Actual source code: mpisbaij.c

petsc-master 2017-09-25
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  2:  #include <../src/mat/impls/baij/mpi/mpibaij.h>
  3:  #include <../src/mat/impls/sbaij/mpi/mpisbaij.h>
  4:  #include <../src/mat/impls/sbaij/seq/sbaij.h>
  5:  #include <petscblaslapack.h>

  7: #if defined(PETSC_HAVE_ELEMENTAL)
  8: PETSC_INTERN PetscErrorCode MatConvert_MPISBAIJ_Elemental(Mat,MatType,MatReuse,Mat*);
  9: #endif
 10: PetscErrorCode  MatStoreValues_MPISBAIJ(Mat mat)
 11: {
 12:   Mat_MPISBAIJ   *aij = (Mat_MPISBAIJ*)mat->data;

 16:   MatStoreValues(aij->A);
 17:   MatStoreValues(aij->B);
 18:   return(0);
 19: }

 21: PetscErrorCode  MatRetrieveValues_MPISBAIJ(Mat mat)
 22: {
 23:   Mat_MPISBAIJ   *aij = (Mat_MPISBAIJ*)mat->data;

 27:   MatRetrieveValues(aij->A);
 28:   MatRetrieveValues(aij->B);
 29:   return(0);
 30: }

 32: #define  MatSetValues_SeqSBAIJ_A_Private(row,col,value,addv,orow,ocol)      \
 33:   { \
 34:  \
 35:     brow = row/bs;  \
 36:     rp   = aj + ai[brow]; ap = aa + bs2*ai[brow]; \
 37:     rmax = aimax[brow]; nrow = ailen[brow]; \
 38:     bcol = col/bs; \
 39:     ridx = row % bs; cidx = col % bs; \
 40:     low  = 0; high = nrow; \
 41:     while (high-low > 3) { \
 42:       t = (low+high)/2; \
 43:       if (rp[t] > bcol) high = t; \
 44:       else              low  = t; \
 45:     } \
 46:     for (_i=low; _i<high; _i++) { \
 47:       if (rp[_i] > bcol) break; \
 48:       if (rp[_i] == bcol) { \
 49:         bap = ap + bs2*_i + bs*cidx + ridx; \
 50:         if (addv == ADD_VALUES) *bap += value;  \
 51:         else                    *bap  = value;  \
 52:         goto a_noinsert; \
 53:       } \
 54:     } \
 55:     if (a->nonew == 1) goto a_noinsert; \
 56:     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); \
 57:     MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,brow,bcol,rmax,aa,ai,aj,rp,ap,aimax,a->nonew,MatScalar); \
 58:     N = nrow++ - 1;  \
 59:     /* shift up all the later entries in this row */ \
 60:     for (ii=N; ii>=_i; ii--) { \
 61:       rp[ii+1] = rp[ii]; \
 62:       PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar)); \
 63:     } \
 64:     if (N>=_i) { PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar)); }  \
 65:     rp[_i]                      = bcol;  \
 66:     ap[bs2*_i + bs*cidx + ridx] = value;  \
 67:     A->nonzerostate++;\
 68: a_noinsert:; \
 69:     ailen[brow] = nrow; \
 70:   }

 72: #define  MatSetValues_SeqSBAIJ_B_Private(row,col,value,addv,orow,ocol) \
 73:   { \
 74:     brow = row/bs;  \
 75:     rp   = bj + bi[brow]; ap = ba + bs2*bi[brow]; \
 76:     rmax = bimax[brow]; nrow = bilen[brow]; \
 77:     bcol = col/bs; \
 78:     ridx = row % bs; cidx = col % bs; \
 79:     low  = 0; high = nrow; \
 80:     while (high-low > 3) { \
 81:       t = (low+high)/2; \
 82:       if (rp[t] > bcol) high = t; \
 83:       else              low  = t; \
 84:     } \
 85:     for (_i=low; _i<high; _i++) { \
 86:       if (rp[_i] > bcol) break; \
 87:       if (rp[_i] == bcol) { \
 88:         bap = ap + bs2*_i + bs*cidx + ridx; \
 89:         if (addv == ADD_VALUES) *bap += value;  \
 90:         else                    *bap  = value;  \
 91:         goto b_noinsert; \
 92:       } \
 93:     } \
 94:     if (b->nonew == 1) goto b_noinsert; \
 95:     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); \
 96:     MatSeqXAIJReallocateAIJ(B,b->mbs,bs2,nrow,brow,bcol,rmax,ba,bi,bj,rp,ap,bimax,b->nonew,MatScalar); \
 97:     N = nrow++ - 1;  \
 98:     /* shift up all the later entries in this row */ \
 99:     for (ii=N; ii>=_i; ii--) { \
100:       rp[ii+1] = rp[ii]; \
101:       PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar)); \
102:     } \
103:     if (N>=_i) { PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar));}  \
104:     rp[_i]                      = bcol;  \
105:     ap[bs2*_i + bs*cidx + ridx] = value;  \
106:     B->nonzerostate++;\
107: b_noinsert:; \
108:     bilen[brow] = nrow; \
109:   }

111: /* Only add/insert a(i,j) with i<=j (blocks).
112:    Any a(i,j) with i>j input by user is ingored.
113: */
114: PetscErrorCode MatSetValues_MPISBAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv)
115: {
116:   Mat_MPISBAIJ   *baij = (Mat_MPISBAIJ*)mat->data;
117:   MatScalar      value;
118:   PetscBool      roworiented = baij->roworiented;
120:   PetscInt       i,j,row,col;
121:   PetscInt       rstart_orig=mat->rmap->rstart;
122:   PetscInt       rend_orig  =mat->rmap->rend,cstart_orig=mat->cmap->rstart;
123:   PetscInt       cend_orig  =mat->cmap->rend,bs=mat->rmap->bs;

125:   /* Some Variables required in the macro */
126:   Mat          A     = baij->A;
127:   Mat_SeqSBAIJ *a    = (Mat_SeqSBAIJ*)(A)->data;
128:   PetscInt     *aimax=a->imax,*ai=a->i,*ailen=a->ilen,*aj=a->j;
129:   MatScalar    *aa   =a->a;

131:   Mat         B     = baij->B;
132:   Mat_SeqBAIJ *b    = (Mat_SeqBAIJ*)(B)->data;
133:   PetscInt    *bimax=b->imax,*bi=b->i,*bilen=b->ilen,*bj=b->j;
134:   MatScalar   *ba   =b->a;

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

140:   /* for stash */
141:   PetscInt  n_loc, *in_loc = NULL;
142:   MatScalar *v_loc = NULL;

145:   if (!baij->donotstash) {
146:     if (n > baij->n_loc) {
147:       PetscFree(baij->in_loc);
148:       PetscFree(baij->v_loc);
149:       PetscMalloc1(n,&baij->in_loc);
150:       PetscMalloc1(n,&baij->v_loc);

152:       baij->n_loc = n;
153:     }
154:     in_loc = baij->in_loc;
155:     v_loc  = baij->v_loc;
156:   }

158:   for (i=0; i<m; i++) {
159:     if (im[i] < 0) continue;
160: #if defined(PETSC_USE_DEBUG)
161:     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);
162: #endif
163:     if (im[i] >= rstart_orig && im[i] < rend_orig) { /* this processor entry */
164:       row = im[i] - rstart_orig;              /* local row index */
165:       for (j=0; j<n; j++) {
166:         if (im[i]/bs > in[j]/bs) {
167:           if (a->ignore_ltriangular) {
168:             continue;    /* ignore lower triangular blocks */
169:           } 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)");
170:         }
171:         if (in[j] >= cstart_orig && in[j] < cend_orig) {  /* diag entry (A) */
172:           col  = in[j] - cstart_orig;         /* local col index */
173:           brow = row/bs; bcol = col/bs;
174:           if (brow > bcol) continue;  /* ignore lower triangular blocks of A */
175:           if (roworiented) value = v[i*n+j];
176:           else             value = v[i+j*m];
177:           MatSetValues_SeqSBAIJ_A_Private(row,col,value,addv,im[i],in[j]);
178:           /* MatSetValues_SeqBAIJ(baij->A,1,&row,1,&col,&value,addv); */
179:         } else if (in[j] < 0) continue;
180: #if defined(PETSC_USE_DEBUG)
181:         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);
182: #endif
183:         else {  /* off-diag entry (B) */
184:           if (mat->was_assembled) {
185:             if (!baij->colmap) {
186:               MatCreateColmap_MPIBAIJ_Private(mat);
187:             }
188: #if defined(PETSC_USE_CTABLE)
189:             PetscTableFind(baij->colmap,in[j]/bs + 1,&col);
190:             col  = col - 1;
191: #else
192:             col = baij->colmap[in[j]/bs] - 1;
193: #endif
194:             if (col < 0 && !((Mat_SeqSBAIJ*)(baij->A->data))->nonew) {
195:               MatDisAssemble_MPISBAIJ(mat);
196:               col  =  in[j];
197:               /* Reinitialize the variables required by MatSetValues_SeqBAIJ_B_Private() */
198:               B    = baij->B;
199:               b    = (Mat_SeqBAIJ*)(B)->data;
200:               bimax= b->imax;bi=b->i;bilen=b->ilen;bj=b->j;
201:               ba   = b->a;
202:             } else col += in[j]%bs;
203:           } else col = in[j];
204:           if (roworiented) value = v[i*n+j];
205:           else             value = v[i+j*m];
206:           MatSetValues_SeqSBAIJ_B_Private(row,col,value,addv,im[i],in[j]);
207:           /* MatSetValues_SeqBAIJ(baij->B,1,&row,1,&col,&value,addv); */
208:         }
209:       }
210:     } else {  /* off processor entry */
211:       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]);
212:       if (!baij->donotstash) {
213:         mat->assembled = PETSC_FALSE;
214:         n_loc          = 0;
215:         for (j=0; j<n; j++) {
216:           if (im[i]/bs > in[j]/bs) continue; /* ignore lower triangular blocks */
217:           in_loc[n_loc] = in[j];
218:           if (roworiented) {
219:             v_loc[n_loc] = v[i*n+j];
220:           } else {
221:             v_loc[n_loc] = v[j*m+i];
222:           }
223:           n_loc++;
224:         }
225:         MatStashValuesRow_Private(&mat->stash,im[i],n_loc,in_loc,v_loc,PETSC_FALSE);
226:       }
227:     }
228:   }
229:   return(0);
230: }

232: PETSC_STATIC_INLINE PetscErrorCode MatSetValuesBlocked_SeqSBAIJ_Inlined(Mat A,PetscInt row,PetscInt col,const PetscScalar v[],InsertMode is,PetscInt orow,PetscInt ocol)
233: {
234:   Mat_SeqSBAIJ      *a = (Mat_SeqSBAIJ*)A->data;
235:   PetscErrorCode    ierr;
236:   PetscInt          *rp,low,high,t,ii,jj,nrow,i,rmax,N;
237:   PetscInt          *imax      =a->imax,*ai=a->i,*ailen=a->ilen;
238:   PetscInt          *aj        =a->j,nonew=a->nonew,bs2=a->bs2,bs=A->rmap->bs;
239:   PetscBool         roworiented=a->roworiented;
240:   const PetscScalar *value     = v;
241:   MatScalar         *ap,*aa = a->a,*bap;

244:   if (col < row) {
245:     if (a->ignore_ltriangular) return(0); /* ignore lower triangular block */
246:     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)");
247:   }
248:   rp   = aj + ai[row];
249:   ap   = aa + bs2*ai[row];
250:   rmax = imax[row];
251:   nrow = ailen[row];
252:   value = v;
253:   low   = 0;
254:   high  = nrow;

256:   while (high-low > 7) {
257:     t = (low+high)/2;
258:     if (rp[t] > col) high = t;
259:     else             low  = t;
260:   }
261:   for (i=low; i<high; i++) {
262:     if (rp[i] > col) break;
263:     if (rp[i] == col) {
264:       bap = ap +  bs2*i;
265:       if (roworiented) {
266:         if (is == ADD_VALUES) {
267:           for (ii=0; ii<bs; ii++) {
268:             for (jj=ii; jj<bs2; jj+=bs) {
269:               bap[jj] += *value++;
270:             }
271:           }
272:         } else {
273:           for (ii=0; ii<bs; ii++) {
274:             for (jj=ii; jj<bs2; jj+=bs) {
275:               bap[jj] = *value++;
276:             }
277:           }
278:         }
279:       } else {
280:         if (is == ADD_VALUES) {
281:           for (ii=0; ii<bs; ii++) {
282:             for (jj=0; jj<bs; jj++) {
283:               *bap++ += *value++;
284:             }
285:           }
286:         } else {
287:           for (ii=0; ii<bs; ii++) {
288:             for (jj=0; jj<bs; jj++) {
289:               *bap++  = *value++;
290:             }
291:           }
292:         }
293:       }
294:       goto noinsert2;
295:     }
296:   }
297:   if (nonew == 1) goto noinsert2;
298:   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);
299:   MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,row,col,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar);
300:   N = nrow++ - 1; high++;
301:   /* shift up all the later entries in this row */
302:   for (ii=N; ii>=i; ii--) {
303:     rp[ii+1] = rp[ii];
304:     PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));
305:   }
306:   if (N >= i) {
307:     PetscMemzero(ap+bs2*i,bs2*sizeof(MatScalar));
308:   }
309:   rp[i] = col;
310:   bap   = ap +  bs2*i;
311:   if (roworiented) {
312:     for (ii=0; ii<bs; ii++) {
313:       for (jj=ii; jj<bs2; jj+=bs) {
314:         bap[jj] = *value++;
315:       }
316:     }
317:   } else {
318:     for (ii=0; ii<bs; ii++) {
319:       for (jj=0; jj<bs; jj++) {
320:         *bap++ = *value++;
321:       }
322:     }
323:   }
324:   noinsert2:;
325:   ailen[row] = nrow;
326:   return(0);
327: }

329: /*
330:    This routine is exactly duplicated in mpibaij.c
331: */
332: PETSC_STATIC_INLINE PetscErrorCode MatSetValuesBlocked_SeqBAIJ_Inlined(Mat A,PetscInt row,PetscInt col,const PetscScalar v[],InsertMode is,PetscInt orow,PetscInt ocol)
333: {
334:   Mat_SeqBAIJ       *a = (Mat_SeqBAIJ*)A->data;
335:   PetscInt          *rp,low,high,t,ii,jj,nrow,i,rmax,N;
336:   PetscInt          *imax=a->imax,*ai=a->i,*ailen=a->ilen;
337:   PetscErrorCode    ierr;
338:   PetscInt          *aj        =a->j,nonew=a->nonew,bs2=a->bs2,bs=A->rmap->bs;
339:   PetscBool         roworiented=a->roworiented;
340:   const PetscScalar *value     = v;
341:   MatScalar         *ap,*aa = a->a,*bap;

344:   rp   = aj + ai[row];
345:   ap   = aa + bs2*ai[row];
346:   rmax = imax[row];
347:   nrow = ailen[row];
348:   low  = 0;
349:   high = nrow;
350:   value = v;
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++,value+=bs) {
377:             for (jj=0; jj<bs; jj++) {
378:               bap[jj] += value[jj];
379:             }
380:             bap += bs;
381:           }
382:         } else {
383:           for (ii=0; ii<bs; ii++,value+=bs) {
384:             for (jj=0; jj<bs; jj++) {
385:               bap[jj]  = value[jj];
386:             }
387:             bap += bs;
388:           }
389:         }
390:       }
391:       goto noinsert2;
392:     }
393:   }
394:   if (nonew == 1) goto noinsert2;
395:   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);
396:   MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,row,col,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar);
397:   N = nrow++ - 1; high++;
398:   /* shift up all the later entries in this row */
399:   for (ii=N; ii>=i; ii--) {
400:     rp[ii+1] = rp[ii];
401:     PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));
402:   }
403:   if (N >= i) {
404:     PetscMemzero(ap+bs2*i,bs2*sizeof(MatScalar));
405:   }
406:   rp[i] = col;
407:   bap   = ap +  bs2*i;
408:   if (roworiented) {
409:     for (ii=0; ii<bs; ii++) {
410:       for (jj=ii; jj<bs2; jj+=bs) {
411:         bap[jj] = *value++;
412:       }
413:     }
414:   } else {
415:     for (ii=0; ii<bs; ii++) {
416:       for (jj=0; jj<bs; jj++) {
417:         *bap++ = *value++;
418:       }
419:     }
420:   }
421:   noinsert2:;
422:   ailen[row] = nrow;
423:   return(0);
424: }

426: /*
427:     This routine could be optimized by removing the need for the block copy below and passing stride information
428:   to the above inline routines; similarly in MatSetValuesBlocked_MPIBAIJ()
429: */
430: PetscErrorCode MatSetValuesBlocked_MPISBAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const MatScalar v[],InsertMode addv)
431: {
432:   Mat_MPISBAIJ    *baij = (Mat_MPISBAIJ*)mat->data;
433:   const MatScalar *value;
434:   MatScalar       *barray     =baij->barray;
435:   PetscBool       roworiented = baij->roworiented,ignore_ltriangular = ((Mat_SeqSBAIJ*)baij->A->data)->ignore_ltriangular;
436:   PetscErrorCode  ierr;
437:   PetscInt        i,j,ii,jj,row,col,rstart=baij->rstartbs;
438:   PetscInt        rend=baij->rendbs,cstart=baij->rstartbs,stepval;
439:   PetscInt        cend=baij->rendbs,bs=mat->rmap->bs,bs2=baij->bs2;

442:   if (!barray) {
443:     PetscMalloc1(bs2,&barray);
444:     baij->barray = barray;
445:   }

447:   if (roworiented) {
448:     stepval = (n-1)*bs;
449:   } else {
450:     stepval = (m-1)*bs;
451:   }
452:   for (i=0; i<m; i++) {
453:     if (im[i] < 0) continue;
454: #if defined(PETSC_USE_DEBUG)
455:     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);
456: #endif
457:     if (im[i] >= rstart && im[i] < rend) {
458:       row = im[i] - rstart;
459:       for (j=0; j<n; j++) {
460:         if (im[i] > in[j]) {
461:           if (ignore_ltriangular) continue; /* ignore lower triangular blocks */
462:           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)");
463:         }
464:         /* If NumCol = 1 then a copy is not required */
465:         if ((roworiented) && (n == 1)) {
466:           barray = (MatScalar*) v + i*bs2;
467:         } else if ((!roworiented) && (m == 1)) {
468:           barray = (MatScalar*) v + j*bs2;
469:         } else { /* Here a copy is required */
470:           if (roworiented) {
471:             value = v + i*(stepval+bs)*bs + j*bs;
472:           } else {
473:             value = v + j*(stepval+bs)*bs + i*bs;
474:           }
475:           for (ii=0; ii<bs; ii++,value+=stepval) {
476:             for (jj=0; jj<bs; jj++) {
477:               *barray++ = *value++;
478:             }
479:           }
480:           barray -=bs2;
481:         }

483:         if (in[j] >= cstart && in[j] < cend) {
484:           col  = in[j] - cstart;
485:           MatSetValuesBlocked_SeqSBAIJ_Inlined(baij->A,row,col,barray,addv,im[i],in[j]);
486:         } else if (in[j] < 0) continue;
487: #if defined(PETSC_USE_DEBUG)
488:         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);
489: #endif
490:         else {
491:           if (mat->was_assembled) {
492:             if (!baij->colmap) {
493:               MatCreateColmap_MPIBAIJ_Private(mat);
494:             }

496: #if defined(PETSC_USE_DEBUG)
497: #if defined(PETSC_USE_CTABLE)
498:             { PetscInt data;
499:               PetscTableFind(baij->colmap,in[j]+1,&data);
500:               if ((data - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap");
501:             }
502: #else
503:             if ((baij->colmap[in[j]] - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap");
504: #endif
505: #endif
506: #if defined(PETSC_USE_CTABLE)
507:             PetscTableFind(baij->colmap,in[j]+1,&col);
508:             col  = (col - 1)/bs;
509: #else
510:             col = (baij->colmap[in[j]] - 1)/bs;
511: #endif
512:             if (col < 0 && !((Mat_SeqBAIJ*)(baij->A->data))->nonew) {
513:               MatDisAssemble_MPISBAIJ(mat);
514:               col  = in[j];
515:             }
516:           } else col = in[j];
517:           MatSetValuesBlocked_SeqBAIJ_Inlined(baij->B,row,col,barray,addv,im[i],in[j]);
518:         }
519:       }
520:     } else {
521:       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]);
522:       if (!baij->donotstash) {
523:         if (roworiented) {
524:           MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);
525:         } else {
526:           MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);
527:         }
528:       }
529:     }
530:   }
531:   return(0);
532: }

534: PetscErrorCode MatGetValues_MPISBAIJ(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[])
535: {
536:   Mat_MPISBAIJ   *baij = (Mat_MPISBAIJ*)mat->data;
538:   PetscInt       bs       = mat->rmap->bs,i,j,bsrstart = mat->rmap->rstart,bsrend = mat->rmap->rend;
539:   PetscInt       bscstart = mat->cmap->rstart,bscend = mat->cmap->rend,row,col,data;

542:   for (i=0; i<m; i++) {
543:     if (idxm[i] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",idxm[i]); */
544:     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);
545:     if (idxm[i] >= bsrstart && idxm[i] < bsrend) {
546:       row = idxm[i] - bsrstart;
547:       for (j=0; j<n; j++) {
548:         if (idxn[j] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column %D",idxn[j]); */
549:         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);
550:         if (idxn[j] >= bscstart && idxn[j] < bscend) {
551:           col  = idxn[j] - bscstart;
552:           MatGetValues_SeqSBAIJ(baij->A,1,&row,1,&col,v+i*n+j);
553:         } else {
554:           if (!baij->colmap) {
555:             MatCreateColmap_MPIBAIJ_Private(mat);
556:           }
557: #if defined(PETSC_USE_CTABLE)
558:           PetscTableFind(baij->colmap,idxn[j]/bs+1,&data);
559:           data--;
560: #else
561:           data = baij->colmap[idxn[j]/bs]-1;
562: #endif
563:           if ((data < 0) || (baij->garray[data/bs] != idxn[j]/bs)) *(v+i*n+j) = 0.0;
564:           else {
565:             col  = data + idxn[j]%bs;
566:             MatGetValues_SeqBAIJ(baij->B,1,&row,1,&col,v+i*n+j);
567:           }
568:         }
569:       }
570:     } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local values currently supported");
571:   }
572:   return(0);
573: }

575: PetscErrorCode MatNorm_MPISBAIJ(Mat mat,NormType type,PetscReal *norm)
576: {
577:   Mat_MPISBAIJ   *baij = (Mat_MPISBAIJ*)mat->data;
579:   PetscReal      sum[2],*lnorm2;

582:   if (baij->size == 1) {
583:      MatNorm(baij->A,type,norm);
584:   } else {
585:     if (type == NORM_FROBENIUS) {
586:       PetscMalloc1(2,&lnorm2);
587:        MatNorm(baij->A,type,lnorm2);
588:       *lnorm2 = (*lnorm2)*(*lnorm2); lnorm2++;            /* squar power of norm(A) */
589:        MatNorm(baij->B,type,lnorm2);
590:       *lnorm2 = (*lnorm2)*(*lnorm2); lnorm2--;             /* squar power of norm(B) */
591:       MPIU_Allreduce(lnorm2,sum,2,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));
592:       *norm   = PetscSqrtReal(sum[0] + 2*sum[1]);
593:       PetscFree(lnorm2);
594:     } else if (type == NORM_INFINITY || type == NORM_1) { /* max row/column sum */
595:       Mat_SeqSBAIJ *amat=(Mat_SeqSBAIJ*)baij->A->data;
596:       Mat_SeqBAIJ  *bmat=(Mat_SeqBAIJ*)baij->B->data;
597:       PetscReal    *rsum,*rsum2,vabs;
598:       PetscInt     *jj,*garray=baij->garray,rstart=baij->rstartbs,nz;
599:       PetscInt     brow,bcol,col,bs=baij->A->rmap->bs,row,grow,gcol,mbs=amat->mbs;
600:       MatScalar    *v;

602:       PetscMalloc2(mat->cmap->N,&rsum,mat->cmap->N,&rsum2);
603:       PetscMemzero(rsum,mat->cmap->N*sizeof(PetscReal));
604:       /* Amat */
605:       v = amat->a; jj = amat->j;
606:       for (brow=0; brow<mbs; brow++) {
607:         grow = bs*(rstart + brow);
608:         nz   = amat->i[brow+1] - amat->i[brow];
609:         for (bcol=0; bcol<nz; bcol++) {
610:           gcol = bs*(rstart + *jj); jj++;
611:           for (col=0; col<bs; col++) {
612:             for (row=0; row<bs; row++) {
613:               vabs            = PetscAbsScalar(*v); v++;
614:               rsum[gcol+col] += vabs;
615:               /* non-diagonal block */
616:               if (bcol > 0 && vabs > 0.0) rsum[grow+row] += vabs;
617:             }
618:           }
619:         }
620:         PetscLogFlops(nz*bs*bs);
621:       }
622:       /* Bmat */
623:       v = bmat->a; jj = bmat->j;
624:       for (brow=0; brow<mbs; brow++) {
625:         grow = bs*(rstart + brow);
626:         nz = bmat->i[brow+1] - bmat->i[brow];
627:         for (bcol=0; bcol<nz; bcol++) {
628:           gcol = bs*garray[*jj]; jj++;
629:           for (col=0; col<bs; col++) {
630:             for (row=0; row<bs; row++) {
631:               vabs            = PetscAbsScalar(*v); v++;
632:               rsum[gcol+col] += vabs;
633:               rsum[grow+row] += vabs;
634:             }
635:           }
636:         }
637:         PetscLogFlops(nz*bs*bs);
638:       }
639:       MPIU_Allreduce(rsum,rsum2,mat->cmap->N,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));
640:       *norm = 0.0;
641:       for (col=0; col<mat->cmap->N; col++) {
642:         if (rsum2[col] > *norm) *norm = rsum2[col];
643:       }
644:       PetscFree2(rsum,rsum2);
645:     } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support for this norm yet");
646:   }
647:   return(0);
648: }

650: PetscErrorCode MatAssemblyBegin_MPISBAIJ(Mat mat,MatAssemblyType mode)
651: {
652:   Mat_MPISBAIJ   *baij = (Mat_MPISBAIJ*)mat->data;
654:   PetscInt       nstash,reallocs;

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

659:   MatStashScatterBegin_Private(mat,&mat->stash,mat->rmap->range);
660:   MatStashScatterBegin_Private(mat,&mat->bstash,baij->rangebs);
661:   MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);
662:   PetscInfo2(mat,"Stash has %D entries,uses %D mallocs.\n",nstash,reallocs);
663:   MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);
664:   PetscInfo2(mat,"Block-Stash has %D entries, uses %D mallocs.\n",nstash,reallocs);
665:   return(0);
666: }

668: PetscErrorCode MatAssemblyEnd_MPISBAIJ(Mat mat,MatAssemblyType mode)
669: {
670:   Mat_MPISBAIJ   *baij=(Mat_MPISBAIJ*)mat->data;
671:   Mat_SeqSBAIJ   *a   =(Mat_SeqSBAIJ*)baij->A->data;
673:   PetscInt       i,j,rstart,ncols,flg,bs2=baij->bs2;
674:   PetscInt       *row,*col;
675:   PetscBool      other_disassembled;
676:   PetscMPIInt    n;
677:   PetscBool      r1,r2,r3;
678:   MatScalar      *val;

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

687:       for (i=0; i<n;) {
688:         /* Now identify the consecutive vals belonging to the same row */
689:         for (j=i,rstart=row[j]; j<n; j++) {
690:           if (row[j] != rstart) break;
691:         }
692:         if (j < n) ncols = j-i;
693:         else       ncols = n-i;
694:         /* Now assemble all these values with a single function call */
695:         MatSetValues_MPISBAIJ(mat,1,row+i,ncols,col+i,val+i,mat->insertmode);
696:         i    = j;
697:       }
698:     }
699:     MatStashScatterEnd_Private(&mat->stash);
700:     /* Now process the block-stash. Since the values are stashed column-oriented,
701:        set the roworiented flag to column oriented, and after MatSetValues()
702:        restore the original flags */
703:     r1 = baij->roworiented;
704:     r2 = a->roworiented;
705:     r3 = ((Mat_SeqBAIJ*)baij->B->data)->roworiented;

707:     baij->roworiented = PETSC_FALSE;
708:     a->roworiented    = PETSC_FALSE;

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

715:       for (i=0; i<n;) {
716:         /* Now identify the consecutive vals belonging to the same row */
717:         for (j=i,rstart=row[j]; j<n; j++) {
718:           if (row[j] != rstart) break;
719:         }
720:         if (j < n) ncols = j-i;
721:         else       ncols = n-i;
722:         MatSetValuesBlocked_MPISBAIJ(mat,1,row+i,ncols,col+i,val+i*bs2,mat->insertmode);
723:         i    = j;
724:       }
725:     }
726:     MatStashScatterEnd_Private(&mat->bstash);

728:     baij->roworiented = r1;
729:     a->roworiented    = r2;

731:     ((Mat_SeqBAIJ*)baij->B->data)->roworiented = r3; /* b->roworinted */
732:   }

734:   MatAssemblyBegin(baij->A,mode);
735:   MatAssemblyEnd(baij->A,mode);

737:   /* determine if any processor has disassembled, if so we must
738:      also disassemble ourselfs, in order that we may reassemble. */
739:   /*
740:      if nonzero structure of submatrix B cannot change then we know that
741:      no processor disassembled thus we can skip this stuff
742:   */
743:   if (!((Mat_SeqBAIJ*)baij->B->data)->nonew) {
744:     MPIU_Allreduce(&mat->was_assembled,&other_disassembled,1,MPIU_BOOL,MPI_PROD,PetscObjectComm((PetscObject)mat));
745:     if (mat->was_assembled && !other_disassembled) {
746:       MatDisAssemble_MPISBAIJ(mat);
747:     }
748:   }

750:   if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) {
751:     MatSetUpMultiply_MPISBAIJ(mat); /* setup Mvctx and sMvctx */
752:   }
753:   MatAssemblyBegin(baij->B,mode);
754:   MatAssemblyEnd(baij->B,mode);

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

758:   baij->rowvalues = 0;

760:   /* if no new nonzero locations are allowed in matrix then only set the matrix state the first time through */
761:   if ((!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) || !((Mat_SeqBAIJ*)(baij->A->data))->nonew) {
762:     PetscObjectState state = baij->A->nonzerostate + baij->B->nonzerostate;
763:     MPIU_Allreduce(&state,&mat->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)mat));
764:   }
765:   return(0);
766: }

768: extern PetscErrorCode MatSetValues_MPIBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const PetscScalar[],InsertMode);
769:  #include <petscdraw.h>
770: static PetscErrorCode MatView_MPISBAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer)
771: {
772:   Mat_MPISBAIJ      *baij = (Mat_MPISBAIJ*)mat->data;
773:   PetscErrorCode    ierr;
774:   PetscInt          bs   = mat->rmap->bs;
775:   PetscMPIInt       rank = baij->rank;
776:   PetscBool         iascii,isdraw;
777:   PetscViewer       sviewer;
778:   PetscViewerFormat format;

781:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
782:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);
783:   if (iascii) {
784:     PetscViewerGetFormat(viewer,&format);
785:     if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) {
786:       MatInfo info;
787:       MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);
788:       MatGetInfo(mat,MAT_LOCAL,&info);
789:       PetscViewerASCIIPushSynchronized(viewer);
790:       PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D bs %D mem %D\n",rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,mat->rmap->bs,(PetscInt)info.memory);
791:       MatGetInfo(baij->A,MAT_LOCAL,&info);
792:       PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);
793:       MatGetInfo(baij->B,MAT_LOCAL,&info);
794:       PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);
795:       PetscViewerFlush(viewer);
796:       PetscViewerASCIIPopSynchronized(viewer);
797:       PetscViewerASCIIPrintf(viewer,"Information on VecScatter used in matrix-vector product: \n");
798:       VecScatterView(baij->Mvctx,viewer);
799:       return(0);
800:     } else if (format == PETSC_VIEWER_ASCII_INFO) {
801:       PetscViewerASCIIPrintf(viewer,"  block size is %D\n",bs);
802:       return(0);
803:     } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) {
804:       return(0);
805:     }
806:   }

808:   if (isdraw) {
809:     PetscDraw draw;
810:     PetscBool isnull;
811:     PetscViewerDrawGetDraw(viewer,0,&draw);
812:     PetscDrawIsNull(draw,&isnull);
813:     if (isnull) return(0);
814:   }

816:   {
817:     /* assemble the entire matrix onto first processor. */
818:     Mat          A;
819:     Mat_SeqSBAIJ *Aloc;
820:     Mat_SeqBAIJ  *Bloc;
821:     PetscInt     M = mat->rmap->N,N = mat->cmap->N,*ai,*aj,col,i,j,k,*rvals,mbs = baij->mbs;
822:     MatScalar    *a;
823:     const char   *matname;

825:     /* Should this be the same type as mat? */
826:     MatCreate(PetscObjectComm((PetscObject)mat),&A);
827:     if (!rank) {
828:       MatSetSizes(A,M,N,M,N);
829:     } else {
830:       MatSetSizes(A,0,0,M,N);
831:     }
832:     MatSetType(A,MATMPISBAIJ);
833:     MatMPISBAIJSetPreallocation(A,mat->rmap->bs,0,NULL,0,NULL);
834:     MatSetOption(A,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_FALSE);
835:     PetscLogObjectParent((PetscObject)mat,(PetscObject)A);

837:     /* copy over the A part */
838:     Aloc = (Mat_SeqSBAIJ*)baij->A->data;
839:     ai   = Aloc->i; aj = Aloc->j; a = Aloc->a;
840:     PetscMalloc1(bs,&rvals);

842:     for (i=0; i<mbs; i++) {
843:       rvals[0] = bs*(baij->rstartbs + i);
844:       for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1;
845:       for (j=ai[i]; j<ai[i+1]; j++) {
846:         col = (baij->cstartbs+aj[j])*bs;
847:         for (k=0; k<bs; k++) {
848:           MatSetValues_MPISBAIJ(A,bs,rvals,1,&col,a,INSERT_VALUES);
849:           col++;
850:           a += bs;
851:         }
852:       }
853:     }
854:     /* copy over the B part */
855:     Bloc = (Mat_SeqBAIJ*)baij->B->data;
856:     ai   = Bloc->i; aj = Bloc->j; a = Bloc->a;
857:     for (i=0; i<mbs; i++) {

859:       rvals[0] = bs*(baij->rstartbs + i);
860:       for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1;
861:       for (j=ai[i]; j<ai[i+1]; j++) {
862:         col = baij->garray[aj[j]]*bs;
863:         for (k=0; k<bs; k++) {
864:           MatSetValues_MPIBAIJ(A,bs,rvals,1,&col,a,INSERT_VALUES);
865:           col++;
866:           a += bs;
867:         }
868:       }
869:     }
870:     PetscFree(rvals);
871:     MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);
872:     MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);
873:     /*
874:        Everyone has to call to draw the matrix since the graphics waits are
875:        synchronized across all processors that share the PetscDraw object
876:     */
877:     PetscViewerGetSubViewer(viewer,PETSC_COMM_SELF,&sviewer);
878:     PetscObjectGetName((PetscObject)mat,&matname);
879:     if (!rank) {
880:       PetscObjectSetName((PetscObject)((Mat_MPISBAIJ*)(A->data))->A,matname);
881:       MatView_SeqSBAIJ(((Mat_MPISBAIJ*)(A->data))->A,sviewer);
882:     }
883:     PetscViewerRestoreSubViewer(viewer,PETSC_COMM_SELF,&sviewer);
884:     PetscViewerFlush(viewer);
885:     MatDestroy(&A);
886:   }
887:   return(0);
888: }

890: static PetscErrorCode MatView_MPISBAIJ_Binary(Mat mat,PetscViewer viewer)
891: {
892:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)mat->data;
893:   Mat_SeqSBAIJ   *A = (Mat_SeqSBAIJ*)a->A->data;
894:   Mat_SeqBAIJ    *B = (Mat_SeqBAIJ*)a->B->data;
896:   PetscInt       i,*row_lens,*crow_lens,bs = mat->rmap->bs,j,k,bs2=a->bs2,header[4],nz,rlen;
897:   PetscInt       *range=0,nzmax,*column_indices,cnt,col,*garray = a->garray,cstart = mat->cmap->rstart/bs,len,pcnt,l,ll;
898:   int            fd;
899:   PetscScalar    *column_values;
900:   FILE           *file;
901:   PetscMPIInt    rank,size,tag = ((PetscObject)viewer)->tag;
902:   PetscInt       message_count,flowcontrolcount;

905:   MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);
906:   MPI_Comm_size(PetscObjectComm((PetscObject)mat),&size);
907:   nz   = bs2*(A->nz + B->nz);
908:   rlen = mat->rmap->n;
909:   PetscViewerBinaryGetDescriptor(viewer,&fd);
910:   if (!rank) {
911:     header[0] = MAT_FILE_CLASSID;
912:     header[1] = mat->rmap->N;
913:     header[2] = mat->cmap->N;

915:     MPI_Reduce(&nz,&header[3],1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));
916:     PetscBinaryWrite(fd,header,4,PETSC_INT,PETSC_TRUE);
917:     /* get largest number of rows any processor has */
918:     range = mat->rmap->range;
919:     for (i=1; i<size; i++) {
920:       rlen = PetscMax(rlen,range[i+1] - range[i]);
921:     }
922:   } else {
923:     MPI_Reduce(&nz,0,1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));
924:   }

926:   PetscMalloc1(rlen/bs,&crow_lens);
927:   /* compute lengths of each row  */
928:   for (i=0; i<a->mbs; i++) {
929:     crow_lens[i] = A->i[i+1] - A->i[i] + B->i[i+1] - B->i[i];
930:   }
931:   /* store the row lengths to the file */
932:   PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);
933:   if (!rank) {
934:     MPI_Status status;
935:     PetscMalloc1(rlen,&row_lens);
936:     rlen = (range[1] - range[0])/bs;
937:     for (i=0; i<rlen; i++) {
938:       for (j=0; j<bs; j++) {
939:         row_lens[i*bs+j] = bs*crow_lens[i];
940:       }
941:     }
942:     PetscBinaryWrite(fd,row_lens,bs*rlen,PETSC_INT,PETSC_TRUE);
943:     for (i=1; i<size; i++) {
944:       rlen = (range[i+1] - range[i])/bs;
945:       PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);
946:       MPI_Recv(crow_lens,rlen,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);
947:       for (k=0; k<rlen; k++) {
948:         for (j=0; j<bs; j++) {
949:           row_lens[k*bs+j] = bs*crow_lens[k];
950:         }
951:       }
952:       PetscBinaryWrite(fd,row_lens,bs*rlen,PETSC_INT,PETSC_TRUE);
953:     }
954:     PetscViewerFlowControlEndMaster(viewer,&message_count);
955:     PetscFree(row_lens);
956:   } else {
957:     PetscViewerFlowControlStepWorker(viewer,rank,&message_count);
958:     MPI_Send(crow_lens,mat->rmap->n/bs,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));
959:     PetscViewerFlowControlEndWorker(viewer,&message_count);
960:   }
961:   PetscFree(crow_lens);

963:   /* load up the local column indices. Include for all rows not just one for each block row since process 0 does not have the
964:      information needed to make it for each row from a block row. This does require more communication but still not more than
965:      the communication needed for the nonzero values  */
966:   nzmax = nz; /*  space a largest processor needs */
967:   MPI_Reduce(&nz,&nzmax,1,MPIU_INT,MPI_MAX,0,PetscObjectComm((PetscObject)mat));
968:   PetscMalloc1(nzmax,&column_indices);
969:   cnt   = 0;
970:   for (i=0; i<a->mbs; i++) {
971:     pcnt = cnt;
972:     for (j=B->i[i]; j<B->i[i+1]; j++) {
973:       if ((col = garray[B->j[j]]) > cstart) break;
974:       for (l=0; l<bs; l++) {
975:         column_indices[cnt++] = bs*col+l;
976:       }
977:     }
978:     for (k=A->i[i]; k<A->i[i+1]; k++) {
979:       for (l=0; l<bs; l++) {
980:         column_indices[cnt++] = bs*(A->j[k] + cstart)+l;
981:       }
982:     }
983:     for (; j<B->i[i+1]; j++) {
984:       for (l=0; l<bs; l++) {
985:         column_indices[cnt++] = bs*garray[B->j[j]]+l;
986:       }
987:     }
988:     len = cnt - pcnt;
989:     for (k=1; k<bs; k++) {
990:       PetscMemcpy(&column_indices[cnt],&column_indices[pcnt],len*sizeof(PetscInt));
991:       cnt += len;
992:     }
993:   }
994:   if (cnt != nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: cnt = %D nz = %D",cnt,nz);

996:   /* store the columns to the file */
997:   PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);
998:   if (!rank) {
999:     MPI_Status status;
1000:     PetscBinaryWrite(fd,column_indices,nz,PETSC_INT,PETSC_TRUE);
1001:     for (i=1; i<size; i++) {
1002:       PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);
1003:       MPI_Recv(&cnt,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);
1004:       MPI_Recv(column_indices,cnt,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);
1005:       PetscBinaryWrite(fd,column_indices,cnt,PETSC_INT,PETSC_TRUE);
1006:     }
1007:     PetscViewerFlowControlEndMaster(viewer,&message_count);
1008:   } else {
1009:     PetscViewerFlowControlStepWorker(viewer,rank,&message_count);
1010:     MPI_Send(&cnt,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));
1011:     MPI_Send(column_indices,cnt,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));
1012:     PetscViewerFlowControlEndWorker(viewer,&message_count);
1013:   }
1014:   PetscFree(column_indices);

1016:   /* load up the numerical values */
1017:   PetscMalloc1(nzmax,&column_values);
1018:   cnt  = 0;
1019:   for (i=0; i<a->mbs; i++) {
1020:     rlen = bs*(B->i[i+1] - B->i[i] + A->i[i+1] - A->i[i]);
1021:     for (j=B->i[i]; j<B->i[i+1]; j++) {
1022:       if (garray[B->j[j]] > cstart) break;
1023:       for (l=0; l<bs; l++) {
1024:         for (ll=0; ll<bs; ll++) {
1025:           column_values[cnt + l*rlen + ll] = B->a[bs2*j+l+bs*ll];
1026:         }
1027:       }
1028:       cnt += bs;
1029:     }
1030:     for (k=A->i[i]; k<A->i[i+1]; k++) {
1031:       for (l=0; l<bs; l++) {
1032:         for (ll=0; ll<bs; ll++) {
1033:           column_values[cnt + l*rlen + ll] = A->a[bs2*k+l+bs*ll];
1034:         }
1035:       }
1036:       cnt += bs;
1037:     }
1038:     for (; j<B->i[i+1]; j++) {
1039:       for (l=0; l<bs; l++) {
1040:         for (ll=0; ll<bs; ll++) {
1041:           column_values[cnt + l*rlen + ll] = B->a[bs2*j+l+bs*ll];
1042:         }
1043:       }
1044:       cnt += bs;
1045:     }
1046:     cnt += (bs-1)*rlen;
1047:   }
1048:   if (cnt != nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Internal PETSc error: cnt = %D nz = %D",cnt,nz);

1050:   /* store the column values to the file */
1051:   PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);
1052:   if (!rank) {
1053:     MPI_Status status;
1054:     PetscBinaryWrite(fd,column_values,nz,PETSC_SCALAR,PETSC_TRUE);
1055:     for (i=1; i<size; i++) {
1056:       PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);
1057:       MPI_Recv(&cnt,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);
1058:       MPI_Recv(column_values,cnt,MPIU_SCALAR,i,tag,PetscObjectComm((PetscObject)mat),&status);
1059:       PetscBinaryWrite(fd,column_values,cnt,PETSC_SCALAR,PETSC_TRUE);
1060:     }
1061:     PetscViewerFlowControlEndMaster(viewer,&message_count);
1062:   } else {
1063:     PetscViewerFlowControlStepWorker(viewer,rank,&message_count);
1064:     MPI_Send(&nz,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));
1065:     MPI_Send(column_values,nz,MPIU_SCALAR,0,tag,PetscObjectComm((PetscObject)mat));
1066:     PetscViewerFlowControlEndWorker(viewer,&message_count);
1067:   }
1068:   PetscFree(column_values);

1070:   PetscViewerBinaryGetInfoPointer(viewer,&file);
1071:   if (file) {
1072:     fprintf(file,"-matload_block_size %d\n",(int)mat->rmap->bs);
1073:   }
1074:   return(0);
1075: }

1077: PetscErrorCode MatView_MPISBAIJ(Mat mat,PetscViewer viewer)
1078: {
1080:   PetscBool      iascii,isdraw,issocket,isbinary;

1083:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
1084:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);
1085:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSOCKET,&issocket);
1086:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);
1087:   if (iascii || isdraw || issocket) {
1088:     MatView_MPISBAIJ_ASCIIorDraworSocket(mat,viewer);
1089:   } else if (isbinary) {
1090:     MatView_MPISBAIJ_Binary(mat,viewer);
1091:   }
1092:   return(0);
1093: }

1095: PetscErrorCode MatDestroy_MPISBAIJ(Mat mat)
1096: {
1097:   Mat_MPISBAIJ   *baij = (Mat_MPISBAIJ*)mat->data;

1101: #if defined(PETSC_USE_LOG)
1102:   PetscLogObjectState((PetscObject)mat,"Rows=%D,Cols=%D",mat->rmap->N,mat->cmap->N);
1103: #endif
1104:   MatStashDestroy_Private(&mat->stash);
1105:   MatStashDestroy_Private(&mat->bstash);
1106:   MatDestroy(&baij->A);
1107:   MatDestroy(&baij->B);
1108: #if defined(PETSC_USE_CTABLE)
1109:   PetscTableDestroy(&baij->colmap);
1110: #else
1111:   PetscFree(baij->colmap);
1112: #endif
1113:   PetscFree(baij->garray);
1114:   VecDestroy(&baij->lvec);
1115:   VecScatterDestroy(&baij->Mvctx);
1116:   VecDestroy(&baij->slvec0);
1117:   VecDestroy(&baij->slvec0b);
1118:   VecDestroy(&baij->slvec1);
1119:   VecDestroy(&baij->slvec1a);
1120:   VecDestroy(&baij->slvec1b);
1121:   VecScatterDestroy(&baij->sMvctx);
1122:   PetscFree2(baij->rowvalues,baij->rowindices);
1123:   PetscFree(baij->barray);
1124:   PetscFree(baij->hd);
1125:   VecDestroy(&baij->diag);
1126:   VecDestroy(&baij->bb1);
1127:   VecDestroy(&baij->xx1);
1128: #if defined(PETSC_USE_REAL_MAT_SINGLE)
1129:   PetscFree(baij->setvaluescopy);
1130: #endif
1131:   PetscFree(baij->in_loc);
1132:   PetscFree(baij->v_loc);
1133:   PetscFree(baij->rangebs);
1134:   PetscFree(mat->data);

1136:   PetscObjectChangeTypeName((PetscObject)mat,0);
1137:   PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C",NULL);
1138:   PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C",NULL);
1139:   PetscObjectComposeFunction((PetscObject)mat,"MatMPISBAIJSetPreallocation_C",NULL);
1140:   PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpisbaij_mpisbstrm_C",NULL);
1141: #if defined(PETSC_HAVE_ELEMENTAL)
1142:   PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpisbaij_elemental_C",NULL);
1143: #endif
1144:   return(0);
1145: }

1147: PetscErrorCode MatMult_MPISBAIJ_Hermitian(Mat A,Vec xx,Vec yy)
1148: {
1149:   Mat_MPISBAIJ      *a = (Mat_MPISBAIJ*)A->data;
1150:   PetscErrorCode    ierr;
1151:   PetscInt          nt,mbs=a->mbs,bs=A->rmap->bs;
1152:   PetscScalar       *from;
1153:   const PetscScalar *x;

1156:   VecGetLocalSize(xx,&nt);
1157:   if (nt != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx");

1159:   /* diagonal part */
1160:   (*a->A->ops->mult)(a->A,xx,a->slvec1a);
1161:   VecSet(a->slvec1b,0.0);

1163:   /* subdiagonal part */
1164:   (*a->B->ops->multhermitiantranspose)(a->B,xx,a->slvec0b);

1166:   /* copy x into the vec slvec0 */
1167:   VecGetArray(a->slvec0,&from);
1168:   VecGetArrayRead(xx,&x);

1170:   PetscMemcpy(from,x,bs*mbs*sizeof(MatScalar));
1171:   VecRestoreArray(a->slvec0,&from);
1172:   VecRestoreArrayRead(xx,&x);

1174:   VecScatterBegin(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);
1175:   VecScatterEnd(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);
1176:   /* supperdiagonal part */
1177:   (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,yy);
1178:   return(0);
1179: }

1181: PetscErrorCode MatMult_MPISBAIJ(Mat A,Vec xx,Vec yy)
1182: {
1183:   Mat_MPISBAIJ      *a = (Mat_MPISBAIJ*)A->data;
1184:   PetscErrorCode    ierr;
1185:   PetscInt          nt,mbs=a->mbs,bs=A->rmap->bs;
1186:   PetscScalar       *from;
1187:   const PetscScalar *x;

1190:   VecGetLocalSize(xx,&nt);
1191:   if (nt != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx");

1193:   /* diagonal part */
1194:   (*a->A->ops->mult)(a->A,xx,a->slvec1a);
1195:   VecSet(a->slvec1b,0.0);

1197:   /* subdiagonal part */
1198:   (*a->B->ops->multtranspose)(a->B,xx,a->slvec0b);

1200:   /* copy x into the vec slvec0 */
1201:   VecGetArray(a->slvec0,&from);
1202:   VecGetArrayRead(xx,&x);

1204:   PetscMemcpy(from,x,bs*mbs*sizeof(MatScalar));
1205:   VecRestoreArray(a->slvec0,&from);
1206:   VecRestoreArrayRead(xx,&x);

1208:   VecScatterBegin(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);
1209:   VecScatterEnd(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);
1210:   /* supperdiagonal part */
1211:   (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,yy);
1212:   return(0);
1213: }

1215: PetscErrorCode MatMult_MPISBAIJ_2comm(Mat A,Vec xx,Vec yy)
1216: {
1217:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;
1219:   PetscInt       nt;

1222:   VecGetLocalSize(xx,&nt);
1223:   if (nt != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx");

1225:   VecGetLocalSize(yy,&nt);
1226:   if (nt != A->rmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible parition of A and yy");

1228:   VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
1229:   /* do diagonal part */
1230:   (*a->A->ops->mult)(a->A,xx,yy);
1231:   /* do supperdiagonal part */
1232:   VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
1233:   (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);
1234:   /* do subdiagonal part */
1235:   (*a->B->ops->multtranspose)(a->B,xx,a->lvec);
1236:   VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
1237:   VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
1238:   return(0);
1239: }

1241: PetscErrorCode MatMultAdd_MPISBAIJ(Mat A,Vec xx,Vec yy,Vec zz)
1242: {
1243:   Mat_MPISBAIJ      *a = (Mat_MPISBAIJ*)A->data;
1244:   PetscErrorCode    ierr;
1245:   PetscInt          mbs=a->mbs,bs=A->rmap->bs;
1246:   PetscScalar       *from,zero=0.0;
1247:   const PetscScalar *x;

1250:   /*
1251:   PetscSynchronizedPrintf(PetscObjectComm((PetscObject)A)," MatMultAdd is called ...\n");
1252:   PetscSynchronizedFlush(PetscObjectComm((PetscObject)A),PETSC_STDOUT);
1253:   */
1254:   /* diagonal part */
1255:   (*a->A->ops->multadd)(a->A,xx,yy,a->slvec1a);
1256:   VecSet(a->slvec1b,zero);

1258:   /* subdiagonal part */
1259:   (*a->B->ops->multtranspose)(a->B,xx,a->slvec0b);

1261:   /* copy x into the vec slvec0 */
1262:   VecGetArray(a->slvec0,&from);
1263:   VecGetArrayRead(xx,&x);
1264:   PetscMemcpy(from,x,bs*mbs*sizeof(MatScalar));
1265:   VecRestoreArray(a->slvec0,&from);

1267:   VecScatterBegin(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);
1268:   VecRestoreArrayRead(xx,&x);
1269:   VecScatterEnd(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);

1271:   /* supperdiagonal part */
1272:   (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,zz);
1273:   return(0);
1274: }

1276: PetscErrorCode MatMultAdd_MPISBAIJ_2comm(Mat A,Vec xx,Vec yy,Vec zz)
1277: {
1278:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;

1282:   VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
1283:   /* do diagonal part */
1284:   (*a->A->ops->multadd)(a->A,xx,yy,zz);
1285:   /* do supperdiagonal part */
1286:   VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
1287:   (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);

1289:   /* do subdiagonal part */
1290:   (*a->B->ops->multtranspose)(a->B,xx,a->lvec);
1291:   VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);
1292:   VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);
1293:   return(0);
1294: }

1296: /*
1297:   This only works correctly for square matrices where the subblock A->A is the
1298:    diagonal block
1299: */
1300: PetscErrorCode MatGetDiagonal_MPISBAIJ(Mat A,Vec v)
1301: {
1302:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;

1306:   /* if (a->rmap->N != a->cmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block"); */
1307:   MatGetDiagonal(a->A,v);
1308:   return(0);
1309: }

1311: PetscErrorCode MatScale_MPISBAIJ(Mat A,PetscScalar aa)
1312: {
1313:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;

1317:   MatScale(a->A,aa);
1318:   MatScale(a->B,aa);
1319:   return(0);
1320: }

1322: PetscErrorCode MatGetRow_MPISBAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
1323: {
1324:   Mat_MPISBAIJ   *mat = (Mat_MPISBAIJ*)matin->data;
1325:   PetscScalar    *vworkA,*vworkB,**pvA,**pvB,*v_p;
1327:   PetscInt       bs = matin->rmap->bs,bs2 = mat->bs2,i,*cworkA,*cworkB,**pcA,**pcB;
1328:   PetscInt       nztot,nzA,nzB,lrow,brstart = matin->rmap->rstart,brend = matin->rmap->rend;
1329:   PetscInt       *cmap,*idx_p,cstart = mat->rstartbs;

1332:   if (mat->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Already active");
1333:   mat->getrowactive = PETSC_TRUE;

1335:   if (!mat->rowvalues && (idx || v)) {
1336:     /*
1337:         allocate enough space to hold information from the longest row.
1338:     */
1339:     Mat_SeqSBAIJ *Aa = (Mat_SeqSBAIJ*)mat->A->data;
1340:     Mat_SeqBAIJ  *Ba = (Mat_SeqBAIJ*)mat->B->data;
1341:     PetscInt     max = 1,mbs = mat->mbs,tmp;
1342:     for (i=0; i<mbs; i++) {
1343:       tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; /* row length */
1344:       if (max < tmp) max = tmp;
1345:     }
1346:     PetscMalloc2(max*bs2,&mat->rowvalues,max*bs2,&mat->rowindices);
1347:   }

1349:   if (row < brstart || row >= brend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local rows");
1350:   lrow = row - brstart;  /* local row index */

1352:   pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB;
1353:   if (!v)   {pvA = 0; pvB = 0;}
1354:   if (!idx) {pcA = 0; if (!v) pcB = 0;}
1355:   (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);
1356:   (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);
1357:   nztot = nzA + nzB;

1359:   cmap = mat->garray;
1360:   if (v  || idx) {
1361:     if (nztot) {
1362:       /* Sort by increasing column numbers, assuming A and B already sorted */
1363:       PetscInt imark = -1;
1364:       if (v) {
1365:         *v = v_p = mat->rowvalues;
1366:         for (i=0; i<nzB; i++) {
1367:           if (cmap[cworkB[i]/bs] < cstart) v_p[i] = vworkB[i];
1368:           else break;
1369:         }
1370:         imark = i;
1371:         for (i=0; i<nzA; i++)     v_p[imark+i] = vworkA[i];
1372:         for (i=imark; i<nzB; i++) v_p[nzA+i]   = vworkB[i];
1373:       }
1374:       if (idx) {
1375:         *idx = idx_p = mat->rowindices;
1376:         if (imark > -1) {
1377:           for (i=0; i<imark; i++) {
1378:             idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs;
1379:           }
1380:         } else {
1381:           for (i=0; i<nzB; i++) {
1382:             if (cmap[cworkB[i]/bs] < cstart) idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs;
1383:             else break;
1384:           }
1385:           imark = i;
1386:         }
1387:         for (i=0; i<nzA; i++)     idx_p[imark+i] = cstart*bs + cworkA[i];
1388:         for (i=imark; i<nzB; i++) idx_p[nzA+i]   = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ;
1389:       }
1390:     } else {
1391:       if (idx) *idx = 0;
1392:       if (v)   *v   = 0;
1393:     }
1394:   }
1395:   *nz  = nztot;
1396:   (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);
1397:   (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);
1398:   return(0);
1399: }

1401: PetscErrorCode MatRestoreRow_MPISBAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
1402: {
1403:   Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data;

1406:   if (!baij->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"MatGetRow() must be called first");
1407:   baij->getrowactive = PETSC_FALSE;
1408:   return(0);
1409: }

1411: PetscErrorCode MatGetRowUpperTriangular_MPISBAIJ(Mat A)
1412: {
1413:   Mat_MPISBAIJ *a  = (Mat_MPISBAIJ*)A->data;
1414:   Mat_SeqSBAIJ *aA = (Mat_SeqSBAIJ*)a->A->data;

1417:   aA->getrow_utriangular = PETSC_TRUE;
1418:   return(0);
1419: }
1420: PetscErrorCode MatRestoreRowUpperTriangular_MPISBAIJ(Mat A)
1421: {
1422:   Mat_MPISBAIJ *a  = (Mat_MPISBAIJ*)A->data;
1423:   Mat_SeqSBAIJ *aA = (Mat_SeqSBAIJ*)a->A->data;

1426:   aA->getrow_utriangular = PETSC_FALSE;
1427:   return(0);
1428: }

1430: PetscErrorCode MatRealPart_MPISBAIJ(Mat A)
1431: {
1432:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;

1436:   MatRealPart(a->A);
1437:   MatRealPart(a->B);
1438:   return(0);
1439: }

1441: PetscErrorCode MatImaginaryPart_MPISBAIJ(Mat A)
1442: {
1443:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;

1447:   MatImaginaryPart(a->A);
1448:   MatImaginaryPart(a->B);
1449:   return(0);
1450: }

1452: /* Check if isrow is a subset of iscol_local, called by MatCreateSubMatrix_MPISBAIJ()
1453:    Input: isrow       - distributed(parallel), 
1454:           iscol_local - locally owned (seq) 
1455: */
1456: PetscErrorCode ISEqual_private(IS isrow,IS iscol_local,PetscBool  *flg)
1457: {
1459:   PetscInt       sz1,sz2,*a1,*a2,i,j,k,nmatch;
1460:   const PetscInt *ptr1,*ptr2;

1463:   ISGetLocalSize(isrow,&sz1);
1464:   ISGetLocalSize(iscol_local,&sz2);
1465:   if (sz1 > sz2) {
1466:     *flg = PETSC_FALSE;
1467:     return(0);
1468:   }

1470:   ISGetIndices(isrow,&ptr1);
1471:   ISGetIndices(iscol_local,&ptr2);

1473:   PetscMalloc1(sz1,&a1);
1474:   PetscMalloc1(sz2,&a2);
1475:   PetscMemcpy(a1,ptr1,sz1*sizeof(PetscInt));
1476:   PetscMemcpy(a2,ptr2,sz2*sizeof(PetscInt));
1477:   PetscSortInt(sz1,a1);
1478:   PetscSortInt(sz2,a2);

1480:   nmatch=0;
1481:   k     = 0;
1482:   for (i=0; i<sz1; i++){
1483:     for (j=k; j<sz2; j++){
1484:       if (a1[i] == a2[j]) {
1485:         k = j; nmatch++;
1486:         break;
1487:       }
1488:     }
1489:   }
1490:   ISRestoreIndices(isrow,&ptr1);
1491:   ISRestoreIndices(iscol_local,&ptr2);
1492:   PetscFree(a1);
1493:   PetscFree(a2);
1494:   if (nmatch < sz1) {
1495:     *flg = PETSC_FALSE;
1496:   } else {
1497:     *flg = PETSC_TRUE;
1498:   }
1499:   return(0);
1500: }

1502: PetscErrorCode MatCreateSubMatrix_MPISBAIJ(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat)
1503: {
1505:   IS             iscol_local;
1506:   PetscInt       csize;
1507:   PetscBool      isequal;

1510:   ISGetLocalSize(iscol,&csize);
1511:   if (call == MAT_REUSE_MATRIX) {
1512:     PetscObjectQuery((PetscObject)*newmat,"ISAllGather",(PetscObject*)&iscol_local);
1513:     if (!iscol_local) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse");
1514:   } else {
1515:     ISAllGather(iscol,&iscol_local);
1516:     ISEqual_private(isrow,iscol_local,&isequal);
1517:     if (!isequal) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"For symmetric format, iscol must equal isrow");
1518:   }

1520:   /* now call MatCreateSubMatrix_MPIBAIJ() */
1521:   MatCreateSubMatrix_MPIBAIJ_Private(mat,isrow,iscol_local,csize,call,newmat);
1522:   if (call == MAT_INITIAL_MATRIX) {
1523:     PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);
1524:     ISDestroy(&iscol_local);
1525:   }
1526:   return(0);
1527: }

1529: PetscErrorCode MatZeroEntries_MPISBAIJ(Mat A)
1530: {
1531:   Mat_MPISBAIJ   *l = (Mat_MPISBAIJ*)A->data;

1535:   MatZeroEntries(l->A);
1536:   MatZeroEntries(l->B);
1537:   return(0);
1538: }

1540: PetscErrorCode MatGetInfo_MPISBAIJ(Mat matin,MatInfoType flag,MatInfo *info)
1541: {
1542:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)matin->data;
1543:   Mat            A  = a->A,B = a->B;
1545:   PetscReal      isend[5],irecv[5];

1548:   info->block_size = (PetscReal)matin->rmap->bs;

1550:   MatGetInfo(A,MAT_LOCAL,info);

1552:   isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded;
1553:   isend[3] = info->memory;  isend[4] = info->mallocs;

1555:   MatGetInfo(B,MAT_LOCAL,info);

1557:   isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded;
1558:   isend[3] += info->memory;  isend[4] += info->mallocs;
1559:   if (flag == MAT_LOCAL) {
1560:     info->nz_used      = isend[0];
1561:     info->nz_allocated = isend[1];
1562:     info->nz_unneeded  = isend[2];
1563:     info->memory       = isend[3];
1564:     info->mallocs      = isend[4];
1565:   } else if (flag == MAT_GLOBAL_MAX) {
1566:     MPIU_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)matin));

1568:     info->nz_used      = irecv[0];
1569:     info->nz_allocated = irecv[1];
1570:     info->nz_unneeded  = irecv[2];
1571:     info->memory       = irecv[3];
1572:     info->mallocs      = irecv[4];
1573:   } else if (flag == MAT_GLOBAL_SUM) {
1574:     MPIU_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)matin));

1576:     info->nz_used      = irecv[0];
1577:     info->nz_allocated = irecv[1];
1578:     info->nz_unneeded  = irecv[2];
1579:     info->memory       = irecv[3];
1580:     info->mallocs      = irecv[4];
1581:   } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Unknown MatInfoType argument %d",(int)flag);
1582:   info->fill_ratio_given  = 0; /* no parallel LU/ILU/Cholesky */
1583:   info->fill_ratio_needed = 0;
1584:   info->factor_mallocs    = 0;
1585:   return(0);
1586: }

1588: PetscErrorCode MatSetOption_MPISBAIJ(Mat A,MatOption op,PetscBool flg)
1589: {
1590:   Mat_MPISBAIJ   *a  = (Mat_MPISBAIJ*)A->data;
1591:   Mat_SeqSBAIJ   *aA = (Mat_SeqSBAIJ*)a->A->data;

1595:   switch (op) {
1596:   case MAT_NEW_NONZERO_LOCATIONS:
1597:   case MAT_NEW_NONZERO_ALLOCATION_ERR:
1598:   case MAT_UNUSED_NONZERO_LOCATION_ERR:
1599:   case MAT_KEEP_NONZERO_PATTERN:
1600:   case MAT_SUBMAT_SINGLEIS:
1601:   case MAT_NEW_NONZERO_LOCATION_ERR:
1602:     MatCheckPreallocated(A,1);
1603:     MatSetOption(a->A,op,flg);
1604:     MatSetOption(a->B,op,flg);
1605:     break;
1606:   case MAT_ROW_ORIENTED:
1607:     MatCheckPreallocated(A,1);
1608:     a->roworiented = flg;

1610:     MatSetOption(a->A,op,flg);
1611:     MatSetOption(a->B,op,flg);
1612:     break;
1613:   case MAT_NEW_DIAGONALS:
1614:     PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);
1615:     break;
1616:   case MAT_IGNORE_OFF_PROC_ENTRIES:
1617:     a->donotstash = flg;
1618:     break;
1619:   case MAT_USE_HASH_TABLE:
1620:     a->ht_flag = flg;
1621:     break;
1622:   case MAT_HERMITIAN:
1623:     MatCheckPreallocated(A,1);
1624:     if (!A->assembled) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Must call MatAssemblyEnd() first");
1625:     MatSetOption(a->A,op,flg);
1626: #if defined(PETSC_USE_COMPLEX)
1627:     A->ops->mult = MatMult_MPISBAIJ_Hermitian;
1628: #endif
1629:     break;
1630:   case MAT_SPD:
1631:     A->spd_set = PETSC_TRUE;
1632:     A->spd     = flg;
1633:     if (flg) {
1634:       A->symmetric                  = PETSC_TRUE;
1635:       A->structurally_symmetric     = PETSC_TRUE;
1636:       A->symmetric_set              = PETSC_TRUE;
1637:       A->structurally_symmetric_set = PETSC_TRUE;
1638:     }
1639:     break;
1640:   case MAT_SYMMETRIC:
1641:     MatCheckPreallocated(A,1);
1642:     MatSetOption(a->A,op,flg);
1643:     break;
1644:   case MAT_STRUCTURALLY_SYMMETRIC:
1645:     MatCheckPreallocated(A,1);
1646:     MatSetOption(a->A,op,flg);
1647:     break;
1648:   case MAT_SYMMETRY_ETERNAL:
1649:     if (!flg) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Matrix must be symmetric");
1650:     PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);
1651:     break;
1652:   case MAT_IGNORE_LOWER_TRIANGULAR:
1653:     aA->ignore_ltriangular = flg;
1654:     break;
1655:   case MAT_ERROR_LOWER_TRIANGULAR:
1656:     aA->ignore_ltriangular = flg;
1657:     break;
1658:   case MAT_GETROW_UPPERTRIANGULAR:
1659:     aA->getrow_utriangular = flg;
1660:     break;
1661:   default:
1662:     SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %d",op);
1663:   }
1664:   return(0);
1665: }

1667: PetscErrorCode MatTranspose_MPISBAIJ(Mat A,MatReuse reuse,Mat *B)
1668: {

1672:   if (reuse == MAT_INITIAL_MATRIX) {
1673:     MatDuplicate(A,MAT_COPY_VALUES,B);
1674:   }  else if (reuse == MAT_REUSE_MATRIX) {
1675:     MatCopy(A,*B,SAME_NONZERO_PATTERN);
1676:   }
1677:   return(0);
1678: }

1680: PetscErrorCode MatDiagonalScale_MPISBAIJ(Mat mat,Vec ll,Vec rr)
1681: {
1682:   Mat_MPISBAIJ   *baij = (Mat_MPISBAIJ*)mat->data;
1683:   Mat            a     = baij->A, b=baij->B;
1685:   PetscInt       nv,m,n;
1686:   PetscBool      flg;

1689:   if (ll != rr) {
1690:     VecEqual(ll,rr,&flg);
1691:     if (!flg) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"For symmetric format, left and right scaling vectors must be same\n");
1692:   }
1693:   if (!ll) return(0);

1695:   MatGetLocalSize(mat,&m,&n);
1696:   if (m != n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"For symmetric format, local size %d %d must be same",m,n);

1698:   VecGetLocalSize(rr,&nv);
1699:   if (nv!=n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Left and right vector non-conforming local size");

1701:   VecScatterBegin(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);

1703:   /* left diagonalscale the off-diagonal part */
1704:   (*b->ops->diagonalscale)(b,ll,NULL);

1706:   /* scale the diagonal part */
1707:   (*a->ops->diagonalscale)(a,ll,rr);

1709:   /* right diagonalscale the off-diagonal part */
1710:   VecScatterEnd(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);
1711:   (*b->ops->diagonalscale)(b,NULL,baij->lvec);
1712:   return(0);
1713: }

1715: PetscErrorCode MatSetUnfactored_MPISBAIJ(Mat A)
1716: {
1717:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;

1721:   MatSetUnfactored(a->A);
1722:   return(0);
1723: }

1725: static PetscErrorCode MatDuplicate_MPISBAIJ(Mat,MatDuplicateOption,Mat*);

1727: PetscErrorCode MatEqual_MPISBAIJ(Mat A,Mat B,PetscBool  *flag)
1728: {
1729:   Mat_MPISBAIJ   *matB = (Mat_MPISBAIJ*)B->data,*matA = (Mat_MPISBAIJ*)A->data;
1730:   Mat            a,b,c,d;
1731:   PetscBool      flg;

1735:   a = matA->A; b = matA->B;
1736:   c = matB->A; d = matB->B;

1738:   MatEqual(a,c,&flg);
1739:   if (flg) {
1740:     MatEqual(b,d,&flg);
1741:   }
1742:   MPIU_Allreduce(&flg,flag,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)A));
1743:   return(0);
1744: }

1746: PetscErrorCode MatCopy_MPISBAIJ(Mat A,Mat B,MatStructure str)
1747: {
1749:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;
1750:   Mat_MPISBAIJ   *b = (Mat_MPISBAIJ*)B->data;

1753:   /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */
1754:   if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) {
1755:     MatGetRowUpperTriangular(A);
1756:     MatCopy_Basic(A,B,str);
1757:     MatRestoreRowUpperTriangular(A);
1758:   } else {
1759:     MatCopy(a->A,b->A,str);
1760:     MatCopy(a->B,b->B,str);
1761:   }
1762:   PetscObjectStateIncrease((PetscObject)B);
1763:   return(0);
1764: }

1766: PetscErrorCode MatSetUp_MPISBAIJ(Mat A)
1767: {

1771:   MatMPISBAIJSetPreallocation(A,A->rmap->bs,PETSC_DEFAULT,0,PETSC_DEFAULT,0);
1772:   return(0);
1773: }

1775: PetscErrorCode MatAXPY_MPISBAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str)
1776: {
1778:   Mat_MPISBAIJ   *xx=(Mat_MPISBAIJ*)X->data,*yy=(Mat_MPISBAIJ*)Y->data;
1779:   PetscBLASInt   bnz,one=1;
1780:   Mat_SeqSBAIJ   *xa,*ya;
1781:   Mat_SeqBAIJ    *xb,*yb;

1784:   if (str == SAME_NONZERO_PATTERN) {
1785:     PetscScalar alpha = a;
1786:     xa   = (Mat_SeqSBAIJ*)xx->A->data;
1787:     ya   = (Mat_SeqSBAIJ*)yy->A->data;
1788:     PetscBLASIntCast(xa->nz,&bnz);
1789:     PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,xa->a,&one,ya->a,&one));
1790:     xb   = (Mat_SeqBAIJ*)xx->B->data;
1791:     yb   = (Mat_SeqBAIJ*)yy->B->data;
1792:     PetscBLASIntCast(xb->nz,&bnz);
1793:     PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,xb->a,&one,yb->a,&one));
1794:     PetscObjectStateIncrease((PetscObject)Y);
1795:   } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */
1796:     MatSetOption(X,MAT_GETROW_UPPERTRIANGULAR,PETSC_TRUE);
1797:     MatAXPY_Basic(Y,a,X,str);
1798:     MatSetOption(X,MAT_GETROW_UPPERTRIANGULAR,PETSC_FALSE);
1799:   } else {
1800:     Mat      B;
1801:     PetscInt *nnz_d,*nnz_o,bs=Y->rmap->bs;
1802:     if (bs != X->rmap->bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Matrices must have same block size");
1803:     MatGetRowUpperTriangular(X);
1804:     MatGetRowUpperTriangular(Y);
1805:     PetscMalloc1(yy->A->rmap->N,&nnz_d);
1806:     PetscMalloc1(yy->B->rmap->N,&nnz_o);
1807:     MatCreate(PetscObjectComm((PetscObject)Y),&B);
1808:     PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);
1809:     MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);
1810:     MatSetBlockSizesFromMats(B,Y,Y);
1811:     MatSetType(B,MATMPISBAIJ);
1812:     MatAXPYGetPreallocation_SeqSBAIJ(yy->A,xx->A,nnz_d);
1813:     MatAXPYGetPreallocation_MPIBAIJ(yy->B,yy->garray,xx->B,xx->garray,nnz_o);
1814:     MatMPISBAIJSetPreallocation(B,bs,0,nnz_d,0,nnz_o);
1815:     MatAXPY_BasicWithPreallocation(B,Y,a,X,str);
1816:     MatHeaderReplace(Y,&B);
1817:     PetscFree(nnz_d);
1818:     PetscFree(nnz_o);
1819:     MatRestoreRowUpperTriangular(X);
1820:     MatRestoreRowUpperTriangular(Y);
1821:   }
1822:   return(0);
1823: }

1825: PetscErrorCode MatCreateSubMatrices_MPISBAIJ(Mat A,PetscInt n,const IS irow[],const IS icol[],MatReuse scall,Mat *B[])
1826: {
1828:   PetscInt       i;
1829:   PetscBool      flg;

1832:   MatCreateSubMatrices_MPIBAIJ(A,n,irow,icol,scall,B); /* B[] are sbaij matrices */
1833:   for (i=0; i<n; i++) {
1834:     ISEqual(irow[i],icol[i],&flg);
1835:     if (!flg) {
1836:       MatSeqSBAIJZeroOps_Private(*B[i]);
1837:     }
1838:   }
1839:   return(0);
1840: }

1842: PetscErrorCode MatShift_MPISBAIJ(Mat Y,PetscScalar a)
1843: {
1845:   Mat_MPISBAIJ    *maij = (Mat_MPISBAIJ*)Y->data;
1846:   Mat_SeqSBAIJ    *aij = (Mat_SeqSBAIJ*)maij->A->data;

1849:   if (!Y->preallocated) {
1850:     MatMPISBAIJSetPreallocation(Y,Y->rmap->bs,1,NULL,0,NULL);
1851:   } else if (!aij->nz) {
1852:     PetscInt nonew = aij->nonew;
1853:     MatSeqSBAIJSetPreallocation(maij->A,Y->rmap->bs,1,NULL);
1854:     aij->nonew = nonew;
1855:   }
1856:   MatShift_Basic(Y,a);
1857:   return(0);
1858: }

1860: PetscErrorCode MatMissingDiagonal_MPISBAIJ(Mat A,PetscBool  *missing,PetscInt *d)
1861: {
1862:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;

1866:   if (A->rmap->n != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only works for square matrices");
1867:   MatMissingDiagonal(a->A,missing,d);
1868:   if (d) {
1869:     PetscInt rstart;
1870:     MatGetOwnershipRange(A,&rstart,NULL);
1871:     *d += rstart/A->rmap->bs;

1873:   }
1874:   return(0);
1875: }

1877: PetscErrorCode  MatGetDiagonalBlock_MPISBAIJ(Mat A,Mat *a)
1878: {
1880:   *a = ((Mat_MPISBAIJ*)A->data)->A;
1881:   return(0);
1882: }

1884: /* -------------------------------------------------------------------*/
1885: static struct _MatOps MatOps_Values = {MatSetValues_MPISBAIJ,
1886:                                        MatGetRow_MPISBAIJ,
1887:                                        MatRestoreRow_MPISBAIJ,
1888:                                        MatMult_MPISBAIJ,
1889:                                /*  4*/ MatMultAdd_MPISBAIJ,
1890:                                        MatMult_MPISBAIJ,       /* transpose versions are same as non-transpose */
1891:                                        MatMultAdd_MPISBAIJ,
1892:                                        0,
1893:                                        0,
1894:                                        0,
1895:                                /* 10*/ 0,
1896:                                        0,
1897:                                        0,
1898:                                        MatSOR_MPISBAIJ,
1899:                                        MatTranspose_MPISBAIJ,
1900:                                /* 15*/ MatGetInfo_MPISBAIJ,
1901:                                        MatEqual_MPISBAIJ,
1902:                                        MatGetDiagonal_MPISBAIJ,
1903:                                        MatDiagonalScale_MPISBAIJ,
1904:                                        MatNorm_MPISBAIJ,
1905:                                /* 20*/ MatAssemblyBegin_MPISBAIJ,
1906:                                        MatAssemblyEnd_MPISBAIJ,
1907:                                        MatSetOption_MPISBAIJ,
1908:                                        MatZeroEntries_MPISBAIJ,
1909:                                /* 24*/ 0,
1910:                                        0,
1911:                                        0,
1912:                                        0,
1913:                                        0,
1914:                                /* 29*/ MatSetUp_MPISBAIJ,
1915:                                        0,
1916:                                        0,
1917:                                        MatGetDiagonalBlock_MPISBAIJ,
1918:                                        0,
1919:                                /* 34*/ MatDuplicate_MPISBAIJ,
1920:                                        0,
1921:                                        0,
1922:                                        0,
1923:                                        0,
1924:                                /* 39*/ MatAXPY_MPISBAIJ,
1925:                                        MatCreateSubMatrices_MPISBAIJ,
1926:                                        MatIncreaseOverlap_MPISBAIJ,
1927:                                        MatGetValues_MPISBAIJ,
1928:                                        MatCopy_MPISBAIJ,
1929:                                /* 44*/ 0,
1930:                                        MatScale_MPISBAIJ,
1931:                                        MatShift_MPISBAIJ,
1932:                                        0,
1933:                                        0,
1934:                                /* 49*/ 0,
1935:                                        0,
1936:                                        0,
1937:                                        0,
1938:                                        0,
1939:                                /* 54*/ 0,
1940:                                        0,
1941:                                        MatSetUnfactored_MPISBAIJ,
1942:                                        0,
1943:                                        MatSetValuesBlocked_MPISBAIJ,
1944:                                /* 59*/ MatCreateSubMatrix_MPISBAIJ,
1945:                                        0,
1946:                                        0,
1947:                                        0,
1948:                                        0,
1949:                                /* 64*/ 0,
1950:                                        0,
1951:                                        0,
1952:                                        0,
1953:                                        0,
1954:                                /* 69*/ MatGetRowMaxAbs_MPISBAIJ,
1955:                                        0,
1956:                                        0,
1957:                                        0,
1958:                                        0,
1959:                                /* 74*/ 0,
1960:                                        0,
1961:                                        0,
1962:                                        0,
1963:                                        0,
1964:                                /* 79*/ 0,
1965:                                        0,
1966:                                        0,
1967:                                        0,
1968:                                        MatLoad_MPISBAIJ,
1969:                                /* 84*/ 0,
1970:                                        0,
1971:                                        0,
1972:                                        0,
1973:                                        0,
1974:                                /* 89*/ 0,
1975:                                        0,
1976:                                        0,
1977:                                        0,
1978:                                        0,
1979:                                /* 94*/ 0,
1980:                                        0,
1981:                                        0,
1982:                                        0,
1983:                                        0,
1984:                                /* 99*/ 0,
1985:                                        0,
1986:                                        0,
1987:                                        0,
1988:                                        0,
1989:                                /*104*/ 0,
1990:                                        MatRealPart_MPISBAIJ,
1991:                                        MatImaginaryPart_MPISBAIJ,
1992:                                        MatGetRowUpperTriangular_MPISBAIJ,
1993:                                        MatRestoreRowUpperTriangular_MPISBAIJ,
1994:                                /*109*/ 0,
1995:                                        0,
1996:                                        0,
1997:                                        0,
1998:                                        MatMissingDiagonal_MPISBAIJ,
1999:                                /*114*/ 0,
2000:                                        0,
2001:                                        0,
2002:                                        0,
2003:                                        0,
2004:                                /*119*/ 0,
2005:                                        0,
2006:                                        0,
2007:                                        0,
2008:                                        0,
2009:                                /*124*/ 0,
2010:                                        0,
2011:                                        0,
2012:                                        0,
2013:                                        0,
2014:                                /*129*/ 0,
2015:                                        0,
2016:                                        0,
2017:                                        0,
2018:                                        0,
2019:                                /*134*/ 0,
2020:                                        0,
2021:                                        0,
2022:                                        0,
2023:                                        0,
2024:                                /*139*/ MatSetBlockSizes_Default,
2025:                                        0,
2026:                                        0,
2027:                                        0,
2028:                                        0,
2029:                                 /*144*/MatCreateMPIMatConcatenateSeqMat_MPISBAIJ
2030: };

2032: PetscErrorCode  MatMPISBAIJSetPreallocation_MPISBAIJ(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt *d_nnz,PetscInt o_nz,const PetscInt *o_nnz)
2033: {
2034:   Mat_MPISBAIJ   *b;
2036:   PetscInt       i,mbs,Mbs;

2039:   MatSetBlockSize(B,PetscAbs(bs));
2040:   PetscLayoutSetUp(B->rmap);
2041:   PetscLayoutSetUp(B->cmap);
2042:   PetscLayoutGetBlockSize(B->rmap,&bs);

2044:   b   = (Mat_MPISBAIJ*)B->data;
2045:   mbs = B->rmap->n/bs;
2046:   Mbs = B->rmap->N/bs;
2047:   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);

2049:   B->rmap->bs = bs;
2050:   b->bs2      = bs*bs;
2051:   b->mbs      = mbs;
2052:   b->Mbs      = Mbs;
2053:   b->nbs      = B->cmap->n/bs;
2054:   b->Nbs      = B->cmap->N/bs;

2056:   for (i=0; i<=b->size; i++) {
2057:     b->rangebs[i] = B->rmap->range[i]/bs;
2058:   }
2059:   b->rstartbs = B->rmap->rstart/bs;
2060:   b->rendbs   = B->rmap->rend/bs;

2062:   b->cstartbs = B->cmap->rstart/bs;
2063:   b->cendbs   = B->cmap->rend/bs;

2065: #if defined(PETSC_USE_CTABLE)
2066:   PetscTableDestroy(&b->colmap);
2067: #else
2068:   PetscFree(b->colmap);
2069: #endif
2070:   PetscFree(b->garray);
2071:   VecDestroy(&b->lvec);
2072:   VecScatterDestroy(&b->Mvctx);
2073:   VecDestroy(&b->slvec0);
2074:   VecDestroy(&b->slvec0b);
2075:   VecDestroy(&b->slvec1);
2076:   VecDestroy(&b->slvec1a);
2077:   VecDestroy(&b->slvec1b);
2078:   VecScatterDestroy(&b->sMvctx);

2080:   /* Because the B will have been resized we simply destroy it and create a new one each time */
2081:   MatDestroy(&b->B);
2082:   MatCreate(PETSC_COMM_SELF,&b->B);
2083:   MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);
2084:   MatSetType(b->B,MATSEQBAIJ);
2085:   PetscLogObjectParent((PetscObject)B,(PetscObject)b->B);

2087:   if (!B->preallocated) {
2088:     MatCreate(PETSC_COMM_SELF,&b->A);
2089:     MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);
2090:     MatSetType(b->A,MATSEQSBAIJ);
2091:     PetscLogObjectParent((PetscObject)B,(PetscObject)b->A);
2092:     MatStashCreate_Private(PetscObjectComm((PetscObject)B),bs,&B->bstash);
2093:   }

2095:   MatSeqSBAIJSetPreallocation(b->A,bs,d_nz,d_nnz);
2096:   MatSeqBAIJSetPreallocation(b->B,bs,o_nz,o_nnz);

2098:   B->preallocated  = PETSC_TRUE;
2099:   B->was_assembled = PETSC_FALSE;
2100:   B->assembled     = PETSC_FALSE;
2101:   return(0);
2102: }

2104: PetscErrorCode MatMPISBAIJSetPreallocationCSR_MPISBAIJ(Mat B,PetscInt bs,const PetscInt ii[],const PetscInt jj[],const PetscScalar V[])
2105: {
2106:   PetscInt       m,rstart,cstart,cend;
2107:   PetscInt       i,j,d,nz,nz_max=0,*d_nnz=0,*o_nnz=0;
2108:   const PetscInt *JJ    =0;
2109:   PetscScalar    *values=0;

2113:   if (bs < 1) SETERRQ1(PetscObjectComm((PetscObject)B),PETSC_ERR_ARG_OUTOFRANGE,"Invalid block size specified, must be positive but it is %D",bs);
2114:   PetscLayoutSetBlockSize(B->rmap,bs);
2115:   PetscLayoutSetBlockSize(B->cmap,bs);
2116:   PetscLayoutSetUp(B->rmap);
2117:   PetscLayoutSetUp(B->cmap);
2118:   PetscLayoutGetBlockSize(B->rmap,&bs);
2119:   m      = B->rmap->n/bs;
2120:   rstart = B->rmap->rstart/bs;
2121:   cstart = B->cmap->rstart/bs;
2122:   cend   = B->cmap->rend/bs;

2124:   if (ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"ii[0] must be 0 but it is %D",ii[0]);
2125:   PetscMalloc2(m,&d_nnz,m,&o_nnz);
2126:   for (i=0; i<m; i++) {
2127:     nz = ii[i+1] - ii[i];
2128:     if (nz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative number of columns %D",i,nz);
2129:     nz_max = PetscMax(nz_max,nz);
2130:     JJ     = jj + ii[i];
2131:     for (j=0; j<nz; j++) {
2132:       if (*JJ >= cstart) break;
2133:       JJ++;
2134:     }
2135:     d = 0;
2136:     for (; j<nz; j++) {
2137:       if (*JJ++ >= cend) break;
2138:       d++;
2139:     }
2140:     d_nnz[i] = d;
2141:     o_nnz[i] = nz - d;
2142:   }
2143:   MatMPISBAIJSetPreallocation(B,bs,0,d_nnz,0,o_nnz);
2144:   PetscFree2(d_nnz,o_nnz);

2146:   values = (PetscScalar*)V;
2147:   if (!values) {
2148:     PetscMalloc1(bs*bs*nz_max,&values);
2149:     PetscMemzero(values,bs*bs*nz_max*sizeof(PetscScalar));
2150:   }
2151:   for (i=0; i<m; i++) {
2152:     PetscInt          row    = i + rstart;
2153:     PetscInt          ncols  = ii[i+1] - ii[i];
2154:     const PetscInt    *icols = jj + ii[i];
2155:     const PetscScalar *svals = values + (V ? (bs*bs*ii[i]) : 0);
2156:     MatSetValuesBlocked_MPISBAIJ(B,1,&row,ncols,icols,svals,INSERT_VALUES);
2157:   }

2159:   if (!V) { PetscFree(values); }
2160:   MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
2161:   MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);
2162:   MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);
2163:   return(0);
2164: }

2166: /*MC
2167:    MATMPISBAIJ - MATMPISBAIJ = "mpisbaij" - A matrix type to be used for distributed symmetric sparse block matrices,
2168:    based on block compressed sparse row format.  Only the upper triangular portion of the "diagonal" portion of
2169:    the matrix is stored.

2171:   For complex numbers by default this matrix is symmetric, NOT Hermitian symmetric. To make it Hermitian symmetric you
2172:   can call MatSetOption(Mat, MAT_HERMITIAN);

2174:    Options Database Keys:
2175: . -mat_type mpisbaij - sets the matrix type to "mpisbaij" during a call to MatSetFromOptions()

2177:   Level: beginner

2179: .seealso: MatCreateMPISBAIJ
2180: M*/

2182: PETSC_INTERN PetscErrorCode MatConvert_MPISBAIJ_MPISBSTRM(Mat,MatType,MatReuse,Mat*);

2184: PETSC_EXTERN PetscErrorCode MatCreate_MPISBAIJ(Mat B)
2185: {
2186:   Mat_MPISBAIJ   *b;
2188:   PetscBool      flg = PETSC_FALSE;

2191:   PetscNewLog(B,&b);
2192:   B->data = (void*)b;
2193:   PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));

2195:   B->ops->destroy = MatDestroy_MPISBAIJ;
2196:   B->ops->view    = MatView_MPISBAIJ;
2197:   B->assembled    = PETSC_FALSE;
2198:   B->insertmode   = NOT_SET_VALUES;

2200:   MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);
2201:   MPI_Comm_size(PetscObjectComm((PetscObject)B),&b->size);

2203:   /* build local table of row and column ownerships */
2204:   PetscMalloc1(b->size+2,&b->rangebs);

2206:   /* build cache for off array entries formed */
2207:   MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);

2209:   b->donotstash  = PETSC_FALSE;
2210:   b->colmap      = NULL;
2211:   b->garray      = NULL;
2212:   b->roworiented = PETSC_TRUE;

2214:   /* stuff used in block assembly */
2215:   b->barray = 0;

2217:   /* stuff used for matrix vector multiply */
2218:   b->lvec    = 0;
2219:   b->Mvctx   = 0;
2220:   b->slvec0  = 0;
2221:   b->slvec0b = 0;
2222:   b->slvec1  = 0;
2223:   b->slvec1a = 0;
2224:   b->slvec1b = 0;
2225:   b->sMvctx  = 0;

2227:   /* stuff for MatGetRow() */
2228:   b->rowindices   = 0;
2229:   b->rowvalues    = 0;
2230:   b->getrowactive = PETSC_FALSE;

2232:   /* hash table stuff */
2233:   b->ht           = 0;
2234:   b->hd           = 0;
2235:   b->ht_size      = 0;
2236:   b->ht_flag      = PETSC_FALSE;
2237:   b->ht_fact      = 0;
2238:   b->ht_total_ct  = 0;
2239:   b->ht_insert_ct = 0;

2241:   /* stuff for MatCreateSubMatrices_MPIBAIJ_local() */
2242:   b->ijonly = PETSC_FALSE;

2244:   b->in_loc = 0;
2245:   b->v_loc  = 0;
2246:   b->n_loc  = 0;

2248:   PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPISBAIJ);
2249:   PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPISBAIJ);
2250:   PetscObjectComposeFunction((PetscObject)B,"MatMPISBAIJSetPreallocation_C",MatMPISBAIJSetPreallocation_MPISBAIJ);
2251:   PetscObjectComposeFunction((PetscObject)B,"MatMPISBAIJSetPreallocationCSR_C",MatMPISBAIJSetPreallocationCSR_MPISBAIJ);
2252: #if defined(PETSC_HAVE_ELEMENTAL)
2253:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpisbaij_elemental_C",MatConvert_MPISBAIJ_Elemental);
2254: #endif

2256:   B->symmetric                  = PETSC_TRUE;
2257:   B->structurally_symmetric     = PETSC_TRUE;
2258:   B->symmetric_set              = PETSC_TRUE;
2259:   B->structurally_symmetric_set = PETSC_TRUE;

2261:   PetscObjectChangeTypeName((PetscObject)B,MATMPISBAIJ);
2262:   PetscOptionsBegin(PetscObjectComm((PetscObject)B),NULL,"Options for loading MPISBAIJ matrix 1","Mat");
2263:   PetscOptionsBool("-mat_use_hash_table","Use hash table to save memory in constructing matrix","MatSetOption",flg,&flg,NULL);
2264:   if (flg) {
2265:     PetscReal fact = 1.39;
2266:     MatSetOption(B,MAT_USE_HASH_TABLE,PETSC_TRUE);
2267:     PetscOptionsReal("-mat_use_hash_table","Use hash table factor","MatMPIBAIJSetHashTableFactor",fact,&fact,NULL);
2268:     if (fact <= 1.0) fact = 1.39;
2269:     MatMPIBAIJSetHashTableFactor(B,fact);
2270:     PetscInfo1(B,"Hash table Factor used %5.2f\n",fact);
2271:   }
2272:   PetscOptionsEnd();
2273:   return(0);
2274: }

2276: /*MC
2277:    MATSBAIJ - MATSBAIJ = "sbaij" - A matrix type to be used for symmetric block sparse matrices.

2279:    This matrix type is identical to MATSEQSBAIJ when constructed with a single process communicator,
2280:    and MATMPISBAIJ otherwise.

2282:    Options Database Keys:
2283: . -mat_type sbaij - sets the matrix type to "sbaij" during a call to MatSetFromOptions()

2285:   Level: beginner

2287: .seealso: MatCreateMPISBAIJ,MATSEQSBAIJ,MATMPISBAIJ
2288: M*/

2290: /*@C
2291:    MatMPISBAIJSetPreallocation - For good matrix assembly performance
2292:    the user should preallocate the matrix storage by setting the parameters
2293:    d_nz (or d_nnz) and o_nz (or o_nnz).  By setting these parameters accurately,
2294:    performance can be increased by more than a factor of 50.

2296:    Collective on Mat

2298:    Input Parameters:
2299: +  B - the matrix
2300: .  bs   - size of block, the blocks are ALWAYS square. One can use MatSetBlockSizes() to set a different row and column blocksize but the row
2301:           blocksize always defines the size of the blocks. The column blocksize sets the blocksize of the vectors obtained with MatCreateVecs()
2302: .  d_nz  - number of block nonzeros per block row in diagonal portion of local
2303:            submatrix  (same for all local rows)
2304: .  d_nnz - array containing the number of block nonzeros in the various block rows
2305:            in the upper triangular and diagonal part of the in diagonal portion of the local
2306:            (possibly different for each block row) or NULL.  If you plan to factor the matrix you must leave room
2307:            for the diagonal entry and set a value even if it is zero.
2308: .  o_nz  - number of block nonzeros per block row in the off-diagonal portion of local
2309:            submatrix (same for all local rows).
2310: -  o_nnz - array containing the number of nonzeros in the various block rows of the
2311:            off-diagonal portion of the local submatrix that is right of the diagonal
2312:            (possibly different for each block row) or NULL.


2315:    Options Database Keys:
2316: .   -mat_no_unroll - uses code that does not unroll the loops in the
2317:                      block calculations (much slower)
2318: .   -mat_block_size - size of the blocks to use

2320:    Notes:

2322:    If PETSC_DECIDE or  PETSC_DETERMINE is used for a particular argument on one processor
2323:    than it must be used on all processors that share the object for that argument.

2325:    If the *_nnz parameter is given then the *_nz parameter is ignored

2327:    Storage Information:
2328:    For a square global matrix we define each processor's diagonal portion
2329:    to be its local rows and the corresponding columns (a square submatrix);
2330:    each processor's off-diagonal portion encompasses the remainder of the
2331:    local matrix (a rectangular submatrix).

2333:    The user can specify preallocated storage for the diagonal part of
2334:    the local submatrix with either d_nz or d_nnz (not both).  Set
2335:    d_nz=PETSC_DEFAULT and d_nnz=NULL for PETSc to control dynamic
2336:    memory allocation.  Likewise, specify preallocated storage for the
2337:    off-diagonal part of the local submatrix with o_nz or o_nnz (not both).

2339:    You can call MatGetInfo() to get information on how effective the preallocation was;
2340:    for example the fields mallocs,nz_allocated,nz_used,nz_unneeded;
2341:    You can also run with the option -info and look for messages with the string
2342:    malloc in them to see if additional memory allocation was needed.

2344:    Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In
2345:    the figure below we depict these three local rows and all columns (0-11).

2347: .vb
2348:            0 1 2 3 4 5 6 7 8 9 10 11
2349:           --------------------------
2350:    row 3  |. . . d d d o o o o  o  o
2351:    row 4  |. . . d d d o o o o  o  o
2352:    row 5  |. . . d d d o o o o  o  o
2353:           --------------------------
2354: .ve

2356:    Thus, any entries in the d locations are stored in the d (diagonal)
2357:    submatrix, and any entries in the o locations are stored in the
2358:    o (off-diagonal) submatrix.  Note that the d matrix is stored in
2359:    MatSeqSBAIJ format and the o submatrix in MATSEQBAIJ format.

2361:    Now d_nz should indicate the number of block nonzeros per row in the upper triangular
2362:    plus the diagonal part of the d matrix,
2363:    and o_nz should indicate the number of block nonzeros per row in the o matrix

2365:    In general, for PDE problems in which most nonzeros are near the diagonal,
2366:    one expects d_nz >> o_nz.   For large problems you MUST preallocate memory
2367:    or you will get TERRIBLE performance; see the users' manual chapter on
2368:    matrices.

2370:    Level: intermediate

2372: .keywords: matrix, block, aij, compressed row, sparse, parallel

2374: .seealso: MatCreate(), MatCreateSeqSBAIJ(), MatSetValues(), MatCreateBAIJ(), PetscSplitOwnership()
2375: @*/
2376: PetscErrorCode  MatMPISBAIJSetPreallocation(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[])
2377: {

2384:   PetscTryMethod(B,"MatMPISBAIJSetPreallocation_C",(Mat,PetscInt,PetscInt,const PetscInt[],PetscInt,const PetscInt[]),(B,bs,d_nz,d_nnz,o_nz,o_nnz));
2385:   return(0);
2386: }

2388: /*@C
2389:    MatCreateSBAIJ - Creates a sparse parallel matrix in symmetric block AIJ format
2390:    (block compressed row).  For good matrix assembly performance
2391:    the user should preallocate the matrix storage by setting the parameters
2392:    d_nz (or d_nnz) and o_nz (or o_nnz).  By setting these parameters accurately,
2393:    performance can be increased by more than a factor of 50.

2395:    Collective on MPI_Comm

2397:    Input Parameters:
2398: +  comm - MPI communicator
2399: .  bs   - size of block, the blocks are ALWAYS square. One can use MatSetBlockSizes() to set a different row and column blocksize but the row
2400:           blocksize always defines the size of the blocks. The column blocksize sets the blocksize of the vectors obtained with MatCreateVecs()
2401: .  m - number of local rows (or PETSC_DECIDE to have calculated if M is given)
2402:            This value should be the same as the local size used in creating the
2403:            y vector for the matrix-vector product y = Ax.
2404: .  n - number of local columns (or PETSC_DECIDE to have calculated if N is given)
2405:            This value should be the same as the local size used in creating the
2406:            x vector for the matrix-vector product y = Ax.
2407: .  M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
2408: .  N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
2409: .  d_nz  - number of block nonzeros per block row in diagonal portion of local
2410:            submatrix  (same for all local rows)
2411: .  d_nnz - array containing the number of block nonzeros in the various block rows
2412:            in the upper triangular portion of the in diagonal portion of the local
2413:            (possibly different for each block block row) or NULL.
2414:            If you plan to factor the matrix you must leave room for the diagonal entry and
2415:            set its value even if it is zero.
2416: .  o_nz  - number of block nonzeros per block row in the off-diagonal portion of local
2417:            submatrix (same for all local rows).
2418: -  o_nnz - array containing the number of nonzeros in the various block rows of the
2419:            off-diagonal portion of the local submatrix (possibly different for
2420:            each block row) or NULL.

2422:    Output Parameter:
2423: .  A - the matrix

2425:    Options Database Keys:
2426: .   -mat_no_unroll - uses code that does not unroll the loops in the
2427:                      block calculations (much slower)
2428: .   -mat_block_size - size of the blocks to use
2429: .   -mat_mpi - use the parallel matrix data structures even on one processor
2430:                (defaults to using SeqBAIJ format on one processor)

2432:    It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(),
2433:    MatXXXXSetPreallocation() paradgm instead of this routine directly.
2434:    [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation]

2436:    Notes:
2437:    The number of rows and columns must be divisible by blocksize.
2438:    This matrix type does not support complex Hermitian operation.

2440:    The user MUST specify either the local or global matrix dimensions
2441:    (possibly both).

2443:    If PETSC_DECIDE or  PETSC_DETERMINE is used for a particular argument on one processor
2444:    than it must be used on all processors that share the object for that argument.

2446:    If the *_nnz parameter is given then the *_nz parameter is ignored

2448:    Storage Information:
2449:    For a square global matrix we define each processor's diagonal portion
2450:    to be its local rows and the corresponding columns (a square submatrix);
2451:    each processor's off-diagonal portion encompasses the remainder of the
2452:    local matrix (a rectangular submatrix).

2454:    The user can specify preallocated storage for the diagonal part of
2455:    the local submatrix with either d_nz or d_nnz (not both).  Set
2456:    d_nz=PETSC_DEFAULT and d_nnz=NULL for PETSc to control dynamic
2457:    memory allocation.  Likewise, specify preallocated storage for the
2458:    off-diagonal part of the local submatrix with o_nz or o_nnz (not both).

2460:    Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In
2461:    the figure below we depict these three local rows and all columns (0-11).

2463: .vb
2464:            0 1 2 3 4 5 6 7 8 9 10 11
2465:           --------------------------
2466:    row 3  |. . . d d d o o o o  o  o
2467:    row 4  |. . . d d d o o o o  o  o
2468:    row 5  |. . . d d d o o o o  o  o
2469:           --------------------------
2470: .ve

2472:    Thus, any entries in the d locations are stored in the d (diagonal)
2473:    submatrix, and any entries in the o locations are stored in the
2474:    o (off-diagonal) submatrix.  Note that the d matrix is stored in
2475:    MatSeqSBAIJ format and the o submatrix in MATSEQBAIJ format.

2477:    Now d_nz should indicate the number of block nonzeros per row in the upper triangular
2478:    plus the diagonal part of the d matrix,
2479:    and o_nz should indicate the number of block nonzeros per row in the o matrix.
2480:    In general, for PDE problems in which most nonzeros are near the diagonal,
2481:    one expects d_nz >> o_nz.   For large problems you MUST preallocate memory
2482:    or you will get TERRIBLE performance; see the users' manual chapter on
2483:    matrices.

2485:    Level: intermediate

2487: .keywords: matrix, block, aij, compressed row, sparse, parallel

2489: .seealso: MatCreate(), MatCreateSeqSBAIJ(), MatSetValues(), MatCreateBAIJ()
2490: @*/

2492: 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)
2493: {
2495:   PetscMPIInt    size;

2498:   MatCreate(comm,A);
2499:   MatSetSizes(*A,m,n,M,N);
2500:   MPI_Comm_size(comm,&size);
2501:   if (size > 1) {
2502:     MatSetType(*A,MATMPISBAIJ);
2503:     MatMPISBAIJSetPreallocation(*A,bs,d_nz,d_nnz,o_nz,o_nnz);
2504:   } else {
2505:     MatSetType(*A,MATSEQSBAIJ);
2506:     MatSeqSBAIJSetPreallocation(*A,bs,d_nz,d_nnz);
2507:   }
2508:   return(0);
2509: }


2512: static PetscErrorCode MatDuplicate_MPISBAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat)
2513: {
2514:   Mat            mat;
2515:   Mat_MPISBAIJ   *a,*oldmat = (Mat_MPISBAIJ*)matin->data;
2517:   PetscInt       len=0,nt,bs=matin->rmap->bs,mbs=oldmat->mbs;
2518:   PetscScalar    *array;

2521:   *newmat = 0;

2523:   MatCreate(PetscObjectComm((PetscObject)matin),&mat);
2524:   MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);
2525:   MatSetType(mat,((PetscObject)matin)->type_name);
2526:   PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));
2527:   PetscLayoutReference(matin->rmap,&mat->rmap);
2528:   PetscLayoutReference(matin->cmap,&mat->cmap);

2530:   mat->factortype   = matin->factortype;
2531:   mat->preallocated = PETSC_TRUE;
2532:   mat->assembled    = PETSC_TRUE;
2533:   mat->insertmode   = NOT_SET_VALUES;

2535:   a      = (Mat_MPISBAIJ*)mat->data;
2536:   a->bs2 = oldmat->bs2;
2537:   a->mbs = oldmat->mbs;
2538:   a->nbs = oldmat->nbs;
2539:   a->Mbs = oldmat->Mbs;
2540:   a->Nbs = oldmat->Nbs;


2543:   a->size         = oldmat->size;
2544:   a->rank         = oldmat->rank;
2545:   a->donotstash   = oldmat->donotstash;
2546:   a->roworiented  = oldmat->roworiented;
2547:   a->rowindices   = 0;
2548:   a->rowvalues    = 0;
2549:   a->getrowactive = PETSC_FALSE;
2550:   a->barray       = 0;
2551:   a->rstartbs     = oldmat->rstartbs;
2552:   a->rendbs       = oldmat->rendbs;
2553:   a->cstartbs     = oldmat->cstartbs;
2554:   a->cendbs       = oldmat->cendbs;

2556:   /* hash table stuff */
2557:   a->ht           = 0;
2558:   a->hd           = 0;
2559:   a->ht_size      = 0;
2560:   a->ht_flag      = oldmat->ht_flag;
2561:   a->ht_fact      = oldmat->ht_fact;
2562:   a->ht_total_ct  = 0;
2563:   a->ht_insert_ct = 0;

2565:   PetscMemcpy(a->rangebs,oldmat->rangebs,(a->size+2)*sizeof(PetscInt));
2566:   if (oldmat->colmap) {
2567: #if defined(PETSC_USE_CTABLE)
2568:     PetscTableCreateCopy(oldmat->colmap,&a->colmap);
2569: #else
2570:     PetscMalloc1(a->Nbs,&a->colmap);
2571:     PetscLogObjectMemory((PetscObject)mat,(a->Nbs)*sizeof(PetscInt));
2572:     PetscMemcpy(a->colmap,oldmat->colmap,(a->Nbs)*sizeof(PetscInt));
2573: #endif
2574:   } else a->colmap = 0;

2576:   if (oldmat->garray && (len = ((Mat_SeqBAIJ*)(oldmat->B->data))->nbs)) {
2577:     PetscMalloc1(len,&a->garray);
2578:     PetscLogObjectMemory((PetscObject)mat,len*sizeof(PetscInt));
2579:     PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));
2580:   } else a->garray = 0;

2582:   MatStashCreate_Private(PetscObjectComm((PetscObject)matin),matin->rmap->bs,&mat->bstash);
2583:   VecDuplicate(oldmat->lvec,&a->lvec);
2584:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->lvec);
2585:   VecScatterCopy(oldmat->Mvctx,&a->Mvctx);
2586:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->Mvctx);

2588:   VecDuplicate(oldmat->slvec0,&a->slvec0);
2589:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec0);
2590:   VecDuplicate(oldmat->slvec1,&a->slvec1);
2591:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec1);

2593:   VecGetLocalSize(a->slvec1,&nt);
2594:   VecGetArray(a->slvec1,&array);
2595:   VecCreateSeqWithArray(PETSC_COMM_SELF,1,bs*mbs,array,&a->slvec1a);
2596:   VecCreateSeqWithArray(PETSC_COMM_SELF,1,nt-bs*mbs,array+bs*mbs,&a->slvec1b);
2597:   VecRestoreArray(a->slvec1,&array);
2598:   VecGetArray(a->slvec0,&array);
2599:   VecCreateSeqWithArray(PETSC_COMM_SELF,1,nt-bs*mbs,array+bs*mbs,&a->slvec0b);
2600:   VecRestoreArray(a->slvec0,&array);
2601:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec0);
2602:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec1);
2603:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec0b);
2604:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec1a);
2605:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec1b);

2607:   /*  VecScatterCopy(oldmat->sMvctx,&a->sMvctx); - not written yet, replaced by the lazy trick: */
2608:   PetscObjectReference((PetscObject)oldmat->sMvctx);
2609:   a->sMvctx = oldmat->sMvctx;
2610:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->sMvctx);

2612:   MatDuplicate(oldmat->A,cpvalues,&a->A);
2613:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->A);
2614:   MatDuplicate(oldmat->B,cpvalues,&a->B);
2615:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->B);
2616:   PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);
2617:   *newmat = mat;
2618:   return(0);
2619: }

2621: PetscErrorCode MatLoad_MPISBAIJ(Mat newmat,PetscViewer viewer)
2622: {
2624:   PetscInt       i,nz,j,rstart,rend;
2625:   PetscScalar    *vals,*buf;
2626:   MPI_Comm       comm;
2627:   MPI_Status     status;
2628:   PetscMPIInt    rank,size,tag = ((PetscObject)viewer)->tag,*sndcounts = 0,*browners,maxnz,*rowners,mmbs;
2629:   PetscInt       header[4],*rowlengths = 0,M,N,m,*cols,*locrowlens;
2630:   PetscInt       *procsnz = 0,jj,*mycols,*ibuf;
2631:   PetscInt       bs = newmat->rmap->bs,Mbs,mbs,extra_rows;
2632:   PetscInt       *dlens,*odlens,*mask,*masked1,*masked2,rowcount,odcount;
2633:   PetscInt       dcount,kmax,k,nzcount,tmp;
2634:   int            fd;

2637:   /* force binary viewer to load .info file if it has not yet done so */
2638:   PetscViewerSetUp(viewer);
2639:   PetscObjectGetComm((PetscObject)viewer,&comm);
2640:   PetscOptionsBegin(comm,NULL,"Options for loading MPISBAIJ matrix 2","Mat");
2641:   PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);
2642:   PetscOptionsEnd();
2643:   if (bs < 0) bs = 1;

2645:   MPI_Comm_size(comm,&size);
2646:   MPI_Comm_rank(comm,&rank);
2647:   PetscViewerBinaryGetDescriptor(viewer,&fd);
2648:   if (!rank) {
2649:     PetscBinaryRead(fd,(char*)header,4,PETSC_INT);
2650:     if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object");
2651:     if (header[3] < 0) SETERRQ(PetscObjectComm((PetscObject)newmat),PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format, cannot load as MPISBAIJ");
2652:   }

2654:   MPI_Bcast(header+1,3,MPIU_INT,0,comm);
2655:   M    = header[1];
2656:   N    = header[2];

2658:   /* If global sizes are set, check if they are consistent with that given in the file */
2659:   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);
2660:   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);

2662:   if (M != N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Can only do square matrices");

2664:   /*
2665:      This code adds extra rows to make sure the number of rows is
2666:      divisible by the blocksize
2667:   */
2668:   Mbs        = M/bs;
2669:   extra_rows = bs - M + bs*(Mbs);
2670:   if (extra_rows == bs) extra_rows = 0;
2671:   else                  Mbs++;
2672:   if (extra_rows &&!rank) {
2673:     PetscInfo(viewer,"Padding loaded matrix to match blocksize\n");
2674:   }

2676:   /* determine ownership of all rows */
2677:   if (newmat->rmap->n < 0) { /* PETSC_DECIDE */
2678:     mbs = Mbs/size + ((Mbs % size) > rank);
2679:     m   = mbs*bs;
2680:   } else { /* User Set */
2681:     m   = newmat->rmap->n;
2682:     mbs = m/bs;
2683:   }
2684:   PetscMalloc2(size+1,&rowners,size+1,&browners);
2685:   PetscMPIIntCast(mbs,&mmbs);
2686:   MPI_Allgather(&mmbs,1,MPI_INT,rowners+1,1,MPI_INT,comm);
2687:   rowners[0] = 0;
2688:   for (i=2; i<=size; i++) rowners[i] += rowners[i-1];
2689:   for (i=0; i<=size; i++) browners[i] = rowners[i]*bs;
2690:   rstart = rowners[rank];
2691:   rend   = rowners[rank+1];

2693:   /* distribute row lengths to all processors */
2694:   PetscMalloc1((rend-rstart)*bs,&locrowlens);
2695:   if (!rank) {
2696:     PetscMalloc1(M+extra_rows,&rowlengths);
2697:     PetscBinaryRead(fd,rowlengths,M,PETSC_INT);
2698:     for (i=0; i<extra_rows; i++) rowlengths[M+i] = 1;
2699:     PetscMalloc1(size,&sndcounts);
2700:     for (i=0; i<size; i++) sndcounts[i] = browners[i+1] - browners[i];
2701:     MPI_Scatterv(rowlengths,sndcounts,browners,MPIU_INT,locrowlens,(rend-rstart)*bs,MPIU_INT,0,comm);
2702:     PetscFree(sndcounts);
2703:   } else {
2704:     MPI_Scatterv(0,0,0,MPIU_INT,locrowlens,(rend-rstart)*bs,MPIU_INT,0,comm);
2705:   }

2707:   if (!rank) {   /* procs[0] */
2708:     /* calculate the number of nonzeros on each processor */
2709:     PetscMalloc1(size,&procsnz);
2710:     PetscMemzero(procsnz,size*sizeof(PetscInt));
2711:     for (i=0; i<size; i++) {
2712:       for (j=rowners[i]*bs; j< rowners[i+1]*bs; j++) {
2713:         procsnz[i] += rowlengths[j];
2714:       }
2715:     }
2716:     PetscFree(rowlengths);

2718:     /* determine max buffer needed and allocate it */
2719:     maxnz = 0;
2720:     for (i=0; i<size; i++) {
2721:       maxnz = PetscMax(maxnz,procsnz[i]);
2722:     }
2723:     PetscMalloc1(maxnz,&cols);

2725:     /* read in my part of the matrix column indices  */
2726:     nz     = procsnz[0];
2727:     PetscMalloc1(nz,&ibuf);
2728:     mycols = ibuf;
2729:     if (size == 1) nz -= extra_rows;
2730:     PetscBinaryRead(fd,mycols,nz,PETSC_INT);
2731:     if (size == 1) {
2732:       for (i=0; i< extra_rows; i++) mycols[nz+i] = M+i;
2733:     }

2735:     /* read in every ones (except the last) and ship off */
2736:     for (i=1; i<size-1; i++) {
2737:       nz   = procsnz[i];
2738:       PetscBinaryRead(fd,cols,nz,PETSC_INT);
2739:       MPI_Send(cols,nz,MPIU_INT,i,tag,comm);
2740:     }
2741:     /* read in the stuff for the last proc */
2742:     if (size != 1) {
2743:       nz   = procsnz[size-1] - extra_rows;  /* the extra rows are not on the disk */
2744:       PetscBinaryRead(fd,cols,nz,PETSC_INT);
2745:       for (i=0; i<extra_rows; i++) cols[nz+i] = M+i;
2746:       MPI_Send(cols,nz+extra_rows,MPIU_INT,size-1,tag,comm);
2747:     }
2748:     PetscFree(cols);
2749:   } else {  /* procs[i], i>0 */
2750:     /* determine buffer space needed for message */
2751:     nz = 0;
2752:     for (i=0; i<m; i++) nz += locrowlens[i];
2753:     PetscMalloc1(nz,&ibuf);
2754:     mycols = ibuf;
2755:     /* receive message of column indices*/
2756:     MPI_Recv(mycols,nz,MPIU_INT,0,tag,comm,&status);
2757:     MPI_Get_count(&status,MPIU_INT,&maxnz);
2758:     if (maxnz != nz) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file");
2759:   }

2761:   /* loop over local rows, determining number of off diagonal entries */
2762:   PetscMalloc2(rend-rstart,&dlens,rend-rstart,&odlens);
2763:   PetscMalloc3(Mbs,&mask,Mbs,&masked1,Mbs,&masked2);
2764:   PetscMemzero(mask,Mbs*sizeof(PetscInt));
2765:   PetscMemzero(masked1,Mbs*sizeof(PetscInt));
2766:   PetscMemzero(masked2,Mbs*sizeof(PetscInt));
2767:   rowcount = 0;
2768:   nzcount  = 0;
2769:   for (i=0; i<mbs; i++) {
2770:     dcount  = 0;
2771:     odcount = 0;
2772:     for (j=0; j<bs; j++) {
2773:       kmax = locrowlens[rowcount];
2774:       for (k=0; k<kmax; k++) {
2775:         tmp = mycols[nzcount++]/bs; /* block col. index */
2776:         if (!mask[tmp]) {
2777:           mask[tmp] = 1;
2778:           if (tmp < rstart || tmp >= rend) masked2[odcount++] = tmp; /* entry in off-diag portion */
2779:           else masked1[dcount++] = tmp; /* entry in diag portion */
2780:         }
2781:       }
2782:       rowcount++;
2783:     }

2785:     dlens[i]  = dcount;  /* d_nzz[i] */
2786:     odlens[i] = odcount; /* o_nzz[i] */

2788:     /* zero out the mask elements we set */
2789:     for (j=0; j<dcount; j++) mask[masked1[j]] = 0;
2790:     for (j=0; j<odcount; j++) mask[masked2[j]] = 0;
2791:   }
2792:   MatSetSizes(newmat,m,m,M+extra_rows,N+extra_rows);
2793:   MatMPISBAIJSetPreallocation(newmat,bs,0,dlens,0,odlens);
2794:   MatSetOption(newmat,MAT_IGNORE_LOWER_TRIANGULAR,PETSC_TRUE);

2796:   if (!rank) {
2797:     PetscMalloc1(maxnz,&buf);
2798:     /* read in my part of the matrix numerical values  */
2799:     nz     = procsnz[0];
2800:     vals   = buf;
2801:     mycols = ibuf;
2802:     if (size == 1) nz -= extra_rows;
2803:     PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);
2804:     if (size == 1) {
2805:       for (i=0; i< extra_rows; i++) vals[nz+i] = 1.0;
2806:     }

2808:     /* insert into matrix */
2809:     jj = rstart*bs;
2810:     for (i=0; i<m; i++) {
2811:       MatSetValues(newmat,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);
2812:       mycols += locrowlens[i];
2813:       vals   += locrowlens[i];
2814:       jj++;
2815:     }

2817:     /* read in other processors (except the last one) and ship out */
2818:     for (i=1; i<size-1; i++) {
2819:       nz   = procsnz[i];
2820:       vals = buf;
2821:       PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);
2822:       MPI_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newmat)->tag,comm);
2823:     }
2824:     /* the last proc */
2825:     if (size != 1) {
2826:       nz   = procsnz[i] - extra_rows;
2827:       vals = buf;
2828:       PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);
2829:       for (i=0; i<extra_rows; i++) vals[nz+i] = 1.0;
2830:       MPI_Send(vals,nz+extra_rows,MPIU_SCALAR,size-1,((PetscObject)newmat)->tag,comm);
2831:     }
2832:     PetscFree(procsnz);

2834:   } else {
2835:     /* receive numeric values */
2836:     PetscMalloc1(nz,&buf);

2838:     /* receive message of values*/
2839:     vals   = buf;
2840:     mycols = ibuf;
2841:     MPI_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newmat)->tag,comm,&status);
2842:     MPI_Get_count(&status,MPIU_SCALAR,&maxnz);
2843:     if (maxnz != nz) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file");

2845:     /* insert into matrix */
2846:     jj = rstart*bs;
2847:     for (i=0; i<m; i++) {
2848:       MatSetValues_MPISBAIJ(newmat,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);
2849:       mycols += locrowlens[i];
2850:       vals   += locrowlens[i];
2851:       jj++;
2852:     }
2853:   }

2855:   PetscFree(locrowlens);
2856:   PetscFree(buf);
2857:   PetscFree(ibuf);
2858:   PetscFree2(rowners,browners);
2859:   PetscFree2(dlens,odlens);
2860:   PetscFree3(mask,masked1,masked2);
2861:   MatAssemblyBegin(newmat,MAT_FINAL_ASSEMBLY);
2862:   MatAssemblyEnd(newmat,MAT_FINAL_ASSEMBLY);
2863:   return(0);
2864: }

2866: /*XXXXX@
2867:    MatMPISBAIJSetHashTableFactor - Sets the factor required to compute the size of the HashTable.

2869:    Input Parameters:
2870: .  mat  - the matrix
2871: .  fact - factor

2873:    Not Collective on Mat, each process can have a different hash factor

2875:    Level: advanced

2877:   Notes:
2878:    This can also be set by the command line option: -mat_use_hash_table fact

2880: .keywords: matrix, hashtable, factor, HT

2882: .seealso: MatSetOption()
2883: @XXXXX*/


2886: PetscErrorCode MatGetRowMaxAbs_MPISBAIJ(Mat A,Vec v,PetscInt idx[])
2887: {
2888:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;
2889:   Mat_SeqBAIJ    *b = (Mat_SeqBAIJ*)(a->B)->data;
2890:   PetscReal      atmp;
2891:   PetscReal      *work,*svalues,*rvalues;
2893:   PetscInt       i,bs,mbs,*bi,*bj,brow,j,ncols,krow,kcol,col,row,Mbs,bcol;
2894:   PetscMPIInt    rank,size;
2895:   PetscInt       *rowners_bs,dest,count,source;
2896:   PetscScalar    *va;
2897:   MatScalar      *ba;
2898:   MPI_Status     stat;

2901:   if (idx) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Send email to petsc-maint@mcs.anl.gov");
2902:   MatGetRowMaxAbs(a->A,v,NULL);
2903:   VecGetArray(v,&va);

2905:   MPI_Comm_size(PetscObjectComm((PetscObject)A),&size);
2906:   MPI_Comm_rank(PetscObjectComm((PetscObject)A),&rank);

2908:   bs  = A->rmap->bs;
2909:   mbs = a->mbs;
2910:   Mbs = a->Mbs;
2911:   ba  = b->a;
2912:   bi  = b->i;
2913:   bj  = b->j;

2915:   /* find ownerships */
2916:   rowners_bs = A->rmap->range;

2918:   /* each proc creates an array to be distributed */
2919:   PetscMalloc1(bs*Mbs,&work);
2920:   PetscMemzero(work,bs*Mbs*sizeof(PetscReal));

2922:   /* row_max for B */
2923:   if (rank != size-1) {
2924:     for (i=0; i<mbs; i++) {
2925:       ncols = bi[1] - bi[0]; bi++;
2926:       brow  = bs*i;
2927:       for (j=0; j<ncols; j++) {
2928:         bcol = bs*(*bj);
2929:         for (kcol=0; kcol<bs; kcol++) {
2930:           col  = bcol + kcol;                /* local col index */
2931:           col += rowners_bs[rank+1];      /* global col index */
2932:           for (krow=0; krow<bs; krow++) {
2933:             atmp = PetscAbsScalar(*ba); ba++;
2934:             row  = brow + krow;   /* local row index */
2935:             if (PetscRealPart(va[row]) < atmp) va[row] = atmp;
2936:             if (work[col] < atmp) work[col] = atmp;
2937:           }
2938:         }
2939:         bj++;
2940:       }
2941:     }

2943:     /* send values to its owners */
2944:     for (dest=rank+1; dest<size; dest++) {
2945:       svalues = work + rowners_bs[dest];
2946:       count   = rowners_bs[dest+1]-rowners_bs[dest];
2947:       MPI_Send(svalues,count,MPIU_REAL,dest,rank,PetscObjectComm((PetscObject)A));
2948:     }
2949:   }

2951:   /* receive values */
2952:   if (rank) {
2953:     rvalues = work;
2954:     count   = rowners_bs[rank+1]-rowners_bs[rank];
2955:     for (source=0; source<rank; source++) {
2956:       MPI_Recv(rvalues,count,MPIU_REAL,MPI_ANY_SOURCE,MPI_ANY_TAG,PetscObjectComm((PetscObject)A),&stat);
2957:       /* process values */
2958:       for (i=0; i<count; i++) {
2959:         if (PetscRealPart(va[i]) < rvalues[i]) va[i] = rvalues[i];
2960:       }
2961:     }
2962:   }

2964:   VecRestoreArray(v,&va);
2965:   PetscFree(work);
2966:   return(0);
2967: }

2969: PetscErrorCode MatSOR_MPISBAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx)
2970: {
2971:   Mat_MPISBAIJ      *mat = (Mat_MPISBAIJ*)matin->data;
2972:   PetscErrorCode    ierr;
2973:   PetscInt          mbs=mat->mbs,bs=matin->rmap->bs;
2974:   PetscScalar       *x,*ptr,*from;
2975:   Vec               bb1;
2976:   const PetscScalar *b;

2979:   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);
2980:   if (bs > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"SSOR for block size > 1 is not yet implemented");

2982:   if (flag == SOR_APPLY_UPPER) {
2983:     (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
2984:     return(0);
2985:   }

2987:   if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) {
2988:     if (flag & SOR_ZERO_INITIAL_GUESS) {
2989:       (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,lits,xx);
2990:       its--;
2991:     }

2993:     VecDuplicate(bb,&bb1);
2994:     while (its--) {

2996:       /* lower triangular part: slvec0b = - B^T*xx */
2997:       (*mat->B->ops->multtranspose)(mat->B,xx,mat->slvec0b);

2999:       /* copy xx into slvec0a */
3000:       VecGetArray(mat->slvec0,&ptr);
3001:       VecGetArray(xx,&x);
3002:       PetscMemcpy(ptr,x,bs*mbs*sizeof(MatScalar));
3003:       VecRestoreArray(mat->slvec0,&ptr);

3005:       VecScale(mat->slvec0,-1.0);

3007:       /* copy bb into slvec1a */
3008:       VecGetArray(mat->slvec1,&ptr);
3009:       VecGetArrayRead(bb,&b);
3010:       PetscMemcpy(ptr,b,bs*mbs*sizeof(MatScalar));
3011:       VecRestoreArray(mat->slvec1,&ptr);

3013:       /* set slvec1b = 0 */
3014:       VecSet(mat->slvec1b,0.0);

3016:       VecScatterBegin(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);
3017:       VecRestoreArray(xx,&x);
3018:       VecRestoreArrayRead(bb,&b);
3019:       VecScatterEnd(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);

3021:       /* upper triangular part: bb1 = bb1 - B*x */
3022:       (*mat->B->ops->multadd)(mat->B,mat->slvec1b,mat->slvec1a,bb1);

3024:       /* local diagonal sweep */
3025:       (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,lits,xx);
3026:     }
3027:     VecDestroy(&bb1);
3028:   } else if ((flag & SOR_LOCAL_FORWARD_SWEEP) && (its == 1) && (flag & SOR_ZERO_INITIAL_GUESS)) {
3029:     (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
3030:   } else if ((flag & SOR_LOCAL_BACKWARD_SWEEP) && (its == 1) && (flag & SOR_ZERO_INITIAL_GUESS)) {
3031:     (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
3032:   } else if (flag & SOR_EISENSTAT) {
3033:     Vec               xx1;
3034:     PetscBool         hasop;
3035:     const PetscScalar *diag;
3036:     PetscScalar       *sl,scale = (omega - 2.0)/omega;
3037:     PetscInt          i,n;

3039:     if (!mat->xx1) {
3040:       VecDuplicate(bb,&mat->xx1);
3041:       VecDuplicate(bb,&mat->bb1);
3042:     }
3043:     xx1 = mat->xx1;
3044:     bb1 = mat->bb1;

3046:     (*mat->A->ops->sor)(mat->A,bb,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_BACKWARD_SWEEP),fshift,lits,1,xx);

3048:     if (!mat->diag) {
3049:       /* this is wrong for same matrix with new nonzero values */
3050:       MatCreateVecs(matin,&mat->diag,NULL);
3051:       MatGetDiagonal(matin,mat->diag);
3052:     }
3053:     MatHasOperation(matin,MATOP_MULT_DIAGONAL_BLOCK,&hasop);

3055:     if (hasop) {
3056:       MatMultDiagonalBlock(matin,xx,bb1);
3057:       VecAYPX(mat->slvec1a,scale,bb);
3058:     } else {
3059:       /*
3060:           These two lines are replaced by code that may be a bit faster for a good compiler
3061:       VecPointwiseMult(mat->slvec1a,mat->diag,xx);
3062:       VecAYPX(mat->slvec1a,scale,bb);
3063:       */
3064:       VecGetArray(mat->slvec1a,&sl);
3065:       VecGetArrayRead(mat->diag,&diag);
3066:       VecGetArrayRead(bb,&b);
3067:       VecGetArray(xx,&x);
3068:       VecGetLocalSize(xx,&n);
3069:       if (omega == 1.0) {
3070:         for (i=0; i<n; i++) sl[i] = b[i] - diag[i]*x[i];
3071:         PetscLogFlops(2.0*n);
3072:       } else {
3073:         for (i=0; i<n; i++) sl[i] = b[i] + scale*diag[i]*x[i];
3074:         PetscLogFlops(3.0*n);
3075:       }
3076:       VecRestoreArray(mat->slvec1a,&sl);
3077:       VecRestoreArrayRead(mat->diag,&diag);
3078:       VecRestoreArrayRead(bb,&b);
3079:       VecRestoreArray(xx,&x);
3080:     }

3082:     /* multiply off-diagonal portion of matrix */
3083:     VecSet(mat->slvec1b,0.0);
3084:     (*mat->B->ops->multtranspose)(mat->B,xx,mat->slvec0b);
3085:     VecGetArray(mat->slvec0,&from);
3086:     VecGetArray(xx,&x);
3087:     PetscMemcpy(from,x,bs*mbs*sizeof(MatScalar));
3088:     VecRestoreArray(mat->slvec0,&from);
3089:     VecRestoreArray(xx,&x);
3090:     VecScatterBegin(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);
3091:     VecScatterEnd(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);
3092:     (*mat->B->ops->multadd)(mat->B,mat->slvec1b,mat->slvec1a,mat->slvec1a);

3094:     /* local sweep */
3095:     (*mat->A->ops->sor)(mat->A,mat->slvec1a,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_FORWARD_SWEEP),fshift,lits,1,xx1);
3096:     VecAXPY(xx,1.0,xx1);
3097:   } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"MatSORType is not supported for SBAIJ matrix format");
3098:   return(0);
3099: }

3101: PetscErrorCode MatSOR_MPISBAIJ_2comm(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx)
3102: {
3103:   Mat_MPISBAIJ   *mat = (Mat_MPISBAIJ*)matin->data;
3105:   Vec            lvec1,bb1;

3108:   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);
3109:   if (matin->rmap->bs > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"SSOR for block size > 1 is not yet implemented");

3111:   if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) {
3112:     if (flag & SOR_ZERO_INITIAL_GUESS) {
3113:       (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,lits,xx);
3114:       its--;
3115:     }

3117:     VecDuplicate(mat->lvec,&lvec1);
3118:     VecDuplicate(bb,&bb1);
3119:     while (its--) {
3120:       VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);

3122:       /* lower diagonal part: bb1 = bb - B^T*xx */
3123:       (*mat->B->ops->multtranspose)(mat->B,xx,lvec1);
3124:       VecScale(lvec1,-1.0);

3126:       VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
3127:       VecCopy(bb,bb1);
3128:       VecScatterBegin(mat->Mvctx,lvec1,bb1,ADD_VALUES,SCATTER_REVERSE);

3130:       /* upper diagonal part: bb1 = bb1 - B*x */
3131:       VecScale(mat->lvec,-1.0);
3132:       (*mat->B->ops->multadd)(mat->B,mat->lvec,bb1,bb1);

3134:       VecScatterEnd(mat->Mvctx,lvec1,bb1,ADD_VALUES,SCATTER_REVERSE);

3136:       /* diagonal sweep */
3137:       (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,lits,xx);
3138:     }
3139:     VecDestroy(&lvec1);
3140:     VecDestroy(&bb1);
3141:   } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"MatSORType is not supported for SBAIJ matrix format");
3142:   return(0);
3143: }

3145: /*@
3146:      MatCreateMPISBAIJWithArrays - creates a MPI SBAIJ matrix using arrays that contain in standard
3147:          CSR format the local rows.

3149:    Collective on MPI_Comm

3151:    Input Parameters:
3152: +  comm - MPI communicator
3153: .  bs - the block size, only a block size of 1 is supported
3154: .  m - number of local rows (Cannot be PETSC_DECIDE)
3155: .  n - This value should be the same as the local size used in creating the
3156:        x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have
3157:        calculated if N is given) For square matrices n is almost always m.
3158: .  M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
3159: .  N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
3160: .   i - row indices
3161: .   j - column indices
3162: -   a - matrix values

3164:    Output Parameter:
3165: .   mat - the matrix

3167:    Level: intermediate

3169:    Notes:
3170:        The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc;
3171:      thus you CANNOT change the matrix entries by changing the values of a[] after you have
3172:      called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays.

3174:        The i and j indices are 0 based, and i indices are indices corresponding to the local j array.

3176: .keywords: matrix, aij, compressed row, sparse, parallel

3178: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(),
3179:           MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays()
3180: @*/
3181: 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)
3182: {


3187:   if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0");
3188:   if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative");
3189:   MatCreate(comm,mat);
3190:   MatSetSizes(*mat,m,n,M,N);
3191:   MatSetType(*mat,MATMPISBAIJ);
3192:   MatMPISBAIJSetPreallocationCSR(*mat,bs,i,j,a);
3193:   return(0);
3194: }


3197: /*@C
3198:    MatMPISBAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in BAIJ format
3199:    (the default parallel PETSc format).

3201:    Collective on MPI_Comm

3203:    Input Parameters:
3204: +  B - the matrix
3205: .  bs - the block size
3206: .  i - the indices into j for the start of each local row (starts with zero)
3207: .  j - the column indices for each local row (starts with zero) these must be sorted for each row
3208: -  v - optional values in the matrix

3210:    Level: developer

3212: .keywords: matrix, aij, compressed row, sparse, parallel

3214: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIBAIJSetPreallocation(), MatCreateAIJ(), MPIAIJ
3215: @*/
3216: PetscErrorCode  MatMPISBAIJSetPreallocationCSR(Mat B,PetscInt bs,const PetscInt i[],const PetscInt j[], const PetscScalar v[])
3217: {

3221:   PetscTryMethod(B,"MatMPISBAIJSetPreallocationCSR_C",(Mat,PetscInt,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,bs,i,j,v));
3222:   return(0);
3223: }

3225: PetscErrorCode MatCreateMPIMatConcatenateSeqMat_MPISBAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat)
3226: {
3228:   PetscInt       m,N,i,rstart,nnz,Ii,bs,cbs;
3229:   PetscInt       *indx;
3230:   PetscScalar    *values;

3233:   MatGetSize(inmat,&m,&N);
3234:   if (scall == MAT_INITIAL_MATRIX) { /* symbolic phase */
3235:     Mat_SeqSBAIJ   *a = (Mat_SeqSBAIJ*)inmat->data;
3236:     PetscInt       *dnz,*onz,sum,bs,cbs,mbs,Nbs;
3237:     PetscInt       *bindx,rmax=a->rmax,j;
3238: 
3239:     MatGetBlockSizes(inmat,&bs,&cbs);
3240:     mbs = m/bs; Nbs = N/cbs;
3241:     if (n == PETSC_DECIDE) {
3242:       PetscSplitOwnership(comm,&n,&Nbs);
3243:     }
3244:     /* Check sum(n) = Nbs */
3245:     MPIU_Allreduce(&n,&sum,1,MPIU_INT,MPI_SUM,comm);
3246:     if (sum != Nbs) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Sum of local columns != global columns %d",Nbs);

3248:     MPI_Scan(&mbs, &rstart,1,MPIU_INT,MPI_SUM,comm);
3249:     rstart -= mbs;

3251:     PetscMalloc1(rmax,&bindx);
3252:     MatPreallocateInitialize(comm,mbs,n,dnz,onz);
3253:     MatSetOption(inmat,MAT_GETROW_UPPERTRIANGULAR,PETSC_TRUE);
3254:     for (i=0; i<mbs; i++) {
3255:       MatGetRow_SeqSBAIJ(inmat,i*bs,&nnz,&indx,NULL); /* non-blocked nnz and indx */
3256:       nnz = nnz/bs;
3257:       for (j=0; j<nnz; j++) bindx[j] = indx[j*bs]/bs;
3258:       MatPreallocateSet(i+rstart,nnz,bindx,dnz,onz);
3259:       MatRestoreRow_SeqSBAIJ(inmat,i*bs,&nnz,&indx,NULL);
3260:     }
3261:     MatSetOption(inmat,MAT_GETROW_UPPERTRIANGULAR,PETSC_FALSE);
3262:     PetscFree(bindx);

3264:     MatCreate(comm,outmat);
3265:     MatSetSizes(*outmat,m,n*bs,PETSC_DETERMINE,PETSC_DETERMINE);
3266:     MatSetBlockSizes(*outmat,bs,cbs);
3267:     MatSetType(*outmat,MATMPISBAIJ);
3268:     MatMPISBAIJSetPreallocation(*outmat,bs,0,dnz,0,onz);
3269:     MatPreallocateFinalize(dnz,onz);
3270:   }
3271: 
3272:   /* numeric phase */
3273:   MatGetBlockSizes(inmat,&bs,&cbs);
3274:   MatGetOwnershipRange(*outmat,&rstart,NULL);

3276:   MatSetOption(inmat,MAT_GETROW_UPPERTRIANGULAR,PETSC_TRUE);
3277:   for (i=0; i<m; i++) {
3278:     MatGetRow_SeqSBAIJ(inmat,i,&nnz,&indx,&values);
3279:     Ii   = i + rstart;
3280:     MatSetValues(*outmat,1,&Ii,nnz,indx,values,INSERT_VALUES);
3281:     MatRestoreRow_SeqSBAIJ(inmat,i,&nnz,&indx,&values);
3282:   }
3283:   MatSetOption(inmat,MAT_GETROW_UPPERTRIANGULAR,PETSC_FALSE);
3284:   MatAssemblyBegin(*outmat,MAT_FINAL_ASSEMBLY);
3285:   MatAssemblyEnd(*outmat,MAT_FINAL_ASSEMBLY);
3286:   return(0);
3287: }