isrowa);
5123:   } else {
5124:     isrowa = *row;
5125:   }
5126:   if (!col) {
5127:     start = A->cmap->rstart;
5128:     cmap  = a->garray;
5129:     nzA   = a->A->cmap->n;
5130:     nzB   = a->B->cmap->n;
5131:     PetscMalloc1(nzA+nzB, &idx);
5132:     ncols = 0;
5133:     for (i=0; i<nzB; i++) {
5134:       if (cmap[i] < start) idx[ncols++] = cmap[i];
5135:       else break;
5136:     }
5137:     imark = i;
5138:     for (i=0; i<nzA; i++) idx[ncols++] = start + i;
5139:     for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i];
5140:     ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&iscola);
5141:   } else {
5142:     iscola = *col;
5143:   }
5144:   if (scall != MAT_INITIAL_MATRIX) {
5145:     PetscMalloc1(1,&aloc);
5146:     aloc[0] = *A_loc;
5147:   }
5148:   MatCreateSubMatrices(A,1,&isrowa,&iscola,scall,&aloc);
5149:   if (!col) { /* attach global id of condensed columns */
5150:     PetscObjectCompose((PetscObject)aloc[0],"_petsc_GetLocalMatCondensed_iscol",(PetscObject)iscola);
5151:   }
5152:   *A_loc = aloc[0];
5153:   PetscFree(aloc);
5154:   if (!row) {
5155:     ISDestroy(&isrowa);
5156:   }
5157:   if (!col) {
5158:     ISDestroy(&iscola);
5159:   }
5160:   PetscLogEventEnd(MAT_Getlocalmatcondensed,A,0,0,0);
5161:   return(0);
5162: }

5164: /*@C
5165:     MatGetBrowsOfAcols - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns of local A

5167:     Collective on Mat

5169:    Input Parameters:
5170: +    A,B - the matrices in mpiaij format
5171: .    scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX
5172: -    rowb, colb - index sets of rows and columns of B to extract (or NULL)

5174:    Output Parameter:
5175: +    rowb, colb - index sets of rows and columns of B to extract
5176: -    B_seq - the sequential matrix generated

5178:     Level: developer

5180: @*/
5181: PetscErrorCode MatGetBrowsOfAcols(Mat A,Mat B,MatReuse scall,IS *rowb,IS *colb,Mat *B_seq)
5182: {
5183:   Mat_MPIAIJ     *a=(Mat_MPIAIJ*)A->data;
5185:   PetscInt       *idx,i,start,ncols,nzA,nzB,*cmap,imark;
5186:   IS             isrowb,iscolb;
5187:   Mat            *bseq=NULL;

5190:   if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) {
5191:     SETERRQ4(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Matrix local dimensions are incompatible, (%D, %D) != (%D,%D)",A->cmap->rstart,A->cmap->rend,B->rmap->rstart,B->rmap->rend);
5192:   }
5193:   PetscLogEventBegin(MAT_GetBrowsOfAcols,A,B,0,0);

5195:   if (scall == MAT_INITIAL_MATRIX) {
5196:     start = A->cmap->rstart;
5197:     cmap  = a->garray;
5198:     nzA   = a->A->cmap->n;
5199:     nzB   = a->B->cmap->n;
5200:     PetscMalloc1(nzA+nzB, &idx);
5201:     ncols = 0;
5202:     for (i=0; i<nzB; i++) {  /* row < local row index */
5203:       if (cmap[i] < start) idx[ncols++] = cmap[i];
5204:       else break;
5205:     }
5206:     imark = i;
5207:     for (i=0; i<nzA; i++) idx[ncols++] = start + i;  /* local rows */
5208:     for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; /* row > local row index */
5209:     ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&isrowb);
5210:     ISCreateStride(PETSC_COMM_SELF,B->cmap->N,0,1,&iscolb);
5211:   } else {
5212:     if (!rowb || !colb) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"IS rowb and colb must be provided for MAT_REUSE_MATRIX");
5213:     isrowb  = *rowb; iscolb = *colb;
5214:     PetscMalloc1(1,&bseq);
5215:     bseq[0] = *B_seq;
5216:   }
5217:   MatCreateSubMatrices(B,1,&isrowb,&iscolb,scall,&bseq);
5218:   *B_seq = bseq[0];
5219:   PetscFree(bseq);
5220:   if (!rowb) {
5221:     ISDestroy(&isrowb);
5222:   } else {
5223:     *rowb = isrowb;
5224:   }
5225:   if (!colb) {
5226:     ISDestroy(&iscolb);
5227:   } else {
5228:     *colb = iscolb;
5229:   }
5230:   PetscLogEventEnd(MAT_GetBrowsOfAcols,A,B,0,0);
5231:   return(0);
5232: }

5234:  #include <petsc/private/vecscatterimpl.h>
5235: /*
5236:     MatGetBrowsOfAoCols_MPIAIJ - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns
5237:     of the OFF-DIAGONAL portion of local A

5239:     Collective on Mat

5241:    Input Parameters:
5242: +    A,B - the matrices in mpiaij format
5243: -    scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX

5245:    Output Parameter:
5246: +    startsj_s - starting point in B's sending j-arrays, saved for MAT_REUSE (or NULL)
5247: .    startsj_r - starting point in B's receiving j-arrays, saved for MAT_REUSE (or NULL)
5248: .    bufa_ptr - array for sending matrix values, saved for MAT_REUSE (or NULL)
5249: -    B_oth - the sequential matrix generated with size aBn=a->B->cmap->n by B->cmap->N

5251:     Developer Notes: This directly accesses information inside the VecScatter associated with the matrix-vector product
5252:      for this matrix. This is not desirable..

5254:     Level: developer

5256: */
5257: PetscErrorCode MatGetBrowsOfAoCols_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscInt **startsj_s,PetscInt **startsj_r,MatScalar **bufa_ptr,Mat *B_oth)
5258: {
5259:   VecScatter_MPI_General *gen_to,*gen_from;
5260:   PetscErrorCode         ierr;
5261:   Mat_MPIAIJ             *a=(Mat_MPIAIJ*)A->data;
5262:   Mat_SeqAIJ             *b_oth;
5263:   VecScatter             ctx;
5264:   MPI_Comm               comm;
5265:   PetscMPIInt            *rprocs,*sprocs,tag,rank;
5266:   PetscInt               *rowlen,*bufj,*bufJ,ncols,aBn=a->B->cmap->n,row,*b_othi,*b_othj;
5267:   PetscInt               *rvalues,*svalues,*cols,sbs,rbs;
5268:   PetscScalar              *b_otha,*bufa,*bufA,*vals;
5269:   PetscInt               i,j,k,l,ll,nrecvs,nsends,nrows,*srow,*rstarts,*rstartsj = 0,*sstarts,*sstartsj,len;
5270:   MPI_Request            *rwaits = NULL,*swaits = NULL;
5271:   MPI_Status             *sstatus,rstatus;
5272:   PetscMPIInt            jj,size;
5273:   VecScatterType         type;
5274:   PetscBool              mpi1;

5277:   PetscObjectGetComm((PetscObject)A,&comm);
5278:   MPI_Comm_size(comm,&size);

5280:   if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) {
5281:     SETERRQ4(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Matrix local dimensions are incompatible, (%d, %d) != (%d,%d)",A->cmap->rstart,A->cmap->rend,B->rmap->rstart,B->rmap->rend);
5282:   }
5283:   PetscLogEventBegin(MAT_GetBrowsOfAocols,A,B,0,0);
5284:   MPI_Comm_rank(comm,&rank);

5286:   if (size == 1) {
5287:     startsj_s = NULL;
5288:     bufa_ptr  = NULL;
5289:     *B_oth    = NULL;
5290:     return(0);
5291:   }

5293:   ctx = a->Mvctx;
5294:   VecScatterGetType(ctx,&type);
5295:   PetscStrcmp(type,"mpi1",&mpi1);
5296:   if (!mpi1) {
5297:     /* a->Mvctx is not type MPI1 which is not implemented for Mat-Mat ops,
5298:      thus create a->Mvctx_mpi1 */
5299:     if (!a->Mvctx_mpi1) {
5300:       a->Mvctx_mpi1_flg = PETSC_TRUE;
5301:       MatSetUpMultiply_MPIAIJ(A);
5302:     }
5303:     ctx = a->Mvctx_mpi1;
5304:   }
5305:   tag = ((PetscObject)ctx)->tag;

5307:   gen_to   = (VecScatter_MPI_General*)ctx->todata;
5308:   gen_from = (VecScatter_MPI_General*)ctx->fromdata;
5309:   nrecvs   = gen_from->n;
5310:   nsends   = gen_to->n;

5312:   PetscMalloc2(nrecvs,&rwaits,nsends,&swaits);
5313:   srow    = gen_to->indices;    /* local row index to be sent */
5314:   sstarts = gen_to->starts;
5315:   sprocs  = gen_to->procs;
5316:   sstatus = gen_to->sstatus;
5317:   sbs     = gen_to->bs;
5318:   rstarts = gen_from->starts;
5319:   rprocs  = gen_from->procs;
5320:   rbs     = gen_from->bs;

5322:   if (!startsj_s || !bufa_ptr) scall = MAT_INITIAL_MATRIX;
5323:   if (scall == MAT_INITIAL_MATRIX) {
5324:     /* i-array */
5325:     /*---------*/
5326:     /*  post receives */
5327:     PetscMalloc1(rbs*(rstarts[nrecvs] - rstarts[0]),&rvalues);
5328:     for (i=0; i<nrecvs; i++) {
5329:       rowlen = rvalues + rstarts[i]*rbs;
5330:       nrows  = (rstarts[i+1]-rstarts[i])*rbs; /* num of indices to be received */
5331:       MPI_Irecv(rowlen,nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);
5332:     }

5334:     /* pack the outgoing message */
5335:     PetscMalloc2(nsends+1,&sstartsj,nrecvs+1,&rstartsj);

5337:     sstartsj[0] = 0;
5338:     rstartsj[0] = 0;
5339:     len         = 0; /* total length of j or a array to be sent */
5340:     k           = 0;
5341:     PetscMalloc1(sbs*(sstarts[nsends] - sstarts[0]),&svalues);
5342:     for (i=0; i<nsends; i++) {
5343:       rowlen = svalues + sstarts[i]*sbs;
5344:       nrows  = sstarts[i+1]-sstarts[i]; /* num of block rows */
5345:       for (j=0; j<nrows; j++) {
5346:         row = srow[k] + B->rmap->range[rank]; /* global row idx */
5347:         for (l=0; l<sbs; l++) {
5348:           MatGetRow_MPIAIJ(B,row+l,&ncols,NULL,NULL); /* rowlength */

5350:           rowlen[j*sbs+l] = ncols;

5352:           len += ncols;
5353:           MatRestoreRow_MPIAIJ(B,row+l,&ncols,NULL,NULL);
5354:         }
5355:         k++;
5356:       }
5357:       MPI_Isend(rowlen,nrows*sbs,MPIU_INT,sprocs[i],tag,comm,swaits+i);

5359:       sstartsj[i+1] = len;  /* starting point of (i+1)-th outgoing msg in bufj and bufa */
5360:     }
5361:     /* recvs and sends of i-array are completed */
5362:     i = nrecvs;
5363:     while (i--) {
5364:       MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);
5365:     }
5366:     if (nsends) {MPI_Waitall(nsends,swaits,sstatus);}
5367:     PetscFree(svalues);

5369:     /* allocate buffers for sending j and a arrays */
5370:     PetscMalloc1(len+1,&bufj);
5371:     PetscMalloc1(len+1,&bufa);

5373:     /* create i-array of B_oth */
5374:     PetscMalloc1(aBn+2,&b_othi);

5376:     b_othi[0] = 0;
5377:     len       = 0; /* total length of j or a array to be received */
5378:     k         = 0;
5379:     for (i=0; i<nrecvs; i++) {
5380:       rowlen = rvalues + rstarts[i]*rbs;
5381:       nrows  = rbs*(rstarts[i+1]-rstarts[i]); /* num of rows to be received */
5382:       for (j=0; j<nrows; j++) {
5383:         b_othi[k+1] = b_othi[k] + rowlen[j];
5384:         PetscIntSumError(rowlen[j],len,&len);
5385:         k++;
5386:       }
5387:       rstartsj[i+1] = len; /* starting point of (i+1)-th incoming msg in bufj and bufa */
5388:     }
5389:     PetscFree(rvalues);

5391:     /* allocate space for j and a arrrays of B_oth */
5392:     PetscMalloc1(b_othi[aBn]+1,&b_othj);
5393:     PetscMalloc1(b_othi[aBn]+1,&b_otha);

5395:     /* j-array */
5396:     /*---------*/
5397:     /*  post receives of j-array */
5398:     for (i=0; i<nrecvs; i++) {
5399:       nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */
5400:       MPI_Irecv(b_othj+rstartsj[i],nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);
5401:     }

5403:     /* pack the outgoing message j-array */
5404:     k = 0;
5405:     for (i=0; i<nsends; i++) {
5406:       nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */
5407:       bufJ  = bufj+sstartsj[i];
5408:       for (j=0; j<nrows; j++) {
5409:         row = srow[k++] + B->rmap->range[rank];  /* global row idx */
5410:         for (ll=0; ll<sbs; ll++) {
5411:           MatGetRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);
5412:           for (l=0; l<ncols; l++) {
5413:             *bufJ++ = cols[l];
5414:           }
5415:           MatRestoreRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);
5416:         }
5417:       }
5418:       MPI_Isend(bufj+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_INT,sprocs[i],tag,comm,swaits+i);
5419:     }

5421:     /* recvs and sends of j-array are completed */
5422:     i = nrecvs;
5423:     while (i--) {
5424:       MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);
5425:     }
5426:     if (nsends) {MPI_Waitall(nsends,swaits,sstatus);}
5427:   } else if (scall == MAT_REUSE_MATRIX) {
5428:     sstartsj = *startsj_s;
5429:     rstartsj = *startsj_r;
5430:     bufa     = *bufa_ptr;
5431:     b_oth    = (Mat_SeqAIJ*)(*B_oth)->data;
5432:     b_otha   = b_oth->a;
5433:   } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE, "Matrix P does not posses an object container");

5435:   /* a-array */
5436:   /*---------*/
5437:   /*  post receives of a-array */
5438:   for (i=0; i<nrecvs; i++) {
5439:     nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */
5440:     MPI_Irecv(b_otha+rstartsj[i],nrows,MPIU_SCALAR,rprocs[i],tag,comm,rwaits+i);
5441:   }

5443:   /* pack the outgoing message a-array */
5444:   k = 0;
5445:   for (i=0; i<nsends; i++) {
5446:     nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */
5447:     bufA  = bufa+sstartsj[i];
5448:     for (j=0; j<nrows; j++) {
5449:       row = srow[k++] + B->rmap->range[rank];  /* global row idx */
5450:       for (ll=0; ll<sbs; ll++) {
5451:         MatGetRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);
5452:         for (l=0; l<ncols; l++) {
5453:           *bufA++ = vals[l];
5454:         }
5455:         MatRestoreRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);
5456:       }
5457:     }
5458:     MPI_Isend(bufa+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_SCALAR,sprocs[i],tag,comm,swaits+i);
5459:   }
5460:   /* recvs and sends of a-array are completed */
5461:   i = nrecvs;
5462:   while (i--) {
5463:     MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);
5464:   }
5465:   if (nsends) {MPI_Waitall(nsends,swaits,sstatus);}
5466:   PetscFree2(rwaits,swaits);

5468:   if (scall == MAT_INITIAL_MATRIX) {
5469:     /* put together the new matrix */
5470:     MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,aBn,B->cmap->N,b_othi,b_othj,b_otha,B_oth);

5472:     /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */
5473:     /* Since these are PETSc arrays, change flags to free them as necessary. */
5474:     b_oth          = (Mat_SeqAIJ*)(*B_oth)->data;
5475:     b_oth->free_a  = PETSC_TRUE;
5476:     b_oth->free_ij = PETSC_TRUE;
5477:     b_oth->nonew   = 0;

5479:     PetscFree(bufj);
5480:     if (!startsj_s || !bufa_ptr) {
5481:       PetscFree2(sstartsj,rstartsj);
5482:       PetscFree(bufa_ptr);
5483:     } else {
5484:       *startsj_s = sstartsj;
5485:       *startsj_r = rstartsj;
5486:       *bufa_ptr  = bufa;
5487:     }
5488:   }
5489:   PetscLogEventEnd(MAT_GetBrowsOfAocols,A,B,0,0);
5490:   return(0);
5491: }

5493: /*@C
5494:   MatGetCommunicationStructs - Provides access to the communication structures used in matrix-vector multiplication.

5496:   Not Collective

5498:   Input Parameters:
5499: . A - The matrix in mpiaij format

5501:   Output Parameter:
5502: + lvec - The local vector holding off-process values from the argument to a matrix-vector product
5503: . colmap - A map from global column index to local index into lvec
5504: - multScatter - A scatter from the argument of a matrix-vector product to lvec

5506:   Level: developer

5508: @*/
5509: #if defined(PETSC_USE_CTABLE)
5510: PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscTable *colmap, VecScatter *multScatter)
5511: #else
5512: PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscInt *colmap[], VecScatter *multScatter)
5513: #endif
5514: {
5515:   Mat_MPIAIJ *a;

5522:   a = (Mat_MPIAIJ*) A->data;
5523:   if (lvec) *lvec = a->lvec;
5524:   if (colmap) *colmap = a->colmap;
5525:   if (multScatter) *multScatter = a->Mvctx;
5526:   return(0);
5527: }

5529: PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJCRL(Mat,MatType,MatReuse,Mat*);
5530: PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJPERM(Mat,MatType,MatReuse,Mat*);
5531: PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJSELL(Mat,MatType,MatReuse,Mat*);
5532: #if defined(PETSC_HAVE_MKL_SPARSE)
5533: PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJMKL(Mat,MatType,MatReuse,Mat*);
5534: #endif
5535: PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPISBAIJ(Mat,MatType,MatReuse,Mat*);
5536: #if defined(PETSC_HAVE_ELEMENTAL)
5537: PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_Elemental(Mat,MatType,MatReuse,Mat*);
5538: #endif
5539: #if defined(PETSC_HAVE_HYPRE)
5540: PETSC_INTERN PetscErrorCode MatConvert_AIJ_HYPRE(Mat,MatType,MatReuse,Mat*);
5541: PETSC_INTERN PetscErrorCode MatMatMatMult_Transpose_AIJ_AIJ(Mat,Mat,Mat,MatReuse,PetscReal,Mat*);
5542: #endif
5543: PETSC_INTERN PetscErrorCode MatConvert_XAIJ_IS(Mat,MatType,MatReuse,Mat*);
5544: PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPISELL(Mat,MatType,MatReuse,Mat*);
5545: PETSC_INTERN PetscErrorCode MatPtAP_IS_XAIJ(Mat,Mat,MatReuse,PetscReal,Mat*);

5547: /*
5548:     Computes (B'*A')' since computing B*A directly is untenable

5550:                n                       p                          p
5551:         (              )       (              )         (                  )
5552:       m (      A       )  *  n (       B      )   =   m (         C        )
5553:         (              )       (              )         (                  )

5555: */
5556: PetscErrorCode MatMatMultNumeric_MPIDense_MPIAIJ(Mat A,Mat B,Mat C)
5557: {
5559:   Mat            At,Bt,Ct;

5562:   MatTranspose(A,MAT_INITIAL_MATRIX,&At);
5563:   MatTranspose(B,MAT_INITIAL_MATRIX,&Bt);
5564:   MatMatMult(Bt,At,MAT_INITIAL_MATRIX,1.0,&Ct);
5565:   MatDestroy(&At);
5566:   MatDestroy(&Bt);
5567:   MatTranspose(Ct,MAT_REUSE_MATRIX,&C);
5568:   MatDestroy(&Ct);
5569:   return(0);
5570: }

5572: PetscErrorCode MatMatMultSymbolic_MPIDense_MPIAIJ(Mat A,Mat B,PetscReal fill,Mat *C)
5573: {
5575:   PetscInt       m=A->rmap->n,n=B->cmap->n;
5576:   Mat            Cmat;

5579:   if (A->cmap->n != B->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"A->cmap->n %d != B->rmap->n %d\n",A->cmap->n,B->rmap->n);
5580:   MatCreate(PetscObjectComm((PetscObject)A),&Cmat);
5581:   MatSetSizes(Cmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);
5582:   MatSetBlockSizesFromMats(Cmat,A,B);
5583:   MatSetType(Cmat,MATMPIDENSE);
5584:   MatMPIDenseSetPreallocation(Cmat,NULL);
5585:   MatAssemblyBegin(Cmat,MAT_FINAL_ASSEMBLY);
5586:   MatAssemblyEnd(Cmat,MAT_FINAL_ASSEMBLY);

5588:   Cmat->ops->matmultnumeric = MatMatMultNumeric_MPIDense_MPIAIJ;

5590:   *C = Cmat;
5591:   return(0);
5592: }

5594: /* ----------------------------------------------------------------*/
5595: PETSC_INTERN PetscErrorCode MatMatMult_MPIDense_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C)
5596: {

5600:   if (scall == MAT_INITIAL_MATRIX) {
5601:     PetscLogEventBegin(MAT_MatMultSymbolic,A,B,0,0);
5602:     MatMatMultSymbolic_MPIDense_MPIAIJ(A,B,fill,C);
5603:     PetscLogEventEnd(MAT_MatMultSymbolic,A,B,0,0);
5604:   }
5605:   PetscLogEventBegin(MAT_MatMultNumeric,A,B,0,0);
5606:   MatMatMultNumeric_MPIDense_MPIAIJ(A,B,*C);
5607:   PetscLogEventEnd(MAT_MatMultNumeric,A,B,0,0);
5608:   return(0);
5609: }

5611: /*MC
5612:    MATMPIAIJ - MATMPIAIJ = "mpiaij" - A matrix type to be used for parallel sparse matrices.

5614:    Options Database Keys:
5615: . -mat_type mpiaij - sets the matrix type to "mpiaij" during a call to MatSetFromOptions()

5617:   Level: beginner

5619: .seealso: MatCreateAIJ()
5620: M*/

5622: PETSC_EXTERN PetscErrorCode MatCreate_MPIAIJ(Mat B)
5623: {
5624:   Mat_MPIAIJ     *b;
5626:   PetscMPIInt    size;

5629:   MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);

5631:   PetscNewLog(B,&b);
5632:   B->data       = (void*)b;
5633:   PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));
5634:   B->assembled  = PETSC_FALSE;
5635:   B->insertmode = NOT_SET_VALUES;
5636:   b->size       = size;

5638:   MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);

5640:   /* build cache for off array entries formed */
5641:   MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);

5643:   b->donotstash  = PETSC_FALSE;
5644:   b->colmap      = 0;
5645:   b->garray      = 0;
5646:   b->roworiented = PETSC_TRUE;

5648:   /* stuff used for matrix vector multiply */
5649:   b->lvec  = NULL;
5650:   b->Mvctx = NULL;

5652:   /* stuff for MatGetRow() */
5653:   b->rowindices   = 0;
5654:   b->rowvalues    = 0;
5655:   b->getrowactive = PETSC_FALSE;

5657:   /* flexible pointer used in CUSP/CUSPARSE classes */
5658:   b->spptr = NULL;

5660:   PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetUseScalableIncreaseOverlap_C",MatMPIAIJSetUseScalableIncreaseOverlap_MPIAIJ);
5661:   PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPIAIJ);
5662:   PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPIAIJ);
5663:   PetscObjectComposeFunction((PetscObject)B,"MatIsTranspose_C",MatIsTranspose_MPIAIJ);
5664:   PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocation_C",MatMPIAIJSetPreallocation_MPIAIJ);
5665:   PetscObjectComposeFunction((PetscObject)B,"MatResetPreallocation_C",MatResetPreallocation_MPIAIJ);
5666:   PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocationCSR_C",MatMPIAIJSetPreallocationCSR_MPIAIJ);
5667:   PetscObjectComposeFunction((PetscObject)B,"MatDiagonalScaleLocal_C",MatDiagonalScaleLocal_MPIAIJ);
5668:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijperm_C",MatConvert_MPIAIJ_MPIAIJPERM);
5669:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijsell_C",MatConvert_MPIAIJ_MPIAIJSELL);
5670: #if defined(PETSC_HAVE_MKL_SPARSE)
5671:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijmkl_C",MatConvert_MPIAIJ_MPIAIJMKL);
5672: #endif
5673:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijcrl_C",MatConvert_MPIAIJ_MPIAIJCRL);
5674:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpisbaij_C",MatConvert_MPIAIJ_MPISBAIJ);
5675: #if defined(PETSC_HAVE_ELEMENTAL)
5676:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_elemental_C",MatConvert_MPIAIJ_Elemental);
5677: #endif
5678: #if defined(PETSC_HAVE_HYPRE)
5679:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_hypre_C",MatConvert_AIJ_HYPRE);
5680: #endif
5681:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_is_C",MatConvert_XAIJ_IS);
5682:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpisell_C",MatConvert_MPIAIJ_MPISELL);
5683:   PetscObjectComposeFunction((PetscObject)B,"MatMatMult_mpidense_mpiaij_C",MatMatMult_MPIDense_MPIAIJ);
5684:   PetscObjectComposeFunction((PetscObject)B,"MatMatMultSymbolic_mpidense_mpiaij_C",MatMatMultSymbolic_MPIDense_MPIAIJ);
5685:   PetscObjectComposeFunction((PetscObject)B,"MatMatMultNumeric_mpidense_mpiaij_C",MatMatMultNumeric_MPIDense_MPIAIJ);
5686: #if defined(PETSC_HAVE_HYPRE)
5687:   PetscObjectComposeFunction((PetscObject)B,"MatMatMatMult_transpose_mpiaij_mpiaij_C",MatMatMatMult_Transpose_AIJ_AIJ);
5688: #endif
5689:   PetscObjectComposeFunction((PetscObject)B,"MatPtAP_is_mpiaij_C",MatPtAP_IS_XAIJ);
5690:   PetscObjectChangeTypeName((PetscObject)B,MATMPIAIJ);
5691:   return(0);
5692: }

5694: /*@C
5695:      MatCreateMPIAIJWithSplitArrays - creates a MPI AIJ matrix using arrays that contain the "diagonal"
5696:          and "off-diagonal" part of the matrix in CSR format.

5698:    Collective on MPI_Comm

5700:    Input Parameters:
5701: +  comm - MPI communicator
5702: .  m - number of local rows (Cannot be PETSC_DECIDE)
5703: .  n - This value should be the same as the local size used in creating the
5704:        x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have
5705:        calculated if N is given) For square matrices n is almost always m.
5706: .  M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
5707: .  N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
5708: .   i - row indices for "diagonal" portion of matrix
5709: .   j - column indices
5710: .   a - matrix values
5711: .   oi - row indices for "off-diagonal" portion of matrix
5712: .   oj - column indices
5713: -   oa - matrix values

5715:    Output Parameter:
5716: .   mat - the matrix

5718:    Level: advanced

5720:    Notes:
5721:        The i, j, and a arrays ARE NOT copied by this routine into the internal format used by PETSc. The user
5722:        must free the arrays once the matrix has been destroyed and not before.

5724:        The i and j indices are 0 based

5726:        See MatCreateAIJ() for the definition of "diagonal" and "off-diagonal" portion of the matrix

5728:        This sets local rows and cannot be used to set off-processor values.

5730:        Use of this routine is discouraged because it is inflexible and cumbersome to use. It is extremely rare that a
5731:        legacy application natively assembles into exactly this split format. The code to do so is nontrivial and does
5732:        not easily support in-place reassembly. It is recommended to use MatSetValues() (or a variant thereof) because
5733:        the resulting assembly is easier to implement, will work with any matrix format, and the user does not have to
5734:        keep track of the underlying array. Use MatSetOption(A,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE) to disable all
5735:        communication if it is known that only local entries will be set.

5737: .keywords: matrix, aij, compressed row, sparse, parallel

5739: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(),
5740:           MATMPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithArrays()
5741: @*/
5742: PetscErrorCode MatCreateMPIAIJWithSplitArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,PetscInt i[],PetscInt j[],PetscScalar a[],PetscInt oi[], PetscInt oj[],PetscScalar oa[],Mat *mat)
5743: {
5745:   Mat_MPIAIJ     *maij;

5748:   if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative");
5749:   if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0");
5750:   if (oi[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"oi (row indices) must start with 0");
5751:   MatCreate(comm,mat);
5752:   MatSetSizes(*mat,m,n,M,N);
5753:   MatSetType(*mat,MATMPIAIJ);
5754:   maij = (Mat_MPIAIJ*) (*mat)->data;

5756:   (*mat)->preallocated = PETSC_TRUE;

5758:   PetscLayoutSetUp((*mat)->rmap);
5759:   PetscLayoutSetUp((*mat)->cmap);

5761:   MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,n,i,j,a,&maij->A);
5762:   MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,(*mat)->cmap->N,oi,oj,oa,&maij->B);

5764:   MatAssemblyBegin(maij->A,MAT_FINAL_ASSEMBLY);
5765:   MatAssemblyEnd(maij->A,MAT_FINAL_ASSEMBLY);
5766:   MatAssemblyBegin(maij->B,MAT_FINAL_ASSEMBLY);
5767:   MatAssemblyEnd(maij->B,MAT_FINAL_ASSEMBLY);

5769:   MatSetOption(*mat,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE);
5770:   MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);
5771:   MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);
5772:   MatSetOption(*mat,MAT_NO_OFF_PROC_ENTRIES,PETSC_FALSE);
5773:   MatSetOption(*mat,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);
5774:   return(0);
5775: }

5777: /*
5778:     Special version for direct calls from Fortran
5779: */
5780:  #include <petsc/private/fortranimpl.h>

5782: /* Change these macros so can be used in void function */
5783: #undef CHKERRQ
5784: #define CHKERRQ(ierr) CHKERRABORT(PETSC_COMM_WORLD,ierr)
5785: #undef SETERRQ2
5786: #define SETERRQ2(comm,ierr,b,c,d) CHKERRABORT(comm,ierr)
5787: #undef SETERRQ3
5788: #define SETERRQ3(comm,ierr,b,c,d,e) CHKERRABORT(comm,ierr)
5789: #undef SETERRQ
5790: #define SETERRQ(c,ierr,b) CHKERRABORT(c,ierr)

5792: #if defined(PETSC_HAVE_FORTRAN_CAPS)
5793: #define matsetvaluesmpiaij_ MATSETVALUESMPIAIJ
5794: #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE)
5795: #define matsetvaluesmpiaij_ matsetvaluesmpiaij
5796: #else
5797: #endif
5798: PETSC_EXTERN void PETSC_STDCALL matsetvaluesmpiaij_(Mat *mmat,PetscInt *mm,const PetscInt im[],PetscInt *mn,const PetscInt in[],const PetscScalar v[],InsertMode *maddv,PetscErrorCode *_ierr)
5799: {
5800:   Mat            mat  = *mmat;
5801:   PetscInt       m    = *mm, n = *mn;
5802:   InsertMode     addv = *maddv;
5803:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)mat->data;
5804:   PetscScalar    value;

5807:   MatCheckPreallocated(mat,1);
5808:   if (mat->insertmode == NOT_SET_VALUES) mat->insertmode = addv;

5810: #if defined(PETSC_USE_DEBUG)
5811:   else if (mat->insertmode != addv) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values");
5812: #endif
5813:   {
5814:     PetscInt  i,j,rstart  = mat->rmap->rstart,rend = mat->rmap->rend;
5815:     PetscInt  cstart      = mat->cmap->rstart,cend = mat->cmap->rend,row,col;
5816:     PetscBool roworiented = aij->roworiented;

5818:     /* Some Variables required in the macro */
5819:     Mat        A                 = aij->A;
5820:     Mat_SeqAIJ *a                = (Mat_SeqAIJ*)A->data;
5821:     PetscInt   *aimax            = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j;
5822:     MatScalar  *aa               = a->a;
5823:     PetscBool  ignorezeroentries = (((a->ignorezeroentries)&&(addv==ADD_VALUES)) ? PETSC_TRUE : PETSC_FALSE);
5824:     Mat        B                 = aij->B;
5825:     Mat_SeqAIJ *b                = (Mat_SeqAIJ*)B->data;
5826:     PetscInt   *bimax            = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n;
5827:     MatScalar  *ba               = b->a;

5829:     PetscInt  *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2;
5830:     PetscInt  nonew = a->nonew;
5831:     MatScalar *ap1,*ap2;

5834:     for (i=0; i<m; i++) {
5835:       if (im[i] < 0) continue;
5836: #if defined(PETSC_USE_DEBUG)
5837:       if (im[i] >= mat->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],mat->rmap->N-1);
5838: #endif
5839:       if (im[i] >= rstart && im[i] < rend) {
5840:         row      = im[i] - rstart;
5841:         lastcol1 = -1;
5842:         rp1      = aj + ai[row];
5843:         ap1      = aa + ai[row];
5844:         rmax1    = aimax[row];
5845:         nrow1    = ailen[row];
5846:         low1     = 0;
5847:         high1    = nrow1;
5848:         lastcol2 = -1;
5849:         rp2      = bj + bi[row];
5850:         ap2      = ba + bi[row];
5851:         rmax2    = bimax[row];
5852:         nrow2    = bilen[row];
5853:         low2     = 0;
5854:         high2    = nrow2;

5856:         for (j=0; j<n; j++) {
5857:           if (roworiented) value = v[i*n+j];
5858:           else value = v[i+j*m];
5859:           if (in[j] >= cstart && in[j] < cend) {
5860:             col = in[j] - cstart;
5861:             if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES) && row != col) continue;
5862:             MatSetValues_SeqAIJ_A_Private(row,col,value,addv,im[i],in[j]);
5863:           } else if (in[j] < 0) continue;
5864: #if defined(PETSC_USE_DEBUG)
5865:           /* extra brace on SETERRQ2() is required for --with-errorchecking=0 - due to the next 'else' clause */
5866:           else if (in[j] >= mat->cmap->N) {SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",in[j],mat->cmap->N-1);}
5867: #endif
5868:           else {
5869:             if (mat->was_assembled) {
5870:               if (!aij->colmap) {
5871:                 MatCreateColmap_MPIAIJ_Private(mat);
5872:               }
5873: #if defined(PETSC_USE_CTABLE)
5874:               PetscTableFind(aij->colmap,in[j]+1,&col);
5875:               col--;
5876: #else
5877:               col = aij->colmap[in[j]] - 1;
5878: #endif
5879:               if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES) && row != col) continue;
5880:               if (col < 0 && !((Mat_SeqAIJ*)(aij->A->data))->nonew) {
5881:                 MatDisAssemble_MPIAIJ(mat);
5882:                 col  =  in[j];
5883:                 /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */
5884:                 B     = aij->B;
5885:                 b     = (Mat_SeqAIJ*)B->data;
5886:                 bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j;
5887:                 rp2   = bj + bi[row];
5888:                 ap2   = ba + bi[row];
5889:                 rmax2 = bimax[row];
5890:                 nrow2 = bilen[row];
5891:                 low2  = 0;
5892:                 high2 = nrow2;
5893:                 bm    = aij->B->rmap->n;
5894:                 ba    = b->a;
5895:               }
5896:             } else col = in[j];
5897:             MatSetValues_SeqAIJ_B_Private(row,col,value,addv,im[i],in[j]);
5898:           }
5899:         }
5900:       } else if (!aij->donotstash) {
5901:         if (roworiented) {
5902:           MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));
5903:         } else {
5904:           MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));
5905:         }
5906:       }
5907:     }
5908:   }
5909:   PetscFunctionReturnVoid();
5910: }