Actual source code: mpisbaij.c

petsc-main 2021-04-20
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  2: #include <../src/mat/impls/baij/mpi/mpibaij.h>
  3: #include <../src/mat/impls/sbaij/mpi/mpisbaij.h>
  4: #include <../src/mat/impls/sbaij/seq/sbaij.h>
  5: #include <petscblaslapack.h>

  7: #if defined(PETSC_HAVE_ELEMENTAL)
  8: PETSC_INTERN PetscErrorCode MatConvert_MPISBAIJ_Elemental(Mat,MatType,MatReuse,Mat*);
  9: #endif
 10: #if defined(PETSC_HAVE_SCALAPACK)
 11: PETSC_INTERN PetscErrorCode MatConvert_SBAIJ_ScaLAPACK(Mat,MatType,MatReuse,Mat*);
 12: #endif

 14: /* This could be moved to matimpl.h */
 15: static PetscErrorCode MatPreallocateWithMats_Private(Mat B, PetscInt nm, Mat X[], PetscBool symm[], PetscBool fill)
 16: {
 17:   Mat            preallocator;
 18:   PetscInt       r,rstart,rend;
 19:   PetscInt       bs,i,m,n,M,N;
 20:   PetscBool      cong = PETSC_TRUE;

 26:   for (i = 0; i < nm; i++) {
 28:     PetscLayoutCompare(B->rmap,X[i]->rmap,&cong);
 29:     if (!cong) SETERRQ(PetscObjectComm((PetscObject)B),PETSC_ERR_SUP,"Not for different layouts");
 30:   }
 32:   MatGetBlockSize(B,&bs);
 33:   MatGetSize(B,&M,&N);
 34:   MatGetLocalSize(B,&m,&n);
 35:   MatCreate(PetscObjectComm((PetscObject)B),&preallocator);
 36:   MatSetType(preallocator,MATPREALLOCATOR);
 37:   MatSetBlockSize(preallocator,bs);
 38:   MatSetSizes(preallocator,m,n,M,N);
 39:   MatSetUp(preallocator);
 40:   MatGetOwnershipRange(preallocator,&rstart,&rend);
 41:   for (r = rstart; r < rend; ++r) {
 42:     PetscInt          ncols;
 43:     const PetscInt    *row;
 44:     const PetscScalar *vals;

 46:     for (i = 0; i < nm; i++) {
 47:       MatGetRow(X[i],r,&ncols,&row,&vals);
 48:       MatSetValues(preallocator,1,&r,ncols,row,vals,INSERT_VALUES);
 49:       if (symm && symm[i]) {
 50:         MatSetValues(preallocator,ncols,row,1,&r,vals,INSERT_VALUES);
 51:       }
 52:       MatRestoreRow(X[i],r,&ncols,&row,&vals);
 53:     }
 54:   }
 55:   MatAssemblyBegin(preallocator,MAT_FINAL_ASSEMBLY);
 56:   MatAssemblyEnd(preallocator,MAT_FINAL_ASSEMBLY);
 57:   MatPreallocatorPreallocate(preallocator,fill,B);
 58:   MatDestroy(&preallocator);
 59:   return(0);
 60: }

 62: PETSC_INTERN PetscErrorCode MatConvert_MPISBAIJ_Basic(Mat A, MatType newtype, MatReuse reuse, Mat *newmat)
 63: {
 64:   Mat            B;
 66:   PetscInt       r;

 69:   if (reuse != MAT_REUSE_MATRIX) {
 70:     PetscBool symm = PETSC_TRUE,isdense;
 71:     PetscInt  bs;

 73:     MatCreate(PetscObjectComm((PetscObject)A),&B);
 74:     MatSetSizes(B,A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N);
 75:     MatSetType(B,newtype);
 76:     MatGetBlockSize(A,&bs);
 77:     MatSetBlockSize(B,bs);
 78:     PetscLayoutSetUp(B->rmap);
 79:     PetscLayoutSetUp(B->cmap);
 80:     PetscObjectTypeCompareAny((PetscObject)B,&isdense,MATSEQDENSE,MATMPIDENSE,MATSEQDENSECUDA,"");
 81:     if (!isdense) {
 82:       MatGetRowUpperTriangular(A);
 83:       MatPreallocateWithMats_Private(B,1,&A,&symm,PETSC_TRUE);
 84:       MatRestoreRowUpperTriangular(A);
 85:     } else {
 86:       MatSetUp(B);
 87:     }
 88:   } else {
 89:     B    = *newmat;
 90:     MatZeroEntries(B);
 91:   }

 93:   MatGetRowUpperTriangular(A);
 94:   for (r = A->rmap->rstart; r < A->rmap->rend; r++) {
 95:     PetscInt          ncols;
 96:     const PetscInt    *row;
 97:     const PetscScalar *vals;

 99:     MatGetRow(A,r,&ncols,&row,&vals);
100:     MatSetValues(B,1,&r,ncols,row,vals,INSERT_VALUES);
101: #if defined(PETSC_USE_COMPLEX)
102:     if (A->hermitian) {
103:       PetscInt i;
104:       for (i = 0; i < ncols; i++) {
105:         MatSetValue(B,row[i],r,PetscConj(vals[i]),INSERT_VALUES);
106:       }
107:     } else {
108:       MatSetValues(B,ncols,row,1,&r,vals,INSERT_VALUES);
109:     }
110: #else
111:     MatSetValues(B,ncols,row,1,&r,vals,INSERT_VALUES);
112: #endif
113:     MatRestoreRow(A,r,&ncols,&row,&vals);
114:   }
115:   MatRestoreRowUpperTriangular(A);
116:   MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
117:   MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);

119:   if (reuse == MAT_INPLACE_MATRIX) {
120:     MatHeaderReplace(A,&B);
121:   } else {
122:     *newmat = B;
123:   }
124:   return(0);
125: }

127: PetscErrorCode  MatStoreValues_MPISBAIJ(Mat mat)
128: {
129:   Mat_MPISBAIJ   *aij = (Mat_MPISBAIJ*)mat->data;

133:   MatStoreValues(aij->A);
134:   MatStoreValues(aij->B);
135:   return(0);
136: }

138: PetscErrorCode  MatRetrieveValues_MPISBAIJ(Mat mat)
139: {
140:   Mat_MPISBAIJ   *aij = (Mat_MPISBAIJ*)mat->data;

144:   MatRetrieveValues(aij->A);
145:   MatRetrieveValues(aij->B);
146:   return(0);
147: }

149: #define  MatSetValues_SeqSBAIJ_A_Private(row,col,value,addv,orow,ocol)      \
150:   { \
151:     brow = row/bs;  \
152:     rp   = aj + ai[brow]; ap = aa + bs2*ai[brow]; \
153:     rmax = aimax[brow]; nrow = ailen[brow]; \
154:     bcol = col/bs; \
155:     ridx = row % bs; cidx = col % bs; \
156:     low  = 0; high = nrow; \
157:     while (high-low > 3) { \
158:       t = (low+high)/2; \
159:       if (rp[t] > bcol) high = t; \
160:       else              low  = t; \
161:     } \
162:     for (_i=low; _i<high; _i++) { \
163:       if (rp[_i] > bcol) break; \
164:       if (rp[_i] == bcol) { \
165:         bap = ap + bs2*_i + bs*cidx + ridx; \
166:         if (addv == ADD_VALUES) *bap += value;  \
167:         else                    *bap  = value;  \
168:         goto a_noinsert; \
169:       } \
170:     } \
171:     if (a->nonew == 1) goto a_noinsert; \
172:     if (a->nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero at global row/column (%D, %D) into matrix", orow, ocol); \
173:     MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,brow,bcol,rmax,aa,ai,aj,rp,ap,aimax,a->nonew,MatScalar); \
174:     N = nrow++ - 1;  \
175:     /* shift up all the later entries in this row */ \
176:     PetscArraymove(rp+_i+1,rp+_i,N-_i+1); \
177:     PetscArraymove(ap+bs2*(_i+1),ap+bs2*_i,bs2*(N-_i+1)); \
178:     PetscArrayzero(ap+bs2*_i,bs2);  \
179:     rp[_i]                      = bcol;  \
180:     ap[bs2*_i + bs*cidx + ridx] = value;  \
181:     A->nonzerostate++;\
182: a_noinsert:; \
183:     ailen[brow] = nrow; \
184:   }

186: #define  MatSetValues_SeqSBAIJ_B_Private(row,col,value,addv,orow,ocol) \
187:   { \
188:     brow = row/bs;  \
189:     rp   = bj + bi[brow]; ap = ba + bs2*bi[brow]; \
190:     rmax = bimax[brow]; nrow = bilen[brow]; \
191:     bcol = col/bs; \
192:     ridx = row % bs; cidx = col % bs; \
193:     low  = 0; high = nrow; \
194:     while (high-low > 3) { \
195:       t = (low+high)/2; \
196:       if (rp[t] > bcol) high = t; \
197:       else              low  = t; \
198:     } \
199:     for (_i=low; _i<high; _i++) { \
200:       if (rp[_i] > bcol) break; \
201:       if (rp[_i] == bcol) { \
202:         bap = ap + bs2*_i + bs*cidx + ridx; \
203:         if (addv == ADD_VALUES) *bap += value;  \
204:         else                    *bap  = value;  \
205:         goto b_noinsert; \
206:       } \
207:     } \
208:     if (b->nonew == 1) goto b_noinsert; \
209:     if (b->nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero at global row/column (%D, %D) into matrix", orow, ocol); \
210:     MatSeqXAIJReallocateAIJ(B,b->mbs,bs2,nrow,brow,bcol,rmax,ba,bi,bj,rp,ap,bimax,b->nonew,MatScalar); \
211:     N = nrow++ - 1;  \
212:     /* shift up all the later entries in this row */ \
213:     PetscArraymove(rp+_i+1,rp+_i,N-_i+1); \
214:     PetscArraymove(ap+bs2*(_i+1),ap+bs2*_i,bs2*(N-_i+1)); \
215:     PetscArrayzero(ap+bs2*_i,bs2); \
216:     rp[_i]                      = bcol;  \
217:     ap[bs2*_i + bs*cidx + ridx] = value;  \
218:     B->nonzerostate++;\
219: b_noinsert:; \
220:     bilen[brow] = nrow; \
221:   }

223: /* Only add/insert a(i,j) with i<=j (blocks).
224:    Any a(i,j) with i>j input by user is ingored or generates an error
225: */
226: PetscErrorCode MatSetValues_MPISBAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv)
227: {
228:   Mat_MPISBAIJ   *baij = (Mat_MPISBAIJ*)mat->data;
229:   MatScalar      value;
230:   PetscBool      roworiented = baij->roworiented;
232:   PetscInt       i,j,row,col;
233:   PetscInt       rstart_orig=mat->rmap->rstart;
234:   PetscInt       rend_orig  =mat->rmap->rend,cstart_orig=mat->cmap->rstart;
235:   PetscInt       cend_orig  =mat->cmap->rend,bs=mat->rmap->bs;

237:   /* Some Variables required in the macro */
238:   Mat          A     = baij->A;
239:   Mat_SeqSBAIJ *a    = (Mat_SeqSBAIJ*)(A)->data;
240:   PetscInt     *aimax=a->imax,*ai=a->i,*ailen=a->ilen,*aj=a->j;
241:   MatScalar    *aa   =a->a;

243:   Mat         B     = baij->B;
244:   Mat_SeqBAIJ *b    = (Mat_SeqBAIJ*)(B)->data;
245:   PetscInt    *bimax=b->imax,*bi=b->i,*bilen=b->ilen,*bj=b->j;
246:   MatScalar   *ba   =b->a;

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

252:   /* for stash */
253:   PetscInt  n_loc, *in_loc = NULL;
254:   MatScalar *v_loc = NULL;

257:   if (!baij->donotstash) {
258:     if (n > baij->n_loc) {
259:       PetscFree(baij->in_loc);
260:       PetscFree(baij->v_loc);
261:       PetscMalloc1(n,&baij->in_loc);
262:       PetscMalloc1(n,&baij->v_loc);

264:       baij->n_loc = n;
265:     }
266:     in_loc = baij->in_loc;
267:     v_loc  = baij->v_loc;
268:   }

270:   for (i=0; i<m; i++) {
271:     if (im[i] < 0) continue;
272:     if (PetscUnlikely(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);
273:     if (im[i] >= rstart_orig && im[i] < rend_orig) { /* this processor entry */
274:       row = im[i] - rstart_orig;              /* local row index */
275:       for (j=0; j<n; j++) {
276:         if (im[i]/bs > in[j]/bs) {
277:           if (a->ignore_ltriangular) {
278:             continue;    /* ignore lower triangular blocks */
279:           } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_USER,"Lower triangular value cannot be set for sbaij format. Ignoring these values, run with -mat_ignore_lower_triangular or call MatSetOption(mat,MAT_IGNORE_LOWER_TRIANGULAR,PETSC_TRUE)");
280:         }
281:         if (in[j] >= cstart_orig && in[j] < cend_orig) {  /* diag entry (A) */
282:           col  = in[j] - cstart_orig;         /* local col index */
283:           brow = row/bs; bcol = col/bs;
284:           if (brow > bcol) continue;  /* ignore lower triangular blocks of A */
285:           if (roworiented) value = v[i*n+j];
286:           else             value = v[i+j*m];
287:           MatSetValues_SeqSBAIJ_A_Private(row,col,value,addv,im[i],in[j]);
288:           /* MatSetValues_SeqBAIJ(baij->A,1,&row,1,&col,&value,addv); */
289:         } else if (in[j] < 0) continue;
290:         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);
291:         else {  /* off-diag entry (B) */
292:           if (mat->was_assembled) {
293:             if (!baij->colmap) {
294:               MatCreateColmap_MPIBAIJ_Private(mat);
295:             }
296: #if defined(PETSC_USE_CTABLE)
297:             PetscTableFind(baij->colmap,in[j]/bs + 1,&col);
298:             col  = col - 1;
299: #else
300:             col = baij->colmap[in[j]/bs] - 1;
301: #endif
302:             if (col < 0 && !((Mat_SeqSBAIJ*)(baij->A->data))->nonew) {
303:               MatDisAssemble_MPISBAIJ(mat);
304:               col  =  in[j];
305:               /* Reinitialize the variables required by MatSetValues_SeqBAIJ_B_Private() */
306:               B    = baij->B;
307:               b    = (Mat_SeqBAIJ*)(B)->data;
308:               bimax= b->imax;bi=b->i;bilen=b->ilen;bj=b->j;
309:               ba   = b->a;
310:             } else col += in[j]%bs;
311:           } else col = in[j];
312:           if (roworiented) value = v[i*n+j];
313:           else             value = v[i+j*m];
314:           MatSetValues_SeqSBAIJ_B_Private(row,col,value,addv,im[i],in[j]);
315:           /* MatSetValues_SeqBAIJ(baij->B,1,&row,1,&col,&value,addv); */
316:         }
317:       }
318:     } else {  /* off processor entry */
319:       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]);
320:       if (!baij->donotstash) {
321:         mat->assembled = PETSC_FALSE;
322:         n_loc          = 0;
323:         for (j=0; j<n; j++) {
324:           if (im[i]/bs > in[j]/bs) continue; /* ignore lower triangular blocks */
325:           in_loc[n_loc] = in[j];
326:           if (roworiented) {
327:             v_loc[n_loc] = v[i*n+j];
328:           } else {
329:             v_loc[n_loc] = v[j*m+i];
330:           }
331:           n_loc++;
332:         }
333:         MatStashValuesRow_Private(&mat->stash,im[i],n_loc,in_loc,v_loc,PETSC_FALSE);
334:       }
335:     }
336:   }
337:   return(0);
338: }

340: PETSC_STATIC_INLINE PetscErrorCode MatSetValuesBlocked_SeqSBAIJ_Inlined(Mat A,PetscInt row,PetscInt col,const PetscScalar v[],InsertMode is,PetscInt orow,PetscInt ocol)
341: {
342:   Mat_SeqSBAIJ      *a = (Mat_SeqSBAIJ*)A->data;
343:   PetscErrorCode    ierr;
344:   PetscInt          *rp,low,high,t,ii,jj,nrow,i,rmax,N;
345:   PetscInt          *imax      =a->imax,*ai=a->i,*ailen=a->ilen;
346:   PetscInt          *aj        =a->j,nonew=a->nonew,bs2=a->bs2,bs=A->rmap->bs;
347:   PetscBool         roworiented=a->roworiented;
348:   const PetscScalar *value     = v;
349:   MatScalar         *ap,*aa = a->a,*bap;

352:   if (col < row) {
353:     if (a->ignore_ltriangular) return(0); /* ignore lower triangular block */
354:     else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_USER,"Lower triangular value cannot be set for sbaij format. Ignoring these values, run with -mat_ignore_lower_triangular or call MatSetOption(mat,MAT_IGNORE_LOWER_TRIANGULAR,PETSC_TRUE)");
355:   }
356:   rp   = aj + ai[row];
357:   ap   = aa + bs2*ai[row];
358:   rmax = imax[row];
359:   nrow = ailen[row];
360:   value = v;
361:   low   = 0;
362:   high  = nrow;

364:   while (high-low > 7) {
365:     t = (low+high)/2;
366:     if (rp[t] > col) high = t;
367:     else             low  = t;
368:   }
369:   for (i=low; i<high; i++) {
370:     if (rp[i] > col) break;
371:     if (rp[i] == col) {
372:       bap = ap +  bs2*i;
373:       if (roworiented) {
374:         if (is == ADD_VALUES) {
375:           for (ii=0; ii<bs; ii++) {
376:             for (jj=ii; jj<bs2; jj+=bs) {
377:               bap[jj] += *value++;
378:             }
379:           }
380:         } else {
381:           for (ii=0; ii<bs; ii++) {
382:             for (jj=ii; jj<bs2; jj+=bs) {
383:               bap[jj] = *value++;
384:             }
385:           }
386:         }
387:       } else {
388:         if (is == ADD_VALUES) {
389:           for (ii=0; ii<bs; ii++) {
390:             for (jj=0; jj<bs; jj++) {
391:               *bap++ += *value++;
392:             }
393:           }
394:         } else {
395:           for (ii=0; ii<bs; ii++) {
396:             for (jj=0; jj<bs; jj++) {
397:               *bap++  = *value++;
398:             }
399:           }
400:         }
401:       }
402:       goto noinsert2;
403:     }
404:   }
405:   if (nonew == 1) goto noinsert2;
406:   if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new block index nonzero block (%D, %D) in the matrix", orow, ocol);
407:   MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,row,col,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar);
408:   N = nrow++ - 1; high++;
409:   /* shift up all the later entries in this row */
410:   PetscArraymove(rp+i+1,rp+i,N-i+1);
411:   PetscArraymove(ap+bs2*(i+1),ap+bs2*i,bs2*(N-i+1));
412:   rp[i] = col;
413:   bap   = ap +  bs2*i;
414:   if (roworiented) {
415:     for (ii=0; ii<bs; ii++) {
416:       for (jj=ii; jj<bs2; jj+=bs) {
417:         bap[jj] = *value++;
418:       }
419:     }
420:   } else {
421:     for (ii=0; ii<bs; ii++) {
422:       for (jj=0; jj<bs; jj++) {
423:         *bap++ = *value++;
424:       }
425:     }
426:   }
427:   noinsert2:;
428:   ailen[row] = nrow;
429:   return(0);
430: }

432: /*
433:    This routine is exactly duplicated in mpibaij.c
434: */
435: PETSC_STATIC_INLINE PetscErrorCode MatSetValuesBlocked_SeqBAIJ_Inlined(Mat A,PetscInt row,PetscInt col,const PetscScalar v[],InsertMode is,PetscInt orow,PetscInt ocol)
436: {
437:   Mat_SeqBAIJ       *a = (Mat_SeqBAIJ*)A->data;
438:   PetscInt          *rp,low,high,t,ii,jj,nrow,i,rmax,N;
439:   PetscInt          *imax=a->imax,*ai=a->i,*ailen=a->ilen;
440:   PetscErrorCode    ierr;
441:   PetscInt          *aj        =a->j,nonew=a->nonew,bs2=a->bs2,bs=A->rmap->bs;
442:   PetscBool         roworiented=a->roworiented;
443:   const PetscScalar *value     = v;
444:   MatScalar         *ap,*aa = a->a,*bap;

447:   rp   = aj + ai[row];
448:   ap   = aa + bs2*ai[row];
449:   rmax = imax[row];
450:   nrow = ailen[row];
451:   low  = 0;
452:   high = nrow;
453:   value = v;
454:   while (high-low > 7) {
455:     t = (low+high)/2;
456:     if (rp[t] > col) high = t;
457:     else             low  = t;
458:   }
459:   for (i=low; i<high; i++) {
460:     if (rp[i] > col) break;
461:     if (rp[i] == col) {
462:       bap = ap +  bs2*i;
463:       if (roworiented) {
464:         if (is == ADD_VALUES) {
465:           for (ii=0; ii<bs; ii++) {
466:             for (jj=ii; jj<bs2; jj+=bs) {
467:               bap[jj] += *value++;
468:             }
469:           }
470:         } else {
471:           for (ii=0; ii<bs; ii++) {
472:             for (jj=ii; jj<bs2; jj+=bs) {
473:               bap[jj] = *value++;
474:             }
475:           }
476:         }
477:       } else {
478:         if (is == ADD_VALUES) {
479:           for (ii=0; ii<bs; ii++,value+=bs) {
480:             for (jj=0; jj<bs; jj++) {
481:               bap[jj] += value[jj];
482:             }
483:             bap += bs;
484:           }
485:         } else {
486:           for (ii=0; ii<bs; ii++,value+=bs) {
487:             for (jj=0; jj<bs; jj++) {
488:               bap[jj]  = value[jj];
489:             }
490:             bap += bs;
491:           }
492:         }
493:       }
494:       goto noinsert2;
495:     }
496:   }
497:   if (nonew == 1) goto noinsert2;
498:   if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new global block indexed nonzero block (%D, %D) in the matrix", orow, ocol);
499:   MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,row,col,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar);
500:   N = nrow++ - 1; high++;
501:   /* shift up all the later entries in this row */
502:   PetscArraymove(rp+i+1,rp+i,N-i+1);
503:   PetscArraymove(ap+bs2*(i+1),ap+bs2*i,bs2*(N-i+1));
504:   rp[i] = col;
505:   bap   = ap +  bs2*i;
506:   if (roworiented) {
507:     for (ii=0; ii<bs; ii++) {
508:       for (jj=ii; jj<bs2; jj+=bs) {
509:         bap[jj] = *value++;
510:       }
511:     }
512:   } else {
513:     for (ii=0; ii<bs; ii++) {
514:       for (jj=0; jj<bs; jj++) {
515:         *bap++ = *value++;
516:       }
517:     }
518:   }
519:   noinsert2:;
520:   ailen[row] = nrow;
521:   return(0);
522: }

524: /*
525:     This routine could be optimized by removing the need for the block copy below and passing stride information
526:   to the above inline routines; similarly in MatSetValuesBlocked_MPIBAIJ()
527: */
528: PetscErrorCode MatSetValuesBlocked_MPISBAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const MatScalar v[],InsertMode addv)
529: {
530:   Mat_MPISBAIJ    *baij = (Mat_MPISBAIJ*)mat->data;
531:   const MatScalar *value;
532:   MatScalar       *barray     =baij->barray;
533:   PetscBool       roworiented = baij->roworiented,ignore_ltriangular = ((Mat_SeqSBAIJ*)baij->A->data)->ignore_ltriangular;
534:   PetscErrorCode  ierr;
535:   PetscInt        i,j,ii,jj,row,col,rstart=baij->rstartbs;
536:   PetscInt        rend=baij->rendbs,cstart=baij->cstartbs,stepval;
537:   PetscInt        cend=baij->cendbs,bs=mat->rmap->bs,bs2=baij->bs2;

540:   if (!barray) {
541:     PetscMalloc1(bs2,&barray);
542:     baij->barray = barray;
543:   }

545:   if (roworiented) {
546:     stepval = (n-1)*bs;
547:   } else {
548:     stepval = (m-1)*bs;
549:   }
550:   for (i=0; i<m; i++) {
551:     if (im[i] < 0) continue;
552:     if (PetscUnlikelyDebug(im[i] >= baij->Mbs)) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Block indexed row too large %D max %D",im[i],baij->Mbs-1);
553:     if (im[i] >= rstart && im[i] < rend) {
554:       row = im[i] - rstart;
555:       for (j=0; j<n; j++) {
556:         if (im[i] > in[j]) {
557:           if (ignore_ltriangular) continue; /* ignore lower triangular blocks */
558:           else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_USER,"Lower triangular value cannot be set for sbaij format. Ignoring these values, run with -mat_ignore_lower_triangular or call MatSetOption(mat,MAT_IGNORE_LOWER_TRIANGULAR,PETSC_TRUE)");
559:         }
560:         /* If NumCol = 1 then a copy is not required */
561:         if ((roworiented) && (n == 1)) {
562:           barray = (MatScalar*) v + i*bs2;
563:         } else if ((!roworiented) && (m == 1)) {
564:           barray = (MatScalar*) v + j*bs2;
565:         } else { /* Here a copy is required */
566:           if (roworiented) {
567:             value = v + i*(stepval+bs)*bs + j*bs;
568:           } else {
569:             value = v + j*(stepval+bs)*bs + i*bs;
570:           }
571:           for (ii=0; ii<bs; ii++,value+=stepval) {
572:             for (jj=0; jj<bs; jj++) {
573:               *barray++ = *value++;
574:             }
575:           }
576:           barray -=bs2;
577:         }

579:         if (in[j] >= cstart && in[j] < cend) {
580:           col  = in[j] - cstart;
581:           MatSetValuesBlocked_SeqSBAIJ_Inlined(baij->A,row,col,barray,addv,im[i],in[j]);
582:         } else if (in[j] < 0) continue;
583:         else if (PetscUnlikelyDebug(in[j] >= baij->Nbs)) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Block indexed column too large %D max %D",in[j],baij->Nbs-1);
584:         else {
585:           if (mat->was_assembled) {
586:             if (!baij->colmap) {
587:               MatCreateColmap_MPIBAIJ_Private(mat);
588:             }

590: #if defined(PETSC_USE_DEBUG)
591: #if defined(PETSC_USE_CTABLE)
592:             { PetscInt data;
593:               PetscTableFind(baij->colmap,in[j]+1,&data);
594:               if ((data - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap");
595:             }
596: #else
597:             if ((baij->colmap[in[j]] - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap");
598: #endif
599: #endif
600: #if defined(PETSC_USE_CTABLE)
601:             PetscTableFind(baij->colmap,in[j]+1,&col);
602:             col  = (col - 1)/bs;
603: #else
604:             col = (baij->colmap[in[j]] - 1)/bs;
605: #endif
606:             if (col < 0 && !((Mat_SeqBAIJ*)(baij->A->data))->nonew) {
607:               MatDisAssemble_MPISBAIJ(mat);
608:               col  = in[j];
609:             }
610:           } else col = in[j];
611:           MatSetValuesBlocked_SeqBAIJ_Inlined(baij->B,row,col,barray,addv,im[i],in[j]);
612:         }
613:       }
614:     } else {
615:       if (mat->nooffprocentries) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Setting off process block indexed row %D even though MatSetOption(,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE) was set",im[i]);
616:       if (!baij->donotstash) {
617:         if (roworiented) {
618:           MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);
619:         } else {
620:           MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);
621:         }
622:       }
623:     }
624:   }
625:   return(0);
626: }

628: PetscErrorCode MatGetValues_MPISBAIJ(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[])
629: {
630:   Mat_MPISBAIJ   *baij = (Mat_MPISBAIJ*)mat->data;
632:   PetscInt       bs       = mat->rmap->bs,i,j,bsrstart = mat->rmap->rstart,bsrend = mat->rmap->rend;
633:   PetscInt       bscstart = mat->cmap->rstart,bscend = mat->cmap->rend,row,col,data;

636:   for (i=0; i<m; i++) {
637:     if (idxm[i] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",idxm[i]); */
638:     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);
639:     if (idxm[i] >= bsrstart && idxm[i] < bsrend) {
640:       row = idxm[i] - bsrstart;
641:       for (j=0; j<n; j++) {
642:         if (idxn[j] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column %D",idxn[j]); */
643:         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);
644:         if (idxn[j] >= bscstart && idxn[j] < bscend) {
645:           col  = idxn[j] - bscstart;
646:           MatGetValues_SeqSBAIJ(baij->A,1,&row,1,&col,v+i*n+j);
647:         } else {
648:           if (!baij->colmap) {
649:             MatCreateColmap_MPIBAIJ_Private(mat);
650:           }
651: #if defined(PETSC_USE_CTABLE)
652:           PetscTableFind(baij->colmap,idxn[j]/bs+1,&data);
653:           data--;
654: #else
655:           data = baij->colmap[idxn[j]/bs]-1;
656: #endif
657:           if ((data < 0) || (baij->garray[data/bs] != idxn[j]/bs)) *(v+i*n+j) = 0.0;
658:           else {
659:             col  = data + idxn[j]%bs;
660:             MatGetValues_SeqBAIJ(baij->B,1,&row,1,&col,v+i*n+j);
661:           }
662:         }
663:       }
664:     } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local values currently supported");
665:   }
666:   return(0);
667: }

669: PetscErrorCode MatNorm_MPISBAIJ(Mat mat,NormType type,PetscReal *norm)
670: {
671:   Mat_MPISBAIJ   *baij = (Mat_MPISBAIJ*)mat->data;
673:   PetscReal      sum[2],*lnorm2;

676:   if (baij->size == 1) {
677:      MatNorm(baij->A,type,norm);
678:   } else {
679:     if (type == NORM_FROBENIUS) {
680:       PetscMalloc1(2,&lnorm2);
681:        MatNorm(baij->A,type,lnorm2);
682:       *lnorm2 = (*lnorm2)*(*lnorm2); lnorm2++;            /* squar power of norm(A) */
683:        MatNorm(baij->B,type,lnorm2);
684:       *lnorm2 = (*lnorm2)*(*lnorm2); lnorm2--;             /* squar power of norm(B) */
685:       MPIU_Allreduce(lnorm2,sum,2,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));
686:       *norm   = PetscSqrtReal(sum[0] + 2*sum[1]);
687:       PetscFree(lnorm2);
688:     } else if (type == NORM_INFINITY || type == NORM_1) { /* max row/column sum */
689:       Mat_SeqSBAIJ *amat=(Mat_SeqSBAIJ*)baij->A->data;
690:       Mat_SeqBAIJ  *bmat=(Mat_SeqBAIJ*)baij->B->data;
691:       PetscReal    *rsum,*rsum2,vabs;
692:       PetscInt     *jj,*garray=baij->garray,rstart=baij->rstartbs,nz;
693:       PetscInt     brow,bcol,col,bs=baij->A->rmap->bs,row,grow,gcol,mbs=amat->mbs;
694:       MatScalar    *v;

696:       PetscMalloc2(mat->cmap->N,&rsum,mat->cmap->N,&rsum2);
697:       PetscArrayzero(rsum,mat->cmap->N);
698:       /* Amat */
699:       v = amat->a; jj = amat->j;
700:       for (brow=0; brow<mbs; brow++) {
701:         grow = bs*(rstart + brow);
702:         nz   = amat->i[brow+1] - amat->i[brow];
703:         for (bcol=0; bcol<nz; bcol++) {
704:           gcol = bs*(rstart + *jj); jj++;
705:           for (col=0; col<bs; col++) {
706:             for (row=0; row<bs; row++) {
707:               vabs            = PetscAbsScalar(*v); v++;
708:               rsum[gcol+col] += vabs;
709:               /* non-diagonal block */
710:               if (bcol > 0 && vabs > 0.0) rsum[grow+row] += vabs;
711:             }
712:           }
713:         }
714:         PetscLogFlops(nz*bs*bs);
715:       }
716:       /* Bmat */
717:       v = bmat->a; jj = bmat->j;
718:       for (brow=0; brow<mbs; brow++) {
719:         grow = bs*(rstart + brow);
720:         nz = bmat->i[brow+1] - bmat->i[brow];
721:         for (bcol=0; bcol<nz; bcol++) {
722:           gcol = bs*garray[*jj]; jj++;
723:           for (col=0; col<bs; col++) {
724:             for (row=0; row<bs; row++) {
725:               vabs            = PetscAbsScalar(*v); v++;
726:               rsum[gcol+col] += vabs;
727:               rsum[grow+row] += vabs;
728:             }
729:           }
730:         }
731:         PetscLogFlops(nz*bs*bs);
732:       }
733:       MPIU_Allreduce(rsum,rsum2,mat->cmap->N,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));
734:       *norm = 0.0;
735:       for (col=0; col<mat->cmap->N; col++) {
736:         if (rsum2[col] > *norm) *norm = rsum2[col];
737:       }
738:       PetscFree2(rsum,rsum2);
739:     } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support for this norm yet");
740:   }
741:   return(0);
742: }

744: PetscErrorCode MatAssemblyBegin_MPISBAIJ(Mat mat,MatAssemblyType mode)
745: {
746:   Mat_MPISBAIJ   *baij = (Mat_MPISBAIJ*)mat->data;
748:   PetscInt       nstash,reallocs;

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

753:   MatStashScatterBegin_Private(mat,&mat->stash,mat->rmap->range);
754:   MatStashScatterBegin_Private(mat,&mat->bstash,baij->rangebs);
755:   MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);
756:   PetscInfo2(mat,"Stash has %D entries,uses %D mallocs.\n",nstash,reallocs);
757:   MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);
758:   PetscInfo2(mat,"Block-Stash has %D entries, uses %D mallocs.\n",nstash,reallocs);
759:   return(0);
760: }

762: PetscErrorCode MatAssemblyEnd_MPISBAIJ(Mat mat,MatAssemblyType mode)
763: {
764:   Mat_MPISBAIJ   *baij=(Mat_MPISBAIJ*)mat->data;
765:   Mat_SeqSBAIJ   *a   =(Mat_SeqSBAIJ*)baij->A->data;
767:   PetscInt       i,j,rstart,ncols,flg,bs2=baij->bs2;
768:   PetscInt       *row,*col;
769:   PetscBool      other_disassembled;
770:   PetscMPIInt    n;
771:   PetscBool      r1,r2,r3;
772:   MatScalar      *val;

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

781:       for (i=0; i<n;) {
782:         /* Now identify the consecutive vals belonging to the same row */
783:         for (j=i,rstart=row[j]; j<n; j++) {
784:           if (row[j] != rstart) break;
785:         }
786:         if (j < n) ncols = j-i;
787:         else       ncols = n-i;
788:         /* Now assemble all these values with a single function call */
789:         MatSetValues_MPISBAIJ(mat,1,row+i,ncols,col+i,val+i,mat->insertmode);
790:         i    = j;
791:       }
792:     }
793:     MatStashScatterEnd_Private(&mat->stash);
794:     /* Now process the block-stash. Since the values are stashed column-oriented,
795:        set the roworiented flag to column oriented, and after MatSetValues()
796:        restore the original flags */
797:     r1 = baij->roworiented;
798:     r2 = a->roworiented;
799:     r3 = ((Mat_SeqBAIJ*)baij->B->data)->roworiented;

801:     baij->roworiented = PETSC_FALSE;
802:     a->roworiented    = PETSC_FALSE;

804:     ((Mat_SeqBAIJ*)baij->B->data)->roworiented = PETSC_FALSE; /* b->roworinted */
805:     while (1) {
806:       MatStashScatterGetMesg_Private(&mat->bstash,&n,&row,&col,&val,&flg);
807:       if (!flg) break;

809:       for (i=0; i<n;) {
810:         /* Now identify the consecutive vals belonging to the same row */
811:         for (j=i,rstart=row[j]; j<n; j++) {
812:           if (row[j] != rstart) break;
813:         }
814:         if (j < n) ncols = j-i;
815:         else       ncols = n-i;
816:         MatSetValuesBlocked_MPISBAIJ(mat,1,row+i,ncols,col+i,val+i*bs2,mat->insertmode);
817:         i    = j;
818:       }
819:     }
820:     MatStashScatterEnd_Private(&mat->bstash);

822:     baij->roworiented = r1;
823:     a->roworiented    = r2;

825:     ((Mat_SeqBAIJ*)baij->B->data)->roworiented = r3; /* b->roworinted */
826:   }

828:   MatAssemblyBegin(baij->A,mode);
829:   MatAssemblyEnd(baij->A,mode);

831:   /* determine if any processor has disassembled, if so we must
832:      also disassemble ourselfs, in order that we may reassemble. */
833:   /*
834:      if nonzero structure of submatrix B cannot change then we know that
835:      no processor disassembled thus we can skip this stuff
836:   */
837:   if (!((Mat_SeqBAIJ*)baij->B->data)->nonew) {
838:     MPIU_Allreduce(&mat->was_assembled,&other_disassembled,1,MPIU_BOOL,MPI_PROD,PetscObjectComm((PetscObject)mat));
839:     if (mat->was_assembled && !other_disassembled) {
840:       MatDisAssemble_MPISBAIJ(mat);
841:     }
842:   }

844:   if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) {
845:     MatSetUpMultiply_MPISBAIJ(mat); /* setup Mvctx and sMvctx */
846:   }
847:   MatAssemblyBegin(baij->B,mode);
848:   MatAssemblyEnd(baij->B,mode);

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

852:   baij->rowvalues = NULL;

854:   /* if no new nonzero locations are allowed in matrix then only set the matrix state the first time through */
855:   if ((!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) || !((Mat_SeqBAIJ*)(baij->A->data))->nonew) {
856:     PetscObjectState state = baij->A->nonzerostate + baij->B->nonzerostate;
857:     MPIU_Allreduce(&state,&mat->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)mat));
858:   }
859:   return(0);
860: }

862: extern PetscErrorCode MatSetValues_MPIBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const PetscScalar[],InsertMode);
863: #include <petscdraw.h>
864: static PetscErrorCode MatView_MPISBAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer)
865: {
866:   Mat_MPISBAIJ      *baij = (Mat_MPISBAIJ*)mat->data;
867:   PetscErrorCode    ierr;
868:   PetscInt          bs   = mat->rmap->bs;
869:   PetscMPIInt       rank = baij->rank;
870:   PetscBool         iascii,isdraw;
871:   PetscViewer       sviewer;
872:   PetscViewerFormat format;

875:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
876:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);
877:   if (iascii) {
878:     PetscViewerGetFormat(viewer,&format);
879:     if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) {
880:       MatInfo info;
881:       MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);
882:       MatGetInfo(mat,MAT_LOCAL,&info);
883:       PetscViewerASCIIPushSynchronized(viewer);
884:       PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D bs %D mem %g\n",rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,mat->rmap->bs,(double)info.memory);
885:       MatGetInfo(baij->A,MAT_LOCAL,&info);
886:       PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);
887:       MatGetInfo(baij->B,MAT_LOCAL,&info);
888:       PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);
889:       PetscViewerFlush(viewer);
890:       PetscViewerASCIIPopSynchronized(viewer);
891:       PetscViewerASCIIPrintf(viewer,"Information on VecScatter used in matrix-vector product: \n");
892:       VecScatterView(baij->Mvctx,viewer);
893:       return(0);
894:     } else if (format == PETSC_VIEWER_ASCII_INFO) {
895:       PetscViewerASCIIPrintf(viewer,"  block size is %D\n",bs);
896:       return(0);
897:     } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) {
898:       return(0);
899:     }
900:   }

902:   if (isdraw) {
903:     PetscDraw draw;
904:     PetscBool isnull;
905:     PetscViewerDrawGetDraw(viewer,0,&draw);
906:     PetscDrawIsNull(draw,&isnull);
907:     if (isnull) return(0);
908:   }

910:   {
911:     /* assemble the entire matrix onto first processor. */
912:     Mat          A;
913:     Mat_SeqSBAIJ *Aloc;
914:     Mat_SeqBAIJ  *Bloc;
915:     PetscInt     M = mat->rmap->N,N = mat->cmap->N,*ai,*aj,col,i,j,k,*rvals,mbs = baij->mbs;
916:     MatScalar    *a;
917:     const char   *matname;

919:     /* Should this be the same type as mat? */
920:     MatCreate(PetscObjectComm((PetscObject)mat),&A);
921:     if (!rank) {
922:       MatSetSizes(A,M,N,M,N);
923:     } else {
924:       MatSetSizes(A,0,0,M,N);
925:     }
926:     MatSetType(A,MATMPISBAIJ);
927:     MatMPISBAIJSetPreallocation(A,mat->rmap->bs,0,NULL,0,NULL);
928:     MatSetOption(A,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_FALSE);
929:     PetscLogObjectParent((PetscObject)mat,(PetscObject)A);

931:     /* copy over the A part */
932:     Aloc = (Mat_SeqSBAIJ*)baij->A->data;
933:     ai   = Aloc->i; aj = Aloc->j; a = Aloc->a;
934:     PetscMalloc1(bs,&rvals);

936:     for (i=0; i<mbs; i++) {
937:       rvals[0] = bs*(baij->rstartbs + i);
938:       for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1;
939:       for (j=ai[i]; j<ai[i+1]; j++) {
940:         col = (baij->cstartbs+aj[j])*bs;
941:         for (k=0; k<bs; k++) {
942:           MatSetValues_MPISBAIJ(A,bs,rvals,1,&col,a,INSERT_VALUES);
943:           col++;
944:           a += bs;
945:         }
946:       }
947:     }
948:     /* copy over the B part */
949:     Bloc = (Mat_SeqBAIJ*)baij->B->data;
950:     ai   = Bloc->i; aj = Bloc->j; a = Bloc->a;
951:     for (i=0; i<mbs; i++) {

953:       rvals[0] = bs*(baij->rstartbs + i);
954:       for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1;
955:       for (j=ai[i]; j<ai[i+1]; j++) {
956:         col = baij->garray[aj[j]]*bs;
957:         for (k=0; k<bs; k++) {
958:           MatSetValues_MPIBAIJ(A,bs,rvals,1,&col,a,INSERT_VALUES);
959:           col++;
960:           a += bs;
961:         }
962:       }
963:     }
964:     PetscFree(rvals);
965:     MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);
966:     MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);
967:     /*
968:        Everyone has to call to draw the matrix since the graphics waits are
969:        synchronized across all processors that share the PetscDraw object
970:     */
971:     PetscViewerGetSubViewer(viewer,PETSC_COMM_SELF,&sviewer);
972:     PetscObjectGetName((PetscObject)mat,&matname);
973:     if (!rank) {
974:       PetscObjectSetName((PetscObject)((Mat_MPISBAIJ*)(A->data))->A,matname);
975:       MatView_SeqSBAIJ(((Mat_MPISBAIJ*)(A->data))->A,sviewer);
976:     }
977:     PetscViewerRestoreSubViewer(viewer,PETSC_COMM_SELF,&sviewer);
978:     PetscViewerFlush(viewer);
979:     MatDestroy(&A);
980:   }
981:   return(0);
982: }

984: /* Used for both MPIBAIJ and MPISBAIJ matrices */
985: #define MatView_MPISBAIJ_Binary MatView_MPIBAIJ_Binary

987: PetscErrorCode MatView_MPISBAIJ(Mat mat,PetscViewer viewer)
988: {
990:   PetscBool      iascii,isdraw,issocket,isbinary;

993:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
994:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);
995:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSOCKET,&issocket);
996:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);
997:   if (iascii || isdraw || issocket) {
998:     MatView_MPISBAIJ_ASCIIorDraworSocket(mat,viewer);
999:   } else if (isbinary) {
1000:     MatView_MPISBAIJ_Binary(mat,viewer);
1001:   }
1002:   return(0);
1003: }

1005: PetscErrorCode MatDestroy_MPISBAIJ(Mat mat)
1006: {
1007:   Mat_MPISBAIJ   *baij = (Mat_MPISBAIJ*)mat->data;

1011: #if defined(PETSC_USE_LOG)
1012:   PetscLogObjectState((PetscObject)mat,"Rows=%D,Cols=%D",mat->rmap->N,mat->cmap->N);
1013: #endif
1014:   MatStashDestroy_Private(&mat->stash);
1015:   MatStashDestroy_Private(&mat->bstash);
1016:   MatDestroy(&baij->A);
1017:   MatDestroy(&baij->B);
1018: #if defined(PETSC_USE_CTABLE)
1019:   PetscTableDestroy(&baij->colmap);
1020: #else
1021:   PetscFree(baij->colmap);
1022: #endif
1023:   PetscFree(baij->garray);
1024:   VecDestroy(&baij->lvec);
1025:   VecScatterDestroy(&baij->Mvctx);
1026:   VecDestroy(&baij->slvec0);
1027:   VecDestroy(&baij->slvec0b);
1028:   VecDestroy(&baij->slvec1);
1029:   VecDestroy(&baij->slvec1a);
1030:   VecDestroy(&baij->slvec1b);
1031:   VecScatterDestroy(&baij->sMvctx);
1032:   PetscFree2(baij->rowvalues,baij->rowindices);
1033:   PetscFree(baij->barray);
1034:   PetscFree(baij->hd);
1035:   VecDestroy(&baij->diag);
1036:   VecDestroy(&baij->bb1);
1037:   VecDestroy(&baij->xx1);
1038: #if defined(PETSC_USE_REAL_MAT_SINGLE)
1039:   PetscFree(baij->setvaluescopy);
1040: #endif
1041:   PetscFree(baij->in_loc);
1042:   PetscFree(baij->v_loc);
1043:   PetscFree(baij->rangebs);
1044:   PetscFree(mat->data);

1046:   PetscObjectChangeTypeName((PetscObject)mat,NULL);
1047:   PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C",NULL);
1048:   PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C",NULL);
1049:   PetscObjectComposeFunction((PetscObject)mat,"MatMPISBAIJSetPreallocation_C",NULL);
1050:   PetscObjectComposeFunction((PetscObject)mat,"MatMPISBAIJSetPreallocationCSR_C",NULL);
1051: #if defined(PETSC_HAVE_ELEMENTAL)
1052:   PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpisbaij_elemental_C",NULL);
1053: #endif
1054: #if defined(PETSC_HAVE_SCALAPACK)
1055:   PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpisbaij_scalapack_C",NULL);
1056: #endif
1057:   PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpisbaij_mpiaij_C",NULL);
1058:   PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpisbaij_mpibaij_C",NULL);
1059:   return(0);
1060: }

1062: PetscErrorCode MatMult_MPISBAIJ_Hermitian(Mat A,Vec xx,Vec yy)
1063: {
1064:   Mat_MPISBAIJ      *a = (Mat_MPISBAIJ*)A->data;
1065:   PetscErrorCode    ierr;
1066:   PetscInt          mbs=a->mbs,bs=A->rmap->bs;
1067:   PetscScalar       *from;
1068:   const PetscScalar *x;

1071:   /* diagonal part */
1072:   (*a->A->ops->mult)(a->A,xx,a->slvec1a);
1073:   VecSet(a->slvec1b,0.0);

1075:   /* subdiagonal part */
1076:   if (!a->B->ops->multhermitiantranspose) SETERRQ1(PetscObjectComm((PetscObject)a->B),PETSC_ERR_SUP,"Not for type %s\n",((PetscObject)a->B)->type_name);
1077:   (*a->B->ops->multhermitiantranspose)(a->B,xx,a->slvec0b);

1079:   /* copy x into the vec slvec0 */
1080:   VecGetArray(a->slvec0,&from);
1081:   VecGetArrayRead(xx,&x);

1083:   PetscArraycpy(from,x,bs*mbs);
1084:   VecRestoreArray(a->slvec0,&from);
1085:   VecRestoreArrayRead(xx,&x);

1087:   VecScatterBegin(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);
1088:   VecScatterEnd(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);
1089:   /* supperdiagonal part */
1090:   (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,yy);
1091:   return(0);
1092: }

1094: PetscErrorCode MatMult_MPISBAIJ(Mat A,Vec xx,Vec yy)
1095: {
1096:   Mat_MPISBAIJ      *a = (Mat_MPISBAIJ*)A->data;
1097:   PetscErrorCode    ierr;
1098:   PetscInt          mbs=a->mbs,bs=A->rmap->bs;
1099:   PetscScalar       *from;
1100:   const PetscScalar *x;

1103:   /* diagonal part */
1104:   (*a->A->ops->mult)(a->A,xx,a->slvec1a);
1105:   VecSet(a->slvec1b,0.0);

1107:   /* subdiagonal part */
1108:   (*a->B->ops->multtranspose)(a->B,xx,a->slvec0b);

1110:   /* copy x into the vec slvec0 */
1111:   VecGetArray(a->slvec0,&from);
1112:   VecGetArrayRead(xx,&x);

1114:   PetscArraycpy(from,x,bs*mbs);
1115:   VecRestoreArray(a->slvec0,&from);
1116:   VecRestoreArrayRead(xx,&x);

1118:   VecScatterBegin(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);
1119:   VecScatterEnd(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);
1120:   /* supperdiagonal part */
1121:   (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,yy);
1122:   return(0);
1123: }

1125: PetscErrorCode MatMultAdd_MPISBAIJ_Hermitian(Mat A,Vec xx,Vec yy,Vec zz)
1126: {
1127:   Mat_MPISBAIJ      *a = (Mat_MPISBAIJ*)A->data;
1128:   PetscErrorCode    ierr;
1129:   PetscInt          mbs=a->mbs,bs=A->rmap->bs;
1130:   PetscScalar       *from,zero=0.0;
1131:   const PetscScalar *x;

1134:   /* diagonal part */
1135:   (*a->A->ops->multadd)(a->A,xx,yy,a->slvec1a);
1136:   VecSet(a->slvec1b,zero);

1138:   /* subdiagonal part */
1139:   if (!a->B->ops->multhermitiantranspose) SETERRQ1(PetscObjectComm((PetscObject)a->B),PETSC_ERR_SUP,"Not for type %s\n",((PetscObject)a->B)->type_name);
1140:   (*a->B->ops->multhermitiantranspose)(a->B,xx,a->slvec0b);

1142:   /* copy x into the vec slvec0 */
1143:   VecGetArray(a->slvec0,&from);
1144:   VecGetArrayRead(xx,&x);
1145:   PetscArraycpy(from,x,bs*mbs);
1146:   VecRestoreArray(a->slvec0,&from);

1148:   VecScatterBegin(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);
1149:   VecRestoreArrayRead(xx,&x);
1150:   VecScatterEnd(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);

1152:   /* supperdiagonal part */
1153:   (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,zz);
1154:   return(0);
1155: }

1157: PetscErrorCode MatMultAdd_MPISBAIJ(Mat A,Vec xx,Vec yy,Vec zz)
1158: {
1159:   Mat_MPISBAIJ      *a = (Mat_MPISBAIJ*)A->data;
1160:   PetscErrorCode    ierr;
1161:   PetscInt          mbs=a->mbs,bs=A->rmap->bs;
1162:   PetscScalar       *from,zero=0.0;
1163:   const PetscScalar *x;

1166:   /* diagonal part */
1167:   (*a->A->ops->multadd)(a->A,xx,yy,a->slvec1a);
1168:   VecSet(a->slvec1b,zero);

1170:   /* subdiagonal part */
1171:   (*a->B->ops->multtranspose)(a->B,xx,a->slvec0b);

1173:   /* copy x into the vec slvec0 */
1174:   VecGetArray(a->slvec0,&from);
1175:   VecGetArrayRead(xx,&x);
1176:   PetscArraycpy(from,x,bs*mbs);
1177:   VecRestoreArray(a->slvec0,&from);

1179:   VecScatterBegin(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);
1180:   VecRestoreArrayRead(xx,&x);
1181:   VecScatterEnd(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);

1183:   /* supperdiagonal part */
1184:   (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,zz);
1185:   return(0);
1186: }

1188: /*
1189:   This only works correctly for square matrices where the subblock A->A is the
1190:    diagonal block
1191: */
1192: PetscErrorCode MatGetDiagonal_MPISBAIJ(Mat A,Vec v)
1193: {
1194:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;

1198:   /* if (a->rmap->N != a->cmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block"); */
1199:   MatGetDiagonal(a->A,v);
1200:   return(0);
1201: }

1203: PetscErrorCode MatScale_MPISBAIJ(Mat A,PetscScalar aa)
1204: {
1205:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;

1209:   MatScale(a->A,aa);
1210:   MatScale(a->B,aa);
1211:   return(0);
1212: }

1214: PetscErrorCode MatGetRow_MPISBAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
1215: {
1216:   Mat_MPISBAIJ   *mat = (Mat_MPISBAIJ*)matin->data;
1217:   PetscScalar    *vworkA,*vworkB,**pvA,**pvB,*v_p;
1219:   PetscInt       bs = matin->rmap->bs,bs2 = mat->bs2,i,*cworkA,*cworkB,**pcA,**pcB;
1220:   PetscInt       nztot,nzA,nzB,lrow,brstart = matin->rmap->rstart,brend = matin->rmap->rend;
1221:   PetscInt       *cmap,*idx_p,cstart = mat->rstartbs;

1224:   if (mat->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Already active");
1225:   mat->getrowactive = PETSC_TRUE;

1227:   if (!mat->rowvalues && (idx || v)) {
1228:     /*
1229:         allocate enough space to hold information from the longest row.
1230:     */
1231:     Mat_SeqSBAIJ *Aa = (Mat_SeqSBAIJ*)mat->A->data;
1232:     Mat_SeqBAIJ  *Ba = (Mat_SeqBAIJ*)mat->B->data;
1233:     PetscInt     max = 1,mbs = mat->mbs,tmp;
1234:     for (i=0; i<mbs; i++) {
1235:       tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; /* row length */
1236:       if (max < tmp) max = tmp;
1237:     }
1238:     PetscMalloc2(max*bs2,&mat->rowvalues,max*bs2,&mat->rowindices);
1239:   }

1241:   if (row < brstart || row >= brend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local rows");
1242:   lrow = row - brstart;  /* local row index */

1244:   pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB;
1245:   if (!v)   {pvA = NULL; pvB = NULL;}
1246:   if (!idx) {pcA = NULL; if (!v) pcB = NULL;}
1247:   (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);
1248:   (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);
1249:   nztot = nzA + nzB;

1251:   cmap = mat->garray;
1252:   if (v  || idx) {
1253:     if (nztot) {
1254:       /* Sort by increasing column numbers, assuming A and B already sorted */
1255:       PetscInt imark = -1;
1256:       if (v) {
1257:         *v = v_p = mat->rowvalues;
1258:         for (i=0; i<nzB; i++) {
1259:           if (cmap[cworkB[i]/bs] < cstart) v_p[i] = vworkB[i];
1260:           else break;
1261:         }
1262:         imark = i;
1263:         for (i=0; i<nzA; i++)     v_p[imark+i] = vworkA[i];
1264:         for (i=imark; i<nzB; i++) v_p[nzA+i]   = vworkB[i];
1265:       }
1266:       if (idx) {
1267:         *idx = idx_p = mat->rowindices;
1268:         if (imark > -1) {
1269:           for (i=0; i<imark; i++) {
1270:             idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs;
1271:           }
1272:         } else {
1273:           for (i=0; i<nzB; i++) {
1274:             if (cmap[cworkB[i]/bs] < cstart) idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs;
1275:             else break;
1276:           }
1277:           imark = i;
1278:         }
1279:         for (i=0; i<nzA; i++)     idx_p[imark+i] = cstart*bs + cworkA[i];
1280:         for (i=imark; i<nzB; i++) idx_p[nzA+i]   = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ;
1281:       }
1282:     } else {
1283:       if (idx) *idx = NULL;
1284:       if (v)   *v   = NULL;
1285:     }
1286:   }
1287:   *nz  = nztot;
1288:   (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);
1289:   (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);
1290:   return(0);
1291: }

1293: PetscErrorCode MatRestoreRow_MPISBAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
1294: {
1295:   Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data;

1298:   if (!baij->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"MatGetRow() must be called first");
1299:   baij->getrowactive = PETSC_FALSE;
1300:   return(0);
1301: }

1303: PetscErrorCode MatGetRowUpperTriangular_MPISBAIJ(Mat A)
1304: {
1305:   Mat_MPISBAIJ *a  = (Mat_MPISBAIJ*)A->data;
1306:   Mat_SeqSBAIJ *aA = (Mat_SeqSBAIJ*)a->A->data;

1309:   aA->getrow_utriangular = PETSC_TRUE;
1310:   return(0);
1311: }
1312: PetscErrorCode MatRestoreRowUpperTriangular_MPISBAIJ(Mat A)
1313: {
1314:   Mat_MPISBAIJ *a  = (Mat_MPISBAIJ*)A->data;
1315:   Mat_SeqSBAIJ *aA = (Mat_SeqSBAIJ*)a->A->data;

1318:   aA->getrow_utriangular = PETSC_FALSE;
1319:   return(0);
1320: }

1322: PetscErrorCode MatConjugate_MPISBAIJ(Mat mat)
1323: {
1324: #if defined(PETSC_USE_COMPLEX)
1326:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)mat->data;

1329:   MatConjugate(a->A);
1330:   MatConjugate(a->B);
1331: #else
1333: #endif
1334:   return(0);
1335: }

1337: PetscErrorCode MatRealPart_MPISBAIJ(Mat A)
1338: {
1339:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;

1343:   MatRealPart(a->A);
1344:   MatRealPart(a->B);
1345:   return(0);
1346: }

1348: PetscErrorCode MatImaginaryPart_MPISBAIJ(Mat A)
1349: {
1350:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;

1354:   MatImaginaryPart(a->A);
1355:   MatImaginaryPart(a->B);
1356:   return(0);
1357: }

1359: /* Check if isrow is a subset of iscol_local, called by MatCreateSubMatrix_MPISBAIJ()
1360:    Input: isrow       - distributed(parallel),
1361:           iscol_local - locally owned (seq)
1362: */
1363: PetscErrorCode ISEqual_private(IS isrow,IS iscol_local,PetscBool  *flg)
1364: {
1366:   PetscInt       sz1,sz2,*a1,*a2,i,j,k,nmatch;
1367:   const PetscInt *ptr1,*ptr2;

1370:   ISGetLocalSize(isrow,&sz1);
1371:   ISGetLocalSize(iscol_local,&sz2);
1372:   if (sz1 > sz2) {
1373:     *flg = PETSC_FALSE;
1374:     return(0);
1375:   }

1377:   ISGetIndices(isrow,&ptr1);
1378:   ISGetIndices(iscol_local,&ptr2);

1380:   PetscMalloc1(sz1,&a1);
1381:   PetscMalloc1(sz2,&a2);
1382:   PetscArraycpy(a1,ptr1,sz1);
1383:   PetscArraycpy(a2,ptr2,sz2);
1384:   PetscSortInt(sz1,a1);
1385:   PetscSortInt(sz2,a2);

1387:   nmatch=0;
1388:   k     = 0;
1389:   for (i=0; i<sz1; i++){
1390:     for (j=k; j<sz2; j++){
1391:       if (a1[i] == a2[j]) {
1392:         k = j; nmatch++;
1393:         break;
1394:       }
1395:     }
1396:   }
1397:   ISRestoreIndices(isrow,&ptr1);
1398:   ISRestoreIndices(iscol_local,&ptr2);
1399:   PetscFree(a1);
1400:   PetscFree(a2);
1401:   if (nmatch < sz1) {
1402:     *flg = PETSC_FALSE;
1403:   } else {
1404:     *flg = PETSC_TRUE;
1405:   }
1406:   return(0);
1407: }

1409: PetscErrorCode MatCreateSubMatrix_MPISBAIJ(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat)
1410: {
1412:   IS             iscol_local;
1413:   PetscInt       csize;
1414:   PetscBool      isequal;

1417:   ISGetLocalSize(iscol,&csize);
1418:   if (call == MAT_REUSE_MATRIX) {
1419:     PetscObjectQuery((PetscObject)*newmat,"ISAllGather",(PetscObject*)&iscol_local);
1420:     if (!iscol_local) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse");
1421:   } else {
1422:     PetscBool issorted;

1424:     ISAllGather(iscol,&iscol_local);
1425:     ISEqual_private(isrow,iscol_local,&isequal);
1426:     ISSorted(iscol_local, &issorted);
1427:     if (!isequal || !issorted) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"For symmetric format, iscol must equal isrow and be sorted");
1428:   }

1430:   /* now call MatCreateSubMatrix_MPIBAIJ() */
1431:   MatCreateSubMatrix_MPIBAIJ_Private(mat,isrow,iscol_local,csize,call,newmat);
1432:   if (call == MAT_INITIAL_MATRIX) {
1433:     PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);
1434:     ISDestroy(&iscol_local);
1435:   }
1436:   return(0);
1437: }

1439: PetscErrorCode MatZeroEntries_MPISBAIJ(Mat A)
1440: {
1441:   Mat_MPISBAIJ   *l = (Mat_MPISBAIJ*)A->data;

1445:   MatZeroEntries(l->A);
1446:   MatZeroEntries(l->B);
1447:   return(0);
1448: }

1450: PetscErrorCode MatGetInfo_MPISBAIJ(Mat matin,MatInfoType flag,MatInfo *info)
1451: {
1452:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)matin->data;
1453:   Mat            A  = a->A,B = a->B;
1455:   PetscLogDouble isend[5],irecv[5];

1458:   info->block_size = (PetscReal)matin->rmap->bs;

1460:   MatGetInfo(A,MAT_LOCAL,info);

1462:   isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded;
1463:   isend[3] = info->memory;  isend[4] = info->mallocs;

1465:   MatGetInfo(B,MAT_LOCAL,info);

1467:   isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded;
1468:   isend[3] += info->memory;  isend[4] += info->mallocs;
1469:   if (flag == MAT_LOCAL) {
1470:     info->nz_used      = isend[0];
1471:     info->nz_allocated = isend[1];
1472:     info->nz_unneeded  = isend[2];
1473:     info->memory       = isend[3];
1474:     info->mallocs      = isend[4];
1475:   } else if (flag == MAT_GLOBAL_MAX) {
1476:     MPIU_Allreduce(isend,irecv,5,MPIU_PETSCLOGDOUBLE,MPI_MAX,PetscObjectComm((PetscObject)matin));

1478:     info->nz_used      = irecv[0];
1479:     info->nz_allocated = irecv[1];
1480:     info->nz_unneeded  = irecv[2];
1481:     info->memory       = irecv[3];
1482:     info->mallocs      = irecv[4];
1483:   } else if (flag == MAT_GLOBAL_SUM) {
1484:     MPIU_Allreduce(isend,irecv,5,MPIU_PETSCLOGDOUBLE,MPI_SUM,PetscObjectComm((PetscObject)matin));

1486:     info->nz_used      = irecv[0];
1487:     info->nz_allocated = irecv[1];
1488:     info->nz_unneeded  = irecv[2];
1489:     info->memory       = irecv[3];
1490:     info->mallocs      = irecv[4];
1491:   } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Unknown MatInfoType argument %d",(int)flag);
1492:   info->fill_ratio_given  = 0; /* no parallel LU/ILU/Cholesky */
1493:   info->fill_ratio_needed = 0;
1494:   info->factor_mallocs    = 0;
1495:   return(0);
1496: }

1498: PetscErrorCode MatSetOption_MPISBAIJ(Mat A,MatOption op,PetscBool flg)
1499: {
1500:   Mat_MPISBAIJ   *a  = (Mat_MPISBAIJ*)A->data;
1501:   Mat_SeqSBAIJ   *aA = (Mat_SeqSBAIJ*)a->A->data;

1505:   switch (op) {
1506:   case MAT_NEW_NONZERO_LOCATIONS:
1507:   case MAT_NEW_NONZERO_ALLOCATION_ERR:
1508:   case MAT_UNUSED_NONZERO_LOCATION_ERR:
1509:   case MAT_KEEP_NONZERO_PATTERN:
1510:   case MAT_SUBMAT_SINGLEIS:
1511:   case MAT_NEW_NONZERO_LOCATION_ERR:
1512:     MatCheckPreallocated(A,1);
1513:     MatSetOption(a->A,op,flg);
1514:     MatSetOption(a->B,op,flg);
1515:     break;
1516:   case MAT_ROW_ORIENTED:
1517:     MatCheckPreallocated(A,1);
1518:     a->roworiented = flg;

1520:     MatSetOption(a->A,op,flg);
1521:     MatSetOption(a->B,op,flg);
1522:     break;
1523:   case MAT_FORCE_DIAGONAL_ENTRIES:
1524:   case MAT_SORTED_FULL:
1525:     PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);
1526:     break;
1527:   case MAT_IGNORE_OFF_PROC_ENTRIES:
1528:     a->donotstash = flg;
1529:     break;
1530:   case MAT_USE_HASH_TABLE:
1531:     a->ht_flag = flg;
1532:     break;
1533:   case MAT_HERMITIAN:
1534:     MatCheckPreallocated(A,1);
1535:     MatSetOption(a->A,op,flg);
1536: #if defined(PETSC_USE_COMPLEX)
1537:     if (flg) { /* need different mat-vec ops */
1538:       A->ops->mult             = MatMult_MPISBAIJ_Hermitian;
1539:       A->ops->multadd          = MatMultAdd_MPISBAIJ_Hermitian;
1540:       A->ops->multtranspose    = NULL;
1541:       A->ops->multtransposeadd = NULL;
1542:       A->symmetric = PETSC_FALSE;
1543:     }
1544: #endif
1545:     break;
1546:   case MAT_SPD:
1547:   case MAT_SYMMETRIC:
1548:     MatCheckPreallocated(A,1);
1549:     MatSetOption(a->A,op,flg);
1550: #if defined(PETSC_USE_COMPLEX)
1551:     if (flg) { /* restore to use default mat-vec ops */
1552:       A->ops->mult             = MatMult_MPISBAIJ;
1553:       A->ops->multadd          = MatMultAdd_MPISBAIJ;
1554:       A->ops->multtranspose    = MatMult_MPISBAIJ;
1555:       A->ops->multtransposeadd = MatMultAdd_MPISBAIJ;
1556:     }
1557: #endif
1558:     break;
1559:   case MAT_STRUCTURALLY_SYMMETRIC:
1560:     MatCheckPreallocated(A,1);
1561:     MatSetOption(a->A,op,flg);
1562:     break;
1563:   case MAT_SYMMETRY_ETERNAL:
1564:     if (!flg) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Matrix must be symmetric");
1565:     PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);
1566:     break;
1567:   case MAT_IGNORE_LOWER_TRIANGULAR:
1568:     aA->ignore_ltriangular = flg;
1569:     break;
1570:   case MAT_ERROR_LOWER_TRIANGULAR:
1571:     aA->ignore_ltriangular = flg;
1572:     break;
1573:   case MAT_GETROW_UPPERTRIANGULAR:
1574:     aA->getrow_utriangular = flg;
1575:     break;
1576:   default:
1577:     SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %d",op);
1578:   }
1579:   return(0);
1580: }

1582: PetscErrorCode MatTranspose_MPISBAIJ(Mat A,MatReuse reuse,Mat *B)
1583: {

1587:   if (reuse == MAT_INITIAL_MATRIX) {
1588:     MatDuplicate(A,MAT_COPY_VALUES,B);
1589:   }  else if (reuse == MAT_REUSE_MATRIX) {
1590:     MatCopy(A,*B,SAME_NONZERO_PATTERN);
1591:   }
1592:   return(0);
1593: }

1595: PetscErrorCode MatDiagonalScale_MPISBAIJ(Mat mat,Vec ll,Vec rr)
1596: {
1597:   Mat_MPISBAIJ   *baij = (Mat_MPISBAIJ*)mat->data;
1598:   Mat            a     = baij->A, b=baij->B;
1600:   PetscInt       nv,m,n;
1601:   PetscBool      flg;

1604:   if (ll != rr) {
1605:     VecEqual(ll,rr,&flg);
1606:     if (!flg) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"For symmetric format, left and right scaling vectors must be same\n");
1607:   }
1608:   if (!ll) return(0);

1610:   MatGetLocalSize(mat,&m,&n);
1611:   if (m != n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"For symmetric format, local size %d %d must be same",m,n);

1613:   VecGetLocalSize(rr,&nv);
1614:   if (nv!=n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Left and right vector non-conforming local size");

1616:   VecScatterBegin(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);

1618:   /* left diagonalscale the off-diagonal part */
1619:   (*b->ops->diagonalscale)(b,ll,NULL);

1621:   /* scale the diagonal part */
1622:   (*a->ops->diagonalscale)(a,ll,rr);

1624:   /* right diagonalscale the off-diagonal part */
1625:   VecScatterEnd(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);
1626:   (*b->ops->diagonalscale)(b,NULL,baij->lvec);
1627:   return(0);
1628: }

1630: PetscErrorCode MatSetUnfactored_MPISBAIJ(Mat A)
1631: {
1632:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;

1636:   MatSetUnfactored(a->A);
1637:   return(0);
1638: }

1640: static PetscErrorCode MatDuplicate_MPISBAIJ(Mat,MatDuplicateOption,Mat*);

1642: PetscErrorCode MatEqual_MPISBAIJ(Mat A,Mat B,PetscBool  *flag)
1643: {
1644:   Mat_MPISBAIJ   *matB = (Mat_MPISBAIJ*)B->data,*matA = (Mat_MPISBAIJ*)A->data;
1645:   Mat            a,b,c,d;
1646:   PetscBool      flg;

1650:   a = matA->A; b = matA->B;
1651:   c = matB->A; d = matB->B;

1653:   MatEqual(a,c,&flg);
1654:   if (flg) {
1655:     MatEqual(b,d,&flg);
1656:   }
1657:   MPIU_Allreduce(&flg,flag,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)A));
1658:   return(0);
1659: }

1661: PetscErrorCode MatCopy_MPISBAIJ(Mat A,Mat B,MatStructure str)
1662: {
1664:   PetscBool      isbaij;

1667:   PetscObjectTypeCompareAny((PetscObject)B,&isbaij,MATSEQSBAIJ,MATMPISBAIJ,"");
1668:   if (!isbaij) SETERRQ1(PetscObjectComm((PetscObject)B),PETSC_ERR_SUP,"Not for matrix type %s",((PetscObject)B)->type_name);
1669:   /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */
1670:   if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) {
1671:     MatGetRowUpperTriangular(A);
1672:     MatCopy_Basic(A,B,str);
1673:     MatRestoreRowUpperTriangular(A);
1674:   } else {
1675:     Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data;
1676:     Mat_MPISBAIJ *b = (Mat_MPISBAIJ*)B->data;

1678:     MatCopy(a->A,b->A,str);
1679:     MatCopy(a->B,b->B,str);
1680:   }
1681:   PetscObjectStateIncrease((PetscObject)B);
1682:   return(0);
1683: }

1685: PetscErrorCode MatSetUp_MPISBAIJ(Mat A)
1686: {

1690:   MatMPISBAIJSetPreallocation(A,A->rmap->bs,PETSC_DEFAULT,NULL,PETSC_DEFAULT,NULL);
1691:   return(0);
1692: }

1694: PetscErrorCode MatAXPY_MPISBAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str)
1695: {
1697:   Mat_MPISBAIJ   *xx=(Mat_MPISBAIJ*)X->data,*yy=(Mat_MPISBAIJ*)Y->data;
1698:   PetscBLASInt   bnz,one=1;
1699:   Mat_SeqSBAIJ   *xa,*ya;
1700:   Mat_SeqBAIJ    *xb,*yb;

1703:   if (str == SAME_NONZERO_PATTERN) {
1704:     PetscScalar alpha = a;
1705:     xa   = (Mat_SeqSBAIJ*)xx->A->data;
1706:     ya   = (Mat_SeqSBAIJ*)yy->A->data;
1707:     PetscBLASIntCast(xa->nz,&bnz);
1708:     PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,xa->a,&one,ya->a,&one));
1709:     xb   = (Mat_SeqBAIJ*)xx->B->data;
1710:     yb   = (Mat_SeqBAIJ*)yy->B->data;
1711:     PetscBLASIntCast(xb->nz,&bnz);
1712:     PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,xb->a,&one,yb->a,&one));
1713:     PetscObjectStateIncrease((PetscObject)Y);
1714:   } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */
1715:     MatSetOption(X,MAT_GETROW_UPPERTRIANGULAR,PETSC_TRUE);
1716:     MatAXPY_Basic(Y,a,X,str);
1717:     MatSetOption(X,MAT_GETROW_UPPERTRIANGULAR,PETSC_FALSE);
1718:   } else {
1719:     Mat      B;
1720:     PetscInt *nnz_d,*nnz_o,bs=Y->rmap->bs;
1721:     if (bs != X->rmap->bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Matrices must have same block size");
1722:     MatGetRowUpperTriangular(X);
1723:     MatGetRowUpperTriangular(Y);
1724:     PetscMalloc1(yy->A->rmap->N,&nnz_d);
1725:     PetscMalloc1(yy->B->rmap->N,&nnz_o);
1726:     MatCreate(PetscObjectComm((PetscObject)Y),&B);
1727:     PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);
1728:     MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);
1729:     MatSetBlockSizesFromMats(B,Y,Y);
1730:     MatSetType(B,MATMPISBAIJ);
1731:     MatAXPYGetPreallocation_SeqSBAIJ(yy->A,xx->A,nnz_d);
1732:     MatAXPYGetPreallocation_MPIBAIJ(yy->B,yy->garray,xx->B,xx->garray,nnz_o);
1733:     MatMPISBAIJSetPreallocation(B,bs,0,nnz_d,0,nnz_o);
1734:     MatAXPY_BasicWithPreallocation(B,Y,a,X,str);
1735:     MatHeaderReplace(Y,&B);
1736:     PetscFree(nnz_d);
1737:     PetscFree(nnz_o);
1738:     MatRestoreRowUpperTriangular(X);
1739:     MatRestoreRowUpperTriangular(Y);
1740:   }
1741:   return(0);
1742: }

1744: PetscErrorCode MatCreateSubMatrices_MPISBAIJ(Mat A,PetscInt n,const IS irow[],const IS icol[],MatReuse scall,Mat *B[])
1745: {
1747:   PetscInt       i;
1748:   PetscBool      flg;

1751:   MatCreateSubMatrices_MPIBAIJ(A,n,irow,icol,scall,B); /* B[] are sbaij matrices */
1752:   for (i=0; i<n; i++) {
1753:     ISEqual(irow[i],icol[i],&flg);
1754:     if (!flg) {
1755:       MatSeqSBAIJZeroOps_Private(*B[i]);
1756:     }
1757:   }
1758:   return(0);
1759: }

1761: PetscErrorCode MatShift_MPISBAIJ(Mat Y,PetscScalar a)
1762: {
1764:   Mat_MPISBAIJ    *maij = (Mat_MPISBAIJ*)Y->data;
1765:   Mat_SeqSBAIJ    *aij = (Mat_SeqSBAIJ*)maij->A->data;

1768:   if (!Y->preallocated) {
1769:     MatMPISBAIJSetPreallocation(Y,Y->rmap->bs,1,NULL,0,NULL);
1770:   } else if (!aij->nz) {
1771:     PetscInt nonew = aij->nonew;
1772:     MatSeqSBAIJSetPreallocation(maij->A,Y->rmap->bs,1,NULL);
1773:     aij->nonew = nonew;
1774:   }
1775:   MatShift_Basic(Y,a);
1776:   return(0);
1777: }

1779: PetscErrorCode MatMissingDiagonal_MPISBAIJ(Mat A,PetscBool  *missing,PetscInt *d)
1780: {
1781:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;

1785:   if (A->rmap->n != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only works for square matrices");
1786:   MatMissingDiagonal(a->A,missing,d);
1787:   if (d) {
1788:     PetscInt rstart;
1789:     MatGetOwnershipRange(A,&rstart,NULL);
1790:     *d += rstart/A->rmap->bs;

1792:   }
1793:   return(0);
1794: }

1796: PetscErrorCode  MatGetDiagonalBlock_MPISBAIJ(Mat A,Mat *a)
1797: {
1799:   *a = ((Mat_MPISBAIJ*)A->data)->A;
1800:   return(0);
1801: }

1803: /* -------------------------------------------------------------------*/
1804: static struct _MatOps MatOps_Values = {MatSetValues_MPISBAIJ,
1805:                                        MatGetRow_MPISBAIJ,
1806:                                        MatRestoreRow_MPISBAIJ,
1807:                                        MatMult_MPISBAIJ,
1808:                                /*  4*/ MatMultAdd_MPISBAIJ,
1809:                                        MatMult_MPISBAIJ,       /* transpose versions are same as non-transpose */
1810:                                        MatMultAdd_MPISBAIJ,
1811:                                        NULL,
1812:                                        NULL,
1813:                                        NULL,
1814:                                /* 10*/ NULL,
1815:                                        NULL,
1816:                                        NULL,
1817:                                        MatSOR_MPISBAIJ,
1818:                                        MatTranspose_MPISBAIJ,
1819:                                /* 15*/ MatGetInfo_MPISBAIJ,
1820:                                        MatEqual_MPISBAIJ,
1821:                                        MatGetDiagonal_MPISBAIJ,
1822:                                        MatDiagonalScale_MPISBAIJ,
1823:                                        MatNorm_MPISBAIJ,
1824:                                /* 20*/ MatAssemblyBegin_MPISBAIJ,
1825:                                        MatAssemblyEnd_MPISBAIJ,
1826:                                        MatSetOption_MPISBAIJ,
1827:                                        MatZeroEntries_MPISBAIJ,
1828:                                /* 24*/ NULL,
1829:                                        NULL,
1830:                                        NULL,
1831:                                        NULL,
1832:                                        NULL,
1833:                                /* 29*/ MatSetUp_MPISBAIJ,
1834:                                        NULL,
1835:                                        NULL,
1836:                                        MatGetDiagonalBlock_MPISBAIJ,
1837:                                        NULL,
1838:                                /* 34*/ MatDuplicate_MPISBAIJ,
1839:                                        NULL,
1840:                                        NULL,
1841:                                        NULL,
1842:                                        NULL,
1843:                                /* 39*/ MatAXPY_MPISBAIJ,
1844:                                        MatCreateSubMatrices_MPISBAIJ,
1845:                                        MatIncreaseOverlap_MPISBAIJ,
1846:                                        MatGetValues_MPISBAIJ,
1847:                                        MatCopy_MPISBAIJ,
1848:                                /* 44*/ NULL,
1849:                                        MatScale_MPISBAIJ,
1850:                                        MatShift_MPISBAIJ,
1851:                                        NULL,
1852:                                        NULL,
1853:                                /* 49*/ NULL,
1854:                                        NULL,
1855:                                        NULL,
1856:                                        NULL,
1857:                                        NULL,
1858:                                /* 54*/ NULL,
1859:                                        NULL,
1860:                                        MatSetUnfactored_MPISBAIJ,
1861:                                        NULL,
1862:                                        MatSetValuesBlocked_MPISBAIJ,
1863:                                /* 59*/ MatCreateSubMatrix_MPISBAIJ,
1864:                                        NULL,
1865:                                        NULL,
1866:                                        NULL,
1867:                                        NULL,
1868:                                /* 64*/ NULL,
1869:                                        NULL,
1870:                                        NULL,
1871:                                        NULL,
1872:                                        NULL,
1873:                                /* 69*/ MatGetRowMaxAbs_MPISBAIJ,
1874:                                        NULL,
1875:                                        MatConvert_MPISBAIJ_Basic,
1876:                                        NULL,
1877:                                        NULL,
1878:                                /* 74*/ NULL,
1879:                                        NULL,
1880:                                        NULL,
1881:                                        NULL,
1882:                                        NULL,
1883:                                /* 79*/ NULL,
1884:                                        NULL,
1885:                                        NULL,
1886:                                        NULL,
1887:                                        MatLoad_MPISBAIJ,
1888:                                /* 84*/ NULL,
1889:                                        NULL,
1890:                                        NULL,
1891:                                        NULL,
1892:                                        NULL,
1893:                                /* 89*/ NULL,
1894:                                        NULL,
1895:                                        NULL,
1896:                                        NULL,
1897:                                        NULL,
1898:                                /* 94*/ NULL,
1899:                                        NULL,
1900:                                        NULL,
1901:                                        NULL,
1902:                                        NULL,
1903:                                /* 99*/ NULL,
1904:                                        NULL,
1905:                                        NULL,
1906:                                        MatConjugate_MPISBAIJ,
1907:                                        NULL,
1908:                                /*104*/ NULL,
1909:                                        MatRealPart_MPISBAIJ,
1910:                                        MatImaginaryPart_MPISBAIJ,
1911:                                        MatGetRowUpperTriangular_MPISBAIJ,
1912:                                        MatRestoreRowUpperTriangular_MPISBAIJ,
1913:                                /*109*/ NULL,
1914:                                        NULL,
1915:                                        NULL,
1916:                                        NULL,
1917:                                        MatMissingDiagonal_MPISBAIJ,
1918:                                /*114*/ NULL,
1919:                                        NULL,
1920:                                        NULL,
1921:                                        NULL,
1922:                                        NULL,
1923:                                /*119*/ NULL,
1924:                                        NULL,
1925:                                        NULL,
1926:                                        NULL,
1927:                                        NULL,
1928:                                /*124*/ NULL,
1929:                                        NULL,
1930:                                        NULL,
1931:                                        NULL,
1932:                                        NULL,
1933:                                /*129*/ NULL,
1934:                                        NULL,
1935:                                        NULL,
1936:                                        NULL,
1937:                                        NULL,
1938:                                /*134*/ NULL,
1939:                                        NULL,
1940:                                        NULL,
1941:                                        NULL,
1942:                                        NULL,
1943:                                /*139*/ MatSetBlockSizes_Default,
1944:                                        NULL,
1945:                                        NULL,
1946:                                        NULL,
1947:                                        NULL,
1948:                                 /*144*/MatCreateMPIMatConcatenateSeqMat_MPISBAIJ
1949: };

1951: PetscErrorCode  MatMPISBAIJSetPreallocation_MPISBAIJ(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt *d_nnz,PetscInt o_nz,const PetscInt *o_nnz)
1952: {
1953:   Mat_MPISBAIJ   *b = (Mat_MPISBAIJ*)B->data;
1955:   PetscInt       i,mbs,Mbs;
1956:   PetscMPIInt    size;

1959:   MatSetBlockSize(B,PetscAbs(bs));
1960:   PetscLayoutSetUp(B->rmap);
1961:   PetscLayoutSetUp(B->cmap);
1962:   PetscLayoutGetBlockSize(B->rmap,&bs);
1963:   if (B->rmap->N > B->cmap->N) SETERRQ2(PetscObjectComm((PetscObject)B),PETSC_ERR_SUP,"MPISBAIJ matrix cannot have more rows %D than columns %D",B->rmap->N,B->cmap->N);
1964:   if (B->rmap->n > B->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_SUP,"MPISBAIJ matrix cannot have more local rows %D than columns %D",B->rmap->n,B->cmap->n);

1966:   mbs = B->rmap->n/bs;
1967:   Mbs = B->rmap->N/bs;
1968:   if (mbs*bs != B->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"No of local rows %D must be divisible by blocksize %D",B->rmap->N,bs);

1970:   B->rmap->bs = bs;
1971:   b->bs2      = bs*bs;
1972:   b->mbs      = mbs;
1973:   b->Mbs      = Mbs;
1974:   b->nbs      = B->cmap->n/bs;
1975:   b->Nbs      = B->cmap->N/bs;

1977:   for (i=0; i<=b->size; i++) {
1978:     b->rangebs[i] = B->rmap->range[i]/bs;
1979:   }
1980:   b->rstartbs = B->rmap->rstart/bs;
1981:   b->rendbs   = B->rmap->rend/bs;

1983:   b->cstartbs = B->cmap->rstart/bs;
1984:   b->cendbs   = B->cmap->rend/bs;

1986: #if defined(PETSC_USE_CTABLE)
1987:   PetscTableDestroy(&b->colmap);
1988: #else
1989:   PetscFree(b->colmap);
1990: #endif
1991:   PetscFree(b->garray);
1992:   VecDestroy(&b->lvec);
1993:   VecScatterDestroy(&b->Mvctx);
1994:   VecDestroy(&b->slvec0);
1995:   VecDestroy(&b->slvec0b);
1996:   VecDestroy(&b->slvec1);
1997:   VecDestroy(&b->slvec1a);
1998:   VecDestroy(&b->slvec1b);
1999:   VecScatterDestroy(&b->sMvctx);

2001:   /* Because the B will have been resized we simply destroy it and create a new one each time */
2002:   MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);
2003:   MatDestroy(&b->B);
2004:   MatCreate(PETSC_COMM_SELF,&b->B);
2005:   MatSetSizes(b->B,B->rmap->n,size > 1 ? B->cmap->N : 0,B->rmap->n,size > 1 ? B->cmap->N : 0);
2006:   MatSetType(b->B,MATSEQBAIJ);
2007:   PetscLogObjectParent((PetscObject)B,(PetscObject)b->B);

2009:   if (!B->preallocated) {
2010:     MatCreate(PETSC_COMM_SELF,&b->A);
2011:     MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);
2012:     MatSetType(b->A,MATSEQSBAIJ);
2013:     PetscLogObjectParent((PetscObject)B,(PetscObject)b->A);
2014:     MatStashCreate_Private(PetscObjectComm((PetscObject)B),bs,&B->bstash);
2015:   }

2017:   MatSeqSBAIJSetPreallocation(b->A,bs,d_nz,d_nnz);
2018:   MatSeqBAIJSetPreallocation(b->B,bs,o_nz,o_nnz);

2020:   B->preallocated  = PETSC_TRUE;
2021:   B->was_assembled = PETSC_FALSE;
2022:   B->assembled     = PETSC_FALSE;
2023:   return(0);
2024: }

2026: PetscErrorCode MatMPISBAIJSetPreallocationCSR_MPISBAIJ(Mat B,PetscInt bs,const PetscInt ii[],const PetscInt jj[],const PetscScalar V[])
2027: {
2028:   PetscInt       m,rstart,cend;
2029:   PetscInt       i,j,d,nz,bd, nz_max=0,*d_nnz=NULL,*o_nnz=NULL;
2030:   const PetscInt *JJ    =NULL;
2031:   PetscScalar    *values=NULL;
2032:   PetscBool      roworiented = ((Mat_MPISBAIJ*)B->data)->roworiented;
2034:   PetscBool      nooffprocentries;

2037:   if (bs < 1) SETERRQ1(PetscObjectComm((PetscObject)B),PETSC_ERR_ARG_OUTOFRANGE,"Invalid block size specified, must be positive but it is %D",bs);
2038:   PetscLayoutSetBlockSize(B->rmap,bs);
2039:   PetscLayoutSetBlockSize(B->cmap,bs);
2040:   PetscLayoutSetUp(B->rmap);
2041:   PetscLayoutSetUp(B->cmap);
2042:   PetscLayoutGetBlockSize(B->rmap,&bs);
2043:   m      = B->rmap->n/bs;
2044:   rstart = B->rmap->rstart/bs;
2045:   cend   = B->cmap->rend/bs;

2047:   if (ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"ii[0] must be 0 but it is %D",ii[0]);
2048:   PetscMalloc2(m,&d_nnz,m,&o_nnz);
2049:   for (i=0; i<m; i++) {
2050:     nz = ii[i+1] - ii[i];
2051:     if (nz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative number of columns %D",i,nz);
2052:     /* count the ones on the diagonal and above, split into diagonal and off diagonal portions. */
2053:     JJ     = jj + ii[i];
2054:     bd     = 0;
2055:     for (j=0; j<nz; j++) {
2056:       if (*JJ >= i + rstart) break;
2057:       JJ++;
2058:       bd++;
2059:     }
2060:     d  = 0;
2061:     for (; j<nz; j++) {
2062:       if (*JJ++ >= cend) break;
2063:       d++;
2064:     }
2065:     d_nnz[i] = d;
2066:     o_nnz[i] = nz - d - bd;
2067:     nz       = nz - bd;
2068:     nz_max = PetscMax(nz_max,nz);
2069:   }
2070:   MatMPISBAIJSetPreallocation(B,bs,0,d_nnz,0,o_nnz);
2071:   MatSetOption(B,MAT_IGNORE_LOWER_TRIANGULAR,PETSC_TRUE);
2072:   PetscFree2(d_nnz,o_nnz);

2074:   values = (PetscScalar*)V;
2075:   if (!values) {
2076:     PetscCalloc1(bs*bs*nz_max,&values);
2077:   }
2078:   for (i=0; i<m; i++) {
2079:     PetscInt          row    = i + rstart;
2080:     PetscInt          ncols  = ii[i+1] - ii[i];
2081:     const PetscInt    *icols = jj + ii[i];
2082:     if (bs == 1 || !roworiented) {         /* block ordering matches the non-nested layout of MatSetValues so we can insert entire rows */
2083:       const PetscScalar *svals = values + (V ? (bs*bs*ii[i]) : 0);
2084:       MatSetValuesBlocked_MPISBAIJ(B,1,&row,ncols,icols,svals,INSERT_VALUES);
2085:     } else {                    /* block ordering does not match so we can only insert one block at a time. */
2086:       PetscInt j;
2087:       for (j=0; j<ncols; j++) {
2088:         const PetscScalar *svals = values + (V ? (bs*bs*(ii[i]+j)) : 0);
2089:         MatSetValuesBlocked_MPISBAIJ(B,1,&row,1,&icols[j],svals,INSERT_VALUES);
2090:       }
2091:     }
2092:   }

2094:   if (!V) { PetscFree(values); }
2095:   nooffprocentries    = B->nooffprocentries;
2096:   B->nooffprocentries = PETSC_TRUE;
2097:   MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
2098:   MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);
2099:   B->nooffprocentries = nooffprocentries;

2101:   MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);
2102:   return(0);
2103: }

2105: /*MC
2106:    MATMPISBAIJ - MATMPISBAIJ = "mpisbaij" - A matrix type to be used for distributed symmetric sparse block matrices,
2107:    based on block compressed sparse row format.  Only the upper triangular portion of the "diagonal" portion of
2108:    the matrix is stored.

2110:    For complex numbers by default this matrix is symmetric, NOT Hermitian symmetric. To make it Hermitian symmetric you
2111:    can call MatSetOption(Mat, MAT_HERMITIAN);

2113:    Options Database Keys:
2114: . -mat_type mpisbaij - sets the matrix type to "mpisbaij" during a call to MatSetFromOptions()

2116:    Notes:
2117:      The number of rows in the matrix must be less than or equal to the number of columns. Similarly the number of rows in the
2118:      diagonal portion of the matrix of each process has to less than or equal the number of columns.

2120:    Level: beginner

2122: .seealso: MatCreateBAIJ(), MATSEQSBAIJ, MatType
2123: M*/

2125: PETSC_EXTERN PetscErrorCode MatCreate_MPISBAIJ(Mat B)
2126: {
2127:   Mat_MPISBAIJ   *b;
2129:   PetscBool      flg = PETSC_FALSE;

2132:   PetscNewLog(B,&b);
2133:   B->data = (void*)b;
2134:   PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));

2136:   B->ops->destroy = MatDestroy_MPISBAIJ;
2137:   B->ops->view    = MatView_MPISBAIJ;
2138:   B->assembled    = PETSC_FALSE;
2139:   B->insertmode   = NOT_SET_VALUES;

2141:   MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);
2142:   MPI_Comm_size(PetscObjectComm((PetscObject)B),&b->size);

2144:   /* build local table of row and column ownerships */
2145:   PetscMalloc1(b->size+2,&b->rangebs);

2147:   /* build cache for off array entries formed */
2148:   MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);

2150:   b->donotstash  = PETSC_FALSE;
2151:   b->colmap      = NULL;
2152:   b->garray      = NULL;
2153:   b->roworiented = PETSC_TRUE;

2155:   /* stuff used in block assembly */
2156:   b->barray = NULL;

2158:   /* stuff used for matrix vector multiply */
2159:   b->lvec    = NULL;
2160:   b->Mvctx   = NULL;
2161:   b->slvec0  = NULL;
2162:   b->slvec0b = NULL;
2163:   b->slvec1  = NULL;
2164:   b->slvec1a = NULL;
2165:   b->slvec1b = NULL;
2166:   b->sMvctx  = NULL;

2168:   /* stuff for MatGetRow() */
2169:   b->rowindices   = NULL;
2170:   b->rowvalues    = NULL;
2171:   b->getrowactive = PETSC_FALSE;

2173:   /* hash table stuff */
2174:   b->ht           = NULL;
2175:   b->hd           = NULL;
2176:   b->ht_size      = 0;
2177:   b->ht_flag      = PETSC_FALSE;
2178:   b->ht_fact      = 0;
2179:   b->ht_total_ct  = 0;
2180:   b->ht_insert_ct = 0;

2182:   /* stuff for MatCreateSubMatrices_MPIBAIJ_local() */
2183:   b->ijonly = PETSC_FALSE;

2185:   b->in_loc = NULL;
2186:   b->v_loc  = NULL;
2187:   b->n_loc  = 0;

2189:   PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPISBAIJ);
2190:   PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPISBAIJ);
2191:   PetscObjectComposeFunction((PetscObject)B,"MatMPISBAIJSetPreallocation_C",MatMPISBAIJSetPreallocation_MPISBAIJ);
2192:   PetscObjectComposeFunction((PetscObject)B,"MatMPISBAIJSetPreallocationCSR_C",MatMPISBAIJSetPreallocationCSR_MPISBAIJ);
2193: #if defined(PETSC_HAVE_ELEMENTAL)
2194:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpisbaij_elemental_C",MatConvert_MPISBAIJ_Elemental);
2195: #endif
2196: #if defined(PETSC_HAVE_SCALAPACK)
2197:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpisbaij_scalapack_C",MatConvert_SBAIJ_ScaLAPACK);
2198: #endif
2199:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpisbaij_mpiaij_C",MatConvert_MPISBAIJ_Basic);
2200:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpisbaij_mpibaij_C",MatConvert_MPISBAIJ_Basic);

2202:   B->symmetric                  = PETSC_TRUE;
2203:   B->structurally_symmetric     = PETSC_TRUE;
2204:   B->symmetric_set              = PETSC_TRUE;
2205:   B->structurally_symmetric_set = PETSC_TRUE;
2206:   B->symmetric_eternal          = PETSC_TRUE;
2207: #if defined(PETSC_USE_COMPLEX)
2208:   B->hermitian                  = PETSC_FALSE;
2209:   B->hermitian_set              = PETSC_FALSE;
2210: #else
2211:   B->hermitian                  = PETSC_TRUE;
2212:   B->hermitian_set              = PETSC_TRUE;
2213: #endif

2215:   PetscObjectChangeTypeName((PetscObject)B,MATMPISBAIJ);
2216:   PetscOptionsBegin(PetscObjectComm((PetscObject)B),NULL,"Options for loading MPISBAIJ matrix 1","Mat");
2217:   PetscOptionsBool("-mat_use_hash_table","Use hash table to save memory in constructing matrix","MatSetOption",flg,&flg,NULL);
2218:   if (flg) {
2219:     PetscReal fact = 1.39;
2220:     MatSetOption(B,MAT_USE_HASH_TABLE,PETSC_TRUE);
2221:     PetscOptionsReal("-mat_use_hash_table","Use hash table factor","MatMPIBAIJSetHashTableFactor",fact,&fact,NULL);
2222:     if (fact <= 1.0) fact = 1.39;
2223:     MatMPIBAIJSetHashTableFactor(B,fact);
2224:     PetscInfo1(B,"Hash table Factor used %5.2f\n",fact);
2225:   }
2226:   PetscOptionsEnd();
2227:   return(0);
2228: }

2230: /*MC
2231:    MATSBAIJ - MATSBAIJ = "sbaij" - A matrix type to be used for symmetric block sparse matrices.

2233:    This matrix type is identical to MATSEQSBAIJ when constructed with a single process communicator,
2234:    and MATMPISBAIJ otherwise.

2236:    Options Database Keys:
2237: . -mat_type sbaij - sets the matrix type to "sbaij" during a call to MatSetFromOptions()

2239:   Level: beginner

2241: .seealso: MatCreateMPISBAIJ, MATSEQSBAIJ, MATMPISBAIJ
2242: M*/

2244: /*@C
2245:    MatMPISBAIJSetPreallocation - For good matrix assembly performance
2246:    the user should preallocate the matrix storage by setting the parameters
2247:    d_nz (or d_nnz) and o_nz (or o_nnz).  By setting these parameters accurately,
2248:    performance can be increased by more than a factor of 50.

2250:    Collective on Mat

2252:    Input Parameters:
2253: +  B - the matrix
2254: .  bs   - size of block, the blocks are ALWAYS square. One can use MatSetBlockSizes() to set a different row and column blocksize but the row
2255:           blocksize always defines the size of the blocks. The column blocksize sets the blocksize of the vectors obtained with MatCreateVecs()
2256: .  d_nz  - number of block nonzeros per block row in diagonal portion of local
2257:            submatrix  (same for all local rows)
2258: .  d_nnz - array containing the number of block nonzeros in the various block rows
2259:            in the upper triangular and diagonal part of the in diagonal portion of the local
2260:            (possibly different for each block row) or NULL.  If you plan to factor the matrix you must leave room
2261:            for the diagonal entry and set a value even if it is zero.
2262: .  o_nz  - number of block nonzeros per block row in the off-diagonal portion of local
2263:            submatrix (same for all local rows).
2264: -  o_nnz - array containing the number of nonzeros in the various block rows of the
2265:            off-diagonal portion of the local submatrix that is right of the diagonal
2266:            (possibly different for each block row) or NULL.


2269:    Options Database Keys:
2270: +   -mat_no_unroll - uses code that does not unroll the loops in the
2271:                      block calculations (much slower)
2272: -   -mat_block_size - size of the blocks to use

2274:    Notes:

2276:    If PETSC_DECIDE or  PETSC_DETERMINE is used for a particular argument on one processor
2277:    than it must be used on all processors that share the object for that argument.

2279:    If the *_nnz parameter is given then the *_nz parameter is ignored

2281:    Storage Information:
2282:    For a square global matrix we define each processor's diagonal portion
2283:    to be its local rows and the corresponding columns (a square submatrix);
2284:    each processor's off-diagonal portion encompasses the remainder of the
2285:    local matrix (a rectangular submatrix).

2287:    The user can specify preallocated storage for the diagonal part of
2288:    the local submatrix with either d_nz or d_nnz (not both).  Set
2289:    d_nz=PETSC_DEFAULT and d_nnz=NULL for PETSc to control dynamic
2290:    memory allocation.  Likewise, specify preallocated storage for the
2291:    off-diagonal part of the local submatrix with o_nz or o_nnz (not both).

2293:    You can call MatGetInfo() to get information on how effective the preallocation was;
2294:    for example the fields mallocs,nz_allocated,nz_used,nz_unneeded;
2295:    You can also run with the option -info and look for messages with the string
2296:    malloc in them to see if additional memory allocation was needed.

2298:    Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In
2299:    the figure below we depict these three local rows and all columns (0-11).

2301: .vb
2302:            0 1 2 3 4 5 6 7 8 9 10 11
2303:           --------------------------
2304:    row 3  |. . . d d d o o o o  o  o
2305:    row 4  |. . . d d d o o o o  o  o
2306:    row 5  |. . . d d d o o o o  o  o
2307:           --------------------------
2308: .ve

2310:    Thus, any entries in the d locations are stored in the d (diagonal)
2311:    submatrix, and any entries in the o locations are stored in the
2312:    o (off-diagonal) submatrix.  Note that the d matrix is stored in
2313:    MatSeqSBAIJ format and the o submatrix in MATSEQBAIJ format.

2315:    Now d_nz should indicate the number of block nonzeros per row in the upper triangular
2316:    plus the diagonal part of the d matrix,
2317:    and o_nz should indicate the number of block nonzeros per row in the o matrix

2319:    In general, for PDE problems in which most nonzeros are near the diagonal,
2320:    one expects d_nz >> o_nz.   For large problems you MUST preallocate memory
2321:    or you will get TERRIBLE performance; see the users' manual chapter on
2322:    matrices.

2324:    Level: intermediate

2326: .seealso: MatCreate(), MatCreateSeqSBAIJ(), MatSetValues(), MatCreateBAIJ(), PetscSplitOwnership()
2327: @*/
2328: PetscErrorCode  MatMPISBAIJSetPreallocation(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[])
2329: {

2336:   PetscTryMethod(B,"MatMPISBAIJSetPreallocation_C",(Mat,PetscInt,PetscInt,const PetscInt[],PetscInt,const PetscInt[]),(B,bs,d_nz,d_nnz,o_nz,o_nnz));
2337:   return(0);
2338: }

2340: /*@C
2341:    MatCreateSBAIJ - Creates a sparse parallel matrix in symmetric block AIJ format
2342:    (block compressed row).  For good matrix assembly performance
2343:    the user should preallocate the matrix storage by setting the parameters
2344:    d_nz (or d_nnz) and o_nz (or o_nnz).  By setting these parameters accurately,
2345:    performance can be increased by more than a factor of 50.

2347:    Collective

2349:    Input Parameters:
2350: +  comm - MPI communicator
2351: .  bs   - size of block, the blocks are ALWAYS square. One can use MatSetBlockSizes() to set a different row and column blocksize but the row
2352:           blocksize always defines the size of the blocks. The column blocksize sets the blocksize of the vectors obtained with MatCreateVecs()
2353: .  m - number of local rows (or PETSC_DECIDE to have calculated if M is given)
2354:            This value should be the same as the local size used in creating the
2355:            y vector for the matrix-vector product y = Ax.
2356: .  n - number of local columns (or PETSC_DECIDE to have calculated if N is given)
2357:            This value should be the same as the local size used in creating the
2358:            x vector for the matrix-vector product y = Ax.
2359: .  M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
2360: .  N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
2361: .  d_nz  - number of block nonzeros per block row in diagonal portion of local
2362:            submatrix  (same for all local rows)
2363: .  d_nnz - array containing the number of block nonzeros in the various block rows
2364:            in the upper triangular portion of the in diagonal portion of the local
2365:            (possibly different for each block block row) or NULL.
2366:            If you plan to factor the matrix you must leave room for the diagonal entry and
2367:            set its value even if it is zero.
2368: .  o_nz  - number of block nonzeros per block row in the off-diagonal portion of local
2369:            submatrix (same for all local rows).
2370: -  o_nnz - array containing the number of nonzeros in the various block rows of the
2371:            off-diagonal portion of the local submatrix (possibly different for
2372:            each block row) or NULL.

2374:    Output Parameter:
2375: .  A - the matrix

2377:    Options Database Keys:
2378: +   -mat_no_unroll - uses code that does not unroll the loops in the
2379:                      block calculations (much slower)
2380: .   -mat_block_size - size of the blocks to use
2381: -   -mat_mpi - use the parallel matrix data structures even on one processor
2382:                (defaults to using SeqBAIJ format on one processor)

2384:    It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(),
2385:    MatXXXXSetPreallocation() paradigm instead of this routine directly.
2386:    [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation]

2388:    Notes:
2389:    The number of rows and columns must be divisible by blocksize.
2390:    This matrix type does not support complex Hermitian operation.

2392:    The user MUST specify either the local or global matrix dimensions
2393:    (possibly both).

2395:    If PETSC_DECIDE or  PETSC_DETERMINE is used for a particular argument on one processor
2396:    than it must be used on all processors that share the object for that argument.

2398:    If the *_nnz parameter is given then the *_nz parameter is ignored

2400:    Storage Information:
2401:    For a square global matrix we define each processor's diagonal portion
2402:    to be its local rows and the corresponding columns (a square submatrix);
2403:    each processor's off-diagonal portion encompasses the remainder of the
2404:    local matrix (a rectangular submatrix).

2406:    The user can specify preallocated storage for the diagonal part of
2407:    the local submatrix with either d_nz or d_nnz (not both).  Set
2408:    d_nz=PETSC_DEFAULT and d_nnz=NULL for PETSc to control dynamic
2409:    memory allocation.  Likewise, specify preallocated storage for the
2410:    off-diagonal part of the local submatrix with o_nz or o_nnz (not both).

2412:    Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In
2413:    the figure below we depict these three local rows and all columns (0-11).

2415: .vb
2416:            0 1 2 3 4 5 6 7 8 9 10 11
2417:           --------------------------
2418:    row 3  |. . . d d d o o o o  o  o
2419:    row 4  |. . . d d d o o o o  o  o
2420:    row 5  |. . . d d d o o o o  o  o
2421:           --------------------------
2422: .ve

2424:    Thus, any entries in the d locations are stored in the d (diagonal)
2425:    submatrix, and any entries in the o locations are stored in the
2426:    o (off-diagonal) submatrix.  Note that the d matrix is stored in
2427:    MatSeqSBAIJ format and the o submatrix in MATSEQBAIJ format.

2429:    Now d_nz should indicate the number of block nonzeros per row in the upper triangular
2430:    plus the diagonal part of the d matrix,
2431:    and o_nz should indicate the number of block nonzeros per row in the o matrix.
2432:    In general, for PDE problems in which most nonzeros are near the diagonal,
2433:    one expects d_nz >> o_nz.   For large problems you MUST preallocate memory
2434:    or you will get TERRIBLE performance; see the users' manual chapter on
2435:    matrices.

2437:    Level: intermediate

2439: .seealso: MatCreate(), MatCreateSeqSBAIJ(), MatSetValues(), MatCreateBAIJ()
2440: @*/

2442: PetscErrorCode  MatCreateSBAIJ(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)
2443: {
2445:   PetscMPIInt    size;

2448:   MatCreate(comm,A);
2449:   MatSetSizes(*A,m,n,M,N);
2450:   MPI_Comm_size(comm,&size);
2451:   if (size > 1) {
2452:     MatSetType(*A,MATMPISBAIJ);
2453:     MatMPISBAIJSetPreallocation(*A,bs,d_nz,d_nnz,o_nz,o_nnz);
2454:   } else {
2455:     MatSetType(*A,MATSEQSBAIJ);
2456:     MatSeqSBAIJSetPreallocation(*A,bs,d_nz,d_nnz);
2457:   }
2458:   return(0);
2459: }


2462: static PetscErrorCode MatDuplicate_MPISBAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat)
2463: {
2464:   Mat            mat;
2465:   Mat_MPISBAIJ   *a,*oldmat = (Mat_MPISBAIJ*)matin->data;
2467:   PetscInt       len=0,nt,bs=matin->rmap->bs,mbs=oldmat->mbs;
2468:   PetscScalar    *array;

2471:   *newmat = NULL;

2473:   MatCreate(PetscObjectComm((PetscObject)matin),&mat);
2474:   MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);
2475:   MatSetType(mat,((PetscObject)matin)->type_name);
2476:   PetscLayoutReference(matin->rmap,&mat->rmap);
2477:   PetscLayoutReference(matin->cmap,&mat->cmap);

2479:   mat->factortype   = matin->factortype;
2480:   mat->preallocated = PETSC_TRUE;
2481:   mat->assembled    = PETSC_TRUE;
2482:   mat->insertmode   = NOT_SET_VALUES;

2484:   a      = (Mat_MPISBAIJ*)mat->data;
2485:   a->bs2 = oldmat->bs2;
2486:   a->mbs = oldmat->mbs;
2487:   a->nbs = oldmat->nbs;
2488:   a->Mbs = oldmat->Mbs;
2489:   a->Nbs = oldmat->Nbs;

2491:   a->size         = oldmat->size;
2492:   a->rank         = oldmat->rank;
2493:   a->donotstash   = oldmat->donotstash;
2494:   a->roworiented  = oldmat->roworiented;
2495:   a->rowindices   = NULL;
2496:   a->rowvalues    = NULL;
2497:   a->getrowactive = PETSC_FALSE;
2498:   a->barray       = NULL;
2499:   a->rstartbs     = oldmat->rstartbs;
2500:   a->rendbs       = oldmat->rendbs;
2501:   a->cstartbs     = oldmat->cstartbs;
2502:   a->cendbs       = oldmat->cendbs;

2504:   /* hash table stuff */
2505:   a->ht           = NULL;
2506:   a->hd           = NULL;
2507:   a->ht_size      = 0;
2508:   a->ht_flag      = oldmat->ht_flag;
2509:   a->ht_fact      = oldmat->ht_fact;
2510:   a->ht_total_ct  = 0;
2511:   a->ht_insert_ct = 0;

2513:   PetscArraycpy(a->rangebs,oldmat->rangebs,a->size+2);
2514:   if (oldmat->colmap) {
2515: #if defined(PETSC_USE_CTABLE)
2516:     PetscTableCreateCopy(oldmat->colmap,&a->colmap);
2517: #else
2518:     PetscMalloc1(a->Nbs,&a->colmap);
2519:     PetscLogObjectMemory((PetscObject)mat,(a->Nbs)*sizeof(PetscInt));
2520:     PetscArraycpy(a->colmap,oldmat->colmap,a->Nbs);
2521: #endif
2522:   } else a->colmap = NULL;

2524:   if (oldmat->garray && (len = ((Mat_SeqBAIJ*)(oldmat->B->data))->nbs)) {
2525:     PetscMalloc1(len,&a->garray);
2526:     PetscLogObjectMemory((PetscObject)mat,len*sizeof(PetscInt));
2527:     PetscArraycpy(a->garray,oldmat->garray,len);
2528:   } else a->garray = NULL;

2530:   MatStashCreate_Private(PetscObjectComm((PetscObject)matin),matin->rmap->bs,&mat->bstash);
2531:   VecDuplicate(oldmat->lvec,&a->lvec);
2532:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->lvec);
2533:   VecScatterCopy(oldmat->Mvctx,&a->Mvctx);
2534:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->Mvctx);

2536:   VecDuplicate(oldmat->slvec0,&a->slvec0);
2537:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec0);
2538:   VecDuplicate(oldmat->slvec1,&a->slvec1);
2539:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec1);

2541:   VecGetLocalSize(a->slvec1,&nt);
2542:   VecGetArray(a->slvec1,&array);
2543:   VecCreateSeqWithArray(PETSC_COMM_SELF,1,bs*mbs,array,&a->slvec1a);
2544:   VecCreateSeqWithArray(PETSC_COMM_SELF,1,nt-bs*mbs,array+bs*mbs,&a->slvec1b);
2545:   VecRestoreArray(a->slvec1,&array);
2546:   VecGetArray(a->slvec0,&array);
2547:   VecCreateSeqWithArray(PETSC_COMM_SELF,1,nt-bs*mbs,array+bs*mbs,&a->slvec0b);
2548:   VecRestoreArray(a->slvec0,&array);
2549:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec0);
2550:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec1);
2551:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec0b);
2552:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec1a);
2553:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec1b);

2555:   /*  VecScatterCopy(oldmat->sMvctx,&a->sMvctx); - not written yet, replaced by the lazy trick: */
2556:   PetscObjectReference((PetscObject)oldmat->sMvctx);
2557:   a->sMvctx = oldmat->sMvctx;
2558:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->sMvctx);

2560:   MatDuplicate(oldmat->A,cpvalues,&a->A);
2561:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->A);
2562:   MatDuplicate(oldmat->B,cpvalues,&a->B);
2563:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->B);
2564:   PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);
2565:   *newmat = mat;
2566:   return(0);
2567: }

2569: /* Used for both MPIBAIJ and MPISBAIJ matrices */
2570: #define MatLoad_MPISBAIJ_Binary MatLoad_MPIBAIJ_Binary

2572: PetscErrorCode MatLoad_MPISBAIJ(Mat mat,PetscViewer viewer)
2573: {
2575:   PetscBool      isbinary;

2578:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);
2579:   if (!isbinary) SETERRQ2(PetscObjectComm((PetscObject)viewer),PETSC_ERR_SUP,"Viewer type %s not yet supported for reading %s matrices",((PetscObject)viewer)->type_name,((PetscObject)mat)->type_name);
2580:   MatLoad_MPISBAIJ_Binary(mat,viewer);
2581:   return(0);
2582: }

2584: /*XXXXX@
2585:    MatMPISBAIJSetHashTableFactor - Sets the factor required to compute the size of the HashTable.

2587:    Input Parameters:
2588: .  mat  - the matrix
2589: .  fact - factor

2591:    Not Collective on Mat, each process can have a different hash factor

2593:    Level: advanced

2595:   Notes:
2596:    This can also be set by the command line option: -mat_use_hash_table fact

2598: .seealso: MatSetOption()
2599: @XXXXX*/


2602: PetscErrorCode MatGetRowMaxAbs_MPISBAIJ(Mat A,Vec v,PetscInt idx[])
2603: {
2604:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;
2605:   Mat_SeqBAIJ    *b = (Mat_SeqBAIJ*)(a->B)->data;
2606:   PetscReal      atmp;
2607:   PetscReal      *work,*svalues,*rvalues;
2609:   PetscInt       i,bs,mbs,*bi,*bj,brow,j,ncols,krow,kcol,col,row,Mbs,bcol;
2610:   PetscMPIInt    rank,size;
2611:   PetscInt       *rowners_bs,dest,count,source;
2612:   PetscScalar    *va;
2613:   MatScalar      *ba;
2614:   MPI_Status     stat;

2617:   if (idx) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Send email to petsc-maint@mcs.anl.gov");
2618:   MatGetRowMaxAbs(a->A,v,NULL);
2619:   VecGetArray(v,&va);

2621:   MPI_Comm_size(PetscObjectComm((PetscObject)A),&size);
2622:   MPI_Comm_rank(PetscObjectComm((PetscObject)A),&rank);

2624:   bs  = A->rmap->bs;
2625:   mbs = a->mbs;
2626:   Mbs = a->Mbs;
2627:   ba  = b->a;
2628:   bi  = b->i;
2629:   bj  = b->j;

2631:   /* find ownerships */
2632:   rowners_bs = A->rmap->range;

2634:   /* each proc creates an array to be distributed */
2635:   PetscCalloc1(bs*Mbs,&work);

2637:   /* row_max for B */
2638:   if (rank != size-1) {
2639:     for (i=0; i<mbs; i++) {
2640:       ncols = bi[1] - bi[0]; bi++;
2641:       brow  = bs*i;
2642:       for (j=0; j<ncols; j++) {
2643:         bcol = bs*(*bj);
2644:         for (kcol=0; kcol<bs; kcol++) {
2645:           col  = bcol + kcol;                /* local col index */
2646:           col += rowners_bs[rank+1];      /* global col index */
2647:           for (krow=0; krow<bs; krow++) {
2648:             atmp = PetscAbsScalar(*ba); ba++;
2649:             row  = brow + krow;   /* local row index */
2650:             if (PetscRealPart(va[row]) < atmp) va[row] = atmp;
2651:             if (work[col] < atmp) work[col] = atmp;
2652:           }
2653:         }
2654:         bj++;
2655:       }
2656:     }

2658:     /* send values to its owners */
2659:     for (dest=rank+1; dest<size; dest++) {
2660:       svalues = work + rowners_bs[dest];
2661:       count   = rowners_bs[dest+1]-rowners_bs[dest];
2662:       MPI_Send(svalues,count,MPIU_REAL,dest,rank,PetscObjectComm((PetscObject)A));
2663:     }
2664:   }

2666:   /* receive values */
2667:   if (rank) {
2668:     rvalues = work;
2669:     count   = rowners_bs[rank+1]-rowners_bs[rank];
2670:     for (source=0; source<rank; source++) {
2671:       MPI_Recv(rvalues,count,MPIU_REAL,MPI_ANY_SOURCE,MPI_ANY_TAG,PetscObjectComm((PetscObject)A),&stat);
2672:       /* process values */
2673:       for (i=0; i<count; i++) {
2674:         if (PetscRealPart(va[i]) < rvalues[i]) va[i] = rvalues[i];
2675:       }
2676:     }
2677:   }

2679:   VecRestoreArray(v,&va);
2680:   PetscFree(work);
2681:   return(0);
2682: }

2684: PetscErrorCode MatSOR_MPISBAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx)
2685: {
2686:   Mat_MPISBAIJ      *mat = (Mat_MPISBAIJ*)matin->data;
2687:   PetscErrorCode    ierr;
2688:   PetscInt          mbs=mat->mbs,bs=matin->rmap->bs;
2689:   PetscScalar       *x,*ptr,*from;
2690:   Vec               bb1;
2691:   const PetscScalar *b;

2694:   if (its <= 0 || lits <= 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Relaxation requires global its %D and local its %D both positive",its,lits);
2695:   if (bs > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"SSOR for block size > 1 is not yet implemented");

2697:   if (flag == SOR_APPLY_UPPER) {
2698:     (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
2699:     return(0);
2700:   }

2702:   if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) {
2703:     if (flag & SOR_ZERO_INITIAL_GUESS) {
2704:       (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,lits,xx);
2705:       its--;
2706:     }

2708:     VecDuplicate(bb,&bb1);
2709:     while (its--) {

2711:       /* lower triangular part: slvec0b = - B^T*xx */
2712:       (*mat->B->ops->multtranspose)(mat->B,xx,mat->slvec0b);

2714:       /* copy xx into slvec0a */
2715:       VecGetArray(mat->slvec0,&ptr);
2716:       VecGetArray(xx,&x);
2717:       PetscArraycpy(ptr,x,bs*mbs);
2718:       VecRestoreArray(mat->slvec0,&ptr);

2720:       VecScale(mat->slvec0,-1.0);

2722:       /* copy bb into slvec1a */
2723:       VecGetArray(mat->slvec1,&ptr);
2724:       VecGetArrayRead(bb,&b);
2725:       PetscArraycpy(ptr,b,bs*mbs);
2726:       VecRestoreArray(mat->slvec1,&ptr);

2728:       /* set slvec1b = 0 */
2729:       VecSet(mat->slvec1b,0.0);

2731:       VecScatterBegin(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);
2732:       VecRestoreArray(xx,&x);
2733:       VecRestoreArrayRead(bb,&b);
2734:       VecScatterEnd(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);

2736:       /* upper triangular part: bb1 = bb1 - B*x */
2737:       (*mat->B->ops->multadd)(mat->B,mat->slvec1b,mat->slvec1a,bb1);

2739:       /* local diagonal sweep */
2740:       (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,lits,xx);
2741:     }
2742:     VecDestroy(&bb1);
2743:   } else if ((flag & SOR_LOCAL_FORWARD_SWEEP) && (its == 1) && (flag & SOR_ZERO_INITIAL_GUESS)) {
2744:     (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
2745:   } else if ((flag & SOR_LOCAL_BACKWARD_SWEEP) && (its == 1) && (flag & SOR_ZERO_INITIAL_GUESS)) {
2746:     (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
2747:   } else if (flag & SOR_EISENSTAT) {
2748:     Vec               xx1;
2749:     PetscBool         hasop;
2750:     const PetscScalar *diag;
2751:     PetscScalar       *sl,scale = (omega - 2.0)/omega;
2752:     PetscInt          i,n;

2754:     if (!mat->xx1) {
2755:       VecDuplicate(bb,&mat->xx1);
2756:       VecDuplicate(bb,&mat->bb1);
2757:     }
2758:     xx1 = mat->xx1;
2759:     bb1 = mat->bb1;

2761:     (*mat->A->ops->sor)(mat->A,bb,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_BACKWARD_SWEEP),fshift,lits,1,xx);

2763:     if (!mat->diag) {
2764:       /* this is wrong for same matrix with new nonzero values */
2765:       MatCreateVecs(matin,&mat->diag,NULL);
2766:       MatGetDiagonal(matin,mat->diag);
2767:     }
2768:     MatHasOperation(matin,MATOP_MULT_DIAGONAL_BLOCK,&hasop);

2770:     if (hasop) {
2771:       MatMultDiagonalBlock(matin,xx,bb1);
2772:       VecAYPX(mat->slvec1a,scale,bb);
2773:     } else {
2774:       /*
2775:           These two lines are replaced by code that may be a bit faster for a good compiler
2776:       VecPointwiseMult(mat->slvec1a,mat->diag,xx);
2777:       VecAYPX(mat->slvec1a,scale,bb);
2778:       */
2779:       VecGetArray(mat->slvec1a,&sl);
2780:       VecGetArrayRead(mat->diag,&diag);
2781:       VecGetArrayRead(bb,&b);
2782:       VecGetArray(xx,&x);
2783:       VecGetLocalSize(xx,&n);
2784:       if (omega == 1.0) {
2785:         for (i=0; i<n; i++) sl[i] = b[i] - diag[i]*x[i];
2786:         PetscLogFlops(2.0*n);
2787:       } else {
2788:         for (i=0; i<n; i++) sl[i] = b[i] + scale*diag[i]*x[i];
2789:         PetscLogFlops(3.0*n);
2790:       }
2791:       VecRestoreArray(mat->slvec1a,&sl);
2792:       VecRestoreArrayRead(mat->diag,&diag);
2793:       VecRestoreArrayRead(bb,&b);
2794:       VecRestoreArray(xx,&x);
2795:     }

2797:     /* multiply off-diagonal portion of matrix */
2798:     VecSet(mat->slvec1b,0.0);
2799:     (*mat->B->ops->multtranspose)(mat->B,xx,mat->slvec0b);
2800:     VecGetArray(mat->slvec0,&from);
2801:     VecGetArray(xx,&x);
2802:     PetscArraycpy(from,x,bs*mbs);
2803:     VecRestoreArray(mat->slvec0,&from);
2804:     VecRestoreArray(xx,&x);
2805:     VecScatterBegin(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);
2806:     VecScatterEnd(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);
2807:     (*mat->B->ops->multadd)(mat->B,mat->slvec1b,mat->slvec1a,mat->slvec1a);

2809:     /* local sweep */
2810:     (*mat->A->ops->sor)(mat->A,mat->slvec1a,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_FORWARD_SWEEP),fshift,lits,1,xx1);
2811:     VecAXPY(xx,1.0,xx1);
2812:   } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"MatSORType is not supported for SBAIJ matrix format");
2813:   return(0);
2814: }

2816: /*@
2817:      MatCreateMPISBAIJWithArrays - creates a MPI SBAIJ matrix using arrays that contain in standard
2818:          CSR format the local rows.

2820:    Collective

2822:    Input Parameters:
2823: +  comm - MPI communicator
2824: .  bs - the block size, only a block size of 1 is supported
2825: .  m - number of local rows (Cannot be PETSC_DECIDE)
2826: .  n - This value should be the same as the local size used in creating the
2827:        x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have
2828:        calculated if N is given) For square matrices n is almost always m.
2829: .  M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
2830: .  N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
2831: .   i - row indices; that is i[0] = 0, i[row] = i[row-1] + number of block elements in that row block row of the matrix
2832: .   j - column indices
2833: -   a - matrix values

2835:    Output Parameter:
2836: .   mat - the matrix

2838:    Level: intermediate

2840:    Notes:
2841:        The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc;
2842:      thus you CANNOT change the matrix entries by changing the values of a[] after you have
2843:      called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays.

2845:        The i and j indices are 0 based, and i indices are indices corresponding to the local j array.

2847: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(),
2848:           MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays()
2849: @*/
2850: PetscErrorCode  MatCreateMPISBAIJWithArrays(MPI_Comm comm,PetscInt bs,PetscInt m,PetscInt n,PetscInt M,PetscInt N,const PetscInt i[],const PetscInt j[],const PetscScalar a[],Mat *mat)
2851: {


2856:   if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0");
2857:   if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative");
2858:   MatCreate(comm,mat);
2859:   MatSetSizes(*mat,m,n,M,N);
2860:   MatSetType(*mat,MATMPISBAIJ);
2861:   MatMPISBAIJSetPreallocationCSR(*mat,bs,i,j,a);
2862:   return(0);
2863: }


2866: /*@C
2867:    MatMPISBAIJSetPreallocationCSR - Creates a sparse parallel matrix in SBAIJ format using the given nonzero structure and (optional) numerical values

2869:    Collective

2871:    Input Parameters:
2872: +  B - the matrix
2873: .  bs - the block size
2874: .  i - the indices into j for the start of each local row (starts with zero)
2875: .  j - the column indices for each local row (starts with zero) these must be sorted for each row
2876: -  v - optional values in the matrix

2878:    Level: advanced

2880:    Notes:
2881:    Though this routine has Preallocation() in the name it also sets the exact nonzero locations of the matrix entries
2882:    and usually the numerical values as well

2884:    Any entries below the diagonal are ignored

2886: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIBAIJSetPreallocation(), MatCreateAIJ(), MPIAIJ
2887: @*/
2888: PetscErrorCode  MatMPISBAIJSetPreallocationCSR(Mat B,PetscInt bs,const PetscInt i[],const PetscInt j[], const PetscScalar v[])
2889: {

2893:   PetscTryMethod(B,"MatMPISBAIJSetPreallocationCSR_C",(Mat,PetscInt,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,bs,i,j,v));
2894:   return(0);
2895: }

2897: PetscErrorCode MatCreateMPIMatConcatenateSeqMat_MPISBAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat)
2898: {
2900:   PetscInt       m,N,i,rstart,nnz,Ii,bs,cbs;
2901:   PetscInt       *indx;
2902:   PetscScalar    *values;

2905:   MatGetSize(inmat,&m,&N);
2906:   if (scall == MAT_INITIAL_MATRIX) { /* symbolic phase */
2907:     Mat_SeqSBAIJ   *a = (Mat_SeqSBAIJ*)inmat->data;
2908:     PetscInt       *dnz,*onz,mbs,Nbs,nbs;
2909:     PetscInt       *bindx,rmax=a->rmax,j;
2910:     PetscMPIInt    rank,size;

2912:     MatGetBlockSizes(inmat,&bs,&cbs);
2913:     mbs = m/bs; Nbs = N/cbs;
2914:     if (n == PETSC_DECIDE) {
2915:       PetscSplitOwnershipBlock(comm,cbs,&n,&N);
2916:     }
2917:     nbs = n/cbs;

2919:     PetscMalloc1(rmax,&bindx);
2920:     MatPreallocateInitialize(comm,mbs,nbs,dnz,onz); /* inline function, output __end and __rstart are used below */

2922:     MPI_Comm_rank(comm,&rank);
2923:     MPI_Comm_rank(comm,&size);
2924:     if (rank == size-1) {
2925:       /* Check sum(nbs) = Nbs */
2926:       if (__end != Nbs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Sum of local block columns %D != global block columns %D",__end,Nbs);
2927:     }

2929:     rstart = __rstart; /* block rstart of *outmat; see inline function MatPreallocateInitialize */
2930:     MatSetOption(inmat,MAT_GETROW_UPPERTRIANGULAR,PETSC_TRUE);
2931:     for (i=0; i<mbs; i++) {
2932:       MatGetRow_SeqSBAIJ(inmat,i*bs,&nnz,&indx,NULL); /* non-blocked nnz and indx */
2933:       nnz  = nnz/bs;
2934:       for (j=0; j<nnz; j++) bindx[j] = indx[j*bs]/bs;
2935:       MatPreallocateSet(i+rstart,nnz,bindx,dnz,onz);
2936:       MatRestoreRow_SeqSBAIJ(inmat,i*bs,&nnz,&indx,NULL);
2937:     }
2938:     MatSetOption(inmat,MAT_GETROW_UPPERTRIANGULAR,PETSC_FALSE);
2939:     PetscFree(bindx);

2941:     MatCreate(comm,outmat);
2942:     MatSetSizes(*outmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);
2943:     MatSetBlockSizes(*outmat,bs,cbs);
2944:     MatSetType(*outmat,MATSBAIJ);
2945:     MatSeqSBAIJSetPreallocation(*outmat,bs,0,dnz);
2946:     MatMPISBAIJSetPreallocation(*outmat,bs,0,dnz,0,onz);
2947:     MatPreallocateFinalize(dnz,onz);
2948:   }

2950:   /* numeric phase */
2951:   MatGetBlockSizes(inmat,&bs,&cbs);
2952:   MatGetOwnershipRange(*outmat,&rstart,NULL);

2954:   MatSetOption(inmat,MAT_GETROW_UPPERTRIANGULAR,PETSC_TRUE);
2955:   for (i=0; i<m; i++) {
2956:     MatGetRow_SeqSBAIJ(inmat,i,&nnz,&indx,&values);
2957:     Ii   = i + rstart;
2958:     MatSetValues(*outmat,1,&Ii,nnz,indx,values,INSERT_VALUES);
2959:     MatRestoreRow_SeqSBAIJ(inmat,i,&nnz,&indx,&values);
2960:   }
2961:   MatSetOption(inmat,MAT_GETROW_UPPERTRIANGULAR,PETSC_FALSE);
2962:   MatAssemblyBegin(*outmat,MAT_FINAL_ASSEMBLY);
2963:   MatAssemblyEnd(*outmat,MAT_FINAL_ASSEMBLY);
2964:   return(0);
2965: }