Actual source code: mpibaij.c

petsc-3.4.4 2014-03-13
  2: #include <../src/mat/impls/baij/mpi/mpibaij.h>   /*I  "petscmat.h"  I*/
  3: #include <petscblaslapack.h>

  5: extern PetscErrorCode MatSetUpMultiply_MPIBAIJ(Mat);
  6: extern PetscErrorCode MatDisAssemble_MPIBAIJ(Mat);
  7: extern PetscErrorCode MatGetValues_SeqBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt [],PetscScalar []);
  8: extern PetscErrorCode MatSetValues_SeqBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt [],const PetscScalar [],InsertMode);
  9: extern PetscErrorCode MatSetValuesBlocked_SeqBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const PetscScalar[],InsertMode);
 10: extern PetscErrorCode MatGetRow_SeqBAIJ(Mat,PetscInt,PetscInt*,PetscInt*[],PetscScalar*[]);
 11: extern PetscErrorCode MatRestoreRow_SeqBAIJ(Mat,PetscInt,PetscInt*,PetscInt*[],PetscScalar*[]);
 12: extern PetscErrorCode MatZeroRows_SeqBAIJ(Mat,PetscInt,const PetscInt[],PetscScalar,Vec,Vec);

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

 25:   MatGetRowMaxAbs(a->A,v,idx);
 26:   VecGetArray(v,&va);
 27:   if (idx) {
 28:     for (i=0; i<A->rmap->n; i++) {
 29:       if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart;
 30:     }
 31:   }

 33:   VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);
 34:   if (idx) {PetscMalloc(A->rmap->n*sizeof(PetscInt),&idxb);}
 35:   MatGetRowMaxAbs(a->B,vtmp,idxb);
 36:   VecGetArray(vtmp,&vb);

 38:   for (i=0; i<A->rmap->n; i++) {
 39:     if (PetscAbsScalar(va[i]) < PetscAbsScalar(vb[i])) {
 40:       va[i] = vb[i];
 41:       if (idx) idx[i] = A->cmap->bs*a->garray[idxb[i]/A->cmap->bs] + (idxb[i] % A->cmap->bs);
 42:     }
 43:   }

 45:   VecRestoreArray(v,&va);
 46:   VecRestoreArray(vtmp,&vb);
 47:   PetscFree(idxb);
 48:   VecDestroy(&vtmp);
 49:   return(0);
 50: }

 54: PetscErrorCode  MatStoreValues_MPIBAIJ(Mat mat)
 55: {
 56:   Mat_MPIBAIJ    *aij = (Mat_MPIBAIJ*)mat->data;

 60:   MatStoreValues(aij->A);
 61:   MatStoreValues(aij->B);
 62:   return(0);
 63: }

 67: PetscErrorCode  MatRetrieveValues_MPIBAIJ(Mat mat)
 68: {
 69:   Mat_MPIBAIJ    *aij = (Mat_MPIBAIJ*)mat->data;

 73:   MatRetrieveValues(aij->A);
 74:   MatRetrieveValues(aij->B);
 75:   return(0);
 76: }

 78: /*
 79:      Local utility routine that creates a mapping from the global column
 80:    number to the local number in the off-diagonal part of the local
 81:    storage of the matrix.  This is done in a non scalable way since the
 82:    length of colmap equals the global matrix length.
 83: */
 86: PetscErrorCode MatCreateColmap_MPIBAIJ_Private(Mat mat)
 87: {
 88:   Mat_MPIBAIJ    *baij = (Mat_MPIBAIJ*)mat->data;
 89:   Mat_SeqBAIJ    *B    = (Mat_SeqBAIJ*)baij->B->data;
 91:   PetscInt       nbs = B->nbs,i,bs=mat->rmap->bs;

 94: #if defined(PETSC_USE_CTABLE)
 95:   PetscTableCreate(baij->nbs,baij->Nbs+1,&baij->colmap);
 96:   for (i=0; i<nbs; i++) {
 97:     PetscTableAdd(baij->colmap,baij->garray[i]+1,i*bs+1,INSERT_VALUES);
 98:   }
 99: #else
100:   PetscMalloc((baij->Nbs+1)*sizeof(PetscInt),&baij->colmap);
101:   PetscLogObjectMemory(mat,baij->Nbs*sizeof(PetscInt));
102:   PetscMemzero(baij->colmap,baij->Nbs*sizeof(PetscInt));
103:   for (i=0; i<nbs; i++) baij->colmap[baij->garray[i]] = i*bs+1;
104: #endif
105:   return(0);
106: }

108: #define  MatSetValues_SeqBAIJ_A_Private(row,col,value,addv) \
109:   { \
110:  \
111:     brow = row/bs;  \
112:     rp   = aj + ai[brow]; ap = aa + bs2*ai[brow]; \
113:     rmax = aimax[brow]; nrow = ailen[brow]; \
114:     bcol = col/bs; \
115:     ridx = row % bs; cidx = col % bs; \
116:     low  = 0; high = nrow; \
117:     while (high-low > 3) { \
118:       t = (low+high)/2; \
119:       if (rp[t] > bcol) high = t; \
120:       else              low  = t; \
121:     } \
122:     for (_i=low; _i<high; _i++) { \
123:       if (rp[_i] > bcol) break; \
124:       if (rp[_i] == bcol) { \
125:         bap = ap +  bs2*_i + bs*cidx + ridx; \
126:         if (addv == ADD_VALUES) *bap += value;  \
127:         else                    *bap  = value;  \
128:         goto a_noinsert; \
129:       } \
130:     } \
131:     if (a->nonew == 1) goto a_noinsert; \
132:     if (a->nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \
133:     MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,brow,bcol,rmax,aa,ai,aj,rp,ap,aimax,a->nonew,MatScalar); \
134:     N = nrow++ - 1;  \
135:     /* shift up all the later entries in this row */ \
136:     for (ii=N; ii>=_i; ii--) { \
137:       rp[ii+1] = rp[ii]; \
138:       PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar)); \
139:     } \
140:     if (N>=_i) { PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar)); }  \
141:     rp[_i]                      = bcol;  \
142:     ap[bs2*_i + bs*cidx + ridx] = value;  \
143: a_noinsert:; \
144:     ailen[brow] = nrow; \
145:   }

147: #define  MatSetValues_SeqBAIJ_B_Private(row,col,value,addv) \
148:   { \
149:     brow = row/bs;  \
150:     rp   = bj + bi[brow]; ap = ba + bs2*bi[brow]; \
151:     rmax = bimax[brow]; nrow = bilen[brow]; \
152:     bcol = col/bs; \
153:     ridx = row % bs; cidx = col % bs; \
154:     low  = 0; high = nrow; \
155:     while (high-low > 3) { \
156:       t = (low+high)/2; \
157:       if (rp[t] > bcol) high = t; \
158:       else              low  = t; \
159:     } \
160:     for (_i=low; _i<high; _i++) { \
161:       if (rp[_i] > bcol) break; \
162:       if (rp[_i] == bcol) { \
163:         bap = ap +  bs2*_i + bs*cidx + ridx; \
164:         if (addv == ADD_VALUES) *bap += value;  \
165:         else                    *bap  = value;  \
166:         goto b_noinsert; \
167:       } \
168:     } \
169:     if (b->nonew == 1) goto b_noinsert; \
170:     if (b->nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \
171:     MatSeqXAIJReallocateAIJ(B,b->mbs,bs2,nrow,brow,bcol,rmax,ba,bi,bj,rp,ap,bimax,b->nonew,MatScalar); \
172:     N = nrow++ - 1;  \
173:     /* shift up all the later entries in this row */ \
174:     for (ii=N; ii>=_i; ii--) { \
175:       rp[ii+1] = rp[ii]; \
176:       PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar)); \
177:     } \
178:     if (N>=_i) { PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar));}  \
179:     rp[_i]                      = bcol;  \
180:     ap[bs2*_i + bs*cidx + ridx] = value;  \
181: b_noinsert:; \
182:     bilen[brow] = nrow; \
183:   }

187: PetscErrorCode MatSetValues_MPIBAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv)
188: {
189:   Mat_MPIBAIJ    *baij = (Mat_MPIBAIJ*)mat->data;
190:   MatScalar      value;
191:   PetscBool      roworiented = baij->roworiented;
193:   PetscInt       i,j,row,col;
194:   PetscInt       rstart_orig=mat->rmap->rstart;
195:   PetscInt       rend_orig  =mat->rmap->rend,cstart_orig=mat->cmap->rstart;
196:   PetscInt       cend_orig  =mat->cmap->rend,bs=mat->rmap->bs;

198:   /* Some Variables required in the macro */
199:   Mat         A     = baij->A;
200:   Mat_SeqBAIJ *a    = (Mat_SeqBAIJ*)(A)->data;
201:   PetscInt    *aimax=a->imax,*ai=a->i,*ailen=a->ilen,*aj=a->j;
202:   MatScalar   *aa   =a->a;

204:   Mat         B     = baij->B;
205:   Mat_SeqBAIJ *b    = (Mat_SeqBAIJ*)(B)->data;
206:   PetscInt    *bimax=b->imax,*bi=b->i,*bilen=b->ilen,*bj=b->j;
207:   MatScalar   *ba   =b->a;

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

215:   for (i=0; i<m; i++) {
216:     if (im[i] < 0) continue;
217: #if defined(PETSC_USE_DEBUG)
218:     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);
219: #endif
220:     if (im[i] >= rstart_orig && im[i] < rend_orig) {
221:       row = im[i] - rstart_orig;
222:       for (j=0; j<n; j++) {
223:         if (in[j] >= cstart_orig && in[j] < cend_orig) {
224:           col = in[j] - cstart_orig;
225:           if (roworiented) value = v[i*n+j];
226:           else             value = v[i+j*m];
227:           MatSetValues_SeqBAIJ_A_Private(row,col,value,addv);
228:           /* MatSetValues_SeqBAIJ(baij->A,1,&row,1,&col,&value,addv); */
229:         } else if (in[j] < 0) continue;
230: #if defined(PETSC_USE_DEBUG)
231:         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);
232: #endif
233:         else {
234:           if (mat->was_assembled) {
235:             if (!baij->colmap) {
236:               MatCreateColmap_MPIBAIJ_Private(mat);
237:             }
238: #if defined(PETSC_USE_CTABLE)
239:             PetscTableFind(baij->colmap,in[j]/bs + 1,&col);
240:             col  = col - 1;
241: #else
242:             col = baij->colmap[in[j]/bs] - 1;
243: #endif
244:             if (col < 0 && !((Mat_SeqBAIJ*)(baij->B->data))->nonew) {
245:               MatDisAssemble_MPIBAIJ(mat);
246:               col  =  in[j];
247:               /* Reinitialize the variables required by MatSetValues_SeqBAIJ_B_Private() */
248:               B    = baij->B;
249:               b    = (Mat_SeqBAIJ*)(B)->data;
250:               bimax=b->imax;bi=b->i;bilen=b->ilen;bj=b->j;
251:               ba   =b->a;
252:             } else if (col < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", im[i], in[j]);
253:             else col += in[j]%bs;
254:           } else col = in[j];
255:           if (roworiented) value = v[i*n+j];
256:           else             value = v[i+j*m];
257:           MatSetValues_SeqBAIJ_B_Private(row,col,value,addv);
258:           /* MatSetValues_SeqBAIJ(baij->B,1,&row,1,&col,&value,addv); */
259:         }
260:       }
261:     } else {
262:       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]);
263:       if (!baij->donotstash) {
264:         mat->assembled = PETSC_FALSE;
265:         if (roworiented) {
266:           MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,PETSC_FALSE);
267:         } else {
268:           MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,PETSC_FALSE);
269:         }
270:       }
271:     }
272:   }
273:   return(0);
274: }

278: PetscErrorCode MatSetValuesBlocked_MPIBAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv)
279: {
280:   Mat_MPIBAIJ       *baij = (Mat_MPIBAIJ*)mat->data;
281:   const PetscScalar *value;
282:   MatScalar         *barray     = baij->barray;
283:   PetscBool         roworiented = baij->roworiented;
284:   PetscErrorCode    ierr;
285:   PetscInt          i,j,ii,jj,row,col,rstart=baij->rstartbs;
286:   PetscInt          rend=baij->rendbs,cstart=baij->cstartbs,stepval;
287:   PetscInt          cend=baij->cendbs,bs=mat->rmap->bs,bs2=baij->bs2;

290:   if (!barray) {
291:     PetscMalloc(bs2*sizeof(MatScalar),&barray);
292:     baij->barray = barray;
293:   }

295:   if (roworiented) stepval = (n-1)*bs;
296:   else stepval = (m-1)*bs;

298:   for (i=0; i<m; i++) {
299:     if (im[i] < 0) continue;
300: #if defined(PETSC_USE_DEBUG)
301:     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);
302: #endif
303:     if (im[i] >= rstart && im[i] < rend) {
304:       row = im[i] - rstart;
305:       for (j=0; j<n; j++) {
306:         /* If NumCol = 1 then a copy is not required */
307:         if ((roworiented) && (n == 1)) {
308:           barray = (MatScalar*)v + i*bs2;
309:         } else if ((!roworiented) && (m == 1)) {
310:           barray = (MatScalar*)v + j*bs2;
311:         } else { /* Here a copy is required */
312:           if (roworiented) {
313:             value = v + (i*(stepval+bs) + j)*bs;
314:           } else {
315:             value = v + (j*(stepval+bs) + i)*bs;
316:           }
317:           for (ii=0; ii<bs; ii++,value+=bs+stepval) {
318:             for (jj=0; jj<bs; jj++) barray[jj] = value[jj];
319:             barray += bs;
320:           }
321:           barray -= bs2;
322:         }

324:         if (in[j] >= cstart && in[j] < cend) {
325:           col  = in[j] - cstart;
326:           MatSetValuesBlocked_SeqBAIJ(baij->A,1,&row,1,&col,barray,addv);
327:         } else if (in[j] < 0) continue;
328: #if defined(PETSC_USE_DEBUG)
329:         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);
330: #endif
331:         else {
332:           if (mat->was_assembled) {
333:             if (!baij->colmap) {
334:               MatCreateColmap_MPIBAIJ_Private(mat);
335:             }

337: #if defined(PETSC_USE_DEBUG)
338: #if defined(PETSC_USE_CTABLE)
339:             { PetscInt data;
340:               PetscTableFind(baij->colmap,in[j]+1,&data);
341:               if ((data - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap");
342:             }
343: #else
344:             if ((baij->colmap[in[j]] - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap");
345: #endif
346: #endif
347: #if defined(PETSC_USE_CTABLE)
348:             PetscTableFind(baij->colmap,in[j]+1,&col);
349:             col  = (col - 1)/bs;
350: #else
351:             col = (baij->colmap[in[j]] - 1)/bs;
352: #endif
353:             if (col < 0 && !((Mat_SeqBAIJ*)(baij->B->data))->nonew) {
354:               MatDisAssemble_MPIBAIJ(mat);
355:               col  =  in[j];
356:             } else if (col < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", bs*im[i], bs*in[j]);
357:           } else col = in[j];
358:           MatSetValuesBlocked_SeqBAIJ(baij->B,1,&row,1,&col,barray,addv);
359:         }
360:       }
361:     } else {
362:       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]);
363:       if (!baij->donotstash) {
364:         if (roworiented) {
365:           MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);
366:         } else {
367:           MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);
368:         }
369:       }
370:     }
371:   }
372:   return(0);
373: }

375: #define HASH_KEY 0.6180339887
376: #define HASH(size,key,tmp) (tmp = (key)*HASH_KEY,(PetscInt)((size)*(tmp-(PetscInt)tmp)))
377: /* #define HASH(size,key) ((PetscInt)((size)*fmod(((key)*HASH_KEY),1))) */
378: /* #define HASH(size,key,tmp) ((PetscInt)((size)*fmod(((key)*HASH_KEY),1))) */
381: PetscErrorCode MatSetValues_MPIBAIJ_HT(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv)
382: {
383:   Mat_MPIBAIJ    *baij       = (Mat_MPIBAIJ*)mat->data;
384:   PetscBool      roworiented = baij->roworiented;
386:   PetscInt       i,j,row,col;
387:   PetscInt       rstart_orig=mat->rmap->rstart;
388:   PetscInt       rend_orig  =mat->rmap->rend,Nbs=baij->Nbs;
389:   PetscInt       h1,key,size=baij->ht_size,bs=mat->rmap->bs,*HT=baij->ht,idx;
390:   PetscReal      tmp;
391:   MatScalar      **HD = baij->hd,value;
392: #if defined(PETSC_USE_DEBUG)
393:   PetscInt total_ct=baij->ht_total_ct,insert_ct=baij->ht_insert_ct;
394: #endif

398:   for (i=0; i<m; i++) {
399: #if defined(PETSC_USE_DEBUG)
400:     if (im[i] < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row");
401:     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);
402: #endif
403:     row = im[i];
404:     if (row >= rstart_orig && row < rend_orig) {
405:       for (j=0; j<n; j++) {
406:         col = in[j];
407:         if (roworiented) value = v[i*n+j];
408:         else             value = v[i+j*m];
409:         /* Look up PetscInto the Hash Table */
410:         key = (row/bs)*Nbs+(col/bs)+1;
411:         h1  = HASH(size,key,tmp);


414:         idx = h1;
415: #if defined(PETSC_USE_DEBUG)
416:         insert_ct++;
417:         total_ct++;
418:         if (HT[idx] != key) {
419:           for (idx=h1; (idx<size) && (HT[idx]!=key); idx++,total_ct++) ;
420:           if (idx == size) {
421:             for (idx=0; (idx<h1) && (HT[idx]!=key); idx++,total_ct++) ;
422:             if (idx == h1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"(%D,%D) has no entry in the hash table", row, col);
423:           }
424:         }
425: #else
426:         if (HT[idx] != key) {
427:           for (idx=h1; (idx<size) && (HT[idx]!=key); idx++) ;
428:           if (idx == size) {
429:             for (idx=0; (idx<h1) && (HT[idx]!=key); idx++) ;
430:             if (idx == h1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"(%D,%D) has no entry in the hash table", row, col);
431:           }
432:         }
433: #endif
434:         /* A HASH table entry is found, so insert the values at the correct address */
435:         if (addv == ADD_VALUES) *(HD[idx]+ (col % bs)*bs + (row % bs)) += value;
436:         else                    *(HD[idx]+ (col % bs)*bs + (row % bs))  = value;
437:       }
438:     } else if (!baij->donotstash) {
439:       if (roworiented) {
440:         MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,PETSC_FALSE);
441:       } else {
442:         MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,PETSC_FALSE);
443:       }
444:     }
445:   }
446: #if defined(PETSC_USE_DEBUG)
447:   baij->ht_total_ct  = total_ct;
448:   baij->ht_insert_ct = insert_ct;
449: #endif
450:   return(0);
451: }

455: PetscErrorCode MatSetValuesBlocked_MPIBAIJ_HT(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv)
456: {
457:   Mat_MPIBAIJ       *baij       = (Mat_MPIBAIJ*)mat->data;
458:   PetscBool         roworiented = baij->roworiented;
459:   PetscErrorCode    ierr;
460:   PetscInt          i,j,ii,jj,row,col;
461:   PetscInt          rstart=baij->rstartbs;
462:   PetscInt          rend  =mat->rmap->rend,stepval,bs=mat->rmap->bs,bs2=baij->bs2,nbs2=n*bs2;
463:   PetscInt          h1,key,size=baij->ht_size,idx,*HT=baij->ht,Nbs=baij->Nbs;
464:   PetscReal         tmp;
465:   MatScalar         **HD = baij->hd,*baij_a;
466:   const PetscScalar *v_t,*value;
467: #if defined(PETSC_USE_DEBUG)
468:   PetscInt total_ct=baij->ht_total_ct,insert_ct=baij->ht_insert_ct;
469: #endif

472:   if (roworiented) stepval = (n-1)*bs;
473:   else stepval = (m-1)*bs;

475:   for (i=0; i<m; i++) {
476: #if defined(PETSC_USE_DEBUG)
477:     if (im[i] < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",im[i]);
478:     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);
479: #endif
480:     row = im[i];
481:     v_t = v + i*nbs2;
482:     if (row >= rstart && row < rend) {
483:       for (j=0; j<n; j++) {
484:         col = in[j];

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

490:         idx = h1;
491: #if defined(PETSC_USE_DEBUG)
492:         total_ct++;
493:         insert_ct++;
494:         if (HT[idx] != key) {
495:           for (idx=h1; (idx<size) && (HT[idx]!=key); idx++,total_ct++) ;
496:           if (idx == size) {
497:             for (idx=0; (idx<h1) && (HT[idx]!=key); idx++,total_ct++) ;
498:             if (idx == h1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"(%D,%D) has no entry in the hash table", row, col);
499:           }
500:         }
501: #else
502:         if (HT[idx] != key) {
503:           for (idx=h1; (idx<size) && (HT[idx]!=key); idx++) ;
504:           if (idx == size) {
505:             for (idx=0; (idx<h1) && (HT[idx]!=key); idx++) ;
506:             if (idx == h1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"(%D,%D) has no entry in the hash table", row, col);
507:           }
508:         }
509: #endif
510:         baij_a = HD[idx];
511:         if (roworiented) {
512:           /*value = v + i*(stepval+bs)*bs + j*bs;*/
513:           /* value = v + (i*(stepval+bs)+j)*bs; */
514:           value = v_t;
515:           v_t  += bs;
516:           if (addv == ADD_VALUES) {
517:             for (ii=0; ii<bs; ii++,value+=stepval) {
518:               for (jj=ii; jj<bs2; jj+=bs) {
519:                 baij_a[jj] += *value++;
520:               }
521:             }
522:           } else {
523:             for (ii=0; ii<bs; ii++,value+=stepval) {
524:               for (jj=ii; jj<bs2; jj+=bs) {
525:                 baij_a[jj] = *value++;
526:               }
527:             }
528:           }
529:         } else {
530:           value = v + j*(stepval+bs)*bs + i*bs;
531:           if (addv == ADD_VALUES) {
532:             for (ii=0; ii<bs; ii++,value+=stepval,baij_a+=bs) {
533:               for (jj=0; jj<bs; jj++) {
534:                 baij_a[jj] += *value++;
535:               }
536:             }
537:           } else {
538:             for (ii=0; ii<bs; ii++,value+=stepval,baij_a+=bs) {
539:               for (jj=0; jj<bs; jj++) {
540:                 baij_a[jj] = *value++;
541:               }
542:             }
543:           }
544:         }
545:       }
546:     } else {
547:       if (!baij->donotstash) {
548:         if (roworiented) {
549:           MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);
550:         } else {
551:           MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);
552:         }
553:       }
554:     }
555:   }
556: #if defined(PETSC_USE_DEBUG)
557:   baij->ht_total_ct  = total_ct;
558:   baij->ht_insert_ct = insert_ct;
559: #endif
560:   return(0);
561: }

565: PetscErrorCode MatGetValues_MPIBAIJ(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[])
566: {
567:   Mat_MPIBAIJ    *baij = (Mat_MPIBAIJ*)mat->data;
569:   PetscInt       bs       = mat->rmap->bs,i,j,bsrstart = mat->rmap->rstart,bsrend = mat->rmap->rend;
570:   PetscInt       bscstart = mat->cmap->rstart,bscend = mat->cmap->rend,row,col,data;

573:   for (i=0; i<m; i++) {
574:     if (idxm[i] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",idxm[i]);*/
575:     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);
576:     if (idxm[i] >= bsrstart && idxm[i] < bsrend) {
577:       row = idxm[i] - bsrstart;
578:       for (j=0; j<n; j++) {
579:         if (idxn[j] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column: %D",idxn[j]); */
580:         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);
581:         if (idxn[j] >= bscstart && idxn[j] < bscend) {
582:           col  = idxn[j] - bscstart;
583:           MatGetValues_SeqBAIJ(baij->A,1,&row,1,&col,v+i*n+j);
584:         } else {
585:           if (!baij->colmap) {
586:             MatCreateColmap_MPIBAIJ_Private(mat);
587:           }
588: #if defined(PETSC_USE_CTABLE)
589:           PetscTableFind(baij->colmap,idxn[j]/bs+1,&data);
590:           data--;
591: #else
592:           data = baij->colmap[idxn[j]/bs]-1;
593: #endif
594:           if ((data < 0) || (baij->garray[data/bs] != idxn[j]/bs)) *(v+i*n+j) = 0.0;
595:           else {
596:             col  = data + idxn[j]%bs;
597:             MatGetValues_SeqBAIJ(baij->B,1,&row,1,&col,v+i*n+j);
598:           }
599:         }
600:       }
601:     } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local values currently supported");
602:   }
603:   return(0);
604: }

608: PetscErrorCode MatNorm_MPIBAIJ(Mat mat,NormType type,PetscReal *nrm)
609: {
610:   Mat_MPIBAIJ    *baij = (Mat_MPIBAIJ*)mat->data;
611:   Mat_SeqBAIJ    *amat = (Mat_SeqBAIJ*)baij->A->data,*bmat = (Mat_SeqBAIJ*)baij->B->data;
613:   PetscInt       i,j,bs2=baij->bs2,bs=baij->A->rmap->bs,nz,row,col;
614:   PetscReal      sum = 0.0;
615:   MatScalar      *v;

618:   if (baij->size == 1) {
619:      MatNorm(baij->A,type,nrm);
620:   } else {
621:     if (type == NORM_FROBENIUS) {
622:       v  = amat->a;
623:       nz = amat->nz*bs2;
624:       for (i=0; i<nz; i++) {
625:         sum += PetscRealPart(PetscConj(*v)*(*v)); v++;
626:       }
627:       v  = bmat->a;
628:       nz = bmat->nz*bs2;
629:       for (i=0; i<nz; i++) {
630:         sum += PetscRealPart(PetscConj(*v)*(*v)); v++;
631:       }
632:       MPI_Allreduce(&sum,nrm,1,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));
633:       *nrm = PetscSqrtReal(*nrm);
634:     } else if (type == NORM_1) { /* max column sum */
635:       PetscReal *tmp,*tmp2;
636:       PetscInt  *jj,*garray=baij->garray,cstart=baij->rstartbs;
637:       PetscMalloc2(mat->cmap->N,PetscReal,&tmp,mat->cmap->N,PetscReal,&tmp2);
638:       PetscMemzero(tmp,mat->cmap->N*sizeof(PetscReal));
639:       v    = amat->a; jj = amat->j;
640:       for (i=0; i<amat->nz; i++) {
641:         for (j=0; j<bs; j++) {
642:           col = bs*(cstart + *jj) + j; /* column index */
643:           for (row=0; row<bs; row++) {
644:             tmp[col] += PetscAbsScalar(*v);  v++;
645:           }
646:         }
647:         jj++;
648:       }
649:       v = bmat->a; jj = bmat->j;
650:       for (i=0; i<bmat->nz; i++) {
651:         for (j=0; j<bs; j++) {
652:           col = bs*garray[*jj] + j;
653:           for (row=0; row<bs; row++) {
654:             tmp[col] += PetscAbsScalar(*v); v++;
655:           }
656:         }
657:         jj++;
658:       }
659:       MPI_Allreduce(tmp,tmp2,mat->cmap->N,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));
660:       *nrm = 0.0;
661:       for (j=0; j<mat->cmap->N; j++) {
662:         if (tmp2[j] > *nrm) *nrm = tmp2[j];
663:       }
664:       PetscFree2(tmp,tmp2);
665:     } else if (type == NORM_INFINITY) { /* max row sum */
666:       PetscReal *sums;
667:       PetscMalloc(bs*sizeof(PetscReal),&sums);
668:       sum  = 0.0;
669:       for (j=0; j<amat->mbs; j++) {
670:         for (row=0; row<bs; row++) sums[row] = 0.0;
671:         v  = amat->a + bs2*amat->i[j];
672:         nz = amat->i[j+1]-amat->i[j];
673:         for (i=0; i<nz; i++) {
674:           for (col=0; col<bs; col++) {
675:             for (row=0; row<bs; row++) {
676:               sums[row] += PetscAbsScalar(*v); v++;
677:             }
678:           }
679:         }
680:         v  = bmat->a + bs2*bmat->i[j];
681:         nz = bmat->i[j+1]-bmat->i[j];
682:         for (i=0; i<nz; i++) {
683:           for (col=0; col<bs; col++) {
684:             for (row=0; row<bs; row++) {
685:               sums[row] += PetscAbsScalar(*v); v++;
686:             }
687:           }
688:         }
689:         for (row=0; row<bs; row++) {
690:           if (sums[row] > sum) sum = sums[row];
691:         }
692:       }
693:       MPI_Allreduce(&sum,nrm,1,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)mat));
694:       PetscFree(sums);
695:     } else SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_SUP,"No support for this norm yet");
696:   }
697:   return(0);
698: }

700: /*
701:   Creates the hash table, and sets the table
702:   This table is created only once.
703:   If new entried need to be added to the matrix
704:   then the hash table has to be destroyed and
705:   recreated.
706: */
709: PetscErrorCode MatCreateHashTable_MPIBAIJ_Private(Mat mat,PetscReal factor)
710: {
711:   Mat_MPIBAIJ    *baij = (Mat_MPIBAIJ*)mat->data;
712:   Mat            A     = baij->A,B=baij->B;
713:   Mat_SeqBAIJ    *a    = (Mat_SeqBAIJ*)A->data,*b=(Mat_SeqBAIJ*)B->data;
714:   PetscInt       i,j,k,nz=a->nz+b->nz,h1,*ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j;
716:   PetscInt       ht_size,bs2=baij->bs2,rstart=baij->rstartbs;
717:   PetscInt       cstart=baij->cstartbs,*garray=baij->garray,row,col,Nbs=baij->Nbs;
718:   PetscInt       *HT,key;
719:   MatScalar      **HD;
720:   PetscReal      tmp;
721: #if defined(PETSC_USE_INFO)
722:   PetscInt ct=0,max=0;
723: #endif

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

728:   baij->ht_size = (PetscInt)(factor*nz);
729:   ht_size       = baij->ht_size;

731:   /* Allocate Memory for Hash Table */
732:   PetscMalloc2(ht_size,MatScalar*,&baij->hd,ht_size,PetscInt,&baij->ht);
733:   PetscMemzero(baij->hd,ht_size*sizeof(MatScalar*));
734:   PetscMemzero(baij->ht,ht_size*sizeof(PetscInt));
735:   HD   = baij->hd;
736:   HT   = baij->ht;

738:   /* Loop Over A */
739:   for (i=0; i<a->mbs; i++) {
740:     for (j=ai[i]; j<ai[i+1]; j++) {
741:       row = i+rstart;
742:       col = aj[j]+cstart;

744:       key = row*Nbs + col + 1;
745:       h1  = HASH(ht_size,key,tmp);
746:       for (k=0; k<ht_size; k++) {
747:         if (!HT[(h1+k)%ht_size]) {
748:           HT[(h1+k)%ht_size] = key;
749:           HD[(h1+k)%ht_size] = a->a + j*bs2;
750:           break;
751: #if defined(PETSC_USE_INFO)
752:         } else {
753:           ct++;
754: #endif
755:         }
756:       }
757: #if defined(PETSC_USE_INFO)
758:       if (k> max) max = k;
759: #endif
760:     }
761:   }
762:   /* Loop Over B */
763:   for (i=0; i<b->mbs; i++) {
764:     for (j=bi[i]; j<bi[i+1]; j++) {
765:       row = i+rstart;
766:       col = garray[bj[j]];
767:       key = row*Nbs + col + 1;
768:       h1  = HASH(ht_size,key,tmp);
769:       for (k=0; k<ht_size; k++) {
770:         if (!HT[(h1+k)%ht_size]) {
771:           HT[(h1+k)%ht_size] = key;
772:           HD[(h1+k)%ht_size] = b->a + j*bs2;
773:           break;
774: #if defined(PETSC_USE_INFO)
775:         } else {
776:           ct++;
777: #endif
778:         }
779:       }
780: #if defined(PETSC_USE_INFO)
781:       if (k> max) max = k;
782: #endif
783:     }
784:   }

786:   /* Print Summary */
787: #if defined(PETSC_USE_INFO)
788:   for (i=0,j=0; i<ht_size; i++) {
789:     if (HT[i]) j++;
790:   }
791:   PetscInfo2(mat,"Average Search = %5.2f,max search = %D\n",(!j)? 0.0:((PetscReal)(ct+j))/j,max);
792: #endif
793:   return(0);
794: }

798: PetscErrorCode MatAssemblyBegin_MPIBAIJ(Mat mat,MatAssemblyType mode)
799: {
800:   Mat_MPIBAIJ    *baij = (Mat_MPIBAIJ*)mat->data;
802:   PetscInt       nstash,reallocs;
803:   InsertMode     addv;

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

808:   /* make sure all processors are either in INSERTMODE or ADDMODE */
809:   MPI_Allreduce((PetscEnum*)&mat->insertmode,(PetscEnum*)&addv,1,MPIU_ENUM,MPI_BOR,PetscObjectComm((PetscObject)mat));
810:   if (addv == (ADD_VALUES|INSERT_VALUES)) SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_ARG_WRONGSTATE,"Some processors inserted others added");
811:   mat->insertmode = addv; /* in case this processor had no cache */

813:   MatStashScatterBegin_Private(mat,&mat->stash,mat->rmap->range);
814:   MatStashScatterBegin_Private(mat,&mat->bstash,baij->rangebs);
815:   MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);
816:   PetscInfo2(mat,"Stash has %D entries,uses %D mallocs.\n",nstash,reallocs);
817:   MatStashGetInfo_Private(&mat->bstash,&nstash,&reallocs);
818:   PetscInfo2(mat,"Block-Stash has %D entries, uses %D mallocs.\n",nstash,reallocs);
819:   return(0);
820: }

824: PetscErrorCode MatAssemblyEnd_MPIBAIJ(Mat mat,MatAssemblyType mode)
825: {
826:   Mat_MPIBAIJ    *baij=(Mat_MPIBAIJ*)mat->data;
827:   Mat_SeqBAIJ    *a   =(Mat_SeqBAIJ*)baij->A->data;
829:   PetscInt       i,j,rstart,ncols,flg,bs2=baij->bs2;
830:   PetscInt       *row,*col;
831:   PetscBool      r1,r2,r3,other_disassembled;
832:   MatScalar      *val;
833:   InsertMode     addv = mat->insertmode;
834:   PetscMPIInt    n;

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

843:       for (i=0; i<n;) {
844:         /* Now identify the consecutive vals belonging to the same row */
845:         for (j=i,rstart=row[j]; j<n; j++) {
846:           if (row[j] != rstart) break;
847:         }
848:         if (j < n) ncols = j-i;
849:         else       ncols = n-i;
850:         /* Now assemble all these values with a single function call */
851:         MatSetValues_MPIBAIJ(mat,1,row+i,ncols,col+i,val+i,addv);
852:         i    = j;
853:       }
854:     }
855:     MatStashScatterEnd_Private(&mat->stash);
856:     /* Now process the block-stash. Since the values are stashed column-oriented,
857:        set the roworiented flag to column oriented, and after MatSetValues()
858:        restore the original flags */
859:     r1 = baij->roworiented;
860:     r2 = a->roworiented;
861:     r3 = ((Mat_SeqBAIJ*)baij->B->data)->roworiented;

863:     baij->roworiented = PETSC_FALSE;
864:     a->roworiented    = PETSC_FALSE;

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

871:       for (i=0; i<n;) {
872:         /* Now identify the consecutive vals belonging to the same row */
873:         for (j=i,rstart=row[j]; j<n; j++) {
874:           if (row[j] != rstart) break;
875:         }
876:         if (j < n) ncols = j-i;
877:         else       ncols = n-i;
878:         MatSetValuesBlocked_MPIBAIJ(mat,1,row+i,ncols,col+i,val+i*bs2,addv);
879:         i    = j;
880:       }
881:     }
882:     MatStashScatterEnd_Private(&mat->bstash);

884:     baij->roworiented = r1;
885:     a->roworiented    = r2;

887:     ((Mat_SeqBAIJ*)baij->B->data)->roworiented = r3; /* b->roworiented */
888:   }

890:   MatAssemblyBegin(baij->A,mode);
891:   MatAssemblyEnd(baij->A,mode);

893:   /* determine if any processor has disassembled, if so we must
894:      also disassemble ourselfs, in order that we may reassemble. */
895:   /*
896:      if nonzero structure of submatrix B cannot change then we know that
897:      no processor disassembled thus we can skip this stuff
898:   */
899:   if (!((Mat_SeqBAIJ*)baij->B->data)->nonew) {
900:     MPI_Allreduce(&mat->was_assembled,&other_disassembled,1,MPIU_BOOL,MPI_PROD,PetscObjectComm((PetscObject)mat));
901:     if (mat->was_assembled && !other_disassembled) {
902:       MatDisAssemble_MPIBAIJ(mat);
903:     }
904:   }

906:   if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) {
907:     MatSetUpMultiply_MPIBAIJ(mat);
908:   }
909:   MatSetOption(baij->B,MAT_CHECK_COMPRESSED_ROW,PETSC_FALSE);
910:   MatAssemblyBegin(baij->B,mode);
911:   MatAssemblyEnd(baij->B,mode);

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

917:     baij->ht_total_ct  = 0;
918:     baij->ht_insert_ct = 0;
919:   }
920: #endif
921:   if (baij->ht_flag && !baij->ht && mode == MAT_FINAL_ASSEMBLY) {
922:     MatCreateHashTable_MPIBAIJ_Private(mat,baij->ht_fact);

924:     mat->ops->setvalues        = MatSetValues_MPIBAIJ_HT;
925:     mat->ops->setvaluesblocked = MatSetValuesBlocked_MPIBAIJ_HT;
926:   }

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

930:   baij->rowvalues = 0;
931:   return(0);
932: }

934: #include <petscdraw.h>
937: static PetscErrorCode MatView_MPIBAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer)
938: {
939:   Mat_MPIBAIJ       *baij = (Mat_MPIBAIJ*)mat->data;
940:   PetscErrorCode    ierr;
941:   PetscMPIInt       size = baij->size,rank = baij->rank;
942:   PetscInt          bs   = mat->rmap->bs;
943:   PetscBool         iascii,isdraw;
944:   PetscViewer       sviewer;
945:   PetscViewerFormat format;

948:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
949:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);
950:   if (iascii) {
951:     PetscViewerGetFormat(viewer,&format);
952:     if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) {
953:       MatInfo info;
954:       MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);
955:       MatGetInfo(mat,MAT_LOCAL,&info);
956:       PetscViewerASCIISynchronizedAllow(viewer,PETSC_TRUE);
957:       PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D bs %D mem %D\n",
958:                                                 rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,mat->rmap->bs,(PetscInt)info.memory);
959:       MatGetInfo(baij->A,MAT_LOCAL,&info);
960:       PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);
961:       MatGetInfo(baij->B,MAT_LOCAL,&info);
962:       PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);
963:       PetscViewerFlush(viewer);
964:       PetscViewerASCIISynchronizedAllow(viewer,PETSC_FALSE);
965:       PetscViewerASCIIPrintf(viewer,"Information on VecScatter used in matrix-vector product: \n");
966:       VecScatterView(baij->Mvctx,viewer);
967:       return(0);
968:     } else if (format == PETSC_VIEWER_ASCII_INFO) {
969:       PetscViewerASCIIPrintf(viewer,"  block size is %D\n",bs);
970:       return(0);
971:     } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) {
972:       return(0);
973:     }
974:   }

976:   if (isdraw) {
977:     PetscDraw draw;
978:     PetscBool isnull;
979:     PetscViewerDrawGetDraw(viewer,0,&draw);
980:     PetscDrawIsNull(draw,&isnull); if (isnull) return(0);
981:   }

983:   if (size == 1) {
984:     PetscObjectSetName((PetscObject)baij->A,((PetscObject)mat)->name);
985:     MatView(baij->A,viewer);
986:   } else {
987:     /* assemble the entire matrix onto first processor. */
988:     Mat         A;
989:     Mat_SeqBAIJ *Aloc;
990:     PetscInt    M = mat->rmap->N,N = mat->cmap->N,*ai,*aj,col,i,j,k,*rvals,mbs = baij->mbs;
991:     MatScalar   *a;

993:     /* Here we are creating a temporary matrix, so will assume MPIBAIJ is acceptable */
994:     /* Perhaps this should be the type of mat? */
995:     MatCreate(PetscObjectComm((PetscObject)mat),&A);
996:     if (!rank) {
997:       MatSetSizes(A,M,N,M,N);
998:     } else {
999:       MatSetSizes(A,0,0,M,N);
1000:     }
1001:     MatSetType(A,MATMPIBAIJ);
1002:     MatMPIBAIJSetPreallocation(A,mat->rmap->bs,0,NULL,0,NULL);
1003:     MatSetOption(A,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_FALSE);
1004:     PetscLogObjectParent(mat,A);

1006:     /* copy over the A part */
1007:     Aloc = (Mat_SeqBAIJ*)baij->A->data;
1008:     ai   = Aloc->i; aj = Aloc->j; a = Aloc->a;
1009:     PetscMalloc(bs*sizeof(PetscInt),&rvals);

1011:     for (i=0; i<mbs; i++) {
1012:       rvals[0] = bs*(baij->rstartbs + i);
1013:       for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1;
1014:       for (j=ai[i]; j<ai[i+1]; j++) {
1015:         col = (baij->cstartbs+aj[j])*bs;
1016:         for (k=0; k<bs; k++) {
1017:           MatSetValues_MPIBAIJ(A,bs,rvals,1,&col,a,INSERT_VALUES);
1018:           col++; a += bs;
1019:         }
1020:       }
1021:     }
1022:     /* copy over the B part */
1023:     Aloc = (Mat_SeqBAIJ*)baij->B->data;
1024:     ai   = Aloc->i; aj = Aloc->j; a = Aloc->a;
1025:     for (i=0; i<mbs; i++) {
1026:       rvals[0] = bs*(baij->rstartbs + i);
1027:       for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1;
1028:       for (j=ai[i]; j<ai[i+1]; j++) {
1029:         col = baij->garray[aj[j]]*bs;
1030:         for (k=0; k<bs; k++) {
1031:           MatSetValues_MPIBAIJ(A,bs,rvals,1,&col,a,INSERT_VALUES);
1032:           col++; a += bs;
1033:         }
1034:       }
1035:     }
1036:     PetscFree(rvals);
1037:     MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);
1038:     MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);
1039:     /*
1040:        Everyone has to call to draw the matrix since the graphics waits are
1041:        synchronized across all processors that share the PetscDraw object
1042:     */
1043:     PetscViewerGetSingleton(viewer,&sviewer);
1044:     if (!rank) {
1045:       PetscObjectSetName((PetscObject)((Mat_MPIBAIJ*)(A->data))->A,((PetscObject)mat)->name);
1046:       /* Set the type name to MATMPIBAIJ so that the correct type can be printed out by PetscObjectPrintClassNamePrefixType() in MatView_SeqBAIJ_ASCII()*/
1047:       PetscStrcpy(((PetscObject)((Mat_MPIBAIJ*)(A->data))->A)->type_name,MATMPIBAIJ);
1048:       MatView(((Mat_MPIBAIJ*)(A->data))->A,sviewer);
1049:     }
1050:     PetscViewerRestoreSingleton(viewer,&sviewer);
1051:     MatDestroy(&A);
1052:   }
1053:   return(0);
1054: }

1058: static PetscErrorCode MatView_MPIBAIJ_Binary(Mat mat,PetscViewer viewer)
1059: {
1060:   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)mat->data;
1061:   Mat_SeqBAIJ    *A = (Mat_SeqBAIJ*)a->A->data;
1062:   Mat_SeqBAIJ    *B = (Mat_SeqBAIJ*)a->B->data;
1064:   PetscInt       i,*row_lens,*crow_lens,bs = mat->rmap->bs,j,k,bs2=a->bs2,header[4],nz,rlen;
1065:   PetscInt       *range=0,nzmax,*column_indices,cnt,col,*garray = a->garray,cstart = mat->cmap->rstart/bs,len,pcnt,l,ll;
1066:   int            fd;
1067:   PetscScalar    *column_values;
1068:   FILE           *file;
1069:   PetscMPIInt    rank,size,tag = ((PetscObject)viewer)->tag;
1070:   PetscInt       message_count,flowcontrolcount;

1073:   MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);
1074:   MPI_Comm_size(PetscObjectComm((PetscObject)mat),&size);
1075:   nz   = bs2*(A->nz + B->nz);
1076:   rlen = mat->rmap->n;
1077:   if (!rank) {
1078:     header[0] = MAT_FILE_CLASSID;
1079:     header[1] = mat->rmap->N;
1080:     header[2] = mat->cmap->N;

1082:     MPI_Reduce(&nz,&header[3],1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));
1083:     PetscViewerBinaryGetDescriptor(viewer,&fd);
1084:     PetscBinaryWrite(fd,header,4,PETSC_INT,PETSC_TRUE);
1085:     /* get largest number of rows any processor has */
1086:     range = mat->rmap->range;
1087:     for (i=1; i<size; i++) {
1088:       rlen = PetscMax(rlen,range[i+1] - range[i]);
1089:     }
1090:   } else {
1091:     MPI_Reduce(&nz,0,1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));
1092:   }

1094:   PetscMalloc((rlen/bs)*sizeof(PetscInt),&crow_lens);
1095:   /* compute lengths of each row  */
1096:   for (i=0; i<a->mbs; i++) {
1097:     crow_lens[i] = A->i[i+1] - A->i[i] + B->i[i+1] - B->i[i];
1098:   }
1099:   /* store the row lengths to the file */
1100:   PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);
1101:   if (!rank) {
1102:     MPI_Status status;
1103:     PetscMalloc(rlen*sizeof(PetscInt),&row_lens);
1104:     rlen = (range[1] - range[0])/bs;
1105:     for (i=0; i<rlen; i++) {
1106:       for (j=0; j<bs; j++) {
1107:         row_lens[i*bs+j] = bs*crow_lens[i];
1108:       }
1109:     }
1110:     PetscBinaryWrite(fd,row_lens,bs*rlen,PETSC_INT,PETSC_TRUE);
1111:     for (i=1; i<size; i++) {
1112:       rlen = (range[i+1] - range[i])/bs;
1113:       PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);
1114:       MPI_Recv(crow_lens,rlen,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);
1115:       for (k=0; k<rlen; k++) {
1116:         for (j=0; j<bs; j++) {
1117:           row_lens[k*bs+j] = bs*crow_lens[k];
1118:         }
1119:       }
1120:       PetscBinaryWrite(fd,row_lens,bs*rlen,PETSC_INT,PETSC_TRUE);
1121:     }
1122:     PetscViewerFlowControlEndMaster(viewer,&message_count);
1123:     PetscFree(row_lens);
1124:   } else {
1125:     PetscViewerFlowControlStepWorker(viewer,rank,&message_count);
1126:     MPI_Send(crow_lens,mat->rmap->n/bs,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));
1127:     PetscViewerFlowControlEndWorker(viewer,&message_count);
1128:   }
1129:   PetscFree(crow_lens);

1131:   /* load up the local column indices. Include for all rows not just one for each block row since process 0 does not have the
1132:      information needed to make it for each row from a block row. This does require more communication but still not more than
1133:      the communication needed for the nonzero values  */
1134:   nzmax = nz; /*  space a largest processor needs */
1135:   MPI_Reduce(&nz,&nzmax,1,MPIU_INT,MPI_MAX,0,PetscObjectComm((PetscObject)mat));
1136:   PetscMalloc(nzmax*sizeof(PetscInt),&column_indices);
1137:   cnt   = 0;
1138:   for (i=0; i<a->mbs; i++) {
1139:     pcnt = cnt;
1140:     for (j=B->i[i]; j<B->i[i+1]; j++) {
1141:       if ((col = garray[B->j[j]]) > cstart) break;
1142:       for (l=0; l<bs; l++) {
1143:         column_indices[cnt++] = bs*col+l;
1144:       }
1145:     }
1146:     for (k=A->i[i]; k<A->i[i+1]; k++) {
1147:       for (l=0; l<bs; l++) {
1148:         column_indices[cnt++] = bs*(A->j[k] + cstart)+l;
1149:       }
1150:     }
1151:     for (; j<B->i[i+1]; j++) {
1152:       for (l=0; l<bs; l++) {
1153:         column_indices[cnt++] = bs*garray[B->j[j]]+l;
1154:       }
1155:     }
1156:     len = cnt - pcnt;
1157:     for (k=1; k<bs; k++) {
1158:       PetscMemcpy(&column_indices[cnt],&column_indices[pcnt],len*sizeof(PetscInt));
1159:       cnt += len;
1160:     }
1161:   }
1162:   if (cnt != nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: cnt = %D nz = %D",cnt,nz);

1164:   /* store the columns to the file */
1165:   PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);
1166:   if (!rank) {
1167:     MPI_Status status;
1168:     PetscBinaryWrite(fd,column_indices,nz,PETSC_INT,PETSC_TRUE);
1169:     for (i=1; i<size; i++) {
1170:       PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);
1171:       MPI_Recv(&cnt,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);
1172:       MPI_Recv(column_indices,cnt,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);
1173:       PetscBinaryWrite(fd,column_indices,cnt,PETSC_INT,PETSC_TRUE);
1174:     }
1175:     PetscViewerFlowControlEndMaster(viewer,&message_count);
1176:   } else {
1177:     PetscViewerFlowControlStepWorker(viewer,rank,&message_count);
1178:     MPI_Send(&cnt,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));
1179:     MPI_Send(column_indices,cnt,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));
1180:     PetscViewerFlowControlEndWorker(viewer,&message_count);
1181:   }
1182:   PetscFree(column_indices);

1184:   /* load up the numerical values */
1185:   PetscMalloc(nzmax*sizeof(PetscScalar),&column_values);
1186:   cnt  = 0;
1187:   for (i=0; i<a->mbs; i++) {
1188:     rlen = bs*(B->i[i+1] - B->i[i] + A->i[i+1] - A->i[i]);
1189:     for (j=B->i[i]; j<B->i[i+1]; j++) {
1190:       if (garray[B->j[j]] > cstart) break;
1191:       for (l=0; l<bs; l++) {
1192:         for (ll=0; ll<bs; ll++) {
1193:           column_values[cnt + l*rlen + ll] = B->a[bs2*j+l+bs*ll];
1194:         }
1195:       }
1196:       cnt += bs;
1197:     }
1198:     for (k=A->i[i]; k<A->i[i+1]; k++) {
1199:       for (l=0; l<bs; l++) {
1200:         for (ll=0; ll<bs; ll++) {
1201:           column_values[cnt + l*rlen + ll] = A->a[bs2*k+l+bs*ll];
1202:         }
1203:       }
1204:       cnt += bs;
1205:     }
1206:     for (; j<B->i[i+1]; j++) {
1207:       for (l=0; l<bs; l++) {
1208:         for (ll=0; ll<bs; ll++) {
1209:           column_values[cnt + l*rlen + ll] = B->a[bs2*j+l+bs*ll];
1210:         }
1211:       }
1212:       cnt += bs;
1213:     }
1214:     cnt += (bs-1)*rlen;
1215:   }
1216:   if (cnt != nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Internal PETSc error: cnt = %D nz = %D",cnt,nz);

1218:   /* store the column values to the file */
1219:   PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);
1220:   if (!rank) {
1221:     MPI_Status status;
1222:     PetscBinaryWrite(fd,column_values,nz,PETSC_SCALAR,PETSC_TRUE);
1223:     for (i=1; i<size; i++) {
1224:       PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);
1225:       MPI_Recv(&cnt,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);
1226:       MPI_Recv(column_values,cnt,MPIU_SCALAR,i,tag,PetscObjectComm((PetscObject)mat),&status);
1227:       PetscBinaryWrite(fd,column_values,cnt,PETSC_SCALAR,PETSC_TRUE);
1228:     }
1229:     PetscViewerFlowControlEndMaster(viewer,&message_count);
1230:   } else {
1231:     PetscViewerFlowControlStepWorker(viewer,rank,&message_count);
1232:     MPI_Send(&nz,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));
1233:     MPI_Send(column_values,nz,MPIU_SCALAR,0,tag,PetscObjectComm((PetscObject)mat));
1234:     PetscViewerFlowControlEndWorker(viewer,&message_count);
1235:   }
1236:   PetscFree(column_values);

1238:   PetscViewerBinaryGetInfoPointer(viewer,&file);
1239:   if (file) {
1240:     fprintf(file,"-matload_block_size %d\n",(int)mat->rmap->bs);
1241:   }
1242:   return(0);
1243: }

1247: PetscErrorCode MatView_MPIBAIJ(Mat mat,PetscViewer viewer)
1248: {
1250:   PetscBool      iascii,isdraw,issocket,isbinary;

1253:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
1254:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);
1255:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSOCKET,&issocket);
1256:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);
1257:   if (iascii || isdraw || issocket) {
1258:     MatView_MPIBAIJ_ASCIIorDraworSocket(mat,viewer);
1259:   } else if (isbinary) {
1260:     MatView_MPIBAIJ_Binary(mat,viewer);
1261:   }
1262:   return(0);
1263: }

1267: PetscErrorCode MatDestroy_MPIBAIJ(Mat mat)
1268: {
1269:   Mat_MPIBAIJ    *baij = (Mat_MPIBAIJ*)mat->data;

1273: #if defined(PETSC_USE_LOG)
1274:   PetscLogObjectState((PetscObject)mat,"Rows=%D,Cols=%D",mat->rmap->N,mat->cmap->N);
1275: #endif
1276:   MatStashDestroy_Private(&mat->stash);
1277:   MatStashDestroy_Private(&mat->bstash);
1278:   MatDestroy(&baij->A);
1279:   MatDestroy(&baij->B);
1280: #if defined(PETSC_USE_CTABLE)
1281:   PetscTableDestroy(&baij->colmap);
1282: #else
1283:   PetscFree(baij->colmap);
1284: #endif
1285:   PetscFree(baij->garray);
1286:   VecDestroy(&baij->lvec);
1287:   VecScatterDestroy(&baij->Mvctx);
1288:   PetscFree2(baij->rowvalues,baij->rowindices);
1289:   PetscFree(baij->barray);
1290:   PetscFree2(baij->hd,baij->ht);
1291:   PetscFree(baij->rangebs);
1292:   PetscFree(mat->data);

1294:   PetscObjectChangeTypeName((PetscObject)mat,0);
1295:   PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C",NULL);
1296:   PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C",NULL);
1297:   PetscObjectComposeFunction((PetscObject)mat,"MatGetDiagonalBlock_C",NULL);
1298:   PetscObjectComposeFunction((PetscObject)mat,"MatMPIBAIJSetPreallocation_C",NULL);
1299:   PetscObjectComposeFunction((PetscObject)mat,"MatMPIBAIJSetPreallocationCSR_C",NULL);
1300:   PetscObjectComposeFunction((PetscObject)mat,"MatDiagonalScaleLocal_C",NULL);
1301:   PetscObjectComposeFunction((PetscObject)mat,"MatSetHashTableFactor_C",NULL);
1302:   PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpibaij_mpisbaij_C",NULL);
1303:   PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpibaij_mpibstrm_C",NULL);
1304:   return(0);
1305: }

1309: PetscErrorCode MatMult_MPIBAIJ(Mat A,Vec xx,Vec yy)
1310: {
1311:   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;
1313:   PetscInt       nt;

1316:   VecGetLocalSize(xx,&nt);
1317:   if (nt != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx");
1318:   VecGetLocalSize(yy,&nt);
1319:   if (nt != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible parition of A and yy");
1320:   VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
1321:   (*a->A->ops->mult)(a->A,xx,yy);
1322:   VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
1323:   (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);
1324:   return(0);
1325: }

1329: PetscErrorCode MatMultAdd_MPIBAIJ(Mat A,Vec xx,Vec yy,Vec zz)
1330: {
1331:   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;

1335:   VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
1336:   (*a->A->ops->multadd)(a->A,xx,yy,zz);
1337:   VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
1338:   (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);
1339:   return(0);
1340: }

1344: PetscErrorCode MatMultTranspose_MPIBAIJ(Mat A,Vec xx,Vec yy)
1345: {
1346:   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;
1348:   PetscBool      merged;

1351:   VecScatterGetMerged(a->Mvctx,&merged);
1352:   /* do nondiagonal part */
1353:   (*a->B->ops->multtranspose)(a->B,xx,a->lvec);
1354:   if (!merged) {
1355:     /* send it on its way */
1356:     VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
1357:     /* do local part */
1358:     (*a->A->ops->multtranspose)(a->A,xx,yy);
1359:     /* receive remote parts: note this assumes the values are not actually */
1360:     /* inserted in yy until the next line */
1361:     VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
1362:   } else {
1363:     /* do local part */
1364:     (*a->A->ops->multtranspose)(a->A,xx,yy);
1365:     /* send it on its way */
1366:     VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
1367:     /* values actually were received in the Begin() but we need to call this nop */
1368:     VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
1369:   }
1370:   return(0);
1371: }

1375: PetscErrorCode MatMultTransposeAdd_MPIBAIJ(Mat A,Vec xx,Vec yy,Vec zz)
1376: {
1377:   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;

1381:   /* do nondiagonal part */
1382:   (*a->B->ops->multtranspose)(a->B,xx,a->lvec);
1383:   /* send it on its way */
1384:   VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);
1385:   /* do local part */
1386:   (*a->A->ops->multtransposeadd)(a->A,xx,yy,zz);
1387:   /* receive remote parts: note this assumes the values are not actually */
1388:   /* inserted in yy until the next line, which is true for my implementation*/
1389:   /* but is not perhaps always true. */
1390:   VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);
1391:   return(0);
1392: }

1394: /*
1395:   This only works correctly for square matrices where the subblock A->A is the
1396:    diagonal block
1397: */
1400: PetscErrorCode MatGetDiagonal_MPIBAIJ(Mat A,Vec v)
1401: {
1402:   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;

1406:   if (A->rmap->N != A->cmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block");
1407:   MatGetDiagonal(a->A,v);
1408:   return(0);
1409: }

1413: PetscErrorCode MatScale_MPIBAIJ(Mat A,PetscScalar aa)
1414: {
1415:   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;

1419:   MatScale(a->A,aa);
1420:   MatScale(a->B,aa);
1421:   return(0);
1422: }

1426: PetscErrorCode MatGetRow_MPIBAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
1427: {
1428:   Mat_MPIBAIJ    *mat = (Mat_MPIBAIJ*)matin->data;
1429:   PetscScalar    *vworkA,*vworkB,**pvA,**pvB,*v_p;
1431:   PetscInt       bs = matin->rmap->bs,bs2 = mat->bs2,i,*cworkA,*cworkB,**pcA,**pcB;
1432:   PetscInt       nztot,nzA,nzB,lrow,brstart = matin->rmap->rstart,brend = matin->rmap->rend;
1433:   PetscInt       *cmap,*idx_p,cstart = mat->cstartbs;

1436:   if (row < brstart || row >= brend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local rows");
1437:   if (mat->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Already active");
1438:   mat->getrowactive = PETSC_TRUE;

1440:   if (!mat->rowvalues && (idx || v)) {
1441:     /*
1442:         allocate enough space to hold information from the longest row.
1443:     */
1444:     Mat_SeqBAIJ *Aa = (Mat_SeqBAIJ*)mat->A->data,*Ba = (Mat_SeqBAIJ*)mat->B->data;
1445:     PetscInt    max = 1,mbs = mat->mbs,tmp;
1446:     for (i=0; i<mbs; i++) {
1447:       tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i];
1448:       if (max < tmp) max = tmp;
1449:     }
1450:     PetscMalloc2(max*bs2,PetscScalar,&mat->rowvalues,max*bs2,PetscInt,&mat->rowindices);
1451:   }
1452:   lrow = row - brstart;

1454:   pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB;
1455:   if (!v)   {pvA = 0; pvB = 0;}
1456:   if (!idx) {pcA = 0; if (!v) pcB = 0;}
1457:   (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);
1458:   (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);
1459:   nztot = nzA + nzB;

1461:   cmap = mat->garray;
1462:   if (v  || idx) {
1463:     if (nztot) {
1464:       /* Sort by increasing column numbers, assuming A and B already sorted */
1465:       PetscInt imark = -1;
1466:       if (v) {
1467:         *v = v_p = mat->rowvalues;
1468:         for (i=0; i<nzB; i++) {
1469:           if (cmap[cworkB[i]/bs] < cstart) v_p[i] = vworkB[i];
1470:           else break;
1471:         }
1472:         imark = i;
1473:         for (i=0; i<nzA; i++)     v_p[imark+i] = vworkA[i];
1474:         for (i=imark; i<nzB; i++) v_p[nzA+i]   = vworkB[i];
1475:       }
1476:       if (idx) {
1477:         *idx = idx_p = mat->rowindices;
1478:         if (imark > -1) {
1479:           for (i=0; i<imark; i++) {
1480:             idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs;
1481:           }
1482:         } else {
1483:           for (i=0; i<nzB; i++) {
1484:             if (cmap[cworkB[i]/bs] < cstart) idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs;
1485:             else break;
1486:           }
1487:           imark = i;
1488:         }
1489:         for (i=0; i<nzA; i++)     idx_p[imark+i] = cstart*bs + cworkA[i];
1490:         for (i=imark; i<nzB; i++) idx_p[nzA+i]   = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ;
1491:       }
1492:     } else {
1493:       if (idx) *idx = 0;
1494:       if (v)   *v   = 0;
1495:     }
1496:   }
1497:   *nz  = nztot;
1498:   (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);
1499:   (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);
1500:   return(0);
1501: }

1505: PetscErrorCode MatRestoreRow_MPIBAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
1506: {
1507:   Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data;

1510:   if (!baij->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"MatGetRow not called");
1511:   baij->getrowactive = PETSC_FALSE;
1512:   return(0);
1513: }

1517: PetscErrorCode MatZeroEntries_MPIBAIJ(Mat A)
1518: {
1519:   Mat_MPIBAIJ    *l = (Mat_MPIBAIJ*)A->data;

1523:   MatZeroEntries(l->A);
1524:   MatZeroEntries(l->B);
1525:   return(0);
1526: }

1530: PetscErrorCode MatGetInfo_MPIBAIJ(Mat matin,MatInfoType flag,MatInfo *info)
1531: {
1532:   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)matin->data;
1533:   Mat            A  = a->A,B = a->B;
1535:   PetscReal      isend[5],irecv[5];

1538:   info->block_size = (PetscReal)matin->rmap->bs;

1540:   MatGetInfo(A,MAT_LOCAL,info);

1542:   isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded;
1543:   isend[3] = info->memory;  isend[4] = info->mallocs;

1545:   MatGetInfo(B,MAT_LOCAL,info);

1547:   isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded;
1548:   isend[3] += info->memory;  isend[4] += info->mallocs;

1550:   if (flag == MAT_LOCAL) {
1551:     info->nz_used      = isend[0];
1552:     info->nz_allocated = isend[1];
1553:     info->nz_unneeded  = isend[2];
1554:     info->memory       = isend[3];
1555:     info->mallocs      = isend[4];
1556:   } else if (flag == MAT_GLOBAL_MAX) {
1557:     MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)matin));

1559:     info->nz_used      = irecv[0];
1560:     info->nz_allocated = irecv[1];
1561:     info->nz_unneeded  = irecv[2];
1562:     info->memory       = irecv[3];
1563:     info->mallocs      = irecv[4];
1564:   } else if (flag == MAT_GLOBAL_SUM) {
1565:     MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)matin));

1567:     info->nz_used      = irecv[0];
1568:     info->nz_allocated = irecv[1];
1569:     info->nz_unneeded  = irecv[2];
1570:     info->memory       = irecv[3];
1571:     info->mallocs      = irecv[4];
1572:   } else SETERRQ1(PetscObjectComm((PetscObject)matin),PETSC_ERR_ARG_WRONG,"Unknown MatInfoType argument %d",(int)flag);
1573:   info->fill_ratio_given  = 0; /* no parallel LU/ILU/Cholesky */
1574:   info->fill_ratio_needed = 0;
1575:   info->factor_mallocs    = 0;
1576:   return(0);
1577: }

1581: PetscErrorCode MatSetOption_MPIBAIJ(Mat A,MatOption op,PetscBool flg)
1582: {
1583:   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;

1587:   switch (op) {
1588:   case MAT_NEW_NONZERO_LOCATIONS:
1589:   case MAT_NEW_NONZERO_ALLOCATION_ERR:
1590:   case MAT_UNUSED_NONZERO_LOCATION_ERR:
1591:   case MAT_KEEP_NONZERO_PATTERN:
1592:   case MAT_NEW_NONZERO_LOCATION_ERR:
1593:     MatSetOption(a->A,op,flg);
1594:     MatSetOption(a->B,op,flg);
1595:     break;
1596:   case MAT_ROW_ORIENTED:
1597:     a->roworiented = flg;

1599:     MatSetOption(a->A,op,flg);
1600:     MatSetOption(a->B,op,flg);
1601:     break;
1602:   case MAT_NEW_DIAGONALS:
1603:     PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);
1604:     break;
1605:   case MAT_IGNORE_OFF_PROC_ENTRIES:
1606:     a->donotstash = flg;
1607:     break;
1608:   case MAT_USE_HASH_TABLE:
1609:     a->ht_flag = flg;
1610:     break;
1611:   case MAT_SYMMETRIC:
1612:   case MAT_STRUCTURALLY_SYMMETRIC:
1613:   case MAT_HERMITIAN:
1614:   case MAT_SYMMETRY_ETERNAL:
1615:     MatSetOption(a->A,op,flg);
1616:     break;
1617:   default:
1618:     SETERRQ1(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"unknown option %d",op);
1619:   }
1620:   return(0);
1621: }

1625: PetscErrorCode MatTranspose_MPIBAIJ(Mat A,MatReuse reuse,Mat *matout)
1626: {
1627:   Mat_MPIBAIJ    *baij = (Mat_MPIBAIJ*)A->data;
1628:   Mat_SeqBAIJ    *Aloc;
1629:   Mat            B;
1631:   PetscInt       M =A->rmap->N,N=A->cmap->N,*ai,*aj,i,*rvals,j,k,col;
1632:   PetscInt       bs=A->rmap->bs,mbs=baij->mbs;
1633:   MatScalar      *a;

1636:   if (reuse == MAT_REUSE_MATRIX && A == *matout && M != N) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_SIZ,"Square matrix only for in-place");
1637:   if (reuse == MAT_INITIAL_MATRIX || *matout == A) {
1638:     MatCreate(PetscObjectComm((PetscObject)A),&B);
1639:     MatSetSizes(B,A->cmap->n,A->rmap->n,N,M);
1640:     MatSetType(B,((PetscObject)A)->type_name);
1641:     /* Do not know preallocation information, but must set block size */
1642:     MatMPIBAIJSetPreallocation(B,A->rmap->bs,PETSC_DECIDE,NULL,PETSC_DECIDE,NULL);
1643:   } else {
1644:     B = *matout;
1645:   }

1647:   /* copy over the A part */
1648:   Aloc = (Mat_SeqBAIJ*)baij->A->data;
1649:   ai   = Aloc->i; aj = Aloc->j; a = Aloc->a;
1650:   PetscMalloc(bs*sizeof(PetscInt),&rvals);

1652:   for (i=0; i<mbs; i++) {
1653:     rvals[0] = bs*(baij->rstartbs + i);
1654:     for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1;
1655:     for (j=ai[i]; j<ai[i+1]; j++) {
1656:       col = (baij->cstartbs+aj[j])*bs;
1657:       for (k=0; k<bs; k++) {
1658:         MatSetValues_MPIBAIJ(B,1,&col,bs,rvals,a,INSERT_VALUES);

1660:         col++; a += bs;
1661:       }
1662:     }
1663:   }
1664:   /* copy over the B part */
1665:   Aloc = (Mat_SeqBAIJ*)baij->B->data;
1666:   ai   = Aloc->i; aj = Aloc->j; a = Aloc->a;
1667:   for (i=0; i<mbs; i++) {
1668:     rvals[0] = bs*(baij->rstartbs + i);
1669:     for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1;
1670:     for (j=ai[i]; j<ai[i+1]; j++) {
1671:       col = baij->garray[aj[j]]*bs;
1672:       for (k=0; k<bs; k++) {
1673:         MatSetValues_MPIBAIJ(B,1,&col,bs,rvals,a,INSERT_VALUES);
1674:         col++;
1675:         a += bs;
1676:       }
1677:     }
1678:   }
1679:   PetscFree(rvals);
1680:   MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
1681:   MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);

1683:   if (reuse == MAT_INITIAL_MATRIX || *matout != A) *matout = B;
1684:   else {
1685:     MatHeaderMerge(A,B);
1686:   }
1687:   return(0);
1688: }

1692: PetscErrorCode MatDiagonalScale_MPIBAIJ(Mat mat,Vec ll,Vec rr)
1693: {
1694:   Mat_MPIBAIJ    *baij = (Mat_MPIBAIJ*)mat->data;
1695:   Mat            a     = baij->A,b = baij->B;
1697:   PetscInt       s1,s2,s3;

1700:   MatGetLocalSize(mat,&s2,&s3);
1701:   if (rr) {
1702:     VecGetLocalSize(rr,&s1);
1703:     if (s1!=s3) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"right vector non-conforming local size");
1704:     /* Overlap communication with computation. */
1705:     VecScatterBegin(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);
1706:   }
1707:   if (ll) {
1708:     VecGetLocalSize(ll,&s1);
1709:     if (s1!=s2) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"left vector non-conforming local size");
1710:     (*b->ops->diagonalscale)(b,ll,NULL);
1711:   }
1712:   /* scale  the diagonal block */
1713:   (*a->ops->diagonalscale)(a,ll,rr);

1715:   if (rr) {
1716:     /* Do a scatter end and then right scale the off-diagonal block */
1717:     VecScatterEnd(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);
1718:     (*b->ops->diagonalscale)(b,NULL,baij->lvec);
1719:   }
1720:   return(0);
1721: }

1725: PetscErrorCode MatZeroRows_MPIBAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b)
1726: {
1727:   Mat_MPIBAIJ       *l = (Mat_MPIBAIJ*)A->data;
1728:   PetscErrorCode    ierr;
1729:   PetscMPIInt       imdex,size = l->size,n,rank = l->rank;
1730:   PetscInt          i,*owners = A->rmap->range;
1731:   PetscInt          *nprocs,j,idx,nsends,row;
1732:   PetscInt          nmax,*svalues,*starts,*owner,nrecvs;
1733:   PetscInt          *rvalues,tag = ((PetscObject)A)->tag,count,base,slen,*source,lastidx = -1;
1734:   PetscInt          *lens,*lrows,*values,rstart_bs=A->rmap->rstart;
1735:   MPI_Comm          comm;
1736:   MPI_Request       *send_waits,*recv_waits;
1737:   MPI_Status        recv_status,*send_status;
1738:   const PetscScalar *xx;
1739:   PetscScalar       *bb;
1740: #if defined(PETSC_DEBUG)
1741:   PetscBool         found = PETSC_FALSE;
1742: #endif

1745:   PetscObjectGetComm((PetscObject)A,&comm);
1746:   /*  first count number of contributors to each processor */
1747:   PetscMalloc(2*size*sizeof(PetscInt),&nprocs);
1748:   PetscMemzero(nprocs,2*size*sizeof(PetscInt));
1749:   PetscMalloc((N+1)*sizeof(PetscInt),&owner);  /* see note*/
1750:   j    = 0;
1751:   for (i=0; i<N; i++) {
1752:     if (lastidx > (idx = rows[i])) j = 0;
1753:     lastidx = idx;
1754:     for (; j<size; j++) {
1755:       if (idx >= owners[j] && idx < owners[j+1]) {
1756:         nprocs[2*j]++;
1757:         nprocs[2*j+1] = 1;
1758:         owner[i]      = j;
1759: #if defined(PETSC_DEBUG)
1760:         found = PETSC_TRUE;
1761: #endif
1762:         break;
1763:       }
1764:     }
1765: #if defined(PETSC_DEBUG)
1766:     if (!found) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Index out of range");
1767:     found = PETSC_FALSE;
1768: #endif
1769:   }
1770:   nsends = 0;  for (i=0; i<size; i++) nsends += nprocs[2*i+1];

1772:   if (A->nooffproczerorows) {
1773:     if (nsends > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"You called MatSetOption(,MAT_NO_OFF_PROC_ZERO_ROWS,PETSC_TRUE) but set an off process zero row");
1774:     nrecvs = nsends;
1775:     nmax   = N;
1776:   } else {
1777:     /* inform other processors of number of messages and max length*/
1778:     PetscMaxSum(comm,nprocs,&nmax,&nrecvs);
1779:   }

1781:   /* post receives:   */
1782:   PetscMalloc((nrecvs+1)*(nmax+1)*sizeof(PetscInt),&rvalues);
1783:   PetscMalloc((nrecvs+1)*sizeof(MPI_Request),&recv_waits);
1784:   for (i=0; i<nrecvs; i++) {
1785:     MPI_Irecv(rvalues+nmax*i,nmax,MPIU_INT,MPI_ANY_SOURCE,tag,comm,recv_waits+i);
1786:   }

1788:   /* do sends:
1789:      1) starts[i] gives the starting index in svalues for stuff going to
1790:      the ith processor
1791:   */
1792:   PetscMalloc((N+1)*sizeof(PetscInt),&svalues);
1793:   PetscMalloc((nsends+1)*sizeof(MPI_Request),&send_waits);
1794:   PetscMalloc((size+1)*sizeof(PetscInt),&starts);
1795:   starts[0] = 0;
1796:   for (i=1; i<size; i++) starts[i] = starts[i-1] + nprocs[2*i-2];
1797:   for (i=0; i<N; i++) {
1798:     svalues[starts[owner[i]]++] = rows[i];
1799:   }

1801:   starts[0] = 0;
1802:   for (i=1; i<size+1; i++) starts[i] = starts[i-1] + nprocs[2*i-2];
1803:   count = 0;
1804:   for (i=0; i<size; i++) {
1805:     if (nprocs[2*i+1]) {
1806:       MPI_Isend(svalues+starts[i],nprocs[2*i],MPIU_INT,i,tag,comm,send_waits+count++);
1807:     }
1808:   }
1809:   PetscFree(starts);

1811:   base = owners[rank];

1813:   /*  wait on receives */
1814:   PetscMalloc2(nrecvs+1,PetscInt,&lens,nrecvs+1,PetscInt,&source);
1815:   count = nrecvs;
1816:   slen  = 0;
1817:   while (count) {
1818:     MPI_Waitany(nrecvs,recv_waits,&imdex,&recv_status);
1819:     /* unpack receives into our local space */
1820:     MPI_Get_count(&recv_status,MPIU_INT,&n);

1822:     source[imdex] = recv_status.MPI_SOURCE;
1823:     lens[imdex]   = n;
1824:     slen         += n;
1825:     count--;
1826:   }
1827:   PetscFree(recv_waits);

1829:   /* move the data into the send scatter */
1830:   PetscMalloc((slen+1)*sizeof(PetscInt),&lrows);
1831:   count = 0;
1832:   for (i=0; i<nrecvs; i++) {
1833:     values = rvalues + i*nmax;
1834:     for (j=0; j<lens[i]; j++) {
1835:       lrows[count++] = values[j] - base;
1836:     }
1837:   }
1838:   PetscFree(rvalues);
1839:   PetscFree2(lens,source);
1840:   PetscFree(owner);
1841:   PetscFree(nprocs);

1843:   /* fix right hand side if needed */
1844:   if (x && b) {
1845:     VecGetArrayRead(x,&xx);
1846:     VecGetArray(b,&bb);
1847:     for (i=0; i<slen; i++) {
1848:       bb[lrows[i]] = diag*xx[lrows[i]];
1849:     }
1850:     VecRestoreArrayRead(x,&xx);
1851:     VecRestoreArray(b,&bb);
1852:   }

1854:   /* actually zap the local rows */
1855:   /*
1856:         Zero the required rows. If the "diagonal block" of the matrix
1857:      is square and the user wishes to set the diagonal we use separate
1858:      code so that MatSetValues() is not called for each diagonal allocating
1859:      new memory, thus calling lots of mallocs and slowing things down.

1861:   */
1862:   /* must zero l->B before l->A because the (diag) case below may put values into l->B*/
1863:   MatZeroRows_SeqBAIJ(l->B,slen,lrows,0.0,0,0);
1864:   if ((diag != 0.0) && (l->A->rmap->N == l->A->cmap->N)) {
1865:     MatZeroRows_SeqBAIJ(l->A,slen,lrows,diag,0,0);
1866:   } else if (diag != 0.0) {
1867:     MatZeroRows_SeqBAIJ(l->A,slen,lrows,0.0,0,0);
1868:     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\
1869:        MAT_NEW_NONZERO_LOCATIONS,MAT_NEW_NONZERO_LOCATION_ERR,MAT_NEW_NONZERO_ALLOCATION_ERR");
1870:     for (i=0; i<slen; i++) {
1871:       row  = lrows[i] + rstart_bs;
1872:       MatSetValues(A,1,&row,1,&row,&diag,INSERT_VALUES);
1873:     }
1874:     MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);
1875:     MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);
1876:   } else {
1877:     MatZeroRows_SeqBAIJ(l->A,slen,lrows,0.0,0,0);
1878:   }

1880:   PetscFree(lrows);

1882:   /* wait on sends */
1883:   if (nsends) {
1884:     PetscMalloc(nsends*sizeof(MPI_Status),&send_status);
1885:     MPI_Waitall(nsends,send_waits,send_status);
1886:     PetscFree(send_status);
1887:   }
1888:   PetscFree(send_waits);
1889:   PetscFree(svalues);
1890:   return(0);
1891: }

1895: PetscErrorCode MatSetUnfactored_MPIBAIJ(Mat A)
1896: {
1897:   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;

1901:   MatSetUnfactored(a->A);
1902:   return(0);
1903: }

1905: static PetscErrorCode MatDuplicate_MPIBAIJ(Mat,MatDuplicateOption,Mat*);

1909: PetscErrorCode MatEqual_MPIBAIJ(Mat A,Mat B,PetscBool  *flag)
1910: {
1911:   Mat_MPIBAIJ    *matB = (Mat_MPIBAIJ*)B->data,*matA = (Mat_MPIBAIJ*)A->data;
1912:   Mat            a,b,c,d;
1913:   PetscBool      flg;

1917:   a = matA->A; b = matA->B;
1918:   c = matB->A; d = matB->B;

1920:   MatEqual(a,c,&flg);
1921:   if (flg) {
1922:     MatEqual(b,d,&flg);
1923:   }
1924:   MPI_Allreduce(&flg,flag,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)A));
1925:   return(0);
1926: }

1930: PetscErrorCode MatCopy_MPIBAIJ(Mat A,Mat B,MatStructure str)
1931: {
1933:   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;
1934:   Mat_MPIBAIJ    *b = (Mat_MPIBAIJ*)B->data;

1937:   /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */
1938:   if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) {
1939:     MatCopy_Basic(A,B,str);
1940:   } else {
1941:     MatCopy(a->A,b->A,str);
1942:     MatCopy(a->B,b->B,str);
1943:   }
1944:   return(0);
1945: }

1949: PetscErrorCode MatSetUp_MPIBAIJ(Mat A)
1950: {

1954:    MatMPIBAIJSetPreallocation(A,A->rmap->bs,PETSC_DEFAULT,0,PETSC_DEFAULT,0);
1955:   return(0);
1956: }

1960: PetscErrorCode MatAXPY_MPIBAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str)
1961: {
1963:   Mat_MPIBAIJ    *xx=(Mat_MPIBAIJ*)X->data,*yy=(Mat_MPIBAIJ*)Y->data;
1964:   PetscBLASInt   bnz,one=1;
1965:   Mat_SeqBAIJ    *x,*y;

1968:   if (str == SAME_NONZERO_PATTERN) {
1969:     PetscScalar alpha = a;
1970:     x    = (Mat_SeqBAIJ*)xx->A->data;
1971:     y    = (Mat_SeqBAIJ*)yy->A->data;
1972:     PetscBLASIntCast(x->nz,&bnz);
1973:     PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one));
1974:     x    = (Mat_SeqBAIJ*)xx->B->data;
1975:     y    = (Mat_SeqBAIJ*)yy->B->data;
1976:     PetscBLASIntCast(x->nz,&bnz);
1977:     PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one));
1978:   } else {
1979:     MatAXPY_Basic(Y,a,X,str);
1980:   }
1981:   return(0);
1982: }

1986: PetscErrorCode MatRealPart_MPIBAIJ(Mat A)
1987: {
1988:   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;

1992:   MatRealPart(a->A);
1993:   MatRealPart(a->B);
1994:   return(0);
1995: }

1999: PetscErrorCode MatImaginaryPart_MPIBAIJ(Mat A)
2000: {
2001:   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;

2005:   MatImaginaryPart(a->A);
2006:   MatImaginaryPart(a->B);
2007:   return(0);
2008: }

2012: PetscErrorCode MatGetSubMatrix_MPIBAIJ(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat)
2013: {
2015:   IS             iscol_local;
2016:   PetscInt       csize;

2019:   ISGetLocalSize(iscol,&csize);
2020:   if (call == MAT_REUSE_MATRIX) {
2021:     PetscObjectQuery((PetscObject)*newmat,"ISAllGather",(PetscObject*)&iscol_local);
2022:     if (!iscol_local) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse");
2023:   } else {
2024:     ISAllGather(iscol,&iscol_local);
2025:   }
2026:   MatGetSubMatrix_MPIBAIJ_Private(mat,isrow,iscol_local,csize,call,newmat);
2027:   if (call == MAT_INITIAL_MATRIX) {
2028:     PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);
2029:     ISDestroy(&iscol_local);
2030:   }
2031:   return(0);
2032: }
2033: extern PetscErrorCode MatGetSubMatrices_MPIBAIJ_local(Mat,PetscInt,const IS[],const IS[],MatReuse,PetscBool*,PetscBool*,Mat*);
2036: /*
2037:   Not great since it makes two copies of the submatrix, first an SeqBAIJ
2038:   in local and then by concatenating the local matrices the end result.
2039:   Writing it directly would be much like MatGetSubMatrices_MPIBAIJ()
2040: */
2041: PetscErrorCode MatGetSubMatrix_MPIBAIJ_Private(Mat mat,IS isrow,IS iscol,PetscInt csize,MatReuse call,Mat *newmat)
2042: {
2044:   PetscMPIInt    rank,size;
2045:   PetscInt       i,m,n,rstart,row,rend,nz,*cwork,j,bs;
2046:   PetscInt       *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal,ncol,nrow;
2047:   Mat            M,Mreuse;
2048:   MatScalar      *vwork,*aa;
2049:   MPI_Comm       comm;
2050:   IS             isrow_new, iscol_new;
2051:   PetscBool      idflag,allrows, allcols;
2052:   Mat_SeqBAIJ    *aij;

2055:   PetscObjectGetComm((PetscObject)mat,&comm);
2056:   MPI_Comm_rank(comm,&rank);
2057:   MPI_Comm_size(comm,&size);
2058:   /* The compression and expansion should be avoided. Doesn't point
2059:      out errors, might change the indices, hence buggey */
2060:   ISCompressIndicesGeneral(mat->rmap->N,mat->rmap->n,mat->rmap->bs,1,&isrow,&isrow_new);
2061:   ISCompressIndicesGeneral(mat->cmap->N,mat->cmap->n,mat->cmap->bs,1,&iscol,&iscol_new);

2063:   /* Check for special case: each processor gets entire matrix columns */
2064:   ISIdentity(iscol,&idflag);
2065:   ISGetLocalSize(iscol,&ncol);
2066:   if (idflag && ncol == mat->cmap->N) allcols = PETSC_TRUE;
2067:   else allcols = PETSC_FALSE;

2069:   ISIdentity(isrow,&idflag);
2070:   ISGetLocalSize(isrow,&nrow);
2071:   if (idflag && nrow == mat->rmap->N) allrows = PETSC_TRUE;
2072:   else allrows = PETSC_FALSE;

2074:   if (call ==  MAT_REUSE_MATRIX) {
2075:     PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject*)&Mreuse);
2076:     if (!Mreuse) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse");
2077:     MatGetSubMatrices_MPIBAIJ_local(mat,1,&isrow_new,&iscol_new,MAT_REUSE_MATRIX,&allrows,&allcols,&Mreuse);
2078:   } else {
2079:     MatGetSubMatrices_MPIBAIJ_local(mat,1,&isrow_new,&iscol_new,MAT_INITIAL_MATRIX,&allrows,&allcols,&Mreuse);
2080:   }
2081:   ISDestroy(&isrow_new);
2082:   ISDestroy(&iscol_new);
2083:   /*
2084:       m - number of local rows
2085:       n - number of columns (same on all processors)
2086:       rstart - first row in new global matrix generated
2087:   */
2088:   MatGetBlockSize(mat,&bs);
2089:   MatGetSize(Mreuse,&m,&n);
2090:   m    = m/bs;
2091:   n    = n/bs;

2093:   if (call == MAT_INITIAL_MATRIX) {
2094:     aij = (Mat_SeqBAIJ*)(Mreuse)->data;
2095:     ii  = aij->i;
2096:     jj  = aij->j;

2098:     /*
2099:         Determine the number of non-zeros in the diagonal and off-diagonal
2100:         portions of the matrix in order to do correct preallocation
2101:     */

2103:     /* first get start and end of "diagonal" columns */
2104:     if (csize == PETSC_DECIDE) {
2105:       ISGetSize(isrow,&mglobal);
2106:       if (mglobal == n*bs) { /* square matrix */
2107:         nlocal = m;
2108:       } else {
2109:         nlocal = n/size + ((n % size) > rank);
2110:       }
2111:     } else {
2112:       nlocal = csize/bs;
2113:     }
2114:     MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);
2115:     rstart = rend - nlocal;
2116:     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);

2118:     /* next, compute all the lengths */
2119:     PetscMalloc((2*m+1)*sizeof(PetscInt),&dlens);
2120:     olens = dlens + m;
2121:     for (i=0; i<m; i++) {
2122:       jend = ii[i+1] - ii[i];
2123:       olen = 0;
2124:       dlen = 0;
2125:       for (j=0; j<jend; j++) {
2126:         if (*jj < rstart || *jj >= rend) olen++;
2127:         else dlen++;
2128:         jj++;
2129:       }
2130:       olens[i] = olen;
2131:       dlens[i] = dlen;
2132:     }
2133:     MatCreate(comm,&M);
2134:     MatSetSizes(M,bs*m,bs*nlocal,PETSC_DECIDE,bs*n);
2135:     MatSetType(M,((PetscObject)mat)->type_name);
2136:     MatMPIBAIJSetPreallocation(M,bs,0,dlens,0,olens);
2137:     PetscFree(dlens);
2138:   } else {
2139:     PetscInt ml,nl;

2141:     M    = *newmat;
2142:     MatGetLocalSize(M,&ml,&nl);
2143:     if (ml != m) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request");
2144:     MatZeroEntries(M);
2145:     /*
2146:          The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly,
2147:        rather than the slower MatSetValues().
2148:     */
2149:     M->was_assembled = PETSC_TRUE;
2150:     M->assembled     = PETSC_FALSE;
2151:   }
2152:   MatSetOption(M,MAT_ROW_ORIENTED,PETSC_FALSE);
2153:   MatGetOwnershipRange(M,&rstart,&rend);
2154:   aij  = (Mat_SeqBAIJ*)(Mreuse)->data;
2155:   ii   = aij->i;
2156:   jj   = aij->j;
2157:   aa   = aij->a;
2158:   for (i=0; i<m; i++) {
2159:     row   = rstart/bs + i;
2160:     nz    = ii[i+1] - ii[i];
2161:     cwork = jj;     jj += nz;
2162:     vwork = aa;     aa += nz*bs*bs;
2163:     MatSetValuesBlocked_MPIBAIJ(M,1,&row,nz,cwork,vwork,INSERT_VALUES);
2164:   }

2166:   MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);
2167:   MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);
2168:   *newmat = M;

2170:   /* save submatrix used in processor for next request */
2171:   if (call ==  MAT_INITIAL_MATRIX) {
2172:     PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Mreuse);
2173:     PetscObjectDereference((PetscObject)Mreuse);
2174:   }
2175:   return(0);
2176: }

2180: PetscErrorCode MatPermute_MPIBAIJ(Mat A,IS rowp,IS colp,Mat *B)
2181: {
2182:   MPI_Comm       comm,pcomm;
2183:   PetscInt       first,rlocal_size,clocal_size,nrows;
2184:   const PetscInt *rows;
2185:   PetscMPIInt    size;
2186:   IS             crowp,growp,irowp,lrowp,lcolp;

2190:   PetscObjectGetComm((PetscObject)A,&comm);
2191:   /* make a collective version of 'rowp' */
2192:   PetscObjectGetComm((PetscObject)rowp,&pcomm);
2193:   if (pcomm==comm) {
2194:     crowp = rowp;
2195:   } else {
2196:     ISGetSize(rowp,&nrows);
2197:     ISGetIndices(rowp,&rows);
2198:     ISCreateGeneral(comm,nrows,rows,PETSC_COPY_VALUES,&crowp);
2199:     ISRestoreIndices(rowp,&rows);
2200:   }
2201:   /* collect the global row permutation and invert it */
2202:   ISAllGather(crowp,&growp);
2203:   ISSetPermutation(growp);
2204:   if (pcomm!=comm) {
2205:     ISDestroy(&crowp);
2206:   }
2207:   ISInvertPermutation(growp,PETSC_DECIDE,&irowp);
2208:   ISDestroy(&growp);
2209:   /* get the local target indices */
2210:   MatGetOwnershipRange(A,&first,NULL);
2211:   MatGetLocalSize(A,&rlocal_size,&clocal_size);
2212:   ISGetIndices(irowp,&rows);
2213:   ISCreateGeneral(MPI_COMM_SELF,rlocal_size,rows+first,PETSC_COPY_VALUES,&lrowp);
2214:   ISRestoreIndices(irowp,&rows);
2215:   ISDestroy(&irowp);
2216:   /* the column permutation is so much easier;
2217:      make a local version of 'colp' and invert it */
2218:   PetscObjectGetComm((PetscObject)colp,&pcomm);
2219:   MPI_Comm_size(pcomm,&size);
2220:   if (size==1) {
2221:     lcolp = colp;
2222:   } else {
2223:     ISAllGather(colp,&lcolp);
2224:   }
2225:   ISSetPermutation(lcolp);
2226:   /* now we just get the submatrix */
2227:   MatGetSubMatrix_MPIBAIJ_Private(A,lrowp,lcolp,clocal_size,MAT_INITIAL_MATRIX,B);
2228:   if (size>1) {
2229:     ISDestroy(&lcolp);
2230:   }
2231:   /* clean up */
2232:   ISDestroy(&lrowp);
2233:   return(0);
2234: }

2238: PetscErrorCode  MatGetGhosts_MPIBAIJ(Mat mat,PetscInt *nghosts,const PetscInt *ghosts[])
2239: {
2240:   Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*) mat->data;
2241:   Mat_SeqBAIJ *B    = (Mat_SeqBAIJ*)baij->B->data;

2244:   if (nghosts) *nghosts = B->nbs;
2245:   if (ghosts) *ghosts = baij->garray;
2246:   return(0);
2247: }

2249: extern PetscErrorCode MatCreateColmap_MPIBAIJ_Private(Mat);

2253: /*
2254:     This routine is almost identical to MatFDColoringCreate_MPIBAIJ()!
2255: */
2256: PetscErrorCode MatFDColoringCreate_MPIBAIJ(Mat mat,ISColoring iscoloring,MatFDColoring c)
2257: {
2258:   Mat_MPIBAIJ            *baij = (Mat_MPIBAIJ*)mat->data;
2259:   PetscErrorCode         ierr;
2260:   PetscMPIInt            size,*ncolsonproc,*disp,nn;
2261:   PetscInt               bs,i,n,nrows,j,k,m,ncols,col;
2262:   const PetscInt         *is,*rows = 0,*A_ci,*A_cj,*B_ci,*B_cj,*ltog;
2263:   PetscInt               nis = iscoloring->n,nctot,*cols;
2264:   PetscInt               *rowhit,M,cstart,cend,colb;
2265:   PetscInt               *columnsforrow,l;
2266:   IS                     *isa;
2267:   PetscBool              done,flg;
2268:   ISLocalToGlobalMapping map = mat->cmap->bmapping;
2269:   PetscInt               ctype=c->ctype;

2272:   if (!mat->assembled) SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_ARG_WRONGSTATE,"Matrix must be assembled first; MatAssemblyBegin/End();");
2273:   if (ctype == IS_COLORING_GHOSTED && !map) SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_ARG_INCOMP,"When using ghosted differencing matrix must have local to global mapping provided with MatSetLocalToGlobalMappingBlock");

2275:   if (map) {ISLocalToGlobalMappingGetIndices(map,&ltog);}
2276:   else     ltog = NULL;
2277:   ISColoringGetIS(iscoloring,PETSC_IGNORE,&isa);
2278:   MatGetBlockSize(mat,&bs);

2280:   M         = mat->rmap->n/bs;
2281:   cstart    = mat->cmap->rstart/bs;
2282:   cend      = mat->cmap->rend/bs;
2283:   c->M      = mat->rmap->N/bs;         /* set the global rows and columns and local rows */
2284:   c->N      = mat->cmap->N/bs;
2285:   c->m      = mat->rmap->n/bs;
2286:   c->rstart = mat->rmap->rstart/bs;

2288:   c->ncolors = nis;
2289:   PetscMalloc(nis*sizeof(PetscInt),&c->ncolumns);
2290:   PetscMalloc(nis*sizeof(PetscInt*),&c->columns);
2291:   PetscMalloc(nis*sizeof(PetscInt),&c->nrows);
2292:   PetscMalloc(nis*sizeof(PetscInt*),&c->rows);
2293:   PetscMalloc(nis*sizeof(PetscInt*),&c->columnsforrow);
2294:   PetscLogObjectMemory(c,5*nis*sizeof(PetscInt));

2296:   /* Allow access to data structures of local part of matrix */
2297:   if (!baij->colmap) {
2298:     MatCreateColmap_MPIBAIJ_Private(mat);
2299:   }
2300:   MatGetColumnIJ(baij->A,0,PETSC_FALSE,PETSC_FALSE,&ncols,&A_ci,&A_cj,&done);
2301:   MatGetColumnIJ(baij->B,0,PETSC_FALSE,PETSC_FALSE,&ncols,&B_ci,&B_cj,&done);

2303:   PetscMalloc((M+1)*sizeof(PetscInt),&rowhit);
2304:   PetscMalloc((M+1)*sizeof(PetscInt),&columnsforrow);

2306:   for (i=0; i<nis; i++) {
2307:     ISGetLocalSize(isa[i],&n);
2308:     ISGetIndices(isa[i],&is);

2310:     c->ncolumns[i] = n;
2311:     if (n) {
2312:       PetscMalloc(n*sizeof(PetscInt),&c->columns[i]);
2313:       PetscLogObjectMemory(c,n*sizeof(PetscInt));
2314:       PetscMemcpy(c->columns[i],is,n*sizeof(PetscInt));
2315:     } else {
2316:       c->columns[i] = 0;
2317:     }

2319:     if (ctype == IS_COLORING_GLOBAL) {
2320:       /* Determine the total (parallel) number of columns of this color */
2321:       MPI_Comm_size(PetscObjectComm((PetscObject)mat),&size);
2322:       PetscMalloc2(size,PetscMPIInt,&ncolsonproc,size,PetscMPIInt,&disp);

2324:       PetscMPIIntCast(n,&nn);
2325:       MPI_Allgather(&nn,1,MPI_INT,ncolsonproc,1,MPI_INT,PetscObjectComm((PetscObject)mat));
2326:       nctot = 0; for (j=0; j<size; j++) nctot += ncolsonproc[j];
2327:       if (!nctot) {
2328:         PetscInfo(mat,"Coloring of matrix has some unneeded colors with no corresponding rows\n");
2329:       }

2331:       disp[0] = 0;
2332:       for (j=1; j<size; j++) {
2333:         disp[j] = disp[j-1] + ncolsonproc[j-1];
2334:       }

2336:       /* Get complete list of columns for color on each processor */
2337:       PetscMalloc((nctot+1)*sizeof(PetscInt),&cols);
2338:       MPI_Allgatherv((void*)is,n,MPIU_INT,cols,ncolsonproc,disp,MPIU_INT,PetscObjectComm((PetscObject)mat));
2339:       PetscFree2(ncolsonproc,disp);
2340:     } else if (ctype == IS_COLORING_GHOSTED) {
2341:       /* Determine local number of columns of this color on this process, including ghost points */
2342:       nctot = n;
2343:       PetscMalloc((nctot+1)*sizeof(PetscInt),&cols);
2344:       PetscMemcpy(cols,is,n*sizeof(PetscInt));
2345:     } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Not provided for this MatFDColoring type");

2347:     /*
2348:        Mark all rows affect by these columns
2349:     */
2350:     /* Temporary option to allow for debugging/testing */
2351:     flg  = PETSC_FALSE;
2352:     PetscOptionsGetBool(NULL,"-matfdcoloring_slow",&flg,NULL);
2353:     if (!flg) { /*-----------------------------------------------------------------------------*/
2354:       /* crude, fast version */
2355:       PetscMemzero(rowhit,M*sizeof(PetscInt));
2356:       /* loop over columns*/
2357:       for (j=0; j<nctot; j++) {
2358:         if (ctype == IS_COLORING_GHOSTED) {
2359:           col = ltog[cols[j]];
2360:         } else {
2361:           col = cols[j];
2362:         }
2363:         if (col >= cstart && col < cend) {
2364:           /* column is in diagonal block of matrix */
2365:           rows = A_cj + A_ci[col-cstart];
2366:           m    = A_ci[col-cstart+1] - A_ci[col-cstart];
2367:         } else {
2368: #if defined(PETSC_USE_CTABLE)
2369:           PetscTableFind(baij->colmap,col+1,&colb);
2370:           colb--;
2371: #else
2372:           colb = baij->colmap[col] - 1;
2373: #endif
2374:           if (colb == -1) {
2375:             m = 0;
2376:           } else {
2377:             colb = colb/bs;
2378:             rows = B_cj + B_ci[colb];
2379:             m    = B_ci[colb+1] - B_ci[colb];
2380:           }
2381:         }
2382:         /* loop over columns marking them in rowhit */
2383:         for (k=0; k<m; k++) {
2384:           rowhit[*rows++] = col + 1;
2385:         }
2386:       }

2388:       /* count the number of hits */
2389:       nrows = 0;
2390:       for (j=0; j<M; j++) {
2391:         if (rowhit[j]) nrows++;
2392:       }
2393:       c->nrows[i] = nrows;
2394:       PetscMalloc((nrows+1)*sizeof(PetscInt),&c->rows[i]);
2395:       PetscMalloc((nrows+1)*sizeof(PetscInt),&c->columnsforrow[i]);
2396:       PetscLogObjectMemory(c,2*(nrows+1)*sizeof(PetscInt));
2397:       nrows       = 0;
2398:       for (j=0; j<M; j++) {
2399:         if (rowhit[j]) {
2400:           c->rows[i][nrows]          = j;
2401:           c->columnsforrow[i][nrows] = rowhit[j] - 1;
2402:           nrows++;
2403:         }
2404:       }
2405:     } else { /*-------------------------------------------------------------------------------*/
2406:       /* slow version, using rowhit as a linked list */
2407:       PetscInt currentcol,fm,mfm;
2408:       rowhit[M] = M;
2409:       nrows     = 0;
2410:       /* loop over columns*/
2411:       for (j=0; j<nctot; j++) {
2412:         if (ctype == IS_COLORING_GHOSTED) {
2413:           col = ltog[cols[j]];
2414:         } else {
2415:           col = cols[j];
2416:         }
2417:         if (col >= cstart && col < cend) {
2418:           /* column is in diagonal block of matrix */
2419:           rows = A_cj + A_ci[col-cstart];
2420:           m    = A_ci[col-cstart+1] - A_ci[col-cstart];
2421:         } else {
2422: #if defined(PETSC_USE_CTABLE)
2423:           PetscTableFind(baij->colmap,col+1,&colb);
2424:           colb--;
2425: #else
2426:           colb = baij->colmap[col] - 1;
2427: #endif
2428:           if (colb == -1) {
2429:             m = 0;
2430:           } else {
2431:             colb = colb/bs;
2432:             rows = B_cj + B_ci[colb];
2433:             m    = B_ci[colb+1] - B_ci[colb];
2434:           }
2435:         }

2437:         /* loop over columns marking them in rowhit */
2438:         fm = M;    /* fm points to first entry in linked list */
2439:         for (k=0; k<m; k++) {
2440:           currentcol = *rows++;
2441:           /* is it already in the list? */
2442:           do {
2443:             mfm = fm;
2444:             fm  = rowhit[fm];
2445:           } while (fm < currentcol);
2446:           /* not in list so add it */
2447:           if (fm != currentcol) {
2448:             nrows++;
2449:             columnsforrow[currentcol] = col;
2450:             /* next three lines insert new entry into linked list */
2451:             rowhit[mfm]        = currentcol;
2452:             rowhit[currentcol] = fm;
2453:             fm                 = currentcol;
2454:             /* fm points to present position in list since we know the columns are sorted */
2455:           } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Invalid coloring of matrix detected");
2456:         }
2457:       }
2458:       c->nrows[i] = nrows;
2459:       PetscMalloc((nrows+1)*sizeof(PetscInt),&c->rows[i]);
2460:       PetscMalloc((nrows+1)*sizeof(PetscInt),&c->columnsforrow[i]);
2461:       PetscLogObjectMemory(c,(nrows+1)*sizeof(PetscInt));
2462:       /* now store the linked list of rows into c->rows[i] */
2463:       nrows = 0;
2464:       fm    = rowhit[M];
2465:       do {
2466:         c->rows[i][nrows]            = fm;
2467:         c->columnsforrow[i][nrows++] = columnsforrow[fm];
2468:         fm                           = rowhit[fm];
2469:       } while (fm < M);
2470:     } /* ---------------------------------------------------------------------------------------*/
2471:     PetscFree(cols);
2472:   }

2474:   /* Optimize by adding the vscale, and scaleforrow[][] fields */
2475:   /*
2476:        vscale will contain the "diagonal" on processor scalings followed by the off processor
2477:   */
2478:   if (ctype == IS_COLORING_GLOBAL) {
2479:     PetscInt *garray;
2480:     PetscMalloc(baij->B->cmap->n*sizeof(PetscInt),&garray);
2481:     for (i=0; i<baij->B->cmap->n/bs; i++) {
2482:       for (j=0; j<bs; j++) {
2483:         garray[i*bs+j] = bs*baij->garray[i]+j;
2484:       }
2485:     }
2486:     VecCreateGhost(PetscObjectComm((PetscObject)mat),baij->A->rmap->n,PETSC_DETERMINE,baij->B->cmap->n,garray,&c->vscale);
2487:     PetscFree(garray);
2488:     PetscMalloc(c->ncolors*sizeof(PetscInt*),&c->vscaleforrow);
2489:     for (k=0; k<c->ncolors; k++) {
2490:       PetscMalloc((c->nrows[k]+1)*sizeof(PetscInt),&c->vscaleforrow[k]);
2491:       for (l=0; l<c->nrows[k]; l++) {
2492:         col = c->columnsforrow[k][l];
2493:         if (col >= cstart && col < cend) {
2494:           /* column is in diagonal block of matrix */
2495:           colb = col - cstart;
2496:         } else {
2497:           /* column  is in "off-processor" part */
2498: #if defined(PETSC_USE_CTABLE)
2499:           PetscTableFind(baij->colmap,col+1,&colb);
2500:           colb--;
2501: #else
2502:           colb = baij->colmap[col] - 1;
2503: #endif
2504:           colb  = colb/bs;
2505:           colb += cend - cstart;
2506:         }
2507:         c->vscaleforrow[k][l] = colb;
2508:       }
2509:     }
2510:   } else if (ctype == IS_COLORING_GHOSTED) {
2511:     /* Get gtol mapping */
2512:     PetscInt N = mat->cmap->N,nlocal,*gtol;
2513:     PetscMalloc((N+1)*sizeof(PetscInt),&gtol);
2514:     for (i=0; i<N; i++) gtol[i] = -1;
2515:     ISLocalToGlobalMappingGetSize(map,&nlocal);
2516:     for (i=0; i<nlocal; i++) gtol[ltog[i]] = i;

2518:     c->vscale = 0; /* will be created in MatFDColoringApply() */
2519:     PetscMalloc(c->ncolors*sizeof(PetscInt*),&c->vscaleforrow);
2520:     for (k=0; k<c->ncolors; k++) {
2521:       PetscMalloc((c->nrows[k]+1)*sizeof(PetscInt),&c->vscaleforrow[k]);
2522:       for (l=0; l<c->nrows[k]; l++) {
2523:         col = c->columnsforrow[k][l];      /* global column index */

2525:         c->vscaleforrow[k][l] = gtol[col]; /* local column index */
2526:       }
2527:     }
2528:     PetscFree(gtol);
2529:   }
2530:   ISColoringRestoreIS(iscoloring,&isa);

2532:   PetscFree(rowhit);
2533:   PetscFree(columnsforrow);
2534:   MatRestoreColumnIJ(baij->A,0,PETSC_FALSE,PETSC_FALSE,&ncols,&A_ci,&A_cj,&done);
2535:   MatRestoreColumnIJ(baij->B,0,PETSC_FALSE,PETSC_FALSE,&ncols,&B_ci,&B_cj,&done);
2536:   if (map) {ISLocalToGlobalMappingRestoreIndices(map,&ltog);}
2537:   return(0);
2538: }

2542: PetscErrorCode MatGetSeqNonzeroStructure_MPIBAIJ(Mat A,Mat *newmat)
2543: {
2544:   Mat            B;
2545:   Mat_MPIBAIJ    *a  = (Mat_MPIBAIJ*)A->data;
2546:   Mat_SeqBAIJ    *ad = (Mat_SeqBAIJ*)a->A->data,*bd = (Mat_SeqBAIJ*)a->B->data;
2547:   Mat_SeqAIJ     *b;
2549:   PetscMPIInt    size,rank,*recvcounts = 0,*displs = 0;
2550:   PetscInt       sendcount,i,*rstarts = A->rmap->range,n,cnt,j,bs = A->rmap->bs;
2551:   PetscInt       m,*garray = a->garray,*lens,*jsendbuf,*a_jsendbuf,*b_jsendbuf;

2554:   MPI_Comm_size(PetscObjectComm((PetscObject)A),&size);
2555:   MPI_Comm_rank(PetscObjectComm((PetscObject)A),&rank);

2557:   /* ----------------------------------------------------------------
2558:      Tell every processor the number of nonzeros per row
2559:   */
2560:   PetscMalloc((A->rmap->N/bs)*sizeof(PetscInt),&lens);
2561:   for (i=A->rmap->rstart/bs; i<A->rmap->rend/bs; i++) {
2562:     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];
2563:   }
2564:   sendcount = A->rmap->rend/bs - A->rmap->rstart/bs;
2565:   PetscMalloc(2*size*sizeof(PetscMPIInt),&recvcounts);
2566:   displs    = recvcounts + size;
2567:   for (i=0; i<size; i++) {
2568:     recvcounts[i] = A->rmap->range[i+1]/bs - A->rmap->range[i]/bs;
2569:     displs[i]     = A->rmap->range[i]/bs;
2570:   }
2571: #if defined(PETSC_HAVE_MPI_IN_PLACE)
2572:   MPI_Allgatherv(MPI_IN_PLACE,0,MPI_DATATYPE_NULL,lens,recvcounts,displs,MPIU_INT,PetscObjectComm((PetscObject)A));
2573: #else
2574:   MPI_Allgatherv(lens+A->rmap->rstart/bs,sendcount,MPIU_INT,lens,recvcounts,displs,MPIU_INT,PetscObjectComm((PetscObject)A));
2575: #endif
2576:   /* ---------------------------------------------------------------
2577:      Create the sequential matrix of the same type as the local block diagonal
2578:   */
2579:   MatCreate(PETSC_COMM_SELF,&B);
2580:   MatSetSizes(B,A->rmap->N/bs,A->cmap->N/bs,PETSC_DETERMINE,PETSC_DETERMINE);
2581:   MatSetType(B,MATSEQAIJ);
2582:   MatSeqAIJSetPreallocation(B,0,lens);
2583:   b    = (Mat_SeqAIJ*)B->data;

2585:   /*--------------------------------------------------------------------
2586:     Copy my part of matrix column indices over
2587:   */
2588:   sendcount  = ad->nz + bd->nz;
2589:   jsendbuf   = b->j + b->i[rstarts[rank]/bs];
2590:   a_jsendbuf = ad->j;
2591:   b_jsendbuf = bd->j;
2592:   n          = A->rmap->rend/bs - A->rmap->rstart/bs;
2593:   cnt        = 0;
2594:   for (i=0; i<n; i++) {

2596:     /* put in lower diagonal portion */
2597:     m = bd->i[i+1] - bd->i[i];
2598:     while (m > 0) {
2599:       /* is it above diagonal (in bd (compressed) numbering) */
2600:       if (garray[*b_jsendbuf] > A->rmap->rstart/bs + i) break;
2601:       jsendbuf[cnt++] = garray[*b_jsendbuf++];
2602:       m--;
2603:     }

2605:     /* put in diagonal portion */
2606:     for (j=ad->i[i]; j<ad->i[i+1]; j++) {
2607:       jsendbuf[cnt++] = A->rmap->rstart/bs + *a_jsendbuf++;
2608:     }

2610:     /* put in upper diagonal portion */
2611:     while (m-- > 0) {
2612:       jsendbuf[cnt++] = garray[*b_jsendbuf++];
2613:     }
2614:   }
2615:   if (cnt != sendcount) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Corrupted PETSc matrix: nz given %D actual nz %D",sendcount,cnt);

2617:   /*--------------------------------------------------------------------
2618:     Gather all column indices to all processors
2619:   */
2620:   for (i=0; i<size; i++) {
2621:     recvcounts[i] = 0;
2622:     for (j=A->rmap->range[i]/bs; j<A->rmap->range[i+1]/bs; j++) {
2623:       recvcounts[i] += lens[j];
2624:     }
2625:   }
2626:   displs[0] = 0;
2627:   for (i=1; i<size; i++) {
2628:     displs[i] = displs[i-1] + recvcounts[i-1];
2629:   }
2630: #if defined(PETSC_HAVE_MPI_IN_PLACE)
2631:   MPI_Allgatherv(MPI_IN_PLACE,0,MPI_DATATYPE_NULL,b->j,recvcounts,displs,MPIU_INT,PetscObjectComm((PetscObject)A));
2632: #else
2633:   MPI_Allgatherv(jsendbuf,sendcount,MPIU_INT,b->j,recvcounts,displs,MPIU_INT,PetscObjectComm((PetscObject)A));
2634: #endif
2635:   /*--------------------------------------------------------------------
2636:     Assemble the matrix into useable form (note numerical values not yet set)
2637:   */
2638:   /* set the b->ilen (length of each row) values */
2639:   PetscMemcpy(b->ilen,lens,(A->rmap->N/bs)*sizeof(PetscInt));
2640:   /* set the b->i indices */
2641:   b->i[0] = 0;
2642:   for (i=1; i<=A->rmap->N/bs; i++) {
2643:     b->i[i] = b->i[i-1] + lens[i-1];
2644:   }
2645:   PetscFree(lens);
2646:   MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
2647:   MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);
2648:   PetscFree(recvcounts);

2650:   if (A->symmetric) {
2651:     MatSetOption(B,MAT_SYMMETRIC,PETSC_TRUE);
2652:   } else if (A->hermitian) {
2653:     MatSetOption(B,MAT_HERMITIAN,PETSC_TRUE);
2654:   } else if (A->structurally_symmetric) {
2655:     MatSetOption(B,MAT_STRUCTURALLY_SYMMETRIC,PETSC_TRUE);
2656:   }
2657:   *newmat = B;
2658:   return(0);
2659: }

2663: PetscErrorCode MatSOR_MPIBAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx)
2664: {
2665:   Mat_MPIBAIJ    *mat = (Mat_MPIBAIJ*)matin->data;
2667:   Vec            bb1 = 0;

2670:   if (flag == SOR_APPLY_UPPER) {
2671:     (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
2672:     return(0);
2673:   }

2675:   if (its > 1 || ~flag & SOR_ZERO_INITIAL_GUESS) {
2676:     VecDuplicate(bb,&bb1);
2677:   }

2679:   if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) {
2680:     if (flag & SOR_ZERO_INITIAL_GUESS) {
2681:       (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
2682:       its--;
2683:     }

2685:     while (its--) {
2686:       VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
2687:       VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);

2689:       /* update rhs: bb1 = bb - B*x */
2690:       VecScale(mat->lvec,-1.0);
2691:       (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);

2693:       /* local sweep */
2694:       (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,1,xx);
2695:     }
2696:   } else if (flag & SOR_LOCAL_FORWARD_SWEEP) {
2697:     if (flag & SOR_ZERO_INITIAL_GUESS) {
2698:       (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
2699:       its--;
2700:     }
2701:     while (its--) {
2702:       VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
2703:       VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);

2705:       /* update rhs: bb1 = bb - B*x */
2706:       VecScale(mat->lvec,-1.0);
2707:       (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);

2709:       /* local sweep */
2710:       (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_FORWARD_SWEEP,fshift,lits,1,xx);
2711:     }
2712:   } else if (flag & SOR_LOCAL_BACKWARD_SWEEP) {
2713:     if (flag & SOR_ZERO_INITIAL_GUESS) {
2714:       (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
2715:       its--;
2716:     }
2717:     while (its--) {
2718:       VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
2719:       VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);

2721:       /* update rhs: bb1 = bb - B*x */
2722:       VecScale(mat->lvec,-1.0);
2723:       (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);

2725:       /* local sweep */
2726:       (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_BACKWARD_SWEEP,fshift,lits,1,xx);
2727:     }
2728:   } else SETERRQ(PetscObjectComm((PetscObject)matin),PETSC_ERR_SUP,"Parallel version of SOR requested not supported");

2730:   VecDestroy(&bb1);
2731:   return(0);
2732: }

2734: extern PetscErrorCode  MatFDColoringApply_BAIJ(Mat,MatFDColoring,Vec,MatStructure*,void*);

2738: PetscErrorCode  MatInvertBlockDiagonal_MPIBAIJ(Mat A,const PetscScalar **values)
2739: {
2740:   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*) A->data;

2744:   MatInvertBlockDiagonal(a->A,values);
2745:   return(0);
2746: }


2749: /* -------------------------------------------------------------------*/
2750: static struct _MatOps MatOps_Values = {MatSetValues_MPIBAIJ,
2751:                                        MatGetRow_MPIBAIJ,
2752:                                        MatRestoreRow_MPIBAIJ,
2753:                                        MatMult_MPIBAIJ,
2754:                                 /* 4*/ MatMultAdd_MPIBAIJ,
2755:                                        MatMultTranspose_MPIBAIJ,
2756:                                        MatMultTransposeAdd_MPIBAIJ,
2757:                                        0,
2758:                                        0,
2759:                                        0,
2760:                                 /*10*/ 0,
2761:                                        0,
2762:                                        0,
2763:                                        MatSOR_MPIBAIJ,
2764:                                        MatTranspose_MPIBAIJ,
2765:                                 /*15*/ MatGetInfo_MPIBAIJ,
2766:                                        MatEqual_MPIBAIJ,
2767:                                        MatGetDiagonal_MPIBAIJ,
2768:                                        MatDiagonalScale_MPIBAIJ,
2769:                                        MatNorm_MPIBAIJ,
2770:                                 /*20*/ MatAssemblyBegin_MPIBAIJ,
2771:                                        MatAssemblyEnd_MPIBAIJ,
2772:                                        MatSetOption_MPIBAIJ,
2773:                                        MatZeroEntries_MPIBAIJ,
2774:                                 /*24*/ MatZeroRows_MPIBAIJ,
2775:                                        0,
2776:                                        0,
2777:                                        0,
2778:                                        0,
2779:                                 /*29*/ MatSetUp_MPIBAIJ,
2780:                                        0,
2781:                                        0,
2782:                                        0,
2783:                                        0,
2784:                                 /*34*/ MatDuplicate_MPIBAIJ,
2785:                                        0,
2786:                                        0,
2787:                                        0,
2788:                                        0,
2789:                                 /*39*/ MatAXPY_MPIBAIJ,
2790:                                        MatGetSubMatrices_MPIBAIJ,
2791:                                        MatIncreaseOverlap_MPIBAIJ,
2792:                                        MatGetValues_MPIBAIJ,
2793:                                        MatCopy_MPIBAIJ,
2794:                                 /*44*/ 0,
2795:                                        MatScale_MPIBAIJ,
2796:                                        0,
2797:                                        0,
2798:                                        0,
2799:                                 /*49*/ 0,
2800:                                        0,
2801:                                        0,
2802:                                        0,
2803:                                        0,
2804:                                 /*54*/ MatFDColoringCreate_MPIBAIJ,
2805:                                        0,
2806:                                        MatSetUnfactored_MPIBAIJ,
2807:                                        MatPermute_MPIBAIJ,
2808:                                        MatSetValuesBlocked_MPIBAIJ,
2809:                                 /*59*/ MatGetSubMatrix_MPIBAIJ,
2810:                                        MatDestroy_MPIBAIJ,
2811:                                        MatView_MPIBAIJ,
2812:                                        0,
2813:                                        0,
2814:                                 /*64*/ 0,
2815:                                        0,
2816:                                        0,
2817:                                        0,
2818:                                        0,
2819:                                 /*69*/ MatGetRowMaxAbs_MPIBAIJ,
2820:                                        0,
2821:                                        0,
2822:                                        0,
2823:                                        0,
2824:                                 /*74*/ 0,
2825:                                        MatFDColoringApply_BAIJ,
2826:                                        0,
2827:                                        0,
2828:                                        0,
2829:                                 /*79*/ 0,
2830:                                        0,
2831:                                        0,
2832:                                        0,
2833:                                        MatLoad_MPIBAIJ,
2834:                                 /*84*/ 0,
2835:                                        0,
2836:                                        0,
2837:                                        0,
2838:                                        0,
2839:                                 /*89*/ 0,
2840:                                        0,
2841:                                        0,
2842:                                        0,
2843:                                        0,
2844:                                 /*94*/ 0,
2845:                                        0,
2846:                                        0,
2847:                                        0,
2848:                                        0,
2849:                                 /*99*/ 0,
2850:                                        0,
2851:                                        0,
2852:                                        0,
2853:                                        0,
2854:                                 /*104*/0,
2855:                                        MatRealPart_MPIBAIJ,
2856:                                        MatImaginaryPart_MPIBAIJ,
2857:                                        0,
2858:                                        0,
2859:                                 /*109*/0,
2860:                                        0,
2861:                                        0,
2862:                                        0,
2863:                                        0,
2864:                                 /*114*/MatGetSeqNonzeroStructure_MPIBAIJ,
2865:                                        0,
2866:                                        MatGetGhosts_MPIBAIJ,
2867:                                        0,
2868:                                        0,
2869:                                 /*119*/0,
2870:                                        0,
2871:                                        0,
2872:                                        0,
2873:                                        0,
2874:                                 /*124*/0,
2875:                                        0,
2876:                                        MatInvertBlockDiagonal_MPIBAIJ,
2877:                                        0,
2878:                                        0,
2879:                                /*129*/ 0,
2880:                                        0,
2881:                                        0,
2882:                                        0,
2883:                                        0,
2884:                                /*134*/ 0,
2885:                                        0,
2886:                                        0,
2887:                                        0,
2888:                                        0,
2889:                                /*139*/ 0,
2890:                                        0
2891: };

2895: PetscErrorCode  MatGetDiagonalBlock_MPIBAIJ(Mat A,Mat *a)
2896: {
2898:   *a = ((Mat_MPIBAIJ*)A->data)->A;
2899:   return(0);
2900: }

2902: PETSC_EXTERN PetscErrorCode MatConvert_MPIBAIJ_MPISBAIJ(Mat, MatType,MatReuse,Mat*);

2906: PetscErrorCode MatMPIBAIJSetPreallocationCSR_MPIBAIJ(Mat B,PetscInt bs,const PetscInt ii[],const PetscInt jj[],const PetscScalar V[])
2907: {
2908:   PetscInt       m,rstart,cstart,cend;
2909:   PetscInt       i,j,d,nz,nz_max=0,*d_nnz=0,*o_nnz=0;
2910:   const PetscInt *JJ    =0;
2911:   PetscScalar    *values=0;

2915:   PetscLayoutSetBlockSize(B->rmap,bs);
2916:   PetscLayoutSetBlockSize(B->cmap,bs);
2917:   PetscLayoutSetUp(B->rmap);
2918:   PetscLayoutSetUp(B->cmap);
2919:   PetscLayoutGetBlockSize(B->rmap,&bs);
2920:   m      = B->rmap->n/bs;
2921:   rstart = B->rmap->rstart/bs;
2922:   cstart = B->cmap->rstart/bs;
2923:   cend   = B->cmap->rend/bs;

2925:   if (ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"ii[0] must be 0 but it is %D",ii[0]);
2926:   PetscMalloc2(m,PetscInt,&d_nnz,m,PetscInt,&o_nnz);
2927:   for (i=0; i<m; i++) {
2928:     nz = ii[i+1] - ii[i];
2929:     if (nz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative number of columns %D",i,nz);
2930:     nz_max = PetscMax(nz_max,nz);
2931:     JJ     = jj + ii[i];
2932:     for (j=0; j<nz; j++) {
2933:       if (*JJ >= cstart) break;
2934:       JJ++;
2935:     }
2936:     d = 0;
2937:     for (; j<nz; j++) {
2938:       if (*JJ++ >= cend) break;
2939:       d++;
2940:     }
2941:     d_nnz[i] = d;
2942:     o_nnz[i] = nz - d;
2943:   }
2944:   MatMPIBAIJSetPreallocation(B,bs,0,d_nnz,0,o_nnz);
2945:   PetscFree2(d_nnz,o_nnz);

2947:   values = (PetscScalar*)V;
2948:   if (!values) {
2949:     PetscMalloc(bs*bs*nz_max*sizeof(PetscScalar),&values);
2950:     PetscMemzero(values,bs*bs*nz_max*sizeof(PetscScalar));
2951:   }
2952:   for (i=0; i<m; i++) {
2953:     PetscInt          row    = i + rstart;
2954:     PetscInt          ncols  = ii[i+1] - ii[i];
2955:     const PetscInt    *icols = jj + ii[i];
2956:     const PetscScalar *svals = values + (V ? (bs*bs*ii[i]) : 0);
2957:     MatSetValuesBlocked_MPIBAIJ(B,1,&row,ncols,icols,svals,INSERT_VALUES);
2958:   }

2960:   if (!V) { PetscFree(values); }
2961:   MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
2962:   MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);
2963:   MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);
2964:   return(0);
2965: }

2969: /*@C
2970:    MatMPIBAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in BAIJ format
2971:    (the default parallel PETSc format).

2973:    Collective on MPI_Comm

2975:    Input Parameters:
2976: +  A - the matrix
2977: .  bs - the block size
2978: .  i - the indices into j for the start of each local row (starts with zero)
2979: .  j - the column indices for each local row (starts with zero) these must be sorted for each row
2980: -  v - optional values in the matrix

2982:    Level: developer

2984: .keywords: matrix, aij, compressed row, sparse, parallel

2986: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIBAIJSetPreallocation(), MatCreateAIJ(), MPIAIJ
2987: @*/
2988: PetscErrorCode  MatMPIBAIJSetPreallocationCSR(Mat B,PetscInt bs,const PetscInt i[],const PetscInt j[], const PetscScalar v[])
2989: {

2996:   PetscTryMethod(B,"MatMPIBAIJSetPreallocationCSR_C",(Mat,PetscInt,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,bs,i,j,v));
2997:   return(0);
2998: }

3002: PetscErrorCode  MatMPIBAIJSetPreallocation_MPIBAIJ(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt *d_nnz,PetscInt o_nz,const PetscInt *o_nnz)
3003: {
3004:   Mat_MPIBAIJ    *b;
3006:   PetscInt       i;

3009:   PetscLayoutSetBlockSize(B->rmap,bs);
3010:   PetscLayoutSetBlockSize(B->cmap,bs);
3011:   PetscLayoutSetUp(B->rmap);
3012:   PetscLayoutSetUp(B->cmap);
3013:   PetscLayoutGetBlockSize(B->rmap,&bs);

3015:   if (d_nnz) {
3016:     for (i=0; i<B->rmap->n/bs; i++) {
3017:       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]);
3018:     }
3019:   }
3020:   if (o_nnz) {
3021:     for (i=0; i<B->rmap->n/bs; i++) {
3022:       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]);
3023:     }
3024:   }

3026:   b      = (Mat_MPIBAIJ*)B->data;
3027:   b->bs2 = bs*bs;
3028:   b->mbs = B->rmap->n/bs;
3029:   b->nbs = B->cmap->n/bs;
3030:   b->Mbs = B->rmap->N/bs;
3031:   b->Nbs = B->cmap->N/bs;

3033:   for (i=0; i<=b->size; i++) {
3034:     b->rangebs[i] = B->rmap->range[i]/bs;
3035:   }
3036:   b->rstartbs = B->rmap->rstart/bs;
3037:   b->rendbs   = B->rmap->rend/bs;
3038:   b->cstartbs = B->cmap->rstart/bs;
3039:   b->cendbs   = B->cmap->rend/bs;

3041:   if (!B->preallocated) {
3042:     MatCreate(PETSC_COMM_SELF,&b->A);
3043:     MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);
3044:     MatSetType(b->A,MATSEQBAIJ);
3045:     PetscLogObjectParent(B,b->A);
3046:     MatCreate(PETSC_COMM_SELF,&b->B);
3047:     MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);
3048:     MatSetType(b->B,MATSEQBAIJ);
3049:     PetscLogObjectParent(B,b->B);
3050:     MatStashCreate_Private(PetscObjectComm((PetscObject)B),bs,&B->bstash);
3051:   }

3053:   MatSeqBAIJSetPreallocation(b->A,bs,d_nz,d_nnz);
3054:   MatSeqBAIJSetPreallocation(b->B,bs,o_nz,o_nnz);
3055:   B->preallocated = PETSC_TRUE;
3056:   return(0);
3057: }

3059: extern PetscErrorCode  MatDiagonalScaleLocal_MPIBAIJ(Mat,Vec);
3060: extern PetscErrorCode  MatSetHashTableFactor_MPIBAIJ(Mat,PetscReal);

3064: PETSC_EXTERN PetscErrorCode MatConvert_MPIBAIJ_MPIAdj(Mat B, MatType newtype,MatReuse reuse,Mat *adj)
3065: {
3066:   Mat_MPIBAIJ    *b = (Mat_MPIBAIJ*)B->data;
3068:   Mat_SeqBAIJ    *d  = (Mat_SeqBAIJ*) b->A->data,*o = (Mat_SeqBAIJ*) b->B->data;
3069:   PetscInt       M   = B->rmap->n/B->rmap->bs,i,*ii,*jj,cnt,j,k,rstart = B->rmap->rstart/B->rmap->bs;
3070:   const PetscInt *id = d->i, *jd = d->j, *io = o->i, *jo = o->j, *garray = b->garray;

3073:   PetscMalloc((M+1)*sizeof(PetscInt),&ii);
3074:   ii[0] = 0;
3075:   for (i=0; i<M; i++) {
3076:     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]);
3077:     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]);
3078:     ii[i+1] = ii[i] + id[i+1] - id[i] + io[i+1] - io[i];
3079:     /* remove one from count of matrix has diagonal */
3080:     for (j=id[i]; j<id[i+1]; j++) {
3081:       if (jd[j] == i) {ii[i+1]--;break;}
3082:     }
3083:   }
3084:   PetscMalloc(ii[M]*sizeof(PetscInt),&jj);
3085:   cnt  = 0;
3086:   for (i=0; i<M; i++) {
3087:     for (j=io[i]; j<io[i+1]; j++) {
3088:       if (garray[jo[j]] > rstart) break;
3089:       jj[cnt++] = garray[jo[j]];
3090:     }
3091:     for (k=id[i]; k<id[i+1]; k++) {
3092:       if (jd[k] != i) {
3093:         jj[cnt++] = rstart + jd[k];
3094:       }
3095:     }
3096:     for (; j<io[i+1]; j++) {
3097:       jj[cnt++] = garray[jo[j]];
3098:     }
3099:   }
3100:   MatCreateMPIAdj(PetscObjectComm((PetscObject)B),M,B->cmap->N/B->rmap->bs,ii,jj,NULL,adj);
3101:   return(0);
3102: }

3104: #include <../src/mat/impls/aij/mpi/mpiaij.h>

3106: PETSC_EXTERN PetscErrorCode MatConvert_SeqBAIJ_SeqAIJ(Mat,MatType,MatReuse,Mat*);

3110: PETSC_EXTERN PetscErrorCode MatConvert_MPIBAIJ_MPIAIJ(Mat A,MatType newtype,MatReuse reuse,Mat *newmat)
3111: {
3113:   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;
3114:   Mat            B;
3115:   Mat_MPIAIJ     *b;

3118:   if (!A->assembled) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Matrix must be assembled");

3120:   MatCreate(PetscObjectComm((PetscObject)A),&B);
3121:   MatSetSizes(B,A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N);
3122:   MatSetType(B,MATMPIAIJ);
3123:   MatSeqAIJSetPreallocation(B,0,NULL);
3124:   MatMPIAIJSetPreallocation(B,0,NULL,0,NULL);
3125:   b    = (Mat_MPIAIJ*) B->data;

3127:   MatDestroy(&b->A);
3128:   MatDestroy(&b->B);
3129:   MatDisAssemble_MPIBAIJ(A);
3130:   MatConvert_SeqBAIJ_SeqAIJ(a->A, MATSEQAIJ, MAT_INITIAL_MATRIX, &b->A);
3131:   MatConvert_SeqBAIJ_SeqAIJ(a->B, MATSEQAIJ, MAT_INITIAL_MATRIX, &b->B);
3132:   MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
3133:   MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);
3134:   MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);
3135:   MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);
3136:   if (reuse == MAT_REUSE_MATRIX) {
3137:     MatHeaderReplace(A,B);
3138:   } else {
3139:    *newmat = B;
3140:   }
3141:   return(0);
3142: }

3144: #if defined(PETSC_HAVE_MUMPS)
3145: PETSC_EXTERN PetscErrorCode MatGetFactor_baij_mumps(Mat,MatFactorType,Mat*);
3146: #endif

3148: /*MC
3149:    MATMPIBAIJ - MATMPIBAIJ = "mpibaij" - A matrix type to be used for distributed block sparse matrices.

3151:    Options Database Keys:
3152: + -mat_type mpibaij - sets the matrix type to "mpibaij" during a call to MatSetFromOptions()
3153: . -mat_block_size <bs> - set the blocksize used to store the matrix
3154: - -mat_use_hash_table <fact>

3156:   Level: beginner

3158: .seealso: MatCreateMPIBAIJ
3159: M*/

3161: PETSC_EXTERN PetscErrorCode MatConvert_MPIBAIJ_MPIBSTRM(Mat,MatType,MatReuse,Mat*);

3165: PETSC_EXTERN PetscErrorCode MatCreate_MPIBAIJ(Mat B)
3166: {
3167:   Mat_MPIBAIJ    *b;
3169:   PetscBool      flg;

3172:   PetscNewLog(B,Mat_MPIBAIJ,&b);
3173:   B->data = (void*)b;

3175:   PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));
3176:   B->assembled = PETSC_FALSE;

3178:   B->insertmode = NOT_SET_VALUES;
3179:   MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);
3180:   MPI_Comm_size(PetscObjectComm((PetscObject)B),&b->size);

3182:   /* build local table of row and column ownerships */
3183:   PetscMalloc((b->size+1)*sizeof(PetscInt),&b->rangebs);

3185:   /* build cache for off array entries formed */
3186:   MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);

3188:   b->donotstash  = PETSC_FALSE;
3189:   b->colmap      = NULL;
3190:   b->garray      = NULL;
3191:   b->roworiented = PETSC_TRUE;

3193:   /* stuff used in block assembly */
3194:   b->barray = 0;

3196:   /* stuff used for matrix vector multiply */
3197:   b->lvec  = 0;
3198:   b->Mvctx = 0;

3200:   /* stuff for MatGetRow() */
3201:   b->rowindices   = 0;
3202:   b->rowvalues    = 0;
3203:   b->getrowactive = PETSC_FALSE;

3205:   /* hash table stuff */
3206:   b->ht           = 0;
3207:   b->hd           = 0;
3208:   b->ht_size      = 0;
3209:   b->ht_flag      = PETSC_FALSE;
3210:   b->ht_fact      = 0;
3211:   b->ht_total_ct  = 0;
3212:   b->ht_insert_ct = 0;

3214:   /* stuff for MatGetSubMatrices_MPIBAIJ_local() */
3215:   b->ijonly = PETSC_FALSE;

3217:   PetscOptionsBegin(PetscObjectComm((PetscObject)B),NULL,"Options for loading MPIBAIJ matrix 1","Mat");
3218:   PetscOptionsBool("-mat_use_hash_table","Use hash table to save memory in constructing matrix","MatSetOption",PETSC_FALSE,&flg,NULL);
3219:   if (flg) {
3220:     PetscReal fact = 1.39;
3221:     MatSetOption(B,MAT_USE_HASH_TABLE,PETSC_TRUE);
3222:     PetscOptionsReal("-mat_use_hash_table","Use hash table factor","MatMPIBAIJSetHashTableFactor",fact,&fact,NULL);
3223:     if (fact <= 1.0) fact = 1.39;
3224:     MatMPIBAIJSetHashTableFactor(B,fact);
3225:     PetscInfo1(B,"Hash table Factor used %5.2f\n",fact);
3226:   }
3227:   PetscOptionsEnd();

3229: #if defined(PETSC_HAVE_MUMPS)
3230:   PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_mumps_C",MatGetFactor_baij_mumps);
3231: #endif
3232:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpibaij_mpiadj_C",MatConvert_MPIBAIJ_MPIAdj);
3233:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpibaij_mpiaij_C",MatConvert_MPIBAIJ_MPIAIJ);
3234:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpibaij_mpisbaij_C",MatConvert_MPIBAIJ_MPISBAIJ);
3235:   PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPIBAIJ);
3236:   PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPIBAIJ);
3237:   PetscObjectComposeFunction((PetscObject)B,"MatGetDiagonalBlock_C",MatGetDiagonalBlock_MPIBAIJ);
3238:   PetscObjectComposeFunction((PetscObject)B,"MatMPIBAIJSetPreallocation_C",MatMPIBAIJSetPreallocation_MPIBAIJ);
3239:   PetscObjectComposeFunction((PetscObject)B,"MatMPIBAIJSetPreallocationCSR_C",MatMPIBAIJSetPreallocationCSR_MPIBAIJ);
3240:   PetscObjectComposeFunction((PetscObject)B,"MatDiagonalScaleLocal_C",MatDiagonalScaleLocal_MPIBAIJ);
3241:   PetscObjectComposeFunction((PetscObject)B,"MatSetHashTableFactor_C",MatSetHashTableFactor_MPIBAIJ);
3242:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpibaij_mpibstrm_C",MatConvert_MPIBAIJ_MPIBSTRM);
3243:   PetscObjectChangeTypeName((PetscObject)B,MATMPIBAIJ);
3244:   return(0);
3245: }

3247: /*MC
3248:    MATBAIJ - MATBAIJ = "baij" - A matrix type to be used for block sparse matrices.

3250:    This matrix type is identical to MATSEQBAIJ when constructed with a single process communicator,
3251:    and MATMPIBAIJ otherwise.

3253:    Options Database Keys:
3254: . -mat_type baij - sets the matrix type to "baij" during a call to MatSetFromOptions()

3256:   Level: beginner

3258: .seealso: MatCreateBAIJ(),MATSEQBAIJ,MATMPIBAIJ, MatMPIBAIJSetPreallocation(), MatMPIBAIJSetPreallocationCSR()
3259: M*/

3263: /*@C
3264:    MatMPIBAIJSetPreallocation - Allocates memory for a sparse parallel matrix in block AIJ format
3265:    (block compressed row).  For good matrix assembly performance
3266:    the user should preallocate the matrix storage by setting the parameters
3267:    d_nz (or d_nnz) and o_nz (or o_nnz).  By setting these parameters accurately,
3268:    performance can be increased by more than a factor of 50.

3270:    Collective on Mat

3272:    Input Parameters:
3273: +  A - the matrix
3274: .  bs   - size of blockk
3275: .  d_nz  - number of block nonzeros per block row in diagonal portion of local
3276:            submatrix  (same for all local rows)
3277: .  d_nnz - array containing the number of block nonzeros in the various block rows
3278:            of the in diagonal portion of the local (possibly different for each block
3279:            row) or NULL.  If you plan to factor the matrix you must leave room for the diagonal entry and
3280:            set it even if it is zero.
3281: .  o_nz  - number of block nonzeros per block row in the off-diagonal portion of local
3282:            submatrix (same for all local rows).
3283: -  o_nnz - array containing the number of nonzeros in the various block rows of the
3284:            off-diagonal portion of the local submatrix (possibly different for
3285:            each block row) or NULL.

3287:    If the *_nnz parameter is given then the *_nz parameter is ignored

3289:    Options Database Keys:
3290: +   -mat_block_size - size of the blocks to use
3291: -   -mat_use_hash_table <fact>

3293:    Notes:
3294:    If PETSC_DECIDE or  PETSC_DETERMINE is used for a particular argument on one processor
3295:    than it must be used on all processors that share the object for that argument.

3297:    Storage Information:
3298:    For a square global matrix we define each processor's diagonal portion
3299:    to be its local rows and the corresponding columns (a square submatrix);
3300:    each processor's off-diagonal portion encompasses the remainder of the
3301:    local matrix (a rectangular submatrix).

3303:    The user can specify preallocated storage for the diagonal part of
3304:    the local submatrix with either d_nz or d_nnz (not both).  Set
3305:    d_nz=PETSC_DEFAULT and d_nnz=NULL for PETSc to control dynamic
3306:    memory allocation.  Likewise, specify preallocated storage for the
3307:    off-diagonal part of the local submatrix with o_nz or o_nnz (not both).

3309:    Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In
3310:    the figure below we depict these three local rows and all columns (0-11).

3312: .vb
3313:            0 1 2 3 4 5 6 7 8 9 10 11
3314:           --------------------------
3315:    row 3  |o o o d d d o o o o  o  o
3316:    row 4  |o o o d d d o o o o  o  o
3317:    row 5  |o o o d d d o o o o  o  o
3318:           --------------------------
3319: .ve

3321:    Thus, any entries in the d locations are stored in the d (diagonal)
3322:    submatrix, and any entries in the o locations are stored in the
3323:    o (off-diagonal) submatrix.  Note that the d and the o submatrices are
3324:    stored simply in the MATSEQBAIJ format for compressed row storage.

3326:    Now d_nz should indicate the number of block nonzeros per row in the d matrix,
3327:    and o_nz should indicate the number of block nonzeros per row in the o matrix.
3328:    In general, for PDE problems in which most nonzeros are near the diagonal,
3329:    one expects d_nz >> o_nz.   For large problems you MUST preallocate memory
3330:    or you will get TERRIBLE performance; see the users' manual chapter on
3331:    matrices.

3333:    You can call MatGetInfo() to get information on how effective the preallocation was;
3334:    for example the fields mallocs,nz_allocated,nz_used,nz_unneeded;
3335:    You can also run with the option -info and look for messages with the string
3336:    malloc in them to see if additional memory allocation was needed.

3338:    Level: intermediate

3340: .keywords: matrix, block, aij, compressed row, sparse, parallel

3342: .seealso: MatCreate(), MatCreateSeqBAIJ(), MatSetValues(), MatCreateBAIJ(), MatMPIBAIJSetPreallocationCSR(), PetscSplitOwnership()
3343: @*/
3344: PetscErrorCode  MatMPIBAIJSetPreallocation(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[])
3345: {

3352:   PetscTryMethod(B,"MatMPIBAIJSetPreallocation_C",(Mat,PetscInt,PetscInt,const PetscInt[],PetscInt,const PetscInt[]),(B,bs,d_nz,d_nnz,o_nz,o_nnz));
3353:   return(0);
3354: }

3358: /*@C
3359:    MatCreateBAIJ - Creates a sparse parallel matrix in block AIJ format
3360:    (block compressed row).  For good matrix assembly performance
3361:    the user should preallocate the matrix storage by setting the parameters
3362:    d_nz (or d_nnz) and o_nz (or o_nnz).  By setting these parameters accurately,
3363:    performance can be increased by more than a factor of 50.

3365:    Collective on MPI_Comm

3367:    Input Parameters:
3368: +  comm - MPI communicator
3369: .  bs   - size of blockk
3370: .  m - number of local rows (or PETSC_DECIDE to have calculated if M is given)
3371:            This value should be the same as the local size used in creating the
3372:            y vector for the matrix-vector product y = Ax.
3373: .  n - number of local columns (or PETSC_DECIDE to have calculated if N is given)
3374:            This value should be the same as the local size used in creating the
3375:            x vector for the matrix-vector product y = Ax.
3376: .  M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
3377: .  N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
3378: .  d_nz  - number of nonzero blocks per block row in diagonal portion of local
3379:            submatrix  (same for all local rows)
3380: .  d_nnz - array containing the number of nonzero blocks in the various block rows
3381:            of the in diagonal portion of the local (possibly different for each block
3382:            row) or NULL.  If you plan to factor the matrix you must leave room for the diagonal entry
3383:            and set it even if it is zero.
3384: .  o_nz  - number of nonzero blocks per block row in the off-diagonal portion of local
3385:            submatrix (same for all local rows).
3386: -  o_nnz - array containing the number of nonzero blocks in the various block rows of the
3387:            off-diagonal portion of the local submatrix (possibly different for
3388:            each block row) or NULL.

3390:    Output Parameter:
3391: .  A - the matrix

3393:    Options Database Keys:
3394: +   -mat_block_size - size of the blocks to use
3395: -   -mat_use_hash_table <fact>

3397:    It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(),
3398:    MatXXXXSetPreallocation() paradgm instead of this routine directly.
3399:    [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation]

3401:    Notes:
3402:    If the *_nnz parameter is given then the *_nz parameter is ignored

3404:    A nonzero block is any block that as 1 or more nonzeros in it

3406:    The user MUST specify either the local or global matrix dimensions
3407:    (possibly both).

3409:    If PETSC_DECIDE or  PETSC_DETERMINE is used for a particular argument on one processor
3410:    than it must be used on all processors that share the object for that argument.

3412:    Storage Information:
3413:    For a square global matrix we define each processor's diagonal portion
3414:    to be its local rows and the corresponding columns (a square submatrix);
3415:    each processor's off-diagonal portion encompasses the remainder of the
3416:    local matrix (a rectangular submatrix).

3418:    The user can specify preallocated storage for the diagonal part of
3419:    the local submatrix with either d_nz or d_nnz (not both).  Set
3420:    d_nz=PETSC_DEFAULT and d_nnz=NULL for PETSc to control dynamic
3421:    memory allocation.  Likewise, specify preallocated storage for the
3422:    off-diagonal part of the local submatrix with o_nz or o_nnz (not both).

3424:    Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In
3425:    the figure below we depict these three local rows and all columns (0-11).

3427: .vb
3428:            0 1 2 3 4 5 6 7 8 9 10 11
3429:           --------------------------
3430:    row 3  |o o o d d d o o o o  o  o
3431:    row 4  |o o o d d d o o o o  o  o
3432:    row 5  |o o o d d d o o o o  o  o
3433:           --------------------------
3434: .ve

3436:    Thus, any entries in the d locations are stored in the d (diagonal)
3437:    submatrix, and any entries in the o locations are stored in the
3438:    o (off-diagonal) submatrix.  Note that the d and the o submatrices are
3439:    stored simply in the MATSEQBAIJ format for compressed row storage.

3441:    Now d_nz should indicate the number of block nonzeros per row in the d matrix,
3442:    and o_nz should indicate the number of block nonzeros per row in the o matrix.
3443:    In general, for PDE problems in which most nonzeros are near the diagonal,
3444:    one expects d_nz >> o_nz.   For large problems you MUST preallocate memory
3445:    or you will get TERRIBLE performance; see the users' manual chapter on
3446:    matrices.

3448:    Level: intermediate

3450: .keywords: matrix, block, aij, compressed row, sparse, parallel

3452: .seealso: MatCreate(), MatCreateSeqBAIJ(), MatSetValues(), MatCreateBAIJ(), MatMPIBAIJSetPreallocation(), MatMPIBAIJSetPreallocationCSR()
3453: @*/
3454: 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)
3455: {
3457:   PetscMPIInt    size;

3460:   MatCreate(comm,A);
3461:   MatSetSizes(*A,m,n,M,N);
3462:   MPI_Comm_size(comm,&size);
3463:   if (size > 1) {
3464:     MatSetType(*A,MATMPIBAIJ);
3465:     MatMPIBAIJSetPreallocation(*A,bs,d_nz,d_nnz,o_nz,o_nnz);
3466:   } else {
3467:     MatSetType(*A,MATSEQBAIJ);
3468:     MatSeqBAIJSetPreallocation(*A,bs,d_nz,d_nnz);
3469:   }
3470:   return(0);
3471: }

3475: static PetscErrorCode MatDuplicate_MPIBAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat)
3476: {
3477:   Mat            mat;
3478:   Mat_MPIBAIJ    *a,*oldmat = (Mat_MPIBAIJ*)matin->data;
3480:   PetscInt       len=0;

3483:   *newmat = 0;
3484:   MatCreate(PetscObjectComm((PetscObject)matin),&mat);
3485:   MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);
3486:   MatSetType(mat,((PetscObject)matin)->type_name);
3487:   PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));

3489:   mat->factortype   = matin->factortype;
3490:   mat->preallocated = PETSC_TRUE;
3491:   mat->assembled    = PETSC_TRUE;
3492:   mat->insertmode   = NOT_SET_VALUES;

3494:   a             = (Mat_MPIBAIJ*)mat->data;
3495:   mat->rmap->bs = matin->rmap->bs;
3496:   a->bs2        = oldmat->bs2;
3497:   a->mbs        = oldmat->mbs;
3498:   a->nbs        = oldmat->nbs;
3499:   a->Mbs        = oldmat->Mbs;
3500:   a->Nbs        = oldmat->Nbs;

3502:   PetscLayoutReference(matin->rmap,&mat->rmap);
3503:   PetscLayoutReference(matin->cmap,&mat->cmap);

3505:   a->size         = oldmat->size;
3506:   a->rank         = oldmat->rank;
3507:   a->donotstash   = oldmat->donotstash;
3508:   a->roworiented  = oldmat->roworiented;
3509:   a->rowindices   = 0;
3510:   a->rowvalues    = 0;
3511:   a->getrowactive = PETSC_FALSE;
3512:   a->barray       = 0;
3513:   a->rstartbs     = oldmat->rstartbs;
3514:   a->rendbs       = oldmat->rendbs;
3515:   a->cstartbs     = oldmat->cstartbs;
3516:   a->cendbs       = oldmat->cendbs;

3518:   /* hash table stuff */
3519:   a->ht           = 0;
3520:   a->hd           = 0;
3521:   a->ht_size      = 0;
3522:   a->ht_flag      = oldmat->ht_flag;
3523:   a->ht_fact      = oldmat->ht_fact;
3524:   a->ht_total_ct  = 0;
3525:   a->ht_insert_ct = 0;

3527:   PetscMemcpy(a->rangebs,oldmat->rangebs,(a->size+1)*sizeof(PetscInt));
3528:   if (oldmat->colmap) {
3529: #if defined(PETSC_USE_CTABLE)
3530:     PetscTableCreateCopy(oldmat->colmap,&a->colmap);
3531: #else
3532:     PetscMalloc((a->Nbs)*sizeof(PetscInt),&a->colmap);
3533:     PetscLogObjectMemory(mat,(a->Nbs)*sizeof(PetscInt));
3534:     PetscMemcpy(a->colmap,oldmat->colmap,(a->Nbs)*sizeof(PetscInt));
3535: #endif
3536:   } else a->colmap = 0;

3538:   if (oldmat->garray && (len = ((Mat_SeqBAIJ*)(oldmat->B->data))->nbs)) {
3539:     PetscMalloc(len*sizeof(PetscInt),&a->garray);
3540:     PetscLogObjectMemory(mat,len*sizeof(PetscInt));
3541:     PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));
3542:   } else a->garray = 0;

3544:   MatStashCreate_Private(PetscObjectComm((PetscObject)matin),matin->rmap->bs,&mat->bstash);
3545:   VecDuplicate(oldmat->lvec,&a->lvec);
3546:   PetscLogObjectParent(mat,a->lvec);
3547:   VecScatterCopy(oldmat->Mvctx,&a->Mvctx);
3548:   PetscLogObjectParent(mat,a->Mvctx);

3550:   MatDuplicate(oldmat->A,cpvalues,&a->A);
3551:   PetscLogObjectParent(mat,a->A);
3552:   MatDuplicate(oldmat->B,cpvalues,&a->B);
3553:   PetscLogObjectParent(mat,a->B);
3554:   PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);
3555:   *newmat = mat;
3556:   return(0);
3557: }

3561: PetscErrorCode MatLoad_MPIBAIJ(Mat newmat,PetscViewer viewer)
3562: {
3564:   int            fd;
3565:   PetscInt       i,nz,j,rstart,rend;
3566:   PetscScalar    *vals,*buf;
3567:   MPI_Comm       comm;
3568:   MPI_Status     status;
3569:   PetscMPIInt    rank,size,maxnz;
3570:   PetscInt       header[4],*rowlengths = 0,M,N,m,*rowners,*cols;
3571:   PetscInt       *locrowlens = NULL,*procsnz = NULL,*browners = NULL;
3572:   PetscInt       jj,*mycols,*ibuf,bs=1,Mbs,mbs,extra_rows,mmax;
3573:   PetscMPIInt    tag    = ((PetscObject)viewer)->tag;
3574:   PetscInt       *dlens = NULL,*odlens = NULL,*mask = NULL,*masked1 = NULL,*masked2 = NULL,rowcount,odcount;
3575:   PetscInt       dcount,kmax,k,nzcount,tmp,mend,sizesset=1,grows,gcols;

3578:   PetscObjectGetComm((PetscObject)viewer,&comm);
3579:   PetscOptionsBegin(comm,NULL,"Options for loading MPIBAIJ matrix 2","Mat");
3580:   PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);
3581:   PetscOptionsEnd();

3583:   MPI_Comm_size(comm,&size);
3584:   MPI_Comm_rank(comm,&rank);
3585:   if (!rank) {
3586:     PetscViewerBinaryGetDescriptor(viewer,&fd);
3587:     PetscBinaryRead(fd,(char*)header,4,PETSC_INT);
3588:     if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object");
3589:   }

3591:   if (newmat->rmap->n < 0 && newmat->rmap->N < 0 && newmat->cmap->n < 0 && newmat->cmap->N < 0) sizesset = 0;

3593:   MPI_Bcast(header+1,3,MPIU_INT,0,comm);
3594:   M    = header[1]; N = header[2];

3596:   /* If global rows/cols are set to PETSC_DECIDE, set it to the sizes given in the file */
3597:   if (sizesset && newmat->rmap->N < 0) newmat->rmap->N = M;
3598:   if (sizesset && newmat->cmap->N < 0) newmat->cmap->N = N;

3600:   /* If global sizes are set, check if they are consistent with that given in the file */
3601:   if (sizesset) {
3602:     MatGetSize(newmat,&grows,&gcols);
3603:   }
3604:   if (sizesset && newmat->rmap->N != grows) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED, "Inconsistent # of rows:Matrix in file has (%d) and input matrix has (%d)",M,grows);
3605:   if (sizesset && newmat->cmap->N != gcols) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED, "Inconsistent # of cols:Matrix in file has (%d) and input matrix has (%d)",N,gcols);

3607:   if (M != N) SETERRQ(PetscObjectComm((PetscObject)viewer),PETSC_ERR_SUP,"Can only do square matrices");

3609:   /*
3610:      This code adds extra rows to make sure the number of rows is
3611:      divisible by the blocksize
3612:   */
3613:   Mbs        = M/bs;
3614:   extra_rows = bs - M + bs*Mbs;
3615:   if (extra_rows == bs) extra_rows = 0;
3616:   else                  Mbs++;
3617:   if (extra_rows && !rank) {
3618:     PetscInfo(viewer,"Padding loaded matrix to match blocksize\n");
3619:   }

3621:   /* determine ownership of all rows */
3622:   if (newmat->rmap->n < 0) { /* PETSC_DECIDE */
3623:     mbs = Mbs/size + ((Mbs % size) > rank);
3624:     m   = mbs*bs;
3625:   } else { /* User set */
3626:     m   = newmat->rmap->n;
3627:     mbs = m/bs;
3628:   }
3629:   PetscMalloc2(size+1,PetscInt,&rowners,size+1,PetscInt,&browners);
3630:   MPI_Allgather(&mbs,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);

3632:   /* process 0 needs enough room for process with most rows */
3633:   if (!rank) {
3634:     mmax = rowners[1];
3635:     for (i=2; i<=size; i++) {
3636:       mmax = PetscMax(mmax,rowners[i]);
3637:     }
3638:     mmax*=bs;
3639:   } else mmax = -1;             /* unused, but compiler warns anyway */

3641:   rowners[0] = 0;
3642:   for (i=2; i<=size; i++) rowners[i] += rowners[i-1];
3643:   for (i=0; i<=size; i++) browners[i] = rowners[i]*bs;
3644:   rstart = rowners[rank];
3645:   rend   = rowners[rank+1];

3647:   /* distribute row lengths to all processors */
3648:   PetscMalloc(m*sizeof(PetscInt),&locrowlens);
3649:   if (!rank) {
3650:     mend = m;
3651:     if (size == 1) mend = mend - extra_rows;
3652:     PetscBinaryRead(fd,locrowlens,mend,PETSC_INT);
3653:     for (j=mend; j<m; j++) locrowlens[j] = 1;
3654:     PetscMalloc(mmax*sizeof(PetscInt),&rowlengths);
3655:     PetscMalloc(size*sizeof(PetscInt),&procsnz);
3656:     PetscMemzero(procsnz,size*sizeof(PetscInt));
3657:     for (j=0; j<m; j++) {
3658:       procsnz[0] += locrowlens[j];
3659:     }
3660:     for (i=1; i<size; i++) {
3661:       mend = browners[i+1] - browners[i];
3662:       if (i == size-1) mend = mend - extra_rows;
3663:       PetscBinaryRead(fd,rowlengths,mend,PETSC_INT);
3664:       for (j=mend; j<browners[i+1] - browners[i]; j++) rowlengths[j] = 1;
3665:       /* calculate the number of nonzeros on each processor */
3666:       for (j=0; j<browners[i+1]-browners[i]; j++) {
3667:         procsnz[i] += rowlengths[j];
3668:       }
3669:       MPI_Send(rowlengths,browners[i+1]-browners[i],MPIU_INT,i,tag,comm);
3670:     }
3671:     PetscFree(rowlengths);
3672:   } else {
3673:     MPI_Recv(locrowlens,m,MPIU_INT,0,tag,comm,&status);
3674:   }

3676:   if (!rank) {
3677:     /* determine max buffer needed and allocate it */
3678:     maxnz = procsnz[0];
3679:     for (i=1; i<size; i++) {
3680:       maxnz = PetscMax(maxnz,procsnz[i]);
3681:     }
3682:     PetscMalloc(maxnz*sizeof(PetscInt),&cols);

3684:     /* read in my part of the matrix column indices  */
3685:     nz     = procsnz[0];
3686:     PetscMalloc((nz+1)*sizeof(PetscInt),&ibuf);
3687:     mycols = ibuf;
3688:     if (size == 1) nz -= extra_rows;
3689:     PetscBinaryRead(fd,mycols,nz,PETSC_INT);
3690:     if (size == 1) {
3691:       for (i=0; i< extra_rows; i++) mycols[nz+i] = M+i;
3692:     }

3694:     /* read in every ones (except the last) and ship off */
3695:     for (i=1; i<size-1; i++) {
3696:       nz   = procsnz[i];
3697:       PetscBinaryRead(fd,cols,nz,PETSC_INT);
3698:       MPI_Send(cols,nz,MPIU_INT,i,tag,comm);
3699:     }
3700:     /* read in the stuff for the last proc */
3701:     if (size != 1) {
3702:       nz   = procsnz[size-1] - extra_rows;  /* the extra rows are not on the disk */
3703:       PetscBinaryRead(fd,cols,nz,PETSC_INT);
3704:       for (i=0; i<extra_rows; i++) cols[nz+i] = M+i;
3705:       MPI_Send(cols,nz+extra_rows,MPIU_INT,size-1,tag,comm);
3706:     }
3707:     PetscFree(cols);
3708:   } else {
3709:     /* determine buffer space needed for message */
3710:     nz = 0;
3711:     for (i=0; i<m; i++) {
3712:       nz += locrowlens[i];
3713:     }
3714:     PetscMalloc((nz+1)*sizeof(PetscInt),&ibuf);
3715:     mycols = ibuf;
3716:     /* receive message of column indices*/
3717:     MPI_Recv(mycols,nz,MPIU_INT,0,tag,comm,&status);
3718:     MPI_Get_count(&status,MPIU_INT,&maxnz);
3719:     if (maxnz != nz) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file");
3720:   }

3722:   /* loop over local rows, determining number of off diagonal entries */
3723:   PetscMalloc2(rend-rstart,PetscInt,&dlens,rend-rstart,PetscInt,&odlens);
3724:   PetscMalloc3(Mbs,PetscInt,&mask,Mbs,PetscInt,&masked1,Mbs,PetscInt,&masked2);
3725:   PetscMemzero(mask,Mbs*sizeof(PetscInt));
3726:   PetscMemzero(masked1,Mbs*sizeof(PetscInt));
3727:   PetscMemzero(masked2,Mbs*sizeof(PetscInt));
3728:   rowcount = 0; nzcount = 0;
3729:   for (i=0; i<mbs; i++) {
3730:     dcount  = 0;
3731:     odcount = 0;
3732:     for (j=0; j<bs; j++) {
3733:       kmax = locrowlens[rowcount];
3734:       for (k=0; k<kmax; k++) {
3735:         tmp = mycols[nzcount++]/bs;
3736:         if (!mask[tmp]) {
3737:           mask[tmp] = 1;
3738:           if (tmp < rstart || tmp >= rend) masked2[odcount++] = tmp;
3739:           else masked1[dcount++] = tmp;
3740:         }
3741:       }
3742:       rowcount++;
3743:     }

3745:     dlens[i]  = dcount;
3746:     odlens[i] = odcount;

3748:     /* zero out the mask elements we set */
3749:     for (j=0; j<dcount; j++) mask[masked1[j]] = 0;
3750:     for (j=0; j<odcount; j++) mask[masked2[j]] = 0;
3751:   }


3754:   if (!sizesset) {
3755:     MatSetSizes(newmat,m,m,M+extra_rows,N+extra_rows);
3756:   }
3757:   MatMPIBAIJSetPreallocation(newmat,bs,0,dlens,0,odlens);

3759:   if (!rank) {
3760:     PetscMalloc((maxnz+1)*sizeof(PetscScalar),&buf);
3761:     /* read in my part of the matrix numerical values  */
3762:     nz     = procsnz[0];
3763:     vals   = buf;
3764:     mycols = ibuf;
3765:     if (size == 1) nz -= extra_rows;
3766:     PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);
3767:     if (size == 1) {
3768:       for (i=0; i< extra_rows; i++) vals[nz+i] = 1.0;
3769:     }

3771:     /* insert into matrix */
3772:     jj = rstart*bs;
3773:     for (i=0; i<m; i++) {
3774:       MatSetValues_MPIBAIJ(newmat,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);
3775:       mycols += locrowlens[i];
3776:       vals   += locrowlens[i];
3777:       jj++;
3778:     }
3779:     /* read in other processors (except the last one) and ship out */
3780:     for (i=1; i<size-1; i++) {
3781:       nz   = procsnz[i];
3782:       vals = buf;
3783:       PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);
3784:       MPIULong_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newmat)->tag,comm);
3785:     }
3786:     /* the last proc */
3787:     if (size != 1) {
3788:       nz   = procsnz[i] - extra_rows;
3789:       vals = buf;
3790:       PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);
3791:       for (i=0; i<extra_rows; i++) vals[nz+i] = 1.0;
3792:       MPIULong_Send(vals,nz+extra_rows,MPIU_SCALAR,size-1,((PetscObject)newmat)->tag,comm);
3793:     }
3794:     PetscFree(procsnz);
3795:   } else {
3796:     /* receive numeric values */
3797:     PetscMalloc((nz+1)*sizeof(PetscScalar),&buf);

3799:     /* receive message of values*/
3800:     vals   = buf;
3801:     mycols = ibuf;
3802:     MPIULong_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newmat)->tag,comm);

3804:     /* insert into matrix */
3805:     jj = rstart*bs;
3806:     for (i=0; i<m; i++) {
3807:       MatSetValues_MPIBAIJ(newmat,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);
3808:       mycols += locrowlens[i];
3809:       vals   += locrowlens[i];
3810:       jj++;
3811:     }
3812:   }
3813:   PetscFree(locrowlens);
3814:   PetscFree(buf);
3815:   PetscFree(ibuf);
3816:   PetscFree2(rowners,browners);
3817:   PetscFree2(dlens,odlens);
3818:   PetscFree3(mask,masked1,masked2);
3819:   MatAssemblyBegin(newmat,MAT_FINAL_ASSEMBLY);
3820:   MatAssemblyEnd(newmat,MAT_FINAL_ASSEMBLY);
3821:   return(0);
3822: }

3826: /*@
3827:    MatMPIBAIJSetHashTableFactor - Sets the factor required to compute the size of the HashTable.

3829:    Input Parameters:
3830: .  mat  - the matrix
3831: .  fact - factor

3833:    Not Collective, each process can use a different factor

3835:    Level: advanced

3837:   Notes:
3838:    This can also be set by the command line option: -mat_use_hash_table <fact>

3840: .keywords: matrix, hashtable, factor, HT

3842: .seealso: MatSetOption()
3843: @*/
3844: PetscErrorCode  MatMPIBAIJSetHashTableFactor(Mat mat,PetscReal fact)
3845: {

3849:   PetscTryMethod(mat,"MatSetHashTableFactor_C",(Mat,PetscReal),(mat,fact));
3850:   return(0);
3851: }

3855: PetscErrorCode  MatSetHashTableFactor_MPIBAIJ(Mat mat,PetscReal fact)
3856: {
3857:   Mat_MPIBAIJ *baij;

3860:   baij          = (Mat_MPIBAIJ*)mat->data;
3861:   baij->ht_fact = fact;
3862:   return(0);
3863: }

3867: PetscErrorCode  MatMPIBAIJGetSeqBAIJ(Mat A,Mat *Ad,Mat *Ao,const PetscInt *colmap[])
3868: {
3869:   Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data;

3872:   *Ad     = a->A;
3873:   *Ao     = a->B;
3874:   *colmap = a->garray;
3875:   return(0);
3876: }

3878: /*
3879:     Special version for direct calls from Fortran (to eliminate two function call overheads
3880: */
3881: #if defined(PETSC_HAVE_FORTRAN_CAPS)
3882: #define matmpibaijsetvaluesblocked_ MATMPIBAIJSETVALUESBLOCKED
3883: #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE)
3884: #define matmpibaijsetvaluesblocked_ matmpibaijsetvaluesblocked
3885: #endif

3889: /*@C
3890:   MatMPIBAIJSetValuesBlocked - Direct Fortran call to replace call to MatSetValuesBlocked()

3892:   Collective on Mat

3894:   Input Parameters:
3895: + mat - the matrix
3896: . min - number of input rows
3897: . im - input rows
3898: . nin - number of input columns
3899: . in - input columns
3900: . v - numerical values input
3901: - addvin - INSERT_VALUES or ADD_VALUES

3903:   Notes: This has a complete copy of MatSetValuesBlocked_MPIBAIJ() which is terrible code un-reuse.

3905:   Level: advanced

3907: .seealso:   MatSetValuesBlocked()
3908: @*/
3909: PetscErrorCode matmpibaijsetvaluesblocked_(Mat *matin,PetscInt *min,const PetscInt im[],PetscInt *nin,const PetscInt in[],const MatScalar v[],InsertMode *addvin)
3910: {
3911:   /* convert input arguments to C version */
3912:   Mat        mat  = *matin;
3913:   PetscInt   m    = *min, n = *nin;
3914:   InsertMode addv = *addvin;

3916:   Mat_MPIBAIJ     *baij = (Mat_MPIBAIJ*)mat->data;
3917:   const MatScalar *value;
3918:   MatScalar       *barray     = baij->barray;
3919:   PetscBool       roworiented = baij->roworiented;
3920:   PetscErrorCode  ierr;
3921:   PetscInt        i,j,ii,jj,row,col,rstart=baij->rstartbs;
3922:   PetscInt        rend=baij->rendbs,cstart=baij->cstartbs,stepval;
3923:   PetscInt        cend=baij->cendbs,bs=mat->rmap->bs,bs2=baij->bs2;

3926:   /* tasks normally handled by MatSetValuesBlocked() */
3927:   if (mat->insertmode == NOT_SET_VALUES) mat->insertmode = addv;
3928: #if defined(PETSC_USE_DEBUG)
3929:   else if (mat->insertmode != addv) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values");
3930:   if (mat->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix");
3931: #endif
3932:   if (mat->assembled) {
3933:     mat->was_assembled = PETSC_TRUE;
3934:     mat->assembled     = PETSC_FALSE;
3935:   }
3936:   PetscLogEventBegin(MAT_SetValues,mat,0,0,0);


3939:   if (!barray) {
3940:     PetscMalloc(bs2*sizeof(MatScalar),&barray);
3941:     baij->barray = barray;
3942:   }

3944:   if (roworiented) stepval = (n-1)*bs;
3945:   else stepval = (m-1)*bs;

3947:   for (i=0; i<m; i++) {
3948:     if (im[i] < 0) continue;
3949: #if defined(PETSC_USE_DEBUG)
3950:     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);
3951: #endif
3952:     if (im[i] >= rstart && im[i] < rend) {
3953:       row = im[i] - rstart;
3954:       for (j=0; j<n; j++) {
3955:         /* If NumCol = 1 then a copy is not required */
3956:         if ((roworiented) && (n == 1)) {
3957:           barray = (MatScalar*)v + i*bs2;
3958:         } else if ((!roworiented) && (m == 1)) {
3959:           barray = (MatScalar*)v + j*bs2;
3960:         } else { /* Here a copy is required */
3961:           if (roworiented) {
3962:             value = v + i*(stepval+bs)*bs + j*bs;
3963:           } else {
3964:             value = v + j*(stepval+bs)*bs + i*bs;
3965:           }
3966:           for (ii=0; ii<bs; ii++,value+=stepval) {
3967:             for (jj=0; jj<bs; jj++) {
3968:               *barray++ = *value++;
3969:             }
3970:           }
3971:           barray -=bs2;
3972:         }

3974:         if (in[j] >= cstart && in[j] < cend) {
3975:           col  = in[j] - cstart;
3976:           MatSetValuesBlocked_SeqBAIJ(baij->A,1,&row,1,&col,barray,addv);
3977:         } else if (in[j] < 0) continue;
3978: #if defined(PETSC_USE_DEBUG)
3979:         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);
3980: #endif
3981:         else {
3982:           if (mat->was_assembled) {
3983:             if (!baij->colmap) {
3984:               MatCreateColmap_MPIBAIJ_Private(mat);
3985:             }

3987: #if defined(PETSC_USE_DEBUG)
3988: #if defined(PETSC_USE_CTABLE)
3989:             { PetscInt data;
3990:               PetscTableFind(baij->colmap,in[j]+1,&data);
3991:               if ((data - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap");
3992:             }
3993: #else
3994:             if ((baij->colmap[in[j]] - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap");
3995: #endif
3996: #endif
3997: #if defined(PETSC_USE_CTABLE)
3998:             PetscTableFind(baij->colmap,in[j]+1,&col);
3999:             col  = (col - 1)/bs;
4000: #else
4001:             col = (baij->colmap[in[j]] - 1)/bs;
4002: #endif
4003:             if (col < 0 && !((Mat_SeqBAIJ*)(baij->A->data))->nonew) {
4004:               MatDisAssemble_MPIBAIJ(mat);
4005:               col  =  in[j];
4006:             }
4007:           } else col = in[j];
4008:           MatSetValuesBlocked_SeqBAIJ(baij->B,1,&row,1,&col,barray,addv);
4009:         }
4010:       }
4011:     } else {
4012:       if (!baij->donotstash) {
4013:         if (roworiented) {
4014:           MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);
4015:         } else {
4016:           MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);
4017:         }
4018:       }
4019:     }
4020:   }

4022:   /* task normally handled by MatSetValuesBlocked() */
4023:   PetscLogEventEnd(MAT_SetValues,mat,0,0,0);
4024:   return(0);
4025: }

4029: /*@
4030:      MatCreateMPIBAIJWithArrays - creates a MPI BAIJ matrix using arrays that contain in standard
4031:          CSR format the local rows.

4033:    Collective on MPI_Comm

4035:    Input Parameters:
4036: +  comm - MPI communicator
4037: .  bs - the block size, only a block size of 1 is supported
4038: .  m - number of local rows (Cannot be PETSC_DECIDE)
4039: .  n - This value should be the same as the local size used in creating the
4040:        x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have
4041:        calculated if N is given) For square matrices n is almost always m.
4042: .  M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
4043: .  N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
4044: .   i - row indices
4045: .   j - column indices
4046: -   a - matrix values

4048:    Output Parameter:
4049: .   mat - the matrix

4051:    Level: intermediate

4053:    Notes:
4054:        The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc;
4055:      thus you CANNOT change the matrix entries by changing the values of a[] after you have
4056:      called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays.

4058:        The i and j indices are 0 based, and i indices are indices corresponding to the local j array.

4060: .keywords: matrix, aij, compressed row, sparse, parallel

4062: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(),
4063:           MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays()
4064: @*/
4065: 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)
4066: {

4070:   if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0");
4071:   if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative");
4072:   MatCreate(comm,mat);
4073:   MatSetSizes(*mat,m,n,M,N);
4074:   MatSetType(*mat,MATMPISBAIJ);
4075:   MatMPIBAIJSetPreallocationCSR(*mat,bs,i,j,a);
4076:   return(0);
4077: }