Actual source code: mpisbaij.c

petsc-master 2019-05-22
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  2:  #include <../src/mat/impls/baij/mpi/mpibaij.h>
  3:  #include <../src/mat/impls/sbaij/mpi/mpisbaij.h>
  4:  #include <../src/mat/impls/sbaij/seq/sbaij.h>
  5:  #include <petscblaslapack.h>

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

 11: /* This could be moved to matimpl.h */
 12: static PetscErrorCode MatPreallocateWithMats_Private(Mat B, PetscInt nm, Mat X[], PetscBool symm[], PetscBool fill)
 13: {
 14:   Mat            preallocator;
 15:   PetscInt       r,rstart,rend;
 16:   PetscInt       bs,i,m,n,M,N;
 17:   PetscBool      cong = PETSC_TRUE;

 23:   for (i = 0; i < nm; i++) {
 25:     PetscLayoutCompare(B->rmap,X[i]->rmap,&cong);
 26:     if (!cong) SETERRQ(PetscObjectComm((PetscObject)B),PETSC_ERR_SUP,"Not for different layouts");
 27:   }
 29:   MatGetBlockSize(B,&bs);
 30:   MatGetSize(B,&M,&N);
 31:   MatGetLocalSize(B,&m,&n);
 32:   MatCreate(PetscObjectComm((PetscObject)B),&preallocator);
 33:   MatSetType(preallocator,MATPREALLOCATOR);
 34:   MatSetBlockSize(preallocator,bs);
 35:   MatSetSizes(preallocator,m,n,M,N);
 36:   MatSetUp(preallocator);
 37:   MatGetOwnershipRange(preallocator,&rstart,&rend);
 38:   for (r = rstart; r < rend; ++r) {
 39:     PetscInt          ncols;
 40:     const PetscInt    *row;
 41:     const PetscScalar *vals;

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

 59: static PetscErrorCode MatConvert_MPISBAIJ_XAIJ(Mat A, MatType newtype, MatReuse reuse, Mat *newmat)
 60: {
 61:   Mat            B;
 63:   PetscInt       r;

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

 70:     MatCreate(PetscObjectComm((PetscObject)A),&B);
 71:     MatSetSizes(B,A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N);
 72:     MatSetType(B,newtype);
 73:     MatGetBlockSize(A,&bs);
 74:     MatSetBlockSize(B,bs);
 75:     PetscLayoutSetUp(B->rmap);
 76:     PetscLayoutSetUp(B->cmap);
 77:     MatGetRowUpperTriangular(A);
 78:     MatPreallocateWithMats_Private(B,1,&A,&symm,PETSC_TRUE);
 79:     MatRestoreRowUpperTriangular(A);
 80:   } else B = *newmat;

 82:   MatGetRowUpperTriangular(A);
 83:   for (r = A->rmap->rstart; r < A->rmap->rend; r++) {
 84:     PetscInt          ncols;
 85:     const PetscInt    *row;
 86:     const PetscScalar *vals;

 88:     MatGetRow(A,r,&ncols,&row,&vals);
 89:     MatSetValues(B,1,&r,ncols,row,vals,INSERT_VALUES);
 90:     MatSetValues(B,ncols,row,1,&r,vals,INSERT_VALUES);
 91:     MatRestoreRow(A,r,&ncols,&row,&vals);
 92:   }
 93:   MatRestoreRowUpperTriangular(A);
 94:   MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
 95:   MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);

 97:   if (reuse == MAT_INPLACE_MATRIX) {
 98:     MatHeaderReplace(A,&B);
 99:   } else {
100:     *newmat = B;
101:   }
102:   return(0);
103: }

105: PetscErrorCode  MatStoreValues_MPISBAIJ(Mat mat)
106: {
107:   Mat_MPISBAIJ   *aij = (Mat_MPISBAIJ*)mat->data;

111:   MatStoreValues(aij->A);
112:   MatStoreValues(aij->B);
113:   return(0);
114: }

116: PetscErrorCode  MatRetrieveValues_MPISBAIJ(Mat mat)
117: {
118:   Mat_MPISBAIJ   *aij = (Mat_MPISBAIJ*)mat->data;

122:   MatRetrieveValues(aij->A);
123:   MatRetrieveValues(aij->B);
124:   return(0);
125: }

127: #define  MatSetValues_SeqSBAIJ_A_Private(row,col,value,addv,orow,ocol)      \
128:   { \
129:  \
130:     brow = row/bs;  \
131:     rp   = aj + ai[brow]; ap = aa + bs2*ai[brow]; \
132:     rmax = aimax[brow]; nrow = ailen[brow]; \
133:     bcol = col/bs; \
134:     ridx = row % bs; cidx = col % bs; \
135:     low  = 0; high = nrow; \
136:     while (high-low > 3) { \
137:       t = (low+high)/2; \
138:       if (rp[t] > bcol) high = t; \
139:       else              low  = t; \
140:     } \
141:     for (_i=low; _i<high; _i++) { \
142:       if (rp[_i] > bcol) break; \
143:       if (rp[_i] == bcol) { \
144:         bap = ap + bs2*_i + bs*cidx + ridx; \
145:         if (addv == ADD_VALUES) *bap += value;  \
146:         else                    *bap  = value;  \
147:         goto a_noinsert; \
148:       } \
149:     } \
150:     if (a->nonew == 1) goto a_noinsert; \
151:     if (a->nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero at global row/column (%D, %D) into matrix", orow, ocol); \
152:     MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,brow,bcol,rmax,aa,ai,aj,rp,ap,aimax,a->nonew,MatScalar); \
153:     N = nrow++ - 1;  \
154:     /* shift up all the later entries in this row */ \
155:     for (ii=N; ii>=_i; ii--) { \
156:       rp[ii+1] = rp[ii]; \
157:       PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar)); \
158:     } \
159:     if (N>=_i) { PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar)); }  \
160:     rp[_i]                      = bcol;  \
161:     ap[bs2*_i + bs*cidx + ridx] = value;  \
162:     A->nonzerostate++;\
163: a_noinsert:; \
164:     ailen[brow] = nrow; \
165:   }

167: #define  MatSetValues_SeqSBAIJ_B_Private(row,col,value,addv,orow,ocol) \
168:   { \
169:     brow = row/bs;  \
170:     rp   = bj + bi[brow]; ap = ba + bs2*bi[brow]; \
171:     rmax = bimax[brow]; nrow = bilen[brow]; \
172:     bcol = col/bs; \
173:     ridx = row % bs; cidx = col % bs; \
174:     low  = 0; high = nrow; \
175:     while (high-low > 3) { \
176:       t = (low+high)/2; \
177:       if (rp[t] > bcol) high = t; \
178:       else              low  = t; \
179:     } \
180:     for (_i=low; _i<high; _i++) { \
181:       if (rp[_i] > bcol) break; \
182:       if (rp[_i] == bcol) { \
183:         bap = ap + bs2*_i + bs*cidx + ridx; \
184:         if (addv == ADD_VALUES) *bap += value;  \
185:         else                    *bap  = value;  \
186:         goto b_noinsert; \
187:       } \
188:     } \
189:     if (b->nonew == 1) goto b_noinsert; \
190:     if (b->nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero at global row/column (%D, %D) into matrix", orow, ocol); \
191:     MatSeqXAIJReallocateAIJ(B,b->mbs,bs2,nrow,brow,bcol,rmax,ba,bi,bj,rp,ap,bimax,b->nonew,MatScalar); \
192:     N = nrow++ - 1;  \
193:     /* shift up all the later entries in this row */ \
194:     for (ii=N; ii>=_i; ii--) { \
195:       rp[ii+1] = rp[ii]; \
196:       PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar)); \
197:     } \
198:     if (N>=_i) { PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar));}  \
199:     rp[_i]                      = bcol;  \
200:     ap[bs2*_i + bs*cidx + ridx] = value;  \
201:     B->nonzerostate++;\
202: b_noinsert:; \
203:     bilen[brow] = nrow; \
204:   }

206: /* Only add/insert a(i,j) with i<=j (blocks).
207:    Any a(i,j) with i>j input by user is ingored.
208: */
209: PetscErrorCode MatSetValues_MPISBAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv)
210: {
211:   Mat_MPISBAIJ   *baij = (Mat_MPISBAIJ*)mat->data;
212:   MatScalar      value;
213:   PetscBool      roworiented = baij->roworiented;
215:   PetscInt       i,j,row,col;
216:   PetscInt       rstart_orig=mat->rmap->rstart;
217:   PetscInt       rend_orig  =mat->rmap->rend,cstart_orig=mat->cmap->rstart;
218:   PetscInt       cend_orig  =mat->cmap->rend,bs=mat->rmap->bs;

220:   /* Some Variables required in the macro */
221:   Mat          A     = baij->A;
222:   Mat_SeqSBAIJ *a    = (Mat_SeqSBAIJ*)(A)->data;
223:   PetscInt     *aimax=a->imax,*ai=a->i,*ailen=a->ilen,*aj=a->j;
224:   MatScalar    *aa   =a->a;

226:   Mat         B     = baij->B;
227:   Mat_SeqBAIJ *b    = (Mat_SeqBAIJ*)(B)->data;
228:   PetscInt    *bimax=b->imax,*bi=b->i,*bilen=b->ilen,*bj=b->j;
229:   MatScalar   *ba   =b->a;

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

235:   /* for stash */
236:   PetscInt  n_loc, *in_loc = NULL;
237:   MatScalar *v_loc = NULL;

240:   if (!baij->donotstash) {
241:     if (n > baij->n_loc) {
242:       PetscFree(baij->in_loc);
243:       PetscFree(baij->v_loc);
244:       PetscMalloc1(n,&baij->in_loc);
245:       PetscMalloc1(n,&baij->v_loc);

247:       baij->n_loc = n;
248:     }
249:     in_loc = baij->in_loc;
250:     v_loc  = baij->v_loc;
251:   }

253:   for (i=0; i<m; i++) {
254:     if (im[i] < 0) continue;
255: #if defined(PETSC_USE_DEBUG)
256:     if (im[i] >= mat->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],mat->rmap->N-1);
257: #endif
258:     if (im[i] >= rstart_orig && im[i] < rend_orig) { /* this processor entry */
259:       row = im[i] - rstart_orig;              /* local row index */
260:       for (j=0; j<n; j++) {
261:         if (im[i]/bs > in[j]/bs) {
262:           if (a->ignore_ltriangular) {
263:             continue;    /* ignore lower triangular blocks */
264:           } 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)");
265:         }
266:         if (in[j] >= cstart_orig && in[j] < cend_orig) {  /* diag entry (A) */
267:           col  = in[j] - cstart_orig;         /* local col index */
268:           brow = row/bs; bcol = col/bs;
269:           if (brow > bcol) continue;  /* ignore lower triangular blocks of A */
270:           if (roworiented) value = v[i*n+j];
271:           else             value = v[i+j*m];
272:           MatSetValues_SeqSBAIJ_A_Private(row,col,value,addv,im[i],in[j]);
273:           /* MatSetValues_SeqBAIJ(baij->A,1,&row,1,&col,&value,addv); */
274:         } else if (in[j] < 0) continue;
275: #if defined(PETSC_USE_DEBUG)
276:         else if (in[j] >= mat->cmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",in[j],mat->cmap->N-1);
277: #endif
278:         else {  /* off-diag entry (B) */
279:           if (mat->was_assembled) {
280:             if (!baij->colmap) {
281:               MatCreateColmap_MPIBAIJ_Private(mat);
282:             }
283: #if defined(PETSC_USE_CTABLE)
284:             PetscTableFind(baij->colmap,in[j]/bs + 1,&col);
285:             col  = col - 1;
286: #else
287:             col = baij->colmap[in[j]/bs] - 1;
288: #endif
289:             if (col < 0 && !((Mat_SeqSBAIJ*)(baij->A->data))->nonew) {
290:               MatDisAssemble_MPISBAIJ(mat);
291:               col  =  in[j];
292:               /* Reinitialize the variables required by MatSetValues_SeqBAIJ_B_Private() */
293:               B    = baij->B;
294:               b    = (Mat_SeqBAIJ*)(B)->data;
295:               bimax= b->imax;bi=b->i;bilen=b->ilen;bj=b->j;
296:               ba   = b->a;
297:             } else col += in[j]%bs;
298:           } else col = in[j];
299:           if (roworiented) value = v[i*n+j];
300:           else             value = v[i+j*m];
301:           MatSetValues_SeqSBAIJ_B_Private(row,col,value,addv,im[i],in[j]);
302:           /* MatSetValues_SeqBAIJ(baij->B,1,&row,1,&col,&value,addv); */
303:         }
304:       }
305:     } else {  /* off processor entry */
306:       if (mat->nooffprocentries) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Setting off process row %D even though MatSetOption(,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE) was set",im[i]);
307:       if (!baij->donotstash) {
308:         mat->assembled = PETSC_FALSE;
309:         n_loc          = 0;
310:         for (j=0; j<n; j++) {
311:           if (im[i]/bs > in[j]/bs) continue; /* ignore lower triangular blocks */
312:           in_loc[n_loc] = in[j];
313:           if (roworiented) {
314:             v_loc[n_loc] = v[i*n+j];
315:           } else {
316:             v_loc[n_loc] = v[j*m+i];
317:           }
318:           n_loc++;
319:         }
320:         MatStashValuesRow_Private(&mat->stash,im[i],n_loc,in_loc,v_loc,PETSC_FALSE);
321:       }
322:     }
323:   }
324:   return(0);
325: }

327: PETSC_STATIC_INLINE PetscErrorCode MatSetValuesBlocked_SeqSBAIJ_Inlined(Mat A,PetscInt row,PetscInt col,const PetscScalar v[],InsertMode is,PetscInt orow,PetscInt ocol)
328: {
329:   Mat_SeqSBAIJ      *a = (Mat_SeqSBAIJ*)A->data;
330:   PetscErrorCode    ierr;
331:   PetscInt          *rp,low,high,t,ii,jj,nrow,i,rmax,N;
332:   PetscInt          *imax      =a->imax,*ai=a->i,*ailen=a->ilen;
333:   PetscInt          *aj        =a->j,nonew=a->nonew,bs2=a->bs2,bs=A->rmap->bs;
334:   PetscBool         roworiented=a->roworiented;
335:   const PetscScalar *value     = v;
336:   MatScalar         *ap,*aa = a->a,*bap;

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

351:   while (high-low > 7) {
352:     t = (low+high)/2;
353:     if (rp[t] > col) high = t;
354:     else             low  = t;
355:   }
356:   for (i=low; i<high; i++) {
357:     if (rp[i] > col) break;
358:     if (rp[i] == col) {
359:       bap = ap +  bs2*i;
360:       if (roworiented) {
361:         if (is == ADD_VALUES) {
362:           for (ii=0; ii<bs; ii++) {
363:             for (jj=ii; jj<bs2; jj+=bs) {
364:               bap[jj] += *value++;
365:             }
366:           }
367:         } else {
368:           for (ii=0; ii<bs; ii++) {
369:             for (jj=ii; jj<bs2; jj+=bs) {
370:               bap[jj] = *value++;
371:             }
372:           }
373:         }
374:       } else {
375:         if (is == ADD_VALUES) {
376:           for (ii=0; ii<bs; ii++) {
377:             for (jj=0; jj<bs; jj++) {
378:               *bap++ += *value++;
379:             }
380:           }
381:         } else {
382:           for (ii=0; ii<bs; ii++) {
383:             for (jj=0; jj<bs; jj++) {
384:               *bap++  = *value++;
385:             }
386:           }
387:         }
388:       }
389:       goto noinsert2;
390:     }
391:   }
392:   if (nonew == 1) goto noinsert2;
393:   if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new block index nonzero block (%D, %D) in the matrix", orow, ocol);
394:   MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,row,col,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar);
395:   N = nrow++ - 1; high++;
396:   /* shift up all the later entries in this row */
397:   for (ii=N; ii>=i; ii--) {
398:     rp[ii+1] = rp[ii];
399:     PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));
400:   }
401:   if (N >= i) {
402:     PetscMemzero(ap+bs2*i,bs2*sizeof(MatScalar));
403:   }
404:   rp[i] = col;
405:   bap   = ap +  bs2*i;
406:   if (roworiented) {
407:     for (ii=0; ii<bs; ii++) {
408:       for (jj=ii; jj<bs2; jj+=bs) {
409:         bap[jj] = *value++;
410:       }
411:     }
412:   } else {
413:     for (ii=0; ii<bs; ii++) {
414:       for (jj=0; jj<bs; jj++) {
415:         *bap++ = *value++;
416:       }
417:     }
418:   }
419:   noinsert2:;
420:   ailen[row] = nrow;
421:   return(0);
422: }

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

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

521: /*
522:     This routine could be optimized by removing the need for the block copy below and passing stride information
523:   to the above inline routines; similarly in MatSetValuesBlocked_MPIBAIJ()
524: */
525: PetscErrorCode MatSetValuesBlocked_MPISBAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const MatScalar v[],InsertMode addv)
526: {
527:   Mat_MPISBAIJ    *baij = (Mat_MPISBAIJ*)mat->data;
528:   const MatScalar *value;
529:   MatScalar       *barray     =baij->barray;
530:   PetscBool       roworiented = baij->roworiented,ignore_ltriangular = ((Mat_SeqSBAIJ*)baij->A->data)->ignore_ltriangular;
531:   PetscErrorCode  ierr;
532:   PetscInt        i,j,ii,jj,row,col,rstart=baij->rstartbs;
533:   PetscInt        rend=baij->rendbs,cstart=baij->rstartbs,stepval;
534:   PetscInt        cend=baij->rendbs,bs=mat->rmap->bs,bs2=baij->bs2;

537:   if (!barray) {
538:     PetscMalloc1(bs2,&barray);
539:     baij->barray = barray;
540:   }

542:   if (roworiented) {
543:     stepval = (n-1)*bs;
544:   } else {
545:     stepval = (m-1)*bs;
546:   }
547:   for (i=0; i<m; i++) {
548:     if (im[i] < 0) continue;
549: #if defined(PETSC_USE_DEBUG)
550:     if (im[i] >= baij->Mbs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Block indexed row too large %D max %D",im[i],baij->Mbs-1);
551: #endif
552:     if (im[i] >= rstart && im[i] < rend) {
553:       row = im[i] - rstart;
554:       for (j=0; j<n; j++) {
555:         if (im[i] > in[j]) {
556:           if (ignore_ltriangular) continue; /* ignore lower triangular blocks */
557:           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)");
558:         }
559:         /* If NumCol = 1 then a copy is not required */
560:         if ((roworiented) && (n == 1)) {
561:           barray = (MatScalar*) v + i*bs2;
562:         } else if ((!roworiented) && (m == 1)) {
563:           barray = (MatScalar*) v + j*bs2;
564:         } else { /* Here a copy is required */
565:           if (roworiented) {
566:             value = v + i*(stepval+bs)*bs + j*bs;
567:           } else {
568:             value = v + j*(stepval+bs)*bs + i*bs;
569:           }
570:           for (ii=0; ii<bs; ii++,value+=stepval) {
571:             for (jj=0; jj<bs; jj++) {
572:               *barray++ = *value++;
573:             }
574:           }
575:           barray -=bs2;
576:         }

578:         if (in[j] >= cstart && in[j] < cend) {
579:           col  = in[j] - cstart;
580:           MatSetValuesBlocked_SeqSBAIJ_Inlined(baij->A,row,col,barray,addv,im[i],in[j]);
581:         } else if (in[j] < 0) continue;
582: #if defined(PETSC_USE_DEBUG)
583:         else if (in[j] >= baij->Nbs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Block indexed column too large %D max %D",in[j],baij->Nbs-1);
584: #endif
585:         else {
586:           if (mat->was_assembled) {
587:             if (!baij->colmap) {
588:               MatCreateColmap_MPIBAIJ_Private(mat);
589:             }

591: #if defined(PETSC_USE_DEBUG)
592: #if defined(PETSC_USE_CTABLE)
593:             { PetscInt data;
594:               PetscTableFind(baij->colmap,in[j]+1,&data);
595:               if ((data - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap");
596:             }
597: #else
598:             if ((baij->colmap[in[j]] - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap");
599: #endif
600: #endif
601: #if defined(PETSC_USE_CTABLE)
602:             PetscTableFind(baij->colmap,in[j]+1,&col);
603:             col  = (col - 1)/bs;
604: #else
605:             col = (baij->colmap[in[j]] - 1)/bs;
606: #endif
607:             if (col < 0 && !((Mat_SeqBAIJ*)(baij->A->data))->nonew) {
608:               MatDisAssemble_MPISBAIJ(mat);
609:               col  = in[j];
610:             }
611:           } else col = in[j];
612:           MatSetValuesBlocked_SeqBAIJ_Inlined(baij->B,row,col,barray,addv,im[i],in[j]);
613:         }
614:       }
615:     } else {
616:       if (mat->nooffprocentries) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Setting off process block indexed row %D even though MatSetOption(,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE) was set",im[i]);
617:       if (!baij->donotstash) {
618:         if (roworiented) {
619:           MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);
620:         } else {
621:           MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);
622:         }
623:       }
624:     }
625:   }
626:   return(0);
627: }

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

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

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

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

697:       PetscMalloc2(mat->cmap->N,&rsum,mat->cmap->N,&rsum2);
698:       PetscMemzero(rsum,mat->cmap->N*sizeof(PetscReal));
699:       /* Amat */
700:       v = amat->a; jj = amat->j;
701:       for (brow=0; brow<mbs; brow++) {
702:         grow = bs*(rstart + brow);
703:         nz   = amat->i[brow+1] - amat->i[brow];
704:         for (bcol=0; bcol<nz; bcol++) {
705:           gcol = bs*(rstart + *jj); jj++;
706:           for (col=0; col<bs; col++) {
707:             for (row=0; row<bs; row++) {
708:               vabs            = PetscAbsScalar(*v); v++;
709:               rsum[gcol+col] += vabs;
710:               /* non-diagonal block */
711:               if (bcol > 0 && vabs > 0.0) rsum[grow+row] += vabs;
712:             }
713:           }
714:         }
715:         PetscLogFlops(nz*bs*bs);
716:       }
717:       /* Bmat */
718:       v = bmat->a; jj = bmat->j;
719:       for (brow=0; brow<mbs; brow++) {
720:         grow = bs*(rstart + brow);
721:         nz = bmat->i[brow+1] - bmat->i[brow];
722:         for (bcol=0; bcol<nz; bcol++) {
723:           gcol = bs*garray[*jj]; jj++;
724:           for (col=0; col<bs; col++) {
725:             for (row=0; row<bs; row++) {
726:               vabs            = PetscAbsScalar(*v); v++;
727:               rsum[gcol+col] += vabs;
728:               rsum[grow+row] += vabs;
729:             }
730:           }
731:         }
732:         PetscLogFlops(nz*bs*bs);
733:       }
734:       MPIU_Allreduce(rsum,rsum2,mat->cmap->N,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));
735:       *norm = 0.0;
736:       for (col=0; col<mat->cmap->N; col++) {
737:         if (rsum2[col] > *norm) *norm = rsum2[col];
738:       }
739:       PetscFree2(rsum,rsum2);
740:     } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support for this norm yet");
741:   }
742:   return(0);
743: }

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

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

754:   MatStashScatterBegin_Private(mat,&mat->stash,mat->rmap->range);
755:   MatStashScatterBegin_Private(mat,&mat->bstash,baij->rangebs);
756:   MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);
757:   PetscInfo2(mat,"Stash has %D entries,uses %D mallocs.\n",nstash,reallocs);
758:   MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);
759:   PetscInfo2(mat,"Block-Stash has %D entries, uses %D mallocs.\n",nstash,reallocs);
760:   return(0);
761: }

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

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

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

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

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

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

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

826:     ((Mat_SeqBAIJ*)baij->B->data)->roworiented = r3; /* b->roworinted */
827:   }

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

832:   /* determine if any processor has disassembled, if so we must
833:      also disassemble ourselfs, in order that we may reassemble. */
834:   /*
835:      if nonzero structure of submatrix B cannot change then we know that
836:      no processor disassembled thus we can skip this stuff
837:   */
838:   if (!((Mat_SeqBAIJ*)baij->B->data)->nonew) {
839:     MPIU_Allreduce(&mat->was_assembled,&other_disassembled,1,MPIU_BOOL,MPI_PROD,PetscObjectComm((PetscObject)mat));
840:     if (mat->was_assembled && !other_disassembled) {
841:       MatDisAssemble_MPISBAIJ(mat);
842:     }
843:   }

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

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

853:   baij->rowvalues = 0;

855:   /* if no new nonzero locations are allowed in matrix then only set the matrix state the first time through */
856:   if ((!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) || !((Mat_SeqBAIJ*)(baij->A->data))->nonew) {
857:     PetscObjectState state = baij->A->nonzerostate + baij->B->nonzerostate;
858:     MPIU_Allreduce(&state,&mat->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)mat));
859:   }
860:   return(0);
861: }

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

876:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
877:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);
878:   if (iascii) {
879:     PetscViewerGetFormat(viewer,&format);
880:     if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) {
881:       MatInfo info;
882:       MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);
883:       MatGetInfo(mat,MAT_LOCAL,&info);
884:       PetscViewerASCIIPushSynchronized(viewer);
885:       PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D bs %D mem %g\n",rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,mat->rmap->bs,(double)info.memory);
886:       MatGetInfo(baij->A,MAT_LOCAL,&info);
887:       PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);
888:       MatGetInfo(baij->B,MAT_LOCAL,&info);
889:       PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);
890:       PetscViewerFlush(viewer);
891:       PetscViewerASCIIPopSynchronized(viewer);
892:       PetscViewerASCIIPrintf(viewer,"Information on VecScatter used in matrix-vector product: \n");
893:       VecScatterView(baij->Mvctx,viewer);
894:       return(0);
895:     } else if (format == PETSC_VIEWER_ASCII_INFO) {
896:       PetscViewerASCIIPrintf(viewer,"  block size is %D\n",bs);
897:       return(0);
898:     } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) {
899:       return(0);
900:     }
901:   }

903:   if (isdraw) {
904:     PetscDraw draw;
905:     PetscBool isnull;
906:     PetscViewerDrawGetDraw(viewer,0,&draw);
907:     PetscDrawIsNull(draw,&isnull);
908:     if (isnull) return(0);
909:   }

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

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

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

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

954:       rvals[0] = bs*(baij->rstartbs + i);
955:       for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1;
956:       for (j=ai[i]; j<ai[i+1]; j++) {
957:         col = baij->garray[aj[j]]*bs;
958:         for (k=0; k<bs; k++) {
959:           MatSetValues_MPIBAIJ(A,bs,rvals,1,&col,a,INSERT_VALUES);
960:           col++;
961:           a += bs;
962:         }
963:       }
964:     }
965:     PetscFree(rvals);
966:     MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);
967:     MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);
968:     /*
969:        Everyone has to call to draw the matrix since the graphics waits are
970:        synchronized across all processors that share the PetscDraw object
971:     */
972:     PetscViewerGetSubViewer(viewer,PETSC_COMM_SELF,&sviewer);
973:     PetscObjectGetName((PetscObject)mat,&matname);
974:     if (!rank) {
975:       PetscObjectSetName((PetscObject)((Mat_MPISBAIJ*)(A->data))->A,matname);
976:       MatView_SeqSBAIJ(((Mat_MPISBAIJ*)(A->data))->A,sviewer);
977:     }
978:     PetscViewerRestoreSubViewer(viewer,PETSC_COMM_SELF,&sviewer);
979:     PetscViewerFlush(viewer);
980:     MatDestroy(&A);
981:   }
982:   return(0);
983: }

985: static PetscErrorCode MatView_MPISBAIJ_Binary(Mat mat,PetscViewer viewer)
986: {
987:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)mat->data;
988:   Mat_SeqSBAIJ   *A = (Mat_SeqSBAIJ*)a->A->data;
989:   Mat_SeqBAIJ    *B = (Mat_SeqBAIJ*)a->B->data;
991:   PetscInt       i,*row_lens,*crow_lens,bs = mat->rmap->bs,j,k,bs2=a->bs2,header[4],nz,rlen;
992:   PetscInt       *range=0,nzmax,*column_indices,cnt,col,*garray = a->garray,cstart = mat->cmap->rstart/bs,len,pcnt,l,ll;
993:   int            fd;
994:   PetscScalar    *column_values;
995:   FILE           *file;
996:   PetscMPIInt    rank,size,tag = ((PetscObject)viewer)->tag;
997:   PetscInt       message_count,flowcontrolcount;

1000:   MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);
1001:   MPI_Comm_size(PetscObjectComm((PetscObject)mat),&size);
1002:   nz   = bs2*(A->nz + B->nz);
1003:   rlen = mat->rmap->n;
1004:   PetscViewerBinaryGetDescriptor(viewer,&fd);
1005:   if (!rank) {
1006:     header[0] = MAT_FILE_CLASSID;
1007:     header[1] = mat->rmap->N;
1008:     header[2] = mat->cmap->N;

1010:     MPI_Reduce(&nz,&header[3],1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));
1011:     PetscBinaryWrite(fd,header,4,PETSC_INT,PETSC_TRUE);
1012:     /* get largest number of rows any processor has */
1013:     range = mat->rmap->range;
1014:     for (i=1; i<size; i++) {
1015:       rlen = PetscMax(rlen,range[i+1] - range[i]);
1016:     }
1017:   } else {
1018:     MPI_Reduce(&nz,0,1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));
1019:   }

1021:   PetscMalloc1(rlen/bs,&crow_lens);
1022:   /* compute lengths of each row  */
1023:   for (i=0; i<a->mbs; i++) {
1024:     crow_lens[i] = A->i[i+1] - A->i[i] + B->i[i+1] - B->i[i];
1025:   }
1026:   /* store the row lengths to the file */
1027:   PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);
1028:   if (!rank) {
1029:     MPI_Status status;
1030:     PetscMalloc1(rlen,&row_lens);
1031:     rlen = (range[1] - range[0])/bs;
1032:     for (i=0; i<rlen; i++) {
1033:       for (j=0; j<bs; j++) {
1034:         row_lens[i*bs+j] = bs*crow_lens[i];
1035:       }
1036:     }
1037:     PetscBinaryWrite(fd,row_lens,bs*rlen,PETSC_INT,PETSC_TRUE);
1038:     for (i=1; i<size; i++) {
1039:       rlen = (range[i+1] - range[i])/bs;
1040:       PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);
1041:       MPI_Recv(crow_lens,rlen,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);
1042:       for (k=0; k<rlen; k++) {
1043:         for (j=0; j<bs; j++) {
1044:           row_lens[k*bs+j] = bs*crow_lens[k];
1045:         }
1046:       }
1047:       PetscBinaryWrite(fd,row_lens,bs*rlen,PETSC_INT,PETSC_TRUE);
1048:     }
1049:     PetscViewerFlowControlEndMaster(viewer,&message_count);
1050:     PetscFree(row_lens);
1051:   } else {
1052:     PetscViewerFlowControlStepWorker(viewer,rank,&message_count);
1053:     MPI_Send(crow_lens,mat->rmap->n/bs,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));
1054:     PetscViewerFlowControlEndWorker(viewer,&message_count);
1055:   }
1056:   PetscFree(crow_lens);

1058:   /* load up the local column indices. Include for all rows not just one for each block row since process 0 does not have the
1059:      information needed to make it for each row from a block row. This does require more communication but still not more than
1060:      the communication needed for the nonzero values  */
1061:   nzmax = nz; /*  space a largest processor needs */
1062:   MPI_Reduce(&nz,&nzmax,1,MPIU_INT,MPI_MAX,0,PetscObjectComm((PetscObject)mat));
1063:   PetscMalloc1(nzmax,&column_indices);
1064:   cnt   = 0;
1065:   for (i=0; i<a->mbs; i++) {
1066:     pcnt = cnt;
1067:     for (j=B->i[i]; j<B->i[i+1]; j++) {
1068:       if ((col = garray[B->j[j]]) > cstart) break;
1069:       for (l=0; l<bs; l++) {
1070:         column_indices[cnt++] = bs*col+l;
1071:       }
1072:     }
1073:     for (k=A->i[i]; k<A->i[i+1]; k++) {
1074:       for (l=0; l<bs; l++) {
1075:         column_indices[cnt++] = bs*(A->j[k] + cstart)+l;
1076:       }
1077:     }
1078:     for (; j<B->i[i+1]; j++) {
1079:       for (l=0; l<bs; l++) {
1080:         column_indices[cnt++] = bs*garray[B->j[j]]+l;
1081:       }
1082:     }
1083:     len = cnt - pcnt;
1084:     for (k=1; k<bs; k++) {
1085:       PetscMemcpy(&column_indices[cnt],&column_indices[pcnt],len*sizeof(PetscInt));
1086:       cnt += len;
1087:     }
1088:   }
1089:   if (cnt != nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: cnt = %D nz = %D",cnt,nz);

1091:   /* store the columns to the file */
1092:   PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);
1093:   if (!rank) {
1094:     MPI_Status status;
1095:     PetscBinaryWrite(fd,column_indices,nz,PETSC_INT,PETSC_TRUE);
1096:     for (i=1; i<size; i++) {
1097:       PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);
1098:       MPI_Recv(&cnt,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);
1099:       MPI_Recv(column_indices,cnt,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);
1100:       PetscBinaryWrite(fd,column_indices,cnt,PETSC_INT,PETSC_TRUE);
1101:     }
1102:     PetscViewerFlowControlEndMaster(viewer,&message_count);
1103:   } else {
1104:     PetscViewerFlowControlStepWorker(viewer,rank,&message_count);
1105:     MPI_Send(&cnt,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));
1106:     MPI_Send(column_indices,cnt,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));
1107:     PetscViewerFlowControlEndWorker(viewer,&message_count);
1108:   }
1109:   PetscFree(column_indices);

1111:   /* load up the numerical values */
1112:   PetscMalloc1(nzmax,&column_values);
1113:   cnt  = 0;
1114:   for (i=0; i<a->mbs; i++) {
1115:     rlen = bs*(B->i[i+1] - B->i[i] + A->i[i+1] - A->i[i]);
1116:     for (j=B->i[i]; j<B->i[i+1]; j++) {
1117:       if (garray[B->j[j]] > cstart) break;
1118:       for (l=0; l<bs; l++) {
1119:         for (ll=0; ll<bs; ll++) {
1120:           column_values[cnt + l*rlen + ll] = B->a[bs2*j+l+bs*ll];
1121:         }
1122:       }
1123:       cnt += bs;
1124:     }
1125:     for (k=A->i[i]; k<A->i[i+1]; k++) {
1126:       for (l=0; l<bs; l++) {
1127:         for (ll=0; ll<bs; ll++) {
1128:           column_values[cnt + l*rlen + ll] = A->a[bs2*k+l+bs*ll];
1129:         }
1130:       }
1131:       cnt += bs;
1132:     }
1133:     for (; j<B->i[i+1]; j++) {
1134:       for (l=0; l<bs; l++) {
1135:         for (ll=0; ll<bs; ll++) {
1136:           column_values[cnt + l*rlen + ll] = B->a[bs2*j+l+bs*ll];
1137:         }
1138:       }
1139:       cnt += bs;
1140:     }
1141:     cnt += (bs-1)*rlen;
1142:   }
1143:   if (cnt != nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Internal PETSc error: cnt = %D nz = %D",cnt,nz);

1145:   /* store the column values to the file */
1146:   PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);
1147:   if (!rank) {
1148:     MPI_Status status;
1149:     PetscBinaryWrite(fd,column_values,nz,PETSC_SCALAR,PETSC_TRUE);
1150:     for (i=1; i<size; i++) {
1151:       PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);
1152:       MPI_Recv(&cnt,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);
1153:       MPI_Recv(column_values,cnt,MPIU_SCALAR,i,tag,PetscObjectComm((PetscObject)mat),&status);
1154:       PetscBinaryWrite(fd,column_values,cnt,PETSC_SCALAR,PETSC_TRUE);
1155:     }
1156:     PetscViewerFlowControlEndMaster(viewer,&message_count);
1157:   } else {
1158:     PetscViewerFlowControlStepWorker(viewer,rank,&message_count);
1159:     MPI_Send(&nz,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));
1160:     MPI_Send(column_values,nz,MPIU_SCALAR,0,tag,PetscObjectComm((PetscObject)mat));
1161:     PetscViewerFlowControlEndWorker(viewer,&message_count);
1162:   }
1163:   PetscFree(column_values);

1165:   PetscViewerBinaryGetInfoPointer(viewer,&file);
1166:   if (file) {
1167:     fprintf(file,"-matload_block_size %d\n",(int)mat->rmap->bs);
1168:   }
1169:   return(0);
1170: }

1172: PetscErrorCode MatView_MPISBAIJ(Mat mat,PetscViewer viewer)
1173: {
1175:   PetscBool      iascii,isdraw,issocket,isbinary;

1178:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
1179:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);
1180:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSOCKET,&issocket);
1181:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);
1182:   if (iascii || isdraw || issocket) {
1183:     MatView_MPISBAIJ_ASCIIorDraworSocket(mat,viewer);
1184:   } else if (isbinary) {
1185:     MatView_MPISBAIJ_Binary(mat,viewer);
1186:   }
1187:   return(0);
1188: }

1190: PetscErrorCode MatDestroy_MPISBAIJ(Mat mat)
1191: {
1192:   Mat_MPISBAIJ   *baij = (Mat_MPISBAIJ*)mat->data;

1196: #if defined(PETSC_USE_LOG)
1197:   PetscLogObjectState((PetscObject)mat,"Rows=%D,Cols=%D",mat->rmap->N,mat->cmap->N);
1198: #endif
1199:   MatStashDestroy_Private(&mat->stash);
1200:   MatStashDestroy_Private(&mat->bstash);
1201:   MatDestroy(&baij->A);
1202:   MatDestroy(&baij->B);
1203: #if defined(PETSC_USE_CTABLE)
1204:   PetscTableDestroy(&baij->colmap);
1205: #else
1206:   PetscFree(baij->colmap);
1207: #endif
1208:   PetscFree(baij->garray);
1209:   VecDestroy(&baij->lvec);
1210:   VecScatterDestroy(&baij->Mvctx);
1211:   VecDestroy(&baij->slvec0);
1212:   VecDestroy(&baij->slvec0b);
1213:   VecDestroy(&baij->slvec1);
1214:   VecDestroy(&baij->slvec1a);
1215:   VecDestroy(&baij->slvec1b);
1216:   VecScatterDestroy(&baij->sMvctx);
1217:   PetscFree2(baij->rowvalues,baij->rowindices);
1218:   PetscFree(baij->barray);
1219:   PetscFree(baij->hd);
1220:   VecDestroy(&baij->diag);
1221:   VecDestroy(&baij->bb1);
1222:   VecDestroy(&baij->xx1);
1223: #if defined(PETSC_USE_REAL_MAT_SINGLE)
1224:   PetscFree(baij->setvaluescopy);
1225: #endif
1226:   PetscFree(baij->in_loc);
1227:   PetscFree(baij->v_loc);
1228:   PetscFree(baij->rangebs);
1229:   PetscFree(mat->data);

1231:   PetscObjectChangeTypeName((PetscObject)mat,0);
1232:   PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C",NULL);
1233:   PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C",NULL);
1234:   PetscObjectComposeFunction((PetscObject)mat,"MatMPISBAIJSetPreallocation_C",NULL);
1235: #if defined(PETSC_HAVE_ELEMENTAL)
1236:   PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpisbaij_elemental_C",NULL);
1237: #endif
1238:   PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpisbaij_mpiaij_C",NULL);
1239:   PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpisbaij_mpibaij_C",NULL);
1240:   return(0);
1241: }

1243: PetscErrorCode MatMult_MPISBAIJ_Hermitian(Mat A,Vec xx,Vec yy)
1244: {
1245:   Mat_MPISBAIJ      *a = (Mat_MPISBAIJ*)A->data;
1246:   PetscErrorCode    ierr;
1247:   PetscInt          nt,mbs=a->mbs,bs=A->rmap->bs;
1248:   PetscScalar       *from;
1249:   const PetscScalar *x;

1252:   VecGetLocalSize(xx,&nt);
1253:   if (nt != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx");

1255:   /* diagonal part */
1256:   (*a->A->ops->mult)(a->A,xx,a->slvec1a);
1257:   VecSet(a->slvec1b,0.0);

1259:   /* subdiagonal part */
1260:   (*a->B->ops->multhermitiantranspose)(a->B,xx,a->slvec0b);

1262:   /* copy x into the vec slvec0 */
1263:   VecGetArray(a->slvec0,&from);
1264:   VecGetArrayRead(xx,&x);

1266:   PetscMemcpy(from,x,bs*mbs*sizeof(MatScalar));
1267:   VecRestoreArray(a->slvec0,&from);
1268:   VecRestoreArrayRead(xx,&x);

1270:   VecScatterBegin(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);
1271:   VecScatterEnd(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);
1272:   /* supperdiagonal part */
1273:   (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,yy);
1274:   return(0);
1275: }

1277: PetscErrorCode MatMult_MPISBAIJ(Mat A,Vec xx,Vec yy)
1278: {
1279:   Mat_MPISBAIJ      *a = (Mat_MPISBAIJ*)A->data;
1280:   PetscErrorCode    ierr;
1281:   PetscInt          nt,mbs=a->mbs,bs=A->rmap->bs;
1282:   PetscScalar       *from;
1283:   const PetscScalar *x;

1286:   VecGetLocalSize(xx,&nt);
1287:   if (nt != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx");

1289:   /* diagonal part */
1290:   (*a->A->ops->mult)(a->A,xx,a->slvec1a);
1291:   VecSet(a->slvec1b,0.0);

1293:   /* subdiagonal part */
1294:   (*a->B->ops->multtranspose)(a->B,xx,a->slvec0b);

1296:   /* copy x into the vec slvec0 */
1297:   VecGetArray(a->slvec0,&from);
1298:   VecGetArrayRead(xx,&x);

1300:   PetscMemcpy(from,x,bs*mbs*sizeof(MatScalar));
1301:   VecRestoreArray(a->slvec0,&from);
1302:   VecRestoreArrayRead(xx,&x);

1304:   VecScatterBegin(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);
1305:   VecScatterEnd(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);
1306:   /* supperdiagonal part */
1307:   (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,yy);
1308:   return(0);
1309: }

1311: PetscErrorCode MatMult_MPISBAIJ_2comm(Mat A,Vec xx,Vec yy)
1312: {
1313:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;
1315:   PetscInt       nt;

1318:   VecGetLocalSize(xx,&nt);
1319:   if (nt != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx");

1321:   VecGetLocalSize(yy,&nt);
1322:   if (nt != A->rmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible parition of A and yy");

1324:   VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
1325:   /* do diagonal part */
1326:   (*a->A->ops->mult)(a->A,xx,yy);
1327:   /* do supperdiagonal part */
1328:   VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
1329:   (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);
1330:   /* do subdiagonal part */
1331:   (*a->B->ops->multtranspose)(a->B,xx,a->lvec);
1332:   VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
1333:   VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
1334:   return(0);
1335: }

1337: PetscErrorCode MatMultAdd_MPISBAIJ(Mat A,Vec xx,Vec yy,Vec zz)
1338: {
1339:   Mat_MPISBAIJ      *a = (Mat_MPISBAIJ*)A->data;
1340:   PetscErrorCode    ierr;
1341:   PetscInt          mbs=a->mbs,bs=A->rmap->bs;
1342:   PetscScalar       *from,zero=0.0;
1343:   const PetscScalar *x;

1346:   /*
1347:   PetscSynchronizedPrintf(PetscObjectComm((PetscObject)A)," MatMultAdd is called ...\n");
1348:   PetscSynchronizedFlush(PetscObjectComm((PetscObject)A),PETSC_STDOUT);
1349:   */
1350:   /* diagonal part */
1351:   (*a->A->ops->multadd)(a->A,xx,yy,a->slvec1a);
1352:   VecSet(a->slvec1b,zero);

1354:   /* subdiagonal part */
1355:   (*a->B->ops->multtranspose)(a->B,xx,a->slvec0b);

1357:   /* copy x into the vec slvec0 */
1358:   VecGetArray(a->slvec0,&from);
1359:   VecGetArrayRead(xx,&x);
1360:   PetscMemcpy(from,x,bs*mbs*sizeof(MatScalar));
1361:   VecRestoreArray(a->slvec0,&from);

1363:   VecScatterBegin(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);
1364:   VecRestoreArrayRead(xx,&x);
1365:   VecScatterEnd(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);

1367:   /* supperdiagonal part */
1368:   (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,zz);
1369:   return(0);
1370: }

1372: PetscErrorCode MatMultAdd_MPISBAIJ_2comm(Mat A,Vec xx,Vec yy,Vec zz)
1373: {
1374:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;

1378:   VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
1379:   /* do diagonal part */
1380:   (*a->A->ops->multadd)(a->A,xx,yy,zz);
1381:   /* do supperdiagonal part */
1382:   VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
1383:   (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);

1385:   /* do subdiagonal part */
1386:   (*a->B->ops->multtranspose)(a->B,xx,a->lvec);
1387:   VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);
1388:   VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);
1389:   return(0);
1390: }

1392: /*
1393:   This only works correctly for square matrices where the subblock A->A is the
1394:    diagonal block
1395: */
1396: PetscErrorCode MatGetDiagonal_MPISBAIJ(Mat A,Vec v)
1397: {
1398:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;

1402:   /* if (a->rmap->N != a->cmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block"); */
1403:   MatGetDiagonal(a->A,v);
1404:   return(0);
1405: }

1407: PetscErrorCode MatScale_MPISBAIJ(Mat A,PetscScalar aa)
1408: {
1409:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;

1413:   MatScale(a->A,aa);
1414:   MatScale(a->B,aa);
1415:   return(0);
1416: }

1418: PetscErrorCode MatGetRow_MPISBAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
1419: {
1420:   Mat_MPISBAIJ   *mat = (Mat_MPISBAIJ*)matin->data;
1421:   PetscScalar    *vworkA,*vworkB,**pvA,**pvB,*v_p;
1423:   PetscInt       bs = matin->rmap->bs,bs2 = mat->bs2,i,*cworkA,*cworkB,**pcA,**pcB;
1424:   PetscInt       nztot,nzA,nzB,lrow,brstart = matin->rmap->rstart,brend = matin->rmap->rend;
1425:   PetscInt       *cmap,*idx_p,cstart = mat->rstartbs;

1428:   if (mat->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Already active");
1429:   mat->getrowactive = PETSC_TRUE;

1431:   if (!mat->rowvalues && (idx || v)) {
1432:     /*
1433:         allocate enough space to hold information from the longest row.
1434:     */
1435:     Mat_SeqSBAIJ *Aa = (Mat_SeqSBAIJ*)mat->A->data;
1436:     Mat_SeqBAIJ  *Ba = (Mat_SeqBAIJ*)mat->B->data;
1437:     PetscInt     max = 1,mbs = mat->mbs,tmp;
1438:     for (i=0; i<mbs; i++) {
1439:       tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; /* row length */
1440:       if (max < tmp) max = tmp;
1441:     }
1442:     PetscMalloc2(max*bs2,&mat->rowvalues,max*bs2,&mat->rowindices);
1443:   }

1445:   if (row < brstart || row >= brend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local rows");
1446:   lrow = row - brstart;  /* local row index */

1448:   pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB;
1449:   if (!v)   {pvA = 0; pvB = 0;}
1450:   if (!idx) {pcA = 0; if (!v) pcB = 0;}
1451:   (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);
1452:   (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);
1453:   nztot = nzA + nzB;

1455:   cmap = mat->garray;
1456:   if (v  || idx) {
1457:     if (nztot) {
1458:       /* Sort by increasing column numbers, assuming A and B already sorted */
1459:       PetscInt imark = -1;
1460:       if (v) {
1461:         *v = v_p = mat->rowvalues;
1462:         for (i=0; i<nzB; i++) {
1463:           if (cmap[cworkB[i]/bs] < cstart) v_p[i] = vworkB[i];
1464:           else break;
1465:         }
1466:         imark = i;
1467:         for (i=0; i<nzA; i++)     v_p[imark+i] = vworkA[i];
1468:         for (i=imark; i<nzB; i++) v_p[nzA+i]   = vworkB[i];
1469:       }
1470:       if (idx) {
1471:         *idx = idx_p = mat->rowindices;
1472:         if (imark > -1) {
1473:           for (i=0; i<imark; i++) {
1474:             idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs;
1475:           }
1476:         } else {
1477:           for (i=0; i<nzB; i++) {
1478:             if (cmap[cworkB[i]/bs] < cstart) idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs;
1479:             else break;
1480:           }
1481:           imark = i;
1482:         }
1483:         for (i=0; i<nzA; i++)     idx_p[imark+i] = cstart*bs + cworkA[i];
1484:         for (i=imark; i<nzB; i++) idx_p[nzA+i]   = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ;
1485:       }
1486:     } else {
1487:       if (idx) *idx = 0;
1488:       if (v)   *v   = 0;
1489:     }
1490:   }
1491:   *nz  = nztot;
1492:   (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);
1493:   (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);
1494:   return(0);
1495: }

1497: PetscErrorCode MatRestoreRow_MPISBAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
1498: {
1499:   Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data;

1502:   if (!baij->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"MatGetRow() must be called first");
1503:   baij->getrowactive = PETSC_FALSE;
1504:   return(0);
1505: }

1507: PetscErrorCode MatGetRowUpperTriangular_MPISBAIJ(Mat A)
1508: {
1509:   Mat_MPISBAIJ *a  = (Mat_MPISBAIJ*)A->data;
1510:   Mat_SeqSBAIJ *aA = (Mat_SeqSBAIJ*)a->A->data;

1513:   aA->getrow_utriangular = PETSC_TRUE;
1514:   return(0);
1515: }
1516: PetscErrorCode MatRestoreRowUpperTriangular_MPISBAIJ(Mat A)
1517: {
1518:   Mat_MPISBAIJ *a  = (Mat_MPISBAIJ*)A->data;
1519:   Mat_SeqSBAIJ *aA = (Mat_SeqSBAIJ*)a->A->data;

1522:   aA->getrow_utriangular = PETSC_FALSE;
1523:   return(0);
1524: }

1526: PetscErrorCode MatRealPart_MPISBAIJ(Mat A)
1527: {
1528:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;

1532:   MatRealPart(a->A);
1533:   MatRealPart(a->B);
1534:   return(0);
1535: }

1537: PetscErrorCode MatImaginaryPart_MPISBAIJ(Mat A)
1538: {
1539:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;

1543:   MatImaginaryPart(a->A);
1544:   MatImaginaryPart(a->B);
1545:   return(0);
1546: }

1548: /* Check if isrow is a subset of iscol_local, called by MatCreateSubMatrix_MPISBAIJ()
1549:    Input: isrow       - distributed(parallel),
1550:           iscol_local - locally owned (seq)
1551: */
1552: PetscErrorCode ISEqual_private(IS isrow,IS iscol_local,PetscBool  *flg)
1553: {
1555:   PetscInt       sz1,sz2,*a1,*a2,i,j,k,nmatch;
1556:   const PetscInt *ptr1,*ptr2;

1559:   ISGetLocalSize(isrow,&sz1);
1560:   ISGetLocalSize(iscol_local,&sz2);
1561:   if (sz1 > sz2) {
1562:     *flg = PETSC_FALSE;
1563:     return(0);
1564:   }

1566:   ISGetIndices(isrow,&ptr1);
1567:   ISGetIndices(iscol_local,&ptr2);

1569:   PetscMalloc1(sz1,&a1);
1570:   PetscMalloc1(sz2,&a2);
1571:   PetscMemcpy(a1,ptr1,sz1*sizeof(PetscInt));
1572:   PetscMemcpy(a2,ptr2,sz2*sizeof(PetscInt));
1573:   PetscSortInt(sz1,a1);
1574:   PetscSortInt(sz2,a2);

1576:   nmatch=0;
1577:   k     = 0;
1578:   for (i=0; i<sz1; i++){
1579:     for (j=k; j<sz2; j++){
1580:       if (a1[i] == a2[j]) {
1581:         k = j; nmatch++;
1582:         break;
1583:       }
1584:     }
1585:   }
1586:   ISRestoreIndices(isrow,&ptr1);
1587:   ISRestoreIndices(iscol_local,&ptr2);
1588:   PetscFree(a1);
1589:   PetscFree(a2);
1590:   if (nmatch < sz1) {
1591:     *flg = PETSC_FALSE;
1592:   } else {
1593:     *flg = PETSC_TRUE;
1594:   }
1595:   return(0);
1596: }

1598: PetscErrorCode MatCreateSubMatrix_MPISBAIJ(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat)
1599: {
1601:   IS             iscol_local;
1602:   PetscInt       csize;
1603:   PetscBool      isequal;

1606:   ISGetLocalSize(iscol,&csize);
1607:   if (call == MAT_REUSE_MATRIX) {
1608:     PetscObjectQuery((PetscObject)*newmat,"ISAllGather",(PetscObject*)&iscol_local);
1609:     if (!iscol_local) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse");
1610:   } else {
1611:     ISAllGather(iscol,&iscol_local);
1612:     ISEqual_private(isrow,iscol_local,&isequal);
1613:     if (!isequal) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"For symmetric format, iscol must equal isrow");
1614:   }

1616:   /* now call MatCreateSubMatrix_MPIBAIJ() */
1617:   MatCreateSubMatrix_MPIBAIJ_Private(mat,isrow,iscol_local,csize,call,newmat);
1618:   if (call == MAT_INITIAL_MATRIX) {
1619:     PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);
1620:     ISDestroy(&iscol_local);
1621:   }
1622:   return(0);
1623: }

1625: PetscErrorCode MatZeroEntries_MPISBAIJ(Mat A)
1626: {
1627:   Mat_MPISBAIJ   *l = (Mat_MPISBAIJ*)A->data;

1631:   MatZeroEntries(l->A);
1632:   MatZeroEntries(l->B);
1633:   return(0);
1634: }

1636: PetscErrorCode MatGetInfo_MPISBAIJ(Mat matin,MatInfoType flag,MatInfo *info)
1637: {
1638:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)matin->data;
1639:   Mat            A  = a->A,B = a->B;
1641:   PetscReal      isend[5],irecv[5];

1644:   info->block_size = (PetscReal)matin->rmap->bs;

1646:   MatGetInfo(A,MAT_LOCAL,info);

1648:   isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded;
1649:   isend[3] = info->memory;  isend[4] = info->mallocs;

1651:   MatGetInfo(B,MAT_LOCAL,info);

1653:   isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded;
1654:   isend[3] += info->memory;  isend[4] += info->mallocs;
1655:   if (flag == MAT_LOCAL) {
1656:     info->nz_used      = isend[0];
1657:     info->nz_allocated = isend[1];
1658:     info->nz_unneeded  = isend[2];
1659:     info->memory       = isend[3];
1660:     info->mallocs      = isend[4];
1661:   } else if (flag == MAT_GLOBAL_MAX) {
1662:     MPIU_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)matin));

1664:     info->nz_used      = irecv[0];
1665:     info->nz_allocated = irecv[1];
1666:     info->nz_unneeded  = irecv[2];
1667:     info->memory       = irecv[3];
1668:     info->mallocs      = irecv[4];
1669:   } else if (flag == MAT_GLOBAL_SUM) {
1670:     MPIU_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)matin));

1672:     info->nz_used      = irecv[0];
1673:     info->nz_allocated = irecv[1];
1674:     info->nz_unneeded  = irecv[2];
1675:     info->memory       = irecv[3];
1676:     info->mallocs      = irecv[4];
1677:   } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Unknown MatInfoType argument %d",(int)flag);
1678:   info->fill_ratio_given  = 0; /* no parallel LU/ILU/Cholesky */
1679:   info->fill_ratio_needed = 0;
1680:   info->factor_mallocs    = 0;
1681:   return(0);
1682: }

1684: PetscErrorCode MatSetOption_MPISBAIJ(Mat A,MatOption op,PetscBool flg)
1685: {
1686:   Mat_MPISBAIJ   *a  = (Mat_MPISBAIJ*)A->data;
1687:   Mat_SeqSBAIJ   *aA = (Mat_SeqSBAIJ*)a->A->data;

1691:   switch (op) {
1692:   case MAT_NEW_NONZERO_LOCATIONS:
1693:   case MAT_NEW_NONZERO_ALLOCATION_ERR:
1694:   case MAT_UNUSED_NONZERO_LOCATION_ERR:
1695:   case MAT_KEEP_NONZERO_PATTERN:
1696:   case MAT_SUBMAT_SINGLEIS:
1697:   case MAT_NEW_NONZERO_LOCATION_ERR:
1698:     MatCheckPreallocated(A,1);
1699:     MatSetOption(a->A,op,flg);
1700:     MatSetOption(a->B,op,flg);
1701:     break;
1702:   case MAT_ROW_ORIENTED:
1703:     MatCheckPreallocated(A,1);
1704:     a->roworiented = flg;

1706:     MatSetOption(a->A,op,flg);
1707:     MatSetOption(a->B,op,flg);
1708:     break;
1709:   case MAT_NEW_DIAGONALS:
1710:     PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);
1711:     break;
1712:   case MAT_IGNORE_OFF_PROC_ENTRIES:
1713:     a->donotstash = flg;
1714:     break;
1715:   case MAT_USE_HASH_TABLE:
1716:     a->ht_flag = flg;
1717:     break;
1718:   case MAT_HERMITIAN:
1719:     MatCheckPreallocated(A,1);
1720:     if (!A->assembled) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Must call MatAssemblyEnd() first");
1721:     MatSetOption(a->A,op,flg);
1722: #if defined(PETSC_USE_COMPLEX)
1723:     A->ops->mult = MatMult_MPISBAIJ_Hermitian;
1724: #endif
1725:     break;
1726:   case MAT_SPD:
1727:     A->spd_set = PETSC_TRUE;
1728:     A->spd     = flg;
1729:     if (flg) {
1730:       A->symmetric                  = PETSC_TRUE;
1731:       A->structurally_symmetric     = PETSC_TRUE;
1732:       A->symmetric_set              = PETSC_TRUE;
1733:       A->structurally_symmetric_set = PETSC_TRUE;
1734:     }
1735:     break;
1736:   case MAT_SYMMETRIC:
1737:     MatCheckPreallocated(A,1);
1738:     MatSetOption(a->A,op,flg);
1739:     break;
1740:   case MAT_STRUCTURALLY_SYMMETRIC:
1741:     MatCheckPreallocated(A,1);
1742:     MatSetOption(a->A,op,flg);
1743:     break;
1744:   case MAT_SYMMETRY_ETERNAL:
1745:     if (!flg) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Matrix must be symmetric");
1746:     PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);
1747:     break;
1748:   case MAT_IGNORE_LOWER_TRIANGULAR:
1749:     aA->ignore_ltriangular = flg;
1750:     break;
1751:   case MAT_ERROR_LOWER_TRIANGULAR:
1752:     aA->ignore_ltriangular = flg;
1753:     break;
1754:   case MAT_GETROW_UPPERTRIANGULAR:
1755:     aA->getrow_utriangular = flg;
1756:     break;
1757:   default:
1758:     SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %d",op);
1759:   }
1760:   return(0);
1761: }

1763: PetscErrorCode MatTranspose_MPISBAIJ(Mat A,MatReuse reuse,Mat *B)
1764: {

1768:   if (reuse == MAT_INITIAL_MATRIX) {
1769:     MatDuplicate(A,MAT_COPY_VALUES,B);
1770:   }  else if (reuse == MAT_REUSE_MATRIX) {
1771:     MatCopy(A,*B,SAME_NONZERO_PATTERN);
1772:   }
1773:   return(0);
1774: }

1776: PetscErrorCode MatDiagonalScale_MPISBAIJ(Mat mat,Vec ll,Vec rr)
1777: {
1778:   Mat_MPISBAIJ   *baij = (Mat_MPISBAIJ*)mat->data;
1779:   Mat            a     = baij->A, b=baij->B;
1781:   PetscInt       nv,m,n;
1782:   PetscBool      flg;

1785:   if (ll != rr) {
1786:     VecEqual(ll,rr,&flg);
1787:     if (!flg) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"For symmetric format, left and right scaling vectors must be same\n");
1788:   }
1789:   if (!ll) return(0);

1791:   MatGetLocalSize(mat,&m,&n);
1792:   if (m != n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"For symmetric format, local size %d %d must be same",m,n);

1794:   VecGetLocalSize(rr,&nv);
1795:   if (nv!=n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Left and right vector non-conforming local size");

1797:   VecScatterBegin(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);

1799:   /* left diagonalscale the off-diagonal part */
1800:   (*b->ops->diagonalscale)(b,ll,NULL);

1802:   /* scale the diagonal part */
1803:   (*a->ops->diagonalscale)(a,ll,rr);

1805:   /* right diagonalscale the off-diagonal part */
1806:   VecScatterEnd(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);
1807:   (*b->ops->diagonalscale)(b,NULL,baij->lvec);
1808:   return(0);
1809: }

1811: PetscErrorCode MatSetUnfactored_MPISBAIJ(Mat A)
1812: {
1813:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;

1817:   MatSetUnfactored(a->A);
1818:   return(0);
1819: }

1821: static PetscErrorCode MatDuplicate_MPISBAIJ(Mat,MatDuplicateOption,Mat*);

1823: PetscErrorCode MatEqual_MPISBAIJ(Mat A,Mat B,PetscBool  *flag)
1824: {
1825:   Mat_MPISBAIJ   *matB = (Mat_MPISBAIJ*)B->data,*matA = (Mat_MPISBAIJ*)A->data;
1826:   Mat            a,b,c,d;
1827:   PetscBool      flg;

1831:   a = matA->A; b = matA->B;
1832:   c = matB->A; d = matB->B;

1834:   MatEqual(a,c,&flg);
1835:   if (flg) {
1836:     MatEqual(b,d,&flg);
1837:   }
1838:   MPIU_Allreduce(&flg,flag,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)A));
1839:   return(0);
1840: }

1842: PetscErrorCode MatCopy_MPISBAIJ(Mat A,Mat B,MatStructure str)
1843: {
1845:   PetscBool      isbaij;

1848:   PetscObjectTypeCompareAny((PetscObject)B,&isbaij,MATSEQSBAIJ,MATMPISBAIJ,"");
1849:   if (!isbaij) SETERRQ1(PetscObjectComm((PetscObject)B),PETSC_ERR_SUP,"Not for matrix type %s",((PetscObject)B)->type_name);
1850:   /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */
1851:   if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) {
1852:     MatGetRowUpperTriangular(A);
1853:     MatCopy_Basic(A,B,str);
1854:     MatRestoreRowUpperTriangular(A);
1855:   } else {
1856:     Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data;
1857:     Mat_MPISBAIJ *b = (Mat_MPISBAIJ*)B->data;

1859:     MatCopy(a->A,b->A,str);
1860:     MatCopy(a->B,b->B,str);
1861:   }
1862:   PetscObjectStateIncrease((PetscObject)B);
1863:   return(0);
1864: }

1866: PetscErrorCode MatSetUp_MPISBAIJ(Mat A)
1867: {

1871:   MatMPISBAIJSetPreallocation(A,A->rmap->bs,PETSC_DEFAULT,0,PETSC_DEFAULT,0);
1872:   return(0);
1873: }

1875: PetscErrorCode MatAXPY_MPISBAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str)
1876: {
1878:   Mat_MPISBAIJ   *xx=(Mat_MPISBAIJ*)X->data,*yy=(Mat_MPISBAIJ*)Y->data;
1879:   PetscBLASInt   bnz,one=1;
1880:   Mat_SeqSBAIJ   *xa,*ya;
1881:   Mat_SeqBAIJ    *xb,*yb;

1884:   if (str == SAME_NONZERO_PATTERN) {
1885:     PetscScalar alpha = a;
1886:     xa   = (Mat_SeqSBAIJ*)xx->A->data;
1887:     ya   = (Mat_SeqSBAIJ*)yy->A->data;
1888:     PetscBLASIntCast(xa->nz,&bnz);
1889:     PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,xa->a,&one,ya->a,&one));
1890:     xb   = (Mat_SeqBAIJ*)xx->B->data;
1891:     yb   = (Mat_SeqBAIJ*)yy->B->data;
1892:     PetscBLASIntCast(xb->nz,&bnz);
1893:     PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,xb->a,&one,yb->a,&one));
1894:     PetscObjectStateIncrease((PetscObject)Y);
1895:   } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */
1896:     MatSetOption(X,MAT_GETROW_UPPERTRIANGULAR,PETSC_TRUE);
1897:     MatAXPY_Basic(Y,a,X,str);
1898:     MatSetOption(X,MAT_GETROW_UPPERTRIANGULAR,PETSC_FALSE);
1899:   } else {
1900:     Mat      B;
1901:     PetscInt *nnz_d,*nnz_o,bs=Y->rmap->bs;
1902:     if (bs != X->rmap->bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Matrices must have same block size");
1903:     MatGetRowUpperTriangular(X);
1904:     MatGetRowUpperTriangular(Y);
1905:     PetscMalloc1(yy->A->rmap->N,&nnz_d);
1906:     PetscMalloc1(yy->B->rmap->N,&nnz_o);
1907:     MatCreate(PetscObjectComm((PetscObject)Y),&B);
1908:     PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);
1909:     MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);
1910:     MatSetBlockSizesFromMats(B,Y,Y);
1911:     MatSetType(B,MATMPISBAIJ);
1912:     MatAXPYGetPreallocation_SeqSBAIJ(yy->A,xx->A,nnz_d);
1913:     MatAXPYGetPreallocation_MPIBAIJ(yy->B,yy->garray,xx->B,xx->garray,nnz_o);
1914:     MatMPISBAIJSetPreallocation(B,bs,0,nnz_d,0,nnz_o);
1915:     MatAXPY_BasicWithPreallocation(B,Y,a,X,str);
1916:     MatHeaderReplace(Y,&B);
1917:     PetscFree(nnz_d);
1918:     PetscFree(nnz_o);
1919:     MatRestoreRowUpperTriangular(X);
1920:     MatRestoreRowUpperTriangular(Y);
1921:   }
1922:   return(0);
1923: }

1925: PetscErrorCode MatCreateSubMatrices_MPISBAIJ(Mat A,PetscInt n,const IS irow[],const IS icol[],MatReuse scall,Mat *B[])
1926: {
1928:   PetscInt       i;
1929:   PetscBool      flg;

1932:   MatCreateSubMatrices_MPIBAIJ(A,n,irow,icol,scall,B); /* B[] are sbaij matrices */
1933:   for (i=0; i<n; i++) {
1934:     ISEqual(irow[i],icol[i],&flg);
1935:     if (!flg) {
1936:       MatSeqSBAIJZeroOps_Private(*B[i]);
1937:     }
1938:   }
1939:   return(0);
1940: }

1942: PetscErrorCode MatShift_MPISBAIJ(Mat Y,PetscScalar a)
1943: {
1945:   Mat_MPISBAIJ    *maij = (Mat_MPISBAIJ*)Y->data;
1946:   Mat_SeqSBAIJ    *aij = (Mat_SeqSBAIJ*)maij->A->data;

1949:   if (!Y->preallocated) {
1950:     MatMPISBAIJSetPreallocation(Y,Y->rmap->bs,1,NULL,0,NULL);
1951:   } else if (!aij->nz) {
1952:     PetscInt nonew = aij->nonew;
1953:     MatSeqSBAIJSetPreallocation(maij->A,Y->rmap->bs,1,NULL);
1954:     aij->nonew = nonew;
1955:   }
1956:   MatShift_Basic(Y,a);
1957:   return(0);
1958: }

1960: PetscErrorCode MatMissingDiagonal_MPISBAIJ(Mat A,PetscBool  *missing,PetscInt *d)
1961: {
1962:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;

1966:   if (A->rmap->n != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only works for square matrices");
1967:   MatMissingDiagonal(a->A,missing,d);
1968:   if (d) {
1969:     PetscInt rstart;
1970:     MatGetOwnershipRange(A,&rstart,NULL);
1971:     *d += rstart/A->rmap->bs;

1973:   }
1974:   return(0);
1975: }

1977: PetscErrorCode  MatGetDiagonalBlock_MPISBAIJ(Mat A,Mat *a)
1978: {
1980:   *a = ((Mat_MPISBAIJ*)A->data)->A;
1981:   return(0);
1982: }

1984: /* -------------------------------------------------------------------*/
1985: static struct _MatOps MatOps_Values = {MatSetValues_MPISBAIJ,
1986:                                        MatGetRow_MPISBAIJ,
1987:                                        MatRestoreRow_MPISBAIJ,
1988:                                        MatMult_MPISBAIJ,
1989:                                /*  4*/ MatMultAdd_MPISBAIJ,
1990:                                        MatMult_MPISBAIJ,       /* transpose versions are same as non-transpose */
1991:                                        MatMultAdd_MPISBAIJ,
1992:                                        0,
1993:                                        0,
1994:                                        0,
1995:                                /* 10*/ 0,
1996:                                        0,
1997:                                        0,
1998:                                        MatSOR_MPISBAIJ,
1999:                                        MatTranspose_MPISBAIJ,
2000:                                /* 15*/ MatGetInfo_MPISBAIJ,
2001:                                        MatEqual_MPISBAIJ,
2002:                                        MatGetDiagonal_MPISBAIJ,
2003:                                        MatDiagonalScale_MPISBAIJ,
2004:                                        MatNorm_MPISBAIJ,
2005:                                /* 20*/ MatAssemblyBegin_MPISBAIJ,
2006:                                        MatAssemblyEnd_MPISBAIJ,
2007:                                        MatSetOption_MPISBAIJ,
2008:                                        MatZeroEntries_MPISBAIJ,
2009:                                /* 24*/ 0,
2010:                                        0,
2011:                                        0,
2012:                                        0,
2013:                                        0,
2014:                                /* 29*/ MatSetUp_MPISBAIJ,
2015:                                        0,
2016:                                        0,
2017:                                        MatGetDiagonalBlock_MPISBAIJ,
2018:                                        0,
2019:                                /* 34*/ MatDuplicate_MPISBAIJ,
2020:                                        0,
2021:                                        0,
2022:                                        0,
2023:                                        0,
2024:                                /* 39*/ MatAXPY_MPISBAIJ,
2025:                                        MatCreateSubMatrices_MPISBAIJ,
2026:                                        MatIncreaseOverlap_MPISBAIJ,
2027:                                        MatGetValues_MPISBAIJ,
2028:                                        MatCopy_MPISBAIJ,
2029:                                /* 44*/ 0,
2030:                                        MatScale_MPISBAIJ,
2031:                                        MatShift_MPISBAIJ,
2032:                                        0,
2033:                                        0,
2034:                                /* 49*/ 0,
2035:                                        0,
2036:                                        0,
2037:                                        0,
2038:                                        0,
2039:                                /* 54*/ 0,
2040:                                        0,
2041:                                        MatSetUnfactored_MPISBAIJ,
2042:                                        0,
2043:                                        MatSetValuesBlocked_MPISBAIJ,
2044:                                /* 59*/ MatCreateSubMatrix_MPISBAIJ,
2045:                                        0,
2046:                                        0,
2047:                                        0,
2048:                                        0,
2049:                                /* 64*/ 0,
2050:                                        0,
2051:                                        0,
2052:                                        0,
2053:                                        0,
2054:                                /* 69*/ MatGetRowMaxAbs_MPISBAIJ,
2055:                                        0,
2056:                                        0,
2057:                                        0,
2058:                                        0,
2059:                                /* 74*/ 0,
2060:                                        0,
2061:                                        0,
2062:                                        0,
2063:                                        0,
2064:                                /* 79*/ 0,
2065:                                        0,
2066:                                        0,
2067:                                        0,
2068:                                        MatLoad_MPISBAIJ,
2069:                                /* 84*/ 0,
2070:                                        0,
2071:                                        0,
2072:                                        0,
2073:                                        0,
2074:                                /* 89*/ 0,
2075:                                        0,
2076:                                        0,
2077:                                        0,
2078:                                        0,
2079:                                /* 94*/ 0,
2080:                                        0,
2081:                                        0,
2082:                                        0,
2083:                                        0,
2084:                                /* 99*/ 0,
2085:                                        0,
2086:                                        0,
2087:                                        0,
2088:                                        0,
2089:                                /*104*/ 0,
2090:                                        MatRealPart_MPISBAIJ,
2091:                                        MatImaginaryPart_MPISBAIJ,
2092:                                        MatGetRowUpperTriangular_MPISBAIJ,
2093:                                        MatRestoreRowUpperTriangular_MPISBAIJ,
2094:                                /*109*/ 0,
2095:                                        0,
2096:                                        0,
2097:                                        0,
2098:                                        MatMissingDiagonal_MPISBAIJ,
2099:                                /*114*/ 0,
2100:                                        0,
2101:                                        0,
2102:                                        0,
2103:                                        0,
2104:                                /*119*/ 0,
2105:                                        0,
2106:                                        0,
2107:                                        0,
2108:                                        0,
2109:                                /*124*/ 0,
2110:                                        0,
2111:                                        0,
2112:                                        0,
2113:                                        0,
2114:                                /*129*/ 0,
2115:                                        0,
2116:                                        0,
2117:                                        0,
2118:                                        0,
2119:                                /*134*/ 0,
2120:                                        0,
2121:                                        0,
2122:                                        0,
2123:                                        0,
2124:                                /*139*/ MatSetBlockSizes_Default,
2125:                                        0,
2126:                                        0,
2127:                                        0,
2128:                                        0,
2129:                                 /*144*/MatCreateMPIMatConcatenateSeqMat_MPISBAIJ
2130: };

2132: PetscErrorCode  MatMPISBAIJSetPreallocation_MPISBAIJ(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt *d_nnz,PetscInt o_nz,const PetscInt *o_nnz)
2133: {
2134:   Mat_MPISBAIJ   *b;
2136:   PetscInt       i,mbs,Mbs;
2137:   PetscMPIInt    size;

2140:   MatSetBlockSize(B,PetscAbs(bs));
2141:   PetscLayoutSetUp(B->rmap);
2142:   PetscLayoutSetUp(B->cmap);
2143:   PetscLayoutGetBlockSize(B->rmap,&bs);

2145:   b   = (Mat_MPISBAIJ*)B->data;
2146:   mbs = B->rmap->n/bs;
2147:   Mbs = B->rmap->N/bs;
2148:   if (mbs*bs != B->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"No of local rows %D must be divisible by blocksize %D",B->rmap->N,bs);

2150:   B->rmap->bs = bs;
2151:   b->bs2      = bs*bs;
2152:   b->mbs      = mbs;
2153:   b->Mbs      = Mbs;
2154:   b->nbs      = B->cmap->n/bs;
2155:   b->Nbs      = B->cmap->N/bs;

2157:   for (i=0; i<=b->size; i++) {
2158:     b->rangebs[i] = B->rmap->range[i]/bs;
2159:   }
2160:   b->rstartbs = B->rmap->rstart/bs;
2161:   b->rendbs   = B->rmap->rend/bs;

2163:   b->cstartbs = B->cmap->rstart/bs;
2164:   b->cendbs   = B->cmap->rend/bs;

2166: #if defined(PETSC_USE_CTABLE)
2167:   PetscTableDestroy(&b->colmap);
2168: #else
2169:   PetscFree(b->colmap);
2170: #endif
2171:   PetscFree(b->garray);
2172:   VecDestroy(&b->lvec);
2173:   VecScatterDestroy(&b->Mvctx);
2174:   VecDestroy(&b->slvec0);
2175:   VecDestroy(&b->slvec0b);
2176:   VecDestroy(&b->slvec1);
2177:   VecDestroy(&b->slvec1a);
2178:   VecDestroy(&b->slvec1b);
2179:   VecScatterDestroy(&b->sMvctx);

2181:   /* Because the B will have been resized we simply destroy it and create a new one each time */
2182:   MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);
2183:   MatDestroy(&b->B);
2184:   MatCreate(PETSC_COMM_SELF,&b->B);
2185:   MatSetSizes(b->B,B->rmap->n,size > 1 ? B->cmap->N : 0,B->rmap->n,size > 1 ? B->cmap->N : 0);
2186:   MatSetType(b->B,MATSEQBAIJ);
2187:   PetscLogObjectParent((PetscObject)B,(PetscObject)b->B);

2189:   if (!B->preallocated) {
2190:     MatCreate(PETSC_COMM_SELF,&b->A);
2191:     MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);
2192:     MatSetType(b->A,MATSEQSBAIJ);
2193:     PetscLogObjectParent((PetscObject)B,(PetscObject)b->A);
2194:     MatStashCreate_Private(PetscObjectComm((PetscObject)B),bs,&B->bstash);
2195:   }

2197:   MatSeqSBAIJSetPreallocation(b->A,bs,d_nz,d_nnz);
2198:   MatSeqBAIJSetPreallocation(b->B,bs,o_nz,o_nnz);

2200:   B->preallocated  = PETSC_TRUE;
2201:   B->was_assembled = PETSC_FALSE;
2202:   B->assembled     = PETSC_FALSE;
2203:   return(0);
2204: }

2206: PetscErrorCode MatMPISBAIJSetPreallocationCSR_MPISBAIJ(Mat B,PetscInt bs,const PetscInt ii[],const PetscInt jj[],const PetscScalar V[])
2207: {
2208:   PetscInt       m,rstart,cstart,cend;
2209:   PetscInt       i,j,d,nz,nz_max=0,*d_nnz=0,*o_nnz=0;
2210:   const PetscInt *JJ    =0;
2211:   PetscScalar    *values=0;

2215:   if (bs < 1) SETERRQ1(PetscObjectComm((PetscObject)B),PETSC_ERR_ARG_OUTOFRANGE,"Invalid block size specified, must be positive but it is %D",bs);
2216:   PetscLayoutSetBlockSize(B->rmap,bs);
2217:   PetscLayoutSetBlockSize(B->cmap,bs);
2218:   PetscLayoutSetUp(B->rmap);
2219:   PetscLayoutSetUp(B->cmap);
2220:   PetscLayoutGetBlockSize(B->rmap,&bs);
2221:   m      = B->rmap->n/bs;
2222:   rstart = B->rmap->rstart/bs;
2223:   cstart = B->cmap->rstart/bs;
2224:   cend   = B->cmap->rend/bs;

2226:   if (ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"ii[0] must be 0 but it is %D",ii[0]);
2227:   PetscMalloc2(m,&d_nnz,m,&o_nnz);
2228:   for (i=0; i<m; i++) {
2229:     nz = ii[i+1] - ii[i];
2230:     if (nz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative number of columns %D",i,nz);
2231:     nz_max = PetscMax(nz_max,nz);
2232:     JJ     = jj + ii[i];
2233:     for (j=0; j<nz; j++) {
2234:       if (*JJ >= cstart) break;
2235:       JJ++;
2236:     }
2237:     d = 0;
2238:     for (; j<nz; j++) {
2239:       if (*JJ++ >= cend) break;
2240:       d++;
2241:     }
2242:     d_nnz[i] = d;
2243:     o_nnz[i] = nz - d;
2244:   }
2245:   MatMPISBAIJSetPreallocation(B,bs,0,d_nnz,0,o_nnz);
2246:   PetscFree2(d_nnz,o_nnz);

2248:   values = (PetscScalar*)V;
2249:   if (!values) {
2250:     PetscMalloc1(bs*bs*nz_max,&values);
2251:     PetscMemzero(values,bs*bs*nz_max*sizeof(PetscScalar));
2252:   }
2253:   for (i=0; i<m; i++) {
2254:     PetscInt          row    = i + rstart;
2255:     PetscInt          ncols  = ii[i+1] - ii[i];
2256:     const PetscInt    *icols = jj + ii[i];
2257:     const PetscScalar *svals = values + (V ? (bs*bs*ii[i]) : 0);
2258:     MatSetValuesBlocked_MPISBAIJ(B,1,&row,ncols,icols,svals,INSERT_VALUES);
2259:   }

2261:   if (!V) { PetscFree(values); }
2262:   MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
2263:   MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);
2264:   MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);
2265:   return(0);
2266: }

2268: /*MC
2269:    MATMPISBAIJ - MATMPISBAIJ = "mpisbaij" - A matrix type to be used for distributed symmetric sparse block matrices,
2270:    based on block compressed sparse row format.  Only the upper triangular portion of the "diagonal" portion of
2271:    the matrix is stored.

2273:   For complex numbers by default this matrix is symmetric, NOT Hermitian symmetric. To make it Hermitian symmetric you
2274:   can call MatSetOption(Mat, MAT_HERMITIAN);

2276:    Options Database Keys:
2277: . -mat_type mpisbaij - sets the matrix type to "mpisbaij" during a call to MatSetFromOptions()

2279:   Level: beginner

2281: .seealso: MatCreateMPISBAIJ
2282: M*/

2284: PETSC_EXTERN PetscErrorCode MatCreate_MPISBAIJ(Mat B)
2285: {
2286:   Mat_MPISBAIJ   *b;
2288:   PetscBool      flg = PETSC_FALSE;

2291:   PetscNewLog(B,&b);
2292:   B->data = (void*)b;
2293:   PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));

2295:   B->ops->destroy = MatDestroy_MPISBAIJ;
2296:   B->ops->view    = MatView_MPISBAIJ;
2297:   B->assembled    = PETSC_FALSE;
2298:   B->insertmode   = NOT_SET_VALUES;

2300:   MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);
2301:   MPI_Comm_size(PetscObjectComm((PetscObject)B),&b->size);

2303:   /* build local table of row and column ownerships */
2304:   PetscMalloc1(b->size+2,&b->rangebs);

2306:   /* build cache for off array entries formed */
2307:   MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);

2309:   b->donotstash  = PETSC_FALSE;
2310:   b->colmap      = NULL;
2311:   b->garray      = NULL;
2312:   b->roworiented = PETSC_TRUE;

2314:   /* stuff used in block assembly */
2315:   b->barray = 0;

2317:   /* stuff used for matrix vector multiply */
2318:   b->lvec    = 0;
2319:   b->Mvctx   = 0;
2320:   b->slvec0  = 0;
2321:   b->slvec0b = 0;
2322:   b->slvec1  = 0;
2323:   b->slvec1a = 0;
2324:   b->slvec1b = 0;
2325:   b->sMvctx  = 0;

2327:   /* stuff for MatGetRow() */
2328:   b->rowindices   = 0;
2329:   b->rowvalues    = 0;
2330:   b->getrowactive = PETSC_FALSE;

2332:   /* hash table stuff */
2333:   b->ht           = 0;
2334:   b->hd           = 0;
2335:   b->ht_size      = 0;
2336:   b->ht_flag      = PETSC_FALSE;
2337:   b->ht_fact      = 0;
2338:   b->ht_total_ct  = 0;
2339:   b->ht_insert_ct = 0;

2341:   /* stuff for MatCreateSubMatrices_MPIBAIJ_local() */
2342:   b->ijonly = PETSC_FALSE;

2344:   b->in_loc = 0;
2345:   b->v_loc  = 0;
2346:   b->n_loc  = 0;

2348:   PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPISBAIJ);
2349:   PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPISBAIJ);
2350:   PetscObjectComposeFunction((PetscObject)B,"MatMPISBAIJSetPreallocation_C",MatMPISBAIJSetPreallocation_MPISBAIJ);
2351:   PetscObjectComposeFunction((PetscObject)B,"MatMPISBAIJSetPreallocationCSR_C",MatMPISBAIJSetPreallocationCSR_MPISBAIJ);
2352: #if defined(PETSC_HAVE_ELEMENTAL)
2353:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpisbaij_elemental_C",MatConvert_MPISBAIJ_Elemental);
2354: #endif
2355:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpisbaij_mpiaij_C",MatConvert_MPISBAIJ_XAIJ);
2356:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpisbaij_mpibaij_C",MatConvert_MPISBAIJ_XAIJ);

2358:   B->symmetric                  = PETSC_TRUE;
2359:   B->structurally_symmetric     = PETSC_TRUE;
2360:   B->symmetric_set              = PETSC_TRUE;
2361:   B->structurally_symmetric_set = PETSC_TRUE;
2362:   B->symmetric_eternal          = PETSC_TRUE;

2364:   B->hermitian                  = PETSC_FALSE;
2365:   B->hermitian_set              = PETSC_FALSE;

2367:   PetscObjectChangeTypeName((PetscObject)B,MATMPISBAIJ);
2368:   PetscOptionsBegin(PetscObjectComm((PetscObject)B),NULL,"Options for loading MPISBAIJ matrix 1","Mat");
2369:   PetscOptionsBool("-mat_use_hash_table","Use hash table to save memory in constructing matrix","MatSetOption",flg,&flg,NULL);
2370:   if (flg) {
2371:     PetscReal fact = 1.39;
2372:     MatSetOption(B,MAT_USE_HASH_TABLE,PETSC_TRUE);
2373:     PetscOptionsReal("-mat_use_hash_table","Use hash table factor","MatMPIBAIJSetHashTableFactor",fact,&fact,NULL);
2374:     if (fact <= 1.0) fact = 1.39;
2375:     MatMPIBAIJSetHashTableFactor(B,fact);
2376:     PetscInfo1(B,"Hash table Factor used %5.2f\n",fact);
2377:   }
2378:   PetscOptionsEnd();
2379:   return(0);
2380: }

2382: /*MC
2383:    MATSBAIJ - MATSBAIJ = "sbaij" - A matrix type to be used for symmetric block sparse matrices.

2385:    This matrix type is identical to MATSEQSBAIJ when constructed with a single process communicator,
2386:    and MATMPISBAIJ otherwise.

2388:    Options Database Keys:
2389: . -mat_type sbaij - sets the matrix type to "sbaij" during a call to MatSetFromOptions()

2391:   Level: beginner

2393: .seealso: MatCreateMPISBAIJ,MATSEQSBAIJ,MATMPISBAIJ
2394: M*/

2396: /*@C
2397:    MatMPISBAIJSetPreallocation - For good matrix assembly performance
2398:    the user should preallocate the matrix storage by setting the parameters
2399:    d_nz (or d_nnz) and o_nz (or o_nnz).  By setting these parameters accurately,
2400:    performance can be increased by more than a factor of 50.

2402:    Collective on Mat

2404:    Input Parameters:
2405: +  B - the matrix
2406: .  bs   - size of block, the blocks are ALWAYS square. One can use MatSetBlockSizes() to set a different row and column blocksize but the row
2407:           blocksize always defines the size of the blocks. The column blocksize sets the blocksize of the vectors obtained with MatCreateVecs()
2408: .  d_nz  - number of block nonzeros per block row in diagonal portion of local
2409:            submatrix  (same for all local rows)
2410: .  d_nnz - array containing the number of block nonzeros in the various block rows
2411:            in the upper triangular and diagonal part of the in diagonal portion of the local
2412:            (possibly different for each block row) or NULL.  If you plan to factor the matrix you must leave room
2413:            for the diagonal entry and set a value even if it is zero.
2414: .  o_nz  - number of block nonzeros per block row in the off-diagonal portion of local
2415:            submatrix (same for all local rows).
2416: -  o_nnz - array containing the number of nonzeros in the various block rows of the
2417:            off-diagonal portion of the local submatrix that is right of the diagonal
2418:            (possibly different for each block row) or NULL.


2421:    Options Database Keys:
2422: .   -mat_no_unroll - uses code that does not unroll the loops in the
2423:                      block calculations (much slower)
2424: .   -mat_block_size - size of the blocks to use

2426:    Notes:

2428:    If PETSC_DECIDE or  PETSC_DETERMINE is used for a particular argument on one processor
2429:    than it must be used on all processors that share the object for that argument.

2431:    If the *_nnz parameter is given then the *_nz parameter is ignored

2433:    Storage Information:
2434:    For a square global matrix we define each processor's diagonal portion
2435:    to be its local rows and the corresponding columns (a square submatrix);
2436:    each processor's off-diagonal portion encompasses the remainder of the
2437:    local matrix (a rectangular submatrix).

2439:    The user can specify preallocated storage for the diagonal part of
2440:    the local submatrix with either d_nz or d_nnz (not both).  Set
2441:    d_nz=PETSC_DEFAULT and d_nnz=NULL for PETSc to control dynamic
2442:    memory allocation.  Likewise, specify preallocated storage for the
2443:    off-diagonal part of the local submatrix with o_nz or o_nnz (not both).

2445:    You can call MatGetInfo() to get information on how effective the preallocation was;
2446:    for example the fields mallocs,nz_allocated,nz_used,nz_unneeded;
2447:    You can also run with the option -info and look for messages with the string
2448:    malloc in them to see if additional memory allocation was needed.

2450:    Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In
2451:    the figure below we depict these three local rows and all columns (0-11).

2453: .vb
2454:            0 1 2 3 4 5 6 7 8 9 10 11
2455:           --------------------------
2456:    row 3  |. . . d d d o o o o  o  o
2457:    row 4  |. . . d d d o o o o  o  o
2458:    row 5  |. . . d d d o o o o  o  o
2459:           --------------------------
2460: .ve

2462:    Thus, any entries in the d locations are stored in the d (diagonal)
2463:    submatrix, and any entries in the o locations are stored in the
2464:    o (off-diagonal) submatrix.  Note that the d matrix is stored in
2465:    MatSeqSBAIJ format and the o submatrix in MATSEQBAIJ format.

2467:    Now d_nz should indicate the number of block nonzeros per row in the upper triangular
2468:    plus the diagonal part of the d matrix,
2469:    and o_nz should indicate the number of block nonzeros per row in the o matrix

2471:    In general, for PDE problems in which most nonzeros are near the diagonal,
2472:    one expects d_nz >> o_nz.   For large problems you MUST preallocate memory
2473:    or you will get TERRIBLE performance; see the users' manual chapter on
2474:    matrices.

2476:    Level: intermediate

2478: .keywords: matrix, block, aij, compressed row, sparse, parallel

2480: .seealso: MatCreate(), MatCreateSeqSBAIJ(), MatSetValues(), MatCreateBAIJ(), PetscSplitOwnership()
2481: @*/
2482: PetscErrorCode  MatMPISBAIJSetPreallocation(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[])
2483: {

2490:   PetscTryMethod(B,"MatMPISBAIJSetPreallocation_C",(Mat,PetscInt,PetscInt,const PetscInt[],PetscInt,const PetscInt[]),(B,bs,d_nz,d_nnz,o_nz,o_nnz));
2491:   return(0);
2492: }

2494: /*@C
2495:    MatCreateSBAIJ - Creates a sparse parallel matrix in symmetric block AIJ format
2496:    (block compressed row).  For good matrix assembly performance
2497:    the user should preallocate the matrix storage by setting the parameters
2498:    d_nz (or d_nnz) and o_nz (or o_nnz).  By setting these parameters accurately,
2499:    performance can be increased by more than a factor of 50.

2501:    Collective on MPI_Comm

2503:    Input Parameters:
2504: +  comm - MPI communicator
2505: .  bs   - size of block, the blocks are ALWAYS square. One can use MatSetBlockSizes() to set a different row and column blocksize but the row
2506:           blocksize always defines the size of the blocks. The column blocksize sets the blocksize of the vectors obtained with MatCreateVecs()
2507: .  m - number of local rows (or PETSC_DECIDE to have calculated if M is given)
2508:            This value should be the same as the local size used in creating the
2509:            y vector for the matrix-vector product y = Ax.
2510: .  n - number of local columns (or PETSC_DECIDE to have calculated if N is given)
2511:            This value should be the same as the local size used in creating the
2512:            x vector for the matrix-vector product y = Ax.
2513: .  M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
2514: .  N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
2515: .  d_nz  - number of block nonzeros per block row in diagonal portion of local
2516:            submatrix  (same for all local rows)
2517: .  d_nnz - array containing the number of block nonzeros in the various block rows
2518:            in the upper triangular portion of the in diagonal portion of the local
2519:            (possibly different for each block block row) or NULL.
2520:            If you plan to factor the matrix you must leave room for the diagonal entry and
2521:            set its value even if it is zero.
2522: .  o_nz  - number of block nonzeros per block row in the off-diagonal portion of local
2523:            submatrix (same for all local rows).
2524: -  o_nnz - array containing the number of nonzeros in the various block rows of the
2525:            off-diagonal portion of the local submatrix (possibly different for
2526:            each block row) or NULL.

2528:    Output Parameter:
2529: .  A - the matrix

2531:    Options Database Keys:
2532: .   -mat_no_unroll - uses code that does not unroll the loops in the
2533:                      block calculations (much slower)
2534: .   -mat_block_size - size of the blocks to use
2535: .   -mat_mpi - use the parallel matrix data structures even on one processor
2536:                (defaults to using SeqBAIJ format on one processor)

2538:    It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(),
2539:    MatXXXXSetPreallocation() paradgm instead of this routine directly.
2540:    [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation]

2542:    Notes:
2543:    The number of rows and columns must be divisible by blocksize.
2544:    This matrix type does not support complex Hermitian operation.

2546:    The user MUST specify either the local or global matrix dimensions
2547:    (possibly both).

2549:    If PETSC_DECIDE or  PETSC_DETERMINE is used for a particular argument on one processor
2550:    than it must be used on all processors that share the object for that argument.

2552:    If the *_nnz parameter is given then the *_nz parameter is ignored

2554:    Storage Information:
2555:    For a square global matrix we define each processor's diagonal portion
2556:    to be its local rows and the corresponding columns (a square submatrix);
2557:    each processor's off-diagonal portion encompasses the remainder of the
2558:    local matrix (a rectangular submatrix).

2560:    The user can specify preallocated storage for the diagonal part of
2561:    the local submatrix with either d_nz or d_nnz (not both).  Set
2562:    d_nz=PETSC_DEFAULT and d_nnz=NULL for PETSc to control dynamic
2563:    memory allocation.  Likewise, specify preallocated storage for the
2564:    off-diagonal part of the local submatrix with o_nz or o_nnz (not both).

2566:    Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In
2567:    the figure below we depict these three local rows and all columns (0-11).

2569: .vb
2570:            0 1 2 3 4 5 6 7 8 9 10 11
2571:           --------------------------
2572:    row 3  |. . . d d d o o o o  o  o
2573:    row 4  |. . . d d d o o o o  o  o
2574:    row 5  |. . . d d d o o o o  o  o
2575:           --------------------------
2576: .ve

2578:    Thus, any entries in the d locations are stored in the d (diagonal)
2579:    submatrix, and any entries in the o locations are stored in the
2580:    o (off-diagonal) submatrix.  Note that the d matrix is stored in
2581:    MatSeqSBAIJ format and the o submatrix in MATSEQBAIJ format.

2583:    Now d_nz should indicate the number of block nonzeros per row in the upper triangular
2584:    plus the diagonal part of the d matrix,
2585:    and o_nz should indicate the number of block nonzeros per row in the o matrix.
2586:    In general, for PDE problems in which most nonzeros are near the diagonal,
2587:    one expects d_nz >> o_nz.   For large problems you MUST preallocate memory
2588:    or you will get TERRIBLE performance; see the users' manual chapter on
2589:    matrices.

2591:    Level: intermediate

2593: .keywords: matrix, block, aij, compressed row, sparse, parallel

2595: .seealso: MatCreate(), MatCreateSeqSBAIJ(), MatSetValues(), MatCreateBAIJ()
2596: @*/

2598: 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)
2599: {
2601:   PetscMPIInt    size;

2604:   MatCreate(comm,A);
2605:   MatSetSizes(*A,m,n,M,N);
2606:   MPI_Comm_size(comm,&size);
2607:   if (size > 1) {
2608:     MatSetType(*A,MATMPISBAIJ);
2609:     MatMPISBAIJSetPreallocation(*A,bs,d_nz,d_nnz,o_nz,o_nnz);
2610:   } else {
2611:     MatSetType(*A,MATSEQSBAIJ);
2612:     MatSeqSBAIJSetPreallocation(*A,bs,d_nz,d_nnz);
2613:   }
2614:   return(0);
2615: }


2618: static PetscErrorCode MatDuplicate_MPISBAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat)
2619: {
2620:   Mat            mat;
2621:   Mat_MPISBAIJ   *a,*oldmat = (Mat_MPISBAIJ*)matin->data;
2623:   PetscInt       len=0,nt,bs=matin->rmap->bs,mbs=oldmat->mbs;
2624:   PetscScalar    *array;

2627:   *newmat = 0;

2629:   MatCreate(PetscObjectComm((PetscObject)matin),&mat);
2630:   MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);
2631:   MatSetType(mat,((PetscObject)matin)->type_name);
2632:   PetscLayoutReference(matin->rmap,&mat->rmap);
2633:   PetscLayoutReference(matin->cmap,&mat->cmap);

2635:   mat->factortype   = matin->factortype;
2636:   mat->preallocated = PETSC_TRUE;
2637:   mat->assembled    = PETSC_TRUE;
2638:   mat->insertmode   = NOT_SET_VALUES;

2640:   a      = (Mat_MPISBAIJ*)mat->data;
2641:   a->bs2 = oldmat->bs2;
2642:   a->mbs = oldmat->mbs;
2643:   a->nbs = oldmat->nbs;
2644:   a->Mbs = oldmat->Mbs;
2645:   a->Nbs = oldmat->Nbs;

2647:   a->size         = oldmat->size;
2648:   a->rank         = oldmat->rank;
2649:   a->donotstash   = oldmat->donotstash;
2650:   a->roworiented  = oldmat->roworiented;
2651:   a->rowindices   = 0;
2652:   a->rowvalues    = 0;
2653:   a->getrowactive = PETSC_FALSE;
2654:   a->barray       = 0;
2655:   a->rstartbs     = oldmat->rstartbs;
2656:   a->rendbs       = oldmat->rendbs;
2657:   a->cstartbs     = oldmat->cstartbs;
2658:   a->cendbs       = oldmat->cendbs;

2660:   /* hash table stuff */
2661:   a->ht           = 0;
2662:   a->hd           = 0;
2663:   a->ht_size      = 0;
2664:   a->ht_flag      = oldmat->ht_flag;
2665:   a->ht_fact      = oldmat->ht_fact;
2666:   a->ht_total_ct  = 0;
2667:   a->ht_insert_ct = 0;

2669:   PetscMemcpy(a->rangebs,oldmat->rangebs,(a->size+2)*sizeof(PetscInt));
2670:   if (oldmat->colmap) {
2671: #if defined(PETSC_USE_CTABLE)
2672:     PetscTableCreateCopy(oldmat->colmap,&a->colmap);
2673: #else
2674:     PetscMalloc1(a->Nbs,&a->colmap);
2675:     PetscLogObjectMemory((PetscObject)mat,(a->Nbs)*sizeof(PetscInt));
2676:     PetscMemcpy(a->colmap,oldmat->colmap,(a->Nbs)*sizeof(PetscInt));
2677: #endif
2678:   } else a->colmap = 0;

2680:   if (oldmat->garray && (len = ((Mat_SeqBAIJ*)(oldmat->B->data))->nbs)) {
2681:     PetscMalloc1(len,&a->garray);
2682:     PetscLogObjectMemory((PetscObject)mat,len*sizeof(PetscInt));
2683:     PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));
2684:   } else a->garray = 0;

2686:   MatStashCreate_Private(PetscObjectComm((PetscObject)matin),matin->rmap->bs,&mat->bstash);
2687:   VecDuplicate(oldmat->lvec,&a->lvec);
2688:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->lvec);
2689:   VecScatterCopy(oldmat->Mvctx,&a->Mvctx);
2690:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->Mvctx);

2692:   VecDuplicate(oldmat->slvec0,&a->slvec0);
2693:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec0);
2694:   VecDuplicate(oldmat->slvec1,&a->slvec1);
2695:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec1);

2697:   VecGetLocalSize(a->slvec1,&nt);
2698:   VecGetArray(a->slvec1,&array);
2699:   VecCreateSeqWithArray(PETSC_COMM_SELF,1,bs*mbs,array,&a->slvec1a);
2700:   VecCreateSeqWithArray(PETSC_COMM_SELF,1,nt-bs*mbs,array+bs*mbs,&a->slvec1b);
2701:   VecRestoreArray(a->slvec1,&array);
2702:   VecGetArray(a->slvec0,&array);
2703:   VecCreateSeqWithArray(PETSC_COMM_SELF,1,nt-bs*mbs,array+bs*mbs,&a->slvec0b);
2704:   VecRestoreArray(a->slvec0,&array);
2705:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec0);
2706:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec1);
2707:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec0b);
2708:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec1a);
2709:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec1b);

2711:   /*  VecScatterCopy(oldmat->sMvctx,&a->sMvctx); - not written yet, replaced by the lazy trick: */
2712:   PetscObjectReference((PetscObject)oldmat->sMvctx);
2713:   a->sMvctx = oldmat->sMvctx;
2714:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->sMvctx);

2716:   MatDuplicate(oldmat->A,cpvalues,&a->A);
2717:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->A);
2718:   MatDuplicate(oldmat->B,cpvalues,&a->B);
2719:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->B);
2720:   PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);
2721:   *newmat = mat;
2722:   return(0);
2723: }

2725: PetscErrorCode MatLoad_MPISBAIJ(Mat newmat,PetscViewer viewer)
2726: {
2728:   PetscInt       i,nz,j,rstart,rend;
2729:   PetscScalar    *vals,*buf;
2730:   MPI_Comm       comm;
2731:   MPI_Status     status;
2732:   PetscMPIInt    rank,size,tag = ((PetscObject)viewer)->tag,*sndcounts = 0,*browners,maxnz,*rowners,mmbs;
2733:   PetscInt       header[4],*rowlengths = 0,M,N,m,*cols,*locrowlens;
2734:   PetscInt       *procsnz = 0,jj,*mycols,*ibuf;
2735:   PetscInt       bs = newmat->rmap->bs,Mbs,mbs,extra_rows;
2736:   PetscInt       *dlens,*odlens,*mask,*masked1,*masked2,rowcount,odcount;
2737:   PetscInt       dcount,kmax,k,nzcount,tmp;
2738:   int            fd;
2739:   PetscBool      isbinary;

2742:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);
2743:   if (!isbinary) SETERRQ2(PetscObjectComm((PetscObject)newmat),PETSC_ERR_SUP,"Viewer type %s not yet supported for reading %s matrices",((PetscObject)viewer)->type_name,((PetscObject)newmat)->type_name);

2745:   /* force binary viewer to load .info file if it has not yet done so */
2746:   PetscViewerSetUp(viewer);
2747:   PetscObjectGetComm((PetscObject)viewer,&comm);
2748:   PetscOptionsBegin(comm,NULL,"Options for loading MPISBAIJ matrix 2","Mat");
2749:   PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);
2750:   PetscOptionsEnd();
2751:   if (bs < 0) bs = 1;

2753:   MPI_Comm_size(comm,&size);
2754:   MPI_Comm_rank(comm,&rank);
2755:   PetscViewerBinaryGetDescriptor(viewer,&fd);
2756:   if (!rank) {
2757:     PetscBinaryRead(fd,(char*)header,4,NULL,PETSC_INT);
2758:     if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object");
2759:     if (header[3] < 0) SETERRQ(PetscObjectComm((PetscObject)newmat),PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format, cannot load as MPISBAIJ");
2760:   }

2762:   MPI_Bcast(header+1,3,MPIU_INT,0,comm);
2763:   M    = header[1];
2764:   N    = header[2];

2766:   /* If global sizes are set, check if they are consistent with that given in the file */
2767:   if (newmat->rmap->N >= 0 && newmat->rmap->N != M) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED, "Inconsistent # of rows:Matrix in file has (%D) and input matrix has (%D)",newmat->rmap->N,M);
2768:   if (newmat->cmap->N >= 0 && newmat->cmap->N != N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED, "Inconsistent # of cols:Matrix in file has (%D) and input matrix has (%D)",newmat->cmap->N,N);

2770:   if (M != N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Can only do square matrices");

2772:   /*
2773:      This code adds extra rows to make sure the number of rows is
2774:      divisible by the blocksize
2775:   */
2776:   Mbs        = M/bs;
2777:   extra_rows = bs - M + bs*(Mbs);
2778:   if (extra_rows == bs) extra_rows = 0;
2779:   else                  Mbs++;
2780:   if (extra_rows &&!rank) {
2781:     PetscInfo(viewer,"Padding loaded matrix to match blocksize\n");
2782:   }

2784:   /* determine ownership of all rows */
2785:   if (newmat->rmap->n < 0) { /* PETSC_DECIDE */
2786:     mbs = Mbs/size + ((Mbs % size) > rank);
2787:     m   = mbs*bs;
2788:   } else { /* User Set */
2789:     m   = newmat->rmap->n;
2790:     mbs = m/bs;
2791:   }
2792:   PetscMalloc2(size+1,&rowners,size+1,&browners);
2793:   PetscMPIIntCast(mbs,&mmbs);
2794:   MPI_Allgather(&mmbs,1,MPI_INT,rowners+1,1,MPI_INT,comm);
2795:   rowners[0] = 0;
2796:   for (i=2; i<=size; i++) rowners[i] += rowners[i-1];
2797:   for (i=0; i<=size; i++) browners[i] = rowners[i]*bs;
2798:   rstart = rowners[rank];
2799:   rend   = rowners[rank+1];

2801:   /* distribute row lengths to all processors */
2802:   PetscMalloc1((rend-rstart)*bs,&locrowlens);
2803:   if (!rank) {
2804:     PetscMalloc1(M+extra_rows,&rowlengths);
2805:     PetscBinaryRead(fd,rowlengths,M,NULL,PETSC_INT);
2806:     for (i=0; i<extra_rows; i++) rowlengths[M+i] = 1;
2807:     PetscMalloc1(size,&sndcounts);
2808:     for (i=0; i<size; i++) sndcounts[i] = browners[i+1] - browners[i];
2809:     MPI_Scatterv(rowlengths,sndcounts,browners,MPIU_INT,locrowlens,(rend-rstart)*bs,MPIU_INT,0,comm);
2810:     PetscFree(sndcounts);
2811:   } else {
2812:     MPI_Scatterv(0,0,0,MPIU_INT,locrowlens,(rend-rstart)*bs,MPIU_INT,0,comm);
2813:   }

2815:   if (!rank) {   /* procs[0] */
2816:     /* calculate the number of nonzeros on each processor */
2817:     PetscMalloc1(size,&procsnz);
2818:     PetscMemzero(procsnz,size*sizeof(PetscInt));
2819:     for (i=0; i<size; i++) {
2820:       for (j=rowners[i]*bs; j< rowners[i+1]*bs; j++) {
2821:         procsnz[i] += rowlengths[j];
2822:       }
2823:     }
2824:     PetscFree(rowlengths);

2826:     /* determine max buffer needed and allocate it */
2827:     maxnz = 0;
2828:     for (i=0; i<size; i++) {
2829:       maxnz = PetscMax(maxnz,procsnz[i]);
2830:     }
2831:     PetscMalloc1(maxnz,&cols);

2833:     /* read in my part of the matrix column indices  */
2834:     nz     = procsnz[0];
2835:     PetscMalloc1(nz,&ibuf);
2836:     mycols = ibuf;
2837:     if (size == 1) nz -= extra_rows;
2838:     PetscBinaryRead(fd,mycols,nz,NULL,PETSC_INT);
2839:     if (size == 1) {
2840:       for (i=0; i< extra_rows; i++) mycols[nz+i] = M+i;
2841:     }

2843:     /* read in every ones (except the last) and ship off */
2844:     for (i=1; i<size-1; i++) {
2845:       nz   = procsnz[i];
2846:       PetscBinaryRead(fd,cols,nz,NULL,PETSC_INT);
2847:       MPI_Send(cols,nz,MPIU_INT,i,tag,comm);
2848:     }
2849:     /* read in the stuff for the last proc */
2850:     if (size != 1) {
2851:       nz   = procsnz[size-1] - extra_rows;  /* the extra rows are not on the disk */
2852:       PetscBinaryRead(fd,cols,nz,NULL,PETSC_INT);
2853:       for (i=0; i<extra_rows; i++) cols[nz+i] = M+i;
2854:       MPI_Send(cols,nz+extra_rows,MPIU_INT,size-1,tag,comm);
2855:     }
2856:     PetscFree(cols);
2857:   } else {  /* procs[i], i>0 */
2858:     /* determine buffer space needed for message */
2859:     nz = 0;
2860:     for (i=0; i<m; i++) nz += locrowlens[i];
2861:     PetscMalloc1(nz,&ibuf);
2862:     mycols = ibuf;
2863:     /* receive message of column indices*/
2864:     MPI_Recv(mycols,nz,MPIU_INT,0,tag,comm,&status);
2865:     MPI_Get_count(&status,MPIU_INT,&maxnz);
2866:     if (maxnz != nz) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file");
2867:   }

2869:   /* loop over local rows, determining number of off diagonal entries */
2870:   PetscMalloc2(rend-rstart,&dlens,rend-rstart,&odlens);
2871:   PetscMalloc3(Mbs,&mask,Mbs,&masked1,Mbs,&masked2);
2872:   PetscMemzero(mask,Mbs*sizeof(PetscInt));
2873:   PetscMemzero(masked1,Mbs*sizeof(PetscInt));
2874:   PetscMemzero(masked2,Mbs*sizeof(PetscInt));
2875:   rowcount = 0;
2876:   nzcount  = 0;
2877:   for (i=0; i<mbs; i++) {
2878:     dcount  = 0;
2879:     odcount = 0;
2880:     for (j=0; j<bs; j++) {
2881:       kmax = locrowlens[rowcount];
2882:       for (k=0; k<kmax; k++) {
2883:         tmp = mycols[nzcount++]/bs; /* block col. index */
2884:         if (!mask[tmp]) {
2885:           mask[tmp] = 1;
2886:           if (tmp < rstart || tmp >= rend) masked2[odcount++] = tmp; /* entry in off-diag portion */
2887:           else masked1[dcount++] = tmp; /* entry in diag portion */
2888:         }
2889:       }
2890:       rowcount++;
2891:     }

2893:     dlens[i]  = dcount;  /* d_nzz[i] */
2894:     odlens[i] = odcount; /* o_nzz[i] */

2896:     /* zero out the mask elements we set */
2897:     for (j=0; j<dcount; j++) mask[masked1[j]] = 0;
2898:     for (j=0; j<odcount; j++) mask[masked2[j]] = 0;
2899:   }
2900:   MatSetSizes(newmat,m,m,M+extra_rows,N+extra_rows);
2901:   MatMPISBAIJSetPreallocation(newmat,bs,0,dlens,0,odlens);
2902:   MatSetOption(newmat,MAT_IGNORE_LOWER_TRIANGULAR,PETSC_TRUE);

2904:   if (!rank) {
2905:     PetscMalloc1(maxnz,&buf);
2906:     /* read in my part of the matrix numerical values  */
2907:     nz     = procsnz[0];
2908:     vals   = buf;
2909:     mycols = ibuf;
2910:     if (size == 1) nz -= extra_rows;
2911:     PetscBinaryRead(fd,vals,nz,NULL,PETSC_SCALAR);
2912:     if (size == 1) {
2913:       for (i=0; i< extra_rows; i++) vals[nz+i] = 1.0;
2914:     }

2916:     /* insert into matrix */
2917:     jj = rstart*bs;
2918:     for (i=0; i<m; i++) {
2919:       MatSetValues(newmat,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);
2920:       mycols += locrowlens[i];
2921:       vals   += locrowlens[i];
2922:       jj++;
2923:     }

2925:     /* read in other processors (except the last one) and ship out */
2926:     for (i=1; i<size-1; i++) {
2927:       nz   = procsnz[i];
2928:       vals = buf;
2929:       PetscBinaryRead(fd,vals,nz,NULL,PETSC_SCALAR);
2930:       MPI_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newmat)->tag,comm);
2931:     }
2932:     /* the last proc */
2933:     if (size != 1) {
2934:       nz   = procsnz[i] - extra_rows;
2935:       vals = buf;
2936:       PetscBinaryRead(fd,vals,nz,NULL,PETSC_SCALAR);
2937:       for (i=0; i<extra_rows; i++) vals[nz+i] = 1.0;
2938:       MPI_Send(vals,nz+extra_rows,MPIU_SCALAR,size-1,((PetscObject)newmat)->tag,comm);
2939:     }
2940:     PetscFree(procsnz);

2942:   } else {
2943:     /* receive numeric values */
2944:     PetscMalloc1(nz,&buf);

2946:     /* receive message of values*/
2947:     vals   = buf;
2948:     mycols = ibuf;
2949:     MPI_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newmat)->tag,comm,&status);
2950:     MPI_Get_count(&status,MPIU_SCALAR,&maxnz);
2951:     if (maxnz != nz) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file");

2953:     /* insert into matrix */
2954:     jj = rstart*bs;
2955:     for (i=0; i<m; i++) {
2956:       MatSetValues_MPISBAIJ(newmat,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);
2957:       mycols += locrowlens[i];
2958:       vals   += locrowlens[i];
2959:       jj++;
2960:     }
2961:   }

2963:   PetscFree(locrowlens);
2964:   PetscFree(buf);
2965:   PetscFree(ibuf);
2966:   PetscFree2(rowners,browners);
2967:   PetscFree2(dlens,odlens);
2968:   PetscFree3(mask,masked1,masked2);
2969:   MatAssemblyBegin(newmat,MAT_FINAL_ASSEMBLY);
2970:   MatAssemblyEnd(newmat,MAT_FINAL_ASSEMBLY);
2971:   return(0);
2972: }

2974: /*XXXXX@
2975:    MatMPISBAIJSetHashTableFactor - Sets the factor required to compute the size of the HashTable.

2977:    Input Parameters:
2978: .  mat  - the matrix
2979: .  fact - factor

2981:    Not Collective on Mat, each process can have a different hash factor

2983:    Level: advanced

2985:   Notes:
2986:    This can also be set by the command line option: -mat_use_hash_table fact

2988: .keywords: matrix, hashtable, factor, HT

2990: .seealso: MatSetOption()
2991: @XXXXX*/


2994: PetscErrorCode MatGetRowMaxAbs_MPISBAIJ(Mat A,Vec v,PetscInt idx[])
2995: {
2996:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;
2997:   Mat_SeqBAIJ    *b = (Mat_SeqBAIJ*)(a->B)->data;
2998:   PetscReal      atmp;
2999:   PetscReal      *work,*svalues,*rvalues;
3001:   PetscInt       i,bs,mbs,*bi,*bj,brow,j,ncols,krow,kcol,col,row,Mbs,bcol;
3002:   PetscMPIInt    rank,size;
3003:   PetscInt       *rowners_bs,dest,count,source;
3004:   PetscScalar    *va;
3005:   MatScalar      *ba;
3006:   MPI_Status     stat;

3009:   if (idx) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Send email to petsc-maint@mcs.anl.gov");
3010:   MatGetRowMaxAbs(a->A,v,NULL);
3011:   VecGetArray(v,&va);

3013:   MPI_Comm_size(PetscObjectComm((PetscObject)A),&size);
3014:   MPI_Comm_rank(PetscObjectComm((PetscObject)A),&rank);

3016:   bs  = A->rmap->bs;
3017:   mbs = a->mbs;
3018:   Mbs = a->Mbs;
3019:   ba  = b->a;
3020:   bi  = b->i;
3021:   bj  = b->j;

3023:   /* find ownerships */
3024:   rowners_bs = A->rmap->range;

3026:   /* each proc creates an array to be distributed */
3027:   PetscMalloc1(bs*Mbs,&work);
3028:   PetscMemzero(work,bs*Mbs*sizeof(PetscReal));

3030:   /* row_max for B */
3031:   if (rank != size-1) {
3032:     for (i=0; i<mbs; i++) {
3033:       ncols = bi[1] - bi[0]; bi++;
3034:       brow  = bs*i;
3035:       for (j=0; j<ncols; j++) {
3036:         bcol = bs*(*bj);
3037:         for (kcol=0; kcol<bs; kcol++) {
3038:           col  = bcol + kcol;                /* local col index */
3039:           col += rowners_bs[rank+1];      /* global col index */
3040:           for (krow=0; krow<bs; krow++) {
3041:             atmp = PetscAbsScalar(*ba); ba++;
3042:             row  = brow + krow;   /* local row index */
3043:             if (PetscRealPart(va[row]) < atmp) va[row] = atmp;
3044:             if (work[col] < atmp) work[col] = atmp;
3045:           }
3046:         }
3047:         bj++;
3048:       }
3049:     }

3051:     /* send values to its owners */
3052:     for (dest=rank+1; dest<size; dest++) {
3053:       svalues = work + rowners_bs[dest];
3054:       count   = rowners_bs[dest+1]-rowners_bs[dest];
3055:       MPI_Send(svalues,count,MPIU_REAL,dest,rank,PetscObjectComm((PetscObject)A));
3056:     }
3057:   }

3059:   /* receive values */
3060:   if (rank) {
3061:     rvalues = work;
3062:     count   = rowners_bs[rank+1]-rowners_bs[rank];
3063:     for (source=0; source<rank; source++) {
3064:       MPI_Recv(rvalues,count,MPIU_REAL,MPI_ANY_SOURCE,MPI_ANY_TAG,PetscObjectComm((PetscObject)A),&stat);
3065:       /* process values */
3066:       for (i=0; i<count; i++) {
3067:         if (PetscRealPart(va[i]) < rvalues[i]) va[i] = rvalues[i];
3068:       }
3069:     }
3070:   }

3072:   VecRestoreArray(v,&va);
3073:   PetscFree(work);
3074:   return(0);
3075: }

3077: PetscErrorCode MatSOR_MPISBAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx)
3078: {
3079:   Mat_MPISBAIJ      *mat = (Mat_MPISBAIJ*)matin->data;
3080:   PetscErrorCode    ierr;
3081:   PetscInt          mbs=mat->mbs,bs=matin->rmap->bs;
3082:   PetscScalar       *x,*ptr,*from;
3083:   Vec               bb1;
3084:   const PetscScalar *b;

3087:   if (its <= 0 || lits <= 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Relaxation requires global its %D and local its %D both positive",its,lits);
3088:   if (bs > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"SSOR for block size > 1 is not yet implemented");

3090:   if (flag == SOR_APPLY_UPPER) {
3091:     (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
3092:     return(0);
3093:   }

3095:   if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) {
3096:     if (flag & SOR_ZERO_INITIAL_GUESS) {
3097:       (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,lits,xx);
3098:       its--;
3099:     }

3101:     VecDuplicate(bb,&bb1);
3102:     while (its--) {

3104:       /* lower triangular part: slvec0b = - B^T*xx */
3105:       (*mat->B->ops->multtranspose)(mat->B,xx,mat->slvec0b);

3107:       /* copy xx into slvec0a */
3108:       VecGetArray(mat->slvec0,&ptr);
3109:       VecGetArray(xx,&x);
3110:       PetscMemcpy(ptr,x,bs*mbs*sizeof(MatScalar));
3111:       VecRestoreArray(mat->slvec0,&ptr);

3113:       VecScale(mat->slvec0,-1.0);

3115:       /* copy bb into slvec1a */
3116:       VecGetArray(mat->slvec1,&ptr);
3117:       VecGetArrayRead(bb,&b);
3118:       PetscMemcpy(ptr,b,bs*mbs*sizeof(MatScalar));
3119:       VecRestoreArray(mat->slvec1,&ptr);

3121:       /* set slvec1b = 0 */
3122:       VecSet(mat->slvec1b,0.0);

3124:       VecScatterBegin(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);
3125:       VecRestoreArray(xx,&x);
3126:       VecRestoreArrayRead(bb,&b);
3127:       VecScatterEnd(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);

3129:       /* upper triangular part: bb1 = bb1 - B*x */
3130:       (*mat->B->ops->multadd)(mat->B,mat->slvec1b,mat->slvec1a,bb1);

3132:       /* local diagonal sweep */
3133:       (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,lits,xx);
3134:     }
3135:     VecDestroy(&bb1);
3136:   } else if ((flag & SOR_LOCAL_FORWARD_SWEEP) && (its == 1) && (flag & SOR_ZERO_INITIAL_GUESS)) {
3137:     (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
3138:   } else if ((flag & SOR_LOCAL_BACKWARD_SWEEP) && (its == 1) && (flag & SOR_ZERO_INITIAL_GUESS)) {
3139:     (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
3140:   } else if (flag & SOR_EISENSTAT) {
3141:     Vec               xx1;
3142:     PetscBool         hasop;
3143:     const PetscScalar *diag;
3144:     PetscScalar       *sl,scale = (omega - 2.0)/omega;
3145:     PetscInt          i,n;

3147:     if (!mat->xx1) {
3148:       VecDuplicate(bb,&mat->xx1);
3149:       VecDuplicate(bb,&mat->bb1);
3150:     }
3151:     xx1 = mat->xx1;
3152:     bb1 = mat->bb1;

3154:     (*mat->A->ops->sor)(mat->A,bb,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_BACKWARD_SWEEP),fshift,lits,1,xx);

3156:     if (!mat->diag) {
3157:       /* this is wrong for same matrix with new nonzero values */
3158:       MatCreateVecs(matin,&mat->diag,NULL);
3159:       MatGetDiagonal(matin,mat->diag);
3160:     }
3161:     MatHasOperation(matin,MATOP_MULT_DIAGONAL_BLOCK,&hasop);

3163:     if (hasop) {
3164:       MatMultDiagonalBlock(matin,xx,bb1);
3165:       VecAYPX(mat->slvec1a,scale,bb);
3166:     } else {
3167:       /*
3168:           These two lines are replaced by code that may be a bit faster for a good compiler
3169:       VecPointwiseMult(mat->slvec1a,mat->diag,xx);
3170:       VecAYPX(mat->slvec1a,scale,bb);
3171:       */
3172:       VecGetArray(mat->slvec1a,&sl);
3173:       VecGetArrayRead(mat->diag,&diag);
3174:       VecGetArrayRead(bb,&b);
3175:       VecGetArray(xx,&x);
3176:       VecGetLocalSize(xx,&n);
3177:       if (omega == 1.0) {
3178:         for (i=0; i<n; i++) sl[i] = b[i] - diag[i]*x[i];
3179:         PetscLogFlops(2.0*n);
3180:       } else {
3181:         for (i=0; i<n; i++) sl[i] = b[i] + scale*diag[i]*x[i];
3182:         PetscLogFlops(3.0*n);
3183:       }
3184:       VecRestoreArray(mat->slvec1a,&sl);
3185:       VecRestoreArrayRead(mat->diag,&diag);
3186:       VecRestoreArrayRead(bb,&b);
3187:       VecRestoreArray(xx,&x);
3188:     }

3190:     /* multiply off-diagonal portion of matrix */
3191:     VecSet(mat->slvec1b,0.0);
3192:     (*mat->B->ops->multtranspose)(mat->B,xx,mat->slvec0b);
3193:     VecGetArray(mat->slvec0,&from);
3194:     VecGetArray(xx,&x);
3195:     PetscMemcpy(from,x,bs*mbs*sizeof(MatScalar));
3196:     VecRestoreArray(mat->slvec0,&from);
3197:     VecRestoreArray(xx,&x);
3198:     VecScatterBegin(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);
3199:     VecScatterEnd(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);
3200:     (*mat->B->ops->multadd)(mat->B,mat->slvec1b,mat->slvec1a,mat->slvec1a);

3202:     /* local sweep */
3203:     (*mat->A->ops->sor)(mat->A,mat->slvec1a,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_FORWARD_SWEEP),fshift,lits,1,xx1);
3204:     VecAXPY(xx,1.0,xx1);
3205:   } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"MatSORType is not supported for SBAIJ matrix format");
3206:   return(0);
3207: }

3209: PetscErrorCode MatSOR_MPISBAIJ_2comm(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx)
3210: {
3211:   Mat_MPISBAIJ   *mat = (Mat_MPISBAIJ*)matin->data;
3213:   Vec            lvec1,bb1;

3216:   if (its <= 0 || lits <= 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Relaxation requires global its %D and local its %D both positive",its,lits);
3217:   if (matin->rmap->bs > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"SSOR for block size > 1 is not yet implemented");

3219:   if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) {
3220:     if (flag & SOR_ZERO_INITIAL_GUESS) {
3221:       (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,lits,xx);
3222:       its--;
3223:     }

3225:     VecDuplicate(mat->lvec,&lvec1);
3226:     VecDuplicate(bb,&bb1);
3227:     while (its--) {
3228:       VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);

3230:       /* lower diagonal part: bb1 = bb - B^T*xx */
3231:       (*mat->B->ops->multtranspose)(mat->B,xx,lvec1);
3232:       VecScale(lvec1,-1.0);

3234:       VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
3235:       VecCopy(bb,bb1);
3236:       VecScatterBegin(mat->Mvctx,lvec1,bb1,ADD_VALUES,SCATTER_REVERSE);

3238:       /* upper diagonal part: bb1 = bb1 - B*x */
3239:       VecScale(mat->lvec,-1.0);
3240:       (*mat->B->ops->multadd)(mat->B,mat->lvec,bb1,bb1);

3242:       VecScatterEnd(mat->Mvctx,lvec1,bb1,ADD_VALUES,SCATTER_REVERSE);

3244:       /* diagonal sweep */
3245:       (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,lits,xx);
3246:     }
3247:     VecDestroy(&lvec1);
3248:     VecDestroy(&bb1);
3249:   } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"MatSORType is not supported for SBAIJ matrix format");
3250:   return(0);
3251: }

3253: /*@
3254:      MatCreateMPISBAIJWithArrays - creates a MPI SBAIJ matrix using arrays that contain in standard
3255:          CSR format the local rows.

3257:    Collective on MPI_Comm

3259:    Input Parameters:
3260: +  comm - MPI communicator
3261: .  bs - the block size, only a block size of 1 is supported
3262: .  m - number of local rows (Cannot be PETSC_DECIDE)
3263: .  n - This value should be the same as the local size used in creating the
3264:        x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have
3265:        calculated if N is given) For square matrices n is almost always m.
3266: .  M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
3267: .  N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
3268: .   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
3269: .   j - column indices
3270: -   a - matrix values

3272:    Output Parameter:
3273: .   mat - the matrix

3275:    Level: intermediate

3277:    Notes:
3278:        The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc;
3279:      thus you CANNOT change the matrix entries by changing the values of a[] after you have
3280:      called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays.

3282:        The i and j indices are 0 based, and i indices are indices corresponding to the local j array.

3284: .keywords: matrix, aij, compressed row, sparse, parallel

3286: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(),
3287:           MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays()
3288: @*/
3289: 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)
3290: {


3295:   if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0");
3296:   if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative");
3297:   MatCreate(comm,mat);
3298:   MatSetSizes(*mat,m,n,M,N);
3299:   MatSetType(*mat,MATMPISBAIJ);
3300:   MatMPISBAIJSetPreallocationCSR(*mat,bs,i,j,a);
3301:   return(0);
3302: }


3305: /*@C
3306:    MatMPISBAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in BAIJ format
3307:    (the default parallel PETSc format).

3309:    Collective on MPI_Comm

3311:    Input Parameters:
3312: +  B - the matrix
3313: .  bs - the block size
3314: .  i - the indices into j for the start of each local row (starts with zero)
3315: .  j - the column indices for each local row (starts with zero) these must be sorted for each row
3316: -  v - optional values in the matrix

3318:    Level: developer

3320: .keywords: matrix, aij, compressed row, sparse, parallel

3322: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIBAIJSetPreallocation(), MatCreateAIJ(), MPIAIJ
3323: @*/
3324: PetscErrorCode  MatMPISBAIJSetPreallocationCSR(Mat B,PetscInt bs,const PetscInt i[],const PetscInt j[], const PetscScalar v[])
3325: {

3329:   PetscTryMethod(B,"MatMPISBAIJSetPreallocationCSR_C",(Mat,PetscInt,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,bs,i,j,v));
3330:   return(0);
3331: }

3333: PetscErrorCode MatCreateMPIMatConcatenateSeqMat_MPISBAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat)
3334: {
3336:   PetscInt       m,N,i,rstart,nnz,Ii,bs,cbs;
3337:   PetscInt       *indx;
3338:   PetscScalar    *values;

3341:   MatGetSize(inmat,&m,&N);
3342:   if (scall == MAT_INITIAL_MATRIX) { /* symbolic phase */
3343:     Mat_SeqSBAIJ   *a = (Mat_SeqSBAIJ*)inmat->data;
3344:     PetscInt       *dnz,*onz,sum,bs,cbs,mbs,Nbs;
3345:     PetscInt       *bindx,rmax=a->rmax,j;

3347:     MatGetBlockSizes(inmat,&bs,&cbs);
3348:     mbs = m/bs; Nbs = N/cbs;
3349:     if (n == PETSC_DECIDE) {
3350:       PetscSplitOwnership(comm,&n,&Nbs);
3351:     }
3352:     /* Check sum(n) = Nbs */
3353:     MPIU_Allreduce(&n,&sum,1,MPIU_INT,MPI_SUM,comm);
3354:     if (sum != Nbs) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Sum of local columns != global columns %d",Nbs);

3356:     MPI_Scan(&mbs, &rstart,1,MPIU_INT,MPI_SUM,comm);
3357:     rstart -= mbs;

3359:     PetscMalloc1(rmax,&bindx);
3360:     MatPreallocateInitialize(comm,mbs,n,dnz,onz);
3361:     MatSetOption(inmat,MAT_GETROW_UPPERTRIANGULAR,PETSC_TRUE);
3362:     for (i=0; i<mbs; i++) {
3363:       MatGetRow_SeqSBAIJ(inmat,i*bs,&nnz,&indx,NULL); /* non-blocked nnz and indx */
3364:       nnz  = nnz/bs;
3365:       for (j=0; j<nnz; j++) bindx[j] = indx[j*bs]/bs;
3366:       MatPreallocateSet(i+rstart,nnz,bindx,dnz,onz);
3367:       MatRestoreRow_SeqSBAIJ(inmat,i*bs,&nnz,&indx,NULL);
3368:     }
3369:     MatSetOption(inmat,MAT_GETROW_UPPERTRIANGULAR,PETSC_FALSE);
3370:     PetscFree(bindx);

3372:     MatCreate(comm,outmat);
3373:     MatSetSizes(*outmat,m,n*bs,PETSC_DETERMINE,PETSC_DETERMINE);
3374:     MatSetBlockSizes(*outmat,bs,cbs);
3375:     MatSetType(*outmat,MATMPISBAIJ);
3376:     MatMPISBAIJSetPreallocation(*outmat,bs,0,dnz,0,onz);
3377:     MatPreallocateFinalize(dnz,onz);
3378:   }

3380:   /* numeric phase */
3381:   MatGetBlockSizes(inmat,&bs,&cbs);
3382:   MatGetOwnershipRange(*outmat,&rstart,NULL);

3384:   MatSetOption(inmat,MAT_GETROW_UPPERTRIANGULAR,PETSC_TRUE);
3385:   for (i=0; i<m; i++) {
3386:     MatGetRow_SeqSBAIJ(inmat,i,&nnz,&indx,&values);
3387:     Ii   = i + rstart;
3388:     MatSetValues(*outmat,1,&Ii,nnz,indx,values,INSERT_VALUES);
3389:     MatRestoreRow_SeqSBAIJ(inmat,i,&nnz,&indx,&values);
3390:   }
3391:   MatSetOption(inmat,MAT_GETROW_UPPERTRIANGULAR,PETSC_FALSE);
3392:   MatAssemblyBegin(*outmat,MAT_FINAL_ASSEMBLY);
3393:   MatAssemblyEnd(*outmat,MAT_FINAL_ASSEMBLY);
3394:   return(0);
3395: }