Actual source code: mpiaij.c

  1: #define PETSCMAT_DLL

 3:  #include ../src/mat/impls/aij/mpi/mpiaij.h
 4:  #include petscblaslapack.h

  8: /*
  9:     Distributes a SeqAIJ matrix across a set of processes. Code stolen from
 10:     MatLoad_MPIAIJ(). Horrible lack of reuse. Should be a routine for each matrix type.

 12:     Only for square matrices
 13: */
 14: PetscErrorCode MatDistribute_MPIAIJ(MPI_Comm comm,Mat gmat,PetscInt m,MatReuse reuse,Mat *inmat)
 15: {
 16:   PetscMPIInt    rank,size;
 17:   PetscInt       *rowners,*dlens,*olens,i,rstart,rend,j,jj,nz,*gmataj,cnt,row,*ld;
 19:   Mat            mat;
 20:   Mat_SeqAIJ     *gmata;
 21:   PetscMPIInt    tag;
 22:   MPI_Status     status;
 23:   PetscTruth     aij;
 24:   MatScalar      *gmataa,*ao,*ad,*gmataarestore=0;

 27:   CHKMEMQ;
 28:   MPI_Comm_rank(comm,&rank);
 29:   MPI_Comm_size(comm,&size);
 30:   if (!rank) {
 31:     PetscTypeCompare((PetscObject)gmat,MATSEQAIJ,&aij);
 32:     if (!aij) SETERRQ1(PETSC_ERR_SUP,"Currently no support for input matrix of type %s\n",((PetscObject)gmat)->type_name);
 33:   }
 34:   if (reuse == MAT_INITIAL_MATRIX) {
 35:     MatCreate(comm,&mat);
 36:     MatSetSizes(mat,m,m,PETSC_DETERMINE,PETSC_DETERMINE);
 37:     MatSetType(mat,MATAIJ);
 38:     PetscMalloc((size+1)*sizeof(PetscInt),&rowners);
 39:     PetscMalloc2(m,PetscInt,&dlens,m,PetscInt,&olens);
 40:     MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);
 41:     rowners[0] = 0;
 42:     for (i=2; i<=size; i++) {
 43:       rowners[i] += rowners[i-1];
 44:     }
 45:     rstart = rowners[rank];
 46:     rend   = rowners[rank+1];
 47:     PetscObjectGetNewTag((PetscObject)mat,&tag);
 48:     if (!rank) {
 49:       gmata = (Mat_SeqAIJ*) gmat->data;
 50:       /* send row lengths to all processors */
 51:       for (i=0; i<m; i++) dlens[i] = gmata->ilen[i];
 52:       for (i=1; i<size; i++) {
 53:         MPI_Send(gmata->ilen + rowners[i],rowners[i+1]-rowners[i],MPIU_INT,i,tag,comm);
 54:       }
 55:       /* determine number diagonal and off-diagonal counts */
 56:       PetscMemzero(olens,m*sizeof(PetscInt));
 57:       PetscMalloc(m*sizeof(PetscInt),&ld);
 58:       PetscMemzero(ld,m*sizeof(PetscInt));
 59:       jj = 0;
 60:       for (i=0; i<m; i++) {
 61:         for (j=0; j<dlens[i]; j++) {
 62:           if (gmata->j[jj] < rstart) ld[i]++;
 63:           if (gmata->j[jj] < rstart || gmata->j[jj] >= rend) olens[i]++;
 64:           jj++;
 65:         }
 66:       }
 67:       /* send column indices to other processes */
 68:       for (i=1; i<size; i++) {
 69:         nz   = gmata->i[rowners[i+1]]-gmata->i[rowners[i]];
 70:         MPI_Send(&nz,1,MPIU_INT,i,tag,comm);
 71:         MPI_Send(gmata->j + gmata->i[rowners[i]],nz,MPIU_INT,i,tag,comm);
 72:       }

 74:       /* send numerical values to other processes */
 75:       for (i=1; i<size; i++) {
 76:         nz   = gmata->i[rowners[i+1]]-gmata->i[rowners[i]];
 77:         MPI_Send(gmata->a + gmata->i[rowners[i]],nz,MPIU_SCALAR,i,tag,comm);
 78:       }
 79:       gmataa = gmata->a;
 80:       gmataj = gmata->j;

 82:     } else {
 83:       /* receive row lengths */
 84:       MPI_Recv(dlens,m,MPIU_INT,0,tag,comm,&status);
 85:       /* receive column indices */
 86:       MPI_Recv(&nz,1,MPIU_INT,0,tag,comm,&status);
 87:       PetscMalloc2(nz,PetscScalar,&gmataa,nz,PetscInt,&gmataj);
 88:       MPI_Recv(gmataj,nz,MPIU_INT,0,tag,comm,&status);
 89:       /* determine number diagonal and off-diagonal counts */
 90:       PetscMemzero(olens,m*sizeof(PetscInt));
 91:       PetscMalloc(m*sizeof(PetscInt),&ld);
 92:       PetscMemzero(ld,m*sizeof(PetscInt));
 93:       jj = 0;
 94:       for (i=0; i<m; i++) {
 95:         for (j=0; j<dlens[i]; j++) {
 96:           if (gmataj[jj] < rstart) ld[i]++;
 97:           if (gmataj[jj] < rstart || gmataj[jj] >= rend) olens[i]++;
 98:           jj++;
 99:         }
100:       }
101:       /* receive numerical values */
102:       PetscMemzero(gmataa,nz*sizeof(PetscScalar));
103:       MPI_Recv(gmataa,nz,MPIU_SCALAR,0,tag,comm,&status);
104:     }
105:     /* set preallocation */
106:     for (i=0; i<m; i++) {
107:       dlens[i] -= olens[i];
108:     }
109:     MatSeqAIJSetPreallocation(mat,0,dlens);
110:     MatMPIAIJSetPreallocation(mat,0,dlens,0,olens);
111: 
112:     for (i=0; i<m; i++) {
113:       dlens[i] += olens[i];
114:     }
115:     cnt  = 0;
116:     for (i=0; i<m; i++) {
117:       row  = rstart + i;
118:       MatSetValues(mat,1,&row,dlens[i],gmataj+cnt,gmataa+cnt,INSERT_VALUES);
119:       cnt += dlens[i];
120:     }
121:     if (rank) {
122:       PetscFree2(gmataa,gmataj);
123:     }
124:     PetscFree2(dlens,olens);
125:     PetscFree(rowners);
126:     ((Mat_MPIAIJ*)(mat->data))->ld = ld;
127:     *inmat = mat;
128:   } else {   /* column indices are already set; only need to move over numerical values from process 0 */
129:     Mat_SeqAIJ *Ad = (Mat_SeqAIJ*)((Mat_MPIAIJ*)((*inmat)->data))->A->data;
130:     Mat_SeqAIJ *Ao = (Mat_SeqAIJ*)((Mat_MPIAIJ*)((*inmat)->data))->B->data;
131:     mat   = *inmat;
132:     PetscObjectGetNewTag((PetscObject)mat,&tag);
133:     if (!rank) {
134:       /* send numerical values to other processes */
135:       gmata = (Mat_SeqAIJ*) gmat->data;
136:       MatGetOwnershipRanges(mat,(const PetscInt**)&rowners);
137:       gmataa = gmata->a;
138:       for (i=1; i<size; i++) {
139:         nz   = gmata->i[rowners[i+1]]-gmata->i[rowners[i]];
140:         MPI_Send(gmataa + gmata->i[rowners[i]],nz,MPIU_SCALAR,i,tag,comm);
141:       }
142:       nz   = gmata->i[rowners[1]]-gmata->i[rowners[0]];
143:     } else {
144:       /* receive numerical values from process 0*/
145:       nz   = Ad->nz + Ao->nz;
146:       PetscMalloc(nz*sizeof(PetscScalar),&gmataa); gmataarestore = gmataa;
147:       MPI_Recv(gmataa,nz,MPIU_SCALAR,0,tag,comm,&status);
148:     }
149:     /* transfer numerical values into the diagonal A and off diagonal B parts of mat */
150:     ld = ((Mat_MPIAIJ*)(mat->data))->ld;
151:     ad = Ad->a;
152:     ao = Ao->a;
153:     if (mat->rmap->n) {
154:       i  = 0;
155:       nz = ld[i];                                   PetscMemcpy(ao,gmataa,nz*sizeof(PetscScalar)); ao += nz; gmataa += nz;
156:       nz = Ad->i[i+1] - Ad->i[i];                   PetscMemcpy(ad,gmataa,nz*sizeof(PetscScalar)); ad += nz; gmataa += nz;
157:     }
158:     for (i=1; i<mat->rmap->n; i++) {
159:       nz = Ao->i[i] - Ao->i[i-1] - ld[i-1] + ld[i]; PetscMemcpy(ao,gmataa,nz*sizeof(PetscScalar)); ao += nz; gmataa += nz;
160:       nz = Ad->i[i+1] - Ad->i[i];                   PetscMemcpy(ad,gmataa,nz*sizeof(PetscScalar)); ad += nz; gmataa += nz;
161:     }
162:     i--;
163:     if (mat->rmap->n) {
164:       nz = Ao->i[i+1] - Ao->i[i] - ld[i];           PetscMemcpy(ao,gmataa,nz*sizeof(PetscScalar)); ao += nz; gmataa += nz;
165:     }
166:     if (rank) {
167:       PetscFree(gmataarestore);
168:     }
169:   }
170:   MatAssemblyBegin(mat,MAT_FINAL_ASSEMBLY);
171:   MatAssemblyEnd(mat,MAT_FINAL_ASSEMBLY);
172:   CHKMEMQ;
173:   return(0);
174: }

176: /* 
177:   Local utility routine that creates a mapping from the global column 
178: number to the local number in the off-diagonal part of the local 
179: storage of the matrix.  When PETSC_USE_CTABLE is used this is scalable at 
180: a slightly higher hash table cost; without it it is not scalable (each processor
181: has an order N integer array but is fast to acess.
182: */
185: PetscErrorCode CreateColmap_MPIAIJ_Private(Mat mat)
186: {
187:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)mat->data;
189:   PetscInt       n = aij->B->cmap->n,i;

192: #if defined (PETSC_USE_CTABLE)
193:   PetscTableCreate(n,&aij->colmap);
194:   for (i=0; i<n; i++){
195:     PetscTableAdd(aij->colmap,aij->garray[i]+1,i+1);
196:   }
197: #else
198:   PetscMalloc((mat->cmap->N+1)*sizeof(PetscInt),&aij->colmap);
199:   PetscLogObjectMemory(mat,mat->cmap->N*sizeof(PetscInt));
200:   PetscMemzero(aij->colmap,mat->cmap->N*sizeof(PetscInt));
201:   for (i=0; i<n; i++) aij->colmap[aij->garray[i]] = i+1;
202: #endif
203:   return(0);
204: }


207: #define CHUNKSIZE   15
208: #define MatSetValues_SeqAIJ_A_Private(row,col,value,addv) \
209: { \
210:     if (col <= lastcol1) low1 = 0; else high1 = nrow1; \
211:     lastcol1 = col;\
212:     while (high1-low1 > 5) { \
213:       t = (low1+high1)/2; \
214:       if (rp1[t] > col) high1 = t; \
215:       else             low1  = t; \
216:     } \
217:       for (_i=low1; _i<high1; _i++) { \
218:         if (rp1[_i] > col) break; \
219:         if (rp1[_i] == col) { \
220:           if (addv == ADD_VALUES) ap1[_i] += value;   \
221:           else                    ap1[_i] = value; \
222:           goto a_noinsert; \
223:         } \
224:       }  \
225:       if (value == 0.0 && ignorezeroentries) {low1 = 0; high1 = nrow1;goto a_noinsert;} \
226:       if (nonew == 1) {low1 = 0; high1 = nrow1; goto a_noinsert;}                \
227:       if (nonew == -1) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \
228:       MatSeqXAIJReallocateAIJ(A,am,1,nrow1,row,col,rmax1,aa,ai,aj,rp1,ap1,aimax,nonew,MatScalar); \
229:       N = nrow1++ - 1; a->nz++; high1++; \
230:       /* shift up all the later entries in this row */ \
231:       for (ii=N; ii>=_i; ii--) { \
232:         rp1[ii+1] = rp1[ii]; \
233:         ap1[ii+1] = ap1[ii]; \
234:       } \
235:       rp1[_i] = col;  \
236:       ap1[_i] = value;  \
237:       a_noinsert: ; \
238:       ailen[row] = nrow1; \
239: } 


242: #define MatSetValues_SeqAIJ_B_Private(row,col,value,addv) \
243: { \
244:     if (col <= lastcol2) low2 = 0; else high2 = nrow2; \
245:     lastcol2 = col;\
246:     while (high2-low2 > 5) { \
247:       t = (low2+high2)/2; \
248:       if (rp2[t] > col) high2 = t; \
249:       else             low2  = t; \
250:     } \
251:     for (_i=low2; _i<high2; _i++) {                \
252:       if (rp2[_i] > col) break;                        \
253:       if (rp2[_i] == col) {                              \
254:         if (addv == ADD_VALUES) ap2[_i] += value;     \
255:         else                    ap2[_i] = value;      \
256:         goto b_noinsert;                              \
257:       }                                                      \
258:     }                                                              \
259:     if (value == 0.0 && ignorezeroentries) {low2 = 0; high2 = nrow2; goto b_noinsert;} \
260:     if (nonew == 1) {low2 = 0; high2 = nrow2; goto b_noinsert;}                \
261:     if (nonew == -1) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \
262:     MatSeqXAIJReallocateAIJ(B,bm,1,nrow2,row,col,rmax2,ba,bi,bj,rp2,ap2,bimax,nonew,MatScalar); \
263:     N = nrow2++ - 1; b->nz++; high2++;                                        \
264:     /* shift up all the later entries in this row */                        \
265:     for (ii=N; ii>=_i; ii--) {                                                \
266:       rp2[ii+1] = rp2[ii];                                                \
267:       ap2[ii+1] = ap2[ii];                                                \
268:     }                                                                        \
269:     rp2[_i] = col;                                                        \
270:     ap2[_i] = value;                                                        \
271:     b_noinsert: ;                                                                \
272:     bilen[row] = nrow2;                                                        \
273: }

277: PetscErrorCode MatSetValuesRow_MPIAIJ(Mat A,PetscInt row,const PetscScalar v[])
278: {
279:   Mat_MPIAIJ     *mat = (Mat_MPIAIJ*)A->data;
280:   Mat_SeqAIJ     *a = (Mat_SeqAIJ*)mat->A->data,*b = (Mat_SeqAIJ*)mat->B->data;
282:   PetscInt       l,*garray = mat->garray,diag;

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

287:   /* find size of row to the left of the diagonal part */
288:   MatGetOwnershipRange(A,&diag,0);
289:   row  = row - diag;
290:   for (l=0; l<b->i[row+1]-b->i[row]; l++) {
291:     if (garray[b->j[b->i[row]+l]] > diag) break;
292:   }
293:   PetscMemcpy(b->a+b->i[row],v,l*sizeof(PetscScalar));

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

298:   /* right of diagonal part */
299:   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));
300:   return(0);
301: }

305: PetscErrorCode MatSetValues_MPIAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv)
306: {
307:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)mat->data;
308:   PetscScalar    value;
310:   PetscInt       i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend;
311:   PetscInt       cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col;
312:   PetscTruth     roworiented = aij->roworiented;

314:   /* Some Variables required in the macro */
315:   Mat            A = aij->A;
316:   Mat_SeqAIJ     *a = (Mat_SeqAIJ*)A->data;
317:   PetscInt       *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j;
318:   MatScalar      *aa = a->a;
319:   PetscTruth     ignorezeroentries = a->ignorezeroentries;
320:   Mat            B = aij->B;
321:   Mat_SeqAIJ     *b = (Mat_SeqAIJ*)B->data;
322:   PetscInt       *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n;
323:   MatScalar      *ba = b->a;

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

331:   for (i=0; i<m; i++) {
332:     if (im[i] < 0) continue;
333: #if defined(PETSC_USE_DEBUG)
334:     if (im[i] >= mat->rmap->N) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],mat->rmap->N-1);
335: #endif
336:     if (im[i] >= rstart && im[i] < rend) {
337:       row      = im[i] - rstart;
338:       lastcol1 = -1;
339:       rp1      = aj + ai[row];
340:       ap1      = aa + ai[row];
341:       rmax1    = aimax[row];
342:       nrow1    = ailen[row];
343:       low1     = 0;
344:       high1    = nrow1;
345:       lastcol2 = -1;
346:       rp2      = bj + bi[row];
347:       ap2      = ba + bi[row];
348:       rmax2    = bimax[row];
349:       nrow2    = bilen[row];
350:       low2     = 0;
351:       high2    = nrow2;

353:       for (j=0; j<n; j++) {
354:         if (v) {if (roworiented) value = v[i*n+j]; else value = v[i+j*m];} else value = 0.0;
355:         if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES)) continue;
356:         if (in[j] >= cstart && in[j] < cend){
357:           col = in[j] - cstart;
358:           MatSetValues_SeqAIJ_A_Private(row,col,value,addv);
359:         } else if (in[j] < 0) continue;
360: #if defined(PETSC_USE_DEBUG)
361:         else if (in[j] >= mat->cmap->N) {SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",in[j],mat->cmap->N-1);}
362: #endif
363:         else {
364:           if (mat->was_assembled) {
365:             if (!aij->colmap) {
366:               CreateColmap_MPIAIJ_Private(mat);
367:             }
368: #if defined (PETSC_USE_CTABLE)
369:             PetscTableFind(aij->colmap,in[j]+1,&col);
370:             col--;
371: #else
372:             col = aij->colmap[in[j]] - 1;
373: #endif
374:             if (col < 0 && !((Mat_SeqAIJ*)(aij->A->data))->nonew) {
375:               DisAssemble_MPIAIJ(mat);
376:               col =  in[j];
377:               /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */
378:               B = aij->B;
379:               b = (Mat_SeqAIJ*)B->data;
380:               bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j; ba = b->a;
381:               rp2      = bj + bi[row];
382:               ap2      = ba + bi[row];
383:               rmax2    = bimax[row];
384:               nrow2    = bilen[row];
385:               low2     = 0;
386:               high2    = nrow2;
387:               bm       = aij->B->rmap->n;
388:               ba = b->a;
389:             }
390:           } else col = in[j];
391:           MatSetValues_SeqAIJ_B_Private(row,col,value,addv);
392:         }
393:       }
394:     } else {
395:       if (!aij->donotstash) {
396:         if (roworiented) {
397:           MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscTruth)(ignorezeroentries && (addv == ADD_VALUES)));
398:         } else {
399:           MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscTruth)(ignorezeroentries && (addv == ADD_VALUES)));
400:         }
401:       }
402:     }
403:   }
404:   return(0);
405: }

409: PetscErrorCode MatGetValues_MPIAIJ(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[])
410: {
411:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)mat->data;
413:   PetscInt       i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend;
414:   PetscInt       cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col;

417:   for (i=0; i<m; i++) {
418:     if (idxm[i] < 0) continue; /* SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",idxm[i]);*/
419:     if (idxm[i] >= mat->rmap->N) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",idxm[i],mat->rmap->N-1);
420:     if (idxm[i] >= rstart && idxm[i] < rend) {
421:       row = idxm[i] - rstart;
422:       for (j=0; j<n; j++) {
423:         if (idxn[j] < 0) continue; /* SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"Negative column: %D",idxn[j]); */
424:         if (idxn[j] >= mat->cmap->N) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",idxn[j],mat->cmap->N-1);
425:         if (idxn[j] >= cstart && idxn[j] < cend){
426:           col = idxn[j] - cstart;
427:           MatGetValues(aij->A,1,&row,1,&col,v+i*n+j);
428:         } else {
429:           if (!aij->colmap) {
430:             CreateColmap_MPIAIJ_Private(mat);
431:           }
432: #if defined (PETSC_USE_CTABLE)
433:           PetscTableFind(aij->colmap,idxn[j]+1,&col);
434:           col --;
435: #else
436:           col = aij->colmap[idxn[j]] - 1;
437: #endif
438:           if ((col < 0) || (aij->garray[col] != idxn[j])) *(v+i*n+j) = 0.0;
439:           else {
440:             MatGetValues(aij->B,1,&row,1,&col,v+i*n+j);
441:           }
442:         }
443:       }
444:     } else {
445:       SETERRQ(PETSC_ERR_SUP,"Only local values currently supported");
446:     }
447:   }
448:   return(0);
449: }


455: PetscErrorCode MatAssemblyBegin_MPIAIJ(Mat mat,MatAssemblyType mode)
456: {
457:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)mat->data;
459:   PetscInt       nstash,reallocs;
460:   InsertMode     addv;

463:   if (aij->donotstash) {
464:     return(0);
465:   }

467:   /* make sure all processors are either in INSERTMODE or ADDMODE */
468:   MPI_Allreduce(&mat->insertmode,&addv,1,MPI_INT,MPI_BOR,((PetscObject)mat)->comm);
469:   if (addv == (ADD_VALUES|INSERT_VALUES)) {
470:     SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Some processors inserted others added");
471:   }
472:   mat->insertmode = addv; /* in case this processor had no cache */

474:   MatStashScatterBegin_Private(mat,&mat->stash,mat->rmap->range);
475:   MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);
476:   PetscInfo2(aij->A,"Stash has %D entries, uses %D mallocs.\n",nstash,reallocs);
477:   return(0);
478: }

482: PetscErrorCode MatAssemblyEnd_MPIAIJ(Mat mat,MatAssemblyType mode)
483: {
484:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)mat->data;
485:   Mat_SeqAIJ     *a=(Mat_SeqAIJ *)aij->A->data;
487:   PetscMPIInt    n;
488:   PetscInt       i,j,rstart,ncols,flg;
489:   PetscInt       *row,*col;
490:   PetscTruth     other_disassembled;
491:   PetscScalar    *val;
492:   InsertMode     addv = mat->insertmode;

494:   /* do not use 'b = (Mat_SeqAIJ *)aij->B->data' as B can be reset in disassembly */
496:   if (!aij->donotstash) {
497:     while (1) {
498:       MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);
499:       if (!flg) break;

501:       for (i=0; i<n;) {
502:         /* Now identify the consecutive vals belonging to the same row */
503:         for (j=i,rstart=row[j]; j<n; j++) { if (row[j] != rstart) break; }
504:         if (j < n) ncols = j-i;
505:         else       ncols = n-i;
506:         /* Now assemble all these values with a single function call */
507:         MatSetValues_MPIAIJ(mat,1,row+i,ncols,col+i,val+i,addv);
508:         i = j;
509:       }
510:     }
511:     MatStashScatterEnd_Private(&mat->stash);
512:   }
513:   a->compressedrow.use     = PETSC_FALSE;
514:   MatAssemblyBegin(aij->A,mode);
515:   MatAssemblyEnd(aij->A,mode);

517:   /* determine if any processor has disassembled, if so we must 
518:      also disassemble ourselfs, in order that we may reassemble. */
519:   /*
520:      if nonzero structure of submatrix B cannot change then we know that
521:      no processor disassembled thus we can skip this stuff
522:   */
523:   if (!((Mat_SeqAIJ*)aij->B->data)->nonew)  {
524:     MPI_Allreduce(&mat->was_assembled,&other_disassembled,1,MPI_INT,MPI_PROD,((PetscObject)mat)->comm);
525:     if (mat->was_assembled && !other_disassembled) {
526:       DisAssemble_MPIAIJ(mat);
527:     }
528:   }
529:   if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) {
530:     MatSetUpMultiply_MPIAIJ(mat);
531:   }
532:   MatSetOption(aij->B,MAT_USE_INODES,PETSC_FALSE);
533:   ((Mat_SeqAIJ *)aij->B->data)->compressedrow.use = PETSC_TRUE; /* b->compressedrow.use */
534:   MatAssemblyBegin(aij->B,mode);
535:   MatAssemblyEnd(aij->B,mode);

537:   PetscFree2(aij->rowvalues,aij->rowindices);
538:   aij->rowvalues = 0;

540:   /* used by MatAXPY() */
541:   a->xtoy = 0; ((Mat_SeqAIJ *)aij->B->data)->xtoy = 0;  /* b->xtoy = 0 */
542:   a->XtoY = 0; ((Mat_SeqAIJ *)aij->B->data)->XtoY = 0;  /* b->XtoY = 0 */

544:   if (aij->diag) {VecDestroy(aij->diag);aij->diag = 0;}
545:   if (a->inode.size) mat->ops->multdiagonalblock = MatMultDiagonalBlock_MPIAIJ;
546:   return(0);
547: }

551: PetscErrorCode MatZeroEntries_MPIAIJ(Mat A)
552: {
553:   Mat_MPIAIJ     *l = (Mat_MPIAIJ*)A->data;

557:   MatZeroEntries(l->A);
558:   MatZeroEntries(l->B);
559:   return(0);
560: }

564: PetscErrorCode MatZeroRows_MPIAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag)
565: {
566:   Mat_MPIAIJ     *l = (Mat_MPIAIJ*)A->data;
568:   PetscMPIInt    size = l->size,imdex,n,rank = l->rank,tag = ((PetscObject)A)->tag,lastidx = -1;
569:   PetscInt       i,*owners = A->rmap->range;
570:   PetscInt       *nprocs,j,idx,nsends,row;
571:   PetscInt       nmax,*svalues,*starts,*owner,nrecvs;
572:   PetscInt       *rvalues,count,base,slen,*source;
573:   PetscInt       *lens,*lrows,*values,rstart=A->rmap->rstart;
574:   MPI_Comm       comm = ((PetscObject)A)->comm;
575:   MPI_Request    *send_waits,*recv_waits;
576:   MPI_Status     recv_status,*send_status;
577: #if defined(PETSC_DEBUG)
578:   PetscTruth     found = PETSC_FALSE;
579: #endif

582:   /*  first count number of contributors to each processor */
583:   PetscMalloc(2*size*sizeof(PetscInt),&nprocs);
584:   PetscMemzero(nprocs,2*size*sizeof(PetscInt));
585:   PetscMalloc((N+1)*sizeof(PetscInt),&owner); /* see note*/
586:   j = 0;
587:   for (i=0; i<N; i++) {
588:     if (lastidx > (idx = rows[i])) j = 0;
589:     lastidx = idx;
590:     for (; j<size; j++) {
591:       if (idx >= owners[j] && idx < owners[j+1]) {
592:         nprocs[2*j]++;
593:         nprocs[2*j+1] = 1;
594:         owner[i] = j;
595: #if defined(PETSC_DEBUG)
596:         found = PETSC_TRUE;
597: #endif
598:         break;
599:       }
600:     }
601: #if defined(PETSC_DEBUG)
602:     if (!found) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Index out of range");
603:     found = PETSC_FALSE;
604: #endif
605:   }
606:   nsends = 0;  for (i=0; i<size; i++) { nsends += nprocs[2*i+1];}

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

611:   /* post receives:   */
612:   PetscMalloc((nrecvs+1)*(nmax+1)*sizeof(PetscInt),&rvalues);
613:   PetscMalloc((nrecvs+1)*sizeof(MPI_Request),&recv_waits);
614:   for (i=0; i<nrecvs; i++) {
615:     MPI_Irecv(rvalues+nmax*i,nmax,MPIU_INT,MPI_ANY_SOURCE,tag,comm,recv_waits+i);
616:   }

618:   /* do sends:
619:       1) starts[i] gives the starting index in svalues for stuff going to 
620:          the ith processor
621:   */
622:   PetscMalloc((N+1)*sizeof(PetscInt),&svalues);
623:   PetscMalloc((nsends+1)*sizeof(MPI_Request),&send_waits);
624:   PetscMalloc((size+1)*sizeof(PetscInt),&starts);
625:   starts[0] = 0;
626:   for (i=1; i<size; i++) { starts[i] = starts[i-1] + nprocs[2*i-2];}
627:   for (i=0; i<N; i++) {
628:     svalues[starts[owner[i]]++] = rows[i];
629:   }

631:   starts[0] = 0;
632:   for (i=1; i<size+1; i++) { starts[i] = starts[i-1] + nprocs[2*i-2];}
633:   count = 0;
634:   for (i=0; i<size; i++) {
635:     if (nprocs[2*i+1]) {
636:       MPI_Isend(svalues+starts[i],nprocs[2*i],MPIU_INT,i,tag,comm,send_waits+count++);
637:     }
638:   }
639:   PetscFree(starts);

641:   base = owners[rank];

643:   /*  wait on receives */
644:   PetscMalloc2(nrecvs,PetscInt,&lens,nrecvs,PetscInt,&source);
645:   count  = nrecvs; slen = 0;
646:   while (count) {
647:     MPI_Waitany(nrecvs,recv_waits,&imdex,&recv_status);
648:     /* unpack receives into our local space */
649:     MPI_Get_count(&recv_status,MPIU_INT,&n);
650:     source[imdex]  = recv_status.MPI_SOURCE;
651:     lens[imdex]    = n;
652:     slen          += n;
653:     count--;
654:   }
655:   PetscFree(recv_waits);
656: 
657:   /* move the data into the send scatter */
658:   PetscMalloc((slen+1)*sizeof(PetscInt),&lrows);
659:   count = 0;
660:   for (i=0; i<nrecvs; i++) {
661:     values = rvalues + i*nmax;
662:     for (j=0; j<lens[i]; j++) {
663:       lrows[count++] = values[j] - base;
664:     }
665:   }
666:   PetscFree(rvalues);
667:   PetscFree2(lens,source);
668:   PetscFree(owner);
669:   PetscFree(nprocs);
670: 
671:   /* actually zap the local rows */
672:   /*
673:         Zero the required rows. If the "diagonal block" of the matrix
674:      is square and the user wishes to set the diagonal we use separate
675:      code so that MatSetValues() is not called for each diagonal allocating
676:      new memory, thus calling lots of mallocs and slowing things down.

678:   */
679:   /* must zero l->B before l->A because the (diag) case below may put values into l->B*/
680:   MatZeroRows(l->B,slen,lrows,0.0);
681:   if ((diag != 0.0) && (l->A->rmap->N == l->A->cmap->N)) {
682:     MatZeroRows(l->A,slen,lrows,diag);
683:   } else if (diag != 0.0) {
684:     MatZeroRows(l->A,slen,lrows,0.0);
685:     if (((Mat_SeqAIJ*)l->A->data)->nonew) {
686:       SETERRQ(PETSC_ERR_SUP,"MatZeroRows() on rectangular matrices cannot be used with the Mat options\n\
687: MAT_NEW_NONZERO_LOCATIONS,MAT_NEW_NONZERO_LOCATION_ERR,MAT_NEW_NONZERO_ALLOCATION_ERR");
688:     }
689:     for (i = 0; i < slen; i++) {
690:       row  = lrows[i] + rstart;
691:       MatSetValues(A,1,&row,1,&row,&diag,INSERT_VALUES);
692:     }
693:     MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);
694:     MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);
695:   } else {
696:     MatZeroRows(l->A,slen,lrows,0.0);
697:   }
698:   PetscFree(lrows);

700:   /* wait on sends */
701:   if (nsends) {
702:     PetscMalloc(nsends*sizeof(MPI_Status),&send_status);
703:     MPI_Waitall(nsends,send_waits,send_status);
704:     PetscFree(send_status);
705:   }
706:   PetscFree(send_waits);
707:   PetscFree(svalues);

709:   return(0);
710: }

714: PetscErrorCode MatMult_MPIAIJ(Mat A,Vec xx,Vec yy)
715: {
716:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;
718:   PetscInt       nt;

721:   VecGetLocalSize(xx,&nt);
722:   if (nt != A->cmap->n) {
723:     SETERRQ2(PETSC_ERR_ARG_SIZ,"Incompatible partition of A (%D) and xx (%D)",A->cmap->n,nt);
724:   }
725:   VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
726:   (*a->A->ops->mult)(a->A,xx,yy);
727:   VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
728:   (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);
729:   return(0);
730: }

734: PetscErrorCode MatMultDiagonalBlock_MPIAIJ(Mat A,Vec bb,Vec xx)
735: {
736:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;
738: 
740:   MatMultDiagonalBlock(a->A,bb,xx);
741:   return(0);
742: }

746: PetscErrorCode MatMultAdd_MPIAIJ(Mat A,Vec xx,Vec yy,Vec zz)
747: {
748:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;

752:   VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
753:   (*a->A->ops->multadd)(a->A,xx,yy,zz);
754:   VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
755:   (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);
756:   return(0);
757: }

761: PetscErrorCode MatMultTranspose_MPIAIJ(Mat A,Vec xx,Vec yy)
762: {
763:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;
765:   PetscTruth     merged;

768:   VecScatterGetMerged(a->Mvctx,&merged);
769:   /* do nondiagonal part */
770:   (*a->B->ops->multtranspose)(a->B,xx,a->lvec);
771:   if (!merged) {
772:     /* send it on its way */
773:     VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
774:     /* do local part */
775:     (*a->A->ops->multtranspose)(a->A,xx,yy);
776:     /* receive remote parts: note this assumes the values are not actually */
777:     /* added in yy until the next line, */
778:     VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
779:   } else {
780:     /* do local part */
781:     (*a->A->ops->multtranspose)(a->A,xx,yy);
782:     /* send it on its way */
783:     VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
784:     /* values actually were received in the Begin() but we need to call this nop */
785:     VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
786:   }
787:   return(0);
788: }

793: PetscErrorCode  MatIsTranspose_MPIAIJ(Mat Amat,Mat Bmat,PetscReal tol,PetscTruth *f)
794: {
795:   MPI_Comm       comm;
796:   Mat_MPIAIJ     *Aij = (Mat_MPIAIJ *) Amat->data, *Bij;
797:   Mat            Adia = Aij->A, Bdia, Aoff,Boff,*Aoffs,*Boffs;
798:   IS             Me,Notme;
800:   PetscInt       M,N,first,last,*notme,i;
801:   PetscMPIInt    size;


805:   /* Easy test: symmetric diagonal block */
806:   Bij = (Mat_MPIAIJ *) Bmat->data; Bdia = Bij->A;
807:   MatIsTranspose(Adia,Bdia,tol,f);
808:   if (!*f) return(0);
809:   PetscObjectGetComm((PetscObject)Amat,&comm);
810:   MPI_Comm_size(comm,&size);
811:   if (size == 1) return(0);

813:   /* Hard test: off-diagonal block. This takes a MatGetSubMatrix. */
814:   MatGetSize(Amat,&M,&N);
815:   MatGetOwnershipRange(Amat,&first,&last);
816:   PetscMalloc((N-last+first)*sizeof(PetscInt),&notme);
817:   for (i=0; i<first; i++) notme[i] = i;
818:   for (i=last; i<M; i++) notme[i-last+first] = i;
819:   ISCreateGeneral(MPI_COMM_SELF,N-last+first,notme,&Notme);
820:   ISCreateStride(MPI_COMM_SELF,last-first,first,1,&Me);
821:   MatGetSubMatrices(Amat,1,&Me,&Notme,MAT_INITIAL_MATRIX,&Aoffs);
822:   Aoff = Aoffs[0];
823:   MatGetSubMatrices(Bmat,1,&Notme,&Me,MAT_INITIAL_MATRIX,&Boffs);
824:   Boff = Boffs[0];
825:   MatIsTranspose(Aoff,Boff,tol,f);
826:   MatDestroyMatrices(1,&Aoffs);
827:   MatDestroyMatrices(1,&Boffs);
828:   ISDestroy(Me);
829:   ISDestroy(Notme);

831:   return(0);
832: }

837: PetscErrorCode MatMultTransposeAdd_MPIAIJ(Mat A,Vec xx,Vec yy,Vec zz)
838: {
839:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;

843:   /* do nondiagonal part */
844:   (*a->B->ops->multtranspose)(a->B,xx,a->lvec);
845:   /* send it on its way */
846:   VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);
847:   /* do local part */
848:   (*a->A->ops->multtransposeadd)(a->A,xx,yy,zz);
849:   /* receive remote parts */
850:   VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);
851:   return(0);
852: }

854: /*
855:   This only works correctly for square matrices where the subblock A->A is the 
856:    diagonal block
857: */
860: PetscErrorCode MatGetDiagonal_MPIAIJ(Mat A,Vec v)
861: {
863:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;

866:   if (A->rmap->N != A->cmap->N) SETERRQ(PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block");
867:   if (A->rmap->rstart != A->cmap->rstart || A->rmap->rend != A->cmap->rend) {
868:     SETERRQ(PETSC_ERR_ARG_SIZ,"row partition must equal col partition");
869:   }
870:   MatGetDiagonal(a->A,v);
871:   return(0);
872: }

876: PetscErrorCode MatScale_MPIAIJ(Mat A,PetscScalar aa)
877: {
878:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;

882:   MatScale(a->A,aa);
883:   MatScale(a->B,aa);
884:   return(0);
885: }

889: PetscErrorCode MatDestroy_MPIAIJ(Mat mat)
890: {
891:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)mat->data;

895: #if defined(PETSC_USE_LOG)
896:   PetscLogObjectState((PetscObject)mat,"Rows=%D, Cols=%D",mat->rmap->N,mat->cmap->N);
897: #endif
898:   MatStashDestroy_Private(&mat->stash);
899:   if (aij->diag) {VecDestroy(aij->diag);}
900:   MatDestroy(aij->A);
901:   MatDestroy(aij->B);
902: #if defined (PETSC_USE_CTABLE)
903:   if (aij->colmap) {PetscTableDestroy(aij->colmap);}
904: #else
905:   PetscFree(aij->colmap);
906: #endif
907:   PetscFree(aij->garray);
908:   if (aij->lvec)   {VecDestroy(aij->lvec);}
909:   if (aij->Mvctx)  {VecScatterDestroy(aij->Mvctx);}
910:   PetscFree2(aij->rowvalues,aij->rowindices);
911:   PetscFree(aij->ld);
912:   PetscFree(aij);

914:   PetscObjectChangeTypeName((PetscObject)mat,0);
915:   PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C","",PETSC_NULL);
916:   PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C","",PETSC_NULL);
917:   PetscObjectComposeFunction((PetscObject)mat,"MatGetDiagonalBlock_C","",PETSC_NULL);
918:   PetscObjectComposeFunction((PetscObject)mat,"MatIsTranspose_C","",PETSC_NULL);
919:   PetscObjectComposeFunction((PetscObject)mat,"MatMPIAIJSetPreallocation_C","",PETSC_NULL);
920:   PetscObjectComposeFunction((PetscObject)mat,"MatMPIAIJSetPreallocationCSR_C","",PETSC_NULL);
921:   PetscObjectComposeFunction((PetscObject)mat,"MatDiagonalScaleLocal_C","",PETSC_NULL);
922:   PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpiaij_mpisbaij_C","",PETSC_NULL);
923:   return(0);
924: }

928: PetscErrorCode MatView_MPIAIJ_Binary(Mat mat,PetscViewer viewer)
929: {
930:   Mat_MPIAIJ        *aij = (Mat_MPIAIJ*)mat->data;
931:   Mat_SeqAIJ*       A = (Mat_SeqAIJ*)aij->A->data;
932:   Mat_SeqAIJ*       B = (Mat_SeqAIJ*)aij->B->data;
933:   PetscErrorCode    ierr;
934:   PetscMPIInt       rank,size,tag = ((PetscObject)viewer)->tag;
935:   int               fd;
936:   PetscInt          nz,header[4],*row_lengths,*range=0,rlen,i;
937:   PetscInt          nzmax,*column_indices,j,k,col,*garray = aij->garray,cnt,cstart = mat->cmap->rstart,rnz;
938:   PetscScalar       *column_values;

941:   MPI_Comm_rank(((PetscObject)mat)->comm,&rank);
942:   MPI_Comm_size(((PetscObject)mat)->comm,&size);
943:   nz   = A->nz + B->nz;
944:   if (!rank) {
945:     header[0] = MAT_FILE_COOKIE;
946:     header[1] = mat->rmap->N;
947:     header[2] = mat->cmap->N;
948:     MPI_Reduce(&nz,&header[3],1,MPIU_INT,MPI_SUM,0,((PetscObject)mat)->comm);
949:     PetscViewerBinaryGetDescriptor(viewer,&fd);
950:     PetscBinaryWrite(fd,header,4,PETSC_INT,PETSC_TRUE);
951:     /* get largest number of rows any processor has */
952:     rlen = mat->rmap->n;
953:     range = mat->rmap->range;
954:     for (i=1; i<size; i++) {
955:       rlen = PetscMax(rlen,range[i+1] - range[i]);
956:     }
957:   } else {
958:     MPI_Reduce(&nz,0,1,MPIU_INT,MPI_SUM,0,((PetscObject)mat)->comm);
959:     rlen = mat->rmap->n;
960:   }

962:   /* load up the local row counts */
963:   PetscMalloc((rlen+1)*sizeof(PetscInt),&row_lengths);
964:   for (i=0; i<mat->rmap->n; i++) {
965:     row_lengths[i] = A->i[i+1] - A->i[i] + B->i[i+1] - B->i[i];
966:   }

968:   /* store the row lengths to the file */
969:   if (!rank) {
970:     MPI_Status status;
971:     PetscBinaryWrite(fd,row_lengths,mat->rmap->n,PETSC_INT,PETSC_TRUE);
972:     for (i=1; i<size; i++) {
973:       rlen = range[i+1] - range[i];
974:       MPI_Recv(row_lengths,rlen,MPIU_INT,i,tag,((PetscObject)mat)->comm,&status);
975:       PetscBinaryWrite(fd,row_lengths,rlen,PETSC_INT,PETSC_TRUE);
976:     }
977:   } else {
978:     MPI_Send(row_lengths,mat->rmap->n,MPIU_INT,0,tag,((PetscObject)mat)->comm);
979:   }
980:   PetscFree(row_lengths);

982:   /* load up the local column indices */
983:   nzmax = nz; /* )th processor needs space a largest processor needs */
984:   MPI_Reduce(&nz,&nzmax,1,MPIU_INT,MPI_MAX,0,((PetscObject)mat)->comm);
985:   PetscMalloc((nzmax+1)*sizeof(PetscInt),&column_indices);
986:   cnt  = 0;
987:   for (i=0; i<mat->rmap->n; i++) {
988:     for (j=B->i[i]; j<B->i[i+1]; j++) {
989:       if ( (col = garray[B->j[j]]) > cstart) break;
990:       column_indices[cnt++] = col;
991:     }
992:     for (k=A->i[i]; k<A->i[i+1]; k++) {
993:       column_indices[cnt++] = A->j[k] + cstart;
994:     }
995:     for (; j<B->i[i+1]; j++) {
996:       column_indices[cnt++] = garray[B->j[j]];
997:     }
998:   }
999:   if (cnt != A->nz + B->nz) SETERRQ2(PETSC_ERR_LIB,"Internal PETSc error: cnt = %D nz = %D",cnt,A->nz+B->nz);

1001:   /* store the column indices to the file */
1002:   if (!rank) {
1003:     MPI_Status status;
1004:     PetscBinaryWrite(fd,column_indices,nz,PETSC_INT,PETSC_TRUE);
1005:     for (i=1; i<size; i++) {
1006:       MPI_Recv(&rnz,1,MPIU_INT,i,tag,((PetscObject)mat)->comm,&status);
1007:       if (rnz > nzmax) SETERRQ2(PETSC_ERR_LIB,"Internal PETSc error: nz = %D nzmax = %D",nz,nzmax);
1008:       MPI_Recv(column_indices,rnz,MPIU_INT,i,tag,((PetscObject)mat)->comm,&status);
1009:       PetscBinaryWrite(fd,column_indices,rnz,PETSC_INT,PETSC_TRUE);
1010:     }
1011:   } else {
1012:     MPI_Send(&nz,1,MPIU_INT,0,tag,((PetscObject)mat)->comm);
1013:     MPI_Send(column_indices,nz,MPIU_INT,0,tag,((PetscObject)mat)->comm);
1014:   }
1015:   PetscFree(column_indices);

1017:   /* load up the local column values */
1018:   PetscMalloc((nzmax+1)*sizeof(PetscScalar),&column_values);
1019:   cnt  = 0;
1020:   for (i=0; i<mat->rmap->n; i++) {
1021:     for (j=B->i[i]; j<B->i[i+1]; j++) {
1022:       if ( garray[B->j[j]] > cstart) break;
1023:       column_values[cnt++] = B->a[j];
1024:     }
1025:     for (k=A->i[i]; k<A->i[i+1]; k++) {
1026:       column_values[cnt++] = A->a[k];
1027:     }
1028:     for (; j<B->i[i+1]; j++) {
1029:       column_values[cnt++] = B->a[j];
1030:     }
1031:   }
1032:   if (cnt != A->nz + B->nz) SETERRQ2(PETSC_ERR_PLIB,"Internal PETSc error: cnt = %D nz = %D",cnt,A->nz+B->nz);

1034:   /* store the column values to the file */
1035:   if (!rank) {
1036:     MPI_Status status;
1037:     PetscBinaryWrite(fd,column_values,nz,PETSC_SCALAR,PETSC_TRUE);
1038:     for (i=1; i<size; i++) {
1039:       MPI_Recv(&rnz,1,MPIU_INT,i,tag,((PetscObject)mat)->comm,&status);
1040:       if (rnz > nzmax) SETERRQ2(PETSC_ERR_LIB,"Internal PETSc error: nz = %D nzmax = %D",nz,nzmax);
1041:       MPI_Recv(column_values,rnz,MPIU_SCALAR,i,tag,((PetscObject)mat)->comm,&status);
1042:       PetscBinaryWrite(fd,column_values,rnz,PETSC_SCALAR,PETSC_TRUE);
1043:     }
1044:   } else {
1045:     MPI_Send(&nz,1,MPIU_INT,0,tag,((PetscObject)mat)->comm);
1046:     MPI_Send(column_values,nz,MPIU_SCALAR,0,tag,((PetscObject)mat)->comm);
1047:   }
1048:   PetscFree(column_values);
1049:   return(0);
1050: }

1054: PetscErrorCode MatView_MPIAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer)
1055: {
1056:   Mat_MPIAIJ        *aij = (Mat_MPIAIJ*)mat->data;
1057:   PetscErrorCode    ierr;
1058:   PetscMPIInt       rank = aij->rank,size = aij->size;
1059:   PetscTruth        isdraw,iascii,isbinary;
1060:   PetscViewer       sviewer;
1061:   PetscViewerFormat format;

1064:   PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_DRAW,&isdraw);
1065:   PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&iascii);
1066:   PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_BINARY,&isbinary);
1067:   if (iascii) {
1068:     PetscViewerGetFormat(viewer,&format);
1069:     if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) {
1070:       MatInfo    info;
1071:       PetscTruth inodes;

1073:       MPI_Comm_rank(((PetscObject)mat)->comm,&rank);
1074:       MatGetInfo(mat,MAT_LOCAL,&info);
1075:       MatInodeGetInodeSizes(aij->A,PETSC_NULL,(PetscInt **)&inodes,PETSC_NULL);
1076:       if (!inodes) {
1077:         PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D mem %D, not using I-node routines\n",
1078:                                               rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(PetscInt)info.memory);
1079:       } else {
1080:         PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D mem %D, using I-node routines\n",
1081:                     rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(PetscInt)info.memory);
1082:       }
1083:       MatGetInfo(aij->A,MAT_LOCAL,&info);
1084:       PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);
1085:       MatGetInfo(aij->B,MAT_LOCAL,&info);
1086:       PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);
1087:       PetscViewerFlush(viewer);
1088:       PetscViewerASCIIPrintf(viewer,"Information on VecScatter used in matrix-vector product: \n");
1089:       VecScatterView(aij->Mvctx,viewer);
1090:       return(0);
1091:     } else if (format == PETSC_VIEWER_ASCII_INFO) {
1092:       PetscInt   inodecount,inodelimit,*inodes;
1093:       MatInodeGetInodeSizes(aij->A,&inodecount,&inodes,&inodelimit);
1094:       if (inodes) {
1095:         PetscViewerASCIIPrintf(viewer,"using I-node (on process 0) routines: found %D nodes, limit used is %D\n",inodecount,inodelimit);
1096:       } else {
1097:         PetscViewerASCIIPrintf(viewer,"not using I-node (on process 0) routines\n");
1098:       }
1099:       return(0);
1100:     } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) {
1101:       return(0);
1102:     }
1103:   } else if (isbinary) {
1104:     if (size == 1) {
1105:       PetscObjectSetName((PetscObject)aij->A,((PetscObject)mat)->name);
1106:       MatView(aij->A,viewer);
1107:     } else {
1108:       MatView_MPIAIJ_Binary(mat,viewer);
1109:     }
1110:     return(0);
1111:   } else if (isdraw) {
1112:     PetscDraw  draw;
1113:     PetscTruth isnull;
1114:     PetscViewerDrawGetDraw(viewer,0,&draw);
1115:     PetscDrawIsNull(draw,&isnull); if (isnull) return(0);
1116:   }

1118:   if (size == 1) {
1119:     PetscObjectSetName((PetscObject)aij->A,((PetscObject)mat)->name);
1120:     MatView(aij->A,viewer);
1121:   } else {
1122:     /* assemble the entire matrix onto first processor. */
1123:     Mat         A;
1124:     Mat_SeqAIJ  *Aloc;
1125:     PetscInt    M = mat->rmap->N,N = mat->cmap->N,m,*ai,*aj,row,*cols,i,*ct;
1126:     MatScalar   *a;

1128:     if (mat->rmap->N > 1024) {
1129:       PetscTruth flg = PETSC_FALSE;

1131:       PetscOptionsGetTruth(((PetscObject) mat)->prefix, "-mat_ascii_output_large", &flg,PETSC_NULL);
1132:       if (!flg) {
1133:         SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"ASCII matrix output not allowed for matrices with more than 1024 rows, use binary format instead.\nYou can override this restriction using -mat_ascii_output_large.");
1134:       }
1135:     }

1137:     MatCreate(((PetscObject)mat)->comm,&A);
1138:     if (!rank) {
1139:       MatSetSizes(A,M,N,M,N);
1140:     } else {
1141:       MatSetSizes(A,0,0,M,N);
1142:     }
1143:     /* This is just a temporary matrix, so explicitly using MATMPIAIJ is probably best */
1144:     MatSetType(A,MATMPIAIJ);
1145:     MatMPIAIJSetPreallocation(A,0,PETSC_NULL,0,PETSC_NULL);
1146:     PetscLogObjectParent(mat,A);

1148:     /* copy over the A part */
1149:     Aloc = (Mat_SeqAIJ*)aij->A->data;
1150:     m = aij->A->rmap->n; ai = Aloc->i; aj = Aloc->j; a = Aloc->a;
1151:     row = mat->rmap->rstart;
1152:     for (i=0; i<ai[m]; i++) {aj[i] += mat->cmap->rstart ;}
1153:     for (i=0; i<m; i++) {
1154:       MatSetValues(A,1,&row,ai[i+1]-ai[i],aj,a,INSERT_VALUES);
1155:       row++; a += ai[i+1]-ai[i]; aj += ai[i+1]-ai[i];
1156:     }
1157:     aj = Aloc->j;
1158:     for (i=0; i<ai[m]; i++) {aj[i] -= mat->cmap->rstart;}

1160:     /* copy over the B part */
1161:     Aloc = (Mat_SeqAIJ*)aij->B->data;
1162:     m    = aij->B->rmap->n;  ai = Aloc->i; aj = Aloc->j; a = Aloc->a;
1163:     row  = mat->rmap->rstart;
1164:     PetscMalloc((ai[m]+1)*sizeof(PetscInt),&cols);
1165:     ct   = cols;
1166:     for (i=0; i<ai[m]; i++) {cols[i] = aij->garray[aj[i]];}
1167:     for (i=0; i<m; i++) {
1168:       MatSetValues(A,1,&row,ai[i+1]-ai[i],cols,a,INSERT_VALUES);
1169:       row++; a += ai[i+1]-ai[i]; cols += ai[i+1]-ai[i];
1170:     }
1171:     PetscFree(ct);
1172:     MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);
1173:     MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);
1174:     /* 
1175:        Everyone has to call to draw the matrix since the graphics waits are
1176:        synchronized across all processors that share the PetscDraw object
1177:     */
1178:     PetscViewerGetSingleton(viewer,&sviewer);
1179:     if (!rank) {
1180:       PetscObjectSetName((PetscObject)((Mat_MPIAIJ*)(A->data))->A,((PetscObject)mat)->name);
1181:       MatView(((Mat_MPIAIJ*)(A->data))->A,sviewer);
1182:     }
1183:     PetscViewerRestoreSingleton(viewer,&sviewer);
1184:     MatDestroy(A);
1185:   }
1186:   return(0);
1187: }

1191: PetscErrorCode MatView_MPIAIJ(Mat mat,PetscViewer viewer)
1192: {
1194:   PetscTruth     iascii,isdraw,issocket,isbinary;
1195: 
1197:   PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&iascii);
1198:   PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_DRAW,&isdraw);
1199:   PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_BINARY,&isbinary);
1200:   PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_SOCKET,&issocket);
1201:   if (iascii || isdraw || isbinary || issocket) {
1202:     MatView_MPIAIJ_ASCIIorDraworSocket(mat,viewer);
1203:   } else {
1204:     SETERRQ1(PETSC_ERR_SUP,"Viewer type %s not supported by MPIAIJ matrices",((PetscObject)viewer)->type_name);
1205:   }
1206:   return(0);
1207: }

1211: PetscErrorCode MatSOR_MPIAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx)
1212: {
1213:   Mat_MPIAIJ     *mat = (Mat_MPIAIJ*)matin->data;
1215:   Vec            bb1 = 0;
1216:   PetscTruth     hasop;

1219:   if (its > 1 || ~flag & SOR_ZERO_INITIAL_GUESS || flag & SOR_EISENSTAT) {
1220:     VecDuplicate(bb,&bb1);
1221:   }

1223:   if (flag == SOR_APPLY_UPPER) {
1224:     (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
1225:     return(0);
1226:   }

1228:   if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP){
1229:     if (flag & SOR_ZERO_INITIAL_GUESS) {
1230:       (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
1231:       its--;
1232:     }
1233: 
1234:     while (its--) {
1235:       VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
1236:       VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);

1238:       /* update rhs: bb1 = bb - B*x */
1239:       VecScale(mat->lvec,-1.0);
1240:       (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);

1242:       /* local sweep */
1243:       (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,1,xx);
1244:     }
1245:   } else if (flag & SOR_LOCAL_FORWARD_SWEEP){
1246:     if (flag & SOR_ZERO_INITIAL_GUESS) {
1247:       (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
1248:       its--;
1249:     }
1250:     while (its--) {
1251:       VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
1252:       VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);

1254:       /* update rhs: bb1 = bb - B*x */
1255:       VecScale(mat->lvec,-1.0);
1256:       (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);

1258:       /* local sweep */
1259:       (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_FORWARD_SWEEP,fshift,lits,1,xx);
1260:     }
1261:   } else if (flag & SOR_LOCAL_BACKWARD_SWEEP){
1262:     if (flag & SOR_ZERO_INITIAL_GUESS) {
1263:       (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
1264:       its--;
1265:     }
1266:     while (its--) {
1267:       VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
1268:       VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);

1270:       /* update rhs: bb1 = bb - B*x */
1271:       VecScale(mat->lvec,-1.0);
1272:       (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);

1274:       /* local sweep */
1275:       (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_BACKWARD_SWEEP,fshift,lits,1,xx);
1276:     }
1277:   }  else if (flag & SOR_EISENSTAT) {
1278:     Vec         xx1;

1280:     VecDuplicate(bb,&xx1);
1281:     (*mat->A->ops->sor)(mat->A,bb,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_BACKWARD_SWEEP),fshift,lits,1,xx);

1283:     VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
1284:     VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
1285:     if (!mat->diag) {
1286:       MatGetVecs(matin,&mat->diag,PETSC_NULL);
1287:       MatGetDiagonal(matin,mat->diag);
1288:     }
1289:     MatHasOperation(matin,MATOP_MULT_DIAGONAL_BLOCK,&hasop);
1290:     if (hasop) {
1291:       MatMultDiagonalBlock(matin,xx,bb1);
1292:     } else {
1293:       VecPointwiseMult(bb1,mat->diag,xx);
1294:     }
1295:     VecAYPX(bb1,(omega-2.0)/omega,bb);

1297:     MatMultAdd(mat->B,mat->lvec,bb1,bb1);

1299:     /* local sweep */
1300:     (*mat->A->ops->sor)(mat->A,bb1,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_FORWARD_SWEEP),fshift,lits,1,xx1);
1301:     VecAXPY(xx,1.0,xx1);
1302:     VecDestroy(xx1);
1303:   } else {
1304:     SETERRQ(PETSC_ERR_SUP,"Parallel SOR not supported");
1305:   }

1307:   if (bb1) {VecDestroy(bb1);}
1308:   return(0);
1309: }

1313: PetscErrorCode MatPermute_MPIAIJ(Mat A,IS rowp,IS colp,Mat *B)
1314: {
1315:   MPI_Comm       comm,pcomm;
1316:   PetscInt       first,local_size,nrows;
1317:   const PetscInt *rows;
1318:   PetscMPIInt    size;
1319:   IS             crowp,growp,irowp,lrowp,lcolp,icolp;

1323:   PetscObjectGetComm((PetscObject)A,&comm);
1324:   /* make a collective version of 'rowp' */
1325:   PetscObjectGetComm((PetscObject)rowp,&pcomm);
1326:   if (pcomm==comm) {
1327:     crowp = rowp;
1328:   } else {
1329:     ISGetSize(rowp,&nrows);
1330:     ISGetIndices(rowp,&rows);
1331:     ISCreateGeneral(comm,nrows,rows,&crowp);
1332:     ISRestoreIndices(rowp,&rows);
1333:   }
1334:   /* collect the global row permutation and invert it */
1335:   ISAllGather(crowp,&growp);
1336:   ISSetPermutation(growp);
1337:   if (pcomm!=comm) {
1338:     ISDestroy(crowp);
1339:   }
1340:   ISInvertPermutation(growp,PETSC_DECIDE,&irowp);
1341:   /* get the local target indices */
1342:   MatGetOwnershipRange(A,&first,PETSC_NULL);
1343:   MatGetLocalSize(A,&local_size,PETSC_NULL);
1344:   ISGetIndices(irowp,&rows);
1345:   ISCreateGeneral(MPI_COMM_SELF,local_size,rows+first,&lrowp);
1346:   ISRestoreIndices(irowp,&rows);
1347:   ISDestroy(irowp);
1348:   /* the column permutation is so much easier;
1349:      make a local version of 'colp' and invert it */
1350:   PetscObjectGetComm((PetscObject)colp,&pcomm);
1351:   MPI_Comm_size(pcomm,&size);
1352:   if (size==1) {
1353:     lcolp = colp;
1354:   } else {
1355:     ISGetSize(colp,&nrows);
1356:     ISGetIndices(colp,&rows);
1357:     ISCreateGeneral(MPI_COMM_SELF,nrows,rows,&lcolp);
1358:   }
1359:   ISSetPermutation(lcolp);
1360:   ISInvertPermutation(lcolp,PETSC_DECIDE,&icolp);
1361:   ISSetPermutation(icolp);
1362:   if (size>1) {
1363:     ISRestoreIndices(colp,&rows);
1364:     ISDestroy(lcolp);
1365:   }
1366:   /* now we just get the submatrix */
1367:   MatGetSubMatrix_MPIAIJ_Private(A,lrowp,icolp,local_size,MAT_INITIAL_MATRIX,B);
1368:   /* clean up */
1369:   ISDestroy(lrowp);
1370:   ISDestroy(icolp);
1371:   return(0);
1372: }

1376: PetscErrorCode MatGetInfo_MPIAIJ(Mat matin,MatInfoType flag,MatInfo *info)
1377: {
1378:   Mat_MPIAIJ     *mat = (Mat_MPIAIJ*)matin->data;
1379:   Mat            A = mat->A,B = mat->B;
1381:   PetscReal      isend[5],irecv[5];

1384:   info->block_size     = 1.0;
1385:   MatGetInfo(A,MAT_LOCAL,info);
1386:   isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded;
1387:   isend[3] = info->memory;  isend[4] = info->mallocs;
1388:   MatGetInfo(B,MAT_LOCAL,info);
1389:   isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded;
1390:   isend[3] += info->memory;  isend[4] += info->mallocs;
1391:   if (flag == MAT_LOCAL) {
1392:     info->nz_used      = isend[0];
1393:     info->nz_allocated = isend[1];
1394:     info->nz_unneeded  = isend[2];
1395:     info->memory       = isend[3];
1396:     info->mallocs      = isend[4];
1397:   } else if (flag == MAT_GLOBAL_MAX) {
1398:     MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPI_MAX,((PetscObject)matin)->comm);
1399:     info->nz_used      = irecv[0];
1400:     info->nz_allocated = irecv[1];
1401:     info->nz_unneeded  = irecv[2];
1402:     info->memory       = irecv[3];
1403:     info->mallocs      = irecv[4];
1404:   } else if (flag == MAT_GLOBAL_SUM) {
1405:     MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPI_SUM,((PetscObject)matin)->comm);
1406:     info->nz_used      = irecv[0];
1407:     info->nz_allocated = irecv[1];
1408:     info->nz_unneeded  = irecv[2];
1409:     info->memory       = irecv[3];
1410:     info->mallocs      = irecv[4];
1411:   }
1412:   info->fill_ratio_given  = 0; /* no parallel LU/ILU/Cholesky */
1413:   info->fill_ratio_needed = 0;
1414:   info->factor_mallocs    = 0;

1416:   return(0);
1417: }

1421: PetscErrorCode MatSetOption_MPIAIJ(Mat A,MatOption op,PetscTruth flg)
1422: {
1423:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;

1427:   switch (op) {
1428:   case MAT_NEW_NONZERO_LOCATIONS:
1429:   case MAT_NEW_NONZERO_ALLOCATION_ERR:
1430:   case MAT_UNUSED_NONZERO_LOCATION_ERR:
1431:   case MAT_KEEP_NONZERO_PATTERN:
1432:   case MAT_NEW_NONZERO_LOCATION_ERR:
1433:   case MAT_USE_INODES:
1434:   case MAT_IGNORE_ZERO_ENTRIES:
1435:     MatSetOption(a->A,op,flg);
1436:     MatSetOption(a->B,op,flg);
1437:     break;
1438:   case MAT_ROW_ORIENTED:
1439:     a->roworiented = flg;
1440:     MatSetOption(a->A,op,flg);
1441:     MatSetOption(a->B,op,flg);
1442:     break;
1443:   case MAT_NEW_DIAGONALS:
1444:     PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);
1445:     break;
1446:   case MAT_IGNORE_OFF_PROC_ENTRIES:
1447:     a->donotstash = PETSC_TRUE;
1448:     break;
1449:   case MAT_SYMMETRIC:
1450:     MatSetOption(a->A,op,flg);
1451:     break;
1452:   case MAT_STRUCTURALLY_SYMMETRIC:
1453:     MatSetOption(a->A,op,flg);
1454:     break;
1455:   case MAT_HERMITIAN:
1456:     MatSetOption(a->A,op,flg);
1457:     break;
1458:   case MAT_SYMMETRY_ETERNAL:
1459:     MatSetOption(a->A,op,flg);
1460:     break;
1461:   default:
1462:     SETERRQ1(PETSC_ERR_SUP,"unknown option %d",op);
1463:   }
1464:   return(0);
1465: }

1469: PetscErrorCode MatGetRow_MPIAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
1470: {
1471:   Mat_MPIAIJ     *mat = (Mat_MPIAIJ*)matin->data;
1472:   PetscScalar    *vworkA,*vworkB,**pvA,**pvB,*v_p;
1474:   PetscInt       i,*cworkA,*cworkB,**pcA,**pcB,cstart = matin->cmap->rstart;
1475:   PetscInt       nztot,nzA,nzB,lrow,rstart = matin->rmap->rstart,rend = matin->rmap->rend;
1476:   PetscInt       *cmap,*idx_p;

1479:   if (mat->getrowactive) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Already active");
1480:   mat->getrowactive = PETSC_TRUE;

1482:   if (!mat->rowvalues && (idx || v)) {
1483:     /*
1484:         allocate enough space to hold information from the longest row.
1485:     */
1486:     Mat_SeqAIJ *Aa = (Mat_SeqAIJ*)mat->A->data,*Ba = (Mat_SeqAIJ*)mat->B->data;
1487:     PetscInt   max = 1,tmp;
1488:     for (i=0; i<matin->rmap->n; i++) {
1489:       tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i];
1490:       if (max < tmp) { max = tmp; }
1491:     }
1492:     PetscMalloc2(max,PetscScalar,&mat->rowvalues,max,PetscInt,&mat->rowindices);
1493:   }

1495:   if (row < rstart || row >= rend) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Only local rows")
1496:   lrow = row - rstart;

1498:   pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB;
1499:   if (!v)   {pvA = 0; pvB = 0;}
1500:   if (!idx) {pcA = 0; if (!v) pcB = 0;}
1501:   (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);
1502:   (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);
1503:   nztot = nzA + nzB;

1505:   cmap  = mat->garray;
1506:   if (v  || idx) {
1507:     if (nztot) {
1508:       /* Sort by increasing column numbers, assuming A and B already sorted */
1509:       PetscInt imark = -1;
1510:       if (v) {
1511:         *v = v_p = mat->rowvalues;
1512:         for (i=0; i<nzB; i++) {
1513:           if (cmap[cworkB[i]] < cstart)   v_p[i] = vworkB[i];
1514:           else break;
1515:         }
1516:         imark = i;
1517:         for (i=0; i<nzA; i++)     v_p[imark+i] = vworkA[i];
1518:         for (i=imark; i<nzB; i++) v_p[nzA+i]   = vworkB[i];
1519:       }
1520:       if (idx) {
1521:         *idx = idx_p = mat->rowindices;
1522:         if (imark > -1) {
1523:           for (i=0; i<imark; i++) {
1524:             idx_p[i] = cmap[cworkB[i]];
1525:           }
1526:         } else {
1527:           for (i=0; i<nzB; i++) {
1528:             if (cmap[cworkB[i]] < cstart)   idx_p[i] = cmap[cworkB[i]];
1529:             else break;
1530:           }
1531:           imark = i;
1532:         }
1533:         for (i=0; i<nzA; i++)     idx_p[imark+i] = cstart + cworkA[i];
1534:         for (i=imark; i<nzB; i++) idx_p[nzA+i]   = cmap[cworkB[i]];
1535:       }
1536:     } else {
1537:       if (idx) *idx = 0;
1538:       if (v)   *v   = 0;
1539:     }
1540:   }
1541:   *nz = nztot;
1542:   (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);
1543:   (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);
1544:   return(0);
1545: }

1549: PetscErrorCode MatRestoreRow_MPIAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
1550: {
1551:   Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;

1554:   if (!aij->getrowactive) {
1555:     SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"MatGetRow() must be called first");
1556:   }
1557:   aij->getrowactive = PETSC_FALSE;
1558:   return(0);
1559: }

1563: PetscErrorCode MatNorm_MPIAIJ(Mat mat,NormType type,PetscReal *norm)
1564: {
1565:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)mat->data;
1566:   Mat_SeqAIJ     *amat = (Mat_SeqAIJ*)aij->A->data,*bmat = (Mat_SeqAIJ*)aij->B->data;
1568:   PetscInt       i,j,cstart = mat->cmap->rstart;
1569:   PetscReal      sum = 0.0;
1570:   MatScalar      *v;

1573:   if (aij->size == 1) {
1574:      MatNorm(aij->A,type,norm);
1575:   } else {
1576:     if (type == NORM_FROBENIUS) {
1577:       v = amat->a;
1578:       for (i=0; i<amat->nz; i++) {
1579: #if defined(PETSC_USE_COMPLEX)
1580:         sum += PetscRealPart(PetscConj(*v)*(*v)); v++;
1581: #else
1582:         sum += (*v)*(*v); v++;
1583: #endif
1584:       }
1585:       v = bmat->a;
1586:       for (i=0; i<bmat->nz; i++) {
1587: #if defined(PETSC_USE_COMPLEX)
1588:         sum += PetscRealPart(PetscConj(*v)*(*v)); v++;
1589: #else
1590:         sum += (*v)*(*v); v++;
1591: #endif
1592:       }
1593:       MPI_Allreduce(&sum,norm,1,MPIU_REAL,MPI_SUM,((PetscObject)mat)->comm);
1594:       *norm = sqrt(*norm);
1595:     } else if (type == NORM_1) { /* max column norm */
1596:       PetscReal *tmp,*tmp2;
1597:       PetscInt  *jj,*garray = aij->garray;
1598:       PetscMalloc((mat->cmap->N+1)*sizeof(PetscReal),&tmp);
1599:       PetscMalloc((mat->cmap->N+1)*sizeof(PetscReal),&tmp2);
1600:       PetscMemzero(tmp,mat->cmap->N*sizeof(PetscReal));
1601:       *norm = 0.0;
1602:       v = amat->a; jj = amat->j;
1603:       for (j=0; j<amat->nz; j++) {
1604:         tmp[cstart + *jj++ ] += PetscAbsScalar(*v);  v++;
1605:       }
1606:       v = bmat->a; jj = bmat->j;
1607:       for (j=0; j<bmat->nz; j++) {
1608:         tmp[garray[*jj++]] += PetscAbsScalar(*v); v++;
1609:       }
1610:       MPI_Allreduce(tmp,tmp2,mat->cmap->N,MPIU_REAL,MPI_SUM,((PetscObject)mat)->comm);
1611:       for (j=0; j<mat->cmap->N; j++) {
1612:         if (tmp2[j] > *norm) *norm = tmp2[j];
1613:       }
1614:       PetscFree(tmp);
1615:       PetscFree(tmp2);
1616:     } else if (type == NORM_INFINITY) { /* max row norm */
1617:       PetscReal ntemp = 0.0;
1618:       for (j=0; j<aij->A->rmap->n; j++) {
1619:         v = amat->a + amat->i[j];
1620:         sum = 0.0;
1621:         for (i=0; i<amat->i[j+1]-amat->i[j]; i++) {
1622:           sum += PetscAbsScalar(*v); v++;
1623:         }
1624:         v = bmat->a + bmat->i[j];
1625:         for (i=0; i<bmat->i[j+1]-bmat->i[j]; i++) {
1626:           sum += PetscAbsScalar(*v); v++;
1627:         }
1628:         if (sum > ntemp) ntemp = sum;
1629:       }
1630:       MPI_Allreduce(&ntemp,norm,1,MPIU_REAL,MPI_MAX,((PetscObject)mat)->comm);
1631:     } else {
1632:       SETERRQ(PETSC_ERR_SUP,"No support for two norm");
1633:     }
1634:   }
1635:   return(0);
1636: }

1640: PetscErrorCode MatTranspose_MPIAIJ(Mat A,MatReuse reuse,Mat *matout)
1641: {
1642:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;
1643:   Mat_SeqAIJ     *Aloc=(Mat_SeqAIJ*)a->A->data,*Bloc=(Mat_SeqAIJ*)a->B->data;
1645:   PetscInt       M = A->rmap->N,N = A->cmap->N,ma,na,mb,*ai,*aj,*bi,*bj,row,*cols,*cols_tmp,i,*d_nnz;
1646:   PetscInt       cstart=A->cmap->rstart,ncol;
1647:   Mat            B;
1648:   MatScalar      *array;

1651:   if (reuse == MAT_REUSE_MATRIX && A == *matout && M != N) SETERRQ(PETSC_ERR_ARG_SIZ,"Square matrix only for in-place");

1653:   ma = A->rmap->n; na = A->cmap->n; mb = a->B->rmap->n;
1654:   ai = Aloc->i; aj = Aloc->j;
1655:   bi = Bloc->i; bj = Bloc->j;
1656:   if (reuse == MAT_INITIAL_MATRIX || *matout == A) {
1657:     /* compute d_nnz for preallocation; o_nnz is approximated by d_nnz to avoid communication */
1658:     PetscMalloc((1+na)*sizeof(PetscInt),&d_nnz);
1659:     PetscMemzero(d_nnz,(1+na)*sizeof(PetscInt));
1660:     for (i=0; i<ai[ma]; i++){
1661:       d_nnz[aj[i]] ++;
1662:       aj[i] += cstart; /* global col index to be used by MatSetValues() */
1663:     }

1665:     MatCreate(((PetscObject)A)->comm,&B);
1666:     MatSetSizes(B,A->cmap->n,A->rmap->n,N,M);
1667:     MatSetType(B,((PetscObject)A)->type_name);
1668:     MatMPIAIJSetPreallocation(B,0,d_nnz,0,d_nnz);
1669:     PetscFree(d_nnz);
1670:   } else {
1671:     B = *matout;
1672:   }

1674:   /* copy over the A part */
1675:   array = Aloc->a;
1676:   row = A->rmap->rstart;
1677:   for (i=0; i<ma; i++) {
1678:     ncol = ai[i+1]-ai[i];
1679:     MatSetValues(B,ncol,aj,1,&row,array,INSERT_VALUES);
1680:     row++; array += ncol; aj += ncol;
1681:   }
1682:   aj = Aloc->j;
1683:   for (i=0; i<ai[ma]; i++) aj[i] -= cstart; /* resume local col index */

1685:   /* copy over the B part */
1686:   PetscMalloc(bi[mb]*sizeof(PetscInt),&cols);
1687:   PetscMemzero(cols,bi[mb]*sizeof(PetscInt));
1688:   array = Bloc->a;
1689:   row = A->rmap->rstart;
1690:   for (i=0; i<bi[mb]; i++) {cols[i] = a->garray[bj[i]];}
1691:   cols_tmp = cols;
1692:   for (i=0; i<mb; i++) {
1693:     ncol = bi[i+1]-bi[i];
1694:     MatSetValues(B,ncol,cols_tmp,1,&row,array,INSERT_VALUES);
1695:     row++; array += ncol; cols_tmp += ncol;
1696:   }
1697:   PetscFree(cols);
1698: 
1699:   MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
1700:   MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);
1701:   if (reuse == MAT_INITIAL_MATRIX || *matout != A) {
1702:     *matout = B;
1703:   } else {
1704:     MatHeaderCopy(A,B);
1705:   }
1706:   return(0);
1707: }

1711: PetscErrorCode MatDiagonalScale_MPIAIJ(Mat mat,Vec ll,Vec rr)
1712: {
1713:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)mat->data;
1714:   Mat            a = aij->A,b = aij->B;
1716:   PetscInt       s1,s2,s3;

1719:   MatGetLocalSize(mat,&s2,&s3);
1720:   if (rr) {
1721:     VecGetLocalSize(rr,&s1);
1722:     if (s1!=s3) SETERRQ(PETSC_ERR_ARG_SIZ,"right vector non-conforming local size");
1723:     /* Overlap communication with computation. */
1724:     VecScatterBegin(aij->Mvctx,rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD);
1725:   }
1726:   if (ll) {
1727:     VecGetLocalSize(ll,&s1);
1728:     if (s1!=s2) SETERRQ(PETSC_ERR_ARG_SIZ,"left vector non-conforming local size");
1729:     (*b->ops->diagonalscale)(b,ll,0);
1730:   }
1731:   /* scale  the diagonal block */
1732:   (*a->ops->diagonalscale)(a,ll,rr);

1734:   if (rr) {
1735:     /* Do a scatter end and then right scale the off-diagonal block */
1736:     VecScatterEnd(aij->Mvctx,rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD);
1737:     (*b->ops->diagonalscale)(b,0,aij->lvec);
1738:   }
1739: 
1740:   return(0);
1741: }

1745: PetscErrorCode MatSetBlockSize_MPIAIJ(Mat A,PetscInt bs)
1746: {
1747:   Mat_MPIAIJ     *a   = (Mat_MPIAIJ*)A->data;

1751:   MatSetBlockSize(a->A,bs);
1752:   MatSetBlockSize(a->B,bs);
1753:   PetscLayoutSetBlockSize(A->rmap,bs);
1754:   PetscLayoutSetBlockSize(A->cmap,bs);
1755:   return(0);
1756: }
1759: PetscErrorCode MatSetUnfactored_MPIAIJ(Mat A)
1760: {
1761:   Mat_MPIAIJ     *a   = (Mat_MPIAIJ*)A->data;

1765:   MatSetUnfactored(a->A);
1766:   return(0);
1767: }

1771: PetscErrorCode MatEqual_MPIAIJ(Mat A,Mat B,PetscTruth *flag)
1772: {
1773:   Mat_MPIAIJ     *matB = (Mat_MPIAIJ*)B->data,*matA = (Mat_MPIAIJ*)A->data;
1774:   Mat            a,b,c,d;
1775:   PetscTruth     flg;

1779:   a = matA->A; b = matA->B;
1780:   c = matB->A; d = matB->B;

1782:   MatEqual(a,c,&flg);
1783:   if (flg) {
1784:     MatEqual(b,d,&flg);
1785:   }
1786:   MPI_Allreduce(&flg,flag,1,MPI_INT,MPI_LAND,((PetscObject)A)->comm);
1787:   return(0);
1788: }

1792: PetscErrorCode MatCopy_MPIAIJ(Mat A,Mat B,MatStructure str)
1793: {
1795:   Mat_MPIAIJ     *a = (Mat_MPIAIJ *)A->data;
1796:   Mat_MPIAIJ     *b = (Mat_MPIAIJ *)B->data;

1799:   /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */
1800:   if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) {
1801:     /* because of the column compression in the off-processor part of the matrix a->B,
1802:        the number of columns in a->B and b->B may be different, hence we cannot call
1803:        the MatCopy() directly on the two parts. If need be, we can provide a more 
1804:        efficient copy than the MatCopy_Basic() by first uncompressing the a->B matrices
1805:        then copying the submatrices */
1806:     MatCopy_Basic(A,B,str);
1807:   } else {
1808:     MatCopy(a->A,b->A,str);
1809:     MatCopy(a->B,b->B,str);
1810:   }
1811:   return(0);
1812: }

1816: PetscErrorCode MatSetUpPreallocation_MPIAIJ(Mat A)
1817: {

1821:    MatMPIAIJSetPreallocation(A,PETSC_DEFAULT,0,PETSC_DEFAULT,0);
1822:   return(0);
1823: }

1827: PetscErrorCode MatAXPY_MPIAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str)
1828: {
1830:   PetscInt       i;
1831:   Mat_MPIAIJ     *xx = (Mat_MPIAIJ *)X->data,*yy = (Mat_MPIAIJ *)Y->data;
1832:   PetscBLASInt   bnz,one=1;
1833:   Mat_SeqAIJ     *x,*y;

1836:   if (str == SAME_NONZERO_PATTERN) {
1837:     PetscScalar alpha = a;
1838:     x = (Mat_SeqAIJ *)xx->A->data;
1839:     y = (Mat_SeqAIJ *)yy->A->data;
1840:     bnz = PetscBLASIntCast(x->nz);
1841:     BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one);
1842:     x = (Mat_SeqAIJ *)xx->B->data;
1843:     y = (Mat_SeqAIJ *)yy->B->data;
1844:     bnz = PetscBLASIntCast(x->nz);
1845:     BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one);
1846:   } else if (str == SUBSET_NONZERO_PATTERN) {
1847:     MatAXPY_SeqAIJ(yy->A,a,xx->A,str);

1849:     x = (Mat_SeqAIJ *)xx->B->data;
1850:     y = (Mat_SeqAIJ *)yy->B->data;
1851:     if (y->xtoy && y->XtoY != xx->B) {
1852:       PetscFree(y->xtoy);
1853:       MatDestroy(y->XtoY);
1854:     }
1855:     if (!y->xtoy) { /* get xtoy */
1856:       MatAXPYGetxtoy_Private(xx->B->rmap->n,x->i,x->j,xx->garray,y->i,y->j,yy->garray,&y->xtoy);
1857:       y->XtoY = xx->B;
1858:       PetscObjectReference((PetscObject)xx->B);
1859:     }
1860:     for (i=0; i<x->nz; i++) y->a[y->xtoy[i]] += a*(x->a[i]);
1861:   } else {
1862:     MatAXPY_Basic(Y,a,X,str);
1863:   }
1864:   return(0);
1865: }

1867: EXTERN PetscErrorCode  MatConjugate_SeqAIJ(Mat);

1871: PetscErrorCode  MatConjugate_MPIAIJ(Mat mat)
1872: {
1873: #if defined(PETSC_USE_COMPLEX)
1875:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ *)mat->data;

1878:   MatConjugate_SeqAIJ(aij->A);
1879:   MatConjugate_SeqAIJ(aij->B);
1880: #else
1882: #endif
1883:   return(0);
1884: }

1888: PetscErrorCode MatRealPart_MPIAIJ(Mat A)
1889: {
1890:   Mat_MPIAIJ   *a = (Mat_MPIAIJ*)A->data;

1894:   MatRealPart(a->A);
1895:   MatRealPart(a->B);
1896:   return(0);
1897: }

1901: PetscErrorCode MatImaginaryPart_MPIAIJ(Mat A)
1902: {
1903:   Mat_MPIAIJ   *a = (Mat_MPIAIJ*)A->data;

1907:   MatImaginaryPart(a->A);
1908:   MatImaginaryPart(a->B);
1909:   return(0);
1910: }

1912: #ifdef PETSC_HAVE_PBGL

1914: #include <boost/parallel/mpi/bsp_process_group.hpp>
1915: #include <boost/graph/distributed/ilu_default_graph.hpp>
1916: #include <boost/graph/distributed/ilu_0_block.hpp>
1917: #include <boost/graph/distributed/ilu_preconditioner.hpp>
1918: #include <boost/graph/distributed/petsc/interface.hpp>
1919: #include <boost/multi_array.hpp>
1920: #include <boost/parallel/distributed_property_map->hpp>

1924: /*
1925:   This uses the parallel ILU factorization of Peter Gottschling <pgottsch@osl.iu.edu>
1926: */
1927: PetscErrorCode MatILUFactorSymbolic_MPIAIJ(Mat fact,Mat A, IS isrow, IS iscol, const MatFactorInfo *info)
1928: {
1929:   namespace petsc = boost::distributed::petsc;
1930: 
1931:   namespace graph_dist = boost::graph::distributed;
1932:   using boost::graph::distributed::ilu_default::process_group_type;
1933:   using boost::graph::ilu_permuted;

1935:   PetscTruth      row_identity, col_identity;
1936:   PetscContainer  c;
1937:   PetscInt        m, n, M, N;
1938:   PetscErrorCode  ierr;

1941:   if (info->levels != 0) SETERRQ(PETSC_ERR_SUP,"Only levels = 0 supported for parallel ilu");
1942:   ISIdentity(isrow, &row_identity);
1943:   ISIdentity(iscol, &col_identity);
1944:   if (!row_identity || !col_identity) {
1945:     SETERRQ(PETSC_ERR_ARG_WRONG,"Row and column permutations must be identity for parallel ILU");
1946:   }

1948:   process_group_type pg;
1949:   typedef graph_dist::ilu_default::ilu_level_graph_type  lgraph_type;
1950:   lgraph_type*   lgraph_p = new lgraph_type(petsc::num_global_vertices(A), pg, petsc::matrix_distribution(A, pg));
1951:   lgraph_type&   level_graph = *lgraph_p;
1952:   graph_dist::ilu_default::graph_type&            graph(level_graph.graph);

1954:   petsc::read_matrix(A, graph, get(boost::edge_weight, graph));
1955:   ilu_permuted(level_graph);

1957:   /* put together the new matrix */
1958:   MatCreate(((PetscObject)A)->comm, fact);
1959:   MatGetLocalSize(A, &m, &n);
1960:   MatGetSize(A, &M, &N);
1961:   MatSetSizes(fact, m, n, M, N);
1962:   MatSetType(fact, ((PetscObject)A)->type_name);
1963:   MatAssemblyBegin(fact, MAT_FINAL_ASSEMBLY);
1964:   MatAssemblyEnd(fact, MAT_FINAL_ASSEMBLY);

1966:   PetscContainerCreate(((PetscObject)A)->comm, &c);
1967:   PetscContainerSetPointer(c, lgraph_p);
1968:   PetscObjectCompose((PetscObject) (fact), "graph", (PetscObject) c);
1969:   return(0);
1970: }

1974: PetscErrorCode MatLUFactorNumeric_MPIAIJ(Mat B,Mat A, const MatFactorInfo *info)
1975: {
1977:   return(0);
1978: }

1982: /*
1983:   This uses the parallel ILU factorization of Peter Gottschling <pgottsch@osl.iu.edu>
1984: */
1985: PetscErrorCode MatSolve_MPIAIJ(Mat A, Vec b, Vec x)
1986: {
1987:   namespace graph_dist = boost::graph::distributed;

1989:   typedef graph_dist::ilu_default::ilu_level_graph_type  lgraph_type;
1990:   lgraph_type*   lgraph_p;
1991:   PetscContainer c;

1995:   PetscObjectQuery((PetscObject) A, "graph", (PetscObject *) &c);
1996:   PetscContainerGetPointer(c, (void **) &lgraph_p);
1997:   VecCopy(b, x);

1999:   PetscScalar* array_x;
2000:   VecGetArray(x, &array_x);
2001:   PetscInt sx;
2002:   VecGetSize(x, &sx);
2003: 
2004:   PetscScalar* array_b;
2005:   VecGetArray(b, &array_b);
2006:   PetscInt sb;
2007:   VecGetSize(b, &sb);

2009:   lgraph_type&   level_graph = *lgraph_p;
2010:   graph_dist::ilu_default::graph_type&            graph(level_graph.graph);

2012:   typedef boost::multi_array_ref<PetscScalar, 1> array_ref_type;
2013:   array_ref_type                                 ref_b(array_b, boost::extents[num_vertices(graph)]),
2014:                                                  ref_x(array_x, boost::extents[num_vertices(graph)]);

2016:   typedef boost::iterator_property_map<array_ref_type::iterator,
2017:                                 boost::property_map<graph_dist::ilu_default::graph_type, boost::vertex_index_t>::type>  gvector_type;
2018:   gvector_type                                   vector_b(ref_b.begin(), get(boost::vertex_index, graph)),
2019:                                                  vector_x(ref_x.begin(), get(boost::vertex_index, graph));
2020: 
2021:   ilu_set_solve(*lgraph_p, vector_b, vector_x);

2023:   return(0);
2024: }
2025: #endif

2027: typedef struct { /* used by MatGetRedundantMatrix() for reusing matredundant */
2028:   PetscInt       nzlocal,nsends,nrecvs;
2029:   PetscMPIInt    *send_rank,*recv_rank;
2030:   PetscInt       *sbuf_nz,*rbuf_nz,*sbuf_j,**rbuf_j;
2031:   PetscScalar    *sbuf_a,**rbuf_a;
2032:   PetscErrorCode (*MatDestroy)(Mat);
2033: } Mat_Redundant;

2037: PetscErrorCode PetscContainerDestroy_MatRedundant(void *ptr)
2038: {
2039:   PetscErrorCode       ierr;
2040:   Mat_Redundant        *redund=(Mat_Redundant*)ptr;
2041:   PetscInt             i;

2044:   PetscFree2(redund->send_rank,redund->recv_rank);
2045:   PetscFree(redund->sbuf_j);
2046:   PetscFree(redund->sbuf_a);
2047:   for (i=0; i<redund->nrecvs; i++){
2048:     PetscFree(redund->rbuf_j[i]);
2049:     PetscFree(redund->rbuf_a[i]);
2050:   }
2051:   PetscFree4(redund->sbuf_nz,redund->rbuf_nz,redund->rbuf_j,redund->rbuf_a);
2052:   PetscFree(redund);
2053:   return(0);
2054: }

2058: PetscErrorCode MatDestroy_MatRedundant(Mat A)
2059: {
2060:   PetscErrorCode  ierr;
2061:   PetscContainer  container;
2062:   Mat_Redundant   *redund=PETSC_NULL;

2065:   PetscObjectQuery((PetscObject)A,"Mat_Redundant",(PetscObject *)&container);
2066:   if (container) {
2067:     PetscContainerGetPointer(container,(void **)&redund);
2068:   } else {
2069:     SETERRQ(PETSC_ERR_PLIB,"Container does not exit");
2070:   }
2071:   A->ops->destroy = redund->MatDestroy;
2072:   PetscObjectCompose((PetscObject)A,"Mat_Redundant",0);
2073:   (*A->ops->destroy)(A);
2074:   PetscContainerDestroy(container);
2075:   return(0);
2076: }

2080: PetscErrorCode MatGetRedundantMatrix_MPIAIJ(Mat mat,PetscInt nsubcomm,MPI_Comm subcomm,PetscInt mlocal_sub,MatReuse reuse,Mat *matredundant)
2081: {
2082:   PetscMPIInt    rank,size;
2083:   MPI_Comm       comm=((PetscObject)mat)->comm;
2085:   PetscInt       nsends=0,nrecvs=0,i,rownz_max=0;
2086:   PetscMPIInt    *send_rank=PETSC_NULL,*recv_rank=PETSC_NULL;
2087:   PetscInt       *rowrange=mat->rmap->range;
2088:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)mat->data;
2089:   Mat            A=aij->A,B=aij->B,C=*matredundant;
2090:   Mat_SeqAIJ     *a=(Mat_SeqAIJ*)A->data,*b=(Mat_SeqAIJ*)B->data;
2091:   PetscScalar    *sbuf_a;
2092:   PetscInt       nzlocal=a->nz+b->nz;
2093:   PetscInt       j,cstart=mat->cmap->rstart,cend=mat->cmap->rend,row,nzA,nzB,ncols,*cworkA,*cworkB;
2094:   PetscInt       rstart=mat->rmap->rstart,rend=mat->rmap->rend,*bmap=aij->garray,M,N;
2095:   PetscInt       *cols,ctmp,lwrite,*rptr,l,*sbuf_j;
2096:   MatScalar      *aworkA,*aworkB;
2097:   PetscScalar    *vals;
2098:   PetscMPIInt    tag1,tag2,tag3,imdex;
2099:   MPI_Request    *s_waits1=PETSC_NULL,*s_waits2=PETSC_NULL,*s_waits3=PETSC_NULL,
2100:                  *r_waits1=PETSC_NULL,*r_waits2=PETSC_NULL,*r_waits3=PETSC_NULL;
2101:   MPI_Status     recv_status,*send_status;
2102:   PetscInt       *sbuf_nz=PETSC_NULL,*rbuf_nz=PETSC_NULL,count;
2103:   PetscInt       **rbuf_j=PETSC_NULL;
2104:   PetscScalar    **rbuf_a=PETSC_NULL;
2105:   Mat_Redundant  *redund=PETSC_NULL;
2106:   PetscContainer container;

2109:   MPI_Comm_rank(comm,&rank);
2110:   MPI_Comm_size(comm,&size);

2112:   if (reuse == MAT_REUSE_MATRIX) {
2113:     MatGetSize(C,&M,&N);
2114:     if (M != N || M != mat->rmap->N) SETERRQ(PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. Wrong global size");
2115:     MatGetLocalSize(C,&M,&N);
2116:     if (M != N || M != mlocal_sub) SETERRQ(PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. Wrong local size");
2117:     PetscObjectQuery((PetscObject)C,"Mat_Redundant",(PetscObject *)&container);
2118:     if (container) {
2119:       PetscContainerGetPointer(container,(void **)&redund);
2120:     } else {
2121:       SETERRQ(PETSC_ERR_PLIB,"Container does not exit");
2122:     }
2123:     if (nzlocal != redund->nzlocal) SETERRQ(PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. Wrong nzlocal");

2125:     nsends    = redund->nsends;
2126:     nrecvs    = redund->nrecvs;
2127:     send_rank = redund->send_rank;
2128:     recv_rank = redund->recv_rank;
2129:     sbuf_nz   = redund->sbuf_nz;
2130:     rbuf_nz   = redund->rbuf_nz;
2131:     sbuf_j    = redund->sbuf_j;
2132:     sbuf_a    = redund->sbuf_a;
2133:     rbuf_j    = redund->rbuf_j;
2134:     rbuf_a    = redund->rbuf_a;
2135:   }

2137:   if (reuse == MAT_INITIAL_MATRIX){
2138:     PetscMPIInt  subrank,subsize;
2139:     PetscInt     nleftover,np_subcomm;
2140:     /* get the destination processors' id send_rank, nsends and nrecvs */
2141:     MPI_Comm_rank(subcomm,&subrank);
2142:     MPI_Comm_size(subcomm,&subsize);
2143:     PetscMalloc2(size,PetscMPIInt,&send_rank,size,PetscMPIInt,&recv_rank);
2144:     np_subcomm = size/nsubcomm;
2145:     nleftover  = size - nsubcomm*np_subcomm;
2146:     nsends = 0; nrecvs = 0;
2147:     for (i=0; i<size; i++){ /* i=rank*/
2148:       if (subrank == i/nsubcomm && rank != i){ /* my_subrank == other's subrank */
2149:         send_rank[nsends] = i; nsends++;
2150:         recv_rank[nrecvs++] = i;
2151:       }
2152:     }
2153:     if (rank >= size - nleftover){/* this proc is a leftover processor */
2154:       i = size-nleftover-1;
2155:       j = 0;
2156:       while (j < nsubcomm - nleftover){
2157:         send_rank[nsends++] = i;
2158:         i--; j++;
2159:       }
2160:     }

2162:     if (nleftover && subsize == size/nsubcomm && subrank==subsize-1){ /* this proc recvs from leftover processors */
2163:       for (i=0; i<nleftover; i++){
2164:         recv_rank[nrecvs++] = size-nleftover+i;
2165:       }
2166:     }

2168:     /* allocate sbuf_j, sbuf_a */
2169:     i = nzlocal + rowrange[rank+1] - rowrange[rank] + 2;
2170:     PetscMalloc(i*sizeof(PetscInt),&sbuf_j);
2171:     PetscMalloc((nzlocal+1)*sizeof(PetscScalar),&sbuf_a);
2172:   } /* endof if (reuse == MAT_INITIAL_MATRIX) */
2173: 
2174:   /* copy mat's local entries into the buffers */
2175:   if (reuse == MAT_INITIAL_MATRIX){
2176:     rownz_max = 0;
2177:     rptr = sbuf_j;
2178:     cols = sbuf_j + rend-rstart + 1;
2179:     vals = sbuf_a;
2180:     rptr[0] = 0;
2181:     for (i=0; i<rend-rstart; i++){
2182:       row = i + rstart;
2183:       nzA    = a->i[i+1] - a->i[i]; nzB = b->i[i+1] - b->i[i];
2184:       ncols  = nzA + nzB;
2185:       cworkA = a->j + a->i[i]; cworkB = b->j + b->i[i];
2186:       aworkA = a->a + a->i[i]; aworkB = b->a + b->i[i];
2187:       /* load the column indices for this row into cols */
2188:       lwrite = 0;
2189:       for (l=0; l<nzB; l++) {
2190:         if ((ctmp = bmap[cworkB[l]]) < cstart){
2191:           vals[lwrite]   = aworkB[l];
2192:           cols[lwrite++] = ctmp;
2193:         }
2194:       }
2195:       for (l=0; l<nzA; l++){
2196:         vals[lwrite]   = aworkA[l];
2197:         cols[lwrite++] = cstart + cworkA[l];
2198:       }
2199:       for (l=0; l<nzB; l++) {
2200:         if ((ctmp = bmap[cworkB[l]]) >= cend){
2201:           vals[lwrite]   = aworkB[l];
2202:           cols[lwrite++] = ctmp;
2203:         }
2204:       }
2205:       vals += ncols;
2206:       cols += ncols;
2207:       rptr[i+1] = rptr[i] + ncols;
2208:       if (rownz_max < ncols) rownz_max = ncols;
2209:     }
2210:     if (rptr[rend-rstart] != a->nz + b->nz) SETERRQ4(1, "rptr[%d] %d != %d + %d",rend-rstart,rptr[rend-rstart+1],a->nz,b->nz);
2211:   } else { /* only copy matrix values into sbuf_a */
2212:     rptr = sbuf_j;
2213:     vals = sbuf_a;
2214:     rptr[0] = 0;
2215:     for (i=0; i<rend-rstart; i++){
2216:       row = i + rstart;
2217:       nzA    = a->i[i+1] - a->i[i]; nzB = b->i[i+1] - b->i[i];
2218:       ncols  = nzA + nzB;
2219:       cworkA = a->j + a->i[i]; cworkB = b->j + b->i[i];
2220:       aworkA = a->a + a->i[i]; aworkB = b->a + b->i[i];
2221:       lwrite = 0;
2222:       for (l=0; l<nzB; l++) {
2223:         if ((ctmp = bmap[cworkB[l]]) < cstart) vals[lwrite++] = aworkB[l];
2224:       }
2225:       for (l=0; l<nzA; l++) vals[lwrite++] = aworkA[l];
2226:       for (l=0; l<nzB; l++) {
2227:         if ((ctmp = bmap[cworkB[l]]) >= cend) vals[lwrite++] = aworkB[l];
2228:       }
2229:       vals += ncols;
2230:       rptr[i+1] = rptr[i] + ncols;
2231:     }
2232:   } /* endof if (reuse == MAT_INITIAL_MATRIX) */

2234:   /* send nzlocal to others, and recv other's nzlocal */
2235:   /*--------------------------------------------------*/
2236:   if (reuse == MAT_INITIAL_MATRIX){
2237:     PetscMalloc2(3*(nsends + nrecvs)+1,MPI_Request,&s_waits3,nsends+1,MPI_Status,&send_status);
2238:     s_waits2 = s_waits3 + nsends;
2239:     s_waits1 = s_waits2 + nsends;
2240:     r_waits1 = s_waits1 + nsends;
2241:     r_waits2 = r_waits1 + nrecvs;
2242:     r_waits3 = r_waits2 + nrecvs;
2243:   } else {
2244:     PetscMalloc2(nsends + nrecvs +1,MPI_Request,&s_waits3,nsends+1,MPI_Status,&send_status);
2245:     r_waits3 = s_waits3 + nsends;
2246:   }

2248:   PetscObjectGetNewTag((PetscObject)mat,&tag3);
2249:   if (reuse == MAT_INITIAL_MATRIX){
2250:     /* get new tags to keep the communication clean */
2251:     PetscObjectGetNewTag((PetscObject)mat,&tag1);
2252:     PetscObjectGetNewTag((PetscObject)mat,&tag2);
2253:     PetscMalloc4(nsends,PetscInt,&sbuf_nz,nrecvs,PetscInt,&rbuf_nz,nrecvs,PetscInt*,&rbuf_j,nrecvs,PetscScalar*,&rbuf_a);
2254: 
2255:     /* post receives of other's nzlocal */
2256:     for (i=0; i<nrecvs; i++){
2257:       MPI_Irecv(rbuf_nz+i,1,MPIU_INT,MPI_ANY_SOURCE,tag1,comm,r_waits1+i);
2258:     }
2259:     /* send nzlocal to others */
2260:     for (i=0; i<nsends; i++){
2261:       sbuf_nz[i] = nzlocal;
2262:       MPI_Isend(sbuf_nz+i,1,MPIU_INT,send_rank[i],tag1,comm,s_waits1+i);
2263:     }
2264:     /* wait on receives of nzlocal; allocate space for rbuf_j, rbuf_a */
2265:     count = nrecvs;
2266:     while (count) {
2267:       MPI_Waitany(nrecvs,r_waits1,&imdex,&recv_status);
2268:       recv_rank[imdex] = recv_status.MPI_SOURCE;
2269:       /* allocate rbuf_a and rbuf_j; then post receives of rbuf_j */
2270:       PetscMalloc((rbuf_nz[imdex]+1)*sizeof(PetscScalar),&rbuf_a[imdex]);

2272:       i = rowrange[recv_status.MPI_SOURCE+1] - rowrange[recv_status.MPI_SOURCE]; /* number of expected mat->i */
2273:       rbuf_nz[imdex] += i + 2;
2274:       PetscMalloc(rbuf_nz[imdex]*sizeof(PetscInt),&rbuf_j[imdex]);
2275:       MPI_Irecv(rbuf_j[imdex],rbuf_nz[imdex],MPIU_INT,recv_status.MPI_SOURCE,tag2,comm,r_waits2+imdex);
2276:       count--;
2277:     }
2278:     /* wait on sends of nzlocal */
2279:     if (nsends) {MPI_Waitall(nsends,s_waits1,send_status);}
2280:     /* send mat->i,j to others, and recv from other's */
2281:     /*------------------------------------------------*/
2282:     for (i=0; i<nsends; i++){
2283:       j = nzlocal + rowrange[rank+1] - rowrange[rank] + 1;
2284:       MPI_Isend(sbuf_j,j,MPIU_INT,send_rank[i],tag2,comm,s_waits2+i);
2285:     }
2286:     /* wait on receives of mat->i,j */
2287:     /*------------------------------*/
2288:     count = nrecvs;
2289:     while (count) {
2290:       MPI_Waitany(nrecvs,r_waits2,&imdex,&recv_status);
2291:       if (recv_rank[imdex] != recv_status.MPI_SOURCE) SETERRQ2(1, "recv_rank %d != MPI_SOURCE %d",recv_rank[imdex],recv_status.MPI_SOURCE);
2292:       count--;
2293:     }
2294:     /* wait on sends of mat->i,j */
2295:     /*---------------------------*/
2296:     if (nsends) {
2297:       MPI_Waitall(nsends,s_waits2,send_status);
2298:     }
2299:   } /* endof if (reuse == MAT_INITIAL_MATRIX) */

2301:   /* post receives, send and receive mat->a */
2302:   /*----------------------------------------*/
2303:   for (imdex=0; imdex<nrecvs; imdex++) {
2304:     MPI_Irecv(rbuf_a[imdex],rbuf_nz[imdex],MPIU_SCALAR,recv_rank[imdex],tag3,comm,r_waits3+imdex);
2305:   }
2306:   for (i=0; i<nsends; i++){
2307:     MPI_Isend(sbuf_a,nzlocal,MPIU_SCALAR,send_rank[i],tag3,comm,s_waits3+i);
2308:   }
2309:   count = nrecvs;
2310:   while (count) {
2311:     MPI_Waitany(nrecvs,r_waits3,&imdex,&recv_status);
2312:     if (recv_rank[imdex] != recv_status.MPI_SOURCE) SETERRQ2(1, "recv_rank %d != MPI_SOURCE %d",recv_rank[imdex],recv_status.MPI_SOURCE);
2313:     count--;
2314:   }
2315:   if (nsends) {
2316:     MPI_Waitall(nsends,s_waits3,send_status);
2317:   }

2319:   PetscFree2(s_waits3,send_status);
2320: 
2321:   /* create redundant matrix */
2322:   /*-------------------------*/
2323:   if (reuse == MAT_INITIAL_MATRIX){
2324:     /* compute rownz_max for preallocation */
2325:     for (imdex=0; imdex<nrecvs; imdex++){
2326:       j = rowrange[recv_rank[imdex]+1] - rowrange[recv_rank[imdex]];
2327:       rptr = rbuf_j[imdex];
2328:       for (i=0; i<j; i++){
2329:         ncols = rptr[i+1] - rptr[i];
2330:         if (rownz_max < ncols) rownz_max = ncols;
2331:       }
2332:     }
2333: 
2334:     MatCreate(subcomm,&C);
2335:     MatSetSizes(C,mlocal_sub,mlocal_sub,PETSC_DECIDE,PETSC_DECIDE);
2336:     MatSetFromOptions(C);
2337:     MatSeqAIJSetPreallocation(C,rownz_max,PETSC_NULL);
2338:     MatMPIAIJSetPreallocation(C,rownz_max,PETSC_NULL,rownz_max,PETSC_NULL);
2339:   } else {
2340:     C = *matredundant;
2341:   }

2343:   /* insert local matrix entries */
2344:   rptr = sbuf_j;
2345:   cols = sbuf_j + rend-rstart + 1;
2346:   vals = sbuf_a;
2347:   for (i=0; i<rend-rstart; i++){
2348:     row   = i + rstart;
2349:     ncols = rptr[i+1] - rptr[i];
2350:     MatSetValues(C,1,&row,ncols,cols,vals,INSERT_VALUES);
2351:     vals += ncols;
2352:     cols += ncols;
2353:   }
2354:   /* insert received matrix entries */
2355:   for (imdex=0; imdex<nrecvs; imdex++){
2356:     rstart = rowrange[recv_rank[imdex]];
2357:     rend   = rowrange[recv_rank[imdex]+1];
2358:     rptr = rbuf_j[imdex];
2359:     cols = rbuf_j[imdex] + rend-rstart + 1;
2360:     vals = rbuf_a[imdex];
2361:     for (i=0; i<rend-rstart; i++){
2362:       row   = i + rstart;
2363:       ncols = rptr[i+1] - rptr[i];
2364:       MatSetValues(C,1,&row,ncols,cols,vals,INSERT_VALUES);
2365:       vals += ncols;
2366:       cols += ncols;
2367:     }
2368:   }
2369:   MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);
2370:   MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);
2371:   MatGetSize(C,&M,&N);
2372:   if (M != mat->rmap->N || N != mat->cmap->N) SETERRQ2(PETSC_ERR_ARG_INCOMP,"redundant mat size %d != input mat size %d",M,mat->rmap->N);
2373:   if (reuse == MAT_INITIAL_MATRIX){
2374:     PetscContainer container;
2375:     *matredundant = C;
2376:     /* create a supporting struct and attach it to C for reuse */
2377:     PetscNewLog(C,Mat_Redundant,&redund);
2378:     PetscContainerCreate(PETSC_COMM_SELF,&container);
2379:     PetscContainerSetPointer(container,redund);
2380:     PetscObjectCompose((PetscObject)C,"Mat_Redundant",(PetscObject)container);
2381:     PetscContainerSetUserDestroy(container,PetscContainerDestroy_MatRedundant);
2382: 
2383:     redund->nzlocal = nzlocal;
2384:     redund->nsends  = nsends;
2385:     redund->nrecvs  = nrecvs;
2386:     redund->send_rank = send_rank;
2387:     redund->recv_rank = recv_rank;
2388:     redund->sbuf_nz = sbuf_nz;
2389:     redund->rbuf_nz = rbuf_nz;
2390:     redund->sbuf_j  = sbuf_j;
2391:     redund->sbuf_a  = sbuf_a;
2392:     redund->rbuf_j  = rbuf_j;
2393:     redund->rbuf_a  = rbuf_a;

2395:     redund->MatDestroy = C->ops->destroy;
2396:     C->ops->destroy    = MatDestroy_MatRedundant;
2397:   }
2398:   return(0);
2399: }

2403: PetscErrorCode MatGetRowMaxAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[])
2404: {
2405:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;
2407:   PetscInt       i,*idxb = 0;
2408:   PetscScalar    *va,*vb;
2409:   Vec            vtmp;

2412:   MatGetRowMaxAbs(a->A,v,idx);
2413:   VecGetArray(v,&va);
2414:   if (idx) {
2415:     for (i=0; i<A->rmap->n; i++) {
2416:       if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart;
2417:     }
2418:   }

2420:   VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);
2421:   if (idx) {
2422:     PetscMalloc(A->rmap->n*sizeof(PetscInt),&idxb);
2423:   }
2424:   MatGetRowMaxAbs(a->B,vtmp,idxb);
2425:   VecGetArray(vtmp,&vb);

2427:   for (i=0; i<A->rmap->n; i++){
2428:     if (PetscAbsScalar(va[i]) < PetscAbsScalar(vb[i])) {
2429:       va[i] = vb[i];
2430:       if (idx) idx[i] = a->garray[idxb[i]];
2431:     }
2432:   }

2434:   VecRestoreArray(v,&va);
2435:   VecRestoreArray(vtmp,&vb);
2436:   if (idxb) {
2437:     PetscFree(idxb);
2438:   }
2439:   VecDestroy(vtmp);
2440:   return(0);
2441: }

2445: PetscErrorCode MatGetRowMinAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[])
2446: {
2447:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;
2449:   PetscInt       i,*idxb = 0;
2450:   PetscScalar    *va,*vb;
2451:   Vec            vtmp;

2454:   MatGetRowMinAbs(a->A,v,idx);
2455:   VecGetArray(v,&va);
2456:   if (idx) {
2457:     for (i=0; i<A->cmap->n; i++) {
2458:       if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart;
2459:     }
2460:   }

2462:   VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);
2463:   if (idx) {
2464:     PetscMalloc(A->rmap->n*sizeof(PetscInt),&idxb);
2465:   }
2466:   MatGetRowMinAbs(a->B,vtmp,idxb);
2467:   VecGetArray(vtmp,&vb);

2469:   for (i=0; i<A->rmap->n; i++){
2470:     if (PetscAbsScalar(va[i]) > PetscAbsScalar(vb[i])) {
2471:       va[i] = vb[i];
2472:       if (idx) idx[i] = a->garray[idxb[i]];
2473:     }
2474:   }

2476:   VecRestoreArray(v,&va);
2477:   VecRestoreArray(vtmp,&vb);
2478:   if (idxb) {
2479:     PetscFree(idxb);
2480:   }
2481:   VecDestroy(vtmp);
2482:   return(0);
2483: }

2487: PetscErrorCode MatGetRowMin_MPIAIJ(Mat A, Vec v, PetscInt idx[])
2488: {
2489:   Mat_MPIAIJ    *mat    = (Mat_MPIAIJ *) A->data;
2490:   PetscInt       n      = A->rmap->n;
2491:   PetscInt       cstart = A->cmap->rstart;
2492:   PetscInt      *cmap   = mat->garray;
2493:   PetscInt      *diagIdx, *offdiagIdx;
2494:   Vec            diagV, offdiagV;
2495:   PetscScalar   *a, *diagA, *offdiagA;
2496:   PetscInt       r;

2500:   PetscMalloc2(n,PetscInt,&diagIdx,n,PetscInt,&offdiagIdx);
2501:   VecCreateSeq(((PetscObject)A)->comm, n, &diagV);
2502:   VecCreateSeq(((PetscObject)A)->comm, n, &offdiagV);
2503:   MatGetRowMin(mat->A, diagV,    diagIdx);
2504:   MatGetRowMin(mat->B, offdiagV, offdiagIdx);
2505:   VecGetArray(v,        &a);
2506:   VecGetArray(diagV,    &diagA);
2507:   VecGetArray(offdiagV, &offdiagA);
2508:   for(r = 0; r < n; ++r) {
2509:     if (PetscAbsScalar(diagA[r]) <= PetscAbsScalar(offdiagA[r])) {
2510:       a[r]   = diagA[r];
2511:       idx[r] = cstart + diagIdx[r];
2512:     } else {
2513:       a[r]   = offdiagA[r];
2514:       idx[r] = cmap[offdiagIdx[r]];
2515:     }
2516:   }
2517:   VecRestoreArray(v,        &a);
2518:   VecRestoreArray(diagV,    &diagA);
2519:   VecRestoreArray(offdiagV, &offdiagA);
2520:   VecDestroy(diagV);
2521:   VecDestroy(offdiagV);
2522:   PetscFree2(diagIdx, offdiagIdx);
2523:   return(0);
2524: }

2528: PetscErrorCode MatGetRowMax_MPIAIJ(Mat A, Vec v, PetscInt idx[])
2529: {
2530:   Mat_MPIAIJ    *mat    = (Mat_MPIAIJ *) A->data;
2531:   PetscInt       n      = A->rmap->n;
2532:   PetscInt       cstart = A->cmap->rstart;
2533:   PetscInt      *cmap   = mat->garray;
2534:   PetscInt      *diagIdx, *offdiagIdx;
2535:   Vec            diagV, offdiagV;
2536:   PetscScalar   *a, *diagA, *offdiagA;
2537:   PetscInt       r;

2541:   PetscMalloc2(n,PetscInt,&diagIdx,n,PetscInt,&offdiagIdx);
2542:   VecCreateSeq(((PetscObject)A)->comm, n, &diagV);
2543:   VecCreateSeq(((PetscObject)A)->comm, n, &offdiagV);
2544:   MatGetRowMax(mat->A, diagV,    diagIdx);
2545:   MatGetRowMax(mat->B, offdiagV, offdiagIdx);
2546:   VecGetArray(v,        &a);
2547:   VecGetArray(diagV,    &diagA);
2548:   VecGetArray(offdiagV, &offdiagA);
2549:   for(r = 0; r < n; ++r) {
2550:     if (PetscAbsScalar(diagA[r]) >= PetscAbsScalar(offdiagA[r])) {
2551:       a[r]   = diagA[r];
2552:       idx[r] = cstart + diagIdx[r];
2553:     } else {
2554:       a[r]   = offdiagA[r];
2555:       idx[r] = cmap[offdiagIdx[r]];
2556:     }
2557:   }
2558:   VecRestoreArray(v,        &a);
2559:   VecRestoreArray(diagV,    &diagA);
2560:   VecRestoreArray(offdiagV, &offdiagA);
2561:   VecDestroy(diagV);
2562:   VecDestroy(offdiagV);
2563:   PetscFree2(diagIdx, offdiagIdx);
2564:   return(0);
2565: }

2569: PetscErrorCode MatGetSeqNonzerostructure_MPIAIJ(Mat mat,Mat *newmat)
2570: {
2572:   Mat            *dummy;

2575:   MatGetSubMatrix_MPIAIJ_All(mat,MAT_DO_NOT_GET_VALUES,MAT_INITIAL_MATRIX,&dummy);
2576:   *newmat = *dummy;
2577:   PetscFree(dummy);
2578:   return(0);
2579: }

2582: /* -------------------------------------------------------------------*/
2583: static struct _MatOps MatOps_Values = {MatSetValues_MPIAIJ,
2584:        MatGetRow_MPIAIJ,
2585:        MatRestoreRow_MPIAIJ,
2586:        MatMult_MPIAIJ,
2587: /* 4*/ MatMultAdd_MPIAIJ,
2588:        MatMultTranspose_MPIAIJ,
2589:        MatMultTransposeAdd_MPIAIJ,
2590: #ifdef PETSC_HAVE_PBGL
2591:        MatSolve_MPIAIJ,
2592: #else
2593:        0,
2594: #endif
2595:        0,
2596:        0,
2597: /*10*/ 0,
2598:        0,
2599:        0,
2600:        MatSOR_MPIAIJ,
2601:        MatTranspose_MPIAIJ,
2602: /*15*/ MatGetInfo_MPIAIJ,
2603:        MatEqual_MPIAIJ,
2604:        MatGetDiagonal_MPIAIJ,
2605:        MatDiagonalScale_MPIAIJ,
2606:        MatNorm_MPIAIJ,
2607: /*20*/ MatAssemblyBegin_MPIAIJ,
2608:        MatAssemblyEnd_MPIAIJ,
2609:        MatSetOption_MPIAIJ,
2610:        MatZeroEntries_MPIAIJ,
2611: /*24*/ MatZeroRows_MPIAIJ,
2612:        0,
2613: #ifdef PETSC_HAVE_PBGL
2614:        0,
2615: #else
2616:        0,
2617: #endif
2618:        0,
2619:        0,
2620: /*29*/ MatSetUpPreallocation_MPIAIJ,
2621: #ifdef PETSC_HAVE_PBGL
2622:        0,
2623: #else
2624:        0,
2625: #endif
2626:        0,
2627:        0,
2628:        0,
2629: /*34*/ MatDuplicate_MPIAIJ,
2630:        0,
2631:        0,
2632:        0,
2633:        0,
2634: /*39*/ MatAXPY_MPIAIJ,
2635:        MatGetSubMatrices_MPIAIJ,
2636:        MatIncreaseOverlap_MPIAIJ,
2637:        MatGetValues_MPIAIJ,
2638:        MatCopy_MPIAIJ,
2639: /*44*/ MatGetRowMax_MPIAIJ,
2640:        MatScale_MPIAIJ,
2641:        0,
2642:        0,
2643:        0,
2644: /*49*/ MatSetBlockSize_MPIAIJ,
2645:        0,
2646:        0,
2647:        0,
2648:        0,
2649: /*54*/ MatFDColoringCreate_MPIAIJ,
2650:        0,
2651:        MatSetUnfactored_MPIAIJ,
2652:        MatPermute_MPIAIJ,
2653:        0,
2654: /*59*/ MatGetSubMatrix_MPIAIJ,
2655:        MatDestroy_MPIAIJ,
2656:        MatView_MPIAIJ,
2657:        0,
2658:        0,
2659: /*64*/ 0,
2660:        0,
2661:        0,
2662:        0,
2663:        0,
2664: /*69*/ MatGetRowMaxAbs_MPIAIJ,
2665:        MatGetRowMinAbs_MPIAIJ,
2666:        0,
2667:        MatSetColoring_MPIAIJ,
2668: #if defined(PETSC_HAVE_ADIC)
2669:        MatSetValuesAdic_MPIAIJ,
2670: #else
2671:        0,
2672: #endif
2673:        MatSetValuesAdifor_MPIAIJ,
2674: /*75*/ MatFDColoringApply_AIJ,
2675:        0,
2676:        0,
2677:        0,
2678:        0,
2679: /*80*/ 0,
2680:        0,
2681:        0,
2682: /*83*/ MatLoad_MPIAIJ,
2683:        0,
2684:        0,
2685:        0,
2686:        0,
2687:        0,
2688: /*89*/ MatMatMult_MPIAIJ_MPIAIJ,
2689:        MatMatMultSymbolic_MPIAIJ_MPIAIJ,
2690:        MatMatMultNumeric_MPIAIJ_MPIAIJ,
2691:        MatPtAP_Basic,
2692:        MatPtAPSymbolic_MPIAIJ,
2693: /*94*/ MatPtAPNumeric_MPIAIJ,
2694:        0,
2695:        0,
2696:        0,
2697:        0,
2698: /*99*/ 0,
2699:        MatPtAPSymbolic_MPIAIJ_MPIAIJ,
2700:        MatPtAPNumeric_MPIAIJ_MPIAIJ,
2701:        MatConjugate_MPIAIJ,
2702:        0,
2703: /*104*/MatSetValuesRow_MPIAIJ,
2704:        MatRealPart_MPIAIJ,
2705:        MatImaginaryPart_MPIAIJ,
2706:        0,
2707:        0,
2708: /*109*/0,
2709:        MatGetRedundantMatrix_MPIAIJ,
2710:        MatGetRowMin_MPIAIJ,
2711:        0,
2712:        0,
2713: /*114*/MatGetSeqNonzerostructure_MPIAIJ,
2714:        0,
2715:        0,
2716:        0,
2717:        0,
2718:        0
2719: };

2721: /* ----------------------------------------------------------------------------------------*/

2726: PetscErrorCode  MatStoreValues_MPIAIJ(Mat mat)
2727: {
2728:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ *)mat->data;

2732:   MatStoreValues(aij->A);
2733:   MatStoreValues(aij->B);
2734:   return(0);
2735: }

2741: PetscErrorCode  MatRetrieveValues_MPIAIJ(Mat mat)
2742: {
2743:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ *)mat->data;

2747:   MatRetrieveValues(aij->A);
2748:   MatRetrieveValues(aij->B);
2749:   return(0);
2750: }

2753:  #include petscpc.h
2757: PetscErrorCode  MatMPIAIJSetPreallocation_MPIAIJ(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[])
2758: {
2759:   Mat_MPIAIJ     *b;
2761:   PetscInt       i;

2764:   if (d_nz == PETSC_DEFAULT || d_nz == PETSC_DECIDE) d_nz = 5;
2765:   if (o_nz == PETSC_DEFAULT || o_nz == PETSC_DECIDE) o_nz = 2;
2766:   if (d_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"d_nz cannot be less than 0: value %D",d_nz);
2767:   if (o_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"o_nz cannot be less than 0: value %D",o_nz);

2769:   PetscLayoutSetBlockSize(B->rmap,1);
2770:   PetscLayoutSetBlockSize(B->cmap,1);
2771:   PetscLayoutSetUp(B->rmap);
2772:   PetscLayoutSetUp(B->cmap);
2773:   if (d_nnz) {
2774:     for (i=0; i<B->rmap->n; i++) {
2775:       if (d_nnz[i] < 0) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"d_nnz cannot be less than 0: local row %D value %D",i,d_nnz[i]);
2776:     }
2777:   }
2778:   if (o_nnz) {
2779:     for (i=0; i<B->rmap->n; i++) {
2780:       if (o_nnz[i] < 0) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"o_nnz cannot be less than 0: local row %D value %D",i,o_nnz[i]);
2781:     }
2782:   }
2783:   b = (Mat_MPIAIJ*)B->data;

2785:   if (!B->preallocated) {
2786:     /* Explicitly create 2 MATSEQAIJ matrices. */
2787:     MatCreate(PETSC_COMM_SELF,&b->A);
2788:     MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);
2789:     MatSetType(b->A,MATSEQAIJ);
2790:     PetscLogObjectParent(B,b->A);
2791:     MatCreate(PETSC_COMM_SELF,&b->B);
2792:     MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);
2793:     MatSetType(b->B,MATSEQAIJ);
2794:     PetscLogObjectParent(B,b->B);
2795:   }

2797:   MatSeqAIJSetPreallocation(b->A,d_nz,d_nnz);
2798:   MatSeqAIJSetPreallocation(b->B,o_nz,o_nnz);
2799:   B->preallocated = PETSC_TRUE;
2800:   return(0);
2801: }

2806: PetscErrorCode MatDuplicate_MPIAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat)
2807: {
2808:   Mat            mat;
2809:   Mat_MPIAIJ     *a,*oldmat = (Mat_MPIAIJ*)matin->data;

2813:   *newmat       = 0;
2814:   MatCreate(((PetscObject)matin)->comm,&mat);
2815:   MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);
2816:   MatSetType(mat,((PetscObject)matin)->type_name);
2817:   PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));
2818:   a    = (Mat_MPIAIJ*)mat->data;
2819: 
2820:   mat->factor       = matin->factor;
2821:   mat->rmap->bs      = matin->rmap->bs;
2822:   mat->assembled    = PETSC_TRUE;
2823:   mat->insertmode   = NOT_SET_VALUES;
2824:   mat->preallocated = PETSC_TRUE;

2826:   a->size           = oldmat->size;
2827:   a->rank           = oldmat->rank;
2828:   a->donotstash     = oldmat->donotstash;
2829:   a->roworiented    = oldmat->roworiented;
2830:   a->rowindices     = 0;
2831:   a->rowvalues      = 0;
2832:   a->getrowactive   = PETSC_FALSE;

2834:   PetscLayoutCopy(matin->rmap,&mat->rmap);
2835:   PetscLayoutCopy(matin->cmap,&mat->cmap);

2837:   if (oldmat->colmap) {
2838: #if defined (PETSC_USE_CTABLE)
2839:     PetscTableCreateCopy(oldmat->colmap,&a->colmap);
2840: #else
2841:     PetscMalloc((mat->cmap->N)*sizeof(PetscInt),&a->colmap);
2842:     PetscLogObjectMemory(mat,(mat->cmap->N)*sizeof(PetscInt));
2843:     PetscMemcpy(a->colmap,oldmat->colmap,(mat->cmap->N)*sizeof(PetscInt));
2844: #endif
2845:   } else a->colmap = 0;
2846:   if (oldmat->garray) {
2847:     PetscInt len;
2848:     len  = oldmat->B->cmap->n;
2849:     PetscMalloc((len+1)*sizeof(PetscInt),&a->garray);
2850:     PetscLogObjectMemory(mat,len*sizeof(PetscInt));
2851:     if (len) { PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt)); }
2852:   } else a->garray = 0;
2853: 
2854:   VecDuplicate(oldmat->lvec,&a->lvec);
2855:   PetscLogObjectParent(mat,a->lvec);
2856:   VecScatterCopy(oldmat->Mvctx,&a->Mvctx);
2857:   PetscLogObjectParent(mat,a->Mvctx);
2858:   MatDuplicate(oldmat->A,cpvalues,&a->A);
2859:   PetscLogObjectParent(mat,a->A);
2860:   MatDuplicate(oldmat->B,cpvalues,&a->B);
2861:   PetscLogObjectParent(mat,a->B);
2862:   PetscFListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);
2863:   *newmat = mat;
2864:   return(0);
2865: }

2869: PetscErrorCode MatLoad_MPIAIJ(PetscViewer viewer, const MatType type,Mat *newmat)
2870: {
2871:   Mat            A;
2872:   PetscScalar    *vals,*svals;
2873:   MPI_Comm       comm = ((PetscObject)viewer)->comm;
2874:   MPI_Status     status;
2876:   PetscMPIInt    rank,size,tag = ((PetscObject)viewer)->tag,mpicnt,mpimaxnz;
2877:   PetscInt       i,nz,j,rstart,rend,mmax,maxnz = 0;
2878:   PetscInt       header[4],*rowlengths = 0,M,N,m,*cols;
2879:   PetscInt       *ourlens = PETSC_NULL,*procsnz = PETSC_NULL,*offlens = PETSC_NULL,jj,*mycols,*smycols;
2880:   PetscInt       cend,cstart,n,*rowners;
2881:   int            fd;

2884:   MPI_Comm_size(comm,&size);
2885:   MPI_Comm_rank(comm,&rank);
2886:   if (!rank) {
2887:     PetscViewerBinaryGetDescriptor(viewer,&fd);
2888:     PetscBinaryRead(fd,(char *)header,4,PETSC_INT);
2889:     if (header[0] != MAT_FILE_COOKIE) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"not matrix object");
2890:   }

2892:   MPI_Bcast(header+1,3,MPIU_INT,0,comm);
2893:   M = header[1]; N = header[2];
2894:   /* determine ownership of all rows */
2895:   m    = M/size + ((M % size) > rank);
2896:   PetscMalloc((size+1)*sizeof(PetscInt),&rowners);
2897:   MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);

2899:   /* First process needs enough room for process with most rows */
2900:   if (!rank) {
2901:     mmax       = rowners[1];
2902:     for (i=2; i<size; i++) {
2903:       mmax = PetscMax(mmax,rowners[i]);
2904:     }
2905:   } else mmax = m;

2907:   rowners[0] = 0;
2908:   for (i=2; i<=size; i++) {
2909:     rowners[i] += rowners[i-1];
2910:   }
2911:   rstart = rowners[rank];
2912:   rend   = rowners[rank+1];

2914:   /* distribute row lengths to all processors */
2915:   PetscMalloc2(mmax,PetscInt,&ourlens,mmax,PetscInt,&offlens);
2916:   if (!rank) {
2917:     PetscBinaryRead(fd,ourlens,m,PETSC_INT);
2918:     PetscMalloc(m*sizeof(PetscInt),&rowlengths);
2919:     PetscMalloc(size*sizeof(PetscInt),&procsnz);
2920:     PetscMemzero(procsnz,size*sizeof(PetscInt));
2921:     for (j=0; j<m; j++) {
2922:       procsnz[0] += ourlens[j];
2923:     }
2924:     for (i=1; i<size; i++) {
2925:       PetscBinaryRead(fd,rowlengths,rowners[i+1]-rowners[i],PETSC_INT);
2926:       /* calculate the number of nonzeros on each processor */
2927:       for (j=0; j<rowners[i+1]-rowners[i]; j++) {
2928:         procsnz[i] += rowlengths[j];
2929:       }
2930:       mpicnt = PetscMPIIntCast(rowners[i+1]-rowners[i]);
2931:       MPI_Send(rowlengths,mpicnt,MPIU_INT,i,tag,comm);
2932:     }
2933:     PetscFree(rowlengths);
2934:   } else {
2935:     mpicnt = PetscMPIIntCast(m);
2936:     MPI_Recv(ourlens,mpicnt,MPIU_INT,0,tag,comm,&status);
2937:   }

2939:   if (!rank) {
2940:     /* determine max buffer needed and allocate it */
2941:     maxnz = 0;
2942:     for (i=0; i<size; i++) {
2943:       maxnz = PetscMax(maxnz,procsnz[i]);
2944:     }
2945:     PetscMalloc(maxnz*sizeof(PetscInt),&cols);

2947:     /* read in my part of the matrix column indices  */
2948:     nz   = procsnz[0];
2949:     PetscMalloc(nz*sizeof(PetscInt),&mycols);
2950:     PetscBinaryRead(fd,mycols,nz,PETSC_INT);

2952:     /* read in every one elses and ship off */
2953:     for (i=1; i<size; i++) {
2954:       nz     = procsnz[i];
2955:       PetscBinaryRead(fd,cols,nz,PETSC_INT);
2956:       mpicnt = PetscMPIIntCast(nz);
2957:       MPI_Send(cols,mpicnt,MPIU_INT,i,tag,comm);
2958:     }
2959:     PetscFree(cols);
2960:   } else {
2961:     /* determine buffer space needed for message */
2962:     nz = 0;
2963:     for (i=0; i<m; i++) {
2964:       nz += ourlens[i];
2965:     }
2966:     PetscMalloc(nz*sizeof(PetscInt),&mycols);

2968:     /* receive message of column indices*/
2969:     mpicnt = PetscMPIIntCast(nz);
2970:     MPI_Recv(mycols,mpicnt,MPIU_INT,0,tag,comm,&status);
2971:     MPI_Get_count(&status,MPIU_INT,&mpimaxnz);
2972:     if (mpimaxnz == MPI_UNDEFINED) {SETERRQ1(PETSC_ERR_LIB,"MPI_Get_count() returned MPI_UNDEFINED, expected %d",mpicnt);}
2973:     else if (mpimaxnz < 0) {SETERRQ2(PETSC_ERR_LIB,"MPI_Get_count() returned impossible negative value %d, expected %d",mpimaxnz,mpicnt);}
2974:     else if (mpimaxnz != mpicnt) {SETERRQ2(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file: expected %d received %d",mpicnt,mpimaxnz);}
2975:   }

2977:   /* determine column ownership if matrix is not square */
2978:   if (N != M) {
2979:     n      = N/size + ((N % size) > rank);
2980:     MPI_Scan(&n,&cend,1,MPIU_INT,MPI_SUM,comm);
2981:     cstart = cend - n;
2982:   } else {
2983:     cstart = rstart;
2984:     cend   = rend;
2985:     n      = cend - cstart;
2986:   }

2988:   /* loop over local rows, determining number of off diagonal entries */
2989:   PetscMemzero(offlens,m*sizeof(PetscInt));
2990:   jj = 0;
2991:   for (i=0; i<m; i++) {
2992:     for (j=0; j<ourlens[i]; j++) {
2993:       if (mycols[jj] < cstart || mycols[jj] >= cend) offlens[i]++;
2994:       jj++;
2995:     }
2996:   }

2998:   /* create our matrix */
2999:   for (i=0; i<m; i++) {
3000:     ourlens[i] -= offlens[i];
3001:   }
3002:   MatCreate(comm,&A);
3003:   MatSetSizes(A,m,n,M,N);
3004:   MatSetType(A,type);
3005:   MatMPIAIJSetPreallocation(A,0,ourlens,0,offlens);

3007:   for (i=0; i<m; i++) {
3008:     ourlens[i] += offlens[i];
3009:   }

3011:   if (!rank) {
3012:     PetscMalloc((maxnz+1)*sizeof(PetscScalar),&vals);

3014:     /* read in my part of the matrix numerical values  */
3015:     nz   = procsnz[0];
3016:     PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);
3017: 
3018:     /* insert into matrix */
3019:     jj      = rstart;
3020:     smycols = mycols;
3021:     svals   = vals;
3022:     for (i=0; i<m; i++) {
3023:       MatSetValues_MPIAIJ(A,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);
3024:       smycols += ourlens[i];
3025:       svals   += ourlens[i];
3026:       jj++;
3027:     }

3029:     /* read in other processors and ship out */
3030:     for (i=1; i<size; i++) {
3031:       nz     = procsnz[i];
3032:       PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);
3033:       mpicnt = PetscMPIIntCast(nz);
3034:       MPI_Send(vals,mpicnt,MPIU_SCALAR,i,((PetscObject)A)->tag,comm);
3035:     }
3036:     PetscFree(procsnz);
3037:   } else {
3038:     /* receive numeric values */
3039:     PetscMalloc((nz+1)*sizeof(PetscScalar),&vals);

3041:     /* receive message of values*/
3042:     mpicnt = PetscMPIIntCast(nz);
3043:     MPI_Recv(vals,mpicnt,MPIU_SCALAR,0,((PetscObject)A)->tag,comm,&status);
3044:     MPI_Get_count(&status,MPIU_SCALAR,&mpimaxnz);
3045:     if (mpimaxnz == MPI_UNDEFINED) {SETERRQ1(PETSC_ERR_LIB,"MPI_Get_count() returned MPI_UNDEFINED, expected %d",mpicnt);}
3046:     else if (mpimaxnz < 0) {SETERRQ2(PETSC_ERR_LIB,"MPI_Get_count() returned impossible negative value %d, expected %d",mpimaxnz,mpicnt);}
3047:     else if (mpimaxnz != mpicnt) {SETERRQ2(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file: expected %d received %d",mpicnt,mpimaxnz);}

3049:     /* insert into matrix */
3050:     jj      = rstart;
3051:     smycols = mycols;
3052:     svals   = vals;
3053:     for (i=0; i<m; i++) {
3054:       MatSetValues_MPIAIJ(A,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);
3055:       smycols += ourlens[i];
3056:       svals   += ourlens[i];
3057:       jj++;
3058:     }
3059:   }
3060:   PetscFree2(ourlens,offlens);
3061:   PetscFree(vals);
3062:   PetscFree(mycols);
3063:   PetscFree(rowners);

3065:   MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);
3066:   MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);
3067:   *newmat = A;
3068:   return(0);
3069: }

3073: PetscErrorCode MatGetSubMatrix_MPIAIJ(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat)
3074: {
3076:   IS             iscol_local;
3077:   PetscInt       csize;

3080:   ISGetLocalSize(iscol,&csize);
3081:   if (call == MAT_REUSE_MATRIX) {
3082:     PetscObjectQuery((PetscObject)*newmat,"ISAllGather",(PetscObject*)&iscol_local);
3083:     if (!iscol_local) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse");
3084:   } else {
3085:     ISAllGather(iscol,&iscol_local);
3086:   }
3087:   MatGetSubMatrix_MPIAIJ_Private(mat,isrow,iscol_local,csize,call,newmat);
3088:   if (call == MAT_INITIAL_MATRIX) {
3089:     PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);
3090:     ISDestroy(iscol_local);
3091:   }
3092:   return(0);
3093: }

3097: /*
3098:     Not great since it makes two copies of the submatrix, first an SeqAIJ 
3099:   in local and then by concatenating the local matrices the end result.
3100:   Writing it directly would be much like MatGetSubMatrices_MPIAIJ()

3102:   Note: This requires a sequential iscol with all indices.
3103: */
3104: PetscErrorCode MatGetSubMatrix_MPIAIJ_Private(Mat mat,IS isrow,IS iscol,PetscInt csize,MatReuse call,Mat *newmat)
3105: {
3107:   PetscMPIInt    rank,size;
3108:   PetscInt       i,m,n,rstart,row,rend,nz,*cwork,j;
3109:   PetscInt       *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal;
3110:   Mat            *local,M,Mreuse;
3111:   MatScalar      *vwork,*aa;
3112:   MPI_Comm       comm = ((PetscObject)mat)->comm;
3113:   Mat_SeqAIJ     *aij;


3117:   MPI_Comm_rank(comm,&rank);
3118:   MPI_Comm_size(comm,&size);

3120:   if (call ==  MAT_REUSE_MATRIX) {
3121:     PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject *)&Mreuse);
3122:     if (!Mreuse) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse");
3123:     local = &Mreuse;
3124:     MatGetSubMatrices(mat,1,&isrow,&iscol,MAT_REUSE_MATRIX,&local);
3125:   } else {
3126:     MatGetSubMatrices(mat,1,&isrow,&iscol,MAT_INITIAL_MATRIX,&local);
3127:     Mreuse = *local;
3128:     PetscFree(local);
3129:   }

3131:   /* 
3132:       m - number of local rows
3133:       n - number of columns (same on all processors)
3134:       rstart - first row in new global matrix generated
3135:   */
3136:   MatGetSize(Mreuse,&m,&n);
3137:   if (call == MAT_INITIAL_MATRIX) {
3138:     aij = (Mat_SeqAIJ*)(Mreuse)->data;
3139:     ii  = aij->i;
3140:     jj  = aij->j;

3142:     /*
3143:         Determine the number of non-zeros in the diagonal and off-diagonal 
3144:         portions of the matrix in order to do correct preallocation
3145:     */

3147:     /* first get start and end of "diagonal" columns */
3148:     if (csize == PETSC_DECIDE) {
3149:       ISGetSize(isrow,&mglobal);
3150:       if (mglobal == n) { /* square matrix */
3151:         nlocal = m;
3152:       } else {
3153:         nlocal = n/size + ((n % size) > rank);
3154:       }
3155:     } else {
3156:       nlocal = csize;
3157:     }
3158:     MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);
3159:     rstart = rend - nlocal;
3160:     if (rank == size - 1 && rend != n) {
3161:       SETERRQ2(PETSC_ERR_ARG_SIZ,"Local column sizes %D do not add up to total number of columns %D",rend,n);
3162:     }

3164:     /* next, compute all the lengths */
3165:     PetscMalloc((2*m+1)*sizeof(PetscInt),&dlens);
3166:     olens = dlens + m;
3167:     for (i=0; i<m; i++) {
3168:       jend = ii[i+1] - ii[i];
3169:       olen = 0;
3170:       dlen = 0;
3171:       for (j=0; j<jend; j++) {
3172:         if (*jj < rstart || *jj >= rend) olen++;
3173:         else dlen++;
3174:         jj++;
3175:       }
3176:       olens[i] = olen;
3177:       dlens[i] = dlen;
3178:     }
3179:     MatCreate(comm,&M);
3180:     MatSetSizes(M,m,nlocal,PETSC_DECIDE,n);
3181:     MatSetType(M,((PetscObject)mat)->type_name);
3182:     MatMPIAIJSetPreallocation(M,0,dlens,0,olens);
3183:     PetscFree(dlens);
3184:   } else {
3185:     PetscInt ml,nl;

3187:     M = *newmat;
3188:     MatGetLocalSize(M,&ml,&nl);
3189:     if (ml != m) SETERRQ(PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request");
3190:     MatZeroEntries(M);
3191:     /*
3192:          The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly,
3193:        rather than the slower MatSetValues().
3194:     */
3195:     M->was_assembled = PETSC_TRUE;
3196:     M->assembled     = PETSC_FALSE;
3197:   }
3198:   MatGetOwnershipRange(M,&rstart,&rend);
3199:   aij = (Mat_SeqAIJ*)(Mreuse)->data;
3200:   ii  = aij->i;
3201:   jj  = aij->j;
3202:   aa  = aij->a;
3203:   for (i=0; i<m; i++) {
3204:     row   = rstart + i;
3205:     nz    = ii[i+1] - ii[i];
3206:     cwork = jj;     jj += nz;
3207:     vwork = aa;     aa += nz;
3208:     MatSetValues_MPIAIJ(M,1,&row,nz,cwork,vwork,INSERT_VALUES);
3209:   }

3211:   MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);
3212:   MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);
3213:   *newmat = M;

3215:   /* save submatrix used in processor for next request */
3216:   if (call ==  MAT_INITIAL_MATRIX) {
3217:     PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Mreuse);
3218:     PetscObjectDereference((PetscObject)Mreuse);
3219:   }

3221:   return(0);
3222: }

3227: PetscErrorCode  MatMPIAIJSetPreallocationCSR_MPIAIJ(Mat B,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[])
3228: {
3229:   PetscInt       m,cstart, cend,j,nnz,i,d;
3230:   PetscInt       *d_nnz,*o_nnz,nnz_max = 0,rstart,ii;
3231:   const PetscInt *JJ;
3232:   PetscScalar    *values;

3236:   if (Ii[0]) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"Ii[0] must be 0 it is %D",Ii[0]);

3238:   PetscLayoutSetBlockSize(B->rmap,1);
3239:   PetscLayoutSetBlockSize(B->cmap,1);
3240:   PetscLayoutSetUp(B->rmap);
3241:   PetscLayoutSetUp(B->cmap);
3242:   m      = B->rmap->n;
3243:   cstart = B->cmap->rstart;
3244:   cend   = B->cmap->rend;
3245:   rstart = B->rmap->rstart;

3247:   PetscMalloc2(m,PetscInt,&d_nnz,m,PetscInt,&o_nnz);

3249: #if defined(PETSC_USE_DEBUGGING)
3250:   for (i=0; i<m; i++) {
3251:     nnz     = Ii[i+1]- Ii[i];
3252:     JJ      = J + Ii[i];
3253:     if (nnz < 0) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative %D number of columns",i,nnz);
3254:     if (nnz && (JJ[0] < 0)) SETERRRQ1(PETSC_ERR_ARG_WRONGSTATE,"Row %D starts with negative column index",i,j);
3255:     if (nnz && (JJ[nnz-1] >= B->cmap->N) SETERRRQ3(PETSC_ERR_ARG_WRONGSTATE,"Row %D ends with too large a column index %D (max allowed %D)",i,JJ[nnz-1],B->cmap->N);
3256:   }
3257: #endif

3259:   for (i=0; i<m; i++) {
3260:     nnz     = Ii[i+1]- Ii[i];
3261:     JJ      = J + Ii[i];
3262:     nnz_max = PetscMax(nnz_max,nnz);
3263:     d       = 0;
3264:     for (j=0; j<nnz; j++) {
3265:       if (cstart <= JJ[j] && JJ[j] < cend) d++;
3266:     }
3267:     d_nnz[i] = d;
3268:     o_nnz[i] = nnz - d;
3269:   }
3270:   MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);
3271:   PetscFree2(d_nnz,o_nnz);

3273:   if (v) values = (PetscScalar*)v;
3274:   else {
3275:     PetscMalloc((nnz_max+1)*sizeof(PetscScalar),&values);
3276:     PetscMemzero(values,nnz_max*sizeof(PetscScalar));
3277:   }

3279:   for (i=0; i<m; i++) {
3280:     ii   = i + rstart;
3281:     nnz  = Ii[i+1]- Ii[i];
3282:     MatSetValues_MPIAIJ(B,1,&ii,nnz,J+Ii[i],values+(v ? Ii[i] : 0),INSERT_VALUES);
3283:   }
3284:   MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
3285:   MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);

3287:   if (!v) {
3288:     PetscFree(values);
3289:   }
3290:   return(0);
3291: }

3296: /*@
3297:    MatMPIAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in AIJ format
3298:    (the default parallel PETSc format).  

3300:    Collective on MPI_Comm

3302:    Input Parameters:
3303: +  B - the matrix 
3304: .  i - the indices into j for the start of each local row (starts with zero)
3305: .  j - the column indices for each local row (starts with zero)
3306: -  v - optional values in the matrix

3308:    Level: developer

3310:    Notes:
3311:        The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc;
3312:      thus you CANNOT change the matrix entries by changing the values of a[] after you have 
3313:      called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays.

3315:        The i and j indices are 0 based, and i indices are indices corresponding to the local j array.

3317:        The format which is used for the sparse matrix input, is equivalent to a
3318:     row-major ordering.. i.e for the following matrix, the input data expected is
3319:     as shown:

3321:         1 0 0
3322:         2 0 3     P0
3323:        -------
3324:         4 5 6     P1

3326:      Process0 [P0]: rows_owned=[0,1]
3327:         i =  {0,1,3}  [size = nrow+1  = 2+1]
3328:         j =  {0,0,2}  [size = nz = 6]
3329:         v =  {1,2,3}  [size = nz = 6]

3331:      Process1 [P1]: rows_owned=[2]
3332:         i =  {0,3}    [size = nrow+1  = 1+1]
3333:         j =  {0,1,2}  [size = nz = 6]
3334:         v =  {4,5,6}  [size = nz = 6]

3336: .keywords: matrix, aij, compressed row, sparse, parallel

3338: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatCreateMPIAIJ(), MPIAIJ,
3339:           MatCreateSeqAIJWithArrays(), MatCreateMPIAIJWithSplitArrays()
3340: @*/
3341: PetscErrorCode  MatMPIAIJSetPreallocationCSR(Mat B,const PetscInt i[],const PetscInt j[], const PetscScalar v[])
3342: {
3343:   PetscErrorCode ierr,(*f)(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]);

3346:   PetscObjectQueryFunction((PetscObject)B,"MatMPIAIJSetPreallocationCSR_C",(void (**)(void))&f);
3347:   if (f) {
3348:     (*f)(B,i,j,v);
3349:   }
3350:   return(0);
3351: }

3355: /*@C
3356:    MatMPIAIJSetPreallocation - Preallocates memory for a sparse parallel matrix in AIJ format
3357:    (the default parallel PETSc format).  For good matrix assembly performance
3358:    the user should preallocate the matrix storage by setting the parameters 
3359:    d_nz (or d_nnz) and o_nz (or o_nnz).  By setting these parameters accurately,
3360:    performance can be increased by more than a factor of 50.

3362:    Collective on MPI_Comm

3364:    Input Parameters:
3365: +  A - the matrix 
3366: .  d_nz  - number of nonzeros per row in DIAGONAL portion of local submatrix
3367:            (same value is used for all local rows)
3368: .  d_nnz - array containing the number of nonzeros in the various rows of the 
3369:            DIAGONAL portion of the local submatrix (possibly different for each row)
3370:            or PETSC_NULL, if d_nz is used to specify the nonzero structure. 
3371:            The size of this array is equal to the number of local rows, i.e 'm'. 
3372:            You must leave room for the diagonal entry even if it is zero.
3373: .  o_nz  - number of nonzeros per row in the OFF-DIAGONAL portion of local
3374:            submatrix (same value is used for all local rows).
3375: -  o_nnz - array containing the number of nonzeros in the various rows of the
3376:            OFF-DIAGONAL portion of the local submatrix (possibly different for
3377:            each row) or PETSC_NULL, if o_nz is used to specify the nonzero 
3378:            structure. The size of this array is equal to the number 
3379:            of local rows, i.e 'm'. 

3381:    If the *_nnz parameter is given then the *_nz parameter is ignored

3383:    The AIJ format (also called the Yale sparse matrix format or
3384:    compressed row storage (CSR)), is fully compatible with standard Fortran 77
3385:    storage.  The stored row and column indices begin with zero.  See the users manual for details.

3387:    The parallel matrix is partitioned such that the first m0 rows belong to 
3388:    process 0, the next m1 rows belong to process 1, the next m2 rows belong 
3389:    to process 2 etc.. where m0,m1,m2... are the input parameter 'm'.

3391:    The DIAGONAL portion of the local submatrix of a processor can be defined 
3392:    as the submatrix which is obtained by extraction the part corresponding 
3393:    to the rows r1-r2 and columns r1-r2 of the global matrix, where r1 is the 
3394:    first row that belongs to the processor, and r2 is the last row belonging 
3395:    to the this processor. This is a square mxm matrix. The remaining portion 
3396:    of the local submatrix (mxN) constitute the OFF-DIAGONAL portion.

3398:    If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored.

3400:    You can call MatGetInfo() to get information on how effective the preallocation was;
3401:    for example the fields mallocs,nz_allocated,nz_used,nz_unneeded;
3402:    You can also run with the option -info and look for messages with the string 
3403:    malloc in them to see if additional memory allocation was needed.

3405:    Example usage:
3406:   
3407:    Consider the following 8x8 matrix with 34 non-zero values, that is 
3408:    assembled across 3 processors. Lets assume that proc0 owns 3 rows,
3409:    proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 
3410:    as follows:

3412: .vb
3413:             1  2  0  |  0  3  0  |  0  4
3414:     Proc0   0  5  6  |  7  0  0  |  8  0
3415:             9  0 10  | 11  0  0  | 12  0
3416:     -------------------------------------
3417:            13  0 14  | 15 16 17  |  0  0
3418:     Proc1   0 18  0  | 19 20 21  |  0  0 
3419:             0  0  0  | 22 23  0  | 24  0
3420:     -------------------------------------
3421:     Proc2  25 26 27  |  0  0 28  | 29  0
3422:            30  0  0  | 31 32 33  |  0 34
3423: .ve

3425:    This can be represented as a collection of submatrices as:

3427: .vb
3428:       A B C
3429:       D E F
3430:       G H I
3431: .ve

3433:    Where the submatrices A,B,C are owned by proc0, D,E,F are
3434:    owned by proc1, G,H,I are owned by proc2.

3436:    The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively.
3437:    The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively.
3438:    The 'M','N' parameters are 8,8, and have the same values on all procs.

3440:    The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are
3441:    submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices
3442:    corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively.
3443:    Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL
3444:    part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ
3445:    matrix, ans [DF] as another SeqAIJ matrix.

3447:    When d_nz, o_nz parameters are specified, d_nz storage elements are
3448:    allocated for every row of the local diagonal submatrix, and o_nz
3449:    storage locations are allocated for every row of the OFF-DIAGONAL submat.
3450:    One way to choose d_nz and o_nz is to use the max nonzerors per local 
3451:    rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 
3452:    In this case, the values of d_nz,o_nz are:
3453: .vb
3454:      proc0 : dnz = 2, o_nz = 2
3455:      proc1 : dnz = 3, o_nz = 2
3456:      proc2 : dnz = 1, o_nz = 4
3457: .ve
3458:    We are allocating m*(d_nz+o_nz) storage locations for every proc. This
3459:    translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10
3460:    for proc3. i.e we are using 12+15+10=37 storage locations to store 
3461:    34 values.

3463:    When d_nnz, o_nnz parameters are specified, the storage is specified
3464:    for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices.
3465:    In the above case the values for d_nnz,o_nnz are:
3466: .vb
3467:      proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2]
3468:      proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1]
3469:      proc2: d_nnz = [1,1]   and o_nnz = [4,4]
3470: .ve
3471:    Here the space allocated is sum of all the above values i.e 34, and
3472:    hence pre-allocation is perfect.

3474:    Level: intermediate

3476: .keywords: matrix, aij, compressed row, sparse, parallel

3478: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateMPIAIJ(), MatMPIAIJSetPreallocationCSR(),
3479:           MPIAIJ, MatGetInfo()
3480: @*/
3481: PetscErrorCode  MatMPIAIJSetPreallocation(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[])
3482: {
3483:   PetscErrorCode ierr,(*f)(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[]);

3486:   PetscObjectQueryFunction((PetscObject)B,"MatMPIAIJSetPreallocation_C",(void (**)(void))&f);
3487:   if (f) {
3488:     (*f)(B,d_nz,d_nnz,o_nz,o_nnz);
3489:   }
3490:   return(0);
3491: }

3495: /*@
3496:      MatCreateMPIAIJWithArrays - creates a MPI AIJ matrix using arrays that contain in standard
3497:          CSR format the local rows.

3499:    Collective on MPI_Comm

3501:    Input Parameters:
3502: +  comm - MPI communicator
3503: .  m - number of local rows (Cannot be PETSC_DECIDE)
3504: .  n - This value should be the same as the local size used in creating the 
3505:        x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have
3506:        calculated if N is given) For square matrices n is almost always m.
3507: .  M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
3508: .  N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
3509: .   i - row indices
3510: .   j - column indices
3511: -   a - matrix values

3513:    Output Parameter:
3514: .   mat - the matrix

3516:    Level: intermediate

3518:    Notes:
3519:        The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc;
3520:      thus you CANNOT change the matrix entries by changing the values of a[] after you have 
3521:      called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays.

3523:        The i and j indices are 0 based, and i indices are indices corresponding to the local j array.

3525:        The format which is used for the sparse matrix input, is equivalent to a
3526:     row-major ordering.. i.e for the following matrix, the input data expected is
3527:     as shown:

3529:         1 0 0
3530:         2 0 3     P0
3531:        -------
3532:         4 5 6     P1

3534:      Process0 [P0]: rows_owned=[0,1]
3535:         i =  {0,1,3}  [size = nrow+1  = 2+1]
3536:         j =  {0,0,2}  [size = nz = 6]
3537:         v =  {1,2,3}  [size = nz = 6]

3539:      Process1 [P1]: rows_owned=[2]
3540:         i =  {0,3}    [size = nrow+1  = 1+1]
3541:         j =  {0,1,2}  [size = nz = 6]
3542:         v =  {4,5,6}  [size = nz = 6]

3544: .keywords: matrix, aij, compressed row, sparse, parallel

3546: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(),
3547:           MPIAIJ, MatCreateMPIAIJ(), MatCreateMPIAIJWithSplitArrays()
3548: @*/
3549: PetscErrorCode  MatCreateMPIAIJWithArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,const PetscInt i[],const PetscInt j[],const PetscScalar a[],Mat *mat)
3550: {

3554:   if (i[0]) {
3555:     SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0");
3556:   }
3557:   if (m < 0) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative");
3558:   MatCreate(comm,mat);
3559:   MatSetSizes(*mat,m,n,M,N);
3560:   MatSetType(*mat,MATMPIAIJ);
3561:   MatMPIAIJSetPreallocationCSR(*mat,i,j,a);
3562:   return(0);
3563: }

3567: /*@C
3568:    MatCreateMPIAIJ - Creates a sparse parallel matrix in AIJ format
3569:    (the default parallel PETSc format).  For good matrix assembly performance
3570:    the user should preallocate the matrix storage by setting the parameters 
3571:    d_nz (or d_nnz) and o_nz (or o_nnz).  By setting these parameters accurately,
3572:    performance can be increased by more than a factor of 50.

3574:    Collective on MPI_Comm

3576:    Input Parameters:
3577: +  comm - MPI communicator
3578: .  m - number of local rows (or PETSC_DECIDE to have calculated if M is given)
3579:            This value should be the same as the local size used in creating the 
3580:            y vector for the matrix-vector product y = Ax.
3581: .  n - This value should be the same as the local size used in creating the 
3582:        x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have
3583:        calculated if N is given) For square matrices n is almost always m.
3584: .  M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
3585: .  N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
3586: .  d_nz  - number of nonzeros per row in DIAGONAL portion of local submatrix
3587:            (same value is used for all local rows)
3588: .  d_nnz - array containing the number of nonzeros in the various rows of the 
3589:            DIAGONAL portion of the local submatrix (possibly different for each row)
3590:            or PETSC_NULL, if d_nz is used to specify the nonzero structure. 
3591:            The size of this array is equal to the number of local rows, i.e 'm'. 
3592:            You must leave room for the diagonal entry even if it is zero.
3593: .  o_nz  - number of nonzeros per row in the OFF-DIAGONAL portion of local
3594:            submatrix (same value is used for all local rows).
3595: -  o_nnz - array containing the number of nonzeros in the various rows of the
3596:            OFF-DIAGONAL portion of the local submatrix (possibly different for
3597:            each row) or PETSC_NULL, if o_nz is used to specify the nonzero 
3598:            structure. The size of this array is equal to the number 
3599:            of local rows, i.e 'm'. 

3601:    Output Parameter:
3602: .  A - the matrix 

3604:    It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(),
3605:    MatXXXXSetPreallocation() paradgm instead of this routine directly. 
3606:    [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation]

3608:    Notes:
3609:    If the *_nnz parameter is given then the *_nz parameter is ignored

3611:    m,n,M,N parameters specify the size of the matrix, and its partitioning across
3612:    processors, while d_nz,d_nnz,o_nz,o_nnz parameters specify the approximate
3613:    storage requirements for this matrix.

3615:    If PETSC_DECIDE or  PETSC_DETERMINE is used for a particular argument on one 
3616:    processor than it must be used on all processors that share the object for 
3617:    that argument.

3619:    The user MUST specify either the local or global matrix dimensions
3620:    (possibly both).

3622:    The parallel matrix is partitioned across processors such that the
3623:    first m0 rows belong to process 0, the next m1 rows belong to
3624:    process 1, the next m2 rows belong to process 2 etc.. where
3625:    m0,m1,m2,.. are the input parameter 'm'. i.e each processor stores
3626:    values corresponding to [m x N] submatrix.

3628:    The columns are logically partitioned with the n0 columns belonging
3629:    to 0th partition, the next n1 columns belonging to the next
3630:    partition etc.. where n0,n1,n2... are the the input parameter 'n'.

3632:    The DIAGONAL portion of the local submatrix on any given processor
3633:    is the submatrix corresponding to the rows and columns m,n
3634:    corresponding to the given processor. i.e diagonal matrix on
3635:    process 0 is [m0 x n0], diagonal matrix on process 1 is [m1 x n1]
3636:    etc. The remaining portion of the local submatrix [m x (N-n)]
3637:    constitute the OFF-DIAGONAL portion. The example below better
3638:    illustrates this concept.

3640:    For a square global matrix we define each processor's diagonal portion 
3641:    to be its local rows and the corresponding columns (a square submatrix);  
3642:    each processor's off-diagonal portion encompasses the remainder of the
3643:    local matrix (a rectangular submatrix). 

3645:    If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored.

3647:    When calling this routine with a single process communicator, a matrix of
3648:    type SEQAIJ is returned.  If a matrix of type MPIAIJ is desired for this
3649:    type of communicator, use the construction mechanism:
3650:      MatCreate(...,&A); MatSetType(A,MATMPIAIJ); MatSetSizes(A, m,n,M,N); MatMPIAIJSetPreallocation(A,...);
3651:  
3652:    By default, this format uses inodes (identical nodes) when possible.
3653:    We search for consecutive rows with the same nonzero structure, thereby
3654:    reusing matrix information to achieve increased efficiency.

3656:    Options Database Keys:
3657: +  -mat_no_inode  - Do not use inodes
3658: .  -mat_inode_limit <limit> - Sets inode limit (max limit=5)
3659: -  -mat_aij_oneindex - Internally use indexing starting at 1
3660:         rather than 0.  Note that when calling MatSetValues(),
3661:         the user still MUST index entries starting at 0!


3664:    Example usage:
3665:   
3666:    Consider the following 8x8 matrix with 34 non-zero values, that is 
3667:    assembled across 3 processors. Lets assume that proc0 owns 3 rows,
3668:    proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 
3669:    as follows:

3671: .vb
3672:             1  2  0  |  0  3  0  |  0  4
3673:     Proc0   0  5  6  |  7  0  0  |  8  0
3674:             9  0 10  | 11  0  0  | 12  0
3675:     -------------------------------------
3676:            13  0 14  | 15 16 17  |  0  0
3677:     Proc1   0 18  0  | 19 20 21  |  0  0 
3678:             0  0  0  | 22 23  0  | 24  0
3679:     -------------------------------------
3680:     Proc2  25 26 27  |  0  0 28  | 29  0
3681:            30  0  0  | 31 32 33  |  0 34
3682: .ve

3684:    This can be represented as a collection of submatrices as:

3686: .vb
3687:       A B C
3688:       D E F
3689:       G H I
3690: .ve

3692:    Where the submatrices A,B,C are owned by proc0, D,E,F are
3693:    owned by proc1, G,H,I are owned by proc2.

3695:    The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively.
3696:    The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively.
3697:    The 'M','N' parameters are 8,8, and have the same values on all procs.

3699:    The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are
3700:    submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices
3701:    corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively.
3702:    Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL
3703:    part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ
3704:    matrix, ans [DF] as another SeqAIJ matrix.

3706:    When d_nz, o_nz parameters are specified, d_nz storage elements are
3707:    allocated for every row of the local diagonal submatrix, and o_nz
3708:    storage locations are allocated for every row of the OFF-DIAGONAL submat.
3709:    One way to choose d_nz and o_nz is to use the max nonzerors per local 
3710:    rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 
3711:    In this case, the values of d_nz,o_nz are:
3712: .vb
3713:      proc0 : dnz = 2, o_nz = 2
3714:      proc1 : dnz = 3, o_nz = 2
3715:      proc2 : dnz = 1, o_nz = 4
3716: .ve
3717:    We are allocating m*(d_nz+o_nz) storage locations for every proc. This
3718:    translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10
3719:    for proc3. i.e we are using 12+15+10=37 storage locations to store 
3720:    34 values.

3722:    When d_nnz, o_nnz parameters are specified, the storage is specified
3723:    for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices.
3724:    In the above case the values for d_nnz,o_nnz are:
3725: .vb
3726:      proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2]
3727:      proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1]
3728:      proc2: d_nnz = [1,1]   and o_nnz = [4,4]
3729: .ve
3730:    Here the space allocated is sum of all the above values i.e 34, and
3731:    hence pre-allocation is perfect.

3733:    Level: intermediate

3735: .keywords: matrix, aij, compressed row, sparse, parallel

3737: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(),
3738:           MPIAIJ, MatCreateMPIAIJWithArrays()
3739: @*/
3740: PetscErrorCode  MatCreateMPIAIJ(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)
3741: {
3743:   PetscMPIInt    size;

3746:   MatCreate(comm,A);
3747:   MatSetSizes(*A,m,n,M,N);
3748:   MPI_Comm_size(comm,&size);
3749:   if (size > 1) {
3750:     MatSetType(*A,MATMPIAIJ);
3751:     MatMPIAIJSetPreallocation(*A,d_nz,d_nnz,o_nz,o_nnz);
3752:   } else {
3753:     MatSetType(*A,MATSEQAIJ);
3754:     MatSeqAIJSetPreallocation(*A,d_nz,d_nnz);
3755:   }
3756:   return(0);
3757: }

3761: PetscErrorCode  MatMPIAIJGetSeqAIJ(Mat A,Mat *Ad,Mat *Ao,PetscInt *colmap[])
3762: {
3763:   Mat_MPIAIJ *a = (Mat_MPIAIJ *)A->data;

3766:   *Ad     = a->A;
3767:   *Ao     = a->B;
3768:   *colmap = a->garray;
3769:   return(0);
3770: }

3774: PetscErrorCode MatSetColoring_MPIAIJ(Mat A,ISColoring coloring)
3775: {
3777:   PetscInt       i;
3778:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;

3781:   if (coloring->ctype == IS_COLORING_GLOBAL) {
3782:     ISColoringValue *allcolors,*colors;
3783:     ISColoring      ocoloring;

3785:     /* set coloring for diagonal portion */
3786:     MatSetColoring_SeqAIJ(a->A,coloring);

3788:     /* set coloring for off-diagonal portion */
3789:     ISAllGatherColors(((PetscObject)A)->comm,coloring->n,coloring->colors,PETSC_NULL,&allcolors);
3790:     PetscMalloc((a->B->cmap->n+1)*sizeof(ISColoringValue),&colors);
3791:     for (i=0; i<a->B->cmap->n; i++) {
3792:       colors[i] = allcolors[a->garray[i]];
3793:     }
3794:     PetscFree(allcolors);
3795:     ISColoringCreate(MPI_COMM_SELF,coloring->n,a->B->cmap->n,colors,&ocoloring);
3796:     MatSetColoring_SeqAIJ(a->B,ocoloring);
3797:     ISColoringDestroy(ocoloring);
3798:   } else if (coloring->ctype == IS_COLORING_GHOSTED) {
3799:     ISColoringValue *colors;
3800:     PetscInt        *larray;
3801:     ISColoring      ocoloring;

3803:     /* set coloring for diagonal portion */
3804:     PetscMalloc((a->A->cmap->n+1)*sizeof(PetscInt),&larray);
3805:     for (i=0; i<a->A->cmap->n; i++) {
3806:       larray[i] = i + A->cmap->rstart;
3807:     }
3808:     ISGlobalToLocalMappingApply(A->mapping,IS_GTOLM_MASK,a->A->cmap->n,larray,PETSC_NULL,larray);
3809:     PetscMalloc((a->A->cmap->n+1)*sizeof(ISColoringValue),&colors);
3810:     for (i=0; i<a->A->cmap->n; i++) {
3811:       colors[i] = coloring->colors[larray[i]];
3812:     }
3813:     PetscFree(larray);
3814:     ISColoringCreate(PETSC_COMM_SELF,coloring->n,a->A->cmap->n,colors,&ocoloring);
3815:     MatSetColoring_SeqAIJ(a->A,ocoloring);
3816:     ISColoringDestroy(ocoloring);

3818:     /* set coloring for off-diagonal portion */
3819:     PetscMalloc((a->B->cmap->n+1)*sizeof(PetscInt),&larray);
3820:     ISGlobalToLocalMappingApply(A->mapping,IS_GTOLM_MASK,a->B->cmap->n,a->garray,PETSC_NULL,larray);
3821:     PetscMalloc((a->B->cmap->n+1)*sizeof(ISColoringValue),&colors);
3822:     for (i=0; i<a->B->cmap->n; i++) {
3823:       colors[i] = coloring->colors[larray[i]];
3824:     }
3825:     PetscFree(larray);
3826:     ISColoringCreate(MPI_COMM_SELF,coloring->n,a->B->cmap->n,colors,&ocoloring);
3827:     MatSetColoring_SeqAIJ(a->B,ocoloring);
3828:     ISColoringDestroy(ocoloring);
3829:   } else {
3830:     SETERRQ1(PETSC_ERR_SUP,"No support ISColoringType %d",(int)coloring->ctype);
3831:   }

3833:   return(0);
3834: }

3836: #if defined(PETSC_HAVE_ADIC)
3839: PetscErrorCode MatSetValuesAdic_MPIAIJ(Mat A,void *advalues)
3840: {
3841:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;

3845:   MatSetValuesAdic_SeqAIJ(a->A,advalues);
3846:   MatSetValuesAdic_SeqAIJ(a->B,advalues);
3847:   return(0);
3848: }
3849: #endif

3853: PetscErrorCode MatSetValuesAdifor_MPIAIJ(Mat A,PetscInt nl,void *advalues)
3854: {
3855:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;

3859:   MatSetValuesAdifor_SeqAIJ(a->A,nl,advalues);
3860:   MatSetValuesAdifor_SeqAIJ(a->B,nl,advalues);
3861:   return(0);
3862: }

3866: /*@
3867:       MatMerge - Creates a single large PETSc matrix by concatinating sequential
3868:                  matrices from each processor

3870:     Collective on MPI_Comm

3872:    Input Parameters:
3873: +    comm - the communicators the parallel matrix will live on
3874: .    inmat - the input sequential matrices
3875: .    n - number of local columns (or PETSC_DECIDE)
3876: -    scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX

3878:    Output Parameter:
3879: .    outmat - the parallel matrix generated

3881:     Level: advanced

3883:    Notes: The number of columns of the matrix in EACH processor MUST be the same.

3885: @*/
3886: PetscErrorCode  MatMerge(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat)
3887: {
3889:   PetscInt       m,N,i,rstart,nnz,Ii,*dnz,*onz;
3890:   PetscInt       *indx;
3891:   PetscScalar    *values;

3894:   MatGetSize(inmat,&m,&N);
3895:   if (scall == MAT_INITIAL_MATRIX){
3896:     /* count nonzeros in each row, for diagonal and off diagonal portion of matrix */
3897:     if (n == PETSC_DECIDE){
3898:       PetscSplitOwnership(comm,&n,&N);
3899:     }
3900:     MPI_Scan(&m, &rstart,1,MPIU_INT,MPI_SUM,comm);
3901:     rstart -= m;

3903:     MatPreallocateInitialize(comm,m,n,dnz,onz);
3904:     for (i=0;i<m;i++) {
3905:       MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,PETSC_NULL);
3906:       MatPreallocateSet(i+rstart,nnz,indx,dnz,onz);
3907:       MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,PETSC_NULL);
3908:     }
3909:     /* This routine will ONLY return MPIAIJ type matrix */
3910:     MatCreate(comm,outmat);
3911:     MatSetSizes(*outmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);
3912:     MatSetType(*outmat,MATMPIAIJ);
3913:     MatMPIAIJSetPreallocation(*outmat,0,dnz,0,onz);
3914:     MatPreallocateFinalize(dnz,onz);
3915: 
3916:   } else if (scall == MAT_REUSE_MATRIX){
3917:     MatGetOwnershipRange(*outmat,&rstart,PETSC_NULL);
3918:   } else {
3919:     SETERRQ1(PETSC_ERR_ARG_WRONG,"Invalid MatReuse %d",(int)scall);
3920:   }

3922:   for (i=0;i<m;i++) {
3923:     MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,&values);
3924:     Ii    = i + rstart;
3925:     MatSetValues(*outmat,1,&Ii,nnz,indx,values,INSERT_VALUES);
3926:     MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,&values);
3927:   }
3928:   MatDestroy(inmat);
3929:   MatAssemblyBegin(*outmat,MAT_FINAL_ASSEMBLY);
3930:   MatAssemblyEnd(*outmat,MAT_FINAL_ASSEMBLY);

3932:   return(0);
3933: }

3937: PetscErrorCode MatFileSplit(Mat A,char *outfile)
3938: {
3939:   PetscErrorCode    ierr;
3940:   PetscMPIInt       rank;
3941:   PetscInt          m,N,i,rstart,nnz;
3942:   size_t            len;
3943:   const PetscInt    *indx;
3944:   PetscViewer       out;
3945:   char              *name;
3946:   Mat               B;
3947:   const PetscScalar *values;

3950:   MatGetLocalSize(A,&m,0);
3951:   MatGetSize(A,0,&N);
3952:   /* Should this be the type of the diagonal block of A? */
3953:   MatCreate(PETSC_COMM_SELF,&B);
3954:   MatSetSizes(B,m,N,m,N);
3955:   MatSetType(B,MATSEQAIJ);
3956:   MatSeqAIJSetPreallocation(B,0,PETSC_NULL);
3957:   MatGetOwnershipRange(A,&rstart,0);
3958:   for (i=0;i<m;i++) {
3959:     MatGetRow(A,i+rstart,&nnz,&indx,&values);
3960:     MatSetValues(B,1,&i,nnz,indx,values,INSERT_VALUES);
3961:     MatRestoreRow(A,i+rstart,&nnz,&indx,&values);
3962:   }
3963:   MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
3964:   MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);

3966:   MPI_Comm_rank(((PetscObject)A)->comm,&rank);
3967:   PetscStrlen(outfile,&len);
3968:   PetscMalloc((len+5)*sizeof(char),&name);
3969:   sprintf(name,"%s.%d",outfile,rank);
3970:   PetscViewerBinaryOpen(PETSC_COMM_SELF,name,FILE_MODE_APPEND,&out);
3971:   PetscFree(name);
3972:   MatView(B,out);
3973:   PetscViewerDestroy(out);
3974:   MatDestroy(B);
3975:   return(0);
3976: }

3978: EXTERN PetscErrorCode MatDestroy_MPIAIJ(Mat);
3981: PetscErrorCode  MatDestroy_MPIAIJ_SeqsToMPI(Mat A)
3982: {
3983:   PetscErrorCode       ierr;
3984:   Mat_Merge_SeqsToMPI  *merge;
3985:   PetscContainer       container;

3988:   PetscObjectQuery((PetscObject)A,"MatMergeSeqsToMPI",(PetscObject *)&container);
3989:   if (container) {
3990:     PetscContainerGetPointer(container,(void **)&merge);
3991:     PetscFree(merge->id_r);
3992:     PetscFree(merge->len_s);
3993:     PetscFree(merge->len_r);
3994:     PetscFree(merge->bi);
3995:     PetscFree(merge->bj);
3996:     PetscFree(merge->buf_ri[0]);
3997:     PetscFree(merge->buf_ri);
3998:     PetscFree(merge->buf_rj[0]);
3999:     PetscFree(merge->buf_rj);
4000:     PetscFree(merge->coi);
4001:     PetscFree(merge->coj);
4002:     PetscFree(merge->owners_co);
4003:     PetscLayoutDestroy(merge->rowmap);
4004: 
4005:     PetscContainerDestroy(container);
4006:     PetscObjectCompose((PetscObject)A,"MatMergeSeqsToMPI",0);
4007:   }
4008:   PetscFree(merge);

4010:   MatDestroy_MPIAIJ(A);
4011:   return(0);
4012: }

4014:  #include ../src/mat/utils/freespace.h
4015:  #include petscbt.h

4019: /*@C
4020:       MatMerge_SeqsToMPI - Creates a MPIAIJ matrix by adding sequential
4021:                  matrices from each processor

4023:     Collective on MPI_Comm

4025:    Input Parameters:
4026: +    comm - the communicators the parallel matrix will live on
4027: .    seqmat - the input sequential matrices
4028: .    m - number of local rows (or PETSC_DECIDE)
4029: .    n - number of local columns (or PETSC_DECIDE)
4030: -    scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX

4032:    Output Parameter:
4033: .    mpimat - the parallel matrix generated

4035:     Level: advanced

4037:    Notes: 
4038:      The dimensions of the sequential matrix in each processor MUST be the same.
4039:      The input seqmat is included into the container "Mat_Merge_SeqsToMPI", and will be
4040:      destroyed when mpimat is destroyed. Call PetscObjectQuery() to access seqmat.
4041: @*/
4042: PetscErrorCode  MatMerge_SeqsToMPINumeric(Mat seqmat,Mat mpimat)
4043: {
4044:   PetscErrorCode       ierr;
4045:   MPI_Comm             comm=((PetscObject)mpimat)->comm;
4046:   Mat_SeqAIJ           *a=(Mat_SeqAIJ*)seqmat->data;
4047:   PetscMPIInt          size,rank,taga,*len_s;
4048:   PetscInt             N=mpimat->cmap->N,i,j,*owners,*ai=a->i,*aj=a->j;
4049:   PetscInt             proc,m;
4050:   PetscInt             **buf_ri,**buf_rj;
4051:   PetscInt             k,anzi,*bj_i,*bi,*bj,arow,bnzi,nextaj;
4052:   PetscInt             nrows,**buf_ri_k,**nextrow,**nextai;
4053:   MPI_Request          *s_waits,*r_waits;
4054:   MPI_Status           *status;
4055:   MatScalar            *aa=a->a;
4056:   MatScalar            **abuf_r,*ba_i;
4057:   Mat_Merge_SeqsToMPI  *merge;
4058:   PetscContainer       container;
4059: 
4061:   PetscLogEventBegin(MAT_Seqstompinum,seqmat,0,0,0);

4063:   MPI_Comm_size(comm,&size);
4064:   MPI_Comm_rank(comm,&rank);

4066:   PetscObjectQuery((PetscObject)mpimat,"MatMergeSeqsToMPI",(PetscObject *)&container);
4067:   if (container) {
4068:     PetscContainerGetPointer(container,(void **)&merge);
4069:   }
4070:   bi     = merge->bi;
4071:   bj     = merge->bj;
4072:   buf_ri = merge->buf_ri;
4073:   buf_rj = merge->buf_rj;

4075:   PetscMalloc(size*sizeof(MPI_Status),&status);
4076:   owners = merge->rowmap->range;
4077:   len_s  = merge->len_s;

4079:   /* send and recv matrix values */
4080:   /*-----------------------------*/
4081:   PetscObjectGetNewTag((PetscObject)mpimat,&taga);
4082:   PetscPostIrecvScalar(comm,taga,merge->nrecv,merge->id_r,merge->len_r,&abuf_r,&r_waits);

4084:   PetscMalloc((merge->nsend+1)*sizeof(MPI_Request),&s_waits);
4085:   for (proc=0,k=0; proc<size; proc++){
4086:     if (!len_s[proc]) continue;
4087:     i = owners[proc];
4088:     MPI_Isend(aa+ai[i],len_s[proc],MPIU_MATSCALAR,proc,taga,comm,s_waits+k);
4089:     k++;
4090:   }

4092:   if (merge->nrecv) {MPI_Waitall(merge->nrecv,r_waits,status);}
4093:   if (merge->nsend) {MPI_Waitall(merge->nsend,s_waits,status);}
4094:   PetscFree(status);

4096:   PetscFree(s_waits);
4097:   PetscFree(r_waits);

4099:   /* insert mat values of mpimat */
4100:   /*----------------------------*/
4101:   PetscMalloc(N*sizeof(PetscScalar),&ba_i);
4102:   PetscMalloc3(merge->nrecv,PetscInt*,&buf_ri_k,merge->nrecv,PetscInt*,&nextrow,merge->nrecv,PetscInt*,&nextai);

4104:   for (k=0; k<merge->nrecv; k++){
4105:     buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */
4106:     nrows = *(buf_ri_k[k]);
4107:     nextrow[k]  = buf_ri_k[k]+1;  /* next row number of k-th recved i-structure */
4108:     nextai[k]   = buf_ri_k[k] + (nrows + 1);/* poins to the next i-structure of k-th recved i-structure  */
4109:   }

4111:   /* set values of ba */
4112:   m = merge->rowmap->n;
4113:   for (i=0; i<m; i++) {
4114:     arow = owners[rank] + i;
4115:     bj_i = bj+bi[i];  /* col indices of the i-th row of mpimat */
4116:     bnzi = bi[i+1] - bi[i];
4117:     PetscMemzero(ba_i,bnzi*sizeof(PetscScalar));

4119:     /* add local non-zero vals of this proc's seqmat into ba */
4120:     anzi = ai[arow+1] - ai[arow];
4121:     aj   = a->j + ai[arow];
4122:     aa   = a->a + ai[arow];
4123:     nextaj = 0;
4124:     for (j=0; nextaj<anzi; j++){
4125:       if (*(bj_i + j) == aj[nextaj]){ /* bcol == acol */
4126:         ba_i[j] += aa[nextaj++];
4127:       }
4128:     }

4130:     /* add received vals into ba */
4131:     for (k=0; k<merge->nrecv; k++){ /* k-th received message */
4132:       /* i-th row */
4133:       if (i == *nextrow[k]) {
4134:         anzi = *(nextai[k]+1) - *nextai[k];
4135:         aj   = buf_rj[k] + *(nextai[k]);
4136:         aa   = abuf_r[k] + *(nextai[k]);
4137:         nextaj = 0;
4138:         for (j=0; nextaj<anzi; j++){
4139:           if (*(bj_i + j) == aj[nextaj]){ /* bcol == acol */
4140:             ba_i[j] += aa[nextaj++];
4141:           }
4142:         }
4143:         nextrow[k]++; nextai[k]++;
4144:       }
4145:     }
4146:     MatSetValues(mpimat,1,&arow,bnzi,bj_i,ba_i,INSERT_VALUES);
4147:   }
4148:   MatAssemblyBegin(mpimat,MAT_FINAL_ASSEMBLY);
4149:   MatAssemblyEnd(mpimat,MAT_FINAL_ASSEMBLY);

4151:   PetscFree(abuf_r[0]);
4152:   PetscFree(abuf_r);
4153:   PetscFree(ba_i);
4154:   PetscFree3(buf_ri_k,nextrow,nextai);
4155:   PetscLogEventEnd(MAT_Seqstompinum,seqmat,0,0,0);
4156:   return(0);
4157: }

4161: PetscErrorCode  MatMerge_SeqsToMPISymbolic(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,Mat *mpimat)
4162: {
4163:   PetscErrorCode       ierr;
4164:   Mat                  B_mpi;
4165:   Mat_SeqAIJ           *a=(Mat_SeqAIJ*)seqmat->data;
4166:   PetscMPIInt          size,rank,tagi,tagj,*len_s,*len_si,*len_ri;
4167:   PetscInt             **buf_rj,**buf_ri,**buf_ri_k;
4168:   PetscInt             M=seqmat->rmap->n,N=seqmat->cmap->n,i,*owners,*ai=a->i,*aj=a->j;
4169:   PetscInt             len,proc,*dnz,*onz;
4170:   PetscInt             k,anzi,*bi,*bj,*lnk,nlnk,arow,bnzi,nspacedouble=0;
4171:   PetscInt             nrows,*buf_s,*buf_si,*buf_si_i,**nextrow,**nextai;
4172:   MPI_Request          *si_waits,*sj_waits,*ri_waits,*rj_waits;
4173:   MPI_Status           *status;
4174:   PetscFreeSpaceList   free_space=PETSC_NULL,current_space=PETSC_NULL;
4175:   PetscBT              lnkbt;
4176:   Mat_Merge_SeqsToMPI  *merge;
4177:   PetscContainer       container;

4180:   PetscLogEventBegin(MAT_Seqstompisym,seqmat,0,0,0);

4182:   /* make sure it is a PETSc comm */
4183:   PetscCommDuplicate(comm,&comm,PETSC_NULL);
4184:   MPI_Comm_size(comm,&size);
4185:   MPI_Comm_rank(comm,&rank);
4186: 
4187:   PetscNew(Mat_Merge_SeqsToMPI,&merge);
4188:   PetscMalloc(size*sizeof(MPI_Status),&status);

4190:   /* determine row ownership */
4191:   /*---------------------------------------------------------*/
4192:   PetscLayoutCreate(comm,&merge->rowmap);
4193:   PetscLayoutSetLocalSize(merge->rowmap,m);
4194:   PetscLayoutSetSize(merge->rowmap,M);
4195:   PetscLayoutSetBlockSize(merge->rowmap,1);
4196:   PetscLayoutSetUp(merge->rowmap);
4197:   PetscMalloc(size*sizeof(PetscMPIInt),&len_si);
4198:   PetscMalloc(size*sizeof(PetscMPIInt),&merge->len_s);
4199: 
4200:   m      = merge->rowmap->n;
4201:   M      = merge->rowmap->N;
4202:   owners = merge->rowmap->range;

4204:   /* determine the number of messages to send, their lengths */
4205:   /*---------------------------------------------------------*/
4206:   len_s  = merge->len_s;

4208:   len = 0;  /* length of buf_si[] */
4209:   merge->nsend = 0;
4210:   for (proc=0; proc<size; proc++){
4211:     len_si[proc] = 0;
4212:     if (proc == rank){
4213:       len_s[proc] = 0;
4214:     } else {
4215:       len_si[proc] = owners[proc+1] - owners[proc] + 1;
4216:       len_s[proc] = ai[owners[proc+1]] - ai[owners[proc]]; /* num of rows to be sent to [proc] */
4217:     }
4218:     if (len_s[proc]) {
4219:       merge->nsend++;
4220:       nrows = 0;
4221:       for (i=owners[proc]; i<owners[proc+1]; i++){
4222:         if (ai[i+1] > ai[i]) nrows++;
4223:       }
4224:       len_si[proc] = 2*(nrows+1);
4225:       len += len_si[proc];
4226:     }
4227:   }

4229:   /* determine the number and length of messages to receive for ij-structure */
4230:   /*-------------------------------------------------------------------------*/
4231:   PetscGatherNumberOfMessages(comm,PETSC_NULL,len_s,&merge->nrecv);
4232:   PetscGatherMessageLengths2(comm,merge->nsend,merge->nrecv,len_s,len_si,&merge->id_r,&merge->len_r,&len_ri);

4234:   /* post the Irecv of j-structure */
4235:   /*-------------------------------*/
4236:   PetscCommGetNewTag(comm,&tagj);
4237:   PetscPostIrecvInt(comm,tagj,merge->nrecv,merge->id_r,merge->len_r,&buf_rj,&rj_waits);

4239:   /* post the Isend of j-structure */
4240:   /*--------------------------------*/
4241:   PetscMalloc2(merge->nsend,MPI_Request,&si_waits,merge->nsend,MPI_Request,&sj_waits);

4243:   for (proc=0, k=0; proc<size; proc++){
4244:     if (!len_s[proc]) continue;
4245:     i = owners[proc];
4246:     MPI_Isend(aj+ai[i],len_s[proc],MPIU_INT,proc,tagj,comm,sj_waits+k);
4247:     k++;
4248:   }

4250:   /* receives and sends of j-structure are complete */
4251:   /*------------------------------------------------*/
4252:   if (merge->nrecv) {MPI_Waitall(merge->nrecv,rj_waits,status);}
4253:   if (merge->nsend) {MPI_Waitall(merge->nsend,sj_waits,status);}
4254: 
4255:   /* send and recv i-structure */
4256:   /*---------------------------*/
4257:   PetscCommGetNewTag(comm,&tagi);
4258:   PetscPostIrecvInt(comm,tagi,merge->nrecv,merge->id_r,len_ri,&buf_ri,&ri_waits);
4259: 
4260:   PetscMalloc((len+1)*sizeof(PetscInt),&buf_s);
4261:   buf_si = buf_s;  /* points to the beginning of k-th msg to be sent */
4262:   for (proc=0,k=0; proc<size; proc++){
4263:     if (!len_s[proc]) continue;
4264:     /* form outgoing message for i-structure: 
4265:          buf_si[0]:                 nrows to be sent
4266:                [1:nrows]:           row index (global)
4267:                [nrows+1:2*nrows+1]: i-structure index
4268:     */
4269:     /*-------------------------------------------*/
4270:     nrows = len_si[proc]/2 - 1;
4271:     buf_si_i    = buf_si + nrows+1;
4272:     buf_si[0]   = nrows;
4273:     buf_si_i[0] = 0;
4274:     nrows = 0;
4275:     for (i=owners[proc]; i<owners[proc+1]; i++){
4276:       anzi = ai[i+1] - ai[i];
4277:       if (anzi) {
4278:         buf_si_i[nrows+1] = buf_si_i[nrows] + anzi; /* i-structure */
4279:         buf_si[nrows+1] = i-owners[proc]; /* local row index */
4280:         nrows++;
4281:       }
4282:     }
4283:     MPI_Isend(buf_si,len_si[proc],MPIU_INT,proc,tagi,comm,si_waits+k);
4284:     k++;
4285:     buf_si += len_si[proc];
4286:   }

4288:   if (merge->nrecv) {MPI_Waitall(merge->nrecv,ri_waits,status);}
4289:   if (merge->nsend) {MPI_Waitall(merge->nsend,si_waits,status);}

4291:   PetscInfo2(seqmat,"nsend: %D, nrecv: %D\n",merge->nsend,merge->nrecv);
4292:   for (i=0; i<merge->nrecv; i++){
4293:     PetscInfo3(seqmat,"recv len_ri=%D, len_rj=%D from [%D]\n",len_ri[i],merge->len_r[i],merge->id_r[i]);
4294:   }

4296:   PetscFree(len_si);
4297:   PetscFree(len_ri);
4298:   PetscFree(rj_waits);
4299:   PetscFree2(si_waits,sj_waits);
4300:   PetscFree(ri_waits);
4301:   PetscFree(buf_s);
4302:   PetscFree(status);

4304:   /* compute a local seq matrix in each processor */
4305:   /*----------------------------------------------*/
4306:   /* allocate bi array and free space for accumulating nonzero column info */
4307:   PetscMalloc((m+1)*sizeof(PetscInt),&bi);
4308:   bi[0] = 0;

4310:   /* create and initialize a linked list */
4311:   nlnk = N+1;
4312:   PetscLLCreate(N,N,nlnk,lnk,lnkbt);
4313: 
4314:   /* initial FreeSpace size is 2*(num of local nnz(seqmat)) */
4315:   len = 0;
4316:   len  = ai[owners[rank+1]] - ai[owners[rank]];
4317:   PetscFreeSpaceGet((PetscInt)(2*len+1),&free_space);
4318:   current_space = free_space;

4320:   /* determine symbolic info for each local row */
4321:   PetscMalloc3(merge->nrecv,PetscInt*,&buf_ri_k,merge->nrecv,PetscInt*,&nextrow,merge->nrecv,PetscInt*,&nextai);

4323:   for (k=0; k<merge->nrecv; k++){
4324:     buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */
4325:     nrows = *buf_ri_k[k];
4326:     nextrow[k]  = buf_ri_k[k] + 1;  /* next row number of k-th recved i-structure */
4327:     nextai[k]   = buf_ri_k[k] + (nrows + 1);/* poins to the next i-structure of k-th recved i-structure  */
4328:   }

4330:   MatPreallocateInitialize(comm,m,n,dnz,onz);
4331:   len = 0;
4332:   for (i=0;i<m;i++) {
4333:     bnzi   = 0;
4334:     /* add local non-zero cols of this proc's seqmat into lnk */
4335:     arow   = owners[rank] + i;
4336:     anzi   = ai[arow+1] - ai[arow];
4337:     aj     = a->j + ai[arow];
4338:     PetscLLAdd(anzi,aj,N,nlnk,lnk,lnkbt);
4339:     bnzi += nlnk;
4340:     /* add received col data into lnk */
4341:     for (k=0; k<merge->nrecv; k++){ /* k-th received message */
4342:       if (i == *nextrow[k]) { /* i-th row */
4343:         anzi = *(nextai[k]+1) - *nextai[k];
4344:         aj   = buf_rj[k] + *nextai[k];
4345:         PetscLLAdd(anzi,aj,N,nlnk,lnk,lnkbt);
4346:         bnzi += nlnk;
4347:         nextrow[k]++; nextai[k]++;
4348:       }
4349:     }
4350:     if (len < bnzi) len = bnzi;  /* =max(bnzi) */

4352:     /* if free space is not available, make more free space */
4353:     if (current_space->local_remaining<bnzi) {
4354:       PetscFreeSpaceGet(bnzi+current_space->total_array_size,&current_space);
4355:       nspacedouble++;
4356:     }
4357:     /* copy data into free space, then initialize lnk */
4358:     PetscLLClean(N,N,bnzi,lnk,current_space->array,lnkbt);
4359:     MatPreallocateSet(i+owners[rank],bnzi,current_space->array,dnz,onz);

4361:     current_space->array           += bnzi;
4362:     current_space->local_used      += bnzi;
4363:     current_space->local_remaining -= bnzi;
4364: 
4365:     bi[i+1] = bi[i] + bnzi;
4366:   }
4367: 
4368:   PetscFree3(buf_ri_k,nextrow,nextai);

4370:   PetscMalloc((bi[m]+1)*sizeof(PetscInt),&bj);
4371:   PetscFreeSpaceContiguous(&free_space,bj);
4372:   PetscLLDestroy(lnk,lnkbt);

4374:   /* create symbolic parallel matrix B_mpi */
4375:   /*---------------------------------------*/
4376:   MatCreate(comm,&B_mpi);
4377:   if (n==PETSC_DECIDE) {
4378:     MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,N);
4379:   } else {
4380:     MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,PETSC_DETERMINE);
4381:   }
4382:   MatSetType(B_mpi,MATMPIAIJ);
4383:   MatMPIAIJSetPreallocation(B_mpi,0,dnz,0,onz);
4384:   MatPreallocateFinalize(dnz,onz);

4386:   /* B_mpi is not ready for use - assembly will be done by MatMerge_SeqsToMPINumeric() */
4387:   B_mpi->assembled     = PETSC_FALSE;
4388:   B_mpi->ops->destroy  = MatDestroy_MPIAIJ_SeqsToMPI;
4389:   merge->bi            = bi;
4390:   merge->bj            = bj;
4391:   merge->buf_ri        = buf_ri;
4392:   merge->buf_rj        = buf_rj;
4393:   merge->coi           = PETSC_NULL;
4394:   merge->coj           = PETSC_NULL;
4395:   merge->owners_co     = PETSC_NULL;

4397:   /* attach the supporting struct to B_mpi for reuse */
4398:   PetscContainerCreate(PETSC_COMM_SELF,&container);
4399:   PetscContainerSetPointer(container,merge);
4400:   PetscObjectCompose((PetscObject)B_mpi,"MatMergeSeqsToMPI",(PetscObject)container);
4401:   *mpimat = B_mpi;

4403:   PetscCommDestroy(&comm);
4404:   PetscLogEventEnd(MAT_Seqstompisym,seqmat,0,0,0);
4405:   return(0);
4406: }

4410: PetscErrorCode  MatMerge_SeqsToMPI(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,MatReuse scall,Mat *mpimat)
4411: {
4412:   PetscErrorCode   ierr;

4415:   PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);
4416:   if (scall == MAT_INITIAL_MATRIX){
4417:     MatMerge_SeqsToMPISymbolic(comm,seqmat,m,n,mpimat);
4418:   }
4419:   MatMerge_SeqsToMPINumeric(seqmat,*mpimat);
4420:   PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);
4421:   return(0);
4422: }

4426: /*@
4427:      MatGetLocalMat - Creates a SeqAIJ matrix by taking all its local rows

4429:     Not Collective

4431:    Input Parameters:
4432: +    A - the matrix 
4433: .    scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 

4435:    Output Parameter:
4436: .    A_loc - the local sequential matrix generated

4438:     Level: developer

4440: @*/
4441: PetscErrorCode  MatGetLocalMat(Mat A,MatReuse scall,Mat *A_loc)
4442: {
4443:   PetscErrorCode  ierr;
4444:   Mat_MPIAIJ      *mpimat=(Mat_MPIAIJ*)A->data;
4445:   Mat_SeqAIJ      *mat,*a=(Mat_SeqAIJ*)(mpimat->A)->data,*b=(Mat_SeqAIJ*)(mpimat->B)->data;
4446:   PetscInt        *ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j,*cmap=mpimat->garray;
4447:   MatScalar       *aa=a->a,*ba=b->a,*cam;
4448:   PetscScalar     *ca;
4449:   PetscInt        am=A->rmap->n,i,j,k,cstart=A->cmap->rstart;
4450:   PetscInt        *ci,*cj,col,ncols_d,ncols_o,jo;

4453:   PetscLogEventBegin(MAT_Getlocalmat,A,0,0,0);
4454:   if (scall == MAT_INITIAL_MATRIX){
4455:     PetscMalloc((1+am)*sizeof(PetscInt),&ci);
4456:     ci[0] = 0;
4457:     for (i=0; i<am; i++){
4458:       ci[i+1] = ci[i] + (ai[i+1] - ai[i]) + (bi[i+1] - bi[i]);
4459:     }
4460:     PetscMalloc((1+ci[am])*sizeof(PetscInt),&cj);
4461:     PetscMalloc((1+ci[am])*sizeof(PetscScalar),&ca);
4462:     k = 0;
4463:     for (i=0; i<am; i++) {
4464:       ncols_o = bi[i+1] - bi[i];
4465:       ncols_d = ai[i+1] - ai[i];
4466:       /* off-diagonal portion of A */
4467:       for (jo=0; jo<ncols_o; jo++) {
4468:         col = cmap[*bj];
4469:         if (col >= cstart) break;
4470:         cj[k]   = col; bj++;
4471:         ca[k++] = *ba++;
4472:       }
4473:       /* diagonal portion of A */
4474:       for (j=0; j<ncols_d; j++) {
4475:         cj[k]   = cstart + *aj++;
4476:         ca[k++] = *aa++;
4477:       }
4478:       /* off-diagonal portion of A */
4479:       for (j=jo; j<ncols_o; j++) {
4480:         cj[k]   = cmap[*bj++];
4481:         ca[k++] = *ba++;
4482:       }
4483:     }
4484:     /* put together the new matrix */
4485:     MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ci,cj,ca,A_loc);
4486:     /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */
4487:     /* Since these are PETSc arrays, change flags to free them as necessary. */
4488:     mat          = (Mat_SeqAIJ*)(*A_loc)->data;
4489:     mat->free_a  = PETSC_TRUE;
4490:     mat->free_ij = PETSC_TRUE;
4491:     mat->nonew   = 0;
4492:   } else if (scall == MAT_REUSE_MATRIX){
4493:     mat=(Mat_SeqAIJ*)(*A_loc)->data;
4494:     ci = mat->i; cj = mat->j; cam = mat->a;
4495:     for (i=0; i<am; i++) {
4496:       /* off-diagonal portion of A */
4497:       ncols_o = bi[i+1] - bi[i];
4498:       for (jo=0; jo<ncols_o; jo++) {
4499:         col = cmap[*bj];
4500:         if (col >= cstart) break;
4501:         *cam++ = *ba++; bj++;
4502:       }
4503:       /* diagonal portion of A */
4504:       ncols_d = ai[i+1] - ai[i];
4505:       for (j=0; j<ncols_d; j++) *cam++ = *aa++;
4506:       /* off-diagonal portion of A */
4507:       for (j=jo; j<ncols_o; j++) {
4508:         *cam++ = *ba++; bj++;
4509:       }
4510:     }
4511:   } else {
4512:     SETERRQ1(PETSC_ERR_ARG_WRONG,"Invalid MatReuse %d",(int)scall);
4513:   }

4515:   PetscLogEventEnd(MAT_Getlocalmat,A,0,0,0);
4516:   return(0);
4517: }

4521: /*@C
4522:      MatGetLocalMatCondensed - Creates a SeqAIJ matrix by taking all its local rows and NON-ZERO columns

4524:     Not Collective

4526:    Input Parameters:
4527: +    A - the matrix 
4528: .    scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX
4529: -    row, col - index sets of rows and columns to extract (or PETSC_NULL)  

4531:    Output Parameter:
4532: .    A_loc - the local sequential matrix generated

4534:     Level: developer

4536: @*/
4537: PetscErrorCode  MatGetLocalMatCondensed(Mat A,MatReuse scall,IS *row,IS *col,Mat *A_loc)
4538: {
4539:   Mat_MPIAIJ        *a=(Mat_MPIAIJ*)A->data;
4540:   PetscErrorCode    ierr;
4541:   PetscInt          i,start,end,ncols,nzA,nzB,*cmap,imark,*idx;
4542:   IS                isrowa,iscola;
4543:   Mat               *aloc;

4546:   PetscLogEventBegin(MAT_Getlocalmatcondensed,A,0,0,0);
4547:   if (!row){
4548:     start = A->rmap->rstart; end = A->rmap->rend;
4549:     ISCreateStride(PETSC_COMM_SELF,end-start,start,1,&isrowa);
4550:   } else {
4551:     isrowa = *row;
4552:   }
4553:   if (!col){
4554:     start = A->cmap->rstart;
4555:     cmap  = a->garray;
4556:     nzA   = a->A->cmap->n;
4557:     nzB   = a->B->cmap->n;
4558:     PetscMalloc((nzA+nzB)*sizeof(PetscInt), &idx);
4559:     ncols = 0;
4560:     for (i=0; i<nzB; i++) {
4561:       if (cmap[i] < start) idx[ncols++] = cmap[i];
4562:       else break;
4563:     }
4564:     imark = i;
4565:     for (i=0; i<nzA; i++) idx[ncols++] = start + i;
4566:     for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i];
4567:     ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,&iscola);
4568:     PetscFree(idx);
4569:   } else {
4570:     iscola = *col;
4571:   }
4572:   if (scall != MAT_INITIAL_MATRIX){
4573:     PetscMalloc(sizeof(Mat),&aloc);
4574:     aloc[0] = *A_loc;
4575:   }
4576:   MatGetSubMatrices(A,1,&isrowa,&iscola,scall,&aloc);
4577:   *A_loc = aloc[0];
4578:   PetscFree(aloc);
4579:   if (!row){
4580:     ISDestroy(isrowa);
4581:   }
4582:   if (!col){
4583:     ISDestroy(iscola);
4584:   }
4585:   PetscLogEventEnd(MAT_Getlocalmatcondensed,A,0,0,0);
4586:   return(0);
4587: }

4591: /*@C
4592:     MatGetBrowsOfAcols - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns of local A 

4594:     Collective on Mat

4596:    Input Parameters:
4597: +    A,B - the matrices in mpiaij format
4598: .    scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX
4599: -    rowb, colb - index sets of rows and columns of B to extract (or PETSC_NULL)   

4601:    Output Parameter:
4602: +    rowb, colb - index sets of rows and columns of B to extract 
4603: .    brstart - row index of B_seq from which next B->rmap->n rows are taken from B's local rows
4604: -    B_seq - the sequential matrix generated

4606:     Level: developer

4608: @*/
4609: PetscErrorCode  MatGetBrowsOfAcols(Mat A,Mat B,MatReuse scall,IS *rowb,IS *colb,PetscInt *brstart,Mat *B_seq)
4610: {
4611:   Mat_MPIAIJ        *a=(Mat_MPIAIJ*)A->data;
4612:   PetscErrorCode    ierr;
4613:   PetscInt          *idx,i,start,ncols,nzA,nzB,*cmap,imark;
4614:   IS                isrowb,iscolb;
4615:   Mat               *bseq;
4616: 
4618:   if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend){
4619:     SETERRQ4(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);
4620:   }
4621:   PetscLogEventBegin(MAT_GetBrowsOfAcols,A,B,0,0);
4622: 
4623:   if (scall == MAT_INITIAL_MATRIX){
4624:     start = A->cmap->rstart;
4625:     cmap  = a->garray;
4626:     nzA   = a->A->cmap->n;
4627:     nzB   = a->B->cmap->n;
4628:     PetscMalloc((nzA+nzB)*sizeof(PetscInt), &idx);
4629:     ncols = 0;
4630:     for (i=0; i<nzB; i++) {  /* row < local row index */
4631:       if (cmap[i] < start) idx[ncols++] = cmap[i];
4632:       else break;
4633:     }
4634:     imark = i;
4635:     for (i=0; i<nzA; i++) idx[ncols++] = start + i;  /* local rows */
4636:     for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; /* row > local row index */
4637:     ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,&isrowb);
4638:     PetscFree(idx);
4639:     *brstart = imark;
4640:     ISCreateStride(PETSC_COMM_SELF,B->cmap->N,0,1,&iscolb);
4641:   } else {
4642:     if (!rowb || !colb) SETERRQ(PETSC_ERR_SUP,"IS rowb and colb must be provided for MAT_REUSE_MATRIX");
4643:     isrowb = *rowb; iscolb = *colb;
4644:     PetscMalloc(sizeof(Mat),&bseq);
4645:     bseq[0] = *B_seq;
4646:   }
4647:   MatGetSubMatrices(B,1,&isrowb,&iscolb,scall,&bseq);
4648:   *B_seq = bseq[0];
4649:   PetscFree(bseq);
4650:   if (!rowb){
4651:     ISDestroy(isrowb);
4652:   } else {
4653:     *rowb = isrowb;
4654:   }
4655:   if (!colb){
4656:     ISDestroy(iscolb);
4657:   } else {
4658:     *colb = iscolb;
4659:   }
4660:   PetscLogEventEnd(MAT_GetBrowsOfAcols,A,B,0,0);
4661:   return(0);
4662: }

4666: /*@C
4667:     MatGetBrowsOfAoCols - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns
4668:     of the OFF-DIAGONAL portion of local A 

4670:     Collective on Mat

4672:    Input Parameters:
4673: +    A,B - the matrices in mpiaij format
4674: .    scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX
4675: .    startsj - starting point in B's sending and receiving j-arrays, saved for MAT_REUSE (or PETSC_NULL) 
4676: .    startsj_r - similar to startsj for receives
4677: -    bufa_ptr - array for sending matrix values, saved for MAT_REUSE (or PETSC_NULL) 

4679:    Output Parameter:
4680: +    B_oth - the sequential matrix generated

4682:     Level: developer

4684: @*/
4685: PetscErrorCode  MatGetBrowsOfAoCols(Mat A,Mat B,MatReuse scall,PetscInt **startsj,PetscInt **startsj_r,MatScalar **bufa_ptr,Mat *B_oth)
4686: {
4687:   VecScatter_MPI_General *gen_to,*gen_from;
4688:   PetscErrorCode         ierr;
4689:   Mat_MPIAIJ             *a=(Mat_MPIAIJ*)A->data;
4690:   Mat_SeqAIJ             *b_oth;
4691:   VecScatter             ctx=a->Mvctx;
4692:   MPI_Comm               comm=((PetscObject)ctx)->comm;
4693:   PetscMPIInt            *rprocs,*sprocs,tag=((PetscObject)ctx)->tag,rank;
4694:   PetscInt               *rowlen,*bufj,*bufJ,ncols,aBn=a->B->cmap->n,row,*b_othi,*b_othj;
4695:   PetscScalar            *rvalues,*svalues;
4696:   MatScalar              *b_otha,*bufa,*bufA;
4697:   PetscInt               i,j,k,l,ll,nrecvs,nsends,nrows,*srow,*rstarts,*rstartsj = 0,*sstarts,*sstartsj,len;
4698:   MPI_Request            *rwaits = PETSC_NULL,*swaits = PETSC_NULL;
4699:   MPI_Status             *sstatus,rstatus;
4700:   PetscMPIInt            jj;
4701:   PetscInt               *cols,sbs,rbs;
4702:   PetscScalar            *vals;

4705:   if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend){
4706:     SETERRQ4(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);
4707:   }
4708:   PetscLogEventBegin(MAT_GetBrowsOfAocols,A,B,0,0);
4709:   MPI_Comm_rank(comm,&rank);

4711:   gen_to   = (VecScatter_MPI_General*)ctx->todata;
4712:   gen_from = (VecScatter_MPI_General*)ctx->fromdata;
4713:   rvalues  = gen_from->values; /* holds the length of receiving row */
4714:   svalues  = gen_to->values;   /* holds the length of sending row */
4715:   nrecvs   = gen_from->n;
4716:   nsends   = gen_to->n;

4718:   PetscMalloc2(nrecvs,MPI_Request,&rwaits,nsends,MPI_Request,&swaits);
4719:   srow     = gen_to->indices;   /* local row index to be sent */
4720:   sstarts  = gen_to->starts;
4721:   sprocs   = gen_to->procs;
4722:   sstatus  = gen_to->sstatus;
4723:   sbs      = gen_to->bs;
4724:   rstarts  = gen_from->starts;
4725:   rprocs   = gen_from->procs;
4726:   rbs      = gen_from->bs;

4728:   if (!startsj || !bufa_ptr) scall = MAT_INITIAL_MATRIX;
4729:   if (scall == MAT_INITIAL_MATRIX){
4730:     /* i-array */
4731:     /*---------*/
4732:     /*  post receives */
4733:     for (i=0; i<nrecvs; i++){
4734:       rowlen = (PetscInt*)rvalues + rstarts[i]*rbs;
4735:       nrows = (rstarts[i+1]-rstarts[i])*rbs; /* num of indices to be received */
4736:       MPI_Irecv(rowlen,nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);
4737:     }

4739:     /* pack the outgoing message */
4740:     PetscMalloc2(nsends+1,PetscInt,&sstartsj,nrecvs+1,PetscInt,&rstartsj);
4741:     sstartsj[0] = 0;  rstartsj[0] = 0;
4742:     len = 0; /* total length of j or a array to be sent */
4743:     k = 0;
4744:     for (i=0; i<nsends; i++){
4745:       rowlen = (PetscInt*)svalues + sstarts[i]*sbs;
4746:       nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */
4747:       for (j=0; j<nrows; j++) {
4748:         row = srow[k] + B->rmap->range[rank]; /* global row idx */
4749:         for (l=0; l<sbs; l++){
4750:           MatGetRow_MPIAIJ(B,row+l,&ncols,PETSC_NULL,PETSC_NULL); /* rowlength */
4751:           rowlen[j*sbs+l] = ncols;
4752:           len += ncols;
4753:           MatRestoreRow_MPIAIJ(B,row+l,&ncols,PETSC_NULL,PETSC_NULL);
4754:         }
4755:         k++;
4756:       }
4757:       MPI_Isend(rowlen,nrows*sbs,MPIU_INT,sprocs[i],tag,comm,swaits+i);
4758:       sstartsj[i+1] = len;  /* starting point of (i+1)-th outgoing msg in bufj and bufa */
4759:     }
4760:     /* recvs and sends of i-array are completed */
4761:     i = nrecvs;
4762:     while (i--) {
4763:       MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);
4764:     }
4765:     if (nsends) {MPI_Waitall(nsends,swaits,sstatus);}

4767:     /* allocate buffers for sending j and a arrays */
4768:     PetscMalloc((len+1)*sizeof(PetscInt),&bufj);
4769:     PetscMalloc((len+1)*sizeof(PetscScalar),&bufa);

4771:     /* create i-array of B_oth */
4772:     PetscMalloc((aBn+2)*sizeof(PetscInt),&b_othi);
4773:     b_othi[0] = 0;
4774:     len = 0; /* total length of j or a array to be received */
4775:     k = 0;
4776:     for (i=0; i<nrecvs; i++){
4777:       rowlen = (PetscInt*)rvalues + rstarts[i]*rbs;
4778:       nrows = rbs*(rstarts[i+1]-rstarts[i]); /* num of rows to be recieved */
4779:       for (j=0; j<nrows; j++) {
4780:         b_othi[k+1] = b_othi[k] + rowlen[j];
4781:         len += rowlen[j]; k++;
4782:       }
4783:       rstartsj[i+1] = len; /* starting point of (i+1)-th incoming msg in bufj and bufa */
4784:     }

4786:     /* allocate space for j and a arrrays of B_oth */
4787:     PetscMalloc((b_othi[aBn]+1)*sizeof(PetscInt),&b_othj);
4788:     PetscMalloc((b_othi[aBn]+1)*sizeof(MatScalar),&b_otha);

4790:     /* j-array */
4791:     /*---------*/
4792:     /*  post receives of j-array */
4793:     for (i=0; i<nrecvs; i++){
4794:       nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */
4795:       MPI_Irecv(b_othj+rstartsj[i],nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);
4796:     }

4798:     /* pack the outgoing message j-array */
4799:     k = 0;
4800:     for (i=0; i<nsends; i++){
4801:       nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */
4802:       bufJ = bufj+sstartsj[i];
4803:       for (j=0; j<nrows; j++) {
4804:         row  = srow[k++] + B->rmap->range[rank]; /* global row idx */
4805:         for (ll=0; ll<sbs; ll++){
4806:           MatGetRow_MPIAIJ(B,row+ll,&ncols,&cols,PETSC_NULL);
4807:           for (l=0; l<ncols; l++){
4808:             *bufJ++ = cols[l];
4809:           }
4810:           MatRestoreRow_MPIAIJ(B,row+ll,&ncols,&cols,PETSC_NULL);
4811:         }
4812:       }
4813:       MPI_Isend(bufj+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_INT,sprocs[i],tag,comm,swaits+i);
4814:     }

4816:     /* recvs and sends of j-array are completed */
4817:     i = nrecvs;
4818:     while (i--) {
4819:       MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);
4820:     }
4821:     if (nsends) {MPI_Waitall(nsends,swaits,sstatus);}
4822:   } else if (scall == MAT_REUSE_MATRIX){
4823:     sstartsj = *startsj;
4824:     rstartsj = *startsj_r;
4825:     bufa     = *bufa_ptr;
4826:     b_oth    = (Mat_SeqAIJ*)(*B_oth)->data;
4827:     b_otha   = b_oth->a;
4828:   } else {
4829:     SETERRQ(PETSC_ERR_ARG_WRONGSTATE, "Matrix P does not posses an object container");
4830:   }

4832:   /* a-array */
4833:   /*---------*/
4834:   /*  post receives of a-array */
4835:   for (i=0; i<nrecvs; i++){
4836:     nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */
4837:     MPI_Irecv(b_otha+rstartsj[i],nrows,MPIU_SCALAR,rprocs[i],tag,comm,rwaits+i);
4838:   }

4840:   /* pack the outgoing message a-array */
4841:   k = 0;
4842:   for (i=0; i<nsends; i++){
4843:     nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */
4844:     bufA = bufa+sstartsj[i];
4845:     for (j=0; j<nrows; j++) {
4846:       row  = srow[k++] + B->rmap->range[rank]; /* global row idx */
4847:       for (ll=0; ll<sbs; ll++){
4848:         MatGetRow_MPIAIJ(B,row+ll,&ncols,PETSC_NULL,&vals);
4849:         for (l=0; l<ncols; l++){
4850:           *bufA++ = vals[l];
4851:         }
4852:         MatRestoreRow_MPIAIJ(B,row+ll,&ncols,PETSC_NULL,&vals);
4853:       }
4854:     }
4855:     MPI_Isend(bufa+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_SCALAR,sprocs[i],tag,comm,swaits+i);
4856:   }
4857:   /* recvs and sends of a-array are completed */
4858:   i = nrecvs;
4859:   while (i--) {
4860:     MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);
4861:   }
4862:   if (nsends) {MPI_Waitall(nsends,swaits,sstatus);}
4863:   PetscFree2(rwaits,swaits);

4865:   if (scall == MAT_INITIAL_MATRIX){
4866:     /* put together the new matrix */
4867:     MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,aBn,B->cmap->N,b_othi,b_othj,b_otha,B_oth);

4869:     /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */
4870:     /* Since these are PETSc arrays, change flags to free them as necessary. */
4871:     b_oth          = (Mat_SeqAIJ *)(*B_oth)->data;
4872:     b_oth->free_a  = PETSC_TRUE;
4873:     b_oth->free_ij = PETSC_TRUE;
4874:     b_oth->nonew   = 0;

4876:     PetscFree(bufj);
4877:     if (!startsj || !bufa_ptr){
4878:       PetscFree2(sstartsj,rstartsj);
4879:       PetscFree(bufa_ptr);
4880:     } else {
4881:       *startsj   = sstartsj;
4882:       *startsj_r = rstartsj;
4883:       *bufa_ptr  = bufa;
4884:     }
4885:   }
4886:   PetscLogEventEnd(MAT_GetBrowsOfAocols,A,B,0,0);
4887:   return(0);
4888: }

4892: /*@C
4893:   MatGetCommunicationStructs - Provides access to the communication structures used in matrix-vector multiplication.

4895:   Not Collective

4897:   Input Parameters:
4898: . A - The matrix in mpiaij format

4900:   Output Parameter:
4901: + lvec - The local vector holding off-process values from the argument to a matrix-vector product
4902: . colmap - A map from global column index to local index into lvec
4903: - multScatter - A scatter from the argument of a matrix-vector product to lvec

4905:   Level: developer

4907: @*/
4908: #if defined (PETSC_USE_CTABLE)
4909: PetscErrorCode  MatGetCommunicationStructs(Mat A, Vec *lvec, PetscTable *colmap, VecScatter *multScatter)
4910: #else
4911: PetscErrorCode  MatGetCommunicationStructs(Mat A, Vec *lvec, PetscInt *colmap[], VecScatter *multScatter)
4912: #endif
4913: {
4914:   Mat_MPIAIJ *a;

4921:   a = (Mat_MPIAIJ *) A->data;
4922:   if (lvec) *lvec = a->lvec;
4923:   if (colmap) *colmap = a->colmap;
4924:   if (multScatter) *multScatter = a->Mvctx;
4925:   return(0);
4926: }


4936: /*
4937:     Computes (B'*A')' since computing B*A directly is untenable

4939:                n                       p                          p
4940:         (              )       (              )         (                  )
4941:       m (      A       )  *  n (       B      )   =   m (         C        )
4942:         (              )       (              )         (                  )

4944: */
4945: PetscErrorCode MatMatMultNumeric_MPIDense_MPIAIJ(Mat A,Mat B,Mat C)
4946: {
4947:   PetscErrorCode     ierr;
4948:   Mat                At,Bt,Ct;

4951:   MatTranspose(A,MAT_INITIAL_MATRIX,&At);
4952:   MatTranspose(B,MAT_INITIAL_MATRIX,&Bt);
4953:   MatMatMult(Bt,At,MAT_INITIAL_MATRIX,1.0,&Ct);
4954:   MatDestroy(At);
4955:   MatDestroy(Bt);
4956:   MatTranspose(Ct,MAT_REUSE_MATRIX,&C);
4957:   MatDestroy(Ct);
4958:   return(0);
4959: }

4963: PetscErrorCode MatMatMultSymbolic_MPIDense_MPIAIJ(Mat A,Mat B,PetscReal fill,Mat *C)
4964: {
4966:   PetscInt       m=A->rmap->n,n=B->cmap->n;
4967:   Mat            Cmat;

4970:   if (A->cmap->n != B->rmap->n) SETERRQ2(PETSC_ERR_ARG_SIZ,"A->cmap->n %d != B->rmap->n %d\n",A->cmap->n,B->rmap->n);
4971:   MatCreate(((PetscObject)A)->comm,&Cmat);
4972:   MatSetSizes(Cmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);
4973:   MatSetType(Cmat,MATMPIDENSE);
4974:   MatMPIDenseSetPreallocation(Cmat,PETSC_NULL);
4975:   MatAssemblyBegin(Cmat,MAT_FINAL_ASSEMBLY);
4976:   MatAssemblyEnd(Cmat,MAT_FINAL_ASSEMBLY);
4977:   *C   = Cmat;
4978:   return(0);
4979: }

4981: /* ----------------------------------------------------------------*/
4984: PetscErrorCode MatMatMult_MPIDense_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C)
4985: {

4989:   if (scall == MAT_INITIAL_MATRIX){
4990:     MatMatMultSymbolic_MPIDense_MPIAIJ(A,B,fill,C);
4991:   }
4992:   MatMatMultNumeric_MPIDense_MPIAIJ(A,B,*C);
4993:   return(0);
4994: }

4997: #if defined(PETSC_HAVE_MUMPS)
4999: #endif
5000: #if defined(PETSC_HAVE_PASTIX)
5002: #endif
5003: #if defined(PETSC_HAVE_SUPERLU_DIST)
5005: #endif
5006: #if defined(PETSC_HAVE_SPOOLES)
5008: #endif

5011: /*MC
5012:    MATMPIAIJ - MATMPIAIJ = "mpiaij" - A matrix type to be used for parallel sparse matrices.

5014:    Options Database Keys:
5015: . -mat_type mpiaij - sets the matrix type to "mpiaij" during a call to MatSetFromOptions()

5017:   Level: beginner

5019: .seealso: MatCreateMPIAIJ()
5020: M*/

5025: PetscErrorCode  MatCreate_MPIAIJ(Mat B)
5026: {
5027:   Mat_MPIAIJ     *b;
5029:   PetscMPIInt    size;

5032:   MPI_Comm_size(((PetscObject)B)->comm,&size);

5034:   PetscNewLog(B,Mat_MPIAIJ,&b);
5035:   B->data         = (void*)b;
5036:   PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));
5037:   B->rmap->bs     = 1;
5038:   B->assembled    = PETSC_FALSE;
5039:   B->mapping      = 0;

5041:   B->insertmode   = NOT_SET_VALUES;
5042:   b->size         = size;
5043:   MPI_Comm_rank(((PetscObject)B)->comm,&b->rank);

5045:   /* build cache for off array entries formed */
5046:   MatStashCreate_Private(((PetscObject)B)->comm,1,&B->stash);
5047:   b->donotstash  = PETSC_FALSE;
5048:   b->colmap      = 0;
5049:   b->garray      = 0;
5050:   b->roworiented = PETSC_TRUE;

5052:   /* stuff used for matrix vector multiply */
5053:   b->lvec      = PETSC_NULL;
5054:   b->Mvctx     = PETSC_NULL;

5056:   /* stuff for MatGetRow() */
5057:   b->rowindices   = 0;
5058:   b->rowvalues    = 0;
5059:   b->getrowactive = PETSC_FALSE;

5061: #if defined(PETSC_HAVE_SPOOLES)
5062:   PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_spooles_C",
5063:                                      "MatGetFactor_mpiaij_spooles",
5064:                                      MatGetFactor_mpiaij_spooles);
5065: #endif
5066: #if defined(PETSC_HAVE_MUMPS)
5067:   PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_mumps_C",
5068:                                      "MatGetFactor_mpiaij_mumps",
5069:                                      MatGetFactor_mpiaij_mumps);
5070: #endif
5071: #if defined(PETSC_HAVE_PASTIX)
5072:   PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_pastix_C",
5073:                                            "MatGetFactor_mpiaij_pastix",
5074:                                            MatGetFactor_mpiaij_pastix);
5075: #endif
5076: #if defined(PETSC_HAVE_SUPERLU_DIST)
5077:   PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_superlu_dist_C",
5078:                                      "MatGetFactor_mpiaij_superlu_dist",
5079:                                      MatGetFactor_mpiaij_superlu_dist);
5080: #endif
5081:   PetscObjectComposeFunctionDynamic((PetscObject)B,"MatStoreValues_C",
5082:                                      "MatStoreValues_MPIAIJ",
5083:                                      MatStoreValues_MPIAIJ);
5084:   PetscObjectComposeFunctionDynamic((PetscObject)B,"MatRetrieveValues_C",
5085:                                      "MatRetrieveValues_MPIAIJ",
5086:                                      MatRetrieveValues_MPIAIJ);
5087:   PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetDiagonalBlock_C",
5088:                                      "MatGetDiagonalBlock_MPIAIJ",
5089:                                      MatGetDiagonalBlock_MPIAIJ);
5090:   PetscObjectComposeFunctionDynamic((PetscObject)B,"MatIsTranspose_C",
5091:                                      "MatIsTranspose_MPIAIJ",
5092:                                      MatIsTranspose_MPIAIJ);
5093:   PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMPIAIJSetPreallocation_C",
5094:                                      "MatMPIAIJSetPreallocation_MPIAIJ",
5095:                                      MatMPIAIJSetPreallocation_MPIAIJ);
5096:   PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMPIAIJSetPreallocationCSR_C",
5097:                                      "MatMPIAIJSetPreallocationCSR_MPIAIJ",
5098:                                      MatMPIAIJSetPreallocationCSR_MPIAIJ);
5099:   PetscObjectComposeFunctionDynamic((PetscObject)B,"MatDiagonalScaleLocal_C",
5100:                                      "MatDiagonalScaleLocal_MPIAIJ",
5101:                                      MatDiagonalScaleLocal_MPIAIJ);
5102:   PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_mpiaij_mpicsrperm_C",
5103:                                      "MatConvert_MPIAIJ_MPICSRPERM",
5104:                                       MatConvert_MPIAIJ_MPICSRPERM);
5105:   PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_mpiaij_mpicrl_C",
5106:                                      "MatConvert_MPIAIJ_MPICRL",
5107:                                       MatConvert_MPIAIJ_MPICRL);
5108:   PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_mpiaij_mpisbaij_C",
5109:                                      "MatConvert_MPIAIJ_MPISBAIJ",
5110:                                       MatConvert_MPIAIJ_MPISBAIJ);
5111:   PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMatMult_mpidense_mpiaij_C",
5112:                                      "MatMatMult_MPIDense_MPIAIJ",
5113:                                       MatMatMult_MPIDense_MPIAIJ);
5114:   PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMatMultSymbolic_mpidense_mpiaij_C",
5115:                                      "MatMatMultSymbolic_MPIDense_MPIAIJ",
5116:                                       MatMatMultSymbolic_MPIDense_MPIAIJ);
5117:   PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMatMultNumeric_mpidense_mpiaij_C",
5118:                                      "MatMatMultNumeric_MPIDense_MPIAIJ",
5119:                                       MatMatMultNumeric_MPIDense_MPIAIJ);
5120:   PetscObjectChangeTypeName((PetscObject)B,MATMPIAIJ);
5121:   return(0);
5122: }

5127: /*@
5128:      MatCreateMPIAIJWithSplitArrays - creates a MPI AIJ matrix using arrays that contain the "diagonal"
5129:          and "off-diagonal" part of the matrix in CSR format.

5131:    Collective on MPI_Comm

5133:    Input Parameters:
5134: +  comm - MPI communicator
5135: .  m - number of local rows (Cannot be PETSC_DECIDE)
5136: .  n - This value should be the same as the local size used in creating the 
5137:        x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have
5138:        calculated if N is given) For square matrices n is almost always m.
5139: .  M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
5140: .  N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
5141: .   i - row indices for "diagonal" portion of matrix
5142: .   j - column indices
5143: .   a - matrix values
5144: .   oi - row indices for "off-diagonal" portion of matrix
5145: .   oj - column indices
5146: -   oa - matrix values

5148:    Output Parameter:
5149: .   mat - the matrix

5151:    Level: advanced

5153:    Notes:
5154:        The i, j, and a arrays ARE NOT copied by this routine into the internal format used by PETSc.

5156:        The i and j indices are 0 based
5157:  
5158:        See MatCreateMPIAIJ() for the definition of "diagonal" and "off-diagonal" portion of the matrix

5160:        This sets local rows and cannot be used to set off-processor values. 

5162:        You cannot later use MatSetValues() to change values in this matrix.

5164: .keywords: matrix, aij, compressed row, sparse, parallel

5166: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(),
5167:           MPIAIJ, MatCreateMPIAIJ(), MatCreateMPIAIJWithArrays()
5168: @*/
5169: PetscErrorCode  MatCreateMPIAIJWithSplitArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,PetscInt i[],PetscInt j[],PetscScalar a[],
5170:                                                                 PetscInt oi[], PetscInt oj[],PetscScalar oa[],Mat *mat)
5171: {
5173:   Mat_MPIAIJ     *maij;

5176:   if (m < 0) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative");
5177:   if (i[0]) {
5178:     SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0");
5179:   }
5180:   if (oi[0]) {
5181:     SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"oi (row indices) must start with 0");
5182:   }
5183:   MatCreate(comm,mat);
5184:   MatSetSizes(*mat,m,n,M,N);
5185:   MatSetType(*mat,MATMPIAIJ);
5186:   maij = (Mat_MPIAIJ*) (*mat)->data;
5187:   maij->donotstash     = PETSC_TRUE;
5188:   (*mat)->preallocated = PETSC_TRUE;

5190:   PetscLayoutSetBlockSize((*mat)->rmap,1);
5191:   PetscLayoutSetBlockSize((*mat)->cmap,1);
5192:   PetscLayoutSetUp((*mat)->rmap);
5193:   PetscLayoutSetUp((*mat)->cmap);

5195:   MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,n,i,j,a,&maij->A);
5196:   MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,(*mat)->cmap->N,oi,oj,oa,&maij->B);

5198:   MatAssemblyBegin(maij->A,MAT_FINAL_ASSEMBLY);
5199:   MatAssemblyEnd(maij->A,MAT_FINAL_ASSEMBLY);
5200:   MatAssemblyBegin(maij->B,MAT_FINAL_ASSEMBLY);
5201:   MatAssemblyEnd(maij->B,MAT_FINAL_ASSEMBLY);

5203:   MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);
5204:   MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);
5205:   return(0);
5206: }

5208: /*
5209:     Special version for direct calls from Fortran 
5210: */
5211: #if defined(PETSC_HAVE_FORTRAN_CAPS)
5212: #define matsetvaluesmpiaij_ MATSETVALUESMPIAIJ
5213: #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE)
5214: #define matsetvaluesmpiaij_ matsetvaluesmpiaij
5215: #endif

5217: /* Change these macros so can be used in void function */
5218: #undef CHKERRQ
5219: #define CHKERRQ(ierr) CHKERRABORT(((PetscObject)mat)->comm,ierr) 
5220: #undef SETERRQ2
5221: #define SETERRQ2(ierr,b,c,d) CHKERRABORT(((PetscObject)mat)->comm,ierr) 
5222: #undef SETERRQ
5223: #define SETERRQ(ierr,b) CHKERRABORT(((PetscObject)mat)->comm,ierr) 

5228: void PETSC_STDCALL matsetvaluesmpiaij_(Mat *mmat,PetscInt *mm,const PetscInt im[],PetscInt *mn,const PetscInt in[],const PetscScalar v[],InsertMode *maddv,PetscErrorCode *_ierr)
5229: {
5230:   Mat             mat = *mmat;
5231:   PetscInt        m = *mm, n = *mn;
5232:   InsertMode      addv = *maddv;
5233:   Mat_MPIAIJ      *aij = (Mat_MPIAIJ*)mat->data;
5234:   PetscScalar     value;
5235:   PetscErrorCode  ierr;

5237:   MatPreallocated(mat);
5238:   if (mat->insertmode == NOT_SET_VALUES) {
5239:     mat->insertmode = addv;
5240:   }
5241: #if defined(PETSC_USE_DEBUG)
5242:   else if (mat->insertmode != addv) {
5243:     SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values");
5244:   }
5245: #endif
5246:   {
5247:   PetscInt        i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend;
5248:   PetscInt        cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col;
5249:   PetscTruth      roworiented = aij->roworiented;

5251:   /* Some Variables required in the macro */
5252:   Mat             A = aij->A;
5253:   Mat_SeqAIJ      *a = (Mat_SeqAIJ*)A->data;
5254:   PetscInt        *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j;
5255:   MatScalar       *aa = a->a;
5256:   PetscTruth      ignorezeroentries = (((a->ignorezeroentries)&&(addv==ADD_VALUES))?PETSC_TRUE:PETSC_FALSE);
5257:   Mat             B = aij->B;
5258:   Mat_SeqAIJ      *b = (Mat_SeqAIJ*)B->data;
5259:   PetscInt        *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n;
5260:   MatScalar       *ba = b->a;

5262:   PetscInt        *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2;
5263:   PetscInt        nonew = a->nonew;
5264:   MatScalar       *ap1,*ap2;

5267:   for (i=0; i<m; i++) {
5268:     if (im[i] < 0) continue;
5269: #if defined(PETSC_USE_DEBUG)
5270:     if (im[i] >= mat->rmap->N) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],mat->rmap->N-1);
5271: #endif
5272:     if (im[i] >= rstart && im[i] < rend) {
5273:       row      = im[i] - rstart;
5274:       lastcol1 = -1;
5275:       rp1      = aj + ai[row];
5276:       ap1      = aa + ai[row];
5277:       rmax1    = aimax[row];
5278:       nrow1    = ailen[row];
5279:       low1     = 0;
5280:       high1    = nrow1;
5281:       lastcol2 = -1;
5282:       rp2      = bj + bi[row];
5283:       ap2      = ba + bi[row];
5284:       rmax2    = bimax[row];
5285:       nrow2    = bilen[row];
5286:       low2     = 0;
5287:       high2    = nrow2;

5289:       for (j=0; j<n; j++) {
5290:         if (roworiented) value = v[i*n+j]; else value = v[i+j*m];
5291:         if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES)) continue;
5292:         if (in[j] >= cstart && in[j] < cend){
5293:           col = in[j] - cstart;
5294:           MatSetValues_SeqAIJ_A_Private(row,col,value,addv);
5295:         } else if (in[j] < 0) continue;
5296: #if defined(PETSC_USE_DEBUG)
5297:         else if (in[j] >= mat->cmap->N) {SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",in[j],mat->cmap->N-1);}
5298: #endif
5299:         else {
5300:           if (mat->was_assembled) {
5301:             if (!aij->colmap) {
5302:               CreateColmap_MPIAIJ_Private(mat);
5303:             }
5304: #if defined (PETSC_USE_CTABLE)
5305:             PetscTableFind(aij->colmap,in[j]+1,&col);
5306:             col--;
5307: #else
5308:             col = aij->colmap[in[j]] - 1;
5309: #endif
5310:             if (col < 0 && !((Mat_SeqAIJ*)(aij->A->data))->nonew) {
5311:               DisAssemble_MPIAIJ(mat);
5312:               col =  in[j];
5313:               /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */
5314:               B = aij->B;
5315:               b = (Mat_SeqAIJ*)B->data;
5316:               bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j;
5317:               rp2      = bj + bi[row];
5318:               ap2      = ba + bi[row];
5319:               rmax2    = bimax[row];
5320:               nrow2    = bilen[row];
5321:               low2     = 0;
5322:               high2    = nrow2;
5323:               bm       = aij->B->rmap->n;
5324:               ba = b->a;
5325:             }
5326:           } else col = in[j];
5327:           MatSetValues_SeqAIJ_B_Private(row,col,value,addv);
5328:         }
5329:       }
5330:     } else {
5331:       if (!aij->donotstash) {
5332:         if (roworiented) {
5333:           MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscTruth)(ignorezeroentries && (addv == ADD_VALUES)));
5334:         } else {
5335:           MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscTruth)(ignorezeroentries && (addv == ADD_VALUES)));
5336:         }
5337:       }
5338:     }
5339:   }}
5340:   PetscFunctionReturnVoid();
5341: }