Actual source code: mpisbaij.c


  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;

 24:   for (i = 0; i < nm; i++) {
 26:     PetscLayoutCompare(B->rmap,X[i]->rmap,&cong);
 28:   }
 30:   MatGetBlockSize(B,&bs);
 31:   MatGetSize(B,&M,&N);
 32:   MatGetLocalSize(B,&m,&n);
 33:   MatCreate(PetscObjectComm((PetscObject)B),&preallocator);
 34:   MatSetType(preallocator,MATPREALLOCATOR);
 35:   MatSetBlockSize(preallocator,bs);
 36:   MatSetSizes(preallocator,m,n,M,N);
 37:   MatSetUp(preallocator);
 38:   MatGetOwnershipRange(preallocator,&rstart,&rend);
 39:   for (r = rstart; r < rend; ++r) {
 40:     PetscInt          ncols;
 41:     const PetscInt    *row;
 42:     const PetscScalar *vals;

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

 60: PETSC_INTERN PetscErrorCode MatConvert_MPISBAIJ_Basic(Mat A, MatType newtype, MatReuse reuse, Mat *newmat)
 61: {
 62:   Mat            B;
 63:   PetscInt       r;

 65:   if (reuse != MAT_REUSE_MATRIX) {
 66:     PetscBool symm = PETSC_TRUE,isdense;
 67:     PetscInt  bs;

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

 89:   MatGetRowUpperTriangular(A);
 90:   for (r = A->rmap->rstart; r < A->rmap->rend; r++) {
 91:     PetscInt          ncols;
 92:     const PetscInt    *row;
 93:     const PetscScalar *vals;

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

115:   if (reuse == MAT_INPLACE_MATRIX) {
116:     MatHeaderReplace(A,&B);
117:   } else {
118:     *newmat = B;
119:   }
120:   return 0;
121: }

123: PetscErrorCode  MatStoreValues_MPISBAIJ(Mat mat)
124: {
125:   Mat_MPISBAIJ   *aij = (Mat_MPISBAIJ*)mat->data;

127:   MatStoreValues(aij->A);
128:   MatStoreValues(aij->B);
129:   return 0;
130: }

132: PetscErrorCode  MatRetrieveValues_MPISBAIJ(Mat mat)
133: {
134:   Mat_MPISBAIJ   *aij = (Mat_MPISBAIJ*)mat->data;

136:   MatRetrieveValues(aij->A);
137:   MatRetrieveValues(aij->B);
138:   return 0;
139: }

141: #define  MatSetValues_SeqSBAIJ_A_Private(row,col,value,addv,orow,ocol)      \
142:   { \
143:     brow = row/bs;  \
144:     rp   = aj + ai[brow]; ap = aa + bs2*ai[brow]; \
145:     rmax = aimax[brow]; nrow = ailen[brow]; \
146:     bcol = col/bs; \
147:     ridx = row % bs; cidx = col % bs; \
148:     low  = 0; high = nrow; \
149:     while (high-low > 3) { \
150:       t = (low+high)/2; \
151:       if (rp[t] > bcol) high = t; \
152:       else              low  = t; \
153:     } \
154:     for (_i=low; _i<high; _i++) { \
155:       if (rp[_i] > bcol) break; \
156:       if (rp[_i] == bcol) { \
157:         bap = ap + bs2*_i + bs*cidx + ridx; \
158:         if (addv == ADD_VALUES) *bap += value;  \
159:         else                    *bap  = value;  \
160:         goto a_noinsert; \
161:       } \
162:     } \
163:     if (a->nonew == 1) goto a_noinsert; \
165:     MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,brow,bcol,rmax,aa,ai,aj,rp,ap,aimax,a->nonew,MatScalar); \
166:     N = nrow++ - 1;  \
167:     /* shift up all the later entries in this row */ \
168:     PetscArraymove(rp+_i+1,rp+_i,N-_i+1); \
169:     PetscArraymove(ap+bs2*(_i+1),ap+bs2*_i,bs2*(N-_i+1)); \
170:     PetscArrayzero(ap+bs2*_i,bs2);  \
171:     rp[_i]                      = bcol;  \
172:     ap[bs2*_i + bs*cidx + ridx] = value;  \
173:     A->nonzerostate++;\
174: a_noinsert:; \
175:     ailen[brow] = nrow; \
176:   }

178: #define  MatSetValues_SeqSBAIJ_B_Private(row,col,value,addv,orow,ocol) \
179:   { \
180:     brow = row/bs;  \
181:     rp   = bj + bi[brow]; ap = ba + bs2*bi[brow]; \
182:     rmax = bimax[brow]; nrow = bilen[brow]; \
183:     bcol = col/bs; \
184:     ridx = row % bs; cidx = col % bs; \
185:     low  = 0; high = nrow; \
186:     while (high-low > 3) { \
187:       t = (low+high)/2; \
188:       if (rp[t] > bcol) high = t; \
189:       else              low  = t; \
190:     } \
191:     for (_i=low; _i<high; _i++) { \
192:       if (rp[_i] > bcol) break; \
193:       if (rp[_i] == bcol) { \
194:         bap = ap + bs2*_i + bs*cidx + ridx; \
195:         if (addv == ADD_VALUES) *bap += value;  \
196:         else                    *bap  = value;  \
197:         goto b_noinsert; \
198:       } \
199:     } \
200:     if (b->nonew == 1) goto b_noinsert; \
202:     MatSeqXAIJReallocateAIJ(B,b->mbs,bs2,nrow,brow,bcol,rmax,ba,bi,bj,rp,ap,bimax,b->nonew,MatScalar); \
203:     N = nrow++ - 1;  \
204:     /* shift up all the later entries in this row */ \
205:     PetscArraymove(rp+_i+1,rp+_i,N-_i+1); \
206:     PetscArraymove(ap+bs2*(_i+1),ap+bs2*_i,bs2*(N-_i+1)); \
207:     PetscArrayzero(ap+bs2*_i,bs2); \
208:     rp[_i]                      = bcol;  \
209:     ap[bs2*_i + bs*cidx + ridx] = value;  \
210:     B->nonzerostate++;\
211: b_noinsert:; \
212:     bilen[brow] = nrow; \
213:   }

215: /* Only add/insert a(i,j) with i<=j (blocks).
216:    Any a(i,j) with i>j input by user is ingored or generates an error
217: */
218: PetscErrorCode MatSetValues_MPISBAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv)
219: {
220:   Mat_MPISBAIJ   *baij = (Mat_MPISBAIJ*)mat->data;
221:   MatScalar      value;
222:   PetscBool      roworiented = baij->roworiented;
223:   PetscInt       i,j,row,col;
224:   PetscInt       rstart_orig=mat->rmap->rstart;
225:   PetscInt       rend_orig  =mat->rmap->rend,cstart_orig=mat->cmap->rstart;
226:   PetscInt       cend_orig  =mat->cmap->rend,bs=mat->rmap->bs;

228:   /* Some Variables required in the macro */
229:   Mat          A     = baij->A;
230:   Mat_SeqSBAIJ *a    = (Mat_SeqSBAIJ*)(A)->data;
231:   PetscInt     *aimax=a->imax,*ai=a->i,*ailen=a->ilen,*aj=a->j;
232:   MatScalar    *aa   =a->a;

234:   Mat         B     = baij->B;
235:   Mat_SeqBAIJ *b    = (Mat_SeqBAIJ*)(B)->data;
236:   PetscInt    *bimax=b->imax,*bi=b->i,*bilen=b->ilen,*bj=b->j;
237:   MatScalar   *ba   =b->a;

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

243:   /* for stash */
244:   PetscInt  n_loc, *in_loc = NULL;
245:   MatScalar *v_loc = NULL;

247:   if (!baij->donotstash) {
248:     if (n > baij->n_loc) {
249:       PetscFree(baij->in_loc);
250:       PetscFree(baij->v_loc);
251:       PetscMalloc1(n,&baij->in_loc);
252:       PetscMalloc1(n,&baij->v_loc);

254:       baij->n_loc = n;
255:     }
256:     in_loc = baij->in_loc;
257:     v_loc  = baij->v_loc;
258:   }

260:   for (i=0; i<m; i++) {
261:     if (im[i] < 0) continue;
263:     if (im[i] >= rstart_orig && im[i] < rend_orig) { /* this processor entry */
264:       row = im[i] - rstart_orig;              /* local row index */
265:       for (j=0; j<n; j++) {
266:         if (im[i]/bs > in[j]/bs) {
267:           if (a->ignore_ltriangular) {
268:             continue;    /* ignore lower triangular blocks */
269:           } 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)");
270:         }
271:         if (in[j] >= cstart_orig && in[j] < cend_orig) {  /* diag entry (A) */
272:           col  = in[j] - cstart_orig;         /* local col index */
273:           brow = row/bs; bcol = col/bs;
274:           if (brow > bcol) continue;  /* ignore lower triangular blocks of A */
275:           if (roworiented) value = v[i*n+j];
276:           else             value = v[i+j*m];
277:           MatSetValues_SeqSBAIJ_A_Private(row,col,value,addv,im[i],in[j]);
278:           /* MatSetValues_SeqBAIJ(baij->A,1,&row,1,&col,&value,addv); */
279:         } else if (in[j] < 0) continue;
281:         else {  /* off-diag entry (B) */
282:           if (mat->was_assembled) {
283:             if (!baij->colmap) {
284:               MatCreateColmap_MPIBAIJ_Private(mat);
285:             }
286: #if defined(PETSC_USE_CTABLE)
287:             PetscTableFind(baij->colmap,in[j]/bs + 1,&col);
288:             col  = col - 1;
289: #else
290:             col = baij->colmap[in[j]/bs] - 1;
291: #endif
292:             if (col < 0 && !((Mat_SeqSBAIJ*)(baij->A->data))->nonew) {
293:               MatDisAssemble_MPISBAIJ(mat);
294:               col  =  in[j];
295:               /* Reinitialize the variables required by MatSetValues_SeqBAIJ_B_Private() */
296:               B    = baij->B;
297:               b    = (Mat_SeqBAIJ*)(B)->data;
298:               bimax= b->imax;bi=b->i;bilen=b->ilen;bj=b->j;
299:               ba   = b->a;
300:             } else col += in[j]%bs;
301:           } else col = in[j];
302:           if (roworiented) value = v[i*n+j];
303:           else             value = v[i+j*m];
304:           MatSetValues_SeqSBAIJ_B_Private(row,col,value,addv,im[i],in[j]);
305:           /* MatSetValues_SeqBAIJ(baij->B,1,&row,1,&col,&value,addv); */
306:         }
307:       }
308:     } else {  /* off processor entry */
310:       if (!baij->donotstash) {
311:         mat->assembled = PETSC_FALSE;
312:         n_loc          = 0;
313:         for (j=0; j<n; j++) {
314:           if (im[i]/bs > in[j]/bs) continue; /* ignore lower triangular blocks */
315:           in_loc[n_loc] = in[j];
316:           if (roworiented) {
317:             v_loc[n_loc] = v[i*n+j];
318:           } else {
319:             v_loc[n_loc] = v[j*m+i];
320:           }
321:           n_loc++;
322:         }
323:         MatStashValuesRow_Private(&mat->stash,im[i],n_loc,in_loc,v_loc,PETSC_FALSE);
324:       }
325:     }
326:   }
327:   return 0;
328: }

330: static inline PetscErrorCode MatSetValuesBlocked_SeqSBAIJ_Inlined(Mat A,PetscInt row,PetscInt col,const PetscScalar v[],InsertMode is,PetscInt orow,PetscInt ocol)
331: {
332:   Mat_SeqSBAIJ      *a = (Mat_SeqSBAIJ*)A->data;
333:   PetscInt          *rp,low,high,t,ii,jj,nrow,i,rmax,N;
334:   PetscInt          *imax      =a->imax,*ai=a->i,*ailen=a->ilen;
335:   PetscInt          *aj        =a->j,nonew=a->nonew,bs2=a->bs2,bs=A->rmap->bs;
336:   PetscBool         roworiented=a->roworiented;
337:   const PetscScalar *value     = v;
338:   MatScalar         *ap,*aa = a->a,*bap;

340:   if (col < row) {
341:     if (a->ignore_ltriangular) return 0; /* ignore lower triangular block */
342:     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)");
343:   }
344:   rp   = aj + ai[row];
345:   ap   = aa + bs2*ai[row];
346:   rmax = imax[row];
347:   nrow = ailen[row];
348:   value = v;
349:   low   = 0;
350:   high  = nrow;

352:   while (high-low > 7) {
353:     t = (low+high)/2;
354:     if (rp[t] > col) high = t;
355:     else             low  = t;
356:   }
357:   for (i=low; i<high; i++) {
358:     if (rp[i] > col) break;
359:     if (rp[i] == col) {
360:       bap = ap +  bs2*i;
361:       if (roworiented) {
362:         if (is == ADD_VALUES) {
363:           for (ii=0; ii<bs; ii++) {
364:             for (jj=ii; jj<bs2; jj+=bs) {
365:               bap[jj] += *value++;
366:             }
367:           }
368:         } else {
369:           for (ii=0; ii<bs; ii++) {
370:             for (jj=ii; jj<bs2; jj+=bs) {
371:               bap[jj] = *value++;
372:             }
373:           }
374:         }
375:       } else {
376:         if (is == ADD_VALUES) {
377:           for (ii=0; ii<bs; ii++) {
378:             for (jj=0; jj<bs; jj++) {
379:               *bap++ += *value++;
380:             }
381:           }
382:         } else {
383:           for (ii=0; ii<bs; ii++) {
384:             for (jj=0; jj<bs; jj++) {
385:               *bap++  = *value++;
386:             }
387:           }
388:         }
389:       }
390:       goto noinsert2;
391:     }
392:   }
393:   if (nonew == 1) goto noinsert2;
395:   MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,row,col,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar);
396:   N = nrow++ - 1; high++;
397:   /* shift up all the later entries in this row */
398:   PetscArraymove(rp+i+1,rp+i,N-i+1);
399:   PetscArraymove(ap+bs2*(i+1),ap+bs2*i,bs2*(N-i+1));
400:   rp[i] = col;
401:   bap   = ap +  bs2*i;
402:   if (roworiented) {
403:     for (ii=0; ii<bs; ii++) {
404:       for (jj=ii; jj<bs2; jj+=bs) {
405:         bap[jj] = *value++;
406:       }
407:     }
408:   } else {
409:     for (ii=0; ii<bs; ii++) {
410:       for (jj=0; jj<bs; jj++) {
411:         *bap++ = *value++;
412:       }
413:     }
414:   }
415:   noinsert2:;
416:   ailen[row] = nrow;
417:   return 0;
418: }

420: /*
421:    This routine is exactly duplicated in mpibaij.c
422: */
423: static inline PetscErrorCode MatSetValuesBlocked_SeqBAIJ_Inlined(Mat A,PetscInt row,PetscInt col,const PetscScalar v[],InsertMode is,PetscInt orow,PetscInt ocol)
424: {
425:   Mat_SeqBAIJ       *a = (Mat_SeqBAIJ*)A->data;
426:   PetscInt          *rp,low,high,t,ii,jj,nrow,i,rmax,N;
427:   PetscInt          *imax=a->imax,*ai=a->i,*ailen=a->ilen;
428:   PetscInt          *aj        =a->j,nonew=a->nonew,bs2=a->bs2,bs=A->rmap->bs;
429:   PetscBool         roworiented=a->roworiented;
430:   const PetscScalar *value     = v;
431:   MatScalar         *ap,*aa = a->a,*bap;

433:   rp   = aj + ai[row];
434:   ap   = aa + bs2*ai[row];
435:   rmax = imax[row];
436:   nrow = ailen[row];
437:   low  = 0;
438:   high = nrow;
439:   value = v;
440:   while (high-low > 7) {
441:     t = (low+high)/2;
442:     if (rp[t] > col) high = t;
443:     else             low  = t;
444:   }
445:   for (i=low; i<high; i++) {
446:     if (rp[i] > col) break;
447:     if (rp[i] == col) {
448:       bap = ap +  bs2*i;
449:       if (roworiented) {
450:         if (is == ADD_VALUES) {
451:           for (ii=0; ii<bs; ii++) {
452:             for (jj=ii; jj<bs2; jj+=bs) {
453:               bap[jj] += *value++;
454:             }
455:           }
456:         } else {
457:           for (ii=0; ii<bs; ii++) {
458:             for (jj=ii; jj<bs2; jj+=bs) {
459:               bap[jj] = *value++;
460:             }
461:           }
462:         }
463:       } else {
464:         if (is == ADD_VALUES) {
465:           for (ii=0; ii<bs; ii++,value+=bs) {
466:             for (jj=0; jj<bs; jj++) {
467:               bap[jj] += value[jj];
468:             }
469:             bap += bs;
470:           }
471:         } else {
472:           for (ii=0; ii<bs; ii++,value+=bs) {
473:             for (jj=0; jj<bs; jj++) {
474:               bap[jj]  = value[jj];
475:             }
476:             bap += bs;
477:           }
478:         }
479:       }
480:       goto noinsert2;
481:     }
482:   }
483:   if (nonew == 1) goto noinsert2;
485:   MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,row,col,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar);
486:   N = nrow++ - 1; high++;
487:   /* shift up all the later entries in this row */
488:   PetscArraymove(rp+i+1,rp+i,N-i+1);
489:   PetscArraymove(ap+bs2*(i+1),ap+bs2*i,bs2*(N-i+1));
490:   rp[i] = col;
491:   bap   = ap +  bs2*i;
492:   if (roworiented) {
493:     for (ii=0; ii<bs; ii++) {
494:       for (jj=ii; jj<bs2; jj+=bs) {
495:         bap[jj] = *value++;
496:       }
497:     }
498:   } else {
499:     for (ii=0; ii<bs; ii++) {
500:       for (jj=0; jj<bs; jj++) {
501:         *bap++ = *value++;
502:       }
503:     }
504:   }
505:   noinsert2:;
506:   ailen[row] = nrow;
507:   return 0;
508: }

510: /*
511:     This routine could be optimized by removing the need for the block copy below and passing stride information
512:   to the above inline routines; similarly in MatSetValuesBlocked_MPIBAIJ()
513: */
514: PetscErrorCode MatSetValuesBlocked_MPISBAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const MatScalar v[],InsertMode addv)
515: {
516:   Mat_MPISBAIJ    *baij = (Mat_MPISBAIJ*)mat->data;
517:   const MatScalar *value;
518:   MatScalar       *barray     =baij->barray;
519:   PetscBool       roworiented = baij->roworiented,ignore_ltriangular = ((Mat_SeqSBAIJ*)baij->A->data)->ignore_ltriangular;
520:   PetscInt        i,j,ii,jj,row,col,rstart=baij->rstartbs;
521:   PetscInt        rend=baij->rendbs,cstart=baij->cstartbs,stepval;
522:   PetscInt        cend=baij->cendbs,bs=mat->rmap->bs,bs2=baij->bs2;

524:   if (!barray) {
525:     PetscMalloc1(bs2,&barray);
526:     baij->barray = barray;
527:   }

529:   if (roworiented) {
530:     stepval = (n-1)*bs;
531:   } else {
532:     stepval = (m-1)*bs;
533:   }
534:   for (i=0; i<m; i++) {
535:     if (im[i] < 0) continue;
537:     if (im[i] >= rstart && im[i] < rend) {
538:       row = im[i] - rstart;
539:       for (j=0; j<n; j++) {
540:         if (im[i] > in[j]) {
541:           if (ignore_ltriangular) continue; /* ignore lower triangular blocks */
542:           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)");
543:         }
544:         /* If NumCol = 1 then a copy is not required */
545:         if ((roworiented) && (n == 1)) {
546:           barray = (MatScalar*) v + i*bs2;
547:         } else if ((!roworiented) && (m == 1)) {
548:           barray = (MatScalar*) v + j*bs2;
549:         } else { /* Here a copy is required */
550:           if (roworiented) {
551:             value = v + i*(stepval+bs)*bs + j*bs;
552:           } else {
553:             value = v + j*(stepval+bs)*bs + i*bs;
554:           }
555:           for (ii=0; ii<bs; ii++,value+=stepval) {
556:             for (jj=0; jj<bs; jj++) {
557:               *barray++ = *value++;
558:             }
559:           }
560:           barray -=bs2;
561:         }

563:         if (in[j] >= cstart && in[j] < cend) {
564:           col  = in[j] - cstart;
565:           MatSetValuesBlocked_SeqSBAIJ_Inlined(baij->A,row,col,barray,addv,im[i],in[j]);
566:         } else if (in[j] < 0) continue;
568:         else {
569:           if (mat->was_assembled) {
570:             if (!baij->colmap) {
571:               MatCreateColmap_MPIBAIJ_Private(mat);
572:             }

574: #if defined(PETSC_USE_DEBUG)
575: #if defined(PETSC_USE_CTABLE)
576:             { PetscInt data;
577:               PetscTableFind(baij->colmap,in[j]+1,&data);
579:             }
580: #else
582: #endif
583: #endif
584: #if defined(PETSC_USE_CTABLE)
585:             PetscTableFind(baij->colmap,in[j]+1,&col);
586:             col  = (col - 1)/bs;
587: #else
588:             col = (baij->colmap[in[j]] - 1)/bs;
589: #endif
590:             if (col < 0 && !((Mat_SeqBAIJ*)(baij->A->data))->nonew) {
591:               MatDisAssemble_MPISBAIJ(mat);
592:               col  = in[j];
593:             }
594:           } else col = in[j];
595:           MatSetValuesBlocked_SeqBAIJ_Inlined(baij->B,row,col,barray,addv,im[i],in[j]);
596:         }
597:       }
598:     } else {
600:       if (!baij->donotstash) {
601:         if (roworiented) {
602:           MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);
603:         } else {
604:           MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);
605:         }
606:       }
607:     }
608:   }
609:   return 0;
610: }

612: PetscErrorCode MatGetValues_MPISBAIJ(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[])
613: {
614:   Mat_MPISBAIJ   *baij = (Mat_MPISBAIJ*)mat->data;
615:   PetscInt       bs       = mat->rmap->bs,i,j,bsrstart = mat->rmap->rstart,bsrend = mat->rmap->rend;
616:   PetscInt       bscstart = mat->cmap->rstart,bscend = mat->cmap->rend,row,col,data;

618:   for (i=0; i<m; i++) {
619:     if (idxm[i] < 0) continue; /* negative row */
621:     if (idxm[i] >= bsrstart && idxm[i] < bsrend) {
622:       row = idxm[i] - bsrstart;
623:       for (j=0; j<n; j++) {
624:         if (idxn[j] < 0) continue; /* negative column */
626:         if (idxn[j] >= bscstart && idxn[j] < bscend) {
627:           col  = idxn[j] - bscstart;
628:           MatGetValues_SeqSBAIJ(baij->A,1,&row,1,&col,v+i*n+j);
629:         } else {
630:           if (!baij->colmap) {
631:             MatCreateColmap_MPIBAIJ_Private(mat);
632:           }
633: #if defined(PETSC_USE_CTABLE)
634:           PetscTableFind(baij->colmap,idxn[j]/bs+1,&data);
635:           data--;
636: #else
637:           data = baij->colmap[idxn[j]/bs]-1;
638: #endif
639:           if ((data < 0) || (baij->garray[data/bs] != idxn[j]/bs)) *(v+i*n+j) = 0.0;
640:           else {
641:             col  = data + idxn[j]%bs;
642:             MatGetValues_SeqBAIJ(baij->B,1,&row,1,&col,v+i*n+j);
643:           }
644:         }
645:       }
646:     } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local values currently supported");
647:   }
648:   return 0;
649: }

651: PetscErrorCode MatNorm_MPISBAIJ(Mat mat,NormType type,PetscReal *norm)
652: {
653:   Mat_MPISBAIJ   *baij = (Mat_MPISBAIJ*)mat->data;
654:   PetscReal      sum[2],*lnorm2;

656:   if (baij->size == 1) {
657:     MatNorm(baij->A,type,norm);
658:   } else {
659:     if (type == NORM_FROBENIUS) {
660:       PetscMalloc1(2,&lnorm2);
661:       MatNorm(baij->A,type,lnorm2);
662:       *lnorm2 = (*lnorm2)*(*lnorm2); lnorm2++;            /* squar power of norm(A) */
663:       MatNorm(baij->B,type,lnorm2);
664:       *lnorm2 = (*lnorm2)*(*lnorm2); lnorm2--;             /* squar power of norm(B) */
665:       MPIU_Allreduce(lnorm2,sum,2,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));
666:       *norm   = PetscSqrtReal(sum[0] + 2*sum[1]);
667:       PetscFree(lnorm2);
668:     } else if (type == NORM_INFINITY || type == NORM_1) { /* max row/column sum */
669:       Mat_SeqSBAIJ *amat=(Mat_SeqSBAIJ*)baij->A->data;
670:       Mat_SeqBAIJ  *bmat=(Mat_SeqBAIJ*)baij->B->data;
671:       PetscReal    *rsum,*rsum2,vabs;
672:       PetscInt     *jj,*garray=baij->garray,rstart=baij->rstartbs,nz;
673:       PetscInt     brow,bcol,col,bs=baij->A->rmap->bs,row,grow,gcol,mbs=amat->mbs;
674:       MatScalar    *v;

676:       PetscMalloc2(mat->cmap->N,&rsum,mat->cmap->N,&rsum2);
677:       PetscArrayzero(rsum,mat->cmap->N);
678:       /* Amat */
679:       v = amat->a; jj = amat->j;
680:       for (brow=0; brow<mbs; brow++) {
681:         grow = bs*(rstart + brow);
682:         nz   = amat->i[brow+1] - amat->i[brow];
683:         for (bcol=0; bcol<nz; bcol++) {
684:           gcol = bs*(rstart + *jj); jj++;
685:           for (col=0; col<bs; col++) {
686:             for (row=0; row<bs; row++) {
687:               vabs            = PetscAbsScalar(*v); v++;
688:               rsum[gcol+col] += vabs;
689:               /* non-diagonal block */
690:               if (bcol > 0 && vabs > 0.0) rsum[grow+row] += vabs;
691:             }
692:           }
693:         }
694:         PetscLogFlops(nz*bs*bs);
695:       }
696:       /* Bmat */
697:       v = bmat->a; jj = bmat->j;
698:       for (brow=0; brow<mbs; brow++) {
699:         grow = bs*(rstart + brow);
700:         nz = bmat->i[brow+1] - bmat->i[brow];
701:         for (bcol=0; bcol<nz; bcol++) {
702:           gcol = bs*garray[*jj]; jj++;
703:           for (col=0; col<bs; col++) {
704:             for (row=0; row<bs; row++) {
705:               vabs            = PetscAbsScalar(*v); v++;
706:               rsum[gcol+col] += vabs;
707:               rsum[grow+row] += vabs;
708:             }
709:           }
710:         }
711:         PetscLogFlops(nz*bs*bs);
712:       }
713:       MPIU_Allreduce(rsum,rsum2,mat->cmap->N,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));
714:       *norm = 0.0;
715:       for (col=0; col<mat->cmap->N; col++) {
716:         if (rsum2[col] > *norm) *norm = rsum2[col];
717:       }
718:       PetscFree2(rsum,rsum2);
719:     } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support for this norm yet");
720:   }
721:   return 0;
722: }

724: PetscErrorCode MatAssemblyBegin_MPISBAIJ(Mat mat,MatAssemblyType mode)
725: {
726:   Mat_MPISBAIJ   *baij = (Mat_MPISBAIJ*)mat->data;
727:   PetscInt       nstash,reallocs;

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

731:   MatStashScatterBegin_Private(mat,&mat->stash,mat->rmap->range);
732:   MatStashScatterBegin_Private(mat,&mat->bstash,baij->rangebs);
733:   MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);
734:   PetscInfo(mat,"Stash has %" PetscInt_FMT " entries,uses %" PetscInt_FMT " mallocs.\n",nstash,reallocs);
735:   MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);
736:   PetscInfo(mat,"Block-Stash has %" PetscInt_FMT " entries, uses %" PetscInt_FMT " mallocs.\n",nstash,reallocs);
737:   return 0;
738: }

740: PetscErrorCode MatAssemblyEnd_MPISBAIJ(Mat mat,MatAssemblyType mode)
741: {
742:   Mat_MPISBAIJ   *baij=(Mat_MPISBAIJ*)mat->data;
743:   Mat_SeqSBAIJ   *a   =(Mat_SeqSBAIJ*)baij->A->data;
744:   PetscInt       i,j,rstart,ncols,flg,bs2=baij->bs2;
745:   PetscInt       *row,*col;
746:   PetscBool      other_disassembled;
747:   PetscMPIInt    n;
748:   PetscBool      r1,r2,r3;
749:   MatScalar      *val;

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

757:       for (i=0; i<n;) {
758:         /* Now identify the consecutive vals belonging to the same row */
759:         for (j=i,rstart=row[j]; j<n; j++) {
760:           if (row[j] != rstart) break;
761:         }
762:         if (j < n) ncols = j-i;
763:         else       ncols = n-i;
764:         /* Now assemble all these values with a single function call */
765:         MatSetValues_MPISBAIJ(mat,1,row+i,ncols,col+i,val+i,mat->insertmode);
766:         i    = j;
767:       }
768:     }
769:     MatStashScatterEnd_Private(&mat->stash);
770:     /* Now process the block-stash. Since the values are stashed column-oriented,
771:        set the roworiented flag to column oriented, and after MatSetValues()
772:        restore the original flags */
773:     r1 = baij->roworiented;
774:     r2 = a->roworiented;
775:     r3 = ((Mat_SeqBAIJ*)baij->B->data)->roworiented;

777:     baij->roworiented = PETSC_FALSE;
778:     a->roworiented    = PETSC_FALSE;

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

785:       for (i=0; i<n;) {
786:         /* Now identify the consecutive vals belonging to the same row */
787:         for (j=i,rstart=row[j]; j<n; j++) {
788:           if (row[j] != rstart) break;
789:         }
790:         if (j < n) ncols = j-i;
791:         else       ncols = n-i;
792:         MatSetValuesBlocked_MPISBAIJ(mat,1,row+i,ncols,col+i,val+i*bs2,mat->insertmode);
793:         i    = j;
794:       }
795:     }
796:     MatStashScatterEnd_Private(&mat->bstash);

798:     baij->roworiented = r1;
799:     a->roworiented    = r2;

801:     ((Mat_SeqBAIJ*)baij->B->data)->roworiented = r3; /* b->roworinted */
802:   }

804:   MatAssemblyBegin(baij->A,mode);
805:   MatAssemblyEnd(baij->A,mode);

807:   /* determine if any processor has disassembled, if so we must
808:      also disassemble ourselfs, in order that we may reassemble. */
809:   /*
810:      if nonzero structure of submatrix B cannot change then we know that
811:      no processor disassembled thus we can skip this stuff
812:   */
813:   if (!((Mat_SeqBAIJ*)baij->B->data)->nonew) {
814:     MPIU_Allreduce(&mat->was_assembled,&other_disassembled,1,MPIU_BOOL,MPI_PROD,PetscObjectComm((PetscObject)mat));
815:     if (mat->was_assembled && !other_disassembled) {
816:       MatDisAssemble_MPISBAIJ(mat);
817:     }
818:   }

820:   if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) {
821:     MatSetUpMultiply_MPISBAIJ(mat); /* setup Mvctx and sMvctx */
822:   }
823:   MatAssemblyBegin(baij->B,mode);
824:   MatAssemblyEnd(baij->B,mode);

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

828:   baij->rowvalues = NULL;

830:   /* if no new nonzero locations are allowed in matrix then only set the matrix state the first time through */
831:   if ((!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) || !((Mat_SeqBAIJ*)(baij->A->data))->nonew) {
832:     PetscObjectState state = baij->A->nonzerostate + baij->B->nonzerostate;
833:     MPIU_Allreduce(&state,&mat->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)mat));
834:   }
835:   return 0;
836: }

838: extern PetscErrorCode MatSetValues_MPIBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const PetscScalar[],InsertMode);
839: #include <petscdraw.h>
840: static PetscErrorCode MatView_MPISBAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer)
841: {
842:   Mat_MPISBAIJ      *baij = (Mat_MPISBAIJ*)mat->data;
843:   PetscInt          bs   = mat->rmap->bs;
844:   PetscMPIInt       rank = baij->rank;
845:   PetscBool         iascii,isdraw;
846:   PetscViewer       sviewer;
847:   PetscViewerFormat format;

849:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
850:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);
851:   if (iascii) {
852:     PetscViewerGetFormat(viewer,&format);
853:     if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) {
854:       MatInfo info;
855:       MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);
856:       MatGetInfo(mat,MAT_LOCAL,&info);
857:       PetscViewerASCIIPushSynchronized(viewer);
858:       PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %" PetscInt_FMT " nz %" PetscInt_FMT " nz alloced %" PetscInt_FMT " bs %" PetscInt_FMT " mem %g\n",rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,mat->rmap->bs,(double)info.memory);
859:       MatGetInfo(baij->A,MAT_LOCAL,&info);
860:       PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %" PetscInt_FMT " \n",rank,(PetscInt)info.nz_used);
861:       MatGetInfo(baij->B,MAT_LOCAL,&info);
862:       PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %" PetscInt_FMT " \n",rank,(PetscInt)info.nz_used);
863:       PetscViewerFlush(viewer);
864:       PetscViewerASCIIPopSynchronized(viewer);
865:       PetscViewerASCIIPrintf(viewer,"Information on VecScatter used in matrix-vector product: \n");
866:       VecScatterView(baij->Mvctx,viewer);
867:       return 0;
868:     } else if (format == PETSC_VIEWER_ASCII_INFO) {
869:       PetscViewerASCIIPrintf(viewer,"  block size is %" PetscInt_FMT "\n",bs);
870:       return 0;
871:     } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) {
872:       return 0;
873:     }
874:   }

876:   if (isdraw) {
877:     PetscDraw draw;
878:     PetscBool isnull;
879:     PetscViewerDrawGetDraw(viewer,0,&draw);
880:     PetscDrawIsNull(draw,&isnull);
881:     if (isnull) return 0;
882:   }

884:   {
885:     /* assemble the entire matrix onto first processor. */
886:     Mat          A;
887:     Mat_SeqSBAIJ *Aloc;
888:     Mat_SeqBAIJ  *Bloc;
889:     PetscInt     M = mat->rmap->N,N = mat->cmap->N,*ai,*aj,col,i,j,k,*rvals,mbs = baij->mbs;
890:     MatScalar    *a;
891:     const char   *matname;

893:     /* Should this be the same type as mat? */
894:     MatCreate(PetscObjectComm((PetscObject)mat),&A);
895:     if (rank == 0) {
896:       MatSetSizes(A,M,N,M,N);
897:     } else {
898:       MatSetSizes(A,0,0,M,N);
899:     }
900:     MatSetType(A,MATMPISBAIJ);
901:     MatMPISBAIJSetPreallocation(A,mat->rmap->bs,0,NULL,0,NULL);
902:     MatSetOption(A,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_FALSE);
903:     PetscLogObjectParent((PetscObject)mat,(PetscObject)A);

905:     /* copy over the A part */
906:     Aloc = (Mat_SeqSBAIJ*)baij->A->data;
907:     ai   = Aloc->i; aj = Aloc->j; a = Aloc->a;
908:     PetscMalloc1(bs,&rvals);

910:     for (i=0; i<mbs; i++) {
911:       rvals[0] = bs*(baij->rstartbs + i);
912:       for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1;
913:       for (j=ai[i]; j<ai[i+1]; j++) {
914:         col = (baij->cstartbs+aj[j])*bs;
915:         for (k=0; k<bs; k++) {
916:           MatSetValues_MPISBAIJ(A,bs,rvals,1,&col,a,INSERT_VALUES);
917:           col++;
918:           a += bs;
919:         }
920:       }
921:     }
922:     /* copy over the B part */
923:     Bloc = (Mat_SeqBAIJ*)baij->B->data;
924:     ai   = Bloc->i; aj = Bloc->j; a = Bloc->a;
925:     for (i=0; i<mbs; i++) {

927:       rvals[0] = bs*(baij->rstartbs + i);
928:       for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1;
929:       for (j=ai[i]; j<ai[i+1]; j++) {
930:         col = baij->garray[aj[j]]*bs;
931:         for (k=0; k<bs; k++) {
932:           MatSetValues_MPIBAIJ(A,bs,rvals,1,&col,a,INSERT_VALUES);
933:           col++;
934:           a += bs;
935:         }
936:       }
937:     }
938:     PetscFree(rvals);
939:     MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);
940:     MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);
941:     /*
942:        Everyone has to call to draw the matrix since the graphics waits are
943:        synchronized across all processors that share the PetscDraw object
944:     */
945:     PetscViewerGetSubViewer(viewer,PETSC_COMM_SELF,&sviewer);
946:     PetscObjectGetName((PetscObject)mat,&matname);
947:     if (rank == 0) {
948:       PetscObjectSetName((PetscObject)((Mat_MPISBAIJ*)(A->data))->A,matname);
949:       MatView_SeqSBAIJ(((Mat_MPISBAIJ*)(A->data))->A,sviewer);
950:     }
951:     PetscViewerRestoreSubViewer(viewer,PETSC_COMM_SELF,&sviewer);
952:     PetscViewerFlush(viewer);
953:     MatDestroy(&A);
954:   }
955:   return 0;
956: }

958: /* Used for both MPIBAIJ and MPISBAIJ matrices */
959: #define MatView_MPISBAIJ_Binary MatView_MPIBAIJ_Binary

961: PetscErrorCode MatView_MPISBAIJ(Mat mat,PetscViewer viewer)
962: {
963:   PetscBool      iascii,isdraw,issocket,isbinary;

965:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
966:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);
967:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSOCKET,&issocket);
968:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);
969:   if (iascii || isdraw || issocket) {
970:     MatView_MPISBAIJ_ASCIIorDraworSocket(mat,viewer);
971:   } else if (isbinary) {
972:     MatView_MPISBAIJ_Binary(mat,viewer);
973:   }
974:   return 0;
975: }

977: PetscErrorCode MatDestroy_MPISBAIJ(Mat mat)
978: {
979:   Mat_MPISBAIJ   *baij = (Mat_MPISBAIJ*)mat->data;

981: #if defined(PETSC_USE_LOG)
982:   PetscLogObjectState((PetscObject)mat,"Rows=%" PetscInt_FMT ",Cols=%" PetscInt_FMT,mat->rmap->N,mat->cmap->N);
983: #endif
984:   MatStashDestroy_Private(&mat->stash);
985:   MatStashDestroy_Private(&mat->bstash);
986:   MatDestroy(&baij->A);
987:   MatDestroy(&baij->B);
988: #if defined(PETSC_USE_CTABLE)
989:   PetscTableDestroy(&baij->colmap);
990: #else
991:   PetscFree(baij->colmap);
992: #endif
993:   PetscFree(baij->garray);
994:   VecDestroy(&baij->lvec);
995:   VecScatterDestroy(&baij->Mvctx);
996:   VecDestroy(&baij->slvec0);
997:   VecDestroy(&baij->slvec0b);
998:   VecDestroy(&baij->slvec1);
999:   VecDestroy(&baij->slvec1a);
1000:   VecDestroy(&baij->slvec1b);
1001:   VecScatterDestroy(&baij->sMvctx);
1002:   PetscFree2(baij->rowvalues,baij->rowindices);
1003:   PetscFree(baij->barray);
1004:   PetscFree(baij->hd);
1005:   VecDestroy(&baij->diag);
1006:   VecDestroy(&baij->bb1);
1007:   VecDestroy(&baij->xx1);
1008: #if defined(PETSC_USE_REAL_MAT_SINGLE)
1009:   PetscFree(baij->setvaluescopy);
1010: #endif
1011:   PetscFree(baij->in_loc);
1012:   PetscFree(baij->v_loc);
1013:   PetscFree(baij->rangebs);
1014:   PetscFree(mat->data);

1016:   PetscObjectChangeTypeName((PetscObject)mat,NULL);
1017:   PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C",NULL);
1018:   PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C",NULL);
1019:   PetscObjectComposeFunction((PetscObject)mat,"MatMPISBAIJSetPreallocation_C",NULL);
1020:   PetscObjectComposeFunction((PetscObject)mat,"MatMPISBAIJSetPreallocationCSR_C",NULL);
1021: #if defined(PETSC_HAVE_ELEMENTAL)
1022:   PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpisbaij_elemental_C",NULL);
1023: #endif
1024: #if defined(PETSC_HAVE_SCALAPACK)
1025:   PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpisbaij_scalapack_C",NULL);
1026: #endif
1027:   PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpisbaij_mpiaij_C",NULL);
1028:   PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpisbaij_mpibaij_C",NULL);
1029:   return 0;
1030: }

1032: PetscErrorCode MatMult_MPISBAIJ_Hermitian(Mat A,Vec xx,Vec yy)
1033: {
1034:   Mat_MPISBAIJ      *a = (Mat_MPISBAIJ*)A->data;
1035:   PetscInt          mbs=a->mbs,bs=A->rmap->bs;
1036:   PetscScalar       *from;
1037:   const PetscScalar *x;

1039:   /* diagonal part */
1040:   (*a->A->ops->mult)(a->A,xx,a->slvec1a);
1041:   VecSet(a->slvec1b,0.0);

1043:   /* subdiagonal part */
1045:   (*a->B->ops->multhermitiantranspose)(a->B,xx,a->slvec0b);

1047:   /* copy x into the vec slvec0 */
1048:   VecGetArray(a->slvec0,&from);
1049:   VecGetArrayRead(xx,&x);

1051:   PetscArraycpy(from,x,bs*mbs);
1052:   VecRestoreArray(a->slvec0,&from);
1053:   VecRestoreArrayRead(xx,&x);

1055:   VecScatterBegin(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);
1056:   VecScatterEnd(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);
1057:   /* supperdiagonal part */
1058:   (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,yy);
1059:   return 0;
1060: }

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

1069:   /* diagonal part */
1070:   (*a->A->ops->mult)(a->A,xx,a->slvec1a);
1071:   VecSet(a->slvec1b,0.0);

1073:   /* subdiagonal part */
1074:   (*a->B->ops->multtranspose)(a->B,xx,a->slvec0b);

1076:   /* copy x into the vec slvec0 */
1077:   VecGetArray(a->slvec0,&from);
1078:   VecGetArrayRead(xx,&x);

1080:   PetscArraycpy(from,x,bs*mbs);
1081:   VecRestoreArray(a->slvec0,&from);
1082:   VecRestoreArrayRead(xx,&x);

1084:   VecScatterBegin(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);
1085:   VecScatterEnd(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);
1086:   /* supperdiagonal part */
1087:   (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,yy);
1088:   return 0;
1089: }

1091: PetscErrorCode MatMultAdd_MPISBAIJ_Hermitian(Mat A,Vec xx,Vec yy,Vec zz)
1092: {
1093:   Mat_MPISBAIJ      *a = (Mat_MPISBAIJ*)A->data;
1094:   PetscInt          mbs=a->mbs,bs=A->rmap->bs;
1095:   PetscScalar       *from,zero=0.0;
1096:   const PetscScalar *x;

1098:   /* diagonal part */
1099:   (*a->A->ops->multadd)(a->A,xx,yy,a->slvec1a);
1100:   VecSet(a->slvec1b,zero);

1102:   /* subdiagonal part */
1104:   (*a->B->ops->multhermitiantranspose)(a->B,xx,a->slvec0b);

1106:   /* copy x into the vec slvec0 */
1107:   VecGetArray(a->slvec0,&from);
1108:   VecGetArrayRead(xx,&x);
1109:   PetscArraycpy(from,x,bs*mbs);
1110:   VecRestoreArray(a->slvec0,&from);

1112:   VecScatterBegin(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);
1113:   VecRestoreArrayRead(xx,&x);
1114:   VecScatterEnd(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);

1116:   /* supperdiagonal part */
1117:   (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,zz);
1118:   return 0;
1119: }

1121: PetscErrorCode MatMultAdd_MPISBAIJ(Mat A,Vec xx,Vec yy,Vec zz)
1122: {
1123:   Mat_MPISBAIJ      *a = (Mat_MPISBAIJ*)A->data;
1124:   PetscInt          mbs=a->mbs,bs=A->rmap->bs;
1125:   PetscScalar       *from,zero=0.0;
1126:   const PetscScalar *x;

1128:   /* diagonal part */
1129:   (*a->A->ops->multadd)(a->A,xx,yy,a->slvec1a);
1130:   VecSet(a->slvec1b,zero);

1132:   /* subdiagonal part */
1133:   (*a->B->ops->multtranspose)(a->B,xx,a->slvec0b);

1135:   /* copy x into the vec slvec0 */
1136:   VecGetArray(a->slvec0,&from);
1137:   VecGetArrayRead(xx,&x);
1138:   PetscArraycpy(from,x,bs*mbs);
1139:   VecRestoreArray(a->slvec0,&from);

1141:   VecScatterBegin(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);
1142:   VecRestoreArrayRead(xx,&x);
1143:   VecScatterEnd(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);

1145:   /* supperdiagonal part */
1146:   (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,zz);
1147:   return 0;
1148: }

1150: /*
1151:   This only works correctly for square matrices where the subblock A->A is the
1152:    diagonal block
1153: */
1154: PetscErrorCode MatGetDiagonal_MPISBAIJ(Mat A,Vec v)
1155: {
1156:   Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data;

1159:   MatGetDiagonal(a->A,v);
1160:   return 0;
1161: }

1163: PetscErrorCode MatScale_MPISBAIJ(Mat A,PetscScalar aa)
1164: {
1165:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;

1167:   MatScale(a->A,aa);
1168:   MatScale(a->B,aa);
1169:   return 0;
1170: }

1172: PetscErrorCode MatGetRow_MPISBAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
1173: {
1174:   Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)matin->data;
1175:   PetscScalar  *vworkA,*vworkB,**pvA,**pvB,*v_p;
1176:   PetscInt     bs = matin->rmap->bs,bs2 = mat->bs2,i,*cworkA,*cworkB,**pcA,**pcB;
1177:   PetscInt     nztot,nzA,nzB,lrow,brstart = matin->rmap->rstart,brend = matin->rmap->rend;
1178:   PetscInt    *cmap,*idx_p,cstart = mat->rstartbs;

1181:   mat->getrowactive = PETSC_TRUE;

1183:   if (!mat->rowvalues && (idx || v)) {
1184:     /*
1185:         allocate enough space to hold information from the longest row.
1186:     */
1187:     Mat_SeqSBAIJ *Aa = (Mat_SeqSBAIJ*)mat->A->data;
1188:     Mat_SeqBAIJ  *Ba = (Mat_SeqBAIJ*)mat->B->data;
1189:     PetscInt     max = 1,mbs = mat->mbs,tmp;
1190:     for (i=0; i<mbs; i++) {
1191:       tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; /* row length */
1192:       if (max < tmp) max = tmp;
1193:     }
1194:     PetscMalloc2(max*bs2,&mat->rowvalues,max*bs2,&mat->rowindices);
1195:   }

1198:   lrow = row - brstart;  /* local row index */

1200:   pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB;
1201:   if (!v)   {pvA = NULL; pvB = NULL;}
1202:   if (!idx) {pcA = NULL; if (!v) pcB = NULL;}
1203:   (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);
1204:   (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);
1205:   nztot = nzA + nzB;

1207:   cmap = mat->garray;
1208:   if (v  || idx) {
1209:     if (nztot) {
1210:       /* Sort by increasing column numbers, assuming A and B already sorted */
1211:       PetscInt imark = -1;
1212:       if (v) {
1213:         *v = v_p = mat->rowvalues;
1214:         for (i=0; i<nzB; i++) {
1215:           if (cmap[cworkB[i]/bs] < cstart) v_p[i] = vworkB[i];
1216:           else break;
1217:         }
1218:         imark = i;
1219:         for (i=0; i<nzA; i++)     v_p[imark+i] = vworkA[i];
1220:         for (i=imark; i<nzB; i++) v_p[nzA+i]   = vworkB[i];
1221:       }
1222:       if (idx) {
1223:         *idx = idx_p = mat->rowindices;
1224:         if (imark > -1) {
1225:           for (i=0; i<imark; i++) {
1226:             idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs;
1227:           }
1228:         } else {
1229:           for (i=0; i<nzB; i++) {
1230:             if (cmap[cworkB[i]/bs] < cstart) idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs;
1231:             else break;
1232:           }
1233:           imark = i;
1234:         }
1235:         for (i=0; i<nzA; i++)     idx_p[imark+i] = cstart*bs + cworkA[i];
1236:         for (i=imark; i<nzB; i++) idx_p[nzA+i]   = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ;
1237:       }
1238:     } else {
1239:       if (idx) *idx = NULL;
1240:       if (v)   *v   = NULL;
1241:     }
1242:   }
1243:   *nz  = nztot;
1244:   (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);
1245:   (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);
1246:   return 0;
1247: }

1249: PetscErrorCode MatRestoreRow_MPISBAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
1250: {
1251:   Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data;

1254:   baij->getrowactive = PETSC_FALSE;
1255:   return 0;
1256: }

1258: PetscErrorCode MatGetRowUpperTriangular_MPISBAIJ(Mat A)
1259: {
1260:   Mat_MPISBAIJ *a  = (Mat_MPISBAIJ*)A->data;
1261:   Mat_SeqSBAIJ *aA = (Mat_SeqSBAIJ*)a->A->data;

1263:   aA->getrow_utriangular = PETSC_TRUE;
1264:   return 0;
1265: }
1266: PetscErrorCode MatRestoreRowUpperTriangular_MPISBAIJ(Mat A)
1267: {
1268:   Mat_MPISBAIJ *a  = (Mat_MPISBAIJ*)A->data;
1269:   Mat_SeqSBAIJ *aA = (Mat_SeqSBAIJ*)a->A->data;

1271:   aA->getrow_utriangular = PETSC_FALSE;
1272:   return 0;
1273: }

1275: PetscErrorCode MatConjugate_MPISBAIJ(Mat mat)
1276: {
1277:   if (PetscDefined(USE_COMPLEX)) {
1278:     Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)mat->data;

1280:     MatConjugate(a->A);
1281:     MatConjugate(a->B);
1282:   }
1283:   return 0;
1284: }

1286: PetscErrorCode MatRealPart_MPISBAIJ(Mat A)
1287: {
1288:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;

1290:   MatRealPart(a->A);
1291:   MatRealPart(a->B);
1292:   return 0;
1293: }

1295: PetscErrorCode MatImaginaryPart_MPISBAIJ(Mat A)
1296: {
1297:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;

1299:   MatImaginaryPart(a->A);
1300:   MatImaginaryPart(a->B);
1301:   return 0;
1302: }

1304: /* Check if isrow is a subset of iscol_local, called by MatCreateSubMatrix_MPISBAIJ()
1305:    Input: isrow       - distributed(parallel),
1306:           iscol_local - locally owned (seq)
1307: */
1308: PetscErrorCode ISEqual_private(IS isrow,IS iscol_local,PetscBool  *flg)
1309: {
1310:   PetscInt       sz1,sz2,*a1,*a2,i,j,k,nmatch;
1311:   const PetscInt *ptr1,*ptr2;

1313:   ISGetLocalSize(isrow,&sz1);
1314:   ISGetLocalSize(iscol_local,&sz2);
1315:   if (sz1 > sz2) {
1316:     *flg = PETSC_FALSE;
1317:     return 0;
1318:   }

1320:   ISGetIndices(isrow,&ptr1);
1321:   ISGetIndices(iscol_local,&ptr2);

1323:   PetscMalloc1(sz1,&a1);
1324:   PetscMalloc1(sz2,&a2);
1325:   PetscArraycpy(a1,ptr1,sz1);
1326:   PetscArraycpy(a2,ptr2,sz2);
1327:   PetscSortInt(sz1,a1);
1328:   PetscSortInt(sz2,a2);

1330:   nmatch=0;
1331:   k     = 0;
1332:   for (i=0; i<sz1; i++) {
1333:     for (j=k; j<sz2; j++) {
1334:       if (a1[i] == a2[j]) {
1335:         k = j; nmatch++;
1336:         break;
1337:       }
1338:     }
1339:   }
1340:   ISRestoreIndices(isrow,&ptr1);
1341:   ISRestoreIndices(iscol_local,&ptr2);
1342:   PetscFree(a1);
1343:   PetscFree(a2);
1344:   if (nmatch < sz1) {
1345:     *flg = PETSC_FALSE;
1346:   } else {
1347:     *flg = PETSC_TRUE;
1348:   }
1349:   return 0;
1350: }

1352: PetscErrorCode MatCreateSubMatrix_MPISBAIJ(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat)
1353: {
1354:   IS             iscol_local;
1355:   PetscInt       csize;
1356:   PetscBool      isequal;

1358:   ISGetLocalSize(iscol,&csize);
1359:   if (call == MAT_REUSE_MATRIX) {
1360:     PetscObjectQuery((PetscObject)*newmat,"ISAllGather",(PetscObject*)&iscol_local);
1362:   } else {
1363:     PetscBool issorted;

1365:     ISAllGather(iscol,&iscol_local);
1366:     ISEqual_private(isrow,iscol_local,&isequal);
1367:     ISSorted(iscol_local, &issorted);
1369:   }

1371:   /* now call MatCreateSubMatrix_MPIBAIJ() */
1372:   MatCreateSubMatrix_MPIBAIJ_Private(mat,isrow,iscol_local,csize,call,newmat);
1373:   if (call == MAT_INITIAL_MATRIX) {
1374:     PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);
1375:     ISDestroy(&iscol_local);
1376:   }
1377:   return 0;
1378: }

1380: PetscErrorCode MatZeroEntries_MPISBAIJ(Mat A)
1381: {
1382:   Mat_MPISBAIJ   *l = (Mat_MPISBAIJ*)A->data;

1384:   MatZeroEntries(l->A);
1385:   MatZeroEntries(l->B);
1386:   return 0;
1387: }

1389: PetscErrorCode MatGetInfo_MPISBAIJ(Mat matin,MatInfoType flag,MatInfo *info)
1390: {
1391:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)matin->data;
1392:   Mat            A  = a->A,B = a->B;
1393:   PetscLogDouble isend[5],irecv[5];

1395:   info->block_size = (PetscReal)matin->rmap->bs;

1397:   MatGetInfo(A,MAT_LOCAL,info);

1399:   isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded;
1400:   isend[3] = info->memory;  isend[4] = info->mallocs;

1402:   MatGetInfo(B,MAT_LOCAL,info);

1404:   isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded;
1405:   isend[3] += info->memory;  isend[4] += info->mallocs;
1406:   if (flag == MAT_LOCAL) {
1407:     info->nz_used      = isend[0];
1408:     info->nz_allocated = isend[1];
1409:     info->nz_unneeded  = isend[2];
1410:     info->memory       = isend[3];
1411:     info->mallocs      = isend[4];
1412:   } else if (flag == MAT_GLOBAL_MAX) {
1413:     MPIU_Allreduce(isend,irecv,5,MPIU_PETSCLOGDOUBLE,MPI_MAX,PetscObjectComm((PetscObject)matin));

1415:     info->nz_used      = irecv[0];
1416:     info->nz_allocated = irecv[1];
1417:     info->nz_unneeded  = irecv[2];
1418:     info->memory       = irecv[3];
1419:     info->mallocs      = irecv[4];
1420:   } else if (flag == MAT_GLOBAL_SUM) {
1421:     MPIU_Allreduce(isend,irecv,5,MPIU_PETSCLOGDOUBLE,MPI_SUM,PetscObjectComm((PetscObject)matin));

1423:     info->nz_used      = irecv[0];
1424:     info->nz_allocated = irecv[1];
1425:     info->nz_unneeded  = irecv[2];
1426:     info->memory       = irecv[3];
1427:     info->mallocs      = irecv[4];
1428:   } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Unknown MatInfoType argument %d",(int)flag);
1429:   info->fill_ratio_given  = 0; /* no parallel LU/ILU/Cholesky */
1430:   info->fill_ratio_needed = 0;
1431:   info->factor_mallocs    = 0;
1432:   return 0;
1433: }

1435: PetscErrorCode MatSetOption_MPISBAIJ(Mat A,MatOption op,PetscBool flg)
1436: {
1437:   Mat_MPISBAIJ   *a  = (Mat_MPISBAIJ*)A->data;
1438:   Mat_SeqSBAIJ   *aA = (Mat_SeqSBAIJ*)a->A->data;

1440:   switch (op) {
1441:   case MAT_NEW_NONZERO_LOCATIONS:
1442:   case MAT_NEW_NONZERO_ALLOCATION_ERR:
1443:   case MAT_UNUSED_NONZERO_LOCATION_ERR:
1444:   case MAT_KEEP_NONZERO_PATTERN:
1445:   case MAT_SUBMAT_SINGLEIS:
1446:   case MAT_NEW_NONZERO_LOCATION_ERR:
1447:     MatCheckPreallocated(A,1);
1448:     MatSetOption(a->A,op,flg);
1449:     MatSetOption(a->B,op,flg);
1450:     break;
1451:   case MAT_ROW_ORIENTED:
1452:     MatCheckPreallocated(A,1);
1453:     a->roworiented = flg;

1455:     MatSetOption(a->A,op,flg);
1456:     MatSetOption(a->B,op,flg);
1457:     break;
1458:   case MAT_FORCE_DIAGONAL_ENTRIES:
1459:   case MAT_SORTED_FULL:
1460:     PetscInfo(A,"Option %s ignored\n",MatOptions[op]);
1461:     break;
1462:   case MAT_IGNORE_OFF_PROC_ENTRIES:
1463:     a->donotstash = flg;
1464:     break;
1465:   case MAT_USE_HASH_TABLE:
1466:     a->ht_flag = flg;
1467:     break;
1468:   case MAT_HERMITIAN:
1469:     MatCheckPreallocated(A,1);
1470:     MatSetOption(a->A,op,flg);
1471: #if defined(PETSC_USE_COMPLEX)
1472:     if (flg) { /* need different mat-vec ops */
1473:       A->ops->mult             = MatMult_MPISBAIJ_Hermitian;
1474:       A->ops->multadd          = MatMultAdd_MPISBAIJ_Hermitian;
1475:       A->ops->multtranspose    = NULL;
1476:       A->ops->multtransposeadd = NULL;
1477:       A->symmetric = PETSC_FALSE;
1478:     }
1479: #endif
1480:     break;
1481:   case MAT_SPD:
1482:   case MAT_SYMMETRIC:
1483:     MatCheckPreallocated(A,1);
1484:     MatSetOption(a->A,op,flg);
1485: #if defined(PETSC_USE_COMPLEX)
1486:     if (flg) { /* restore to use default mat-vec ops */
1487:       A->ops->mult             = MatMult_MPISBAIJ;
1488:       A->ops->multadd          = MatMultAdd_MPISBAIJ;
1489:       A->ops->multtranspose    = MatMult_MPISBAIJ;
1490:       A->ops->multtransposeadd = MatMultAdd_MPISBAIJ;
1491:     }
1492: #endif
1493:     break;
1494:   case MAT_STRUCTURALLY_SYMMETRIC:
1495:     MatCheckPreallocated(A,1);
1496:     MatSetOption(a->A,op,flg);
1497:     break;
1498:   case MAT_SYMMETRY_ETERNAL:
1500:     PetscInfo(A,"Option %s ignored\n",MatOptions[op]);
1501:     break;
1502:   case MAT_IGNORE_LOWER_TRIANGULAR:
1503:     aA->ignore_ltriangular = flg;
1504:     break;
1505:   case MAT_ERROR_LOWER_TRIANGULAR:
1506:     aA->ignore_ltriangular = flg;
1507:     break;
1508:   case MAT_GETROW_UPPERTRIANGULAR:
1509:     aA->getrow_utriangular = flg;
1510:     break;
1511:   default:
1512:     SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %d",op);
1513:   }
1514:   return 0;
1515: }

1517: PetscErrorCode MatTranspose_MPISBAIJ(Mat A,MatReuse reuse,Mat *B)
1518: {
1519:   if (reuse == MAT_INITIAL_MATRIX) {
1520:     MatDuplicate(A,MAT_COPY_VALUES,B);
1521:   }  else if (reuse == MAT_REUSE_MATRIX) {
1522:     MatCopy(A,*B,SAME_NONZERO_PATTERN);
1523:   }
1524:   return 0;
1525: }

1527: PetscErrorCode MatDiagonalScale_MPISBAIJ(Mat mat,Vec ll,Vec rr)
1528: {
1529:   Mat_MPISBAIJ   *baij = (Mat_MPISBAIJ*)mat->data;
1530:   Mat            a     = baij->A, b=baij->B;
1531:   PetscInt       nv,m,n;
1532:   PetscBool      flg;

1534:   if (ll != rr) {
1535:     VecEqual(ll,rr,&flg);
1537:   }
1538:   if (!ll) return 0;

1540:   MatGetLocalSize(mat,&m,&n);

1543:   VecGetLocalSize(rr,&nv);

1546:   VecScatterBegin(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);

1548:   /* left diagonalscale the off-diagonal part */
1549:   (*b->ops->diagonalscale)(b,ll,NULL);

1551:   /* scale the diagonal part */
1552:   (*a->ops->diagonalscale)(a,ll,rr);

1554:   /* right diagonalscale the off-diagonal part */
1555:   VecScatterEnd(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);
1556:   (*b->ops->diagonalscale)(b,NULL,baij->lvec);
1557:   return 0;
1558: }

1560: PetscErrorCode MatSetUnfactored_MPISBAIJ(Mat A)
1561: {
1562:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;

1564:   MatSetUnfactored(a->A);
1565:   return 0;
1566: }

1568: static PetscErrorCode MatDuplicate_MPISBAIJ(Mat,MatDuplicateOption,Mat*);

1570: PetscErrorCode MatEqual_MPISBAIJ(Mat A,Mat B,PetscBool  *flag)
1571: {
1572:   Mat_MPISBAIJ   *matB = (Mat_MPISBAIJ*)B->data,*matA = (Mat_MPISBAIJ*)A->data;
1573:   Mat            a,b,c,d;
1574:   PetscBool      flg;

1576:   a = matA->A; b = matA->B;
1577:   c = matB->A; d = matB->B;

1579:   MatEqual(a,c,&flg);
1580:   if (flg) {
1581:     MatEqual(b,d,&flg);
1582:   }
1583:   MPIU_Allreduce(&flg,flag,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)A));
1584:   return 0;
1585: }

1587: PetscErrorCode MatCopy_MPISBAIJ(Mat A,Mat B,MatStructure str)
1588: {
1589:   PetscBool      isbaij;

1591:   PetscObjectTypeCompareAny((PetscObject)B,&isbaij,MATSEQSBAIJ,MATMPISBAIJ,"");
1593:   /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */
1594:   if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) {
1595:     MatGetRowUpperTriangular(A);
1596:     MatCopy_Basic(A,B,str);
1597:     MatRestoreRowUpperTriangular(A);
1598:   } else {
1599:     Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data;
1600:     Mat_MPISBAIJ *b = (Mat_MPISBAIJ*)B->data;

1602:     MatCopy(a->A,b->A,str);
1603:     MatCopy(a->B,b->B,str);
1604:   }
1605:   PetscObjectStateIncrease((PetscObject)B);
1606:   return 0;
1607: }

1609: PetscErrorCode MatSetUp_MPISBAIJ(Mat A)
1610: {
1611:   MatMPISBAIJSetPreallocation(A,A->rmap->bs,PETSC_DEFAULT,NULL,PETSC_DEFAULT,NULL);
1612:   return 0;
1613: }

1615: PetscErrorCode MatAXPY_MPISBAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str)
1616: {
1617:   Mat_MPISBAIJ   *xx=(Mat_MPISBAIJ*)X->data,*yy=(Mat_MPISBAIJ*)Y->data;
1618:   PetscBLASInt   bnz,one=1;
1619:   Mat_SeqSBAIJ   *xa,*ya;
1620:   Mat_SeqBAIJ    *xb,*yb;

1622:   if (str == SAME_NONZERO_PATTERN) {
1623:     PetscScalar alpha = a;
1624:     xa   = (Mat_SeqSBAIJ*)xx->A->data;
1625:     ya   = (Mat_SeqSBAIJ*)yy->A->data;
1626:     PetscBLASIntCast(xa->nz,&bnz);
1627:     PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,xa->a,&one,ya->a,&one));
1628:     xb   = (Mat_SeqBAIJ*)xx->B->data;
1629:     yb   = (Mat_SeqBAIJ*)yy->B->data;
1630:     PetscBLASIntCast(xb->nz,&bnz);
1631:     PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,xb->a,&one,yb->a,&one));
1632:     PetscObjectStateIncrease((PetscObject)Y);
1633:   } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */
1634:     MatSetOption(X,MAT_GETROW_UPPERTRIANGULAR,PETSC_TRUE);
1635:     MatAXPY_Basic(Y,a,X,str);
1636:     MatSetOption(X,MAT_GETROW_UPPERTRIANGULAR,PETSC_FALSE);
1637:   } else {
1638:     Mat      B;
1639:     PetscInt *nnz_d,*nnz_o,bs=Y->rmap->bs;
1641:     MatGetRowUpperTriangular(X);
1642:     MatGetRowUpperTriangular(Y);
1643:     PetscMalloc1(yy->A->rmap->N,&nnz_d);
1644:     PetscMalloc1(yy->B->rmap->N,&nnz_o);
1645:     MatCreate(PetscObjectComm((PetscObject)Y),&B);
1646:     PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);
1647:     MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);
1648:     MatSetBlockSizesFromMats(B,Y,Y);
1649:     MatSetType(B,MATMPISBAIJ);
1650:     MatAXPYGetPreallocation_SeqSBAIJ(yy->A,xx->A,nnz_d);
1651:     MatAXPYGetPreallocation_MPIBAIJ(yy->B,yy->garray,xx->B,xx->garray,nnz_o);
1652:     MatMPISBAIJSetPreallocation(B,bs,0,nnz_d,0,nnz_o);
1653:     MatAXPY_BasicWithPreallocation(B,Y,a,X,str);
1654:     MatHeaderMerge(Y,&B);
1655:     PetscFree(nnz_d);
1656:     PetscFree(nnz_o);
1657:     MatRestoreRowUpperTriangular(X);
1658:     MatRestoreRowUpperTriangular(Y);
1659:   }
1660:   return 0;
1661: }

1663: PetscErrorCode MatCreateSubMatrices_MPISBAIJ(Mat A,PetscInt n,const IS irow[],const IS icol[],MatReuse scall,Mat *B[])
1664: {
1665:   PetscInt       i;
1666:   PetscBool      flg;

1668:   MatCreateSubMatrices_MPIBAIJ(A,n,irow,icol,scall,B); /* B[] are sbaij matrices */
1669:   for (i=0; i<n; i++) {
1670:     ISEqual(irow[i],icol[i],&flg);
1671:     if (!flg) {
1672:       MatSeqSBAIJZeroOps_Private(*B[i]);
1673:     }
1674:   }
1675:   return 0;
1676: }

1678: PetscErrorCode MatShift_MPISBAIJ(Mat Y,PetscScalar a)
1679: {
1680:   Mat_MPISBAIJ    *maij = (Mat_MPISBAIJ*)Y->data;
1681:   Mat_SeqSBAIJ    *aij = (Mat_SeqSBAIJ*)maij->A->data;

1683:   if (!Y->preallocated) {
1684:     MatMPISBAIJSetPreallocation(Y,Y->rmap->bs,1,NULL,0,NULL);
1685:   } else if (!aij->nz) {
1686:     PetscInt nonew = aij->nonew;
1687:     MatSeqSBAIJSetPreallocation(maij->A,Y->rmap->bs,1,NULL);
1688:     aij->nonew = nonew;
1689:   }
1690:   MatShift_Basic(Y,a);
1691:   return 0;
1692: }

1694: PetscErrorCode MatMissingDiagonal_MPISBAIJ(Mat A,PetscBool  *missing,PetscInt *d)
1695: {
1696:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;

1699:   MatMissingDiagonal(a->A,missing,d);
1700:   if (d) {
1701:     PetscInt rstart;
1702:     MatGetOwnershipRange(A,&rstart,NULL);
1703:     *d += rstart/A->rmap->bs;

1705:   }
1706:   return 0;
1707: }

1709: PetscErrorCode  MatGetDiagonalBlock_MPISBAIJ(Mat A,Mat *a)
1710: {
1711:   *a = ((Mat_MPISBAIJ*)A->data)->A;
1712:   return 0;
1713: }

1715: /* -------------------------------------------------------------------*/
1716: static struct _MatOps MatOps_Values = {MatSetValues_MPISBAIJ,
1717:                                        MatGetRow_MPISBAIJ,
1718:                                        MatRestoreRow_MPISBAIJ,
1719:                                        MatMult_MPISBAIJ,
1720:                                /*  4*/ MatMultAdd_MPISBAIJ,
1721:                                        MatMult_MPISBAIJ,       /* transpose versions are same as non-transpose */
1722:                                        MatMultAdd_MPISBAIJ,
1723:                                        NULL,
1724:                                        NULL,
1725:                                        NULL,
1726:                                /* 10*/ NULL,
1727:                                        NULL,
1728:                                        NULL,
1729:                                        MatSOR_MPISBAIJ,
1730:                                        MatTranspose_MPISBAIJ,
1731:                                /* 15*/ MatGetInfo_MPISBAIJ,
1732:                                        MatEqual_MPISBAIJ,
1733:                                        MatGetDiagonal_MPISBAIJ,
1734:                                        MatDiagonalScale_MPISBAIJ,
1735:                                        MatNorm_MPISBAIJ,
1736:                                /* 20*/ MatAssemblyBegin_MPISBAIJ,
1737:                                        MatAssemblyEnd_MPISBAIJ,
1738:                                        MatSetOption_MPISBAIJ,
1739:                                        MatZeroEntries_MPISBAIJ,
1740:                                /* 24*/ NULL,
1741:                                        NULL,
1742:                                        NULL,
1743:                                        NULL,
1744:                                        NULL,
1745:                                /* 29*/ MatSetUp_MPISBAIJ,
1746:                                        NULL,
1747:                                        NULL,
1748:                                        MatGetDiagonalBlock_MPISBAIJ,
1749:                                        NULL,
1750:                                /* 34*/ MatDuplicate_MPISBAIJ,
1751:                                        NULL,
1752:                                        NULL,
1753:                                        NULL,
1754:                                        NULL,
1755:                                /* 39*/ MatAXPY_MPISBAIJ,
1756:                                        MatCreateSubMatrices_MPISBAIJ,
1757:                                        MatIncreaseOverlap_MPISBAIJ,
1758:                                        MatGetValues_MPISBAIJ,
1759:                                        MatCopy_MPISBAIJ,
1760:                                /* 44*/ NULL,
1761:                                        MatScale_MPISBAIJ,
1762:                                        MatShift_MPISBAIJ,
1763:                                        NULL,
1764:                                        NULL,
1765:                                /* 49*/ NULL,
1766:                                        NULL,
1767:                                        NULL,
1768:                                        NULL,
1769:                                        NULL,
1770:                                /* 54*/ NULL,
1771:                                        NULL,
1772:                                        MatSetUnfactored_MPISBAIJ,
1773:                                        NULL,
1774:                                        MatSetValuesBlocked_MPISBAIJ,
1775:                                /* 59*/ MatCreateSubMatrix_MPISBAIJ,
1776:                                        NULL,
1777:                                        NULL,
1778:                                        NULL,
1779:                                        NULL,
1780:                                /* 64*/ NULL,
1781:                                        NULL,
1782:                                        NULL,
1783:                                        NULL,
1784:                                        NULL,
1785:                                /* 69*/ MatGetRowMaxAbs_MPISBAIJ,
1786:                                        NULL,
1787:                                        MatConvert_MPISBAIJ_Basic,
1788:                                        NULL,
1789:                                        NULL,
1790:                                /* 74*/ NULL,
1791:                                        NULL,
1792:                                        NULL,
1793:                                        NULL,
1794:                                        NULL,
1795:                                /* 79*/ NULL,
1796:                                        NULL,
1797:                                        NULL,
1798:                                        NULL,
1799:                                        MatLoad_MPISBAIJ,
1800:                                /* 84*/ NULL,
1801:                                        NULL,
1802:                                        NULL,
1803:                                        NULL,
1804:                                        NULL,
1805:                                /* 89*/ NULL,
1806:                                        NULL,
1807:                                        NULL,
1808:                                        NULL,
1809:                                        NULL,
1810:                                /* 94*/ NULL,
1811:                                        NULL,
1812:                                        NULL,
1813:                                        NULL,
1814:                                        NULL,
1815:                                /* 99*/ NULL,
1816:                                        NULL,
1817:                                        NULL,
1818:                                        MatConjugate_MPISBAIJ,
1819:                                        NULL,
1820:                                /*104*/ NULL,
1821:                                        MatRealPart_MPISBAIJ,
1822:                                        MatImaginaryPart_MPISBAIJ,
1823:                                        MatGetRowUpperTriangular_MPISBAIJ,
1824:                                        MatRestoreRowUpperTriangular_MPISBAIJ,
1825:                                /*109*/ NULL,
1826:                                        NULL,
1827:                                        NULL,
1828:                                        NULL,
1829:                                        MatMissingDiagonal_MPISBAIJ,
1830:                                /*114*/ NULL,
1831:                                        NULL,
1832:                                        NULL,
1833:                                        NULL,
1834:                                        NULL,
1835:                                /*119*/ NULL,
1836:                                        NULL,
1837:                                        NULL,
1838:                                        NULL,
1839:                                        NULL,
1840:                                /*124*/ NULL,
1841:                                        NULL,
1842:                                        NULL,
1843:                                        NULL,
1844:                                        NULL,
1845:                                /*129*/ NULL,
1846:                                        NULL,
1847:                                        NULL,
1848:                                        NULL,
1849:                                        NULL,
1850:                                /*134*/ NULL,
1851:                                        NULL,
1852:                                        NULL,
1853:                                        NULL,
1854:                                        NULL,
1855:                                /*139*/ MatSetBlockSizes_Default,
1856:                                        NULL,
1857:                                        NULL,
1858:                                        NULL,
1859:                                        NULL,
1860:                                 /*144*/MatCreateMPIMatConcatenateSeqMat_MPISBAIJ,
1861:                                        NULL,
1862:                                        NULL,
1863:                                        NULL
1864: };

1866: PetscErrorCode  MatMPISBAIJSetPreallocation_MPISBAIJ(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt *d_nnz,PetscInt o_nz,const PetscInt *o_nnz)
1867: {
1868:   Mat_MPISBAIJ   *b = (Mat_MPISBAIJ*)B->data;
1869:   PetscInt       i,mbs,Mbs;
1870:   PetscMPIInt    size;

1872:   MatSetBlockSize(B,PetscAbs(bs));
1873:   PetscLayoutSetUp(B->rmap);
1874:   PetscLayoutSetUp(B->cmap);
1875:   PetscLayoutGetBlockSize(B->rmap,&bs);

1879:   mbs = B->rmap->n/bs;
1880:   Mbs = B->rmap->N/bs;

1883:   B->rmap->bs = bs;
1884:   b->bs2      = bs*bs;
1885:   b->mbs      = mbs;
1886:   b->Mbs      = Mbs;
1887:   b->nbs      = B->cmap->n/bs;
1888:   b->Nbs      = B->cmap->N/bs;

1890:   for (i=0; i<=b->size; i++) {
1891:     b->rangebs[i] = B->rmap->range[i]/bs;
1892:   }
1893:   b->rstartbs = B->rmap->rstart/bs;
1894:   b->rendbs   = B->rmap->rend/bs;

1896:   b->cstartbs = B->cmap->rstart/bs;
1897:   b->cendbs   = B->cmap->rend/bs;

1899: #if defined(PETSC_USE_CTABLE)
1900:   PetscTableDestroy(&b->colmap);
1901: #else
1902:   PetscFree(b->colmap);
1903: #endif
1904:   PetscFree(b->garray);
1905:   VecDestroy(&b->lvec);
1906:   VecScatterDestroy(&b->Mvctx);
1907:   VecDestroy(&b->slvec0);
1908:   VecDestroy(&b->slvec0b);
1909:   VecDestroy(&b->slvec1);
1910:   VecDestroy(&b->slvec1a);
1911:   VecDestroy(&b->slvec1b);
1912:   VecScatterDestroy(&b->sMvctx);

1914:   /* Because the B will have been resized we simply destroy it and create a new one each time */
1915:   MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);
1916:   MatDestroy(&b->B);
1917:   MatCreate(PETSC_COMM_SELF,&b->B);
1918:   MatSetSizes(b->B,B->rmap->n,size > 1 ? B->cmap->N : 0,B->rmap->n,size > 1 ? B->cmap->N : 0);
1919:   MatSetType(b->B,MATSEQBAIJ);
1920:   PetscLogObjectParent((PetscObject)B,(PetscObject)b->B);

1922:   if (!B->preallocated) {
1923:     MatCreate(PETSC_COMM_SELF,&b->A);
1924:     MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);
1925:     MatSetType(b->A,MATSEQSBAIJ);
1926:     PetscLogObjectParent((PetscObject)B,(PetscObject)b->A);
1927:     MatStashCreate_Private(PetscObjectComm((PetscObject)B),bs,&B->bstash);
1928:   }

1930:   MatSeqSBAIJSetPreallocation(b->A,bs,d_nz,d_nnz);
1931:   MatSeqBAIJSetPreallocation(b->B,bs,o_nz,o_nnz);

1933:   B->preallocated  = PETSC_TRUE;
1934:   B->was_assembled = PETSC_FALSE;
1935:   B->assembled     = PETSC_FALSE;
1936:   return 0;
1937: }

1939: PetscErrorCode MatMPISBAIJSetPreallocationCSR_MPISBAIJ(Mat B,PetscInt bs,const PetscInt ii[],const PetscInt jj[],const PetscScalar V[])
1940: {
1941:   PetscInt       m,rstart,cend;
1942:   PetscInt       i,j,d,nz,bd, nz_max=0,*d_nnz=NULL,*o_nnz=NULL;
1943:   const PetscInt *JJ    =NULL;
1944:   PetscScalar    *values=NULL;
1945:   PetscBool      roworiented = ((Mat_MPISBAIJ*)B->data)->roworiented;
1946:   PetscBool      nooffprocentries;

1949:   PetscLayoutSetBlockSize(B->rmap,bs);
1950:   PetscLayoutSetBlockSize(B->cmap,bs);
1951:   PetscLayoutSetUp(B->rmap);
1952:   PetscLayoutSetUp(B->cmap);
1953:   PetscLayoutGetBlockSize(B->rmap,&bs);
1954:   m      = B->rmap->n/bs;
1955:   rstart = B->rmap->rstart/bs;
1956:   cend   = B->cmap->rend/bs;

1959:   PetscMalloc2(m,&d_nnz,m,&o_nnz);
1960:   for (i=0; i<m; i++) {
1961:     nz = ii[i+1] - ii[i];
1963:     /* count the ones on the diagonal and above, split into diagonal and off diagonal portions. */
1964:     JJ     = jj + ii[i];
1965:     bd     = 0;
1966:     for (j=0; j<nz; j++) {
1967:       if (*JJ >= i + rstart) break;
1968:       JJ++;
1969:       bd++;
1970:     }
1971:     d  = 0;
1972:     for (; j<nz; j++) {
1973:       if (*JJ++ >= cend) break;
1974:       d++;
1975:     }
1976:     d_nnz[i] = d;
1977:     o_nnz[i] = nz - d - bd;
1978:     nz       = nz - bd;
1979:     nz_max = PetscMax(nz_max,nz);
1980:   }
1981:   MatMPISBAIJSetPreallocation(B,bs,0,d_nnz,0,o_nnz);
1982:   MatSetOption(B,MAT_IGNORE_LOWER_TRIANGULAR,PETSC_TRUE);
1983:   PetscFree2(d_nnz,o_nnz);

1985:   values = (PetscScalar*)V;
1986:   if (!values) {
1987:     PetscCalloc1(bs*bs*nz_max,&values);
1988:   }
1989:   for (i=0; i<m; i++) {
1990:     PetscInt          row    = i + rstart;
1991:     PetscInt          ncols  = ii[i+1] - ii[i];
1992:     const PetscInt    *icols = jj + ii[i];
1993:     if (bs == 1 || !roworiented) {         /* block ordering matches the non-nested layout of MatSetValues so we can insert entire rows */
1994:       const PetscScalar *svals = values + (V ? (bs*bs*ii[i]) : 0);
1995:       MatSetValuesBlocked_MPISBAIJ(B,1,&row,ncols,icols,svals,INSERT_VALUES);
1996:     } else {                    /* block ordering does not match so we can only insert one block at a time. */
1997:       PetscInt j;
1998:       for (j=0; j<ncols; j++) {
1999:         const PetscScalar *svals = values + (V ? (bs*bs*(ii[i]+j)) : 0);
2000:         MatSetValuesBlocked_MPISBAIJ(B,1,&row,1,&icols[j],svals,INSERT_VALUES);
2001:       }
2002:     }
2003:   }

2005:   if (!V) PetscFree(values);
2006:   nooffprocentries    = B->nooffprocentries;
2007:   B->nooffprocentries = PETSC_TRUE;
2008:   MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
2009:   MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);
2010:   B->nooffprocentries = nooffprocentries;

2012:   MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);
2013:   return 0;
2014: }

2016: /*MC
2017:    MATMPISBAIJ - MATMPISBAIJ = "mpisbaij" - A matrix type to be used for distributed symmetric sparse block matrices,
2018:    based on block compressed sparse row format.  Only the upper triangular portion of the "diagonal" portion of
2019:    the matrix is stored.

2021:    For complex numbers by default this matrix is symmetric, NOT Hermitian symmetric. To make it Hermitian symmetric you
2022:    can call MatSetOption(Mat, MAT_HERMITIAN);

2024:    Options Database Keys:
2025: . -mat_type mpisbaij - sets the matrix type to "mpisbaij" during a call to MatSetFromOptions()

2027:    Notes:
2028:      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
2029:      diagonal portion of the matrix of each process has to less than or equal the number of columns.

2031:    Level: beginner

2033: .seealso: MatCreateBAIJ(), MATSEQSBAIJ, MatType
2034: M*/

2036: PETSC_EXTERN PetscErrorCode MatCreate_MPISBAIJ(Mat B)
2037: {
2038:   Mat_MPISBAIJ   *b;
2040:   PetscBool      flg = PETSC_FALSE;

2042:   PetscNewLog(B,&b);
2043:   B->data = (void*)b;
2044:   PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));

2046:   B->ops->destroy = MatDestroy_MPISBAIJ;
2047:   B->ops->view    = MatView_MPISBAIJ;
2048:   B->assembled    = PETSC_FALSE;
2049:   B->insertmode   = NOT_SET_VALUES;

2051:   MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);
2052:   MPI_Comm_size(PetscObjectComm((PetscObject)B),&b->size);

2054:   /* build local table of row and column ownerships */
2055:   PetscMalloc1(b->size+2,&b->rangebs);

2057:   /* build cache for off array entries formed */
2058:   MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);

2060:   b->donotstash  = PETSC_FALSE;
2061:   b->colmap      = NULL;
2062:   b->garray      = NULL;
2063:   b->roworiented = PETSC_TRUE;

2065:   /* stuff used in block assembly */
2066:   b->barray = NULL;

2068:   /* stuff used for matrix vector multiply */
2069:   b->lvec    = NULL;
2070:   b->Mvctx   = NULL;
2071:   b->slvec0  = NULL;
2072:   b->slvec0b = NULL;
2073:   b->slvec1  = NULL;
2074:   b->slvec1a = NULL;
2075:   b->slvec1b = NULL;
2076:   b->sMvctx  = NULL;

2078:   /* stuff for MatGetRow() */
2079:   b->rowindices   = NULL;
2080:   b->rowvalues    = NULL;
2081:   b->getrowactive = PETSC_FALSE;

2083:   /* hash table stuff */
2084:   b->ht           = NULL;
2085:   b->hd           = NULL;
2086:   b->ht_size      = 0;
2087:   b->ht_flag      = PETSC_FALSE;
2088:   b->ht_fact      = 0;
2089:   b->ht_total_ct  = 0;
2090:   b->ht_insert_ct = 0;

2092:   /* stuff for MatCreateSubMatrices_MPIBAIJ_local() */
2093:   b->ijonly = PETSC_FALSE;

2095:   b->in_loc = NULL;
2096:   b->v_loc  = NULL;
2097:   b->n_loc  = 0;

2099:   PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPISBAIJ);
2100:   PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPISBAIJ);
2101:   PetscObjectComposeFunction((PetscObject)B,"MatMPISBAIJSetPreallocation_C",MatMPISBAIJSetPreallocation_MPISBAIJ);
2102:   PetscObjectComposeFunction((PetscObject)B,"MatMPISBAIJSetPreallocationCSR_C",MatMPISBAIJSetPreallocationCSR_MPISBAIJ);
2103: #if defined(PETSC_HAVE_ELEMENTAL)
2104:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpisbaij_elemental_C",MatConvert_MPISBAIJ_Elemental);
2105: #endif
2106: #if defined(PETSC_HAVE_SCALAPACK)
2107:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpisbaij_scalapack_C",MatConvert_SBAIJ_ScaLAPACK);
2108: #endif
2109:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpisbaij_mpiaij_C",MatConvert_MPISBAIJ_Basic);
2110:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpisbaij_mpibaij_C",MatConvert_MPISBAIJ_Basic);

2112:   B->symmetric                  = PETSC_TRUE;
2113:   B->structurally_symmetric     = PETSC_TRUE;
2114:   B->symmetric_set              = PETSC_TRUE;
2115:   B->structurally_symmetric_set = PETSC_TRUE;
2116:   B->symmetric_eternal          = PETSC_TRUE;
2117: #if defined(PETSC_USE_COMPLEX)
2118:   B->hermitian                  = PETSC_FALSE;
2119:   B->hermitian_set              = PETSC_FALSE;
2120: #else
2121:   B->hermitian                  = PETSC_TRUE;
2122:   B->hermitian_set              = PETSC_TRUE;
2123: #endif

2125:   PetscObjectChangeTypeName((PetscObject)B,MATMPISBAIJ);
2126:   PetscOptionsBegin(PetscObjectComm((PetscObject)B),NULL,"Options for loading MPISBAIJ matrix 1","Mat");
2127:   PetscOptionsBool("-mat_use_hash_table","Use hash table to save memory in constructing matrix","MatSetOption",flg,&flg,NULL);
2128:   if (flg) {
2129:     PetscReal fact = 1.39;
2130:     MatSetOption(B,MAT_USE_HASH_TABLE,PETSC_TRUE);
2131:     PetscOptionsReal("-mat_use_hash_table","Use hash table factor","MatMPIBAIJSetHashTableFactor",fact,&fact,NULL);
2132:     if (fact <= 1.0) fact = 1.39;
2133:     MatMPIBAIJSetHashTableFactor(B,fact);
2134:     PetscInfo(B,"Hash table Factor used %5.2g\n",(double)fact);
2135:   }
2136:   PetscOptionsEnd();
2137:   return 0;
2138: }

2140: /*MC
2141:    MATSBAIJ - MATSBAIJ = "sbaij" - A matrix type to be used for symmetric block sparse matrices.

2143:    This matrix type is identical to MATSEQSBAIJ when constructed with a single process communicator,
2144:    and MATMPISBAIJ otherwise.

2146:    Options Database Keys:
2147: . -mat_type sbaij - sets the matrix type to "sbaij" during a call to MatSetFromOptions()

2149:   Level: beginner

2151: .seealso: MatCreateSBAIJ, MATSEQSBAIJ, MATMPISBAIJ
2152: M*/

2154: /*@C
2155:    MatMPISBAIJSetPreallocation - For good matrix assembly performance
2156:    the user should preallocate the matrix storage by setting the parameters
2157:    d_nz (or d_nnz) and o_nz (or o_nnz).  By setting these parameters accurately,
2158:    performance can be increased by more than a factor of 50.

2160:    Collective on Mat

2162:    Input Parameters:
2163: +  B - the matrix
2164: .  bs   - size of block, the blocks are ALWAYS square. One can use MatSetBlockSizes() to set a different row and column blocksize but the row
2165:           blocksize always defines the size of the blocks. The column blocksize sets the blocksize of the vectors obtained with MatCreateVecs()
2166: .  d_nz  - number of block nonzeros per block row in diagonal portion of local
2167:            submatrix  (same for all local rows)
2168: .  d_nnz - array containing the number of block nonzeros in the various block rows
2169:            in the upper triangular and diagonal part of the in diagonal portion of the local
2170:            (possibly different for each block row) or NULL.  If you plan to factor the matrix you must leave room
2171:            for the diagonal entry and set a value even if it is zero.
2172: .  o_nz  - number of block nonzeros per block row in the off-diagonal portion of local
2173:            submatrix (same for all local rows).
2174: -  o_nnz - array containing the number of nonzeros in the various block rows of the
2175:            off-diagonal portion of the local submatrix that is right of the diagonal
2176:            (possibly different for each block row) or NULL.

2178:    Options Database Keys:
2179: +   -mat_no_unroll - uses code that does not unroll the loops in the
2180:                      block calculations (much slower)
2181: -   -mat_block_size - size of the blocks to use

2183:    Notes:

2185:    If PETSC_DECIDE or  PETSC_DETERMINE is used for a particular argument on one processor
2186:    than it must be used on all processors that share the object for that argument.

2188:    If the *_nnz parameter is given then the *_nz parameter is ignored

2190:    Storage Information:
2191:    For a square global matrix we define each processor's diagonal portion
2192:    to be its local rows and the corresponding columns (a square submatrix);
2193:    each processor's off-diagonal portion encompasses the remainder of the
2194:    local matrix (a rectangular submatrix).

2196:    The user can specify preallocated storage for the diagonal part of
2197:    the local submatrix with either d_nz or d_nnz (not both).  Set
2198:    d_nz=PETSC_DEFAULT and d_nnz=NULL for PETSc to control dynamic
2199:    memory allocation.  Likewise, specify preallocated storage for the
2200:    off-diagonal part of the local submatrix with o_nz or o_nnz (not both).

2202:    You can call MatGetInfo() to get information on how effective the preallocation was;
2203:    for example the fields mallocs,nz_allocated,nz_used,nz_unneeded;
2204:    You can also run with the option -info and look for messages with the string
2205:    malloc in them to see if additional memory allocation was needed.

2207:    Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In
2208:    the figure below we depict these three local rows and all columns (0-11).

2210: .vb
2211:            0 1 2 3 4 5 6 7 8 9 10 11
2212:           --------------------------
2213:    row 3  |. . . d d d o o o o  o  o
2214:    row 4  |. . . d d d o o o o  o  o
2215:    row 5  |. . . d d d o o o o  o  o
2216:           --------------------------
2217: .ve

2219:    Thus, any entries in the d locations are stored in the d (diagonal)
2220:    submatrix, and any entries in the o locations are stored in the
2221:    o (off-diagonal) submatrix.  Note that the d matrix is stored in
2222:    MatSeqSBAIJ format and the o submatrix in MATSEQBAIJ format.

2224:    Now d_nz should indicate the number of block nonzeros per row in the upper triangular
2225:    plus the diagonal part of the d matrix,
2226:    and o_nz should indicate the number of block nonzeros per row in the o matrix

2228:    In general, for PDE problems in which most nonzeros are near the diagonal,
2229:    one expects d_nz >> o_nz.   For large problems you MUST preallocate memory
2230:    or you will get TERRIBLE performance; see the users' manual chapter on
2231:    matrices.

2233:    Level: intermediate

2235: .seealso: MatCreate(), MatCreateSeqSBAIJ(), MatSetValues(), MatCreateBAIJ(), PetscSplitOwnership()
2236: @*/
2237: PetscErrorCode  MatMPISBAIJSetPreallocation(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[])
2238: {
2242:   PetscTryMethod(B,"MatMPISBAIJSetPreallocation_C",(Mat,PetscInt,PetscInt,const PetscInt[],PetscInt,const PetscInt[]),(B,bs,d_nz,d_nnz,o_nz,o_nnz));
2243:   return 0;
2244: }

2246: /*@C
2247:    MatCreateSBAIJ - Creates a sparse parallel matrix in symmetric block AIJ format
2248:    (block compressed row).  For good matrix assembly performance
2249:    the user should preallocate the matrix storage by setting the parameters
2250:    d_nz (or d_nnz) and o_nz (or o_nnz).  By setting these parameters accurately,
2251:    performance can be increased by more than a factor of 50.

2253:    Collective

2255:    Input Parameters:
2256: +  comm - MPI communicator
2257: .  bs   - size of block, the blocks are ALWAYS square. One can use MatSetBlockSizes() to set a different row and column blocksize but the row
2258:           blocksize always defines the size of the blocks. The column blocksize sets the blocksize of the vectors obtained with MatCreateVecs()
2259: .  m - number of local rows (or PETSC_DECIDE to have calculated if M is given)
2260:            This value should be the same as the local size used in creating the
2261:            y vector for the matrix-vector product y = Ax.
2262: .  n - number of local columns (or PETSC_DECIDE to have calculated if N is given)
2263:            This value should be the same as the local size used in creating the
2264:            x vector for the matrix-vector product y = Ax.
2265: .  M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
2266: .  N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
2267: .  d_nz  - number of block nonzeros per block row in diagonal portion of local
2268:            submatrix  (same for all local rows)
2269: .  d_nnz - array containing the number of block nonzeros in the various block rows
2270:            in the upper triangular portion of the in diagonal portion of the local
2271:            (possibly different for each block block row) or NULL.
2272:            If you plan to factor the matrix you must leave room for the diagonal entry and
2273:            set its value even if it is zero.
2274: .  o_nz  - number of block nonzeros per block row in the off-diagonal portion of local
2275:            submatrix (same for all local rows).
2276: -  o_nnz - array containing the number of nonzeros in the various block rows of the
2277:            off-diagonal portion of the local submatrix (possibly different for
2278:            each block row) or NULL.

2280:    Output Parameter:
2281: .  A - the matrix

2283:    Options Database Keys:
2284: +   -mat_no_unroll - uses code that does not unroll the loops in the
2285:                      block calculations (much slower)
2286: .   -mat_block_size - size of the blocks to use
2287: -   -mat_mpi - use the parallel matrix data structures even on one processor
2288:                (defaults to using SeqBAIJ format on one processor)

2290:    It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(),
2291:    MatXXXXSetPreallocation() paradigm instead of this routine directly.
2292:    [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation]

2294:    Notes:
2295:    The number of rows and columns must be divisible by blocksize.
2296:    This matrix type does not support complex Hermitian operation.

2298:    The user MUST specify either the local or global matrix dimensions
2299:    (possibly both).

2301:    If PETSC_DECIDE or  PETSC_DETERMINE is used for a particular argument on one processor
2302:    than it must be used on all processors that share the object for that argument.

2304:    If the *_nnz parameter is given then the *_nz parameter is ignored

2306:    Storage Information:
2307:    For a square global matrix we define each processor's diagonal portion
2308:    to be its local rows and the corresponding columns (a square submatrix);
2309:    each processor's off-diagonal portion encompasses the remainder of the
2310:    local matrix (a rectangular submatrix).

2312:    The user can specify preallocated storage for the diagonal part of
2313:    the local submatrix with either d_nz or d_nnz (not both).  Set
2314:    d_nz=PETSC_DEFAULT and d_nnz=NULL for PETSc to control dynamic
2315:    memory allocation.  Likewise, specify preallocated storage for the
2316:    off-diagonal part of the local submatrix with o_nz or o_nnz (not both).

2318:    Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In
2319:    the figure below we depict these three local rows and all columns (0-11).

2321: .vb
2322:            0 1 2 3 4 5 6 7 8 9 10 11
2323:           --------------------------
2324:    row 3  |. . . d d d o o o o  o  o
2325:    row 4  |. . . d d d o o o o  o  o
2326:    row 5  |. . . d d d o o o o  o  o
2327:           --------------------------
2328: .ve

2330:    Thus, any entries in the d locations are stored in the d (diagonal)
2331:    submatrix, and any entries in the o locations are stored in the
2332:    o (off-diagonal) submatrix.  Note that the d matrix is stored in
2333:    MatSeqSBAIJ format and the o submatrix in MATSEQBAIJ format.

2335:    Now d_nz should indicate the number of block nonzeros per row in the upper triangular
2336:    plus the diagonal part of the d matrix,
2337:    and o_nz should indicate the number of block nonzeros per row in the o matrix.
2338:    In general, for PDE problems in which most nonzeros are near the diagonal,
2339:    one expects d_nz >> o_nz.   For large problems you MUST preallocate memory
2340:    or you will get TERRIBLE performance; see the users' manual chapter on
2341:    matrices.

2343:    Level: intermediate

2345: .seealso: MatCreate(), MatCreateSeqSBAIJ(), MatSetValues(), MatCreateBAIJ()
2346: @*/

2348: 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)
2349: {
2350:   PetscMPIInt    size;

2352:   MatCreate(comm,A);
2353:   MatSetSizes(*A,m,n,M,N);
2354:   MPI_Comm_size(comm,&size);
2355:   if (size > 1) {
2356:     MatSetType(*A,MATMPISBAIJ);
2357:     MatMPISBAIJSetPreallocation(*A,bs,d_nz,d_nnz,o_nz,o_nnz);
2358:   } else {
2359:     MatSetType(*A,MATSEQSBAIJ);
2360:     MatSeqSBAIJSetPreallocation(*A,bs,d_nz,d_nnz);
2361:   }
2362:   return 0;
2363: }

2365: static PetscErrorCode MatDuplicate_MPISBAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat)
2366: {
2367:   Mat            mat;
2368:   Mat_MPISBAIJ   *a,*oldmat = (Mat_MPISBAIJ*)matin->data;
2369:   PetscInt       len=0,nt,bs=matin->rmap->bs,mbs=oldmat->mbs;
2370:   PetscScalar    *array;

2372:   *newmat = NULL;

2374:   MatCreate(PetscObjectComm((PetscObject)matin),&mat);
2375:   MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);
2376:   MatSetType(mat,((PetscObject)matin)->type_name);
2377:   PetscLayoutReference(matin->rmap,&mat->rmap);
2378:   PetscLayoutReference(matin->cmap,&mat->cmap);

2380:   mat->factortype   = matin->factortype;
2381:   mat->preallocated = PETSC_TRUE;
2382:   mat->assembled    = PETSC_TRUE;
2383:   mat->insertmode   = NOT_SET_VALUES;

2385:   a      = (Mat_MPISBAIJ*)mat->data;
2386:   a->bs2 = oldmat->bs2;
2387:   a->mbs = oldmat->mbs;
2388:   a->nbs = oldmat->nbs;
2389:   a->Mbs = oldmat->Mbs;
2390:   a->Nbs = oldmat->Nbs;

2392:   a->size         = oldmat->size;
2393:   a->rank         = oldmat->rank;
2394:   a->donotstash   = oldmat->donotstash;
2395:   a->roworiented  = oldmat->roworiented;
2396:   a->rowindices   = NULL;
2397:   a->rowvalues    = NULL;
2398:   a->getrowactive = PETSC_FALSE;
2399:   a->barray       = NULL;
2400:   a->rstartbs     = oldmat->rstartbs;
2401:   a->rendbs       = oldmat->rendbs;
2402:   a->cstartbs     = oldmat->cstartbs;
2403:   a->cendbs       = oldmat->cendbs;

2405:   /* hash table stuff */
2406:   a->ht           = NULL;
2407:   a->hd           = NULL;
2408:   a->ht_size      = 0;
2409:   a->ht_flag      = oldmat->ht_flag;
2410:   a->ht_fact      = oldmat->ht_fact;
2411:   a->ht_total_ct  = 0;
2412:   a->ht_insert_ct = 0;

2414:   PetscArraycpy(a->rangebs,oldmat->rangebs,a->size+2);
2415:   if (oldmat->colmap) {
2416: #if defined(PETSC_USE_CTABLE)
2417:     PetscTableCreateCopy(oldmat->colmap,&a->colmap);
2418: #else
2419:     PetscMalloc1(a->Nbs,&a->colmap);
2420:     PetscLogObjectMemory((PetscObject)mat,(a->Nbs)*sizeof(PetscInt));
2421:     PetscArraycpy(a->colmap,oldmat->colmap,a->Nbs);
2422: #endif
2423:   } else a->colmap = NULL;

2425:   if (oldmat->garray && (len = ((Mat_SeqBAIJ*)(oldmat->B->data))->nbs)) {
2426:     PetscMalloc1(len,&a->garray);
2427:     PetscLogObjectMemory((PetscObject)mat,len*sizeof(PetscInt));
2428:     PetscArraycpy(a->garray,oldmat->garray,len);
2429:   } else a->garray = NULL;

2431:   MatStashCreate_Private(PetscObjectComm((PetscObject)matin),matin->rmap->bs,&mat->bstash);
2432:   VecDuplicate(oldmat->lvec,&a->lvec);
2433:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->lvec);
2434:   VecScatterCopy(oldmat->Mvctx,&a->Mvctx);
2435:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->Mvctx);

2437:   VecDuplicate(oldmat->slvec0,&a->slvec0);
2438:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec0);
2439:   VecDuplicate(oldmat->slvec1,&a->slvec1);
2440:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec1);

2442:   VecGetLocalSize(a->slvec1,&nt);
2443:   VecGetArray(a->slvec1,&array);
2444:   VecCreateSeqWithArray(PETSC_COMM_SELF,1,bs*mbs,array,&a->slvec1a);
2445:   VecCreateSeqWithArray(PETSC_COMM_SELF,1,nt-bs*mbs,array+bs*mbs,&a->slvec1b);
2446:   VecRestoreArray(a->slvec1,&array);
2447:   VecGetArray(a->slvec0,&array);
2448:   VecCreateSeqWithArray(PETSC_COMM_SELF,1,nt-bs*mbs,array+bs*mbs,&a->slvec0b);
2449:   VecRestoreArray(a->slvec0,&array);
2450:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec0);
2451:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec1);
2452:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec0b);
2453:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec1a);
2454:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec1b);

2456:   /* VecScatterCopy(oldmat->sMvctx,&a->sMvctx); - not written yet, replaced by the lazy trick: */
2457:   PetscObjectReference((PetscObject)oldmat->sMvctx);
2458:   a->sMvctx = oldmat->sMvctx;
2459:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->sMvctx);

2461:   MatDuplicate(oldmat->A,cpvalues,&a->A);
2462:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->A);
2463:   MatDuplicate(oldmat->B,cpvalues,&a->B);
2464:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->B);
2465:   PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);
2466:   *newmat = mat;
2467:   return 0;
2468: }

2470: /* Used for both MPIBAIJ and MPISBAIJ matrices */
2471: #define MatLoad_MPISBAIJ_Binary MatLoad_MPIBAIJ_Binary

2473: PetscErrorCode MatLoad_MPISBAIJ(Mat mat,PetscViewer viewer)
2474: {
2475:   PetscBool      isbinary;

2477:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);
2479:   MatLoad_MPISBAIJ_Binary(mat,viewer);
2480:   return 0;
2481: }

2483: /*XXXXX@
2484:    MatMPISBAIJSetHashTableFactor - Sets the factor required to compute the size of the HashTable.

2486:    Input Parameters:
2487: .  mat  - the matrix
2488: .  fact - factor

2490:    Not Collective on Mat, each process can have a different hash factor

2492:    Level: advanced

2494:   Notes:
2495:    This can also be set by the command line option: -mat_use_hash_table fact

2497: .seealso: MatSetOption()
2498: @XXXXX*/

2500: PetscErrorCode MatGetRowMaxAbs_MPISBAIJ(Mat A,Vec v,PetscInt idx[])
2501: {
2502:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;
2503:   Mat_SeqBAIJ    *b = (Mat_SeqBAIJ*)(a->B)->data;
2504:   PetscReal      atmp;
2505:   PetscReal      *work,*svalues,*rvalues;
2506:   PetscInt       i,bs,mbs,*bi,*bj,brow,j,ncols,krow,kcol,col,row,Mbs,bcol;
2507:   PetscMPIInt    rank,size;
2508:   PetscInt       *rowners_bs,dest,count,source;
2509:   PetscScalar    *va;
2510:   MatScalar      *ba;
2511:   MPI_Status     stat;

2514:   MatGetRowMaxAbs(a->A,v,NULL);
2515:   VecGetArray(v,&va);

2517:   MPI_Comm_size(PetscObjectComm((PetscObject)A),&size);
2518:   MPI_Comm_rank(PetscObjectComm((PetscObject)A),&rank);

2520:   bs  = A->rmap->bs;
2521:   mbs = a->mbs;
2522:   Mbs = a->Mbs;
2523:   ba  = b->a;
2524:   bi  = b->i;
2525:   bj  = b->j;

2527:   /* find ownerships */
2528:   rowners_bs = A->rmap->range;

2530:   /* each proc creates an array to be distributed */
2531:   PetscCalloc1(bs*Mbs,&work);

2533:   /* row_max for B */
2534:   if (rank != size-1) {
2535:     for (i=0; i<mbs; i++) {
2536:       ncols = bi[1] - bi[0]; bi++;
2537:       brow  = bs*i;
2538:       for (j=0; j<ncols; j++) {
2539:         bcol = bs*(*bj);
2540:         for (kcol=0; kcol<bs; kcol++) {
2541:           col  = bcol + kcol;                /* local col index */
2542:           col += rowners_bs[rank+1];      /* global col index */
2543:           for (krow=0; krow<bs; krow++) {
2544:             atmp = PetscAbsScalar(*ba); ba++;
2545:             row  = brow + krow;   /* local row index */
2546:             if (PetscRealPart(va[row]) < atmp) va[row] = atmp;
2547:             if (work[col] < atmp) work[col] = atmp;
2548:           }
2549:         }
2550:         bj++;
2551:       }
2552:     }

2554:     /* send values to its owners */
2555:     for (dest=rank+1; dest<size; dest++) {
2556:       svalues = work + rowners_bs[dest];
2557:       count   = rowners_bs[dest+1]-rowners_bs[dest];
2558:       MPI_Send(svalues,count,MPIU_REAL,dest,rank,PetscObjectComm((PetscObject)A));
2559:     }
2560:   }

2562:   /* receive values */
2563:   if (rank) {
2564:     rvalues = work;
2565:     count   = rowners_bs[rank+1]-rowners_bs[rank];
2566:     for (source=0; source<rank; source++) {
2567:       MPI_Recv(rvalues,count,MPIU_REAL,MPI_ANY_SOURCE,MPI_ANY_TAG,PetscObjectComm((PetscObject)A),&stat);
2568:       /* process values */
2569:       for (i=0; i<count; i++) {
2570:         if (PetscRealPart(va[i]) < rvalues[i]) va[i] = rvalues[i];
2571:       }
2572:     }
2573:   }

2575:   VecRestoreArray(v,&va);
2576:   PetscFree(work);
2577:   return 0;
2578: }

2580: PetscErrorCode MatSOR_MPISBAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx)
2581: {
2582:   Mat_MPISBAIJ      *mat = (Mat_MPISBAIJ*)matin->data;
2583:   PetscInt          mbs=mat->mbs,bs=matin->rmap->bs;
2584:   PetscScalar       *x,*ptr,*from;
2585:   Vec               bb1;
2586:   const PetscScalar *b;


2591:   if (flag == SOR_APPLY_UPPER) {
2592:     (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
2593:     return 0;
2594:   }

2596:   if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) {
2597:     if (flag & SOR_ZERO_INITIAL_GUESS) {
2598:       (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,lits,xx);
2599:       its--;
2600:     }

2602:     VecDuplicate(bb,&bb1);
2603:     while (its--) {

2605:       /* lower triangular part: slvec0b = - B^T*xx */
2606:       (*mat->B->ops->multtranspose)(mat->B,xx,mat->slvec0b);

2608:       /* copy xx into slvec0a */
2609:       VecGetArray(mat->slvec0,&ptr);
2610:       VecGetArray(xx,&x);
2611:       PetscArraycpy(ptr,x,bs*mbs);
2612:       VecRestoreArray(mat->slvec0,&ptr);

2614:       VecScale(mat->slvec0,-1.0);

2616:       /* copy bb into slvec1a */
2617:       VecGetArray(mat->slvec1,&ptr);
2618:       VecGetArrayRead(bb,&b);
2619:       PetscArraycpy(ptr,b,bs*mbs);
2620:       VecRestoreArray(mat->slvec1,&ptr);

2622:       /* set slvec1b = 0 */
2623:       VecSet(mat->slvec1b,0.0);

2625:       VecScatterBegin(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);
2626:       VecRestoreArray(xx,&x);
2627:       VecRestoreArrayRead(bb,&b);
2628:       VecScatterEnd(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);

2630:       /* upper triangular part: bb1 = bb1 - B*x */
2631:       (*mat->B->ops->multadd)(mat->B,mat->slvec1b,mat->slvec1a,bb1);

2633:       /* local diagonal sweep */
2634:       (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,lits,xx);
2635:     }
2636:     VecDestroy(&bb1);
2637:   } else if ((flag & SOR_LOCAL_FORWARD_SWEEP) && (its == 1) && (flag & SOR_ZERO_INITIAL_GUESS)) {
2638:     (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
2639:   } else if ((flag & SOR_LOCAL_BACKWARD_SWEEP) && (its == 1) && (flag & SOR_ZERO_INITIAL_GUESS)) {
2640:     (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
2641:   } else if (flag & SOR_EISENSTAT) {
2642:     Vec               xx1;
2643:     PetscBool         hasop;
2644:     const PetscScalar *diag;
2645:     PetscScalar       *sl,scale = (omega - 2.0)/omega;
2646:     PetscInt          i,n;

2648:     if (!mat->xx1) {
2649:       VecDuplicate(bb,&mat->xx1);
2650:       VecDuplicate(bb,&mat->bb1);
2651:     }
2652:     xx1 = mat->xx1;
2653:     bb1 = mat->bb1;

2655:     (*mat->A->ops->sor)(mat->A,bb,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_BACKWARD_SWEEP),fshift,lits,1,xx);

2657:     if (!mat->diag) {
2658:       /* this is wrong for same matrix with new nonzero values */
2659:       MatCreateVecs(matin,&mat->diag,NULL);
2660:       MatGetDiagonal(matin,mat->diag);
2661:     }
2662:     MatHasOperation(matin,MATOP_MULT_DIAGONAL_BLOCK,&hasop);

2664:     if (hasop) {
2665:       MatMultDiagonalBlock(matin,xx,bb1);
2666:       VecAYPX(mat->slvec1a,scale,bb);
2667:     } else {
2668:       /*
2669:           These two lines are replaced by code that may be a bit faster for a good compiler
2670:       VecPointwiseMult(mat->slvec1a,mat->diag,xx);
2671:       VecAYPX(mat->slvec1a,scale,bb);
2672:       */
2673:       VecGetArray(mat->slvec1a,&sl);
2674:       VecGetArrayRead(mat->diag,&diag);
2675:       VecGetArrayRead(bb,&b);
2676:       VecGetArray(xx,&x);
2677:       VecGetLocalSize(xx,&n);
2678:       if (omega == 1.0) {
2679:         for (i=0; i<n; i++) sl[i] = b[i] - diag[i]*x[i];
2680:         PetscLogFlops(2.0*n);
2681:       } else {
2682:         for (i=0; i<n; i++) sl[i] = b[i] + scale*diag[i]*x[i];
2683:         PetscLogFlops(3.0*n);
2684:       }
2685:       VecRestoreArray(mat->slvec1a,&sl);
2686:       VecRestoreArrayRead(mat->diag,&diag);
2687:       VecRestoreArrayRead(bb,&b);
2688:       VecRestoreArray(xx,&x);
2689:     }

2691:     /* multiply off-diagonal portion of matrix */
2692:     VecSet(mat->slvec1b,0.0);
2693:     (*mat->B->ops->multtranspose)(mat->B,xx,mat->slvec0b);
2694:     VecGetArray(mat->slvec0,&from);
2695:     VecGetArray(xx,&x);
2696:     PetscArraycpy(from,x,bs*mbs);
2697:     VecRestoreArray(mat->slvec0,&from);
2698:     VecRestoreArray(xx,&x);
2699:     VecScatterBegin(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);
2700:     VecScatterEnd(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);
2701:     (*mat->B->ops->multadd)(mat->B,mat->slvec1b,mat->slvec1a,mat->slvec1a);

2703:     /* local sweep */
2704:     (*mat->A->ops->sor)(mat->A,mat->slvec1a,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_FORWARD_SWEEP),fshift,lits,1,xx1);
2705:     VecAXPY(xx,1.0,xx1);
2706:   } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"MatSORType is not supported for SBAIJ matrix format");
2707:   return 0;
2708: }

2710: /*@
2711:      MatCreateMPISBAIJWithArrays - creates a MPI SBAIJ matrix using arrays that contain in standard
2712:          CSR format the local rows.

2714:    Collective

2716:    Input Parameters:
2717: +  comm - MPI communicator
2718: .  bs - the block size, only a block size of 1 is supported
2719: .  m - number of local rows (Cannot be PETSC_DECIDE)
2720: .  n - This value should be the same as the local size used in creating the
2721:        x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have
2722:        calculated if N is given) For square matrices n is almost always m.
2723: .  M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
2724: .  N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
2725: .   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
2726: .   j - column indices
2727: -   a - matrix values

2729:    Output Parameter:
2730: .   mat - the matrix

2732:    Level: intermediate

2734:    Notes:
2735:        The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc;
2736:      thus you CANNOT change the matrix entries by changing the values of a[] after you have
2737:      called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays.

2739:        The i and j indices are 0 based, and i indices are indices corresponding to the local j array.

2741: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(),
2742:           MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays()
2743: @*/
2744: 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)
2745: {
2748:   MatCreate(comm,mat);
2749:   MatSetSizes(*mat,m,n,M,N);
2750:   MatSetType(*mat,MATMPISBAIJ);
2751:   MatMPISBAIJSetPreallocationCSR(*mat,bs,i,j,a);
2752:   return 0;
2753: }

2755: /*@C
2756:    MatMPISBAIJSetPreallocationCSR - Creates a sparse parallel matrix in SBAIJ format using the given nonzero structure and (optional) numerical values

2758:    Collective

2760:    Input Parameters:
2761: +  B - the matrix
2762: .  bs - the block size
2763: .  i - the indices into j for the start of each local row (starts with zero)
2764: .  j - the column indices for each local row (starts with zero) these must be sorted for each row
2765: -  v - optional values in the matrix

2767:    Level: advanced

2769:    Notes:
2770:    Though this routine has Preallocation() in the name it also sets the exact nonzero locations of the matrix entries
2771:    and usually the numerical values as well

2773:    Any entries below the diagonal are ignored

2775: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIBAIJSetPreallocation(), MatCreateAIJ(), MPIAIJ
2776: @*/
2777: PetscErrorCode  MatMPISBAIJSetPreallocationCSR(Mat B,PetscInt bs,const PetscInt i[],const PetscInt j[], const PetscScalar v[])
2778: {
2779:   PetscTryMethod(B,"MatMPISBAIJSetPreallocationCSR_C",(Mat,PetscInt,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,bs,i,j,v));
2780:   return 0;
2781: }

2783: PetscErrorCode MatCreateMPIMatConcatenateSeqMat_MPISBAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat)
2784: {
2786:   PetscInt       m,N,i,rstart,nnz,Ii,bs,cbs;
2787:   PetscInt       *indx;
2788:   PetscScalar    *values;

2790:   MatGetSize(inmat,&m,&N);
2791:   if (scall == MAT_INITIAL_MATRIX) { /* symbolic phase */
2792:     Mat_SeqSBAIJ   *a = (Mat_SeqSBAIJ*)inmat->data;
2793:     PetscInt       *dnz,*onz,mbs,Nbs,nbs;
2794:     PetscInt       *bindx,rmax=a->rmax,j;
2795:     PetscMPIInt    rank,size;

2797:     MatGetBlockSizes(inmat,&bs,&cbs);
2798:     mbs = m/bs; Nbs = N/cbs;
2799:     if (n == PETSC_DECIDE) {
2800:       PetscSplitOwnershipBlock(comm,cbs,&n,&N);
2801:     }
2802:     nbs = n/cbs;

2804:     PetscMalloc1(rmax,&bindx);
2805:     MatPreallocateInitialize(comm,mbs,nbs,dnz,onz); /* inline function, output __end and __rstart are used below */

2807:     MPI_Comm_rank(comm,&rank);
2808:     MPI_Comm_rank(comm,&size);
2809:     if (rank == size-1) {
2810:       /* Check sum(nbs) = Nbs */
2812:     }

2814:     rstart = __rstart; /* block rstart of *outmat; see inline function MatPreallocateInitialize */
2815:     MatSetOption(inmat,MAT_GETROW_UPPERTRIANGULAR,PETSC_TRUE);
2816:     for (i=0; i<mbs; i++) {
2817:       MatGetRow_SeqSBAIJ(inmat,i*bs,&nnz,&indx,NULL); /* non-blocked nnz and indx */
2818:       nnz  = nnz/bs;
2819:       for (j=0; j<nnz; j++) bindx[j] = indx[j*bs]/bs;
2820:       MatPreallocateSet(i+rstart,nnz,bindx,dnz,onz);
2821:       MatRestoreRow_SeqSBAIJ(inmat,i*bs,&nnz,&indx,NULL);
2822:     }
2823:     MatSetOption(inmat,MAT_GETROW_UPPERTRIANGULAR,PETSC_FALSE);
2824:     PetscFree(bindx);

2826:     MatCreate(comm,outmat);
2827:     MatSetSizes(*outmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);
2828:     MatSetBlockSizes(*outmat,bs,cbs);
2829:     MatSetType(*outmat,MATSBAIJ);
2830:     MatSeqSBAIJSetPreallocation(*outmat,bs,0,dnz);
2831:     MatMPISBAIJSetPreallocation(*outmat,bs,0,dnz,0,onz);
2832:     MatPreallocateFinalize(dnz,onz);
2833:   }

2835:   /* numeric phase */
2836:   MatGetBlockSizes(inmat,&bs,&cbs);
2837:   MatGetOwnershipRange(*outmat,&rstart,NULL);

2839:   MatSetOption(inmat,MAT_GETROW_UPPERTRIANGULAR,PETSC_TRUE);
2840:   for (i=0; i<m; i++) {
2841:     MatGetRow_SeqSBAIJ(inmat,i,&nnz,&indx,&values);
2842:     Ii   = i + rstart;
2843:     MatSetValues(*outmat,1,&Ii,nnz,indx,values,INSERT_VALUES);
2844:     MatRestoreRow_SeqSBAIJ(inmat,i,&nnz,&indx,&values);
2845:   }
2846:   MatSetOption(inmat,MAT_GETROW_UPPERTRIANGULAR,PETSC_FALSE);
2847:   MatAssemblyBegin(*outmat,MAT_FINAL_ASSEMBLY);
2848:   MatAssemblyEnd(*outmat,MAT_FINAL_ASSEMBLY);
2849:   return 0;
2850: }