Actual source code: mpibaij.c

petsc-master 2017-11-20
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  2:  #include <../src/mat/impls/baij/mpi/mpibaij.h>

  4:  #include <petscblaslapack.h>
  5:  #include <petscsf.h>

  7: #if defined(PETSC_HAVE_HYPRE)
  8: PETSC_INTERN PetscErrorCode MatConvert_AIJ_HYPRE(Mat,MatType,MatReuse,Mat*);
  9: #endif

 11: PetscErrorCode MatGetRowMaxAbs_MPIBAIJ(Mat A,Vec v,PetscInt idx[])
 12: {
 13:   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;
 15:   PetscInt       i,*idxb = 0;
 16:   PetscScalar    *va,*vb;
 17:   Vec            vtmp;

 20:   MatGetRowMaxAbs(a->A,v,idx);
 21:   VecGetArray(v,&va);
 22:   if (idx) {
 23:     for (i=0; i<A->rmap->n; i++) {
 24:       if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart;
 25:     }
 26:   }

 28:   VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);
 29:   if (idx) {PetscMalloc1(A->rmap->n,&idxb);}
 30:   MatGetRowMaxAbs(a->B,vtmp,idxb);
 31:   VecGetArray(vtmp,&vb);

 33:   for (i=0; i<A->rmap->n; i++) {
 34:     if (PetscAbsScalar(va[i]) < PetscAbsScalar(vb[i])) {
 35:       va[i] = vb[i];
 36:       if (idx) idx[i] = A->cmap->bs*a->garray[idxb[i]/A->cmap->bs] + (idxb[i] % A->cmap->bs);
 37:     }
 38:   }

 40:   VecRestoreArray(v,&va);
 41:   VecRestoreArray(vtmp,&vb);
 42:   PetscFree(idxb);
 43:   VecDestroy(&vtmp);
 44:   return(0);
 45: }

 47: PetscErrorCode  MatStoreValues_MPIBAIJ(Mat mat)
 48: {
 49:   Mat_MPIBAIJ    *aij = (Mat_MPIBAIJ*)mat->data;

 53:   MatStoreValues(aij->A);
 54:   MatStoreValues(aij->B);
 55:   return(0);
 56: }

 58: PetscErrorCode  MatRetrieveValues_MPIBAIJ(Mat mat)
 59: {
 60:   Mat_MPIBAIJ    *aij = (Mat_MPIBAIJ*)mat->data;

 64:   MatRetrieveValues(aij->A);
 65:   MatRetrieveValues(aij->B);
 66:   return(0);
 67: }

 69: /*
 70:      Local utility routine that creates a mapping from the global column
 71:    number to the local number in the off-diagonal part of the local
 72:    storage of the matrix.  This is done in a non scalable way since the
 73:    length of colmap equals the global matrix length.
 74: */
 75: PetscErrorCode MatCreateColmap_MPIBAIJ_Private(Mat mat)
 76: {
 77:   Mat_MPIBAIJ    *baij = (Mat_MPIBAIJ*)mat->data;
 78:   Mat_SeqBAIJ    *B    = (Mat_SeqBAIJ*)baij->B->data;
 80:   PetscInt       nbs = B->nbs,i,bs=mat->rmap->bs;

 83: #if defined(PETSC_USE_CTABLE)
 84:   PetscTableCreate(baij->nbs,baij->Nbs+1,&baij->colmap);
 85:   for (i=0; i<nbs; i++) {
 86:     PetscTableAdd(baij->colmap,baij->garray[i]+1,i*bs+1,INSERT_VALUES);
 87:   }
 88: #else
 89:   PetscMalloc1(baij->Nbs+1,&baij->colmap);
 90:   PetscLogObjectMemory((PetscObject)mat,baij->Nbs*sizeof(PetscInt));
 91:   PetscMemzero(baij->colmap,baij->Nbs*sizeof(PetscInt));
 92:   for (i=0; i<nbs; i++) baij->colmap[baij->garray[i]] = i*bs+1;
 93: #endif
 94:   return(0);
 95: }

 97: #define  MatSetValues_SeqBAIJ_A_Private(row,col,value,addv,orow,ocol)       \
 98:   { \
 99:  \
100:     brow = row/bs;  \
101:     rp   = aj + ai[brow]; ap = aa + bs2*ai[brow]; \
102:     rmax = aimax[brow]; nrow = ailen[brow]; \
103:     bcol = col/bs; \
104:     ridx = row % bs; cidx = col % bs; \
105:     low  = 0; high = nrow; \
106:     while (high-low > 3) { \
107:       t = (low+high)/2; \
108:       if (rp[t] > bcol) high = t; \
109:       else              low  = t; \
110:     } \
111:     for (_i=low; _i<high; _i++) { \
112:       if (rp[_i] > bcol) break; \
113:       if (rp[_i] == bcol) { \
114:         bap = ap +  bs2*_i + bs*cidx + ridx; \
115:         if (addv == ADD_VALUES) *bap += value;  \
116:         else                    *bap  = value;  \
117:         goto a_noinsert; \
118:       } \
119:     } \
120:     if (a->nonew == 1) goto a_noinsert; \
121:     if (a->nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero at global row/column (%D, %D) into matrix", orow, ocol); \
122:     MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,brow,bcol,rmax,aa,ai,aj,rp,ap,aimax,a->nonew,MatScalar); \
123:     N = nrow++ - 1;  \
124:     /* shift up all the later entries in this row */ \
125:     for (ii=N; ii>=_i; ii--) { \
126:       rp[ii+1] = rp[ii]; \
127:       PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar)); \
128:     } \
129:     if (N>=_i) { PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar)); }  \
130:     rp[_i]                      = bcol;  \
131:     ap[bs2*_i + bs*cidx + ridx] = value;  \
132: a_noinsert:; \
133:     ailen[brow] = nrow; \
134:   }

136: #define  MatSetValues_SeqBAIJ_B_Private(row,col,value,addv,orow,ocol)       \
137:   { \
138:     brow = row/bs;  \
139:     rp   = bj + bi[brow]; ap = ba + bs2*bi[brow]; \
140:     rmax = bimax[brow]; nrow = bilen[brow]; \
141:     bcol = col/bs; \
142:     ridx = row % bs; cidx = col % bs; \
143:     low  = 0; high = nrow; \
144:     while (high-low > 3) { \
145:       t = (low+high)/2; \
146:       if (rp[t] > bcol) high = t; \
147:       else              low  = t; \
148:     } \
149:     for (_i=low; _i<high; _i++) { \
150:       if (rp[_i] > bcol) break; \
151:       if (rp[_i] == bcol) { \
152:         bap = ap +  bs2*_i + bs*cidx + ridx; \
153:         if (addv == ADD_VALUES) *bap += value;  \
154:         else                    *bap  = value;  \
155:         goto b_noinsert; \
156:       } \
157:     } \
158:     if (b->nonew == 1) goto b_noinsert; \
159:     if (b->nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero at global row/column  (%D, %D) into matrix", orow, ocol); \
160:     MatSeqXAIJReallocateAIJ(B,b->mbs,bs2,nrow,brow,bcol,rmax,ba,bi,bj,rp,ap,bimax,b->nonew,MatScalar); \
161:     N = nrow++ - 1;  \
162:     /* shift up all the later entries in this row */ \
163:     for (ii=N; ii>=_i; ii--) { \
164:       rp[ii+1] = rp[ii]; \
165:       PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar)); \
166:     } \
167:     if (N>=_i) { PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar));}  \
168:     rp[_i]                      = bcol;  \
169:     ap[bs2*_i + bs*cidx + ridx] = value;  \
170: b_noinsert:; \
171:     bilen[brow] = nrow; \
172:   }

174: PetscErrorCode MatSetValues_MPIBAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv)
175: {
176:   Mat_MPIBAIJ    *baij = (Mat_MPIBAIJ*)mat->data;
177:   MatScalar      value;
178:   PetscBool      roworiented = baij->roworiented;
180:   PetscInt       i,j,row,col;
181:   PetscInt       rstart_orig=mat->rmap->rstart;
182:   PetscInt       rend_orig  =mat->rmap->rend,cstart_orig=mat->cmap->rstart;
183:   PetscInt       cend_orig  =mat->cmap->rend,bs=mat->rmap->bs;

185:   /* Some Variables required in the macro */
186:   Mat         A     = baij->A;
187:   Mat_SeqBAIJ *a    = (Mat_SeqBAIJ*)(A)->data;
188:   PetscInt    *aimax=a->imax,*ai=a->i,*ailen=a->ilen,*aj=a->j;
189:   MatScalar   *aa   =a->a;

191:   Mat         B     = baij->B;
192:   Mat_SeqBAIJ *b    = (Mat_SeqBAIJ*)(B)->data;
193:   PetscInt    *bimax=b->imax,*bi=b->i,*bilen=b->ilen,*bj=b->j;
194:   MatScalar   *ba   =b->a;

196:   PetscInt  *rp,ii,nrow,_i,rmax,N,brow,bcol;
197:   PetscInt  low,high,t,ridx,cidx,bs2=a->bs2;
198:   MatScalar *ap,*bap;

201:   for (i=0; i<m; i++) {
202:     if (im[i] < 0) continue;
203: #if defined(PETSC_USE_DEBUG)
204:     if (im[i] >= mat->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],mat->rmap->N-1);
205: #endif
206:     if (im[i] >= rstart_orig && im[i] < rend_orig) {
207:       row = im[i] - rstart_orig;
208:       for (j=0; j<n; j++) {
209:         if (in[j] >= cstart_orig && in[j] < cend_orig) {
210:           col = in[j] - cstart_orig;
211:           if (roworiented) value = v[i*n+j];
212:           else             value = v[i+j*m];
213:           MatSetValues_SeqBAIJ_A_Private(row,col,value,addv,im[i],in[j]);
214:           /* MatSetValues_SeqBAIJ(baij->A,1,&row,1,&col,&value,addv); */
215:         } else if (in[j] < 0) continue;
216: #if defined(PETSC_USE_DEBUG)
217:         else if (in[j] >= mat->cmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",in[j],mat->cmap->N-1);
218: #endif
219:         else {
220:           if (mat->was_assembled) {
221:             if (!baij->colmap) {
222:               MatCreateColmap_MPIBAIJ_Private(mat);
223:             }
224: #if defined(PETSC_USE_CTABLE)
225:             PetscTableFind(baij->colmap,in[j]/bs + 1,&col);
226:             col  = col - 1;
227: #else
228:             col = baij->colmap[in[j]/bs] - 1;
229: #endif
230:             if (col < 0 && !((Mat_SeqBAIJ*)(baij->B->data))->nonew) {
231:               MatDisAssemble_MPIBAIJ(mat);
232:               col  =  in[j];
233:               /* Reinitialize the variables required by MatSetValues_SeqBAIJ_B_Private() */
234:               B    = baij->B;
235:               b    = (Mat_SeqBAIJ*)(B)->data;
236:               bimax=b->imax;bi=b->i;bilen=b->ilen;bj=b->j;
237:               ba   =b->a;
238:             } else if (col < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", im[i], in[j]);
239:             else col += in[j]%bs;
240:           } else col = in[j];
241:           if (roworiented) value = v[i*n+j];
242:           else             value = v[i+j*m];
243:           MatSetValues_SeqBAIJ_B_Private(row,col,value,addv,im[i],in[j]);
244:           /* MatSetValues_SeqBAIJ(baij->B,1,&row,1,&col,&value,addv); */
245:         }
246:       }
247:     } else {
248:       if (mat->nooffprocentries) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Setting off process row %D even though MatSetOption(,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE) was set",im[i]);
249:       if (!baij->donotstash) {
250:         mat->assembled = PETSC_FALSE;
251:         if (roworiented) {
252:           MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,PETSC_FALSE);
253:         } else {
254:           MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,PETSC_FALSE);
255:         }
256:       }
257:     }
258:   }
259:   return(0);
260: }

262: PETSC_STATIC_INLINE PetscErrorCode MatSetValuesBlocked_SeqBAIJ_Inlined(Mat A,PetscInt row,PetscInt col,const PetscScalar v[],InsertMode is,PetscInt orow,PetscInt ocol)
263: {
264:   Mat_SeqBAIJ       *a = (Mat_SeqBAIJ*)A->data;
265:   PetscInt          *rp,low,high,t,ii,jj,nrow,i,rmax,N;
266:   PetscInt          *imax=a->imax,*ai=a->i,*ailen=a->ilen;
267:   PetscErrorCode    ierr;
268:   PetscInt          *aj        =a->j,nonew=a->nonew,bs2=a->bs2,bs=A->rmap->bs;
269:   PetscBool         roworiented=a->roworiented;
270:   const PetscScalar *value     = v;
271:   MatScalar         *ap,*aa = a->a,*bap;

274:   rp   = aj + ai[row];
275:   ap   = aa + bs2*ai[row];
276:   rmax = imax[row];
277:   nrow = ailen[row];
278:   value = v;
279:   low = 0;
280:   high = nrow;
281:   while (high-low > 7) {
282:     t = (low+high)/2;
283:     if (rp[t] > col) high = t;
284:     else             low  = t;
285:   }
286:   for (i=low; i<high; i++) {
287:     if (rp[i] > col) break;
288:     if (rp[i] == col) {
289:       bap = ap +  bs2*i;
290:       if (roworiented) {
291:         if (is == ADD_VALUES) {
292:           for (ii=0; ii<bs; ii++) {
293:             for (jj=ii; jj<bs2; jj+=bs) {
294:               bap[jj] += *value++;
295:             }
296:           }
297:         } else {
298:           for (ii=0; ii<bs; ii++) {
299:             for (jj=ii; jj<bs2; jj+=bs) {
300:               bap[jj] = *value++;
301:             }
302:           }
303:         }
304:       } else {
305:         if (is == ADD_VALUES) {
306:           for (ii=0; ii<bs; ii++,value+=bs) {
307:             for (jj=0; jj<bs; jj++) {
308:               bap[jj] += value[jj];
309:             }
310:             bap += bs;
311:           }
312:         } else {
313:           for (ii=0; ii<bs; ii++,value+=bs) {
314:             for (jj=0; jj<bs; jj++) {
315:               bap[jj]  = value[jj];
316:             }
317:             bap += bs;
318:           }
319:         }
320:       }
321:       goto noinsert2;
322:     }
323:   }
324:   if (nonew == 1) goto noinsert2;
325:   if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new global block indexed nonzero block (%D, %D) in the matrix", orow, ocol);
326:   MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,row,col,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar);
327:   N = nrow++ - 1; high++;
328:   /* shift up all the later entries in this row */
329:   for (ii=N; ii>=i; ii--) {
330:     rp[ii+1] = rp[ii];
331:     PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));
332:   }
333:   if (N >= i) {
334:     PetscMemzero(ap+bs2*i,bs2*sizeof(MatScalar));
335:   }
336:   rp[i] = col;
337:   bap   = ap +  bs2*i;
338:   if (roworiented) {
339:     for (ii=0; ii<bs; ii++) {
340:       for (jj=ii; jj<bs2; jj+=bs) {
341:         bap[jj] = *value++;
342:       }
343:     }
344:   } else {
345:     for (ii=0; ii<bs; ii++) {
346:       for (jj=0; jj<bs; jj++) {
347:         *bap++ = *value++;
348:       }
349:     }
350:   }
351:   noinsert2:;
352:   ailen[row] = nrow;
353:   return(0);
354: }

356: /*
357:     This routine should be optimized so that the block copy at ** Here a copy is required ** below is not needed
358:     by passing additional stride information into the MatSetValuesBlocked_SeqBAIJ_Inlined() routine
359: */
360: PetscErrorCode MatSetValuesBlocked_MPIBAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv)
361: {
362:   Mat_MPIBAIJ       *baij = (Mat_MPIBAIJ*)mat->data;
363:   const PetscScalar *value;
364:   MatScalar         *barray     = baij->barray;
365:   PetscBool         roworiented = baij->roworiented;
366:   PetscErrorCode    ierr;
367:   PetscInt          i,j,ii,jj,row,col,rstart=baij->rstartbs;
368:   PetscInt          rend=baij->rendbs,cstart=baij->cstartbs,stepval;
369:   PetscInt          cend=baij->cendbs,bs=mat->rmap->bs,bs2=baij->bs2;

372:   if (!barray) {
373:     PetscMalloc1(bs2,&barray);
374:     baij->barray = barray;
375:   }

377:   if (roworiented) stepval = (n-1)*bs;
378:   else stepval = (m-1)*bs;

380:   for (i=0; i<m; i++) {
381:     if (im[i] < 0) continue;
382: #if defined(PETSC_USE_DEBUG)
383:     if (im[i] >= baij->Mbs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Block indexed row too large %D max %D",im[i],baij->Mbs-1);
384: #endif
385:     if (im[i] >= rstart && im[i] < rend) {
386:       row = im[i] - rstart;
387:       for (j=0; j<n; j++) {
388:         /* If NumCol = 1 then a copy is not required */
389:         if ((roworiented) && (n == 1)) {
390:           barray = (MatScalar*)v + i*bs2;
391:         } else if ((!roworiented) && (m == 1)) {
392:           barray = (MatScalar*)v + j*bs2;
393:         } else { /* Here a copy is required */
394:           if (roworiented) {
395:             value = v + (i*(stepval+bs) + j)*bs;
396:           } else {
397:             value = v + (j*(stepval+bs) + i)*bs;
398:           }
399:           for (ii=0; ii<bs; ii++,value+=bs+stepval) {
400:             for (jj=0; jj<bs; jj++) barray[jj] = value[jj];
401:             barray += bs;
402:           }
403:           barray -= bs2;
404:         }

406:         if (in[j] >= cstart && in[j] < cend) {
407:           col  = in[j] - cstart;
408:           MatSetValuesBlocked_SeqBAIJ_Inlined(baij->A,row,col,barray,addv,im[i],in[j]);
409:         } else if (in[j] < 0) continue;
410: #if defined(PETSC_USE_DEBUG)
411:         else if (in[j] >= baij->Nbs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Block indexed column too large %D max %D",in[j],baij->Nbs-1);
412: #endif
413:         else {
414:           if (mat->was_assembled) {
415:             if (!baij->colmap) {
416:               MatCreateColmap_MPIBAIJ_Private(mat);
417:             }

419: #if defined(PETSC_USE_DEBUG)
420: #if defined(PETSC_USE_CTABLE)
421:             { PetscInt data;
422:               PetscTableFind(baij->colmap,in[j]+1,&data);
423:               if ((data - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap");
424:             }
425: #else
426:             if ((baij->colmap[in[j]] - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap");
427: #endif
428: #endif
429: #if defined(PETSC_USE_CTABLE)
430:             PetscTableFind(baij->colmap,in[j]+1,&col);
431:             col  = (col - 1)/bs;
432: #else
433:             col = (baij->colmap[in[j]] - 1)/bs;
434: #endif
435:             if (col < 0 && !((Mat_SeqBAIJ*)(baij->B->data))->nonew) {
436:               MatDisAssemble_MPIBAIJ(mat);
437:               col  =  in[j];
438:             } else if (col < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new blocked indexed nonzero block (%D, %D) into matrix",im[i],in[j]);
439:           } else col = in[j];
440:           MatSetValuesBlocked_SeqBAIJ_Inlined(baij->B,row,col,barray,addv,im[i],in[j]);
441:         }
442:       }
443:     } else {
444:       if (mat->nooffprocentries) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Setting off process block indexed row %D even though MatSetOption(,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE) was set",im[i]);
445:       if (!baij->donotstash) {
446:         if (roworiented) {
447:           MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);
448:         } else {
449:           MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);
450:         }
451:       }
452:     }
453:   }
454:   return(0);
455: }

457: #define HASH_KEY 0.6180339887
458: #define HASH(size,key,tmp) (tmp = (key)*HASH_KEY,(PetscInt)((size)*(tmp-(PetscInt)tmp)))
459: /* #define HASH(size,key) ((PetscInt)((size)*fmod(((key)*HASH_KEY),1))) */
460: /* #define HASH(size,key,tmp) ((PetscInt)((size)*fmod(((key)*HASH_KEY),1))) */
461: PetscErrorCode MatSetValues_MPIBAIJ_HT(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv)
462: {
463:   Mat_MPIBAIJ    *baij       = (Mat_MPIBAIJ*)mat->data;
464:   PetscBool      roworiented = baij->roworiented;
466:   PetscInt       i,j,row,col;
467:   PetscInt       rstart_orig=mat->rmap->rstart;
468:   PetscInt       rend_orig  =mat->rmap->rend,Nbs=baij->Nbs;
469:   PetscInt       h1,key,size=baij->ht_size,bs=mat->rmap->bs,*HT=baij->ht,idx;
470:   PetscReal      tmp;
471:   MatScalar      **HD = baij->hd,value;
472: #if defined(PETSC_USE_DEBUG)
473:   PetscInt       total_ct=baij->ht_total_ct,insert_ct=baij->ht_insert_ct;
474: #endif

477:   for (i=0; i<m; i++) {
478: #if defined(PETSC_USE_DEBUG)
479:     if (im[i] < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row");
480:     if (im[i] >= mat->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],mat->rmap->N-1);
481: #endif
482:     row = im[i];
483:     if (row >= rstart_orig && row < rend_orig) {
484:       for (j=0; j<n; j++) {
485:         col = in[j];
486:         if (roworiented) value = v[i*n+j];
487:         else             value = v[i+j*m];
488:         /* Look up PetscInto the Hash Table */
489:         key = (row/bs)*Nbs+(col/bs)+1;
490:         h1  = HASH(size,key,tmp);


493:         idx = h1;
494: #if defined(PETSC_USE_DEBUG)
495:         insert_ct++;
496:         total_ct++;
497:         if (HT[idx] != key) {
498:           for (idx=h1; (idx<size) && (HT[idx]!=key); idx++,total_ct++) ;
499:           if (idx == size) {
500:             for (idx=0; (idx<h1) && (HT[idx]!=key); idx++,total_ct++) ;
501:             if (idx == h1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"(%D,%D) has no entry in the hash table", row, col);
502:           }
503:         }
504: #else
505:         if (HT[idx] != key) {
506:           for (idx=h1; (idx<size) && (HT[idx]!=key); idx++) ;
507:           if (idx == size) {
508:             for (idx=0; (idx<h1) && (HT[idx]!=key); idx++) ;
509:             if (idx == h1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"(%D,%D) has no entry in the hash table", row, col);
510:           }
511:         }
512: #endif
513:         /* A HASH table entry is found, so insert the values at the correct address */
514:         if (addv == ADD_VALUES) *(HD[idx]+ (col % bs)*bs + (row % bs)) += value;
515:         else                    *(HD[idx]+ (col % bs)*bs + (row % bs))  = value;
516:       }
517:     } else if (!baij->donotstash) {
518:       if (roworiented) {
519:         MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,PETSC_FALSE);
520:       } else {
521:         MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,PETSC_FALSE);
522:       }
523:     }
524:   }
525: #if defined(PETSC_USE_DEBUG)
526:   baij->ht_total_ct  += total_ct;
527:   baij->ht_insert_ct += insert_ct;
528: #endif
529:   return(0);
530: }

532: PetscErrorCode MatSetValuesBlocked_MPIBAIJ_HT(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv)
533: {
534:   Mat_MPIBAIJ       *baij       = (Mat_MPIBAIJ*)mat->data;
535:   PetscBool         roworiented = baij->roworiented;
536:   PetscErrorCode    ierr;
537:   PetscInt          i,j,ii,jj,row,col;
538:   PetscInt          rstart=baij->rstartbs;
539:   PetscInt          rend  =mat->rmap->rend,stepval,bs=mat->rmap->bs,bs2=baij->bs2,nbs2=n*bs2;
540:   PetscInt          h1,key,size=baij->ht_size,idx,*HT=baij->ht,Nbs=baij->Nbs;
541:   PetscReal         tmp;
542:   MatScalar         **HD = baij->hd,*baij_a;
543:   const PetscScalar *v_t,*value;
544: #if defined(PETSC_USE_DEBUG)
545:   PetscInt          total_ct=baij->ht_total_ct,insert_ct=baij->ht_insert_ct;
546: #endif

549:   if (roworiented) stepval = (n-1)*bs;
550:   else stepval = (m-1)*bs;

552:   for (i=0; i<m; i++) {
553: #if defined(PETSC_USE_DEBUG)
554:     if (im[i] < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",im[i]);
555:     if (im[i] >= baij->Mbs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],baij->Mbs-1);
556: #endif
557:     row = im[i];
558:     v_t = v + i*nbs2;
559:     if (row >= rstart && row < rend) {
560:       for (j=0; j<n; j++) {
561:         col = in[j];

563:         /* Look up into the Hash Table */
564:         key = row*Nbs+col+1;
565:         h1  = HASH(size,key,tmp);

567:         idx = h1;
568: #if defined(PETSC_USE_DEBUG)
569:         total_ct++;
570:         insert_ct++;
571:         if (HT[idx] != key) {
572:           for (idx=h1; (idx<size) && (HT[idx]!=key); idx++,total_ct++) ;
573:           if (idx == size) {
574:             for (idx=0; (idx<h1) && (HT[idx]!=key); idx++,total_ct++) ;
575:             if (idx == h1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"(%D,%D) has no entry in the hash table", row, col);
576:           }
577:         }
578: #else
579:         if (HT[idx] != key) {
580:           for (idx=h1; (idx<size) && (HT[idx]!=key); idx++) ;
581:           if (idx == size) {
582:             for (idx=0; (idx<h1) && (HT[idx]!=key); idx++) ;
583:             if (idx == h1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"(%D,%D) has no entry in the hash table", row, col);
584:           }
585:         }
586: #endif
587:         baij_a = HD[idx];
588:         if (roworiented) {
589:           /*value = v + i*(stepval+bs)*bs + j*bs;*/
590:           /* value = v + (i*(stepval+bs)+j)*bs; */
591:           value = v_t;
592:           v_t  += bs;
593:           if (addv == ADD_VALUES) {
594:             for (ii=0; ii<bs; ii++,value+=stepval) {
595:               for (jj=ii; jj<bs2; jj+=bs) {
596:                 baij_a[jj] += *value++;
597:               }
598:             }
599:           } else {
600:             for (ii=0; ii<bs; ii++,value+=stepval) {
601:               for (jj=ii; jj<bs2; jj+=bs) {
602:                 baij_a[jj] = *value++;
603:               }
604:             }
605:           }
606:         } else {
607:           value = v + j*(stepval+bs)*bs + i*bs;
608:           if (addv == ADD_VALUES) {
609:             for (ii=0; ii<bs; ii++,value+=stepval,baij_a+=bs) {
610:               for (jj=0; jj<bs; jj++) {
611:                 baij_a[jj] += *value++;
612:               }
613:             }
614:           } else {
615:             for (ii=0; ii<bs; ii++,value+=stepval,baij_a+=bs) {
616:               for (jj=0; jj<bs; jj++) {
617:                 baij_a[jj] = *value++;
618:               }
619:             }
620:           }
621:         }
622:       }
623:     } else {
624:       if (!baij->donotstash) {
625:         if (roworiented) {
626:           MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);
627:         } else {
628:           MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);
629:         }
630:       }
631:     }
632:   }
633: #if defined(PETSC_USE_DEBUG)
634:   baij->ht_total_ct  += total_ct;
635:   baij->ht_insert_ct += insert_ct;
636: #endif
637:   return(0);
638: }

640: PetscErrorCode MatGetValues_MPIBAIJ(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[])
641: {
642:   Mat_MPIBAIJ    *baij = (Mat_MPIBAIJ*)mat->data;
644:   PetscInt       bs       = mat->rmap->bs,i,j,bsrstart = mat->rmap->rstart,bsrend = mat->rmap->rend;
645:   PetscInt       bscstart = mat->cmap->rstart,bscend = mat->cmap->rend,row,col,data;

648:   for (i=0; i<m; i++) {
649:     if (idxm[i] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",idxm[i]);*/
650:     if (idxm[i] >= mat->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",idxm[i],mat->rmap->N-1);
651:     if (idxm[i] >= bsrstart && idxm[i] < bsrend) {
652:       row = idxm[i] - bsrstart;
653:       for (j=0; j<n; j++) {
654:         if (idxn[j] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column: %D",idxn[j]); */
655:         if (idxn[j] >= mat->cmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",idxn[j],mat->cmap->N-1);
656:         if (idxn[j] >= bscstart && idxn[j] < bscend) {
657:           col  = idxn[j] - bscstart;
658:           MatGetValues_SeqBAIJ(baij->A,1,&row,1,&col,v+i*n+j);
659:         } else {
660:           if (!baij->colmap) {
661:             MatCreateColmap_MPIBAIJ_Private(mat);
662:           }
663: #if defined(PETSC_USE_CTABLE)
664:           PetscTableFind(baij->colmap,idxn[j]/bs+1,&data);
665:           data--;
666: #else
667:           data = baij->colmap[idxn[j]/bs]-1;
668: #endif
669:           if ((data < 0) || (baij->garray[data/bs] != idxn[j]/bs)) *(v+i*n+j) = 0.0;
670:           else {
671:             col  = data + idxn[j]%bs;
672:             MatGetValues_SeqBAIJ(baij->B,1,&row,1,&col,v+i*n+j);
673:           }
674:         }
675:       }
676:     } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local values currently supported");
677:   }
678:   return(0);
679: }

681: PetscErrorCode MatNorm_MPIBAIJ(Mat mat,NormType type,PetscReal *nrm)
682: {
683:   Mat_MPIBAIJ    *baij = (Mat_MPIBAIJ*)mat->data;
684:   Mat_SeqBAIJ    *amat = (Mat_SeqBAIJ*)baij->A->data,*bmat = (Mat_SeqBAIJ*)baij->B->data;
686:   PetscInt       i,j,bs2=baij->bs2,bs=baij->A->rmap->bs,nz,row,col;
687:   PetscReal      sum = 0.0;
688:   MatScalar      *v;

691:   if (baij->size == 1) {
692:      MatNorm(baij->A,type,nrm);
693:   } else {
694:     if (type == NORM_FROBENIUS) {
695:       v  = amat->a;
696:       nz = amat->nz*bs2;
697:       for (i=0; i<nz; i++) {
698:         sum += PetscRealPart(PetscConj(*v)*(*v)); v++;
699:       }
700:       v  = bmat->a;
701:       nz = bmat->nz*bs2;
702:       for (i=0; i<nz; i++) {
703:         sum += PetscRealPart(PetscConj(*v)*(*v)); v++;
704:       }
705:       MPIU_Allreduce(&sum,nrm,1,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));
706:       *nrm = PetscSqrtReal(*nrm);
707:     } else if (type == NORM_1) { /* max column sum */
708:       PetscReal *tmp,*tmp2;
709:       PetscInt  *jj,*garray=baij->garray,cstart=baij->rstartbs;
710:       PetscMalloc2(mat->cmap->N,&tmp,mat->cmap->N,&tmp2);
711:       PetscMemzero(tmp,mat->cmap->N*sizeof(PetscReal));
712:       v    = amat->a; jj = amat->j;
713:       for (i=0; i<amat->nz; i++) {
714:         for (j=0; j<bs; j++) {
715:           col = bs*(cstart + *jj) + j; /* column index */
716:           for (row=0; row<bs; row++) {
717:             tmp[col] += PetscAbsScalar(*v);  v++;
718:           }
719:         }
720:         jj++;
721:       }
722:       v = bmat->a; jj = bmat->j;
723:       for (i=0; i<bmat->nz; i++) {
724:         for (j=0; j<bs; j++) {
725:           col = bs*garray[*jj] + j;
726:           for (row=0; row<bs; row++) {
727:             tmp[col] += PetscAbsScalar(*v); v++;
728:           }
729:         }
730:         jj++;
731:       }
732:       MPIU_Allreduce(tmp,tmp2,mat->cmap->N,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));
733:       *nrm = 0.0;
734:       for (j=0; j<mat->cmap->N; j++) {
735:         if (tmp2[j] > *nrm) *nrm = tmp2[j];
736:       }
737:       PetscFree2(tmp,tmp2);
738:     } else if (type == NORM_INFINITY) { /* max row sum */
739:       PetscReal *sums;
740:       PetscMalloc1(bs,&sums);
741:       sum  = 0.0;
742:       for (j=0; j<amat->mbs; j++) {
743:         for (row=0; row<bs; row++) sums[row] = 0.0;
744:         v  = amat->a + bs2*amat->i[j];
745:         nz = amat->i[j+1]-amat->i[j];
746:         for (i=0; i<nz; i++) {
747:           for (col=0; col<bs; col++) {
748:             for (row=0; row<bs; row++) {
749:               sums[row] += PetscAbsScalar(*v); v++;
750:             }
751:           }
752:         }
753:         v  = bmat->a + bs2*bmat->i[j];
754:         nz = bmat->i[j+1]-bmat->i[j];
755:         for (i=0; i<nz; i++) {
756:           for (col=0; col<bs; col++) {
757:             for (row=0; row<bs; row++) {
758:               sums[row] += PetscAbsScalar(*v); v++;
759:             }
760:           }
761:         }
762:         for (row=0; row<bs; row++) {
763:           if (sums[row] > sum) sum = sums[row];
764:         }
765:       }
766:       MPIU_Allreduce(&sum,nrm,1,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)mat));
767:       PetscFree(sums);
768:     } else SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_SUP,"No support for this norm yet");
769:   }
770:   return(0);
771: }

773: /*
774:   Creates the hash table, and sets the table
775:   This table is created only once.
776:   If new entried need to be added to the matrix
777:   then the hash table has to be destroyed and
778:   recreated.
779: */
780: PetscErrorCode MatCreateHashTable_MPIBAIJ_Private(Mat mat,PetscReal factor)
781: {
782:   Mat_MPIBAIJ    *baij = (Mat_MPIBAIJ*)mat->data;
783:   Mat            A     = baij->A,B=baij->B;
784:   Mat_SeqBAIJ    *a    = (Mat_SeqBAIJ*)A->data,*b=(Mat_SeqBAIJ*)B->data;
785:   PetscInt       i,j,k,nz=a->nz+b->nz,h1,*ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j;
787:   PetscInt       ht_size,bs2=baij->bs2,rstart=baij->rstartbs;
788:   PetscInt       cstart=baij->cstartbs,*garray=baij->garray,row,col,Nbs=baij->Nbs;
789:   PetscInt       *HT,key;
790:   MatScalar      **HD;
791:   PetscReal      tmp;
792: #if defined(PETSC_USE_INFO)
793:   PetscInt ct=0,max=0;
794: #endif

797:   if (baij->ht) return(0);

799:   baij->ht_size = (PetscInt)(factor*nz);
800:   ht_size       = baij->ht_size;

802:   /* Allocate Memory for Hash Table */
803:   PetscCalloc2(ht_size,&baij->hd,ht_size,&baij->ht);
804:   HD   = baij->hd;
805:   HT   = baij->ht;

807:   /* Loop Over A */
808:   for (i=0; i<a->mbs; i++) {
809:     for (j=ai[i]; j<ai[i+1]; j++) {
810:       row = i+rstart;
811:       col = aj[j]+cstart;

813:       key = row*Nbs + col + 1;
814:       h1  = HASH(ht_size,key,tmp);
815:       for (k=0; k<ht_size; k++) {
816:         if (!HT[(h1+k)%ht_size]) {
817:           HT[(h1+k)%ht_size] = key;
818:           HD[(h1+k)%ht_size] = a->a + j*bs2;
819:           break;
820: #if defined(PETSC_USE_INFO)
821:         } else {
822:           ct++;
823: #endif
824:         }
825:       }
826: #if defined(PETSC_USE_INFO)
827:       if (k> max) max = k;
828: #endif
829:     }
830:   }
831:   /* Loop Over B */
832:   for (i=0; i<b->mbs; i++) {
833:     for (j=bi[i]; j<bi[i+1]; j++) {
834:       row = i+rstart;
835:       col = garray[bj[j]];
836:       key = row*Nbs + col + 1;
837:       h1  = HASH(ht_size,key,tmp);
838:       for (k=0; k<ht_size; k++) {
839:         if (!HT[(h1+k)%ht_size]) {
840:           HT[(h1+k)%ht_size] = key;
841:           HD[(h1+k)%ht_size] = b->a + j*bs2;
842:           break;
843: #if defined(PETSC_USE_INFO)
844:         } else {
845:           ct++;
846: #endif
847:         }
848:       }
849: #if defined(PETSC_USE_INFO)
850:       if (k> max) max = k;
851: #endif
852:     }
853:   }

855:   /* Print Summary */
856: #if defined(PETSC_USE_INFO)
857:   for (i=0,j=0; i<ht_size; i++) {
858:     if (HT[i]) j++;
859:   }
860:   PetscInfo2(mat,"Average Search = %5.2f,max search = %D\n",(!j)? 0.0:((PetscReal)(ct+j))/j,max);
861: #endif
862:   return(0);
863: }

865: PetscErrorCode MatAssemblyBegin_MPIBAIJ(Mat mat,MatAssemblyType mode)
866: {
867:   Mat_MPIBAIJ    *baij = (Mat_MPIBAIJ*)mat->data;
869:   PetscInt       nstash,reallocs;

872:   if (baij->donotstash || mat->nooffprocentries) return(0);

874:   MatStashScatterBegin_Private(mat,&mat->stash,mat->rmap->range);
875:   MatStashScatterBegin_Private(mat,&mat->bstash,baij->rangebs);
876:   MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);
877:   PetscInfo2(mat,"Stash has %D entries,uses %D mallocs.\n",nstash,reallocs);
878:   MatStashGetInfo_Private(&mat->bstash,&nstash,&reallocs);
879:   PetscInfo2(mat,"Block-Stash has %D entries, uses %D mallocs.\n",nstash,reallocs);
880:   return(0);
881: }

883: PetscErrorCode MatAssemblyEnd_MPIBAIJ(Mat mat,MatAssemblyType mode)
884: {
885:   Mat_MPIBAIJ    *baij=(Mat_MPIBAIJ*)mat->data;
886:   Mat_SeqBAIJ    *a   =(Mat_SeqBAIJ*)baij->A->data;
888:   PetscInt       i,j,rstart,ncols,flg,bs2=baij->bs2;
889:   PetscInt       *row,*col;
890:   PetscBool      r1,r2,r3,other_disassembled;
891:   MatScalar      *val;
892:   PetscMPIInt    n;

895:   /* do not use 'b=(Mat_SeqBAIJ*)baij->B->data' as B can be reset in disassembly */
896:   if (!baij->donotstash && !mat->nooffprocentries) {
897:     while (1) {
898:       MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);
899:       if (!flg) break;

901:       for (i=0; i<n;) {
902:         /* Now identify the consecutive vals belonging to the same row */
903:         for (j=i,rstart=row[j]; j<n; j++) {
904:           if (row[j] != rstart) break;
905:         }
906:         if (j < n) ncols = j-i;
907:         else       ncols = n-i;
908:         /* Now assemble all these values with a single function call */
909:         MatSetValues_MPIBAIJ(mat,1,row+i,ncols,col+i,val+i,mat->insertmode);
910:         i    = j;
911:       }
912:     }
913:     MatStashScatterEnd_Private(&mat->stash);
914:     /* Now process the block-stash. Since the values are stashed column-oriented,
915:        set the roworiented flag to column oriented, and after MatSetValues()
916:        restore the original flags */
917:     r1 = baij->roworiented;
918:     r2 = a->roworiented;
919:     r3 = ((Mat_SeqBAIJ*)baij->B->data)->roworiented;

921:     baij->roworiented = PETSC_FALSE;
922:     a->roworiented    = PETSC_FALSE;

924:     (((Mat_SeqBAIJ*)baij->B->data))->roworiented = PETSC_FALSE; /* b->roworiented */
925:     while (1) {
926:       MatStashScatterGetMesg_Private(&mat->bstash,&n,&row,&col,&val,&flg);
927:       if (!flg) break;

929:       for (i=0; i<n;) {
930:         /* Now identify the consecutive vals belonging to the same row */
931:         for (j=i,rstart=row[j]; j<n; j++) {
932:           if (row[j] != rstart) break;
933:         }
934:         if (j < n) ncols = j-i;
935:         else       ncols = n-i;
936:         MatSetValuesBlocked_MPIBAIJ(mat,1,row+i,ncols,col+i,val+i*bs2,mat->insertmode);
937:         i    = j;
938:       }
939:     }
940:     MatStashScatterEnd_Private(&mat->bstash);

942:     baij->roworiented = r1;
943:     a->roworiented    = r2;

945:     ((Mat_SeqBAIJ*)baij->B->data)->roworiented = r3; /* b->roworiented */
946:   }

948:   MatAssemblyBegin(baij->A,mode);
949:   MatAssemblyEnd(baij->A,mode);

951:   /* determine if any processor has disassembled, if so we must
952:      also disassemble ourselfs, in order that we may reassemble. */
953:   /*
954:      if nonzero structure of submatrix B cannot change then we know that
955:      no processor disassembled thus we can skip this stuff
956:   */
957:   if (!((Mat_SeqBAIJ*)baij->B->data)->nonew) {
958:     MPIU_Allreduce(&mat->was_assembled,&other_disassembled,1,MPIU_BOOL,MPI_PROD,PetscObjectComm((PetscObject)mat));
959:     if (mat->was_assembled && !other_disassembled) {
960:       MatDisAssemble_MPIBAIJ(mat);
961:     }
962:   }

964:   if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) {
965:     MatSetUpMultiply_MPIBAIJ(mat);
966:   }
967:   MatAssemblyBegin(baij->B,mode);
968:   MatAssemblyEnd(baij->B,mode);

970: #if defined(PETSC_USE_INFO)
971:   if (baij->ht && mode== MAT_FINAL_ASSEMBLY) {
972:     PetscInfo1(mat,"Average Hash Table Search in MatSetValues = %5.2f\n",(double)((PetscReal)baij->ht_total_ct)/baij->ht_insert_ct);

974:     baij->ht_total_ct  = 0;
975:     baij->ht_insert_ct = 0;
976:   }
977: #endif
978:   if (baij->ht_flag && !baij->ht && mode == MAT_FINAL_ASSEMBLY) {
979:     MatCreateHashTable_MPIBAIJ_Private(mat,baij->ht_fact);

981:     mat->ops->setvalues        = MatSetValues_MPIBAIJ_HT;
982:     mat->ops->setvaluesblocked = MatSetValuesBlocked_MPIBAIJ_HT;
983:   }

985:   PetscFree2(baij->rowvalues,baij->rowindices);

987:   baij->rowvalues = 0;

989:   /* if no new nonzero locations are allowed in matrix then only set the matrix state the first time through */
990:   if ((!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) || !((Mat_SeqBAIJ*)(baij->A->data))->nonew) {
991:     PetscObjectState state = baij->A->nonzerostate + baij->B->nonzerostate;
992:     MPIU_Allreduce(&state,&mat->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)mat));
993:   }
994:   return(0);
995: }

997: extern PetscErrorCode MatView_SeqBAIJ(Mat,PetscViewer);
998:  #include <petscdraw.h>
999: static PetscErrorCode MatView_MPIBAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer)
1000: {
1001:   Mat_MPIBAIJ       *baij = (Mat_MPIBAIJ*)mat->data;
1002:   PetscErrorCode    ierr;
1003:   PetscMPIInt       rank = baij->rank;
1004:   PetscInt          bs   = mat->rmap->bs;
1005:   PetscBool         iascii,isdraw;
1006:   PetscViewer       sviewer;
1007:   PetscViewerFormat format;

1010:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
1011:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);
1012:   if (iascii) {
1013:     PetscViewerGetFormat(viewer,&format);
1014:     if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) {
1015:       MatInfo info;
1016:       MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);
1017:       MatGetInfo(mat,MAT_LOCAL,&info);
1018:       PetscViewerASCIIPushSynchronized(viewer);
1019:       PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D bs %D mem %D\n",
1020:                                                 rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,mat->rmap->bs,(PetscInt)info.memory);
1021:       MatGetInfo(baij->A,MAT_LOCAL,&info);
1022:       PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);
1023:       MatGetInfo(baij->B,MAT_LOCAL,&info);
1024:       PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);
1025:       PetscViewerFlush(viewer);
1026:       PetscViewerASCIIPopSynchronized(viewer);
1027:       PetscViewerASCIIPrintf(viewer,"Information on VecScatter used in matrix-vector product: \n");
1028:       VecScatterView(baij->Mvctx,viewer);
1029:       return(0);
1030:     } else if (format == PETSC_VIEWER_ASCII_INFO) {
1031:       PetscViewerASCIIPrintf(viewer,"  block size is %D\n",bs);
1032:       return(0);
1033:     } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) {
1034:       return(0);
1035:     }
1036:   }

1038:   if (isdraw) {
1039:     PetscDraw draw;
1040:     PetscBool isnull;
1041:     PetscViewerDrawGetDraw(viewer,0,&draw);
1042:     PetscDrawIsNull(draw,&isnull);
1043:     if (isnull) return(0);
1044:   }

1046:   {
1047:     /* assemble the entire matrix onto first processor. */
1048:     Mat         A;
1049:     Mat_SeqBAIJ *Aloc;
1050:     PetscInt    M = mat->rmap->N,N = mat->cmap->N,*ai,*aj,col,i,j,k,*rvals,mbs = baij->mbs;
1051:     MatScalar   *a;
1052:     const char  *matname;

1054:     /* Here we are creating a temporary matrix, so will assume MPIBAIJ is acceptable */
1055:     /* Perhaps this should be the type of mat? */
1056:     MatCreate(PetscObjectComm((PetscObject)mat),&A);
1057:     if (!rank) {
1058:       MatSetSizes(A,M,N,M,N);
1059:     } else {
1060:       MatSetSizes(A,0,0,M,N);
1061:     }
1062:     MatSetType(A,MATMPIBAIJ);
1063:     MatMPIBAIJSetPreallocation(A,mat->rmap->bs,0,NULL,0,NULL);
1064:     MatSetOption(A,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_FALSE);
1065:     PetscLogObjectParent((PetscObject)mat,(PetscObject)A);

1067:     /* copy over the A part */
1068:     Aloc = (Mat_SeqBAIJ*)baij->A->data;
1069:     ai   = Aloc->i; aj = Aloc->j; a = Aloc->a;
1070:     PetscMalloc1(bs,&rvals);

1072:     for (i=0; i<mbs; i++) {
1073:       rvals[0] = bs*(baij->rstartbs + i);
1074:       for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1;
1075:       for (j=ai[i]; j<ai[i+1]; j++) {
1076:         col = (baij->cstartbs+aj[j])*bs;
1077:         for (k=0; k<bs; k++) {
1078:           MatSetValues_MPIBAIJ(A,bs,rvals,1,&col,a,INSERT_VALUES);
1079:           col++; a += bs;
1080:         }
1081:       }
1082:     }
1083:     /* copy over the B part */
1084:     Aloc = (Mat_SeqBAIJ*)baij->B->data;
1085:     ai   = Aloc->i; aj = Aloc->j; a = Aloc->a;
1086:     for (i=0; i<mbs; i++) {
1087:       rvals[0] = bs*(baij->rstartbs + i);
1088:       for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1;
1089:       for (j=ai[i]; j<ai[i+1]; j++) {
1090:         col = baij->garray[aj[j]]*bs;
1091:         for (k=0; k<bs; k++) {
1092:           MatSetValues_MPIBAIJ(A,bs,rvals,1,&col,a,INSERT_VALUES);
1093:           col++; a += bs;
1094:         }
1095:       }
1096:     }
1097:     PetscFree(rvals);
1098:     MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);
1099:     MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);
1100:     /*
1101:        Everyone has to call to draw the matrix since the graphics waits are
1102:        synchronized across all processors that share the PetscDraw object
1103:     */
1104:     PetscViewerGetSubViewer(viewer,PETSC_COMM_SELF,&sviewer);
1105:     PetscObjectGetName((PetscObject)mat,&matname);
1106:     if (!rank) {
1107:       PetscObjectSetName((PetscObject)((Mat_MPIBAIJ*)(A->data))->A,matname);
1108:       MatView_SeqBAIJ(((Mat_MPIBAIJ*)(A->data))->A,sviewer);
1109:     }
1110:     PetscViewerRestoreSubViewer(viewer,PETSC_COMM_SELF,&sviewer);
1111:     PetscViewerFlush(viewer);
1112:     MatDestroy(&A);
1113:   }
1114:   return(0);
1115: }

1117: static PetscErrorCode MatView_MPIBAIJ_Binary(Mat mat,PetscViewer viewer)
1118: {
1119:   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)mat->data;
1120:   Mat_SeqBAIJ    *A = (Mat_SeqBAIJ*)a->A->data;
1121:   Mat_SeqBAIJ    *B = (Mat_SeqBAIJ*)a->B->data;
1123:   PetscInt       i,*row_lens,*crow_lens,bs = mat->rmap->bs,j,k,bs2=a->bs2,header[4],nz,rlen;
1124:   PetscInt       *range=0,nzmax,*column_indices,cnt,col,*garray = a->garray,cstart = mat->cmap->rstart/bs,len,pcnt,l,ll;
1125:   int            fd;
1126:   PetscScalar    *column_values;
1127:   FILE           *file;
1128:   PetscMPIInt    rank,size,tag = ((PetscObject)viewer)->tag;
1129:   PetscInt       message_count,flowcontrolcount;

1132:   MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);
1133:   MPI_Comm_size(PetscObjectComm((PetscObject)mat),&size);
1134:   nz   = bs2*(A->nz + B->nz);
1135:   rlen = mat->rmap->n;
1136:   PetscViewerBinaryGetDescriptor(viewer,&fd);
1137:   if (!rank) {
1138:     header[0] = MAT_FILE_CLASSID;
1139:     header[1] = mat->rmap->N;
1140:     header[2] = mat->cmap->N;

1142:     MPI_Reduce(&nz,&header[3],1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));
1143:     PetscBinaryWrite(fd,header,4,PETSC_INT,PETSC_TRUE);
1144:     /* get largest number of rows any processor has */
1145:     range = mat->rmap->range;
1146:     for (i=1; i<size; i++) {
1147:       rlen = PetscMax(rlen,range[i+1] - range[i]);
1148:     }
1149:   } else {
1150:     MPI_Reduce(&nz,0,1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));
1151:   }

1153:   PetscMalloc1(rlen/bs,&crow_lens);
1154:   /* compute lengths of each row  */
1155:   for (i=0; i<a->mbs; i++) {
1156:     crow_lens[i] = A->i[i+1] - A->i[i] + B->i[i+1] - B->i[i];
1157:   }
1158:   /* store the row lengths to the file */
1159:   PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);
1160:   if (!rank) {
1161:     MPI_Status status;
1162:     PetscMalloc1(rlen,&row_lens);
1163:     rlen = (range[1] - range[0])/bs;
1164:     for (i=0; i<rlen; i++) {
1165:       for (j=0; j<bs; j++) {
1166:         row_lens[i*bs+j] = bs*crow_lens[i];
1167:       }
1168:     }
1169:     PetscBinaryWrite(fd,row_lens,bs*rlen,PETSC_INT,PETSC_TRUE);
1170:     for (i=1; i<size; i++) {
1171:       rlen = (range[i+1] - range[i])/bs;
1172:       PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);
1173:       MPI_Recv(crow_lens,rlen,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);
1174:       for (k=0; k<rlen; k++) {
1175:         for (j=0; j<bs; j++) {
1176:           row_lens[k*bs+j] = bs*crow_lens[k];
1177:         }
1178:       }
1179:       PetscBinaryWrite(fd,row_lens,bs*rlen,PETSC_INT,PETSC_TRUE);
1180:     }
1181:     PetscViewerFlowControlEndMaster(viewer,&message_count);
1182:     PetscFree(row_lens);
1183:   } else {
1184:     PetscViewerFlowControlStepWorker(viewer,rank,&message_count);
1185:     MPI_Send(crow_lens,mat->rmap->n/bs,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));
1186:     PetscViewerFlowControlEndWorker(viewer,&message_count);
1187:   }
1188:   PetscFree(crow_lens);

1190:   /* load up the local column indices. Include for all rows not just one for each block row since process 0 does not have the
1191:      information needed to make it for each row from a block row. This does require more communication but still not more than
1192:      the communication needed for the nonzero values  */
1193:   nzmax = nz; /*  space a largest processor needs */
1194:   MPI_Reduce(&nz,&nzmax,1,MPIU_INT,MPI_MAX,0,PetscObjectComm((PetscObject)mat));
1195:   PetscMalloc1(nzmax,&column_indices);
1196:   cnt   = 0;
1197:   for (i=0; i<a->mbs; i++) {
1198:     pcnt = cnt;
1199:     for (j=B->i[i]; j<B->i[i+1]; j++) {
1200:       if ((col = garray[B->j[j]]) > cstart) break;
1201:       for (l=0; l<bs; l++) {
1202:         column_indices[cnt++] = bs*col+l;
1203:       }
1204:     }
1205:     for (k=A->i[i]; k<A->i[i+1]; k++) {
1206:       for (l=0; l<bs; l++) {
1207:         column_indices[cnt++] = bs*(A->j[k] + cstart)+l;
1208:       }
1209:     }
1210:     for (; j<B->i[i+1]; j++) {
1211:       for (l=0; l<bs; l++) {
1212:         column_indices[cnt++] = bs*garray[B->j[j]]+l;
1213:       }
1214:     }
1215:     len = cnt - pcnt;
1216:     for (k=1; k<bs; k++) {
1217:       PetscMemcpy(&column_indices[cnt],&column_indices[pcnt],len*sizeof(PetscInt));
1218:       cnt += len;
1219:     }
1220:   }
1221:   if (cnt != nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: cnt = %D nz = %D",cnt,nz);

1223:   /* store the columns to the file */
1224:   PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);
1225:   if (!rank) {
1226:     MPI_Status status;
1227:     PetscBinaryWrite(fd,column_indices,nz,PETSC_INT,PETSC_TRUE);
1228:     for (i=1; i<size; i++) {
1229:       PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);
1230:       MPI_Recv(&cnt,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);
1231:       MPI_Recv(column_indices,cnt,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);
1232:       PetscBinaryWrite(fd,column_indices,cnt,PETSC_INT,PETSC_TRUE);
1233:     }
1234:     PetscViewerFlowControlEndMaster(viewer,&message_count);
1235:   } else {
1236:     PetscViewerFlowControlStepWorker(viewer,rank,&message_count);
1237:     MPI_Send(&cnt,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));
1238:     MPI_Send(column_indices,cnt,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));
1239:     PetscViewerFlowControlEndWorker(viewer,&message_count);
1240:   }
1241:   PetscFree(column_indices);

1243:   /* load up the numerical values */
1244:   PetscMalloc1(nzmax,&column_values);
1245:   cnt  = 0;
1246:   for (i=0; i<a->mbs; i++) {
1247:     rlen = bs*(B->i[i+1] - B->i[i] + A->i[i+1] - A->i[i]);
1248:     for (j=B->i[i]; j<B->i[i+1]; j++) {
1249:       if (garray[B->j[j]] > cstart) break;
1250:       for (l=0; l<bs; l++) {
1251:         for (ll=0; ll<bs; ll++) {
1252:           column_values[cnt + l*rlen + ll] = B->a[bs2*j+l+bs*ll];
1253:         }
1254:       }
1255:       cnt += bs;
1256:     }
1257:     for (k=A->i[i]; k<A->i[i+1]; k++) {
1258:       for (l=0; l<bs; l++) {
1259:         for (ll=0; ll<bs; ll++) {
1260:           column_values[cnt + l*rlen + ll] = A->a[bs2*k+l+bs*ll];
1261:         }
1262:       }
1263:       cnt += bs;
1264:     }
1265:     for (; j<B->i[i+1]; j++) {
1266:       for (l=0; l<bs; l++) {
1267:         for (ll=0; ll<bs; ll++) {
1268:           column_values[cnt + l*rlen + ll] = B->a[bs2*j+l+bs*ll];
1269:         }
1270:       }
1271:       cnt += bs;
1272:     }
1273:     cnt += (bs-1)*rlen;
1274:   }
1275:   if (cnt != nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Internal PETSc error: cnt = %D nz = %D",cnt,nz);

1277:   /* store the column values to the file */
1278:   PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);
1279:   if (!rank) {
1280:     MPI_Status status;
1281:     PetscBinaryWrite(fd,column_values,nz,PETSC_SCALAR,PETSC_TRUE);
1282:     for (i=1; i<size; i++) {
1283:       PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);
1284:       MPI_Recv(&cnt,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);
1285:       MPI_Recv(column_values,cnt,MPIU_SCALAR,i,tag,PetscObjectComm((PetscObject)mat),&status);
1286:       PetscBinaryWrite(fd,column_values,cnt,PETSC_SCALAR,PETSC_TRUE);
1287:     }
1288:     PetscViewerFlowControlEndMaster(viewer,&message_count);
1289:   } else {
1290:     PetscViewerFlowControlStepWorker(viewer,rank,&message_count);
1291:     MPI_Send(&nz,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));
1292:     MPI_Send(column_values,nz,MPIU_SCALAR,0,tag,PetscObjectComm((PetscObject)mat));
1293:     PetscViewerFlowControlEndWorker(viewer,&message_count);
1294:   }
1295:   PetscFree(column_values);

1297:   PetscViewerBinaryGetInfoPointer(viewer,&file);
1298:   if (file) {
1299:     fprintf(file,"-matload_block_size %d\n",(int)mat->rmap->bs);
1300:   }
1301:   return(0);
1302: }

1304: PetscErrorCode MatView_MPIBAIJ(Mat mat,PetscViewer viewer)
1305: {
1307:   PetscBool      iascii,isdraw,issocket,isbinary;

1310:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
1311:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);
1312:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSOCKET,&issocket);
1313:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);
1314:   if (iascii || isdraw || issocket) {
1315:     MatView_MPIBAIJ_ASCIIorDraworSocket(mat,viewer);
1316:   } else if (isbinary) {
1317:     MatView_MPIBAIJ_Binary(mat,viewer);
1318:   }
1319:   return(0);
1320: }

1322: PetscErrorCode MatDestroy_MPIBAIJ(Mat mat)
1323: {
1324:   Mat_MPIBAIJ    *baij = (Mat_MPIBAIJ*)mat->data;

1328: #if defined(PETSC_USE_LOG)
1329:   PetscLogObjectState((PetscObject)mat,"Rows=%D,Cols=%D",mat->rmap->N,mat->cmap->N);
1330: #endif
1331:   MatStashDestroy_Private(&mat->stash);
1332:   MatStashDestroy_Private(&mat->bstash);
1333:   MatDestroy(&baij->A);
1334:   MatDestroy(&baij->B);
1335: #if defined(PETSC_USE_CTABLE)
1336:   PetscTableDestroy(&baij->colmap);
1337: #else
1338:   PetscFree(baij->colmap);
1339: #endif
1340:   PetscFree(baij->garray);
1341:   VecDestroy(&baij->lvec);
1342:   VecScatterDestroy(&baij->Mvctx);
1343:   PetscFree2(baij->rowvalues,baij->rowindices);
1344:   PetscFree(baij->barray);
1345:   PetscFree2(baij->hd,baij->ht);
1346:   PetscFree(baij->rangebs);
1347:   PetscFree(mat->data);

1349:   PetscObjectChangeTypeName((PetscObject)mat,0);
1350:   PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C",NULL);
1351:   PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C",NULL);
1352:   PetscObjectComposeFunction((PetscObject)mat,"MatMPIBAIJSetPreallocation_C",NULL);
1353:   PetscObjectComposeFunction((PetscObject)mat,"MatMPIBAIJSetPreallocationCSR_C",NULL);
1354:   PetscObjectComposeFunction((PetscObject)mat,"MatDiagonalScaleLocal_C",NULL);
1355:   PetscObjectComposeFunction((PetscObject)mat,"MatSetHashTableFactor_C",NULL);
1356:   PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpibaij_mpisbaij_C",NULL);
1357:   PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpibaij_mpibstrm_C",NULL);
1358: #if defined(PETSC_HAVE_HYPRE)
1359:   PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpibaij_hypre_C",NULL);
1360: #endif
1361:   return(0);
1362: }

1364: PetscErrorCode MatMult_MPIBAIJ(Mat A,Vec xx,Vec yy)
1365: {
1366:   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;
1368:   PetscInt       nt;

1371:   VecGetLocalSize(xx,&nt);
1372:   if (nt != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx");
1373:   VecGetLocalSize(yy,&nt);
1374:   if (nt != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible parition of A and yy");
1375:   VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
1376:   (*a->A->ops->mult)(a->A,xx,yy);
1377:   VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
1378:   (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);
1379:   return(0);
1380: }

1382: PetscErrorCode MatMultAdd_MPIBAIJ(Mat A,Vec xx,Vec yy,Vec zz)
1383: {
1384:   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;

1388:   VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
1389:   (*a->A->ops->multadd)(a->A,xx,yy,zz);
1390:   VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
1391:   (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);
1392:   return(0);
1393: }

1395: PetscErrorCode MatMultTranspose_MPIBAIJ(Mat A,Vec xx,Vec yy)
1396: {
1397:   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;
1399:   PetscBool      merged;

1402:   VecScatterGetMerged(a->Mvctx,&merged);
1403:   /* do nondiagonal part */
1404:   (*a->B->ops->multtranspose)(a->B,xx,a->lvec);
1405:   if (!merged) {
1406:     /* send it on its way */
1407:     VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
1408:     /* do local part */
1409:     (*a->A->ops->multtranspose)(a->A,xx,yy);
1410:     /* receive remote parts: note this assumes the values are not actually */
1411:     /* inserted in yy until the next line */
1412:     VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
1413:   } else {
1414:     /* do local part */
1415:     (*a->A->ops->multtranspose)(a->A,xx,yy);
1416:     /* send it on its way */
1417:     VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
1418:     /* values actually were received in the Begin() but we need to call this nop */
1419:     VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
1420:   }
1421:   return(0);
1422: }

1424: PetscErrorCode MatMultTransposeAdd_MPIBAIJ(Mat A,Vec xx,Vec yy,Vec zz)
1425: {
1426:   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;

1430:   /* do nondiagonal part */
1431:   (*a->B->ops->multtranspose)(a->B,xx,a->lvec);
1432:   /* send it on its way */
1433:   VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);
1434:   /* do local part */
1435:   (*a->A->ops->multtransposeadd)(a->A,xx,yy,zz);
1436:   /* receive remote parts: note this assumes the values are not actually */
1437:   /* inserted in yy until the next line, which is true for my implementation*/
1438:   /* but is not perhaps always true. */
1439:   VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);
1440:   return(0);
1441: }

1443: /*
1444:   This only works correctly for square matrices where the subblock A->A is the
1445:    diagonal block
1446: */
1447: PetscErrorCode MatGetDiagonal_MPIBAIJ(Mat A,Vec v)
1448: {
1449:   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;

1453:   if (A->rmap->N != A->cmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block");
1454:   MatGetDiagonal(a->A,v);
1455:   return(0);
1456: }

1458: PetscErrorCode MatScale_MPIBAIJ(Mat A,PetscScalar aa)
1459: {
1460:   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;

1464:   MatScale(a->A,aa);
1465:   MatScale(a->B,aa);
1466:   return(0);
1467: }

1469: PetscErrorCode MatGetRow_MPIBAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
1470: {
1471:   Mat_MPIBAIJ    *mat = (Mat_MPIBAIJ*)matin->data;
1472:   PetscScalar    *vworkA,*vworkB,**pvA,**pvB,*v_p;
1474:   PetscInt       bs = matin->rmap->bs,bs2 = mat->bs2,i,*cworkA,*cworkB,**pcA,**pcB;
1475:   PetscInt       nztot,nzA,nzB,lrow,brstart = matin->rmap->rstart,brend = matin->rmap->rend;
1476:   PetscInt       *cmap,*idx_p,cstart = mat->cstartbs;

1479:   if (row < brstart || row >= brend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local rows");
1480:   if (mat->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Already active");
1481:   mat->getrowactive = PETSC_TRUE;

1483:   if (!mat->rowvalues && (idx || v)) {
1484:     /*
1485:         allocate enough space to hold information from the longest row.
1486:     */
1487:     Mat_SeqBAIJ *Aa = (Mat_SeqBAIJ*)mat->A->data,*Ba = (Mat_SeqBAIJ*)mat->B->data;
1488:     PetscInt    max = 1,mbs = mat->mbs,tmp;
1489:     for (i=0; i<mbs; i++) {
1490:       tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i];
1491:       if (max < tmp) max = tmp;
1492:     }
1493:     PetscMalloc2(max*bs2,&mat->rowvalues,max*bs2,&mat->rowindices);
1494:   }
1495:   lrow = row - brstart;

1497:   pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB;
1498:   if (!v)   {pvA = 0; pvB = 0;}
1499:   if (!idx) {pcA = 0; if (!v) pcB = 0;}
1500:   (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);
1501:   (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);
1502:   nztot = nzA + nzB;

1504:   cmap = mat->garray;
1505:   if (v  || idx) {
1506:     if (nztot) {
1507:       /* Sort by increasing column numbers, assuming A and B already sorted */
1508:       PetscInt imark = -1;
1509:       if (v) {
1510:         *v = v_p = mat->rowvalues;
1511:         for (i=0; i<nzB; i++) {
1512:           if (cmap[cworkB[i]/bs] < cstart) v_p[i] = vworkB[i];
1513:           else break;
1514:         }
1515:         imark = i;
1516:         for (i=0; i<nzA; i++)     v_p[imark+i] = vworkA[i];
1517:         for (i=imark; i<nzB; i++) v_p[nzA+i]   = vworkB[i];
1518:       }
1519:       if (idx) {
1520:         *idx = idx_p = mat->rowindices;
1521:         if (imark > -1) {
1522:           for (i=0; i<imark; i++) {
1523:             idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs;
1524:           }
1525:         } else {
1526:           for (i=0; i<nzB; i++) {
1527:             if (cmap[cworkB[i]/bs] < cstart) idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs;
1528:             else break;
1529:           }
1530:           imark = i;
1531:         }
1532:         for (i=0; i<nzA; i++)     idx_p[imark+i] = cstart*bs + cworkA[i];
1533:         for (i=imark; i<nzB; i++) idx_p[nzA+i]   = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ;
1534:       }
1535:     } else {
1536:       if (idx) *idx = 0;
1537:       if (v)   *v   = 0;
1538:     }
1539:   }
1540:   *nz  = nztot;
1541:   (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);
1542:   (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);
1543:   return(0);
1544: }

1546: PetscErrorCode MatRestoreRow_MPIBAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
1547: {
1548:   Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data;

1551:   if (!baij->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"MatGetRow not called");
1552:   baij->getrowactive = PETSC_FALSE;
1553:   return(0);
1554: }

1556: PetscErrorCode MatZeroEntries_MPIBAIJ(Mat A)
1557: {
1558:   Mat_MPIBAIJ    *l = (Mat_MPIBAIJ*)A->data;

1562:   MatZeroEntries(l->A);
1563:   MatZeroEntries(l->B);
1564:   return(0);
1565: }

1567: PetscErrorCode MatGetInfo_MPIBAIJ(Mat matin,MatInfoType flag,MatInfo *info)
1568: {
1569:   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)matin->data;
1570:   Mat            A  = a->A,B = a->B;
1572:   PetscReal      isend[5],irecv[5];

1575:   info->block_size = (PetscReal)matin->rmap->bs;

1577:   MatGetInfo(A,MAT_LOCAL,info);

1579:   isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded;
1580:   isend[3] = info->memory;  isend[4] = info->mallocs;

1582:   MatGetInfo(B,MAT_LOCAL,info);

1584:   isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded;
1585:   isend[3] += info->memory;  isend[4] += info->mallocs;

1587:   if (flag == MAT_LOCAL) {
1588:     info->nz_used      = isend[0];
1589:     info->nz_allocated = isend[1];
1590:     info->nz_unneeded  = isend[2];
1591:     info->memory       = isend[3];
1592:     info->mallocs      = isend[4];
1593:   } else if (flag == MAT_GLOBAL_MAX) {
1594:     MPIU_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)matin));

1596:     info->nz_used      = irecv[0];
1597:     info->nz_allocated = irecv[1];
1598:     info->nz_unneeded  = irecv[2];
1599:     info->memory       = irecv[3];
1600:     info->mallocs      = irecv[4];
1601:   } else if (flag == MAT_GLOBAL_SUM) {
1602:     MPIU_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)matin));

1604:     info->nz_used      = irecv[0];
1605:     info->nz_allocated = irecv[1];
1606:     info->nz_unneeded  = irecv[2];
1607:     info->memory       = irecv[3];
1608:     info->mallocs      = irecv[4];
1609:   } else SETERRQ1(PetscObjectComm((PetscObject)matin),PETSC_ERR_ARG_WRONG,"Unknown MatInfoType argument %d",(int)flag);
1610:   info->fill_ratio_given  = 0; /* no parallel LU/ILU/Cholesky */
1611:   info->fill_ratio_needed = 0;
1612:   info->factor_mallocs    = 0;
1613:   return(0);
1614: }

1616: PetscErrorCode MatSetOption_MPIBAIJ(Mat A,MatOption op,PetscBool flg)
1617: {
1618:   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;

1622:   switch (op) {
1623:   case MAT_NEW_NONZERO_LOCATIONS:
1624:   case MAT_NEW_NONZERO_ALLOCATION_ERR:
1625:   case MAT_UNUSED_NONZERO_LOCATION_ERR:
1626:   case MAT_KEEP_NONZERO_PATTERN:
1627:   case MAT_NEW_NONZERO_LOCATION_ERR:
1628:     MatCheckPreallocated(A,1);
1629:     MatSetOption(a->A,op,flg);
1630:     MatSetOption(a->B,op,flg);
1631:     break;
1632:   case MAT_ROW_ORIENTED:
1633:     MatCheckPreallocated(A,1);
1634:     a->roworiented = flg;

1636:     MatSetOption(a->A,op,flg);
1637:     MatSetOption(a->B,op,flg);
1638:     break;
1639:   case MAT_NEW_DIAGONALS:
1640:     PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);
1641:     break;
1642:   case MAT_IGNORE_OFF_PROC_ENTRIES:
1643:     a->donotstash = flg;
1644:     break;
1645:   case MAT_USE_HASH_TABLE:
1646:     a->ht_flag = flg;
1647:     a->ht_fact = 1.39;
1648:     break;
1649:   case MAT_SYMMETRIC:
1650:   case MAT_STRUCTURALLY_SYMMETRIC:
1651:   case MAT_HERMITIAN:
1652:   case MAT_SUBMAT_SINGLEIS:
1653:   case MAT_SYMMETRY_ETERNAL:
1654:     MatCheckPreallocated(A,1);
1655:     MatSetOption(a->A,op,flg);
1656:     break;
1657:   default:
1658:     SETERRQ1(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"unknown option %d",op);
1659:   }
1660:   return(0);
1661: }

1663: PetscErrorCode MatTranspose_MPIBAIJ(Mat A,MatReuse reuse,Mat *matout)
1664: {
1665:   Mat_MPIBAIJ    *baij = (Mat_MPIBAIJ*)A->data;
1666:   Mat_SeqBAIJ    *Aloc;
1667:   Mat            B;
1669:   PetscInt       M =A->rmap->N,N=A->cmap->N,*ai,*aj,i,*rvals,j,k,col;
1670:   PetscInt       bs=A->rmap->bs,mbs=baij->mbs;
1671:   MatScalar      *a;

1674:   if (reuse == MAT_INPLACE_MATRIX && M != N) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_SIZ,"Square matrix only for in-place");
1675:   if (reuse == MAT_INITIAL_MATRIX || reuse == MAT_INPLACE_MATRIX) {
1676:     MatCreate(PetscObjectComm((PetscObject)A),&B);
1677:     MatSetSizes(B,A->cmap->n,A->rmap->n,N,M);
1678:     MatSetType(B,((PetscObject)A)->type_name);
1679:     /* Do not know preallocation information, but must set block size */
1680:     MatMPIBAIJSetPreallocation(B,A->rmap->bs,PETSC_DECIDE,NULL,PETSC_DECIDE,NULL);
1681:   } else {
1682:     B = *matout;
1683:   }

1685:   /* copy over the A part */
1686:   Aloc = (Mat_SeqBAIJ*)baij->A->data;
1687:   ai   = Aloc->i; aj = Aloc->j; a = Aloc->a;
1688:   PetscMalloc1(bs,&rvals);

1690:   for (i=0; i<mbs; i++) {
1691:     rvals[0] = bs*(baij->rstartbs + i);
1692:     for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1;
1693:     for (j=ai[i]; j<ai[i+1]; j++) {
1694:       col = (baij->cstartbs+aj[j])*bs;
1695:       for (k=0; k<bs; k++) {
1696:         MatSetValues_MPIBAIJ(B,1,&col,bs,rvals,a,INSERT_VALUES);

1698:         col++; a += bs;
1699:       }
1700:     }
1701:   }
1702:   /* copy over the B part */
1703:   Aloc = (Mat_SeqBAIJ*)baij->B->data;
1704:   ai   = Aloc->i; aj = Aloc->j; a = Aloc->a;
1705:   for (i=0; i<mbs; i++) {
1706:     rvals[0] = bs*(baij->rstartbs + i);
1707:     for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1;
1708:     for (j=ai[i]; j<ai[i+1]; j++) {
1709:       col = baij->garray[aj[j]]*bs;
1710:       for (k=0; k<bs; k++) {
1711:         MatSetValues_MPIBAIJ(B,1,&col,bs,rvals,a,INSERT_VALUES);
1712:         col++;
1713:         a += bs;
1714:       }
1715:     }
1716:   }
1717:   PetscFree(rvals);
1718:   MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
1719:   MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);

1721:   if (reuse == MAT_INITIAL_MATRIX || reuse == MAT_REUSE_MATRIX) *matout = B;
1722:   else {
1723:     MatHeaderMerge(A,&B);
1724:   }
1725:   return(0);
1726: }

1728: PetscErrorCode MatDiagonalScale_MPIBAIJ(Mat mat,Vec ll,Vec rr)
1729: {
1730:   Mat_MPIBAIJ    *baij = (Mat_MPIBAIJ*)mat->data;
1731:   Mat            a     = baij->A,b = baij->B;
1733:   PetscInt       s1,s2,s3;

1736:   MatGetLocalSize(mat,&s2,&s3);
1737:   if (rr) {
1738:     VecGetLocalSize(rr,&s1);
1739:     if (s1!=s3) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"right vector non-conforming local size");
1740:     /* Overlap communication with computation. */
1741:     VecScatterBegin(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);
1742:   }
1743:   if (ll) {
1744:     VecGetLocalSize(ll,&s1);
1745:     if (s1!=s2) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"left vector non-conforming local size");
1746:     (*b->ops->diagonalscale)(b,ll,NULL);
1747:   }
1748:   /* scale  the diagonal block */
1749:   (*a->ops->diagonalscale)(a,ll,rr);

1751:   if (rr) {
1752:     /* Do a scatter end and then right scale the off-diagonal block */
1753:     VecScatterEnd(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);
1754:     (*b->ops->diagonalscale)(b,NULL,baij->lvec);
1755:   }
1756:   return(0);
1757: }

1759: PetscErrorCode MatZeroRows_MPIBAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b)
1760: {
1761:   Mat_MPIBAIJ   *l      = (Mat_MPIBAIJ *) A->data;
1762:   PetscInt      *lrows;
1763:   PetscInt       r, len;

1767:   /* get locally owned rows */
1768:   MatZeroRowsMapLocal_Private(A,N,rows,&len,&lrows);
1769:   /* fix right hand side if needed */
1770:   if (x && b) {
1771:     const PetscScalar *xx;
1772:     PetscScalar       *bb;

1774:     VecGetArrayRead(x,&xx);
1775:     VecGetArray(b,&bb);
1776:     for (r = 0; r < len; ++r) bb[lrows[r]] = diag*xx[lrows[r]];
1777:     VecRestoreArrayRead(x,&xx);
1778:     VecRestoreArray(b,&bb);
1779:   }

1781:   /* actually zap the local rows */
1782:   /*
1783:         Zero the required rows. If the "diagonal block" of the matrix
1784:      is square and the user wishes to set the diagonal we use separate
1785:      code so that MatSetValues() is not called for each diagonal allocating
1786:      new memory, thus calling lots of mallocs and slowing things down.

1788:   */
1789:   /* must zero l->B before l->A because the (diag) case below may put values into l->B*/
1790:   MatZeroRows_SeqBAIJ(l->B,len,lrows,0.0,NULL,NULL);
1791:   if (A->congruentlayouts == -1) { /* first time we compare rows and cols layouts */
1792:     PetscBool cong;
1793:     PetscLayoutCompare(A->rmap,A->cmap,&cong);
1794:     if (cong) A->congruentlayouts = 1;
1795:     else      A->congruentlayouts = 0;
1796:   }
1797:   if ((diag != 0.0) && A->congruentlayouts) {
1798:     MatZeroRows_SeqBAIJ(l->A,len,lrows,diag,NULL,NULL);
1799:   } else if (diag != 0.0) {
1800:     MatZeroRows_SeqBAIJ(l->A,len,lrows,0.0,0,0);
1801:     if (((Mat_SeqBAIJ*)l->A->data)->nonew) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"MatZeroRows() on rectangular matrices cannot be used with the Mat options \n\
1802:        MAT_NEW_NONZERO_LOCATIONS,MAT_NEW_NONZERO_LOCATION_ERR,MAT_NEW_NONZERO_ALLOCATION_ERR");
1803:     for (r = 0; r < len; ++r) {
1804:       const PetscInt row = lrows[r] + A->rmap->rstart;
1805:       MatSetValues(A,1,&row,1,&row,&diag,INSERT_VALUES);
1806:     }
1807:     MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);
1808:     MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);
1809:   } else {
1810:     MatZeroRows_SeqBAIJ(l->A,len,lrows,0.0,NULL,NULL);
1811:   }
1812:   PetscFree(lrows);

1814:   /* only change matrix nonzero state if pattern was allowed to be changed */
1815:   if (!((Mat_SeqBAIJ*)(l->A->data))->keepnonzeropattern) {
1816:     PetscObjectState state = l->A->nonzerostate + l->B->nonzerostate;
1817:     MPIU_Allreduce(&state,&A->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)A));
1818:   }
1819:   return(0);
1820: }

1822: PetscErrorCode MatZeroRowsColumns_MPIBAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b)
1823: {
1824:   Mat_MPIBAIJ       *l = (Mat_MPIBAIJ*)A->data;
1825:   PetscErrorCode    ierr;
1826:   PetscMPIInt       n = A->rmap->n;
1827:   PetscInt          i,j,k,r,p = 0,len = 0,row,col,count;
1828:   PetscInt          *lrows,*owners = A->rmap->range;
1829:   PetscSFNode       *rrows;
1830:   PetscSF           sf;
1831:   const PetscScalar *xx;
1832:   PetscScalar       *bb,*mask;
1833:   Vec               xmask,lmask;
1834:   Mat_SeqBAIJ       *baij = (Mat_SeqBAIJ*)l->B->data;
1835:   PetscInt           bs = A->rmap->bs, bs2 = baij->bs2;
1836:   PetscScalar       *aa;

1839:   /* Create SF where leaves are input rows and roots are owned rows */
1840:   PetscMalloc1(n, &lrows);
1841:   for (r = 0; r < n; ++r) lrows[r] = -1;
1842:   PetscMalloc1(N, &rrows);
1843:   for (r = 0; r < N; ++r) {
1844:     const PetscInt idx   = rows[r];
1845:     if (idx < 0 || A->rmap->N <= idx) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row %D out of range [0,%D)",idx,A->rmap->N);
1846:     if (idx < owners[p] || owners[p+1] <= idx) { /* short-circuit the search if the last p owns this row too */
1847:       PetscLayoutFindOwner(A->rmap,idx,&p);
1848:     }
1849:     rrows[r].rank  = p;
1850:     rrows[r].index = rows[r] - owners[p];
1851:   }
1852:   PetscSFCreate(PetscObjectComm((PetscObject) A), &sf);
1853:   PetscSFSetGraph(sf, n, N, NULL, PETSC_OWN_POINTER, rrows, PETSC_OWN_POINTER);
1854:   /* Collect flags for rows to be zeroed */
1855:   PetscSFReduceBegin(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);
1856:   PetscSFReduceEnd(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);
1857:   PetscSFDestroy(&sf);
1858:   /* Compress and put in row numbers */
1859:   for (r = 0; r < n; ++r) if (lrows[r] >= 0) lrows[len++] = r;
1860:   /* zero diagonal part of matrix */
1861:   MatZeroRowsColumns(l->A,len,lrows,diag,x,b);
1862:   /* handle off diagonal part of matrix */
1863:   MatCreateVecs(A,&xmask,NULL);
1864:   VecDuplicate(l->lvec,&lmask);
1865:   VecGetArray(xmask,&bb);
1866:   for (i=0; i<len; i++) bb[lrows[i]] = 1;
1867:   VecRestoreArray(xmask,&bb);
1868:   VecScatterBegin(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);
1869:   VecScatterEnd(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);
1870:   VecDestroy(&xmask);
1871:   if (x) {
1872:     VecScatterBegin(l->Mvctx,x,l->lvec,INSERT_VALUES,SCATTER_FORWARD);
1873:     VecScatterEnd(l->Mvctx,x,l->lvec,INSERT_VALUES,SCATTER_FORWARD);
1874:     VecGetArrayRead(l->lvec,&xx);
1875:     VecGetArray(b,&bb);
1876:   }
1877:   VecGetArray(lmask,&mask);
1878:   /* remove zeroed rows of off diagonal matrix */
1879:   for (i = 0; i < len; ++i) {
1880:     row   = lrows[i];
1881:     count = (baij->i[row/bs +1] - baij->i[row/bs])*bs;
1882:     aa    = ((MatScalar*)(baij->a)) + baij->i[row/bs]*bs2 + (row%bs);
1883:     for (k = 0; k < count; ++k) {
1884:       aa[0] = 0.0;
1885:       aa   += bs;
1886:     }
1887:   }
1888:   /* loop over all elements of off process part of matrix zeroing removed columns*/
1889:   for (i = 0; i < l->B->rmap->N; ++i) {
1890:     row = i/bs;
1891:     for (j = baij->i[row]; j < baij->i[row+1]; ++j) {
1892:       for (k = 0; k < bs; ++k) {
1893:         col = bs*baij->j[j] + k;
1894:         if (PetscAbsScalar(mask[col])) {
1895:           aa = ((MatScalar*)(baij->a)) + j*bs2 + (i%bs) + bs*k;
1896:           if (x) bb[i] -= aa[0]*xx[col];
1897:           aa[0] = 0.0;
1898:         }
1899:       }
1900:     }
1901:   }
1902:   if (x) {
1903:     VecRestoreArray(b,&bb);
1904:     VecRestoreArrayRead(l->lvec,&xx);
1905:   }
1906:   VecRestoreArray(lmask,&mask);
1907:   VecDestroy(&lmask);
1908:   PetscFree(lrows);

1910:   /* only change matrix nonzero state if pattern was allowed to be changed */
1911:   if (!((Mat_SeqBAIJ*)(l->A->data))->keepnonzeropattern) {
1912:     PetscObjectState state = l->A->nonzerostate + l->B->nonzerostate;
1913:     MPIU_Allreduce(&state,&A->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)A));
1914:   }
1915:   return(0);
1916: }

1918: PetscErrorCode MatSetUnfactored_MPIBAIJ(Mat A)
1919: {
1920:   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;

1924:   MatSetUnfactored(a->A);
1925:   return(0);
1926: }

1928: static PetscErrorCode MatDuplicate_MPIBAIJ(Mat,MatDuplicateOption,Mat*);

1930: PetscErrorCode MatEqual_MPIBAIJ(Mat A,Mat B,PetscBool  *flag)
1931: {
1932:   Mat_MPIBAIJ    *matB = (Mat_MPIBAIJ*)B->data,*matA = (Mat_MPIBAIJ*)A->data;
1933:   Mat            a,b,c,d;
1934:   PetscBool      flg;

1938:   a = matA->A; b = matA->B;
1939:   c = matB->A; d = matB->B;

1941:   MatEqual(a,c,&flg);
1942:   if (flg) {
1943:     MatEqual(b,d,&flg);
1944:   }
1945:   MPIU_Allreduce(&flg,flag,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)A));
1946:   return(0);
1947: }

1949: PetscErrorCode MatCopy_MPIBAIJ(Mat A,Mat B,MatStructure str)
1950: {
1952:   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;
1953:   Mat_MPIBAIJ    *b = (Mat_MPIBAIJ*)B->data;

1956:   /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */
1957:   if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) {
1958:     MatCopy_Basic(A,B,str);
1959:   } else {
1960:     MatCopy(a->A,b->A,str);
1961:     MatCopy(a->B,b->B,str);
1962:   }
1963:   PetscObjectStateIncrease((PetscObject)B);
1964:   return(0);
1965: }

1967: PetscErrorCode MatSetUp_MPIBAIJ(Mat A)
1968: {

1972:   MatMPIBAIJSetPreallocation(A,A->rmap->bs,PETSC_DEFAULT,0,PETSC_DEFAULT,0);
1973:   return(0);
1974: }

1976: PetscErrorCode MatAXPYGetPreallocation_MPIBAIJ(Mat Y,const PetscInt *yltog,Mat X,const PetscInt *xltog,PetscInt *nnz)
1977: {
1979:   PetscInt       bs = Y->rmap->bs,m = Y->rmap->N/bs;
1980:   Mat_SeqBAIJ    *x = (Mat_SeqBAIJ*)X->data;
1981:   Mat_SeqBAIJ    *y = (Mat_SeqBAIJ*)Y->data;

1984:   MatAXPYGetPreallocation_MPIX_private(m,x->i,x->j,xltog,y->i,y->j,yltog,nnz);
1985:   return(0);
1986: }

1988: PetscErrorCode MatAXPY_MPIBAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str)
1989: {
1991:   Mat_MPIBAIJ    *xx=(Mat_MPIBAIJ*)X->data,*yy=(Mat_MPIBAIJ*)Y->data;
1992:   PetscBLASInt   bnz,one=1;
1993:   Mat_SeqBAIJ    *x,*y;
1994:   PetscInt       bs2 = Y->rmap->bs*Y->rmap->bs;

1997:   if (str == SAME_NONZERO_PATTERN) {
1998:     PetscScalar alpha = a;
1999:     x    = (Mat_SeqBAIJ*)xx->A->data;
2000:     y    = (Mat_SeqBAIJ*)yy->A->data;
2001:     PetscBLASIntCast(x->nz*bs2,&bnz);
2002:     PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one));
2003:     x    = (Mat_SeqBAIJ*)xx->B->data;
2004:     y    = (Mat_SeqBAIJ*)yy->B->data;
2005:     PetscBLASIntCast(x->nz*bs2,&bnz);
2006:     PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one));
2007:     PetscObjectStateIncrease((PetscObject)Y);
2008:   } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */
2009:     MatAXPY_Basic(Y,a,X,str);
2010:   } else {
2011:     Mat      B;
2012:     PetscInt *nnz_d,*nnz_o,bs=Y->rmap->bs;
2013:     PetscMalloc1(yy->A->rmap->N,&nnz_d);
2014:     PetscMalloc1(yy->B->rmap->N,&nnz_o);
2015:     MatCreate(PetscObjectComm((PetscObject)Y),&B);
2016:     PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);
2017:     MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);
2018:     MatSetBlockSizesFromMats(B,Y,Y);
2019:     MatSetType(B,MATMPIBAIJ);
2020:     MatAXPYGetPreallocation_SeqBAIJ(yy->A,xx->A,nnz_d);
2021:     MatAXPYGetPreallocation_MPIBAIJ(yy->B,yy->garray,xx->B,xx->garray,nnz_o);
2022:     MatMPIBAIJSetPreallocation(B,bs,0,nnz_d,0,nnz_o);
2023:     /* MatAXPY_BasicWithPreallocation() for BAIJ matrix is much slower than AIJ, even for bs=1 ! */
2024:     MatAXPY_BasicWithPreallocation(B,Y,a,X,str);
2025:     MatHeaderReplace(Y,&B);
2026:     PetscFree(nnz_d);
2027:     PetscFree(nnz_o);
2028:   }
2029:   return(0);
2030: }

2032: PetscErrorCode MatRealPart_MPIBAIJ(Mat A)
2033: {
2034:   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;

2038:   MatRealPart(a->A);
2039:   MatRealPart(a->B);
2040:   return(0);
2041: }

2043: PetscErrorCode MatImaginaryPart_MPIBAIJ(Mat A)
2044: {
2045:   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;

2049:   MatImaginaryPart(a->A);
2050:   MatImaginaryPart(a->B);
2051:   return(0);
2052: }

2054: PetscErrorCode MatCreateSubMatrix_MPIBAIJ(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat)
2055: {
2057:   IS             iscol_local;
2058:   PetscInt       csize;

2061:   ISGetLocalSize(iscol,&csize);
2062:   if (call == MAT_REUSE_MATRIX) {
2063:     PetscObjectQuery((PetscObject)*newmat,"ISAllGather",(PetscObject*)&iscol_local);
2064:     if (!iscol_local) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse");
2065:   } else {
2066:     ISAllGather(iscol,&iscol_local);
2067:   }
2068:   MatCreateSubMatrix_MPIBAIJ_Private(mat,isrow,iscol_local,csize,call,newmat);
2069:   if (call == MAT_INITIAL_MATRIX) {
2070:     PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);
2071:     ISDestroy(&iscol_local);
2072:   }
2073:   return(0);
2074: }

2076: /*
2077:   Not great since it makes two copies of the submatrix, first an SeqBAIJ
2078:   in local and then by concatenating the local matrices the end result.
2079:   Writing it directly would be much like MatCreateSubMatrices_MPIBAIJ().
2080:   This routine is used for BAIJ and SBAIJ matrices (unfortunate dependency).
2081: */
2082: PetscErrorCode MatCreateSubMatrix_MPIBAIJ_Private(Mat mat,IS isrow,IS iscol,PetscInt csize,MatReuse call,Mat *newmat)
2083: {
2085:   PetscMPIInt    rank,size;
2086:   PetscInt       i,m,n,rstart,row,rend,nz,*cwork,j,bs;
2087:   PetscInt       *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal;
2088:   Mat            M,Mreuse;
2089:   MatScalar      *vwork,*aa;
2090:   MPI_Comm       comm;
2091:   IS             isrow_new, iscol_new;
2092:   Mat_SeqBAIJ    *aij;

2095:   PetscObjectGetComm((PetscObject)mat,&comm);
2096:   MPI_Comm_rank(comm,&rank);
2097:   MPI_Comm_size(comm,&size);
2098:   /* The compression and expansion should be avoided. Doesn't point
2099:      out errors, might change the indices, hence buggey */
2100:   ISCompressIndicesGeneral(mat->rmap->N,mat->rmap->n,mat->rmap->bs,1,&isrow,&isrow_new);
2101:   ISCompressIndicesGeneral(mat->cmap->N,mat->cmap->n,mat->cmap->bs,1,&iscol,&iscol_new);

2103:   if (call ==  MAT_REUSE_MATRIX) {
2104:     PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject*)&Mreuse);
2105:     if (!Mreuse) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse");
2106:     MatCreateSubMatrices_MPIBAIJ_local(mat,1,&isrow_new,&iscol_new,MAT_REUSE_MATRIX,&Mreuse);
2107:   } else {
2108:     MatCreateSubMatrices_MPIBAIJ_local(mat,1,&isrow_new,&iscol_new,MAT_INITIAL_MATRIX,&Mreuse);
2109:   }
2110:   ISDestroy(&isrow_new);
2111:   ISDestroy(&iscol_new);
2112:   /*
2113:       m - number of local rows
2114:       n - number of columns (same on all processors)
2115:       rstart - first row in new global matrix generated
2116:   */
2117:   MatGetBlockSize(mat,&bs);
2118:   MatGetSize(Mreuse,&m,&n);
2119:   m    = m/bs;
2120:   n    = n/bs;

2122:   if (call == MAT_INITIAL_MATRIX) {
2123:     aij = (Mat_SeqBAIJ*)(Mreuse)->data;
2124:     ii  = aij->i;
2125:     jj  = aij->j;

2127:     /*
2128:         Determine the number of non-zeros in the diagonal and off-diagonal
2129:         portions of the matrix in order to do correct preallocation
2130:     */

2132:     /* first get start and end of "diagonal" columns */
2133:     if (csize == PETSC_DECIDE) {
2134:       ISGetSize(isrow,&mglobal);
2135:       if (mglobal == n*bs) { /* square matrix */
2136:         nlocal = m;
2137:       } else {
2138:         nlocal = n/size + ((n % size) > rank);
2139:       }
2140:     } else {
2141:       nlocal = csize/bs;
2142:     }
2143:     MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);
2144:     rstart = rend - nlocal;
2145:     if (rank == size - 1 && rend != n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Local column sizes %D do not add up to total number of columns %D",rend,n);

2147:     /* next, compute all the lengths */
2148:     PetscMalloc2(m+1,&dlens,m+1,&olens);
2149:     for (i=0; i<m; i++) {
2150:       jend = ii[i+1] - ii[i];
2151:       olen = 0;
2152:       dlen = 0;
2153:       for (j=0; j<jend; j++) {
2154:         if (*jj < rstart || *jj >= rend) olen++;
2155:         else dlen++;
2156:         jj++;
2157:       }
2158:       olens[i] = olen;
2159:       dlens[i] = dlen;
2160:     }
2161:     MatCreate(comm,&M);
2162:     MatSetSizes(M,bs*m,bs*nlocal,PETSC_DECIDE,bs*n);
2163:     MatSetType(M,((PetscObject)mat)->type_name);
2164:     MatMPIBAIJSetPreallocation(M,bs,0,dlens,0,olens);
2165:     MatMPISBAIJSetPreallocation(M,bs,0,dlens,0,olens);
2166:     PetscFree2(dlens,olens);
2167:   } else {
2168:     PetscInt ml,nl;

2170:     M    = *newmat;
2171:     MatGetLocalSize(M,&ml,&nl);
2172:     if (ml != m) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request");
2173:     MatZeroEntries(M);
2174:     /*
2175:          The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly,
2176:        rather than the slower MatSetValues().
2177:     */
2178:     M->was_assembled = PETSC_TRUE;
2179:     M->assembled     = PETSC_FALSE;
2180:   }
2181:   MatSetOption(M,MAT_ROW_ORIENTED,PETSC_FALSE);
2182:   MatGetOwnershipRange(M,&rstart,&rend);
2183:   aij  = (Mat_SeqBAIJ*)(Mreuse)->data;
2184:   ii   = aij->i;
2185:   jj   = aij->j;
2186:   aa   = aij->a;
2187:   for (i=0; i<m; i++) {
2188:     row   = rstart/bs + i;
2189:     nz    = ii[i+1] - ii[i];
2190:     cwork = jj;     jj += nz;
2191:     vwork = aa;     aa += nz*bs*bs;
2192:     MatSetValuesBlocked_MPIBAIJ(M,1,&row,nz,cwork,vwork,INSERT_VALUES);
2193:   }

2195:   MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);
2196:   MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);
2197:   *newmat = M;

2199:   /* save submatrix used in processor for next request */
2200:   if (call ==  MAT_INITIAL_MATRIX) {
2201:     PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Mreuse);
2202:     PetscObjectDereference((PetscObject)Mreuse);
2203:   }
2204:   return(0);
2205: }

2207: PetscErrorCode MatPermute_MPIBAIJ(Mat A,IS rowp,IS colp,Mat *B)
2208: {
2209:   MPI_Comm       comm,pcomm;
2210:   PetscInt       clocal_size,nrows;
2211:   const PetscInt *rows;
2212:   PetscMPIInt    size;
2213:   IS             crowp,lcolp;

2217:   PetscObjectGetComm((PetscObject)A,&comm);
2218:   /* make a collective version of 'rowp' */
2219:   PetscObjectGetComm((PetscObject)rowp,&pcomm);
2220:   if (pcomm==comm) {
2221:     crowp = rowp;
2222:   } else {
2223:     ISGetSize(rowp,&nrows);
2224:     ISGetIndices(rowp,&rows);
2225:     ISCreateGeneral(comm,nrows,rows,PETSC_COPY_VALUES,&crowp);
2226:     ISRestoreIndices(rowp,&rows);
2227:   }
2228:   ISSetPermutation(crowp);
2229:   /* make a local version of 'colp' */
2230:   PetscObjectGetComm((PetscObject)colp,&pcomm);
2231:   MPI_Comm_size(pcomm,&size);
2232:   if (size==1) {
2233:     lcolp = colp;
2234:   } else {
2235:     ISAllGather(colp,&lcolp);
2236:   }
2237:   ISSetPermutation(lcolp);
2238:   /* now we just get the submatrix */
2239:   MatGetLocalSize(A,NULL,&clocal_size);
2240:   MatCreateSubMatrix_MPIBAIJ_Private(A,crowp,lcolp,clocal_size,MAT_INITIAL_MATRIX,B);
2241:   /* clean up */
2242:   if (pcomm!=comm) {
2243:     ISDestroy(&crowp);
2244:   }
2245:   if (size>1) {
2246:     ISDestroy(&lcolp);
2247:   }
2248:   return(0);
2249: }

2251: PetscErrorCode  MatGetGhosts_MPIBAIJ(Mat mat,PetscInt *nghosts,const PetscInt *ghosts[])
2252: {
2253:   Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*) mat->data;
2254:   Mat_SeqBAIJ *B    = (Mat_SeqBAIJ*)baij->B->data;

2257:   if (nghosts) *nghosts = B->nbs;
2258:   if (ghosts) *ghosts = baij->garray;
2259:   return(0);
2260: }

2262: PetscErrorCode MatGetSeqNonzeroStructure_MPIBAIJ(Mat A,Mat *newmat)
2263: {
2264:   Mat            B;
2265:   Mat_MPIBAIJ    *a  = (Mat_MPIBAIJ*)A->data;
2266:   Mat_SeqBAIJ    *ad = (Mat_SeqBAIJ*)a->A->data,*bd = (Mat_SeqBAIJ*)a->B->data;
2267:   Mat_SeqAIJ     *b;
2269:   PetscMPIInt    size,rank,*recvcounts = 0,*displs = 0;
2270:   PetscInt       sendcount,i,*rstarts = A->rmap->range,n,cnt,j,bs = A->rmap->bs;
2271:   PetscInt       m,*garray = a->garray,*lens,*jsendbuf,*a_jsendbuf,*b_jsendbuf;

2274:   MPI_Comm_size(PetscObjectComm((PetscObject)A),&size);
2275:   MPI_Comm_rank(PetscObjectComm((PetscObject)A),&rank);

2277:   /* ----------------------------------------------------------------
2278:      Tell every processor the number of nonzeros per row
2279:   */
2280:   PetscMalloc1(A->rmap->N/bs,&lens);
2281:   for (i=A->rmap->rstart/bs; i<A->rmap->rend/bs; i++) {
2282:     lens[i] = ad->i[i-A->rmap->rstart/bs+1] - ad->i[i-A->rmap->rstart/bs] + bd->i[i-A->rmap->rstart/bs+1] - bd->i[i-A->rmap->rstart/bs];
2283:   }
2284:   PetscMalloc1(2*size,&recvcounts);
2285:   displs    = recvcounts + size;
2286:   for (i=0; i<size; i++) {
2287:     recvcounts[i] = A->rmap->range[i+1]/bs - A->rmap->range[i]/bs;
2288:     displs[i]     = A->rmap->range[i]/bs;
2289:   }
2290: #if defined(PETSC_HAVE_MPI_IN_PLACE)
2291:   MPI_Allgatherv(MPI_IN_PLACE,0,MPI_DATATYPE_NULL,lens,recvcounts,displs,MPIU_INT,PetscObjectComm((PetscObject)A));
2292: #else
2293:   sendcount = A->rmap->rend/bs - A->rmap->rstart/bs;
2294:   MPI_Allgatherv(lens+A->rmap->rstart/bs,sendcount,MPIU_INT,lens,recvcounts,displs,MPIU_INT,PetscObjectComm((PetscObject)A));
2295: #endif
2296:   /* ---------------------------------------------------------------
2297:      Create the sequential matrix of the same type as the local block diagonal
2298:   */
2299:   MatCreate(PETSC_COMM_SELF,&B);
2300:   MatSetSizes(B,A->rmap->N/bs,A->cmap->N/bs,PETSC_DETERMINE,PETSC_DETERMINE);
2301:   MatSetType(B,MATSEQAIJ);
2302:   MatSeqAIJSetPreallocation(B,0,lens);
2303:   b    = (Mat_SeqAIJ*)B->data;

2305:   /*--------------------------------------------------------------------
2306:     Copy my part of matrix column indices over
2307:   */
2308:   sendcount  = ad->nz + bd->nz;
2309:   jsendbuf   = b->j + b->i[rstarts[rank]/bs];
2310:   a_jsendbuf = ad->j;
2311:   b_jsendbuf = bd->j;
2312:   n          = A->rmap->rend/bs - A->rmap->rstart/bs;
2313:   cnt        = 0;
2314:   for (i=0; i<n; i++) {

2316:     /* put in lower diagonal portion */
2317:     m = bd->i[i+1] - bd->i[i];
2318:     while (m > 0) {
2319:       /* is it above diagonal (in bd (compressed) numbering) */
2320:       if (garray[*b_jsendbuf] > A->rmap->rstart/bs + i) break;
2321:       jsendbuf[cnt++] = garray[*b_jsendbuf++];
2322:       m--;
2323:     }

2325:     /* put in diagonal portion */
2326:     for (j=ad->i[i]; j<ad->i[i+1]; j++) {
2327:       jsendbuf[cnt++] = A->rmap->rstart/bs + *a_jsendbuf++;
2328:     }

2330:     /* put in upper diagonal portion */
2331:     while (m-- > 0) {
2332:       jsendbuf[cnt++] = garray[*b_jsendbuf++];
2333:     }
2334:   }
2335:   if (cnt != sendcount) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Corrupted PETSc matrix: nz given %D actual nz %D",sendcount,cnt);

2337:   /*--------------------------------------------------------------------
2338:     Gather all column indices to all processors
2339:   */
2340:   for (i=0; i<size; i++) {
2341:     recvcounts[i] = 0;
2342:     for (j=A->rmap->range[i]/bs; j<A->rmap->range[i+1]/bs; j++) {
2343:       recvcounts[i] += lens[j];
2344:     }
2345:   }
2346:   displs[0] = 0;
2347:   for (i=1; i<size; i++) {
2348:     displs[i] = displs[i-1] + recvcounts[i-1];
2349:   }
2350: #if defined(PETSC_HAVE_MPI_IN_PLACE)
2351:   MPI_Allgatherv(MPI_IN_PLACE,0,MPI_DATATYPE_NULL,b->j,recvcounts,displs,MPIU_INT,PetscObjectComm((PetscObject)A));
2352: #else
2353:   MPI_Allgatherv(jsendbuf,sendcount,MPIU_INT,b->j,recvcounts,displs,MPIU_INT,PetscObjectComm((PetscObject)A));
2354: #endif
2355:   /*--------------------------------------------------------------------
2356:     Assemble the matrix into useable form (note numerical values not yet set)
2357:   */
2358:   /* set the b->ilen (length of each row) values */
2359:   PetscMemcpy(b->ilen,lens,(A->rmap->N/bs)*sizeof(PetscInt));
2360:   /* set the b->i indices */
2361:   b->i[0] = 0;
2362:   for (i=1; i<=A->rmap->N/bs; i++) {
2363:     b->i[i] = b->i[i-1] + lens[i-1];
2364:   }
2365:   PetscFree(lens);
2366:   MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
2367:   MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);
2368:   PetscFree(recvcounts);

2370:   if (A->symmetric) {
2371:     MatSetOption(B,MAT_SYMMETRIC,PETSC_TRUE);
2372:   } else if (A->hermitian) {
2373:     MatSetOption(B,MAT_HERMITIAN,PETSC_TRUE);
2374:   } else if (A->structurally_symmetric) {
2375:     MatSetOption(B,MAT_STRUCTURALLY_SYMMETRIC,PETSC_TRUE);
2376:   }
2377:   *newmat = B;
2378:   return(0);
2379: }

2381: PetscErrorCode MatSOR_MPIBAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx)
2382: {
2383:   Mat_MPIBAIJ    *mat = (Mat_MPIBAIJ*)matin->data;
2385:   Vec            bb1 = 0;

2388:   if (flag == SOR_APPLY_UPPER) {
2389:     (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
2390:     return(0);
2391:   }

2393:   if (its > 1 || ~flag & SOR_ZERO_INITIAL_GUESS) {
2394:     VecDuplicate(bb,&bb1);
2395:   }

2397:   if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) {
2398:     if (flag & SOR_ZERO_INITIAL_GUESS) {
2399:       (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
2400:       its--;
2401:     }

2403:     while (its--) {
2404:       VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
2405:       VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);

2407:       /* update rhs: bb1 = bb - B*x */
2408:       VecScale(mat->lvec,-1.0);
2409:       (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);

2411:       /* local sweep */
2412:       (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,1,xx);
2413:     }
2414:   } else if (flag & SOR_LOCAL_FORWARD_SWEEP) {
2415:     if (flag & SOR_ZERO_INITIAL_GUESS) {
2416:       (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
2417:       its--;
2418:     }
2419:     while (its--) {
2420:       VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
2421:       VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);

2423:       /* update rhs: bb1 = bb - B*x */
2424:       VecScale(mat->lvec,-1.0);
2425:       (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);

2427:       /* local sweep */
2428:       (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_FORWARD_SWEEP,fshift,lits,1,xx);
2429:     }
2430:   } else if (flag & SOR_LOCAL_BACKWARD_SWEEP) {
2431:     if (flag & SOR_ZERO_INITIAL_GUESS) {
2432:       (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
2433:       its--;
2434:     }
2435:     while (its--) {
2436:       VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
2437:       VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);

2439:       /* update rhs: bb1 = bb - B*x */
2440:       VecScale(mat->lvec,-1.0);
2441:       (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);

2443:       /* local sweep */
2444:       (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_BACKWARD_SWEEP,fshift,lits,1,xx);
2445:     }
2446:   } else SETERRQ(PetscObjectComm((PetscObject)matin),PETSC_ERR_SUP,"Parallel version of SOR requested not supported");

2448:   VecDestroy(&bb1);
2449:   return(0);
2450: }

2452: PetscErrorCode MatGetColumnNorms_MPIBAIJ(Mat A,NormType type,PetscReal *norms)
2453: {
2455:   Mat_MPIBAIJ    *aij = (Mat_MPIBAIJ*)A->data;
2456:   PetscInt       N,i,*garray = aij->garray;
2457:   PetscInt       ib,jb,bs = A->rmap->bs;
2458:   Mat_SeqBAIJ    *a_aij = (Mat_SeqBAIJ*) aij->A->data;
2459:   MatScalar      *a_val = a_aij->a;
2460:   Mat_SeqBAIJ    *b_aij = (Mat_SeqBAIJ*) aij->B->data;
2461:   MatScalar      *b_val = b_aij->a;
2462:   PetscReal      *work;

2465:   MatGetSize(A,NULL,&N);
2466:   PetscCalloc1(N,&work);
2467:   if (type == NORM_2) {
2468:     for (i=a_aij->i[0]; i<a_aij->i[aij->A->rmap->n/bs]; i++) {
2469:       for (jb=0; jb<bs; jb++) {
2470:         for (ib=0; ib<bs; ib++) {
2471:           work[A->cmap->rstart + a_aij->j[i] * bs + jb] += PetscAbsScalar(*a_val * *a_val);
2472:           a_val++;
2473:         }
2474:       }
2475:     }
2476:     for (i=b_aij->i[0]; i<b_aij->i[aij->B->rmap->n/bs]; i++) {
2477:       for (jb=0; jb<bs; jb++) {
2478:         for (ib=0; ib<bs; ib++) {
2479:           work[garray[b_aij->j[i]] * bs + jb] += PetscAbsScalar(*b_val * *b_val);
2480:           b_val++;
2481:         }
2482:       }
2483:     }
2484:   } else if (type == NORM_1) {
2485:     for (i=a_aij->i[0]; i<a_aij->i[aij->A->rmap->n/bs]; i++) {
2486:       for (jb=0; jb<bs; jb++) {
2487:         for (ib=0; ib<bs; ib++) {
2488:           work[A->cmap->rstart + a_aij->j[i] * bs + jb] += PetscAbsScalar(*a_val);
2489:           a_val++;
2490:         }
2491:       }
2492:     }
2493:     for (i=b_aij->i[0]; i<b_aij->i[aij->B->rmap->n/bs]; i++) {
2494:       for (jb=0; jb<bs; jb++) {
2495:        for (ib=0; ib<bs; ib++) {
2496:           work[garray[b_aij->j[i]] * bs + jb] += PetscAbsScalar(*b_val);
2497:           b_val++;
2498:         }
2499:       }
2500:     }
2501:   } else if (type == NORM_INFINITY) {
2502:     for (i=a_aij->i[0]; i<a_aij->i[aij->A->rmap->n/bs]; i++) {
2503:       for (jb=0; jb<bs; jb++) {
2504:         for (ib=0; ib<bs; ib++) {
2505:           int col = A->cmap->rstart + a_aij->j[i] * bs + jb;
2506:           work[col] = PetscMax(PetscAbsScalar(*a_val), work[col]);
2507:           a_val++;
2508:         }
2509:       }
2510:     }
2511:     for (i=b_aij->i[0]; i<b_aij->i[aij->B->rmap->n/bs]; i++) {
2512:       for (jb=0; jb<bs; jb++) {
2513:         for (ib=0; ib<bs; ib++) {
2514:           int col = garray[b_aij->j[i]] * bs + jb;
2515:           work[col] = PetscMax(PetscAbsScalar(*b_val), work[col]);
2516:           b_val++;
2517:         }
2518:       }
2519:     }
2520:   } else SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Unknown NormType");
2521:   if (type == NORM_INFINITY) {
2522:     MPIU_Allreduce(work,norms,N,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)A));
2523:   } else {
2524:     MPIU_Allreduce(work,norms,N,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)A));
2525:   }
2526:   PetscFree(work);
2527:   if (type == NORM_2) {
2528:     for (i=0; i<N; i++) norms[i] = PetscSqrtReal(norms[i]);
2529:   }
2530:   return(0);
2531: }

2533: PetscErrorCode MatInvertBlockDiagonal_MPIBAIJ(Mat A,const PetscScalar **values)
2534: {
2535:   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*) A->data;

2539:   MatInvertBlockDiagonal(a->A,values);
2540:   A->factorerrortype             = a->A->factorerrortype;
2541:   A->factorerror_zeropivot_value = a->A->factorerror_zeropivot_value;
2542:   A->factorerror_zeropivot_row   = a->A->factorerror_zeropivot_row;
2543:   return(0);
2544: }

2546: PetscErrorCode MatShift_MPIBAIJ(Mat Y,PetscScalar a)
2547: {
2549:   Mat_MPIBAIJ    *maij = (Mat_MPIBAIJ*)Y->data;
2550:   Mat_SeqBAIJ    *aij = (Mat_SeqBAIJ*)maij->A->data;

2553:   if (!Y->preallocated) {
2554:     MatMPIBAIJSetPreallocation(Y,Y->rmap->bs,1,NULL,0,NULL);
2555:   } else if (!aij->nz) {
2556:     PetscInt nonew = aij->nonew;
2557:     MatSeqBAIJSetPreallocation(maij->A,Y->rmap->bs,1,NULL);
2558:     aij->nonew = nonew;
2559:   }
2560:   MatShift_Basic(Y,a);
2561:   return(0);
2562: }

2564: PetscErrorCode MatMissingDiagonal_MPIBAIJ(Mat A,PetscBool  *missing,PetscInt *d)
2565: {
2566:   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;

2570:   if (A->rmap->n != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only works for square matrices");
2571:   MatMissingDiagonal(a->A,missing,d);
2572:   if (d) {
2573:     PetscInt rstart;
2574:     MatGetOwnershipRange(A,&rstart,NULL);
2575:     *d += rstart/A->rmap->bs;

2577:   }
2578:   return(0);
2579: }

2581: PetscErrorCode  MatGetDiagonalBlock_MPIBAIJ(Mat A,Mat *a)
2582: {
2584:   *a = ((Mat_MPIBAIJ*)A->data)->A;
2585:   return(0);
2586: }

2588: /* -------------------------------------------------------------------*/
2589: static struct _MatOps MatOps_Values = {MatSetValues_MPIBAIJ,
2590:                                        MatGetRow_MPIBAIJ,
2591:                                        MatRestoreRow_MPIBAIJ,
2592:                                        MatMult_MPIBAIJ,
2593:                                 /* 4*/ MatMultAdd_MPIBAIJ,
2594:                                        MatMultTranspose_MPIBAIJ,
2595:                                        MatMultTransposeAdd_MPIBAIJ,
2596:                                        0,
2597:                                        0,
2598:                                        0,
2599:                                 /*10*/ 0,
2600:                                        0,
2601:                                        0,
2602:                                        MatSOR_MPIBAIJ,
2603:                                        MatTranspose_MPIBAIJ,
2604:                                 /*15*/ MatGetInfo_MPIBAIJ,
2605:                                        MatEqual_MPIBAIJ,
2606:                                        MatGetDiagonal_MPIBAIJ,
2607:                                        MatDiagonalScale_MPIBAIJ,
2608:                                        MatNorm_MPIBAIJ,
2609:                                 /*20*/ MatAssemblyBegin_MPIBAIJ,
2610:                                        MatAssemblyEnd_MPIBAIJ,
2611:                                        MatSetOption_MPIBAIJ,
2612:                                        MatZeroEntries_MPIBAIJ,
2613:                                 /*24*/ MatZeroRows_MPIBAIJ,
2614:                                        0,
2615:                                        0,
2616:                                        0,
2617:                                        0,
2618:                                 /*29*/ MatSetUp_MPIBAIJ,
2619:                                        0,
2620:                                        0,
2621:                                        MatGetDiagonalBlock_MPIBAIJ,
2622:                                        0,
2623:                                 /*34*/ MatDuplicate_MPIBAIJ,
2624:                                        0,
2625:                                        0,
2626:                                        0,
2627:                                        0,
2628:                                 /*39*/ MatAXPY_MPIBAIJ,
2629:                                        MatCreateSubMatrices_MPIBAIJ,
2630:                                        MatIncreaseOverlap_MPIBAIJ,
2631:                                        MatGetValues_MPIBAIJ,
2632:                                        MatCopy_MPIBAIJ,
2633:                                 /*44*/ 0,
2634:                                        MatScale_MPIBAIJ,
2635:                                        MatShift_MPIBAIJ,
2636:                                        0,
2637:                                        MatZeroRowsColumns_MPIBAIJ,
2638:                                 /*49*/ 0,
2639:                                        0,
2640:                                        0,
2641:                                        0,
2642:                                        0,
2643:                                 /*54*/ MatFDColoringCreate_MPIXAIJ,
2644:                                        0,
2645:                                        MatSetUnfactored_MPIBAIJ,
2646:                                        MatPermute_MPIBAIJ,
2647:                                        MatSetValuesBlocked_MPIBAIJ,
2648:                                 /*59*/ MatCreateSubMatrix_MPIBAIJ,
2649:                                        MatDestroy_MPIBAIJ,
2650:                                        MatView_MPIBAIJ,
2651:                                        0,
2652:                                        0,
2653:                                 /*64*/ 0,
2654:                                        0,
2655:                                        0,
2656:                                        0,
2657:                                        0,
2658:                                 /*69*/ MatGetRowMaxAbs_MPIBAIJ,
2659:                                        0,
2660:                                        0,
2661:                                        0,
2662:                                        0,
2663:                                 /*74*/ 0,
2664:                                        MatFDColoringApply_BAIJ,
2665:                                        0,
2666:                                        0,
2667:                                        0,
2668:                                 /*79*/ 0,
2669:                                        0,
2670:                                        0,
2671:                                        0,
2672:                                        MatLoad_MPIBAIJ,
2673:                                 /*84*/ 0,
2674:                                        0,
2675:                                        0,
2676:                                        0,
2677:                                        0,
2678:                                 /*89*/ 0,
2679:                                        0,
2680:                                        0,
2681:                                        0,
2682:                                        0,
2683:                                 /*94*/ 0,
2684:                                        0,
2685:                                        0,
2686:                                        0,
2687:                                        0,
2688:                                 /*99*/ 0,
2689:                                        0,
2690:                                        0,
2691:                                        0,
2692:                                        0,
2693:                                 /*104*/0,
2694:                                        MatRealPart_MPIBAIJ,
2695:                                        MatImaginaryPart_MPIBAIJ,
2696:                                        0,
2697:                                        0,
2698:                                 /*109*/0,
2699:                                        0,
2700:                                        0,
2701:                                        0,
2702:                                        MatMissingDiagonal_MPIBAIJ,
2703:                                 /*114*/MatGetSeqNonzeroStructure_MPIBAIJ,
2704:                                        0,
2705:                                        MatGetGhosts_MPIBAIJ,
2706:                                        0,
2707:                                        0,
2708:                                 /*119*/0,
2709:                                        0,
2710:                                        0,
2711:                                        0,
2712:                                        MatGetMultiProcBlock_MPIBAIJ,
2713:                                 /*124*/0,
2714:                                        MatGetColumnNorms_MPIBAIJ,
2715:                                        MatInvertBlockDiagonal_MPIBAIJ,
2716:                                        0,
2717:                                        0,
2718:                                /*129*/ 0,
2719:                                        0,
2720:                                        0,
2721:                                        0,
2722:                                        0,
2723:                                /*134*/ 0,
2724:                                        0,
2725:                                        0,
2726:                                        0,
2727:                                        0,
2728:                                /*139*/ MatSetBlockSizes_Default,
2729:                                        0,
2730:                                        0,
2731:                                        MatFDColoringSetUp_MPIXAIJ,
2732:                                        0,
2733:                                 /*144*/MatCreateMPIMatConcatenateSeqMat_MPIBAIJ
2734: };


2737: PETSC_INTERN PetscErrorCode MatConvert_MPIBAIJ_MPISBAIJ(Mat, MatType,MatReuse,Mat*);

2739: PetscErrorCode MatMPIBAIJSetPreallocationCSR_MPIBAIJ(Mat B,PetscInt bs,const PetscInt ii[],const PetscInt jj[],const PetscScalar V[])
2740: {
2741:   PetscInt       m,rstart,cstart,cend;
2742:   PetscInt       i,j,d,nz,nz_max=0,*d_nnz=0,*o_nnz=0;
2743:   const PetscInt *JJ    =0;
2744:   PetscScalar    *values=0;
2745:   PetscBool      roworiented = ((Mat_MPIBAIJ*)B->data)->roworiented;

2749:   PetscLayoutSetBlockSize(B->rmap,bs);
2750:   PetscLayoutSetBlockSize(B->cmap,bs);
2751:   PetscLayoutSetUp(B->rmap);
2752:   PetscLayoutSetUp(B->cmap);
2753:   PetscLayoutGetBlockSize(B->rmap,&bs);
2754:   m      = B->rmap->n/bs;
2755:   rstart = B->rmap->rstart/bs;
2756:   cstart = B->cmap->rstart/bs;
2757:   cend   = B->cmap->rend/bs;

2759:   if (ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"ii[0] must be 0 but it is %D",ii[0]);
2760:   PetscMalloc2(m,&d_nnz,m,&o_nnz);
2761:   for (i=0; i<m; i++) {
2762:     nz = ii[i+1] - ii[i];
2763:     if (nz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative number of columns %D",i,nz);
2764:     nz_max = PetscMax(nz_max,nz);
2765:     JJ     = jj + ii[i];
2766:     for (j=0; j<nz; j++) {
2767:       if (*JJ >= cstart) break;
2768:       JJ++;
2769:     }
2770:     d = 0;
2771:     for (; j<nz; j++) {
2772:       if (*JJ++ >= cend) break;
2773:       d++;
2774:     }
2775:     d_nnz[i] = d;
2776:     o_nnz[i] = nz - d;
2777:   }
2778:   MatMPIBAIJSetPreallocation(B,bs,0,d_nnz,0,o_nnz);
2779:   PetscFree2(d_nnz,o_nnz);

2781:   values = (PetscScalar*)V;
2782:   if (!values) {
2783:     PetscMalloc1(bs*bs*nz_max,&values);
2784:     PetscMemzero(values,bs*bs*nz_max*sizeof(PetscScalar));
2785:   }
2786:   for (i=0; i<m; i++) {
2787:     PetscInt          row    = i + rstart;
2788:     PetscInt          ncols  = ii[i+1] - ii[i];
2789:     const PetscInt    *icols = jj + ii[i];
2790:     if (!roworiented) {         /* block ordering matches the non-nested layout of MatSetValues so we can insert entire rows */
2791:       const PetscScalar *svals = values + (V ? (bs*bs*ii[i]) : 0);
2792:       MatSetValuesBlocked_MPIBAIJ(B,1,&row,ncols,icols,svals,INSERT_VALUES);
2793:     } else {                    /* block ordering does not match so we can only insert one block at a time. */
2794:       PetscInt j;
2795:       for (j=0; j<ncols; j++) {
2796:         const PetscScalar *svals = values + (V ? (bs*bs*(ii[i]+j)) : 0);
2797:         MatSetValuesBlocked_MPIBAIJ(B,1,&row,1,&icols[j],svals,INSERT_VALUES);
2798:       }
2799:     }
2800:   }

2802:   if (!V) { PetscFree(values); }
2803:   MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
2804:   MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);
2805:   MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);
2806:   return(0);
2807: }

2809: /*@C
2810:    MatMPIBAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in BAIJ format
2811:    (the default parallel PETSc format).

2813:    Collective on MPI_Comm

2815:    Input Parameters:
2816: +  B - the matrix
2817: .  bs - the block size
2818: .  i - the indices into j for the start of each local row (starts with zero)
2819: .  j - the column indices for each local row (starts with zero) these must be sorted for each row
2820: -  v - optional values in the matrix

2822:    Level: developer

2824:    Notes: The order of the entries in values is specified by the MatOption MAT_ROW_ORIENTED.  For example, C programs
2825:    may want to use the default MAT_ROW_ORIENTED=PETSC_TRUE and use an array v[nnz][bs][bs] where the second index is
2826:    over rows within a block and the last index is over columns within a block row.  Fortran programs will likely set
2827:    MAT_ROW_ORIENTED=PETSC_FALSE and use a Fortran array v(bs,bs,nnz) in which the first index is over rows within a
2828:    block column and the second index is over columns within a block.

2830: .keywords: matrix, aij, compressed row, sparse, parallel

2832: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIBAIJSetPreallocation(), MatCreateAIJ(), MPIAIJ, MatCreateMPIBAIJWithArrays(), MPIBAIJ
2833: @*/
2834: PetscErrorCode  MatMPIBAIJSetPreallocationCSR(Mat B,PetscInt bs,const PetscInt i[],const PetscInt j[], const PetscScalar v[])
2835: {

2842:   PetscTryMethod(B,"MatMPIBAIJSetPreallocationCSR_C",(Mat,PetscInt,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,bs,i,j,v));
2843:   return(0);
2844: }

2846: PetscErrorCode  MatMPIBAIJSetPreallocation_MPIBAIJ(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt *d_nnz,PetscInt o_nz,const PetscInt *o_nnz)
2847: {
2848:   Mat_MPIBAIJ    *b;
2850:   PetscInt       i;

2853:   MatSetBlockSize(B,PetscAbs(bs));
2854:   PetscLayoutSetUp(B->rmap);
2855:   PetscLayoutSetUp(B->cmap);
2856:   PetscLayoutGetBlockSize(B->rmap,&bs);

2858:   if (d_nnz) {
2859:     for (i=0; i<B->rmap->n/bs; i++) {
2860:       if (d_nnz[i] < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"d_nnz cannot be less than -1: local row %D value %D",i,d_nnz[i]);
2861:     }
2862:   }
2863:   if (o_nnz) {
2864:     for (i=0; i<B->rmap->n/bs; i++) {
2865:       if (o_nnz[i] < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"o_nnz cannot be less than -1: local row %D value %D",i,o_nnz[i]);
2866:     }
2867:   }

2869:   b      = (Mat_MPIBAIJ*)B->data;
2870:   b->bs2 = bs*bs;
2871:   b->mbs = B->rmap->n/bs;
2872:   b->nbs = B->cmap->n/bs;
2873:   b->Mbs = B->rmap->N/bs;
2874:   b->Nbs = B->cmap->N/bs;

2876:   for (i=0; i<=b->size; i++) {
2877:     b->rangebs[i] = B->rmap->range[i]/bs;
2878:   }
2879:   b->rstartbs = B->rmap->rstart/bs;
2880:   b->rendbs   = B->rmap->rend/bs;
2881:   b->cstartbs = B->cmap->rstart/bs;
2882:   b->cendbs   = B->cmap->rend/bs;

2884: #if defined(PETSC_USE_CTABLE)
2885:   PetscTableDestroy(&b->colmap);
2886: #else
2887:   PetscFree(b->colmap);
2888: #endif
2889:   PetscFree(b->garray);
2890:   VecDestroy(&b->lvec);
2891:   VecScatterDestroy(&b->Mvctx);

2893:   /* Because the B will have been resized we simply destroy it and create a new one each time */
2894:   MatDestroy(&b->B);
2895:   MatCreate(PETSC_COMM_SELF,&b->B);
2896:   MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);
2897:   MatSetType(b->B,MATSEQBAIJ);
2898:   PetscLogObjectParent((PetscObject)B,(PetscObject)b->B);

2900:   if (!B->preallocated) {
2901:     MatCreate(PETSC_COMM_SELF,&b->A);
2902:     MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);
2903:     MatSetType(b->A,MATSEQBAIJ);
2904:     PetscLogObjectParent((PetscObject)B,(PetscObject)b->A);
2905:     MatStashCreate_Private(PetscObjectComm((PetscObject)B),bs,&B->bstash);
2906:   }

2908:   MatSeqBAIJSetPreallocation(b->A,bs,d_nz,d_nnz);
2909:   MatSeqBAIJSetPreallocation(b->B,bs,o_nz,o_nnz);
2910:   B->preallocated  = PETSC_TRUE;
2911:   B->was_assembled = PETSC_FALSE;
2912:   B->assembled     = PETSC_FALSE;
2913:   return(0);
2914: }

2916: extern PetscErrorCode  MatDiagonalScaleLocal_MPIBAIJ(Mat,Vec);
2917: extern PetscErrorCode  MatSetHashTableFactor_MPIBAIJ(Mat,PetscReal);

2919: PETSC_INTERN PetscErrorCode MatConvert_MPIBAIJ_MPIAdj(Mat B, MatType newtype,MatReuse reuse,Mat *adj)
2920: {
2921:   Mat_MPIBAIJ    *b = (Mat_MPIBAIJ*)B->data;
2923:   Mat_SeqBAIJ    *d  = (Mat_SeqBAIJ*) b->A->data,*o = (Mat_SeqBAIJ*) b->B->data;
2924:   PetscInt       M   = B->rmap->n/B->rmap->bs,i,*ii,*jj,cnt,j,k,rstart = B->rmap->rstart/B->rmap->bs;
2925:   const PetscInt *id = d->i, *jd = d->j, *io = o->i, *jo = o->j, *garray = b->garray;

2928:   PetscMalloc1(M+1,&ii);
2929:   ii[0] = 0;
2930:   for (i=0; i<M; i++) {
2931:     if ((id[i+1] - id[i]) < 0) SETERRQ3(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Indices wrong %D %D %D",i,id[i],id[i+1]);
2932:     if ((io[i+1] - io[i]) < 0) SETERRQ3(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Indices wrong %D %D %D",i,io[i],io[i+1]);
2933:     ii[i+1] = ii[i] + id[i+1] - id[i] + io[i+1] - io[i];
2934:     /* remove one from count of matrix has diagonal */
2935:     for (j=id[i]; j<id[i+1]; j++) {
2936:       if (jd[j] == i) {ii[i+1]--;break;}
2937:     }
2938:   }
2939:   PetscMalloc1(ii[M],&jj);
2940:   cnt  = 0;
2941:   for (i=0; i<M; i++) {
2942:     for (j=io[i]; j<io[i+1]; j++) {
2943:       if (garray[jo[j]] > rstart) break;
2944:       jj[cnt++] = garray[jo[j]];
2945:     }
2946:     for (k=id[i]; k<id[i+1]; k++) {
2947:       if (jd[k] != i) {
2948:         jj[cnt++] = rstart + jd[k];
2949:       }
2950:     }
2951:     for (; j<io[i+1]; j++) {
2952:       jj[cnt++] = garray[jo[j]];
2953:     }
2954:   }
2955:   MatCreateMPIAdj(PetscObjectComm((PetscObject)B),M,B->cmap->N/B->rmap->bs,ii,jj,NULL,adj);
2956:   return(0);
2957: }

2959:  #include <../src/mat/impls/aij/mpi/mpiaij.h>

2961: PETSC_INTERN PetscErrorCode MatConvert_SeqBAIJ_SeqAIJ(Mat,MatType,MatReuse,Mat*);

2963: PETSC_INTERN PetscErrorCode MatConvert_MPIBAIJ_MPIAIJ(Mat A,MatType newtype,MatReuse reuse,Mat *newmat)
2964: {
2966:   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;
2967:   Mat            B;
2968:   Mat_MPIAIJ     *b;

2971:   if (!A->assembled) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Matrix must be assembled");

2973:   if (reuse == MAT_REUSE_MATRIX) {
2974:     B = *newmat;
2975:   } else {
2976:     MatCreate(PetscObjectComm((PetscObject)A),&B);
2977:     MatSetType(B,MATMPIAIJ);
2978:     MatSetSizes(B,A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N);
2979:     MatSetBlockSizes(B,A->rmap->bs,A->cmap->bs);
2980:     MatSeqAIJSetPreallocation(B,0,NULL);
2981:     MatMPIAIJSetPreallocation(B,0,NULL,0,NULL);
2982:   }
2983:   b = (Mat_MPIAIJ*) B->data;

2985:   if (reuse == MAT_REUSE_MATRIX) {
2986:     MatConvert_SeqBAIJ_SeqAIJ(a->A, MATSEQAIJ, MAT_REUSE_MATRIX, &b->A);
2987:     MatConvert_SeqBAIJ_SeqAIJ(a->B, MATSEQAIJ, MAT_REUSE_MATRIX, &b->B);
2988:   } else {
2989:     MatDestroy(&b->A);
2990:     MatDestroy(&b->B);
2991:     MatDisAssemble_MPIBAIJ(A);
2992:     MatConvert_SeqBAIJ_SeqAIJ(a->A, MATSEQAIJ, MAT_INITIAL_MATRIX, &b->A);
2993:     MatConvert_SeqBAIJ_SeqAIJ(a->B, MATSEQAIJ, MAT_INITIAL_MATRIX, &b->B);
2994:     MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);
2995:     MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);
2996:   }
2997:   MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
2998:   MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);

3000:   if (reuse == MAT_INPLACE_MATRIX) {
3001:     MatHeaderReplace(A,&B);
3002:   } else {
3003:    *newmat = B;
3004:   }
3005:   return(0);
3006: }

3008: /*MC
3009:    MATMPIBAIJ - MATMPIBAIJ = "mpibaij" - A matrix type to be used for distributed block sparse matrices.

3011:    Options Database Keys:
3012: + -mat_type mpibaij - sets the matrix type to "mpibaij" during a call to MatSetFromOptions()
3013: . -mat_block_size <bs> - set the blocksize used to store the matrix
3014: - -mat_use_hash_table <fact>

3016:   Level: beginner

3018: .seealso: MatCreateMPIBAIJ
3019: M*/

3021: PETSC_INTERN PetscErrorCode MatConvert_MPIBAIJ_MPIBSTRM(Mat,MatType,MatReuse,Mat*);

3023: PETSC_EXTERN PetscErrorCode MatCreate_MPIBAIJ(Mat B)
3024: {
3025:   Mat_MPIBAIJ    *b;
3027:   PetscBool      flg = PETSC_FALSE;

3030:   PetscNewLog(B,&b);
3031:   B->data = (void*)b;

3033:   PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));
3034:   B->assembled = PETSC_FALSE;

3036:   B->insertmode = NOT_SET_VALUES;
3037:   MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);
3038:   MPI_Comm_size(PetscObjectComm((PetscObject)B),&b->size);

3040:   /* build local table of row and column ownerships */
3041:   PetscMalloc1(b->size+1,&b->rangebs);

3043:   /* build cache for off array entries formed */
3044:   MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);

3046:   b->donotstash  = PETSC_FALSE;
3047:   b->colmap      = NULL;
3048:   b->garray      = NULL;
3049:   b->roworiented = PETSC_TRUE;

3051:   /* stuff used in block assembly */
3052:   b->barray = 0;

3054:   /* stuff used for matrix vector multiply */
3055:   b->lvec  = 0;
3056:   b->Mvctx = 0;

3058:   /* stuff for MatGetRow() */
3059:   b->rowindices   = 0;
3060:   b->rowvalues    = 0;
3061:   b->getrowactive = PETSC_FALSE;

3063:   /* hash table stuff */
3064:   b->ht           = 0;
3065:   b->hd           = 0;
3066:   b->ht_size      = 0;
3067:   b->ht_flag      = PETSC_FALSE;
3068:   b->ht_fact      = 0;
3069:   b->ht_total_ct  = 0;
3070:   b->ht_insert_ct = 0;

3072:   /* stuff for MatCreateSubMatrices_MPIBAIJ_local() */
3073:   b->ijonly = PETSC_FALSE;


3076:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpibaij_mpiadj_C",MatConvert_MPIBAIJ_MPIAdj);
3077:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpibaij_mpiaij_C",MatConvert_MPIBAIJ_MPIAIJ);
3078:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpibaij_mpisbaij_C",MatConvert_MPIBAIJ_MPISBAIJ);
3079: #if defined(PETSC_HAVE_HYPRE)
3080:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpibaij_hypre_C",MatConvert_AIJ_HYPRE);
3081: #endif
3082:   PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPIBAIJ);
3083:   PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPIBAIJ);
3084:   PetscObjectComposeFunction((PetscObject)B,"MatMPIBAIJSetPreallocation_C",MatMPIBAIJSetPreallocation_MPIBAIJ);
3085:   PetscObjectComposeFunction((PetscObject)B,"MatMPIBAIJSetPreallocationCSR_C",MatMPIBAIJSetPreallocationCSR_MPIBAIJ);
3086:   PetscObjectComposeFunction((PetscObject)B,"MatDiagonalScaleLocal_C",MatDiagonalScaleLocal_MPIBAIJ);
3087:   PetscObjectComposeFunction((PetscObject)B,"MatSetHashTableFactor_C",MatSetHashTableFactor_MPIBAIJ);
3088:   PetscObjectChangeTypeName((PetscObject)B,MATMPIBAIJ);

3090:   PetscOptionsBegin(PetscObjectComm((PetscObject)B),NULL,"Options for loading MPIBAIJ matrix 1","Mat");
3091:   PetscOptionsName("-mat_use_hash_table","Use hash table to save time in constructing matrix","MatSetOption",&flg);
3092:   if (flg) {
3093:     PetscReal fact = 1.39;
3094:     MatSetOption(B,MAT_USE_HASH_TABLE,PETSC_TRUE);
3095:     PetscOptionsReal("-mat_use_hash_table","Use hash table factor","MatMPIBAIJSetHashTableFactor",fact,&fact,NULL);
3096:     if (fact <= 1.0) fact = 1.39;
3097:     MatMPIBAIJSetHashTableFactor(B,fact);
3098:     PetscInfo1(B,"Hash table Factor used %5.2f\n",fact);
3099:   }
3100:   PetscOptionsEnd();
3101:   return(0);
3102: }

3104: /*MC
3105:    MATBAIJ - MATBAIJ = "baij" - A matrix type to be used for block sparse matrices.

3107:    This matrix type is identical to MATSEQBAIJ when constructed with a single process communicator,
3108:    and MATMPIBAIJ otherwise.

3110:    Options Database Keys:
3111: . -mat_type baij - sets the matrix type to "baij" during a call to MatSetFromOptions()

3113:   Level: beginner

3115: .seealso: MatCreateBAIJ(),MATSEQBAIJ,MATMPIBAIJ, MatMPIBAIJSetPreallocation(), MatMPIBAIJSetPreallocationCSR()
3116: M*/

3118: /*@C
3119:    MatMPIBAIJSetPreallocation - Allocates memory for a sparse parallel matrix in block AIJ format
3120:    (block compressed row).  For good matrix assembly performance
3121:    the user should preallocate the matrix storage by setting the parameters
3122:    d_nz (or d_nnz) and o_nz (or o_nnz).  By setting these parameters accurately,
3123:    performance can be increased by more than a factor of 50.

3125:    Collective on Mat

3127:    Input Parameters:
3128: +  B - the matrix
3129: .  bs   - size of block, the blocks are ALWAYS square. One can use MatSetBlockSizes() to set a different row and column blocksize but the row
3130:           blocksize always defines the size of the blocks. The column blocksize sets the blocksize of the vectors obtained with MatCreateVecs()
3131: .  d_nz  - number of block nonzeros per block row in diagonal portion of local
3132:            submatrix  (same for all local rows)
3133: .  d_nnz - array containing the number of block nonzeros in the various block rows
3134:            of the in diagonal portion of the local (possibly different for each block
3135:            row) or NULL.  If you plan to factor the matrix you must leave room for the diagonal entry and
3136:            set it even if it is zero.
3137: .  o_nz  - number of block nonzeros per block row in the off-diagonal portion of local
3138:            submatrix (same for all local rows).
3139: -  o_nnz - array containing the number of nonzeros in the various block rows of the
3140:            off-diagonal portion of the local submatrix (possibly different for
3141:            each block row) or NULL.

3143:    If the *_nnz parameter is given then the *_nz parameter is ignored

3145:    Options Database Keys:
3146: +   -mat_block_size - size of the blocks to use
3147: -   -mat_use_hash_table <fact>

3149:    Notes:
3150:    If PETSC_DECIDE or  PETSC_DETERMINE is used for a particular argument on one processor
3151:    than it must be used on all processors that share the object for that argument.

3153:    Storage Information:
3154:    For a square global matrix we define each processor's diagonal portion
3155:    to be its local rows and the corresponding columns (a square submatrix);
3156:    each processor's off-diagonal portion encompasses the remainder of the
3157:    local matrix (a rectangular submatrix).

3159:    The user can specify preallocated storage for the diagonal part of
3160:    the local submatrix with either d_nz or d_nnz (not both).  Set
3161:    d_nz=PETSC_DEFAULT and d_nnz=NULL for PETSc to control dynamic
3162:    memory allocation.  Likewise, specify preallocated storage for the
3163:    off-diagonal part of the local submatrix with o_nz or o_nnz (not both).

3165:    Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In
3166:    the figure below we depict these three local rows and all columns (0-11).

3168: .vb
3169:            0 1 2 3 4 5 6 7 8 9 10 11
3170:           --------------------------
3171:    row 3  |o o o d d d o o o o  o  o
3172:    row 4  |o o o d d d o o o o  o  o
3173:    row 5  |o o o d d d o o o o  o  o
3174:           --------------------------
3175: .ve

3177:    Thus, any entries in the d locations are stored in the d (diagonal)
3178:    submatrix, and any entries in the o locations are stored in the
3179:    o (off-diagonal) submatrix.  Note that the d and the o submatrices are
3180:    stored simply in the MATSEQBAIJ format for compressed row storage.

3182:    Now d_nz should indicate the number of block nonzeros per row in the d matrix,
3183:    and o_nz should indicate the number of block nonzeros per row in the o matrix.
3184:    In general, for PDE problems in which most nonzeros are near the diagonal,
3185:    one expects d_nz >> o_nz.   For large problems you MUST preallocate memory
3186:    or you will get TERRIBLE performance; see the users' manual chapter on
3187:    matrices.

3189:    You can call MatGetInfo() to get information on how effective the preallocation was;
3190:    for example the fields mallocs,nz_allocated,nz_used,nz_unneeded;
3191:    You can also run with the option -info and look for messages with the string
3192:    malloc in them to see if additional memory allocation was needed.

3194:    Level: intermediate

3196: .keywords: matrix, block, aij, compressed row, sparse, parallel

3198: .seealso: MatCreate(), MatCreateSeqBAIJ(), MatSetValues(), MatCreateBAIJ(), MatMPIBAIJSetPreallocationCSR(), PetscSplitOwnership()
3199: @*/
3200: PetscErrorCode  MatMPIBAIJSetPreallocation(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[])
3201: {

3208:   PetscTryMethod(B,"MatMPIBAIJSetPreallocation_C",(Mat,PetscInt,PetscInt,const PetscInt[],PetscInt,const PetscInt[]),(B,bs,d_nz,d_nnz,o_nz,o_nnz));
3209:   return(0);
3210: }

3212: /*@C
3213:    MatCreateBAIJ - Creates a sparse parallel matrix in block AIJ format
3214:    (block compressed row).  For good matrix assembly performance
3215:    the user should preallocate the matrix storage by setting the parameters
3216:    d_nz (or d_nnz) and o_nz (or o_nnz).  By setting these parameters accurately,
3217:    performance can be increased by more than a factor of 50.

3219:    Collective on MPI_Comm

3221:    Input Parameters:
3222: +  comm - MPI communicator
3223: .  bs   - size of block, the blocks are ALWAYS square. One can use MatSetBlockSizes() to set a different row and column blocksize but the row
3224:           blocksize always defines the size of the blocks. The column blocksize sets the blocksize of the vectors obtained with MatCreateVecs()
3225: .  m - number of local rows (or PETSC_DECIDE to have calculated if M is given)
3226:            This value should be the same as the local size used in creating the
3227:            y vector for the matrix-vector product y = Ax.
3228: .  n - number of local columns (or PETSC_DECIDE to have calculated if N is given)
3229:            This value should be the same as the local size used in creating the
3230:            x vector for the matrix-vector product y = Ax.
3231: .  M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
3232: .  N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
3233: .  d_nz  - number of nonzero blocks per block row in diagonal portion of local
3234:            submatrix  (same for all local rows)
3235: .  d_nnz - array containing the number of nonzero blocks in the various block rows
3236:            of the in diagonal portion of the local (possibly different for each block
3237:            row) or NULL.  If you plan to factor the matrix you must leave room for the diagonal entry
3238:            and set it even if it is zero.
3239: .  o_nz  - number of nonzero blocks per block row in the off-diagonal portion of local
3240:            submatrix (same for all local rows).
3241: -  o_nnz - array containing the number of nonzero blocks in the various block rows of the
3242:            off-diagonal portion of the local submatrix (possibly different for
3243:            each block row) or NULL.

3245:    Output Parameter:
3246: .  A - the matrix

3248:    Options Database Keys:
3249: +   -mat_block_size - size of the blocks to use
3250: -   -mat_use_hash_table <fact>

3252:    It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(),
3253:    MatXXXXSetPreallocation() paradgm instead of this routine directly.
3254:    [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation]

3256:    Notes:
3257:    If the *_nnz parameter is given then the *_nz parameter is ignored

3259:    A nonzero block is any block that as 1 or more nonzeros in it

3261:    The user MUST specify either the local or global matrix dimensions
3262:    (possibly both).

3264:    If PETSC_DECIDE or  PETSC_DETERMINE is used for a particular argument on one processor
3265:    than it must be used on all processors that share the object for that argument.

3267:    Storage Information:
3268:    For a square global matrix we define each processor's diagonal portion
3269:    to be its local rows and the corresponding columns (a square submatrix);
3270:    each processor's off-diagonal portion encompasses the remainder of the
3271:    local matrix (a rectangular submatrix).

3273:    The user can specify preallocated storage for the diagonal part of
3274:    the local submatrix with either d_nz or d_nnz (not both).  Set
3275:    d_nz=PETSC_DEFAULT and d_nnz=NULL for PETSc to control dynamic
3276:    memory allocation.  Likewise, specify preallocated storage for the
3277:    off-diagonal part of the local submatrix with o_nz or o_nnz (not both).

3279:    Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In
3280:    the figure below we depict these three local rows and all columns (0-11).

3282: .vb
3283:            0 1 2 3 4 5 6 7 8 9 10 11
3284:           --------------------------
3285:    row 3  |o o o d d d o o o o  o  o
3286:    row 4  |o o o d d d o o o o  o  o
3287:    row 5  |o o o d d d o o o o  o  o
3288:           --------------------------
3289: .ve

3291:    Thus, any entries in the d locations are stored in the d (diagonal)
3292:    submatrix, and any entries in the o locations are stored in the
3293:    o (off-diagonal) submatrix.  Note that the d and the o submatrices are
3294:    stored simply in the MATSEQBAIJ format for compressed row storage.

3296:    Now d_nz should indicate the number of block nonzeros per row in the d matrix,
3297:    and o_nz should indicate the number of block nonzeros per row in the o matrix.
3298:    In general, for PDE problems in which most nonzeros are near the diagonal,
3299:    one expects d_nz >> o_nz.   For large problems you MUST preallocate memory
3300:    or you will get TERRIBLE performance; see the users' manual chapter on
3301:    matrices.

3303:    Level: intermediate

3305: .keywords: matrix, block, aij, compressed row, sparse, parallel

3307: .seealso: MatCreate(), MatCreateSeqBAIJ(), MatSetValues(), MatCreateBAIJ(), MatMPIBAIJSetPreallocation(), MatMPIBAIJSetPreallocationCSR()
3308: @*/
3309: PetscErrorCode  MatCreateBAIJ(MPI_Comm comm,PetscInt bs,PetscInt m,PetscInt n,PetscInt M,PetscInt N,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[],Mat *A)
3310: {
3312:   PetscMPIInt    size;

3315:   MatCreate(comm,A);
3316:   MatSetSizes(*A,m,n,M,N);
3317:   MPI_Comm_size(comm,&size);
3318:   if (size > 1) {
3319:     MatSetType(*A,MATMPIBAIJ);
3320:     MatMPIBAIJSetPreallocation(*A,bs,d_nz,d_nnz,o_nz,o_nnz);
3321:   } else {
3322:     MatSetType(*A,MATSEQBAIJ);
3323:     MatSeqBAIJSetPreallocation(*A,bs,d_nz,d_nnz);
3324:   }
3325:   return(0);
3326: }

3328: static PetscErrorCode MatDuplicate_MPIBAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat)
3329: {
3330:   Mat            mat;
3331:   Mat_MPIBAIJ    *a,*oldmat = (Mat_MPIBAIJ*)matin->data;
3333:   PetscInt       len=0;

3336:   *newmat = 0;
3337:   MatCreate(PetscObjectComm((PetscObject)matin),&mat);
3338:   MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);
3339:   MatSetType(mat,((PetscObject)matin)->type_name);
3340:   PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));

3342:   mat->factortype   = matin->factortype;
3343:   mat->preallocated = PETSC_TRUE;
3344:   mat->assembled    = PETSC_TRUE;
3345:   mat->insertmode   = NOT_SET_VALUES;

3347:   a             = (Mat_MPIBAIJ*)mat->data;
3348:   mat->rmap->bs = matin->rmap->bs;
3349:   a->bs2        = oldmat->bs2;
3350:   a->mbs        = oldmat->mbs;
3351:   a->nbs        = oldmat->nbs;
3352:   a->Mbs        = oldmat->Mbs;
3353:   a->Nbs        = oldmat->Nbs;

3355:   PetscLayoutReference(matin->rmap,&mat->rmap);
3356:   PetscLayoutReference(matin->cmap,&mat->cmap);

3358:   a->size         = oldmat->size;
3359:   a->rank         = oldmat->rank;
3360:   a->donotstash   = oldmat->donotstash;
3361:   a->roworiented  = oldmat->roworiented;
3362:   a->rowindices   = 0;
3363:   a->rowvalues    = 0;
3364:   a->getrowactive = PETSC_FALSE;
3365:   a->barray       = 0;
3366:   a->rstartbs     = oldmat->rstartbs;
3367:   a->rendbs       = oldmat->rendbs;
3368:   a->cstartbs     = oldmat->cstartbs;
3369:   a->cendbs       = oldmat->cendbs;

3371:   /* hash table stuff */
3372:   a->ht           = 0;
3373:   a->hd           = 0;
3374:   a->ht_size      = 0;
3375:   a->ht_flag      = oldmat->ht_flag;
3376:   a->ht_fact      = oldmat->ht_fact;
3377:   a->ht_total_ct  = 0;
3378:   a->ht_insert_ct = 0;

3380:   PetscMemcpy(a->rangebs,oldmat->rangebs,(a->size+1)*sizeof(PetscInt));
3381:   if (oldmat->colmap) {
3382: #if defined(PETSC_USE_CTABLE)
3383:     PetscTableCreateCopy(oldmat->colmap,&a->colmap);
3384: #else
3385:     PetscMalloc1(a->Nbs,&a->colmap);
3386:     PetscLogObjectMemory((PetscObject)mat,(a->Nbs)*sizeof(PetscInt));
3387:     PetscMemcpy(a->colmap,oldmat->colmap,(a->Nbs)*sizeof(PetscInt));
3388: #endif
3389:   } else a->colmap = 0;

3391:   if (oldmat->garray && (len = ((Mat_SeqBAIJ*)(oldmat->B->data))->nbs)) {
3392:     PetscMalloc1(len,&a->garray);
3393:     PetscLogObjectMemory((PetscObject)mat,len*sizeof(PetscInt));
3394:     PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));
3395:   } else a->garray = 0;

3397:   MatStashCreate_Private(PetscObjectComm((PetscObject)matin),matin->rmap->bs,&mat->bstash);
3398:   VecDuplicate(oldmat->lvec,&a->lvec);
3399:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->lvec);
3400:   VecScatterCopy(oldmat->Mvctx,&a->Mvctx);
3401:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->Mvctx);

3403:   MatDuplicate(oldmat->A,cpvalues,&a->A);
3404:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->A);
3405:   MatDuplicate(oldmat->B,cpvalues,&a->B);
3406:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->B);
3407:   PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);
3408:   *newmat = mat;
3409:   return(0);
3410: }

3412: PetscErrorCode MatLoad_MPIBAIJ(Mat newmat,PetscViewer viewer)
3413: {
3415:   int            fd;
3416:   PetscInt       i,nz,j,rstart,rend;
3417:   PetscScalar    *vals,*buf;
3418:   MPI_Comm       comm;
3419:   MPI_Status     status;
3420:   PetscMPIInt    rank,size,maxnz;
3421:   PetscInt       header[4],*rowlengths = 0,M,N,m,*rowners,*cols;
3422:   PetscInt       *locrowlens = NULL,*procsnz = NULL,*browners = NULL;
3423:   PetscInt       jj,*mycols,*ibuf,bs = newmat->rmap->bs,Mbs,mbs,extra_rows,mmax;
3424:   PetscMPIInt    tag    = ((PetscObject)viewer)->tag;
3425:   PetscInt       *dlens = NULL,*odlens = NULL,*mask = NULL,*masked1 = NULL,*masked2 = NULL,rowcount,odcount;
3426:   PetscInt       dcount,kmax,k,nzcount,tmp,mend;

3429:   /* force binary viewer to load .info file if it has not yet done so */
3430:   PetscViewerSetUp(viewer);
3431:   PetscObjectGetComm((PetscObject)viewer,&comm);
3432:   PetscOptionsBegin(comm,NULL,"Options for loading MPIBAIJ matrix 2","Mat");
3433:   PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);
3434:   PetscOptionsEnd();
3435:   if (bs < 0) bs = 1;

3437:   MPI_Comm_size(comm,&size);
3438:   MPI_Comm_rank(comm,&rank);
3439:   PetscViewerBinaryGetDescriptor(viewer,&fd);
3440:   if (!rank) {
3441:     PetscBinaryRead(fd,(char*)header,4,PETSC_INT);
3442:     if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object");
3443:     if (header[3] < 0) SETERRQ(PetscObjectComm((PetscObject)newmat),PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format on disk, cannot load as MPIAIJ");
3444:   }
3445:   MPI_Bcast(header+1,3,MPIU_INT,0,comm);
3446:   M    = header[1]; N = header[2];

3448:   /* If global sizes are set, check if they are consistent with that given in the file */
3449:   if (newmat->rmap->N >= 0 && newmat->rmap->N != M) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Inconsistent # of rows:Matrix in file has (%D) and input matrix has (%D)",newmat->rmap->N,M);
3450:   if (newmat->cmap->N >= 0 && newmat->cmap->N != N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Inconsistent # of cols:Matrix in file has (%D) and input matrix has (%D)",newmat->cmap->N,N);

3452:   if (M != N) SETERRQ(PetscObjectComm((PetscObject)viewer),PETSC_ERR_SUP,"Can only do square matrices");

3454:   /*
3455:      This code adds extra rows to make sure the number of rows is
3456:      divisible by the blocksize
3457:   */
3458:   Mbs        = M/bs;
3459:   extra_rows = bs - M + bs*Mbs;
3460:   if (extra_rows == bs) extra_rows = 0;
3461:   else                  Mbs++;
3462:   if (extra_rows && !rank) {
3463:     PetscInfo(viewer,"Padding loaded matrix to match blocksize\n");
3464:   }

3466:   /* determine ownership of all rows */
3467:   if (newmat->rmap->n < 0) { /* PETSC_DECIDE */
3468:     mbs = Mbs/size + ((Mbs % size) > rank);
3469:     m   = mbs*bs;
3470:   } else { /* User set */
3471:     m   = newmat->rmap->n;
3472:     mbs = m/bs;
3473:   }
3474:   PetscMalloc2(size+1,&rowners,size+1,&browners);
3475:   MPI_Allgather(&mbs,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);

3477:   /* process 0 needs enough room for process with most rows */
3478:   if (!rank) {
3479:     mmax = rowners[1];
3480:     for (i=2; i<=size; i++) {
3481:       mmax = PetscMax(mmax,rowners[i]);
3482:     }
3483:     mmax*=bs;
3484:   } else mmax = -1;             /* unused, but compiler warns anyway */

3486:   rowners[0] = 0;
3487:   for (i=2; i<=size; i++) rowners[i] += rowners[i-1];
3488:   for (i=0; i<=size; i++) browners[i] = rowners[i]*bs;
3489:   rstart = rowners[rank];
3490:   rend   = rowners[rank+1];

3492:   /* distribute row lengths to all processors */
3493:   PetscMalloc1(m,&locrowlens);
3494:   if (!rank) {
3495:     mend = m;
3496:     if (size == 1) mend = mend - extra_rows;
3497:     PetscBinaryRead(fd,locrowlens,mend,PETSC_INT);
3498:     for (j=mend; j<m; j++) locrowlens[j] = 1;
3499:     PetscMalloc1(mmax,&rowlengths);
3500:     PetscCalloc1(size,&procsnz);
3501:     for (j=0; j<m; j++) {
3502:       procsnz[0] += locrowlens[j];
3503:     }
3504:     for (i=1; i<size; i++) {
3505:       mend = browners[i+1] - browners[i];
3506:       if (i == size-1) mend = mend - extra_rows;
3507:       PetscBinaryRead(fd,rowlengths,mend,PETSC_INT);
3508:       for (j=mend; j<browners[i+1] - browners[i]; j++) rowlengths[j] = 1;
3509:       /* calculate the number of nonzeros on each processor */
3510:       for (j=0; j<browners[i+1]-browners[i]; j++) {
3511:         procsnz[i] += rowlengths[j];
3512:       }
3513:       MPI_Send(rowlengths,browners[i+1]-browners[i],MPIU_INT,i,tag,comm);
3514:     }
3515:     PetscFree(rowlengths);
3516:   } else {
3517:     MPI_Recv(locrowlens,m,MPIU_INT,0,tag,comm,&status);
3518:   }

3520:   if (!rank) {
3521:     /* determine max buffer needed and allocate it */
3522:     maxnz = procsnz[0];
3523:     for (i=1; i<size; i++) {
3524:       maxnz = PetscMax(maxnz,procsnz[i]);
3525:     }
3526:     PetscMalloc1(maxnz,&cols);

3528:     /* read in my part of the matrix column indices  */
3529:     nz     = procsnz[0];
3530:     PetscMalloc1(nz+1,&ibuf);
3531:     mycols = ibuf;
3532:     if (size == 1) nz -= extra_rows;
3533:     PetscBinaryRead(fd,mycols,nz,PETSC_INT);
3534:     if (size == 1) {
3535:       for (i=0; i< extra_rows; i++) mycols[nz+i] = M+i;
3536:     }

3538:     /* read in every ones (except the last) and ship off */
3539:     for (i=1; i<size-1; i++) {
3540:       nz   = procsnz[i];
3541:       PetscBinaryRead(fd,cols,nz,PETSC_INT);
3542:       MPI_Send(cols,nz,MPIU_INT,i,tag,comm);
3543:     }
3544:     /* read in the stuff for the last proc */
3545:     if (size != 1) {
3546:       nz   = procsnz[size-1] - extra_rows;  /* the extra rows are not on the disk */
3547:       PetscBinaryRead(fd,cols,nz,PETSC_INT);
3548:       for (i=0; i<extra_rows; i++) cols[nz+i] = M+i;
3549:       MPI_Send(cols,nz+extra_rows,MPIU_INT,size-1,tag,comm);
3550:     }
3551:     PetscFree(cols);
3552:   } else {
3553:     /* determine buffer space needed for message */
3554:     nz = 0;
3555:     for (i=0; i<m; i++) {
3556:       nz += locrowlens[i];
3557:     }
3558:     PetscMalloc1(nz+1,&ibuf);
3559:     mycols = ibuf;
3560:     /* receive message of column indices*/
3561:     MPI_Recv(mycols,nz,MPIU_INT,0,tag,comm,&status);
3562:     MPI_Get_count(&status,MPIU_INT,&maxnz);
3563:     if (maxnz != nz) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file");
3564:   }

3566:   /* loop over local rows, determining number of off diagonal entries */
3567:   PetscMalloc2(rend-rstart,&dlens,rend-rstart,&odlens);
3568:   PetscCalloc3(Mbs,&mask,Mbs,&masked1,Mbs,&masked2);
3569:   rowcount = 0; nzcount = 0;
3570:   for (i=0; i<mbs; i++) {
3571:     dcount  = 0;
3572:     odcount = 0;
3573:     for (j=0; j<bs; j++) {
3574:       kmax = locrowlens[rowcount];
3575:       for (k=0; k<kmax; k++) {
3576:         tmp = mycols[nzcount++]/bs;
3577:         if (!mask[tmp]) {
3578:           mask[tmp] = 1;
3579:           if (tmp < rstart || tmp >= rend) masked2[odcount++] = tmp;
3580:           else masked1[dcount++] = tmp;
3581:         }
3582:       }
3583:       rowcount++;
3584:     }

3586:     dlens[i]  = dcount;
3587:     odlens[i] = odcount;

3589:     /* zero out the mask elements we set */
3590:     for (j=0; j<dcount; j++) mask[masked1[j]] = 0;
3591:     for (j=0; j<odcount; j++) mask[masked2[j]] = 0;
3592:   }

3594:   MatSetSizes(newmat,m,m,M+extra_rows,N+extra_rows);
3595:   MatMPIBAIJSetPreallocation(newmat,bs,0,dlens,0,odlens);

3597:   if (!rank) {
3598:     PetscMalloc1(maxnz+1,&buf);
3599:     /* read in my part of the matrix numerical values  */
3600:     nz     = procsnz[0];
3601:     vals   = buf;
3602:     mycols = ibuf;
3603:     if (size == 1) nz -= extra_rows;
3604:     PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);
3605:     if (size == 1) {
3606:       for (i=0; i< extra_rows; i++) vals[nz+i] = 1.0;
3607:     }

3609:     /* insert into matrix */
3610:     jj = rstart*bs;
3611:     for (i=0; i<m; i++) {
3612:       MatSetValues_MPIBAIJ(newmat,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);
3613:       mycols += locrowlens[i];
3614:       vals   += locrowlens[i];
3615:       jj++;
3616:     }
3617:     /* read in other processors (except the last one) and ship out */
3618:     for (i=1; i<size-1; i++) {
3619:       nz   = procsnz[i];
3620:       vals = buf;
3621:       PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);
3622:       MPIULong_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newmat)->tag,comm);
3623:     }
3624:     /* the last proc */
3625:     if (size != 1) {
3626:       nz   = procsnz[i] - extra_rows;
3627:       vals = buf;
3628:       PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);
3629:       for (i=0; i<extra_rows; i++) vals[nz+i] = 1.0;
3630:       MPIULong_Send(vals,nz+extra_rows,MPIU_SCALAR,size-1,((PetscObject)newmat)->tag,comm);
3631:     }
3632:     PetscFree(procsnz);
3633:   } else {
3634:     /* receive numeric values */
3635:     PetscMalloc1(nz+1,&buf);

3637:     /* receive message of values*/
3638:     vals   = buf;
3639:     mycols = ibuf;
3640:     MPIULong_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newmat)->tag,comm);

3642:     /* insert into matrix */
3643:     jj = rstart*bs;
3644:     for (i=0; i<m; i++) {
3645:       MatSetValues_MPIBAIJ(newmat,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);
3646:       mycols += locrowlens[i];
3647:       vals   += locrowlens[i];
3648:       jj++;
3649:     }
3650:   }
3651:   PetscFree(locrowlens);
3652:   PetscFree(buf);
3653:   PetscFree(ibuf);
3654:   PetscFree2(rowners,browners);
3655:   PetscFree2(dlens,odlens);
3656:   PetscFree3(mask,masked1,masked2);
3657:   MatAssemblyBegin(newmat,MAT_FINAL_ASSEMBLY);
3658:   MatAssemblyEnd(newmat,MAT_FINAL_ASSEMBLY);
3659:   return(0);
3660: }

3662: /*@
3663:    MatMPIBAIJSetHashTableFactor - Sets the factor required to compute the size of the HashTable.

3665:    Input Parameters:
3666: .  mat  - the matrix
3667: .  fact - factor

3669:    Not Collective, each process can use a different factor

3671:    Level: advanced

3673:   Notes:
3674:    This can also be set by the command line option: -mat_use_hash_table <fact>

3676: .keywords: matrix, hashtable, factor, HT

3678: .seealso: MatSetOption()
3679: @*/
3680: PetscErrorCode  MatMPIBAIJSetHashTableFactor(Mat mat,PetscReal fact)
3681: {

3685:   PetscTryMethod(mat,"MatSetHashTableFactor_C",(Mat,PetscReal),(mat,fact));
3686:   return(0);
3687: }

3689: PetscErrorCode  MatSetHashTableFactor_MPIBAIJ(Mat mat,PetscReal fact)
3690: {
3691:   Mat_MPIBAIJ *baij;

3694:   baij          = (Mat_MPIBAIJ*)mat->data;
3695:   baij->ht_fact = fact;
3696:   return(0);
3697: }

3699: PetscErrorCode  MatMPIBAIJGetSeqBAIJ(Mat A,Mat *Ad,Mat *Ao,const PetscInt *colmap[])
3700: {
3701:   Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data;

3704:   if (Ad)     *Ad     = a->A;
3705:   if (Ao)     *Ao     = a->B;
3706:   if (colmap) *colmap = a->garray;
3707:   return(0);
3708: }

3710: /*
3711:     Special version for direct calls from Fortran (to eliminate two function call overheads
3712: */
3713: #if defined(PETSC_HAVE_FORTRAN_CAPS)
3714: #define matmpibaijsetvaluesblocked_ MATMPIBAIJSETVALUESBLOCKED
3715: #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE)
3716: #define matmpibaijsetvaluesblocked_ matmpibaijsetvaluesblocked
3717: #endif

3719: /*@C
3720:   MatMPIBAIJSetValuesBlocked - Direct Fortran call to replace call to MatSetValuesBlocked()

3722:   Collective on Mat

3724:   Input Parameters:
3725: + mat - the matrix
3726: . min - number of input rows
3727: . im - input rows
3728: . nin - number of input columns
3729: . in - input columns
3730: . v - numerical values input
3731: - addvin - INSERT_VALUES or ADD_VALUES

3733:   Notes: This has a complete copy of MatSetValuesBlocked_MPIBAIJ() which is terrible code un-reuse.

3735:   Level: advanced

3737: .seealso:   MatSetValuesBlocked()
3738: @*/
3739: PetscErrorCode matmpibaijsetvaluesblocked_(Mat *matin,PetscInt *min,const PetscInt im[],PetscInt *nin,const PetscInt in[],const MatScalar v[],InsertMode *addvin)
3740: {
3741:   /* convert input arguments to C version */
3742:   Mat        mat  = *matin;
3743:   PetscInt   m    = *min, n = *nin;
3744:   InsertMode addv = *addvin;

3746:   Mat_MPIBAIJ     *baij = (Mat_MPIBAIJ*)mat->data;
3747:   const MatScalar *value;
3748:   MatScalar       *barray     = baij->barray;
3749:   PetscBool       roworiented = baij->roworiented;
3750:   PetscErrorCode  ierr;
3751:   PetscInt        i,j,ii,jj,row,col,rstart=baij->rstartbs;
3752:   PetscInt        rend=baij->rendbs,cstart=baij->cstartbs,stepval;
3753:   PetscInt        cend=baij->cendbs,bs=mat->rmap->bs,bs2=baij->bs2;

3756:   /* tasks normally handled by MatSetValuesBlocked() */
3757:   if (mat->insertmode == NOT_SET_VALUES) mat->insertmode = addv;
3758: #if defined(PETSC_USE_DEBUG)
3759:   else if (mat->insertmode != addv) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values");
3760:   if (mat->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix");
3761: #endif
3762:   if (mat->assembled) {
3763:     mat->was_assembled = PETSC_TRUE;
3764:     mat->assembled     = PETSC_FALSE;
3765:   }
3766:   PetscLogEventBegin(MAT_SetValues,mat,0,0,0);


3769:   if (!barray) {
3770:     PetscMalloc1(bs2,&barray);
3771:     baij->barray = barray;
3772:   }

3774:   if (roworiented) stepval = (n-1)*bs;
3775:   else stepval = (m-1)*bs;

3777:   for (i=0; i<m; i++) {
3778:     if (im[i] < 0) continue;
3779: #if defined(PETSC_USE_DEBUG)
3780:     if (im[i] >= baij->Mbs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large, row %D max %D",im[i],baij->Mbs-1);
3781: #endif
3782:     if (im[i] >= rstart && im[i] < rend) {
3783:       row = im[i] - rstart;
3784:       for (j=0; j<n; j++) {
3785:         /* If NumCol = 1 then a copy is not required */
3786:         if ((roworiented) && (n == 1)) {
3787:           barray = (MatScalar*)v + i*bs2;
3788:         } else if ((!roworiented) && (m == 1)) {
3789:           barray = (MatScalar*)v + j*bs2;
3790:         } else { /* Here a copy is required */
3791:           if (roworiented) {
3792:             value = v + i*(stepval+bs)*bs + j*bs;
3793:           } else {
3794:             value = v + j*(stepval+bs)*bs + i*bs;
3795:           }
3796:           for (ii=0; ii<bs; ii++,value+=stepval) {
3797:             for (jj=0; jj<bs; jj++) {
3798:               *barray++ = *value++;
3799:             }
3800:           }
3801:           barray -=bs2;
3802:         }

3804:         if (in[j] >= cstart && in[j] < cend) {
3805:           col  = in[j] - cstart;
3806:           MatSetValuesBlocked_SeqBAIJ_Inlined(baij->A,row,col,barray,addv,im[i],in[j]);
3807:         } else if (in[j] < 0) continue;
3808: #if defined(PETSC_USE_DEBUG)
3809:         else if (in[j] >= baij->Nbs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large, col %D max %D",in[j],baij->Nbs-1);
3810: #endif
3811:         else {
3812:           if (mat->was_assembled) {
3813:             if (!baij->colmap) {
3814:               MatCreateColmap_MPIBAIJ_Private(mat);
3815:             }

3817: #if defined(PETSC_USE_DEBUG)
3818: #if defined(PETSC_USE_CTABLE)
3819:             { PetscInt data;
3820:               PetscTableFind(baij->colmap,in[j]+1,&data);
3821:               if ((data - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap");
3822:             }
3823: #else
3824:             if ((baij->colmap[in[j]] - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap");
3825: #endif
3826: #endif
3827: #if defined(PETSC_USE_CTABLE)
3828:             PetscTableFind(baij->colmap,in[j]+1,&col);
3829:             col  = (col - 1)/bs;
3830: #else
3831:             col = (baij->colmap[in[j]] - 1)/bs;
3832: #endif
3833:             if (col < 0 && !((Mat_SeqBAIJ*)(baij->A->data))->nonew) {
3834:               MatDisAssemble_MPIBAIJ(mat);
3835:               col  =  in[j];
3836:             }
3837:           } else col = in[j];
3838:           MatSetValuesBlocked_SeqBAIJ_Inlined(baij->B,row,col,barray,addv,im[i],in[j]);
3839:         }
3840:       }
3841:     } else {
3842:       if (!baij->donotstash) {
3843:         if (roworiented) {
3844:           MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);
3845:         } else {
3846:           MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);
3847:         }
3848:       }
3849:     }
3850:   }

3852:   /* task normally handled by MatSetValuesBlocked() */
3853:   PetscLogEventEnd(MAT_SetValues,mat,0,0,0);
3854:   return(0);
3855: }

3857: /*@
3858:      MatCreateMPIBAIJWithArrays - creates a MPI BAIJ matrix using arrays that contain in standard
3859:          CSR format the local rows.

3861:    Collective on MPI_Comm

3863:    Input Parameters:
3864: +  comm - MPI communicator
3865: .  bs - the block size, only a block size of 1 is supported
3866: .  m - number of local rows (Cannot be PETSC_DECIDE)
3867: .  n - This value should be the same as the local size used in creating the
3868:        x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have
3869:        calculated if N is given) For square matrices n is almost always m.
3870: .  M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
3871: .  N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
3872: .   i - row indices
3873: .   j - column indices
3874: -   a - matrix values

3876:    Output Parameter:
3877: .   mat - the matrix

3879:    Level: intermediate

3881:    Notes:
3882:        The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc;
3883:      thus you CANNOT change the matrix entries by changing the values of a[] after you have
3884:      called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays.

3886:      The order of the entries in values is the same as the block compressed sparse row storage format; that is, it is
3887:      the same as a three dimensional array in Fortran values(bs,bs,nnz) that contains the first column of the first
3888:      block, followed by the second column of the first block etc etc.  That is, the blocks are contiguous in memory
3889:      with column-major ordering within blocks.

3891:        The i and j indices are 0 based, and i indices are indices corresponding to the local j array.

3893: .keywords: matrix, aij, compressed row, sparse, parallel

3895: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(),
3896:           MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays()
3897: @*/
3898: PetscErrorCode  MatCreateMPIBAIJWithArrays(MPI_Comm comm,PetscInt bs,PetscInt m,PetscInt n,PetscInt M,PetscInt N,const PetscInt i[],const PetscInt j[],const PetscScalar a[],Mat *mat)
3899: {

3903:   if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0");
3904:   if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative");
3905:   MatCreate(comm,mat);
3906:   MatSetSizes(*mat,m,n,M,N);
3907:   MatSetType(*mat,MATMPIBAIJ);
3908:   MatSetBlockSize(*mat,bs);
3909:   MatSetUp(*mat);
3910:   MatSetOption(*mat,MAT_ROW_ORIENTED,PETSC_FALSE);
3911:   MatMPIBAIJSetPreallocationCSR(*mat,bs,i,j,a);
3912:   MatSetOption(*mat,MAT_ROW_ORIENTED,PETSC_TRUE);
3913:   return(0);
3914: }

3916: PetscErrorCode MatCreateMPIMatConcatenateSeqMat_MPIBAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat)
3917: {
3919:   PetscInt       m,N,i,rstart,nnz,Ii,bs,cbs;
3920:   PetscInt       *indx;
3921:   PetscScalar    *values;

3924:   MatGetSize(inmat,&m,&N);
3925:   if (scall == MAT_INITIAL_MATRIX) { /* symbolic phase */
3926:     Mat_SeqBAIJ    *a = (Mat_SeqBAIJ*)inmat->data;
3927:     PetscInt       *dnz,*onz,mbs,Nbs,nbs;
3928:     PetscInt       *bindx,rmax=a->rmax,j;
3929:     PetscMPIInt    rank,size;

3931:     MatGetBlockSizes(inmat,&bs,&cbs);
3932:     mbs = m/bs; Nbs = N/cbs;
3933:     if (n == PETSC_DECIDE) {
3934:       nbs  = n;
3935:       PetscSplitOwnership(comm,&nbs,&Nbs);
3936:       n    = nbs*cbs;
3937:     } else {
3938:       nbs = n/cbs;
3939:     }

3941:     PetscMalloc1(rmax,&bindx);
3942:     MatPreallocateInitialize(comm,mbs,nbs,dnz,onz); /* inline function, output __end and __rstart are used below */

3944:     MPI_Comm_rank(comm,&rank);
3945:     MPI_Comm_rank(comm,&size);
3946:     if (rank == size-1) {
3947:       /* Check sum(nbs) = Nbs */
3948:       if (__end != Nbs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Sum of local block columns %D != global block columns %D",__end,Nbs);
3949:     }

3951:     rstart = __rstart; /* block rstart of *outmat; see inline function MatPreallocateInitialize */
3952:     for (i=0; i<mbs; i++) {
3953:       MatGetRow_SeqBAIJ(inmat,i*bs,&nnz,&indx,NULL); /* non-blocked nnz and indx */
3954:       nnz = nnz/bs;
3955:       for (j=0; j<nnz; j++) bindx[j] = indx[j*bs]/bs;
3956:       MatPreallocateSet(i+rstart,nnz,bindx,dnz,onz);
3957:       MatRestoreRow_SeqBAIJ(inmat,i*bs,&nnz,&indx,NULL);
3958:     }
3959:     PetscFree(bindx);

3961:     MatCreate(comm,outmat);
3962:     MatSetSizes(*outmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);
3963:     MatSetBlockSizes(*outmat,bs,cbs);
3964:     MatSetType(*outmat,MATBAIJ);
3965:     MatSeqBAIJSetPreallocation(*outmat,bs,0,dnz);
3966:     MatMPIBAIJSetPreallocation(*outmat,bs,0,dnz,0,onz);
3967:     MatPreallocateFinalize(dnz,onz);
3968:   }

3970:   /* numeric phase */
3971:   MatGetBlockSizes(inmat,&bs,&cbs);
3972:   MatGetOwnershipRange(*outmat,&rstart,NULL);

3974:   for (i=0; i<m; i++) {
3975:     MatGetRow_SeqBAIJ(inmat,i,&nnz,&indx,&values);
3976:     Ii   = i + rstart;
3977:     MatSetValues(*outmat,1,&Ii,nnz,indx,values,INSERT_VALUES);
3978:     MatRestoreRow_SeqBAIJ(inmat,i,&nnz,&indx,&values);
3979:   }
3980:   MatAssemblyBegin(*outmat,MAT_FINAL_ASSEMBLY);
3981:   MatAssemblyEnd(*outmat,MAT_FINAL_ASSEMBLY);
3982:   return(0);
3983: }