Actual source code: mpisbaij.c

petsc-3.7.4 2016-10-02
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  2: #include <../src/mat/impls/baij/mpi/mpibaij.h>    /*I "petscmat.h" I*/
  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
 12: PetscErrorCode  MatStoreValues_MPISBAIJ(Mat mat)
 13: {
 14:   Mat_MPISBAIJ   *aij = (Mat_MPISBAIJ*)mat->data;

 18:   MatStoreValues(aij->A);
 19:   MatStoreValues(aij->B);
 20:   return(0);
 21: }

 25: PetscErrorCode  MatRetrieveValues_MPISBAIJ(Mat mat)
 26: {
 27:   Mat_MPISBAIJ   *aij = (Mat_MPISBAIJ*)mat->data;

 31:   MatRetrieveValues(aij->A);
 32:   MatRetrieveValues(aij->B);
 33:   return(0);
 34: }

 36: #define  MatSetValues_SeqSBAIJ_A_Private(row,col,value,addv,orow,ocol)      \
 37:   { \
 38:  \
 39:     brow = row/bs;  \
 40:     rp   = aj + ai[brow]; ap = aa + bs2*ai[brow]; \
 41:     rmax = aimax[brow]; nrow = ailen[brow]; \
 42:     bcol = col/bs; \
 43:     ridx = row % bs; cidx = col % bs; \
 44:     low  = 0; high = nrow; \
 45:     while (high-low > 3) { \
 46:       t = (low+high)/2; \
 47:       if (rp[t] > bcol) high = t; \
 48:       else              low  = t; \
 49:     } \
 50:     for (_i=low; _i<high; _i++) { \
 51:       if (rp[_i] > bcol) break; \
 52:       if (rp[_i] == bcol) { \
 53:         bap = ap + bs2*_i + bs*cidx + ridx; \
 54:         if (addv == ADD_VALUES) *bap += value;  \
 55:         else                    *bap  = value;  \
 56:         goto a_noinsert; \
 57:       } \
 58:     } \
 59:     if (a->nonew == 1) goto a_noinsert; \
 60:     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); \
 61:     MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,brow,bcol,rmax,aa,ai,aj,rp,ap,aimax,a->nonew,MatScalar); \
 62:     N = nrow++ - 1;  \
 63:     /* shift up all the later entries in this row */ \
 64:     for (ii=N; ii>=_i; ii--) { \
 65:       rp[ii+1] = rp[ii]; \
 66:       PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar)); \
 67:     } \
 68:     if (N>=_i) { PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar)); }  \
 69:     rp[_i]                      = bcol;  \
 70:     ap[bs2*_i + bs*cidx + ridx] = value;  \
 71:     A->nonzerostate++;\
 72: a_noinsert:; \
 73:     ailen[brow] = nrow; \
 74:   }

 76: #define  MatSetValues_SeqSBAIJ_B_Private(row,col,value,addv,orow,ocol) \
 77:   { \
 78:     brow = row/bs;  \
 79:     rp   = bj + bi[brow]; ap = ba + bs2*bi[brow]; \
 80:     rmax = bimax[brow]; nrow = bilen[brow]; \
 81:     bcol = col/bs; \
 82:     ridx = row % bs; cidx = col % bs; \
 83:     low  = 0; high = nrow; \
 84:     while (high-low > 3) { \
 85:       t = (low+high)/2; \
 86:       if (rp[t] > bcol) high = t; \
 87:       else              low  = t; \
 88:     } \
 89:     for (_i=low; _i<high; _i++) { \
 90:       if (rp[_i] > bcol) break; \
 91:       if (rp[_i] == bcol) { \
 92:         bap = ap + bs2*_i + bs*cidx + ridx; \
 93:         if (addv == ADD_VALUES) *bap += value;  \
 94:         else                    *bap  = value;  \
 95:         goto b_noinsert; \
 96:       } \
 97:     } \
 98:     if (b->nonew == 1) goto b_noinsert; \
 99:     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); \
100:     MatSeqXAIJReallocateAIJ(B,b->mbs,bs2,nrow,brow,bcol,rmax,ba,bi,bj,rp,ap,bimax,b->nonew,MatScalar); \
101:     N = nrow++ - 1;  \
102:     /* shift up all the later entries in this row */ \
103:     for (ii=N; ii>=_i; ii--) { \
104:       rp[ii+1] = rp[ii]; \
105:       PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar)); \
106:     } \
107:     if (N>=_i) { PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar));}  \
108:     rp[_i]                      = bcol;  \
109:     ap[bs2*_i + bs*cidx + ridx] = value;  \
110:     B->nonzerostate++;\
111: b_noinsert:; \
112:     bilen[brow] = nrow; \
113:   }

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

131:   /* Some Variables required in the macro */
132:   Mat          A     = baij->A;
133:   Mat_SeqSBAIJ *a    = (Mat_SeqSBAIJ*)(A)->data;
134:   PetscInt     *aimax=a->imax,*ai=a->i,*ailen=a->ilen,*aj=a->j;
135:   MatScalar    *aa   =a->a;

137:   Mat         B     = baij->B;
138:   Mat_SeqBAIJ *b    = (Mat_SeqBAIJ*)(B)->data;
139:   PetscInt    *bimax=b->imax,*bi=b->i,*bilen=b->ilen,*bj=b->j;
140:   MatScalar   *ba   =b->a;

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

146:   /* for stash */
147:   PetscInt  n_loc, *in_loc = NULL;
148:   MatScalar *v_loc = NULL;

151:   if (!baij->donotstash) {
152:     if (n > baij->n_loc) {
153:       PetscFree(baij->in_loc);
154:       PetscFree(baij->v_loc);
155:       PetscMalloc1(n,&baij->in_loc);
156:       PetscMalloc1(n,&baij->v_loc);

158:       baij->n_loc = n;
159:     }
160:     in_loc = baij->in_loc;
161:     v_loc  = baij->v_loc;
162:   }

164:   for (i=0; i<m; i++) {
165:     if (im[i] < 0) continue;
166: #if defined(PETSC_USE_DEBUG)
167:     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);
168: #endif
169:     if (im[i] >= rstart_orig && im[i] < rend_orig) { /* this processor entry */
170:       row = im[i] - rstart_orig;              /* local row index */
171:       for (j=0; j<n; j++) {
172:         if (im[i]/bs > in[j]/bs) {
173:           if (a->ignore_ltriangular) {
174:             continue;    /* ignore lower triangular blocks */
175:           } 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)");
176:         }
177:         if (in[j] >= cstart_orig && in[j] < cend_orig) {  /* diag entry (A) */
178:           col  = in[j] - cstart_orig;         /* local col index */
179:           brow = row/bs; bcol = col/bs;
180:           if (brow > bcol) continue;  /* ignore lower triangular blocks of A */
181:           if (roworiented) value = v[i*n+j];
182:           else             value = v[i+j*m];
183:           MatSetValues_SeqSBAIJ_A_Private(row,col,value,addv,im[i],in[j]);
184:           /* MatSetValues_SeqBAIJ(baij->A,1,&row,1,&col,&value,addv); */
185:         } else if (in[j] < 0) continue;
186: #if defined(PETSC_USE_DEBUG)
187:         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);
188: #endif
189:         else {  /* off-diag entry (B) */
190:           if (mat->was_assembled) {
191:             if (!baij->colmap) {
192:               MatCreateColmap_MPIBAIJ_Private(mat);
193:             }
194: #if defined(PETSC_USE_CTABLE)
195:             PetscTableFind(baij->colmap,in[j]/bs + 1,&col);
196:             col  = col - 1;
197: #else
198:             col = baij->colmap[in[j]/bs] - 1;
199: #endif
200:             if (col < 0 && !((Mat_SeqSBAIJ*)(baij->A->data))->nonew) {
201:               MatDisAssemble_MPISBAIJ(mat);
202:               col  =  in[j];
203:               /* Reinitialize the variables required by MatSetValues_SeqBAIJ_B_Private() */
204:               B    = baij->B;
205:               b    = (Mat_SeqBAIJ*)(B)->data;
206:               bimax= b->imax;bi=b->i;bilen=b->ilen;bj=b->j;
207:               ba   = b->a;
208:             } else col += in[j]%bs;
209:           } else col = in[j];
210:           if (roworiented) value = v[i*n+j];
211:           else             value = v[i+j*m];
212:           MatSetValues_SeqSBAIJ_B_Private(row,col,value,addv,im[i],in[j]);
213:           /* MatSetValues_SeqBAIJ(baij->B,1,&row,1,&col,&value,addv); */
214:         }
215:       }
216:     } else {  /* off processor entry */
217:       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]);
218:       if (!baij->donotstash) {
219:         mat->assembled = PETSC_FALSE;
220:         n_loc          = 0;
221:         for (j=0; j<n; j++) {
222:           if (im[i]/bs > in[j]/bs) continue; /* ignore lower triangular blocks */
223:           in_loc[n_loc] = in[j];
224:           if (roworiented) {
225:             v_loc[n_loc] = v[i*n+j];
226:           } else {
227:             v_loc[n_loc] = v[j*m+i];
228:           }
229:           n_loc++;
230:         }
231:         MatStashValuesRow_Private(&mat->stash,im[i],n_loc,in_loc,v_loc,PETSC_FALSE);
232:       }
233:     }
234:   }
235:   return(0);
236: }

240: PETSC_STATIC_INLINE PetscErrorCode MatSetValuesBlocked_SeqSBAIJ_Inlined(Mat A,PetscInt row,PetscInt col,const PetscScalar v[],InsertMode is,PetscInt orow,PetscInt ocol)
241: {
242:   Mat_SeqSBAIJ      *a = (Mat_SeqSBAIJ*)A->data;
243:   PetscErrorCode    ierr;
244:   PetscInt          *rp,low,high,t,ii,jj,nrow,i,rmax,N;
245:   PetscInt          *imax      =a->imax,*ai=a->i,*ailen=a->ilen;
246:   PetscInt          *aj        =a->j,nonew=a->nonew,bs2=a->bs2,bs=A->rmap->bs;
247:   PetscBool         roworiented=a->roworiented;
248:   const PetscScalar *value     = v;
249:   MatScalar         *ap,*aa = a->a,*bap;

252:   if (col < row) {
253:     if (a->ignore_ltriangular) return(0); /* ignore lower triangular block */
254:     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)");
255:   }
256:   rp   = aj + ai[row];
257:   ap   = aa + bs2*ai[row];
258:   rmax = imax[row];
259:   nrow = ailen[row];
260:   value = v;
261:   low   = 0;
262:   high  = nrow;

264:   while (high-low > 7) {
265:     t = (low+high)/2;
266:     if (rp[t] > col) high = t;
267:     else             low  = t;
268:   }
269:   for (i=low; i<high; i++) {
270:     if (rp[i] > col) break;
271:     if (rp[i] == col) {
272:       bap = ap +  bs2*i;
273:       if (roworiented) {
274:         if (is == ADD_VALUES) {
275:           for (ii=0; ii<bs; ii++) {
276:             for (jj=ii; jj<bs2; jj+=bs) {
277:               bap[jj] += *value++;
278:             }
279:           }
280:         } else {
281:           for (ii=0; ii<bs; ii++) {
282:             for (jj=ii; jj<bs2; jj+=bs) {
283:               bap[jj] = *value++;
284:             }
285:           }
286:         }
287:       } else {
288:         if (is == ADD_VALUES) {
289:           for (ii=0; ii<bs; ii++) {
290:             for (jj=0; jj<bs; jj++) {
291:               *bap++ += *value++;
292:             }
293:           }
294:         } else {
295:           for (ii=0; ii<bs; ii++) {
296:             for (jj=0; jj<bs; jj++) {
297:               *bap++  = *value++;
298:             }
299:           }
300:         }
301:       }
302:       goto noinsert2;
303:     }
304:   }
305:   if (nonew == 1) goto noinsert2;
306:   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);
307:   MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,row,col,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar);
308:   N = nrow++ - 1; high++;
309:   /* shift up all the later entries in this row */
310:   for (ii=N; ii>=i; ii--) {
311:     rp[ii+1] = rp[ii];
312:     PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));
313:   }
314:   if (N >= i) {
315:     PetscMemzero(ap+bs2*i,bs2*sizeof(MatScalar));
316:   }
317:   rp[i] = col;
318:   bap   = ap +  bs2*i;
319:   if (roworiented) {
320:     for (ii=0; ii<bs; ii++) {
321:       for (jj=ii; jj<bs2; jj+=bs) {
322:         bap[jj] = *value++;
323:       }
324:     }
325:   } else {
326:     for (ii=0; ii<bs; ii++) {
327:       for (jj=0; jj<bs; jj++) {
328:         *bap++ = *value++;
329:       }
330:     }
331:   }
332:   noinsert2:;
333:   ailen[row] = nrow;
334:   return(0);
335: }

339: /*
340:    This routine is exactly duplicated in mpibaij.c
341: */
342: PETSC_STATIC_INLINE PetscErrorCode MatSetValuesBlocked_SeqBAIJ_Inlined(Mat A,PetscInt row,PetscInt col,const PetscScalar v[],InsertMode is,PetscInt orow,PetscInt ocol)
343: {
344:   Mat_SeqBAIJ       *a = (Mat_SeqBAIJ*)A->data;
345:   PetscInt          *rp,low,high,t,ii,jj,nrow,i,rmax,N;
346:   PetscInt          *imax=a->imax,*ai=a->i,*ailen=a->ilen;
347:   PetscErrorCode    ierr;
348:   PetscInt          *aj        =a->j,nonew=a->nonew,bs2=a->bs2,bs=A->rmap->bs;
349:   PetscBool         roworiented=a->roworiented;
350:   const PetscScalar *value     = v;
351:   MatScalar         *ap,*aa = a->a,*bap;

354:   rp   = aj + ai[row];
355:   ap   = aa + bs2*ai[row];
356:   rmax = imax[row];
357:   nrow = ailen[row];
358:   low  = 0;
359:   high = nrow;
360:   value = v;
361:   while (high-low > 7) {
362:     t = (low+high)/2;
363:     if (rp[t] > col) high = t;
364:     else             low  = t;
365:   }
366:   for (i=low; i<high; i++) {
367:     if (rp[i] > col) break;
368:     if (rp[i] == col) {
369:       bap = ap +  bs2*i;
370:       if (roworiented) {
371:         if (is == ADD_VALUES) {
372:           for (ii=0; ii<bs; ii++) {
373:             for (jj=ii; jj<bs2; jj+=bs) {
374:               bap[jj] += *value++;
375:             }
376:           }
377:         } else {
378:           for (ii=0; ii<bs; ii++) {
379:             for (jj=ii; jj<bs2; jj+=bs) {
380:               bap[jj] = *value++;
381:             }
382:           }
383:         }
384:       } else {
385:         if (is == ADD_VALUES) {
386:           for (ii=0; ii<bs; ii++,value+=bs) {
387:             for (jj=0; jj<bs; jj++) {
388:               bap[jj] += value[jj];
389:             }
390:             bap += bs;
391:           }
392:         } else {
393:           for (ii=0; ii<bs; ii++,value+=bs) {
394:             for (jj=0; jj<bs; jj++) {
395:               bap[jj]  = value[jj];
396:             }
397:             bap += bs;
398:           }
399:         }
400:       }
401:       goto noinsert2;
402:     }
403:   }
404:   if (nonew == 1) goto noinsert2;
405:   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);
406:   MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,row,col,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar);
407:   N = nrow++ - 1; high++;
408:   /* shift up all the later entries in this row */
409:   for (ii=N; ii>=i; ii--) {
410:     rp[ii+1] = rp[ii];
411:     PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));
412:   }
413:   if (N >= i) {
414:     PetscMemzero(ap+bs2*i,bs2*sizeof(MatScalar));
415:   }
416:   rp[i] = col;
417:   bap   = ap +  bs2*i;
418:   if (roworiented) {
419:     for (ii=0; ii<bs; ii++) {
420:       for (jj=ii; jj<bs2; jj+=bs) {
421:         bap[jj] = *value++;
422:       }
423:     }
424:   } else {
425:     for (ii=0; ii<bs; ii++) {
426:       for (jj=0; jj<bs; jj++) {
427:         *bap++ = *value++;
428:       }
429:     }
430:   }
431:   noinsert2:;
432:   ailen[row] = nrow;
433:   return(0);
434: }

438: /*
439:     This routine could be optimized by removing the need for the block copy below and passing stride information
440:   to the above inline routines; similarly in MatSetValuesBlocked_MPIBAIJ()
441: */
442: PetscErrorCode MatSetValuesBlocked_MPISBAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const MatScalar v[],InsertMode addv)
443: {
444:   Mat_MPISBAIJ    *baij = (Mat_MPISBAIJ*)mat->data;
445:   const MatScalar *value;
446:   MatScalar       *barray     =baij->barray;
447:   PetscBool       roworiented = baij->roworiented,ignore_ltriangular = ((Mat_SeqSBAIJ*)baij->A->data)->ignore_ltriangular;
448:   PetscErrorCode  ierr;
449:   PetscInt        i,j,ii,jj,row,col,rstart=baij->rstartbs;
450:   PetscInt        rend=baij->rendbs,cstart=baij->rstartbs,stepval;
451:   PetscInt        cend=baij->rendbs,bs=mat->rmap->bs,bs2=baij->bs2;

454:   if (!barray) {
455:     PetscMalloc1(bs2,&barray);
456:     baij->barray = barray;
457:   }

459:   if (roworiented) {
460:     stepval = (n-1)*bs;
461:   } else {
462:     stepval = (m-1)*bs;
463:   }
464:   for (i=0; i<m; i++) {
465:     if (im[i] < 0) continue;
466: #if defined(PETSC_USE_DEBUG)
467:     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);
468: #endif
469:     if (im[i] >= rstart && im[i] < rend) {
470:       row = im[i] - rstart;
471:       for (j=0; j<n; j++) {
472:         if (im[i] > in[j]) {
473:           if (ignore_ltriangular) continue; /* ignore lower triangular blocks */
474:           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)");
475:         }
476:         /* If NumCol = 1 then a copy is not required */
477:         if ((roworiented) && (n == 1)) {
478:           barray = (MatScalar*) v + i*bs2;
479:         } else if ((!roworiented) && (m == 1)) {
480:           barray = (MatScalar*) v + j*bs2;
481:         } else { /* Here a copy is required */
482:           if (roworiented) {
483:             value = v + i*(stepval+bs)*bs + j*bs;
484:           } else {
485:             value = v + j*(stepval+bs)*bs + i*bs;
486:           }
487:           for (ii=0; ii<bs; ii++,value+=stepval) {
488:             for (jj=0; jj<bs; jj++) {
489:               *barray++ = *value++;
490:             }
491:           }
492:           barray -=bs2;
493:         }

495:         if (in[j] >= cstart && in[j] < cend) {
496:           col  = in[j] - cstart;
497:           MatSetValuesBlocked_SeqSBAIJ_Inlined(baij->A,row,col,barray,addv,im[i],in[j]);
498:         } else if (in[j] < 0) continue;
499: #if defined(PETSC_USE_DEBUG)
500:         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);
501: #endif
502:         else {
503:           if (mat->was_assembled) {
504:             if (!baij->colmap) {
505:               MatCreateColmap_MPIBAIJ_Private(mat);
506:             }

508: #if defined(PETSC_USE_DEBUG)
509: #if defined(PETSC_USE_CTABLE)
510:             { PetscInt data;
511:               PetscTableFind(baij->colmap,in[j]+1,&data);
512:               if ((data - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap");
513:             }
514: #else
515:             if ((baij->colmap[in[j]] - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap");
516: #endif
517: #endif
518: #if defined(PETSC_USE_CTABLE)
519:             PetscTableFind(baij->colmap,in[j]+1,&col);
520:             col  = (col - 1)/bs;
521: #else
522:             col = (baij->colmap[in[j]] - 1)/bs;
523: #endif
524:             if (col < 0 && !((Mat_SeqBAIJ*)(baij->A->data))->nonew) {
525:               MatDisAssemble_MPISBAIJ(mat);
526:               col  = in[j];
527:             }
528:           } else col = in[j];
529:           MatSetValuesBlocked_SeqBAIJ_Inlined(baij->B,row,col,barray,addv,im[i],in[j]);
530:         }
531:       }
532:     } else {
533:       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]);
534:       if (!baij->donotstash) {
535:         if (roworiented) {
536:           MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);
537:         } else {
538:           MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);
539:         }
540:       }
541:     }
542:   }
543:   return(0);
544: }

548: PetscErrorCode MatGetValues_MPISBAIJ(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[])
549: {
550:   Mat_MPISBAIJ   *baij = (Mat_MPISBAIJ*)mat->data;
552:   PetscInt       bs       = mat->rmap->bs,i,j,bsrstart = mat->rmap->rstart,bsrend = mat->rmap->rend;
553:   PetscInt       bscstart = mat->cmap->rstart,bscend = mat->cmap->rend,row,col,data;

556:   for (i=0; i<m; i++) {
557:     if (idxm[i] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",idxm[i]); */
558:     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);
559:     if (idxm[i] >= bsrstart && idxm[i] < bsrend) {
560:       row = idxm[i] - bsrstart;
561:       for (j=0; j<n; j++) {
562:         if (idxn[j] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column %D",idxn[j]); */
563:         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);
564:         if (idxn[j] >= bscstart && idxn[j] < bscend) {
565:           col  = idxn[j] - bscstart;
566:           MatGetValues_SeqSBAIJ(baij->A,1,&row,1,&col,v+i*n+j);
567:         } else {
568:           if (!baij->colmap) {
569:             MatCreateColmap_MPIBAIJ_Private(mat);
570:           }
571: #if defined(PETSC_USE_CTABLE)
572:           PetscTableFind(baij->colmap,idxn[j]/bs+1,&data);
573:           data--;
574: #else
575:           data = baij->colmap[idxn[j]/bs]-1;
576: #endif
577:           if ((data < 0) || (baij->garray[data/bs] != idxn[j]/bs)) *(v+i*n+j) = 0.0;
578:           else {
579:             col  = data + idxn[j]%bs;
580:             MatGetValues_SeqBAIJ(baij->B,1,&row,1,&col,v+i*n+j);
581:           }
582:         }
583:       }
584:     } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local values currently supported");
585:   }
586:   return(0);
587: }

591: PetscErrorCode MatNorm_MPISBAIJ(Mat mat,NormType type,PetscReal *norm)
592: {
593:   Mat_MPISBAIJ   *baij = (Mat_MPISBAIJ*)mat->data;
595:   PetscReal      sum[2],*lnorm2;

598:   if (baij->size == 1) {
599:      MatNorm(baij->A,type,norm);
600:   } else {
601:     if (type == NORM_FROBENIUS) {
602:       PetscMalloc1(2,&lnorm2);
603:        MatNorm(baij->A,type,lnorm2);
604:       *lnorm2 = (*lnorm2)*(*lnorm2); lnorm2++;            /* squar power of norm(A) */
605:        MatNorm(baij->B,type,lnorm2);
606:       *lnorm2 = (*lnorm2)*(*lnorm2); lnorm2--;             /* squar power of norm(B) */
607:       MPIU_Allreduce(lnorm2,sum,2,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));
608:       *norm   = PetscSqrtReal(sum[0] + 2*sum[1]);
609:       PetscFree(lnorm2);
610:     } else if (type == NORM_INFINITY || type == NORM_1) { /* max row/column sum */
611:       Mat_SeqSBAIJ *amat=(Mat_SeqSBAIJ*)baij->A->data;
612:       Mat_SeqBAIJ  *bmat=(Mat_SeqBAIJ*)baij->B->data;
613:       PetscReal    *rsum,*rsum2,vabs;
614:       PetscInt     *jj,*garray=baij->garray,rstart=baij->rstartbs,nz;
615:       PetscInt     brow,bcol,col,bs=baij->A->rmap->bs,row,grow,gcol,mbs=amat->mbs;
616:       MatScalar    *v;

618:       PetscMalloc2(mat->cmap->N,&rsum,mat->cmap->N,&rsum2);
619:       PetscMemzero(rsum,mat->cmap->N*sizeof(PetscReal));
620:       /* Amat */
621:       v = amat->a; jj = amat->j;
622:       for (brow=0; brow<mbs; brow++) {
623:         grow = bs*(rstart + brow);
624:         nz   = amat->i[brow+1] - amat->i[brow];
625:         for (bcol=0; bcol<nz; bcol++) {
626:           gcol = bs*(rstart + *jj); jj++;
627:           for (col=0; col<bs; col++) {
628:             for (row=0; row<bs; row++) {
629:               vabs            = PetscAbsScalar(*v); v++;
630:               rsum[gcol+col] += vabs;
631:               /* non-diagonal block */
632:               if (bcol > 0 && vabs > 0.0) rsum[grow+row] += vabs;
633:             }
634:           }
635:         }
636:         PetscLogFlops(nz*bs*bs);
637:       }
638:       /* Bmat */
639:       v = bmat->a; jj = bmat->j;
640:       for (brow=0; brow<mbs; brow++) {
641:         grow = bs*(rstart + brow);
642:         nz = bmat->i[brow+1] - bmat->i[brow];
643:         for (bcol=0; bcol<nz; bcol++) {
644:           gcol = bs*garray[*jj]; jj++;
645:           for (col=0; col<bs; col++) {
646:             for (row=0; row<bs; row++) {
647:               vabs            = PetscAbsScalar(*v); v++;
648:               rsum[gcol+col] += vabs;
649:               rsum[grow+row] += vabs;
650:             }
651:           }
652:         }
653:         PetscLogFlops(nz*bs*bs);
654:       }
655:       MPIU_Allreduce(rsum,rsum2,mat->cmap->N,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));
656:       *norm = 0.0;
657:       for (col=0; col<mat->cmap->N; col++) {
658:         if (rsum2[col] > *norm) *norm = rsum2[col];
659:       }
660:       PetscFree2(rsum,rsum2);
661:     } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support for this norm yet");
662:   }
663:   return(0);
664: }

668: PetscErrorCode MatAssemblyBegin_MPISBAIJ(Mat mat,MatAssemblyType mode)
669: {
670:   Mat_MPISBAIJ   *baij = (Mat_MPISBAIJ*)mat->data;
672:   PetscInt       nstash,reallocs;

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

677:   MatStashScatterBegin_Private(mat,&mat->stash,mat->rmap->range);
678:   MatStashScatterBegin_Private(mat,&mat->bstash,baij->rangebs);
679:   MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);
680:   PetscInfo2(mat,"Stash has %D entries,uses %D mallocs.\n",nstash,reallocs);
681:   MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);
682:   PetscInfo2(mat,"Block-Stash has %D entries, uses %D mallocs.\n",nstash,reallocs);
683:   return(0);
684: }

688: PetscErrorCode MatAssemblyEnd_MPISBAIJ(Mat mat,MatAssemblyType mode)
689: {
690:   Mat_MPISBAIJ   *baij=(Mat_MPISBAIJ*)mat->data;
691:   Mat_SeqSBAIJ   *a   =(Mat_SeqSBAIJ*)baij->A->data;
693:   PetscInt       i,j,rstart,ncols,flg,bs2=baij->bs2;
694:   PetscInt       *row,*col;
695:   PetscBool      other_disassembled;
696:   PetscMPIInt    n;
697:   PetscBool      r1,r2,r3;
698:   MatScalar      *val;

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

707:       for (i=0; i<n;) {
708:         /* Now identify the consecutive vals belonging to the same row */
709:         for (j=i,rstart=row[j]; j<n; j++) {
710:           if (row[j] != rstart) break;
711:         }
712:         if (j < n) ncols = j-i;
713:         else       ncols = n-i;
714:         /* Now assemble all these values with a single function call */
715:         MatSetValues_MPISBAIJ(mat,1,row+i,ncols,col+i,val+i,mat->insertmode);
716:         i    = j;
717:       }
718:     }
719:     MatStashScatterEnd_Private(&mat->stash);
720:     /* Now process the block-stash. Since the values are stashed column-oriented,
721:        set the roworiented flag to column oriented, and after MatSetValues()
722:        restore the original flags */
723:     r1 = baij->roworiented;
724:     r2 = a->roworiented;
725:     r3 = ((Mat_SeqBAIJ*)baij->B->data)->roworiented;

727:     baij->roworiented = PETSC_FALSE;
728:     a->roworiented    = PETSC_FALSE;

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

735:       for (i=0; i<n;) {
736:         /* Now identify the consecutive vals belonging to the same row */
737:         for (j=i,rstart=row[j]; j<n; j++) {
738:           if (row[j] != rstart) break;
739:         }
740:         if (j < n) ncols = j-i;
741:         else       ncols = n-i;
742:         MatSetValuesBlocked_MPISBAIJ(mat,1,row+i,ncols,col+i,val+i*bs2,mat->insertmode);
743:         i    = j;
744:       }
745:     }
746:     MatStashScatterEnd_Private(&mat->bstash);

748:     baij->roworiented = r1;
749:     a->roworiented    = r2;

751:     ((Mat_SeqBAIJ*)baij->B->data)->roworiented = r3; /* b->roworinted */
752:   }

754:   MatAssemblyBegin(baij->A,mode);
755:   MatAssemblyEnd(baij->A,mode);

757:   /* determine if any processor has disassembled, if so we must
758:      also disassemble ourselfs, in order that we may reassemble. */
759:   /*
760:      if nonzero structure of submatrix B cannot change then we know that
761:      no processor disassembled thus we can skip this stuff
762:   */
763:   if (!((Mat_SeqBAIJ*)baij->B->data)->nonew) {
764:     MPIU_Allreduce(&mat->was_assembled,&other_disassembled,1,MPIU_BOOL,MPI_PROD,PetscObjectComm((PetscObject)mat));
765:     if (mat->was_assembled && !other_disassembled) {
766:       MatDisAssemble_MPISBAIJ(mat);
767:     }
768:   }

770:   if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) {
771:     MatSetUpMultiply_MPISBAIJ(mat); /* setup Mvctx and sMvctx */
772:   }
773:   MatAssemblyBegin(baij->B,mode);
774:   MatAssemblyEnd(baij->B,mode);

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

778:   baij->rowvalues = 0;

780:   /* if no new nonzero locations are allowed in matrix then only set the matrix state the first time through */
781:   if ((!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) || !((Mat_SeqBAIJ*)(baij->A->data))->nonew) {
782:     PetscObjectState state = baij->A->nonzerostate + baij->B->nonzerostate;
783:     MPIU_Allreduce(&state,&mat->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)mat));
784:   }
785:   return(0);
786: }

788: extern PetscErrorCode MatView_SeqSBAIJ(Mat,PetscViewer);
789: extern PetscErrorCode MatSetValues_MPIBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const PetscScalar[],InsertMode);
790: #include <petscdraw.h>
793: static PetscErrorCode MatView_MPISBAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer)
794: {
795:   Mat_MPISBAIJ      *baij = (Mat_MPISBAIJ*)mat->data;
796:   PetscErrorCode    ierr;
797:   PetscInt          bs   = mat->rmap->bs;
798:   PetscMPIInt       rank = baij->rank;
799:   PetscBool         iascii,isdraw;
800:   PetscViewer       sviewer;
801:   PetscViewerFormat format;

804:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
805:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);
806:   if (iascii) {
807:     PetscViewerGetFormat(viewer,&format);
808:     if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) {
809:       MatInfo info;
810:       MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);
811:       MatGetInfo(mat,MAT_LOCAL,&info);
812:       PetscViewerASCIIPushSynchronized(viewer);
813:       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);
814:       MatGetInfo(baij->A,MAT_LOCAL,&info);
815:       PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);
816:       MatGetInfo(baij->B,MAT_LOCAL,&info);
817:       PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);
818:       PetscViewerFlush(viewer);
819:       PetscViewerASCIIPopSynchronized(viewer);
820:       PetscViewerASCIIPrintf(viewer,"Information on VecScatter used in matrix-vector product: \n");
821:       VecScatterView(baij->Mvctx,viewer);
822:       return(0);
823:     } else if (format == PETSC_VIEWER_ASCII_INFO) {
824:       PetscViewerASCIIPrintf(viewer,"  block size is %D\n",bs);
825:       return(0);
826:     } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) {
827:       return(0);
828:     }
829:   }

831:   if (isdraw) {
832:     PetscDraw draw;
833:     PetscBool isnull;
834:     PetscViewerDrawGetDraw(viewer,0,&draw);
835:     PetscDrawIsNull(draw,&isnull);
836:     if (isnull) return(0);
837:   }

839:   {
840:     /* assemble the entire matrix onto first processor. */
841:     Mat          A;
842:     Mat_SeqSBAIJ *Aloc;
843:     Mat_SeqBAIJ  *Bloc;
844:     PetscInt     M = mat->rmap->N,N = mat->cmap->N,*ai,*aj,col,i,j,k,*rvals,mbs = baij->mbs;
845:     MatScalar    *a;
846:     const char   *matname;

848:     /* Should this be the same type as mat? */
849:     MatCreate(PetscObjectComm((PetscObject)mat),&A);
850:     if (!rank) {
851:       MatSetSizes(A,M,N,M,N);
852:     } else {
853:       MatSetSizes(A,0,0,M,N);
854:     }
855:     MatSetType(A,MATMPISBAIJ);
856:     MatMPISBAIJSetPreallocation(A,mat->rmap->bs,0,NULL,0,NULL);
857:     MatSetOption(A,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_FALSE);
858:     PetscLogObjectParent((PetscObject)mat,(PetscObject)A);

860:     /* copy over the A part */
861:     Aloc = (Mat_SeqSBAIJ*)baij->A->data;
862:     ai   = Aloc->i; aj = Aloc->j; a = Aloc->a;
863:     PetscMalloc1(bs,&rvals);

865:     for (i=0; i<mbs; i++) {
866:       rvals[0] = bs*(baij->rstartbs + i);
867:       for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1;
868:       for (j=ai[i]; j<ai[i+1]; j++) {
869:         col = (baij->cstartbs+aj[j])*bs;
870:         for (k=0; k<bs; k++) {
871:           MatSetValues_MPISBAIJ(A,bs,rvals,1,&col,a,INSERT_VALUES);
872:           col++;
873:           a += bs;
874:         }
875:       }
876:     }
877:     /* copy over the B part */
878:     Bloc = (Mat_SeqBAIJ*)baij->B->data;
879:     ai   = Bloc->i; aj = Bloc->j; a = Bloc->a;
880:     for (i=0; i<mbs; i++) {

882:       rvals[0] = bs*(baij->rstartbs + i);
883:       for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1;
884:       for (j=ai[i]; j<ai[i+1]; j++) {
885:         col = baij->garray[aj[j]]*bs;
886:         for (k=0; k<bs; k++) {
887:           MatSetValues_MPIBAIJ(A,bs,rvals,1,&col,a,INSERT_VALUES);
888:           col++;
889:           a += bs;
890:         }
891:       }
892:     }
893:     PetscFree(rvals);
894:     MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);
895:     MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);
896:     /*
897:        Everyone has to call to draw the matrix since the graphics waits are
898:        synchronized across all processors that share the PetscDraw object
899:     */
900:     PetscViewerGetSubViewer(viewer,PETSC_COMM_SELF,&sviewer);
901:     PetscObjectGetName((PetscObject)mat,&matname);
902:     if (!rank) {
903:       PetscObjectSetName((PetscObject)((Mat_MPISBAIJ*)(A->data))->A,matname);
904:       MatView_SeqSBAIJ(((Mat_MPISBAIJ*)(A->data))->A,sviewer);
905:     }
906:     PetscViewerRestoreSubViewer(viewer,PETSC_COMM_SELF,&sviewer);
907:     PetscViewerFlush(viewer);
908:     MatDestroy(&A);
909:   }
910:   return(0);
911: }

915: static PetscErrorCode MatView_MPISBAIJ_Binary(Mat mat,PetscViewer viewer)
916: {
917:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)mat->data;
918:   Mat_SeqSBAIJ   *A = (Mat_SeqSBAIJ*)a->A->data;
919:   Mat_SeqBAIJ    *B = (Mat_SeqBAIJ*)a->B->data;
921:   PetscInt       i,*row_lens,*crow_lens,bs = mat->rmap->bs,j,k,bs2=a->bs2,header[4],nz,rlen;
922:   PetscInt       *range=0,nzmax,*column_indices,cnt,col,*garray = a->garray,cstart = mat->cmap->rstart/bs,len,pcnt,l,ll;
923:   int            fd;
924:   PetscScalar    *column_values;
925:   FILE           *file;
926:   PetscMPIInt    rank,size,tag = ((PetscObject)viewer)->tag;
927:   PetscInt       message_count,flowcontrolcount;

930:   MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);
931:   MPI_Comm_size(PetscObjectComm((PetscObject)mat),&size);
932:   nz   = bs2*(A->nz + B->nz);
933:   rlen = mat->rmap->n;
934:   PetscViewerBinaryGetDescriptor(viewer,&fd);
935:   if (!rank) {
936:     header[0] = MAT_FILE_CLASSID;
937:     header[1] = mat->rmap->N;
938:     header[2] = mat->cmap->N;

940:     MPI_Reduce(&nz,&header[3],1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));
941:     PetscBinaryWrite(fd,header,4,PETSC_INT,PETSC_TRUE);
942:     /* get largest number of rows any processor has */
943:     range = mat->rmap->range;
944:     for (i=1; i<size; i++) {
945:       rlen = PetscMax(rlen,range[i+1] - range[i]);
946:     }
947:   } else {
948:     MPI_Reduce(&nz,0,1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));
949:   }

951:   PetscMalloc1(rlen/bs,&crow_lens);
952:   /* compute lengths of each row  */
953:   for (i=0; i<a->mbs; i++) {
954:     crow_lens[i] = A->i[i+1] - A->i[i] + B->i[i+1] - B->i[i];
955:   }
956:   /* store the row lengths to the file */
957:   PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);
958:   if (!rank) {
959:     MPI_Status status;
960:     PetscMalloc1(rlen,&row_lens);
961:     rlen = (range[1] - range[0])/bs;
962:     for (i=0; i<rlen; i++) {
963:       for (j=0; j<bs; j++) {
964:         row_lens[i*bs+j] = bs*crow_lens[i];
965:       }
966:     }
967:     PetscBinaryWrite(fd,row_lens,bs*rlen,PETSC_INT,PETSC_TRUE);
968:     for (i=1; i<size; i++) {
969:       rlen = (range[i+1] - range[i])/bs;
970:       PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);
971:       MPI_Recv(crow_lens,rlen,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);
972:       for (k=0; k<rlen; k++) {
973:         for (j=0; j<bs; j++) {
974:           row_lens[k*bs+j] = bs*crow_lens[k];
975:         }
976:       }
977:       PetscBinaryWrite(fd,row_lens,bs*rlen,PETSC_INT,PETSC_TRUE);
978:     }
979:     PetscViewerFlowControlEndMaster(viewer,&message_count);
980:     PetscFree(row_lens);
981:   } else {
982:     PetscViewerFlowControlStepWorker(viewer,rank,&message_count);
983:     MPI_Send(crow_lens,mat->rmap->n/bs,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));
984:     PetscViewerFlowControlEndWorker(viewer,&message_count);
985:   }
986:   PetscFree(crow_lens);

988:   /* load up the local column indices. Include for all rows not just one for each block row since process 0 does not have the
989:      information needed to make it for each row from a block row. This does require more communication but still not more than
990:      the communication needed for the nonzero values  */
991:   nzmax = nz; /*  space a largest processor needs */
992:   MPI_Reduce(&nz,&nzmax,1,MPIU_INT,MPI_MAX,0,PetscObjectComm((PetscObject)mat));
993:   PetscMalloc1(nzmax,&column_indices);
994:   cnt   = 0;
995:   for (i=0; i<a->mbs; i++) {
996:     pcnt = cnt;
997:     for (j=B->i[i]; j<B->i[i+1]; j++) {
998:       if ((col = garray[B->j[j]]) > cstart) break;
999:       for (l=0; l<bs; l++) {
1000:         column_indices[cnt++] = bs*col+l;
1001:       }
1002:     }
1003:     for (k=A->i[i]; k<A->i[i+1]; k++) {
1004:       for (l=0; l<bs; l++) {
1005:         column_indices[cnt++] = bs*(A->j[k] + cstart)+l;
1006:       }
1007:     }
1008:     for (; j<B->i[i+1]; j++) {
1009:       for (l=0; l<bs; l++) {
1010:         column_indices[cnt++] = bs*garray[B->j[j]]+l;
1011:       }
1012:     }
1013:     len = cnt - pcnt;
1014:     for (k=1; k<bs; k++) {
1015:       PetscMemcpy(&column_indices[cnt],&column_indices[pcnt],len*sizeof(PetscInt));
1016:       cnt += len;
1017:     }
1018:   }
1019:   if (cnt != nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: cnt = %D nz = %D",cnt,nz);

1021:   /* store the columns to the file */
1022:   PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);
1023:   if (!rank) {
1024:     MPI_Status status;
1025:     PetscBinaryWrite(fd,column_indices,nz,PETSC_INT,PETSC_TRUE);
1026:     for (i=1; i<size; i++) {
1027:       PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);
1028:       MPI_Recv(&cnt,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);
1029:       MPI_Recv(column_indices,cnt,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);
1030:       PetscBinaryWrite(fd,column_indices,cnt,PETSC_INT,PETSC_TRUE);
1031:     }
1032:     PetscViewerFlowControlEndMaster(viewer,&message_count);
1033:   } else {
1034:     PetscViewerFlowControlStepWorker(viewer,rank,&message_count);
1035:     MPI_Send(&cnt,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));
1036:     MPI_Send(column_indices,cnt,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));
1037:     PetscViewerFlowControlEndWorker(viewer,&message_count);
1038:   }
1039:   PetscFree(column_indices);

1041:   /* load up the numerical values */
1042:   PetscMalloc1(nzmax,&column_values);
1043:   cnt  = 0;
1044:   for (i=0; i<a->mbs; i++) {
1045:     rlen = bs*(B->i[i+1] - B->i[i] + A->i[i+1] - A->i[i]);
1046:     for (j=B->i[i]; j<B->i[i+1]; j++) {
1047:       if (garray[B->j[j]] > cstart) break;
1048:       for (l=0; l<bs; l++) {
1049:         for (ll=0; ll<bs; ll++) {
1050:           column_values[cnt + l*rlen + ll] = B->a[bs2*j+l+bs*ll];
1051:         }
1052:       }
1053:       cnt += bs;
1054:     }
1055:     for (k=A->i[i]; k<A->i[i+1]; k++) {
1056:       for (l=0; l<bs; l++) {
1057:         for (ll=0; ll<bs; ll++) {
1058:           column_values[cnt + l*rlen + ll] = A->a[bs2*k+l+bs*ll];
1059:         }
1060:       }
1061:       cnt += bs;
1062:     }
1063:     for (; j<B->i[i+1]; j++) {
1064:       for (l=0; l<bs; l++) {
1065:         for (ll=0; ll<bs; ll++) {
1066:           column_values[cnt + l*rlen + ll] = B->a[bs2*j+l+bs*ll];
1067:         }
1068:       }
1069:       cnt += bs;
1070:     }
1071:     cnt += (bs-1)*rlen;
1072:   }
1073:   if (cnt != nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Internal PETSc error: cnt = %D nz = %D",cnt,nz);

1075:   /* store the column values to the file */
1076:   PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);
1077:   if (!rank) {
1078:     MPI_Status status;
1079:     PetscBinaryWrite(fd,column_values,nz,PETSC_SCALAR,PETSC_TRUE);
1080:     for (i=1; i<size; i++) {
1081:       PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);
1082:       MPI_Recv(&cnt,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);
1083:       MPI_Recv(column_values,cnt,MPIU_SCALAR,i,tag,PetscObjectComm((PetscObject)mat),&status);
1084:       PetscBinaryWrite(fd,column_values,cnt,PETSC_SCALAR,PETSC_TRUE);
1085:     }
1086:     PetscViewerFlowControlEndMaster(viewer,&message_count);
1087:   } else {
1088:     PetscViewerFlowControlStepWorker(viewer,rank,&message_count);
1089:     MPI_Send(&nz,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));
1090:     MPI_Send(column_values,nz,MPIU_SCALAR,0,tag,PetscObjectComm((PetscObject)mat));
1091:     PetscViewerFlowControlEndWorker(viewer,&message_count);
1092:   }
1093:   PetscFree(column_values);

1095:   PetscViewerBinaryGetInfoPointer(viewer,&file);
1096:   if (file) {
1097:     fprintf(file,"-matload_block_size %d\n",(int)mat->rmap->bs);
1098:   }
1099:   return(0);
1100: }

1104: PetscErrorCode MatView_MPISBAIJ(Mat mat,PetscViewer viewer)
1105: {
1107:   PetscBool      iascii,isdraw,issocket,isbinary;

1110:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
1111:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);
1112:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSOCKET,&issocket);
1113:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);
1114:   if (iascii || isdraw || issocket) {
1115:     MatView_MPISBAIJ_ASCIIorDraworSocket(mat,viewer);
1116:   } else if (isbinary) {
1117:     MatView_MPISBAIJ_Binary(mat,viewer);
1118:   }
1119:   return(0);
1120: }

1124: PetscErrorCode MatDestroy_MPISBAIJ(Mat mat)
1125: {
1126:   Mat_MPISBAIJ   *baij = (Mat_MPISBAIJ*)mat->data;

1130: #if defined(PETSC_USE_LOG)
1131:   PetscLogObjectState((PetscObject)mat,"Rows=%D,Cols=%D",mat->rmap->N,mat->cmap->N);
1132: #endif
1133:   MatStashDestroy_Private(&mat->stash);
1134:   MatStashDestroy_Private(&mat->bstash);
1135:   MatDestroy(&baij->A);
1136:   MatDestroy(&baij->B);
1137: #if defined(PETSC_USE_CTABLE)
1138:   PetscTableDestroy(&baij->colmap);
1139: #else
1140:   PetscFree(baij->colmap);
1141: #endif
1142:   PetscFree(baij->garray);
1143:   VecDestroy(&baij->lvec);
1144:   VecScatterDestroy(&baij->Mvctx);
1145:   VecDestroy(&baij->slvec0);
1146:   VecDestroy(&baij->slvec0b);
1147:   VecDestroy(&baij->slvec1);
1148:   VecDestroy(&baij->slvec1a);
1149:   VecDestroy(&baij->slvec1b);
1150:   VecScatterDestroy(&baij->sMvctx);
1151:   PetscFree2(baij->rowvalues,baij->rowindices);
1152:   PetscFree(baij->barray);
1153:   PetscFree(baij->hd);
1154:   VecDestroy(&baij->diag);
1155:   VecDestroy(&baij->bb1);
1156:   VecDestroy(&baij->xx1);
1157: #if defined(PETSC_USE_REAL_MAT_SINGLE)
1158:   PetscFree(baij->setvaluescopy);
1159: #endif
1160:   PetscFree(baij->in_loc);
1161:   PetscFree(baij->v_loc);
1162:   PetscFree(baij->rangebs);
1163:   PetscFree(mat->data);

1165:   PetscObjectChangeTypeName((PetscObject)mat,0);
1166:   PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C",NULL);
1167:   PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C",NULL);
1168:   PetscObjectComposeFunction((PetscObject)mat,"MatGetDiagonalBlock_C",NULL);
1169:   PetscObjectComposeFunction((PetscObject)mat,"MatMPISBAIJSetPreallocation_C",NULL);
1170:   PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpisbaij_mpisbstrm_C",NULL);
1171: #if defined(PETSC_HAVE_ELEMENTAL)
1172:   PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpisbaij_elemental_C",NULL);
1173: #endif
1174:   return(0);
1175: }

1179: PetscErrorCode MatMult_MPISBAIJ_Hermitian(Mat A,Vec xx,Vec yy)
1180: {
1181:   Mat_MPISBAIJ      *a = (Mat_MPISBAIJ*)A->data;
1182:   PetscErrorCode    ierr;
1183:   PetscInt          nt,mbs=a->mbs,bs=A->rmap->bs;
1184:   PetscScalar       *from;
1185:   const PetscScalar *x;

1188:   VecGetLocalSize(xx,&nt);
1189:   if (nt != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx");

1191:   /* diagonal part */
1192:   (*a->A->ops->mult)(a->A,xx,a->slvec1a);
1193:   VecSet(a->slvec1b,0.0);

1195:   /* subdiagonal part */
1196:   (*a->B->ops->multhermitiantranspose)(a->B,xx,a->slvec0b);

1198:   /* copy x into the vec slvec0 */
1199:   VecGetArray(a->slvec0,&from);
1200:   VecGetArrayRead(xx,&x);

1202:   PetscMemcpy(from,x,bs*mbs*sizeof(MatScalar));
1203:   VecRestoreArray(a->slvec0,&from);
1204:   VecRestoreArrayRead(xx,&x);

1206:   VecScatterBegin(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);
1207:   VecScatterEnd(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);
1208:   /* supperdiagonal part */
1209:   (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,yy);
1210:   return(0);
1211: }

1215: PetscErrorCode MatMult_MPISBAIJ(Mat A,Vec xx,Vec yy)
1216: {
1217:   Mat_MPISBAIJ      *a = (Mat_MPISBAIJ*)A->data;
1218:   PetscErrorCode    ierr;
1219:   PetscInt          nt,mbs=a->mbs,bs=A->rmap->bs;
1220:   PetscScalar       *from;
1221:   const PetscScalar *x;

1224:   VecGetLocalSize(xx,&nt);
1225:   if (nt != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx");

1227:   /* diagonal part */
1228:   (*a->A->ops->mult)(a->A,xx,a->slvec1a);
1229:   VecSet(a->slvec1b,0.0);

1231:   /* subdiagonal part */
1232:   (*a->B->ops->multtranspose)(a->B,xx,a->slvec0b);

1234:   /* copy x into the vec slvec0 */
1235:   VecGetArray(a->slvec0,&from);
1236:   VecGetArrayRead(xx,&x);

1238:   PetscMemcpy(from,x,bs*mbs*sizeof(MatScalar));
1239:   VecRestoreArray(a->slvec0,&from);
1240:   VecRestoreArrayRead(xx,&x);

1242:   VecScatterBegin(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);
1243:   VecScatterEnd(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);
1244:   /* supperdiagonal part */
1245:   (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,yy);
1246:   return(0);
1247: }

1251: PetscErrorCode MatMult_MPISBAIJ_2comm(Mat A,Vec xx,Vec yy)
1252: {
1253:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;
1255:   PetscInt       nt;

1258:   VecGetLocalSize(xx,&nt);
1259:   if (nt != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx");

1261:   VecGetLocalSize(yy,&nt);
1262:   if (nt != A->rmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible parition of A and yy");

1264:   VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
1265:   /* do diagonal part */
1266:   (*a->A->ops->mult)(a->A,xx,yy);
1267:   /* do supperdiagonal part */
1268:   VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
1269:   (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);
1270:   /* do subdiagonal part */
1271:   (*a->B->ops->multtranspose)(a->B,xx,a->lvec);
1272:   VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
1273:   VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
1274:   return(0);
1275: }

1279: PetscErrorCode MatMultAdd_MPISBAIJ(Mat A,Vec xx,Vec yy,Vec zz)
1280: {
1281:   Mat_MPISBAIJ      *a = (Mat_MPISBAIJ*)A->data;
1282:   PetscErrorCode    ierr;
1283:   PetscInt          mbs=a->mbs,bs=A->rmap->bs;
1284:   PetscScalar       *from,zero=0.0;
1285:   const PetscScalar *x;

1288:   /*
1289:   PetscSynchronizedPrintf(PetscObjectComm((PetscObject)A)," MatMultAdd is called ...\n");
1290:   PetscSynchronizedFlush(PetscObjectComm((PetscObject)A),PETSC_STDOUT);
1291:   */
1292:   /* diagonal part */
1293:   (*a->A->ops->multadd)(a->A,xx,yy,a->slvec1a);
1294:   VecSet(a->slvec1b,zero);

1296:   /* subdiagonal part */
1297:   (*a->B->ops->multtranspose)(a->B,xx,a->slvec0b);

1299:   /* copy x into the vec slvec0 */
1300:   VecGetArray(a->slvec0,&from);
1301:   VecGetArrayRead(xx,&x);
1302:   PetscMemcpy(from,x,bs*mbs*sizeof(MatScalar));
1303:   VecRestoreArray(a->slvec0,&from);

1305:   VecScatterBegin(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);
1306:   VecRestoreArrayRead(xx,&x);
1307:   VecScatterEnd(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);

1309:   /* supperdiagonal part */
1310:   (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,zz);
1311:   return(0);
1312: }

1316: PetscErrorCode MatMultAdd_MPISBAIJ_2comm(Mat A,Vec xx,Vec yy,Vec zz)
1317: {
1318:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;

1322:   VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
1323:   /* do diagonal part */
1324:   (*a->A->ops->multadd)(a->A,xx,yy,zz);
1325:   /* do supperdiagonal part */
1326:   VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
1327:   (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);

1329:   /* do subdiagonal part */
1330:   (*a->B->ops->multtranspose)(a->B,xx,a->lvec);
1331:   VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);
1332:   VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);
1333:   return(0);
1334: }

1336: /*
1337:   This only works correctly for square matrices where the subblock A->A is the
1338:    diagonal block
1339: */
1342: PetscErrorCode MatGetDiagonal_MPISBAIJ(Mat A,Vec v)
1343: {
1344:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;

1348:   /* if (a->rmap->N != a->cmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block"); */
1349:   MatGetDiagonal(a->A,v);
1350:   return(0);
1351: }

1355: PetscErrorCode MatScale_MPISBAIJ(Mat A,PetscScalar aa)
1356: {
1357:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;

1361:   MatScale(a->A,aa);
1362:   MatScale(a->B,aa);
1363:   return(0);
1364: }

1368: PetscErrorCode MatGetRow_MPISBAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
1369: {
1370:   Mat_MPISBAIJ   *mat = (Mat_MPISBAIJ*)matin->data;
1371:   PetscScalar    *vworkA,*vworkB,**pvA,**pvB,*v_p;
1373:   PetscInt       bs = matin->rmap->bs,bs2 = mat->bs2,i,*cworkA,*cworkB,**pcA,**pcB;
1374:   PetscInt       nztot,nzA,nzB,lrow,brstart = matin->rmap->rstart,brend = matin->rmap->rend;
1375:   PetscInt       *cmap,*idx_p,cstart = mat->rstartbs;

1378:   if (mat->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Already active");
1379:   mat->getrowactive = PETSC_TRUE;

1381:   if (!mat->rowvalues && (idx || v)) {
1382:     /*
1383:         allocate enough space to hold information from the longest row.
1384:     */
1385:     Mat_SeqSBAIJ *Aa = (Mat_SeqSBAIJ*)mat->A->data;
1386:     Mat_SeqBAIJ  *Ba = (Mat_SeqBAIJ*)mat->B->data;
1387:     PetscInt     max = 1,mbs = mat->mbs,tmp;
1388:     for (i=0; i<mbs; i++) {
1389:       tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; /* row length */
1390:       if (max < tmp) max = tmp;
1391:     }
1392:     PetscMalloc2(max*bs2,&mat->rowvalues,max*bs2,&mat->rowindices);
1393:   }

1395:   if (row < brstart || row >= brend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local rows");
1396:   lrow = row - brstart;  /* local row index */

1398:   pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB;
1399:   if (!v)   {pvA = 0; pvB = 0;}
1400:   if (!idx) {pcA = 0; if (!v) pcB = 0;}
1401:   (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);
1402:   (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);
1403:   nztot = nzA + nzB;

1405:   cmap = mat->garray;
1406:   if (v  || idx) {
1407:     if (nztot) {
1408:       /* Sort by increasing column numbers, assuming A and B already sorted */
1409:       PetscInt imark = -1;
1410:       if (v) {
1411:         *v = v_p = mat->rowvalues;
1412:         for (i=0; i<nzB; i++) {
1413:           if (cmap[cworkB[i]/bs] < cstart) v_p[i] = vworkB[i];
1414:           else break;
1415:         }
1416:         imark = i;
1417:         for (i=0; i<nzA; i++)     v_p[imark+i] = vworkA[i];
1418:         for (i=imark; i<nzB; i++) v_p[nzA+i]   = vworkB[i];
1419:       }
1420:       if (idx) {
1421:         *idx = idx_p = mat->rowindices;
1422:         if (imark > -1) {
1423:           for (i=0; i<imark; i++) {
1424:             idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs;
1425:           }
1426:         } else {
1427:           for (i=0; i<nzB; i++) {
1428:             if (cmap[cworkB[i]/bs] < cstart) idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs;
1429:             else break;
1430:           }
1431:           imark = i;
1432:         }
1433:         for (i=0; i<nzA; i++)     idx_p[imark+i] = cstart*bs + cworkA[i];
1434:         for (i=imark; i<nzB; i++) idx_p[nzA+i]   = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ;
1435:       }
1436:     } else {
1437:       if (idx) *idx = 0;
1438:       if (v)   *v   = 0;
1439:     }
1440:   }
1441:   *nz  = nztot;
1442:   (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);
1443:   (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);
1444:   return(0);
1445: }

1449: PetscErrorCode MatRestoreRow_MPISBAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
1450: {
1451:   Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data;

1454:   if (!baij->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"MatGetRow() must be called first");
1455:   baij->getrowactive = PETSC_FALSE;
1456:   return(0);
1457: }

1461: PetscErrorCode MatGetRowUpperTriangular_MPISBAIJ(Mat A)
1462: {
1463:   Mat_MPISBAIJ *a  = (Mat_MPISBAIJ*)A->data;
1464:   Mat_SeqSBAIJ *aA = (Mat_SeqSBAIJ*)a->A->data;

1467:   aA->getrow_utriangular = PETSC_TRUE;
1468:   return(0);
1469: }
1472: PetscErrorCode MatRestoreRowUpperTriangular_MPISBAIJ(Mat A)
1473: {
1474:   Mat_MPISBAIJ *a  = (Mat_MPISBAIJ*)A->data;
1475:   Mat_SeqSBAIJ *aA = (Mat_SeqSBAIJ*)a->A->data;

1478:   aA->getrow_utriangular = PETSC_FALSE;
1479:   return(0);
1480: }

1484: PetscErrorCode MatRealPart_MPISBAIJ(Mat A)
1485: {
1486:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;

1490:   MatRealPart(a->A);
1491:   MatRealPart(a->B);
1492:   return(0);
1493: }

1497: PetscErrorCode MatImaginaryPart_MPISBAIJ(Mat A)
1498: {
1499:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;

1503:   MatImaginaryPart(a->A);
1504:   MatImaginaryPart(a->B);
1505:   return(0);
1506: }

1508: /* Check if isrow is a subset of iscol_local, called by MatGetSubMatrix_MPISBAIJ()
1509:    Input: isrow       - distributed(parallel), 
1510:           iscol_local - locally owned (seq) 
1511: */
1514: PetscErrorCode ISEqual_private(IS isrow,IS iscol_local,PetscBool  *flg)
1515: {
1517:   PetscInt       sz1,sz2,*a1,*a2,i,j,k,nmatch;
1518:   const PetscInt *ptr1,*ptr2;

1521:   ISGetLocalSize(isrow,&sz1);
1522:   ISGetLocalSize(iscol_local,&sz2);
1523:   if (sz1 > sz2) {
1524:     *flg = PETSC_FALSE;
1525:     return(0);
1526:   }

1528:   ISGetIndices(isrow,&ptr1);
1529:   ISGetIndices(iscol_local,&ptr2);

1531:   PetscMalloc1(sz1,&a1);
1532:   PetscMalloc1(sz2,&a2);
1533:   PetscMemcpy(a1,ptr1,sz1*sizeof(PetscInt));
1534:   PetscMemcpy(a2,ptr2,sz2*sizeof(PetscInt));
1535:   PetscSortInt(sz1,a1);
1536:   PetscSortInt(sz2,a2);

1538:   nmatch=0;
1539:   k     = 0;
1540:   for (i=0; i<sz1; i++){
1541:     for (j=k; j<sz2; j++){
1542:       if (a1[i] == a2[j]) {
1543:         k = j; nmatch++;
1544:         break;
1545:       }
1546:     }
1547:   }
1548:   ISRestoreIndices(isrow,&ptr1);
1549:   ISRestoreIndices(iscol_local,&ptr2);
1550:   PetscFree(a1);
1551:   PetscFree(a2);
1552:   if (nmatch < sz1) {
1553:     *flg = PETSC_FALSE;
1554:   } else {
1555:     *flg = PETSC_TRUE;
1556:   }
1557:   return(0);
1558: }

1562: PetscErrorCode MatGetSubMatrix_MPISBAIJ(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat)
1563: {
1565:   IS             iscol_local;
1566:   PetscInt       csize;
1567:   PetscBool      isequal;

1570:   ISGetLocalSize(iscol,&csize);
1571:   if (call == MAT_REUSE_MATRIX) {
1572:     PetscObjectQuery((PetscObject)*newmat,"ISAllGather",(PetscObject*)&iscol_local);
1573:     if (!iscol_local) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse");
1574:   } else {
1575:     ISAllGather(iscol,&iscol_local);
1576:     ISEqual_private(isrow,iscol_local,&isequal);
1577:     if (!isequal) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"For symmetric format, iscol must equal isrow");
1578:   }

1580:   /* now call MatGetSubMatrix_MPIBAIJ() */
1581:   MatGetSubMatrix_MPIBAIJ_Private(mat,isrow,iscol_local,csize,call,newmat);
1582:   if (call == MAT_INITIAL_MATRIX) {
1583:     PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);
1584:     ISDestroy(&iscol_local);
1585:   }
1586:   return(0);
1587: }

1591: PetscErrorCode MatZeroEntries_MPISBAIJ(Mat A)
1592: {
1593:   Mat_MPISBAIJ   *l = (Mat_MPISBAIJ*)A->data;

1597:   MatZeroEntries(l->A);
1598:   MatZeroEntries(l->B);
1599:   return(0);
1600: }

1604: PetscErrorCode MatGetInfo_MPISBAIJ(Mat matin,MatInfoType flag,MatInfo *info)
1605: {
1606:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)matin->data;
1607:   Mat            A  = a->A,B = a->B;
1609:   PetscReal      isend[5],irecv[5];

1612:   info->block_size = (PetscReal)matin->rmap->bs;

1614:   MatGetInfo(A,MAT_LOCAL,info);

1616:   isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded;
1617:   isend[3] = info->memory;  isend[4] = info->mallocs;

1619:   MatGetInfo(B,MAT_LOCAL,info);

1621:   isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded;
1622:   isend[3] += info->memory;  isend[4] += info->mallocs;
1623:   if (flag == MAT_LOCAL) {
1624:     info->nz_used      = isend[0];
1625:     info->nz_allocated = isend[1];
1626:     info->nz_unneeded  = isend[2];
1627:     info->memory       = isend[3];
1628:     info->mallocs      = isend[4];
1629:   } else if (flag == MAT_GLOBAL_MAX) {
1630:     MPIU_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)matin));

1632:     info->nz_used      = irecv[0];
1633:     info->nz_allocated = irecv[1];
1634:     info->nz_unneeded  = irecv[2];
1635:     info->memory       = irecv[3];
1636:     info->mallocs      = irecv[4];
1637:   } else if (flag == MAT_GLOBAL_SUM) {
1638:     MPIU_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)matin));

1640:     info->nz_used      = irecv[0];
1641:     info->nz_allocated = irecv[1];
1642:     info->nz_unneeded  = irecv[2];
1643:     info->memory       = irecv[3];
1644:     info->mallocs      = irecv[4];
1645:   } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Unknown MatInfoType argument %d",(int)flag);
1646:   info->fill_ratio_given  = 0; /* no parallel LU/ILU/Cholesky */
1647:   info->fill_ratio_needed = 0;
1648:   info->factor_mallocs    = 0;
1649:   return(0);
1650: }

1654: PetscErrorCode MatSetOption_MPISBAIJ(Mat A,MatOption op,PetscBool flg)
1655: {
1656:   Mat_MPISBAIJ   *a  = (Mat_MPISBAIJ*)A->data;
1657:   Mat_SeqSBAIJ   *aA = (Mat_SeqSBAIJ*)a->A->data;

1661:   switch (op) {
1662:   case MAT_NEW_NONZERO_LOCATIONS:
1663:   case MAT_NEW_NONZERO_ALLOCATION_ERR:
1664:   case MAT_UNUSED_NONZERO_LOCATION_ERR:
1665:   case MAT_KEEP_NONZERO_PATTERN:
1666:   case MAT_NEW_NONZERO_LOCATION_ERR:
1667:     MatCheckPreallocated(A,1);
1668:     MatSetOption(a->A,op,flg);
1669:     MatSetOption(a->B,op,flg);
1670:     break;
1671:   case MAT_ROW_ORIENTED:
1672:     MatCheckPreallocated(A,1);
1673:     a->roworiented = flg;

1675:     MatSetOption(a->A,op,flg);
1676:     MatSetOption(a->B,op,flg);
1677:     break;
1678:   case MAT_NEW_DIAGONALS:
1679:     PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);
1680:     break;
1681:   case MAT_IGNORE_OFF_PROC_ENTRIES:
1682:     a->donotstash = flg;
1683:     break;
1684:   case MAT_USE_HASH_TABLE:
1685:     a->ht_flag = flg;
1686:     break;
1687:   case MAT_HERMITIAN:
1688:     MatCheckPreallocated(A,1);
1689:     if (!A->assembled) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Must call MatAssemblyEnd() first");
1690:     MatSetOption(a->A,op,flg);

1692:     A->ops->mult = MatMult_MPISBAIJ_Hermitian;
1693:     break;
1694:   case MAT_SPD:
1695:     A->spd_set = PETSC_TRUE;
1696:     A->spd     = flg;
1697:     if (flg) {
1698:       A->symmetric                  = PETSC_TRUE;
1699:       A->structurally_symmetric     = PETSC_TRUE;
1700:       A->symmetric_set              = PETSC_TRUE;
1701:       A->structurally_symmetric_set = PETSC_TRUE;
1702:     }
1703:     break;
1704:   case MAT_SYMMETRIC:
1705:     MatCheckPreallocated(A,1);
1706:     MatSetOption(a->A,op,flg);
1707:     break;
1708:   case MAT_STRUCTURALLY_SYMMETRIC:
1709:     MatCheckPreallocated(A,1);
1710:     MatSetOption(a->A,op,flg);
1711:     break;
1712:   case MAT_SYMMETRY_ETERNAL:
1713:     if (!flg) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Matrix must be symmetric");
1714:     PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);
1715:     break;
1716:   case MAT_IGNORE_LOWER_TRIANGULAR:
1717:     aA->ignore_ltriangular = flg;
1718:     break;
1719:   case MAT_ERROR_LOWER_TRIANGULAR:
1720:     aA->ignore_ltriangular = flg;
1721:     break;
1722:   case MAT_GETROW_UPPERTRIANGULAR:
1723:     aA->getrow_utriangular = flg;
1724:     break;
1725:   default:
1726:     SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %d",op);
1727:   }
1728:   return(0);
1729: }

1733: PetscErrorCode MatTranspose_MPISBAIJ(Mat A,MatReuse reuse,Mat *B)
1734: {

1738:   if (MAT_INITIAL_MATRIX || *B != A) {
1739:     MatDuplicate(A,MAT_COPY_VALUES,B);
1740:   }
1741:   return(0);
1742: }

1746: PetscErrorCode MatDiagonalScale_MPISBAIJ(Mat mat,Vec ll,Vec rr)
1747: {
1748:   Mat_MPISBAIJ   *baij = (Mat_MPISBAIJ*)mat->data;
1749:   Mat            a     = baij->A, b=baij->B;
1751:   PetscInt       nv,m,n;
1752:   PetscBool      flg;

1755:   if (ll != rr) {
1756:     VecEqual(ll,rr,&flg);
1757:     if (!flg) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"For symmetric format, left and right scaling vectors must be same\n");
1758:   }
1759:   if (!ll) return(0);

1761:   MatGetLocalSize(mat,&m,&n);
1762:   if (m != n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"For symmetric format, local size %d %d must be same",m,n);

1764:   VecGetLocalSize(rr,&nv);
1765:   if (nv!=n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Left and right vector non-conforming local size");

1767:   VecScatterBegin(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);

1769:   /* left diagonalscale the off-diagonal part */
1770:   (*b->ops->diagonalscale)(b,ll,NULL);

1772:   /* scale the diagonal part */
1773:   (*a->ops->diagonalscale)(a,ll,rr);

1775:   /* right diagonalscale the off-diagonal part */
1776:   VecScatterEnd(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);
1777:   (*b->ops->diagonalscale)(b,NULL,baij->lvec);
1778:   return(0);
1779: }

1783: PetscErrorCode MatSetUnfactored_MPISBAIJ(Mat A)
1784: {
1785:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;

1789:   MatSetUnfactored(a->A);
1790:   return(0);
1791: }

1793: static PetscErrorCode MatDuplicate_MPISBAIJ(Mat,MatDuplicateOption,Mat*);

1797: PetscErrorCode MatEqual_MPISBAIJ(Mat A,Mat B,PetscBool  *flag)
1798: {
1799:   Mat_MPISBAIJ   *matB = (Mat_MPISBAIJ*)B->data,*matA = (Mat_MPISBAIJ*)A->data;
1800:   Mat            a,b,c,d;
1801:   PetscBool      flg;

1805:   a = matA->A; b = matA->B;
1806:   c = matB->A; d = matB->B;

1808:   MatEqual(a,c,&flg);
1809:   if (flg) {
1810:     MatEqual(b,d,&flg);
1811:   }
1812:   MPIU_Allreduce(&flg,flag,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)A));
1813:   return(0);
1814: }

1818: PetscErrorCode MatCopy_MPISBAIJ(Mat A,Mat B,MatStructure str)
1819: {
1821:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;
1822:   Mat_MPISBAIJ   *b = (Mat_MPISBAIJ*)B->data;

1825:   /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */
1826:   if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) {
1827:     MatGetRowUpperTriangular(A);
1828:     MatCopy_Basic(A,B,str);
1829:     MatRestoreRowUpperTriangular(A);
1830:   } else {
1831:     MatCopy(a->A,b->A,str);
1832:     MatCopy(a->B,b->B,str);
1833:   }
1834:   return(0);
1835: }

1839: PetscErrorCode MatSetUp_MPISBAIJ(Mat A)
1840: {

1844:   MatMPISBAIJSetPreallocation(A,A->rmap->bs,PETSC_DEFAULT,0,PETSC_DEFAULT,0);
1845:   return(0);
1846: }

1850: PetscErrorCode MatAXPY_MPISBAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str)
1851: {
1853:   Mat_MPISBAIJ   *xx=(Mat_MPISBAIJ*)X->data,*yy=(Mat_MPISBAIJ*)Y->data;
1854:   PetscBLASInt   bnz,one=1;
1855:   Mat_SeqSBAIJ   *xa,*ya;
1856:   Mat_SeqBAIJ    *xb,*yb;

1859:   if (str == SAME_NONZERO_PATTERN) {
1860:     PetscScalar alpha = a;
1861:     xa   = (Mat_SeqSBAIJ*)xx->A->data;
1862:     ya   = (Mat_SeqSBAIJ*)yy->A->data;
1863:     PetscBLASIntCast(xa->nz,&bnz);
1864:     PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,xa->a,&one,ya->a,&one));
1865:     xb   = (Mat_SeqBAIJ*)xx->B->data;
1866:     yb   = (Mat_SeqBAIJ*)yy->B->data;
1867:     PetscBLASIntCast(xb->nz,&bnz);
1868:     PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,xb->a,&one,yb->a,&one));
1869:     PetscObjectStateIncrease((PetscObject)Y);
1870:   } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */
1871:     MatSetOption(X,MAT_GETROW_UPPERTRIANGULAR,PETSC_TRUE);
1872:     MatAXPY_Basic(Y,a,X,str);
1873:     MatSetOption(X,MAT_GETROW_UPPERTRIANGULAR,PETSC_FALSE);
1874:   } else {
1875:     Mat      B;
1876:     PetscInt *nnz_d,*nnz_o,bs=Y->rmap->bs;
1877:     if (bs != X->rmap->bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Matrices must have same block size");
1878:     MatGetRowUpperTriangular(X);
1879:     MatGetRowUpperTriangular(Y);
1880:     PetscMalloc1(yy->A->rmap->N,&nnz_d);
1881:     PetscMalloc1(yy->B->rmap->N,&nnz_o);
1882:     MatCreate(PetscObjectComm((PetscObject)Y),&B);
1883:     PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);
1884:     MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);
1885:     MatSetBlockSizesFromMats(B,Y,Y);
1886:     MatSetType(B,MATMPISBAIJ);
1887:     MatAXPYGetPreallocation_SeqSBAIJ(yy->A,xx->A,nnz_d);
1888:     MatAXPYGetPreallocation_MPIBAIJ(yy->B,yy->garray,xx->B,xx->garray,nnz_o);
1889:     MatMPISBAIJSetPreallocation(B,bs,0,nnz_d,0,nnz_o);
1890:     MatAXPY_BasicWithPreallocation(B,Y,a,X,str);
1891:     MatHeaderReplace(Y,&B);
1892:     PetscFree(nnz_d);
1893:     PetscFree(nnz_o);
1894:     MatRestoreRowUpperTriangular(X);
1895:     MatRestoreRowUpperTriangular(Y);
1896:   }
1897:   return(0);
1898: }

1902: PetscErrorCode MatGetSubMatrices_MPISBAIJ(Mat A,PetscInt n,const IS irow[],const IS icol[],MatReuse scall,Mat *B[])
1903: {
1905:   PetscInt       i;
1906:   PetscBool      flg;

1909:   MatGetSubMatrices_MPIBAIJ(A,n,irow,icol,scall,B); /* B[] are sbaij matrices */
1910:   for (i=0; i<n; i++) {
1911:     ISEqual(irow[i],icol[i],&flg);
1912:     if (!flg) {
1913:       MatSeqSBAIJZeroOps_Private(*B[i]);
1914:     }
1915:   }
1916:   return(0);
1917: }

1921: PetscErrorCode MatShift_MPISBAIJ(Mat Y,PetscScalar a)
1922: {
1924:   Mat_MPISBAIJ    *maij = (Mat_MPISBAIJ*)Y->data;
1925:   Mat_SeqSBAIJ    *aij = (Mat_SeqSBAIJ*)maij->A->data;

1928:   if (!Y->preallocated) {
1929:     MatMPISBAIJSetPreallocation(Y,Y->rmap->bs,1,NULL,0,NULL);
1930:   } else if (!aij->nz) {
1931:     PetscInt nonew = aij->nonew;
1932:     MatSeqSBAIJSetPreallocation(maij->A,Y->rmap->bs,1,NULL);
1933:     aij->nonew = nonew;
1934:   }
1935:   MatShift_Basic(Y,a);
1936:   return(0);
1937: }

1941: PetscErrorCode MatMissingDiagonal_MPISBAIJ(Mat A,PetscBool  *missing,PetscInt *d)
1942: {
1943:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;

1947:   if (A->rmap->n != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only works for square matrices");
1948:   MatMissingDiagonal(a->A,missing,d);
1949:   if (d) {
1950:     PetscInt rstart;
1951:     MatGetOwnershipRange(A,&rstart,NULL);
1952:     *d += rstart/A->rmap->bs;

1954:   }
1955:   return(0);
1956: }


1959: /* -------------------------------------------------------------------*/
1960: static struct _MatOps MatOps_Values = {MatSetValues_MPISBAIJ,
1961:                                        MatGetRow_MPISBAIJ,
1962:                                        MatRestoreRow_MPISBAIJ,
1963:                                        MatMult_MPISBAIJ,
1964:                                /*  4*/ MatMultAdd_MPISBAIJ,
1965:                                        MatMult_MPISBAIJ,       /* transpose versions are same as non-transpose */
1966:                                        MatMultAdd_MPISBAIJ,
1967:                                        0,
1968:                                        0,
1969:                                        0,
1970:                                /* 10*/ 0,
1971:                                        0,
1972:                                        0,
1973:                                        MatSOR_MPISBAIJ,
1974:                                        MatTranspose_MPISBAIJ,
1975:                                /* 15*/ MatGetInfo_MPISBAIJ,
1976:                                        MatEqual_MPISBAIJ,
1977:                                        MatGetDiagonal_MPISBAIJ,
1978:                                        MatDiagonalScale_MPISBAIJ,
1979:                                        MatNorm_MPISBAIJ,
1980:                                /* 20*/ MatAssemblyBegin_MPISBAIJ,
1981:                                        MatAssemblyEnd_MPISBAIJ,
1982:                                        MatSetOption_MPISBAIJ,
1983:                                        MatZeroEntries_MPISBAIJ,
1984:                                /* 24*/ 0,
1985:                                        0,
1986:                                        0,
1987:                                        0,
1988:                                        0,
1989:                                /* 29*/ MatSetUp_MPISBAIJ,
1990:                                        0,
1991:                                        0,
1992:                                        0,
1993:                                        0,
1994:                                /* 34*/ MatDuplicate_MPISBAIJ,
1995:                                        0,
1996:                                        0,
1997:                                        0,
1998:                                        0,
1999:                                /* 39*/ MatAXPY_MPISBAIJ,
2000:                                        MatGetSubMatrices_MPISBAIJ,
2001:                                        MatIncreaseOverlap_MPISBAIJ,
2002:                                        MatGetValues_MPISBAIJ,
2003:                                        MatCopy_MPISBAIJ,
2004:                                /* 44*/ 0,
2005:                                        MatScale_MPISBAIJ,
2006:                                        MatShift_MPISBAIJ,
2007:                                        0,
2008:                                        0,
2009:                                /* 49*/ 0,
2010:                                        0,
2011:                                        0,
2012:                                        0,
2013:                                        0,
2014:                                /* 54*/ 0,
2015:                                        0,
2016:                                        MatSetUnfactored_MPISBAIJ,
2017:                                        0,
2018:                                        MatSetValuesBlocked_MPISBAIJ,
2019:                                /* 59*/ MatGetSubMatrix_MPISBAIJ,
2020:                                        0,
2021:                                        0,
2022:                                        0,
2023:                                        0,
2024:                                /* 64*/ 0,
2025:                                        0,
2026:                                        0,
2027:                                        0,
2028:                                        0,
2029:                                /* 69*/ MatGetRowMaxAbs_MPISBAIJ,
2030:                                        0,
2031:                                        0,
2032:                                        0,
2033:                                        0,
2034:                                /* 74*/ 0,
2035:                                        0,
2036:                                        0,
2037:                                        0,
2038:                                        0,
2039:                                /* 79*/ 0,
2040:                                        0,
2041:                                        0,
2042:                                        0,
2043:                                        MatLoad_MPISBAIJ,
2044:                                /* 84*/ 0,
2045:                                        0,
2046:                                        0,
2047:                                        0,
2048:                                        0,
2049:                                /* 89*/ 0,
2050:                                        0,
2051:                                        0,
2052:                                        0,
2053:                                        0,
2054:                                /* 94*/ 0,
2055:                                        0,
2056:                                        0,
2057:                                        0,
2058:                                        0,
2059:                                /* 99*/ 0,
2060:                                        0,
2061:                                        0,
2062:                                        0,
2063:                                        0,
2064:                                /*104*/ 0,
2065:                                        MatRealPart_MPISBAIJ,
2066:                                        MatImaginaryPart_MPISBAIJ,
2067:                                        MatGetRowUpperTriangular_MPISBAIJ,
2068:                                        MatRestoreRowUpperTriangular_MPISBAIJ,
2069:                                /*109*/ 0,
2070:                                        0,
2071:                                        0,
2072:                                        0,
2073:                                        MatMissingDiagonal_MPISBAIJ,
2074:                                /*114*/ 0,
2075:                                        0,
2076:                                        0,
2077:                                        0,
2078:                                        0,
2079:                                /*119*/ 0,
2080:                                        0,
2081:                                        0,
2082:                                        0,
2083:                                        0,
2084:                                /*124*/ 0,
2085:                                        0,
2086:                                        0,
2087:                                        0,
2088:                                        0,
2089:                                /*129*/ 0,
2090:                                        0,
2091:                                        0,
2092:                                        0,
2093:                                        0,
2094:                                /*134*/ 0,
2095:                                        0,
2096:                                        0,
2097:                                        0,
2098:                                        0,
2099:                                /*139*/ 0,
2100:                                        0,
2101:                                        0,
2102:                                        0,
2103:                                        0,
2104:                                 /*144*/MatCreateMPIMatConcatenateSeqMat_MPISBAIJ
2105: };

2109: PetscErrorCode  MatGetDiagonalBlock_MPISBAIJ(Mat A,Mat *a)
2110: {
2112:   *a = ((Mat_MPISBAIJ*)A->data)->A;
2113:   return(0);
2114: }

2118: PetscErrorCode  MatMPISBAIJSetPreallocation_MPISBAIJ(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt *d_nnz,PetscInt o_nz,const PetscInt *o_nnz)
2119: {
2120:   Mat_MPISBAIJ   *b;
2122:   PetscInt       i,mbs,Mbs;

2125:   MatSetBlockSize(B,PetscAbs(bs));
2126:   PetscLayoutSetUp(B->rmap);
2127:   PetscLayoutSetUp(B->cmap);
2128:   PetscLayoutGetBlockSize(B->rmap,&bs);

2130:   b   = (Mat_MPISBAIJ*)B->data;
2131:   mbs = B->rmap->n/bs;
2132:   Mbs = B->rmap->N/bs;
2133:   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);

2135:   B->rmap->bs = bs;
2136:   b->bs2      = bs*bs;
2137:   b->mbs      = mbs;
2138:   b->Mbs      = Mbs;
2139:   b->nbs      = B->cmap->n/bs;
2140:   b->Nbs      = B->cmap->N/bs;

2142:   for (i=0; i<=b->size; i++) {
2143:     b->rangebs[i] = B->rmap->range[i]/bs;
2144:   }
2145:   b->rstartbs = B->rmap->rstart/bs;
2146:   b->rendbs   = B->rmap->rend/bs;

2148:   b->cstartbs = B->cmap->rstart/bs;
2149:   b->cendbs   = B->cmap->rend/bs;

2151:   if (!B->preallocated) {
2152:     MatCreate(PETSC_COMM_SELF,&b->A);
2153:     MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);
2154:     MatSetType(b->A,MATSEQSBAIJ);
2155:     PetscLogObjectParent((PetscObject)B,(PetscObject)b->A);
2156:     MatCreate(PETSC_COMM_SELF,&b->B);
2157:     MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);
2158:     MatSetType(b->B,MATSEQBAIJ);
2159:     PetscLogObjectParent((PetscObject)B,(PetscObject)b->B);
2160:     MatStashCreate_Private(PetscObjectComm((PetscObject)B),bs,&B->bstash);
2161:   }

2163:   MatSeqSBAIJSetPreallocation(b->A,bs,d_nz,d_nnz);
2164:   MatSeqBAIJSetPreallocation(b->B,bs,o_nz,o_nnz);

2166:   B->preallocated = PETSC_TRUE;
2167:   return(0);
2168: }

2172: PetscErrorCode MatMPISBAIJSetPreallocationCSR_MPISBAIJ(Mat B,PetscInt bs,const PetscInt ii[],const PetscInt jj[],const PetscScalar V[])
2173: {
2174:   PetscInt       m,rstart,cstart,cend;
2175:   PetscInt       i,j,d,nz,nz_max=0,*d_nnz=0,*o_nnz=0;
2176:   const PetscInt *JJ    =0;
2177:   PetscScalar    *values=0;

2181:   if (bs < 1) SETERRQ1(PetscObjectComm((PetscObject)B),PETSC_ERR_ARG_OUTOFRANGE,"Invalid block size specified, must be positive but it is %D",bs);
2182:   PetscLayoutSetBlockSize(B->rmap,bs);
2183:   PetscLayoutSetBlockSize(B->cmap,bs);
2184:   PetscLayoutSetUp(B->rmap);
2185:   PetscLayoutSetUp(B->cmap);
2186:   PetscLayoutGetBlockSize(B->rmap,&bs);
2187:   m      = B->rmap->n/bs;
2188:   rstart = B->rmap->rstart/bs;
2189:   cstart = B->cmap->rstart/bs;
2190:   cend   = B->cmap->rend/bs;

2192:   if (ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"ii[0] must be 0 but it is %D",ii[0]);
2193:   PetscMalloc2(m,&d_nnz,m,&o_nnz);
2194:   for (i=0; i<m; i++) {
2195:     nz = ii[i+1] - ii[i];
2196:     if (nz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative number of columns %D",i,nz);
2197:     nz_max = PetscMax(nz_max,nz);
2198:     JJ     = jj + ii[i];
2199:     for (j=0; j<nz; j++) {
2200:       if (*JJ >= cstart) break;
2201:       JJ++;
2202:     }
2203:     d = 0;
2204:     for (; j<nz; j++) {
2205:       if (*JJ++ >= cend) break;
2206:       d++;
2207:     }
2208:     d_nnz[i] = d;
2209:     o_nnz[i] = nz - d;
2210:   }
2211:   MatMPISBAIJSetPreallocation(B,bs,0,d_nnz,0,o_nnz);
2212:   PetscFree2(d_nnz,o_nnz);

2214:   values = (PetscScalar*)V;
2215:   if (!values) {
2216:     PetscMalloc1(bs*bs*nz_max,&values);
2217:     PetscMemzero(values,bs*bs*nz_max*sizeof(PetscScalar));
2218:   }
2219:   for (i=0; i<m; i++) {
2220:     PetscInt          row    = i + rstart;
2221:     PetscInt          ncols  = ii[i+1] - ii[i];
2222:     const PetscInt    *icols = jj + ii[i];
2223:     const PetscScalar *svals = values + (V ? (bs*bs*ii[i]) : 0);
2224:     MatSetValuesBlocked_MPISBAIJ(B,1,&row,ncols,icols,svals,INSERT_VALUES);
2225:   }

2227:   if (!V) { PetscFree(values); }
2228:   MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
2229:   MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);
2230:   MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);
2231:   return(0);
2232: }

2234: /*MC
2235:    MATMPISBAIJ - MATMPISBAIJ = "mpisbaij" - A matrix type to be used for distributed symmetric sparse block matrices,
2236:    based on block compressed sparse row format.  Only the upper triangular portion of the "diagonal" portion of
2237:    the matrix is stored.

2239:   For complex numbers by default this matrix is symmetric, NOT Hermitian symmetric. To make it Hermitian symmetric you
2240:   can call MatSetOption(Mat, MAT_HERMITIAN);

2242:    Options Database Keys:
2243: . -mat_type mpisbaij - sets the matrix type to "mpisbaij" during a call to MatSetFromOptions()

2245:   Level: beginner

2247: .seealso: MatCreateMPISBAIJ
2248: M*/

2250: PETSC_INTERN PetscErrorCode MatConvert_MPISBAIJ_MPISBSTRM(Mat,MatType,MatReuse,Mat*);

2254: PETSC_EXTERN PetscErrorCode MatCreate_MPISBAIJ(Mat B)
2255: {
2256:   Mat_MPISBAIJ   *b;
2258:   PetscBool      flg = PETSC_FALSE;

2261:   PetscNewLog(B,&b);
2262:   B->data = (void*)b;
2263:   PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));

2265:   B->ops->destroy = MatDestroy_MPISBAIJ;
2266:   B->ops->view    = MatView_MPISBAIJ;
2267:   B->assembled    = PETSC_FALSE;
2268:   B->insertmode   = NOT_SET_VALUES;

2270:   MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);
2271:   MPI_Comm_size(PetscObjectComm((PetscObject)B),&b->size);

2273:   /* build local table of row and column ownerships */
2274:   PetscMalloc1(b->size+2,&b->rangebs);

2276:   /* build cache for off array entries formed */
2277:   MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);

2279:   b->donotstash  = PETSC_FALSE;
2280:   b->colmap      = NULL;
2281:   b->garray      = NULL;
2282:   b->roworiented = PETSC_TRUE;

2284:   /* stuff used in block assembly */
2285:   b->barray = 0;

2287:   /* stuff used for matrix vector multiply */
2288:   b->lvec    = 0;
2289:   b->Mvctx   = 0;
2290:   b->slvec0  = 0;
2291:   b->slvec0b = 0;
2292:   b->slvec1  = 0;
2293:   b->slvec1a = 0;
2294:   b->slvec1b = 0;
2295:   b->sMvctx  = 0;

2297:   /* stuff for MatGetRow() */
2298:   b->rowindices   = 0;
2299:   b->rowvalues    = 0;
2300:   b->getrowactive = PETSC_FALSE;

2302:   /* hash table stuff */
2303:   b->ht           = 0;
2304:   b->hd           = 0;
2305:   b->ht_size      = 0;
2306:   b->ht_flag      = PETSC_FALSE;
2307:   b->ht_fact      = 0;
2308:   b->ht_total_ct  = 0;
2309:   b->ht_insert_ct = 0;

2311:   /* stuff for MatGetSubMatrices_MPIBAIJ_local() */
2312:   b->ijonly = PETSC_FALSE;

2314:   b->in_loc = 0;
2315:   b->v_loc  = 0;
2316:   b->n_loc  = 0;

2318:   PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPISBAIJ);
2319:   PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPISBAIJ);
2320:   PetscObjectComposeFunction((PetscObject)B,"MatGetDiagonalBlock_C",MatGetDiagonalBlock_MPISBAIJ);
2321:   PetscObjectComposeFunction((PetscObject)B,"MatMPISBAIJSetPreallocation_C",MatMPISBAIJSetPreallocation_MPISBAIJ);
2322:   PetscObjectComposeFunction((PetscObject)B,"MatMPISBAIJSetPreallocationCSR_C",MatMPISBAIJSetPreallocationCSR_MPISBAIJ);
2323:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpisbaij_mpisbstrm_C",MatConvert_MPISBAIJ_MPISBSTRM);
2324: #if defined(PETSC_HAVE_ELEMENTAL)
2325:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpisbaij_elemental_C",MatConvert_MPISBAIJ_Elemental);
2326: #endif

2328:   B->symmetric                  = PETSC_TRUE;
2329:   B->structurally_symmetric     = PETSC_TRUE;
2330:   B->symmetric_set              = PETSC_TRUE;
2331:   B->structurally_symmetric_set = PETSC_TRUE;

2333:   PetscObjectChangeTypeName((PetscObject)B,MATMPISBAIJ);
2334:   PetscOptionsBegin(PetscObjectComm((PetscObject)B),NULL,"Options for loading MPISBAIJ matrix 1","Mat");
2335:   PetscOptionsBool("-mat_use_hash_table","Use hash table to save memory in constructing matrix","MatSetOption",flg,&flg,NULL);
2336:   if (flg) {
2337:     PetscReal fact = 1.39;
2338:     MatSetOption(B,MAT_USE_HASH_TABLE,PETSC_TRUE);
2339:     PetscOptionsReal("-mat_use_hash_table","Use hash table factor","MatMPIBAIJSetHashTableFactor",fact,&fact,NULL);
2340:     if (fact <= 1.0) fact = 1.39;
2341:     MatMPIBAIJSetHashTableFactor(B,fact);
2342:     PetscInfo1(B,"Hash table Factor used %5.2f\n",fact);
2343:   }
2344:   PetscOptionsEnd();
2345:   return(0);
2346: }

2348: /*MC
2349:    MATSBAIJ - MATSBAIJ = "sbaij" - A matrix type to be used for symmetric block sparse matrices.

2351:    This matrix type is identical to MATSEQSBAIJ when constructed with a single process communicator,
2352:    and MATMPISBAIJ otherwise.

2354:    Options Database Keys:
2355: . -mat_type sbaij - sets the matrix type to "sbaij" during a call to MatSetFromOptions()

2357:   Level: beginner

2359: .seealso: MatCreateMPISBAIJ,MATSEQSBAIJ,MATMPISBAIJ
2360: M*/

2364: /*@C
2365:    MatMPISBAIJSetPreallocation - For good matrix assembly performance
2366:    the user should preallocate the matrix storage by setting the parameters
2367:    d_nz (or d_nnz) and o_nz (or o_nnz).  By setting these parameters accurately,
2368:    performance can be increased by more than a factor of 50.

2370:    Collective on Mat

2372:    Input Parameters:
2373: +  B - the matrix
2374: .  bs   - size of block, the blocks are ALWAYS square. One can use MatSetBlockSizes() to set a different row and column blocksize but the row
2375:           blocksize always defines the size of the blocks. The column blocksize sets the blocksize of the vectors obtained with MatCreateVecs()
2376: .  d_nz  - number of block nonzeros per block row in diagonal portion of local
2377:            submatrix  (same for all local rows)
2378: .  d_nnz - array containing the number of block nonzeros in the various block rows
2379:            in the upper triangular and diagonal part of the in diagonal portion of the local
2380:            (possibly different for each block row) or NULL.  If you plan to factor the matrix you must leave room
2381:            for the diagonal entry and set a value even if it is zero.
2382: .  o_nz  - number of block nonzeros per block row in the off-diagonal portion of local
2383:            submatrix (same for all local rows).
2384: -  o_nnz - array containing the number of nonzeros in the various block rows of the
2385:            off-diagonal portion of the local submatrix that is right of the diagonal
2386:            (possibly different for each block row) or NULL.


2389:    Options Database Keys:
2390: .   -mat_no_unroll - uses code that does not unroll the loops in the
2391:                      block calculations (much slower)
2392: .   -mat_block_size - size of the blocks to use

2394:    Notes:

2396:    If PETSC_DECIDE or  PETSC_DETERMINE is used for a particular argument on one processor
2397:    than it must be used on all processors that share the object for that argument.

2399:    If the *_nnz parameter is given then the *_nz parameter is ignored

2401:    Storage Information:
2402:    For a square global matrix we define each processor's diagonal portion
2403:    to be its local rows and the corresponding columns (a square submatrix);
2404:    each processor's off-diagonal portion encompasses the remainder of the
2405:    local matrix (a rectangular submatrix).

2407:    The user can specify preallocated storage for the diagonal part of
2408:    the local submatrix with either d_nz or d_nnz (not both).  Set
2409:    d_nz=PETSC_DEFAULT and d_nnz=NULL for PETSc to control dynamic
2410:    memory allocation.  Likewise, specify preallocated storage for the
2411:    off-diagonal part of the local submatrix with o_nz or o_nnz (not both).

2413:    You can call MatGetInfo() to get information on how effective the preallocation was;
2414:    for example the fields mallocs,nz_allocated,nz_used,nz_unneeded;
2415:    You can also run with the option -info and look for messages with the string
2416:    malloc in them to see if additional memory allocation was needed.

2418:    Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In
2419:    the figure below we depict these three local rows and all columns (0-11).

2421: .vb
2422:            0 1 2 3 4 5 6 7 8 9 10 11
2423:           --------------------------
2424:    row 3  |. . . d d d o o o o  o  o
2425:    row 4  |. . . d d d o o o o  o  o
2426:    row 5  |. . . d d d o o o o  o  o
2427:           --------------------------
2428: .ve

2430:    Thus, any entries in the d locations are stored in the d (diagonal)
2431:    submatrix, and any entries in the o locations are stored in the
2432:    o (off-diagonal) submatrix.  Note that the d matrix is stored in
2433:    MatSeqSBAIJ format and the o submatrix in MATSEQBAIJ format.

2435:    Now d_nz should indicate the number of block nonzeros per row in the upper triangular
2436:    plus the diagonal part of the d matrix,
2437:    and o_nz should indicate the number of block nonzeros per row in the o matrix

2439:    In general, for PDE problems in which most nonzeros are near the diagonal,
2440:    one expects d_nz >> o_nz.   For large problems you MUST preallocate memory
2441:    or you will get TERRIBLE performance; see the users' manual chapter on
2442:    matrices.

2444:    Level: intermediate

2446: .keywords: matrix, block, aij, compressed row, sparse, parallel

2448: .seealso: MatCreate(), MatCreateSeqSBAIJ(), MatSetValues(), MatCreateBAIJ(), PetscSplitOwnership()
2449: @*/
2450: PetscErrorCode  MatMPISBAIJSetPreallocation(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[])
2451: {

2458:   PetscTryMethod(B,"MatMPISBAIJSetPreallocation_C",(Mat,PetscInt,PetscInt,const PetscInt[],PetscInt,const PetscInt[]),(B,bs,d_nz,d_nnz,o_nz,o_nnz));
2459:   return(0);
2460: }

2464: /*@C
2465:    MatCreateSBAIJ - Creates a sparse parallel matrix in symmetric block AIJ format
2466:    (block compressed row).  For good matrix assembly performance
2467:    the user should preallocate the matrix storage by setting the parameters
2468:    d_nz (or d_nnz) and o_nz (or o_nnz).  By setting these parameters accurately,
2469:    performance can be increased by more than a factor of 50.

2471:    Collective on MPI_Comm

2473:    Input Parameters:
2474: +  comm - MPI communicator
2475: .  bs   - size of block, the blocks are ALWAYS square. One can use MatSetBlockSizes() to set a different row and column blocksize but the row
2476:           blocksize always defines the size of the blocks. The column blocksize sets the blocksize of the vectors obtained with MatCreateVecs()
2477: .  m - number of local rows (or PETSC_DECIDE to have calculated if M is given)
2478:            This value should be the same as the local size used in creating the
2479:            y vector for the matrix-vector product y = Ax.
2480: .  n - number of local columns (or PETSC_DECIDE to have calculated if N is given)
2481:            This value should be the same as the local size used in creating the
2482:            x vector for the matrix-vector product y = Ax.
2483: .  M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
2484: .  N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
2485: .  d_nz  - number of block nonzeros per block row in diagonal portion of local
2486:            submatrix  (same for all local rows)
2487: .  d_nnz - array containing the number of block nonzeros in the various block rows
2488:            in the upper triangular portion of the in diagonal portion of the local
2489:            (possibly different for each block block row) or NULL.
2490:            If you plan to factor the matrix you must leave room for the diagonal entry and
2491:            set its value even if it is zero.
2492: .  o_nz  - number of block nonzeros per block row in the off-diagonal portion of local
2493:            submatrix (same for all local rows).
2494: -  o_nnz - array containing the number of nonzeros in the various block rows of the
2495:            off-diagonal portion of the local submatrix (possibly different for
2496:            each block row) or NULL.

2498:    Output Parameter:
2499: .  A - the matrix

2501:    Options Database Keys:
2502: .   -mat_no_unroll - uses code that does not unroll the loops in the
2503:                      block calculations (much slower)
2504: .   -mat_block_size - size of the blocks to use
2505: .   -mat_mpi - use the parallel matrix data structures even on one processor
2506:                (defaults to using SeqBAIJ format on one processor)

2508:    It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(),
2509:    MatXXXXSetPreallocation() paradgm instead of this routine directly.
2510:    [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation]

2512:    Notes:
2513:    The number of rows and columns must be divisible by blocksize.
2514:    This matrix type does not support complex Hermitian operation.

2516:    The user MUST specify either the local or global matrix dimensions
2517:    (possibly both).

2519:    If PETSC_DECIDE or  PETSC_DETERMINE is used for a particular argument on one processor
2520:    than it must be used on all processors that share the object for that argument.

2522:    If the *_nnz parameter is given then the *_nz parameter is ignored

2524:    Storage Information:
2525:    For a square global matrix we define each processor's diagonal portion
2526:    to be its local rows and the corresponding columns (a square submatrix);
2527:    each processor's off-diagonal portion encompasses the remainder of the
2528:    local matrix (a rectangular submatrix).

2530:    The user can specify preallocated storage for the diagonal part of
2531:    the local submatrix with either d_nz or d_nnz (not both).  Set
2532:    d_nz=PETSC_DEFAULT and d_nnz=NULL for PETSc to control dynamic
2533:    memory allocation.  Likewise, specify preallocated storage for the
2534:    off-diagonal part of the local submatrix with o_nz or o_nnz (not both).

2536:    Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In
2537:    the figure below we depict these three local rows and all columns (0-11).

2539: .vb
2540:            0 1 2 3 4 5 6 7 8 9 10 11
2541:           --------------------------
2542:    row 3  |. . . d d d o o o o  o  o
2543:    row 4  |. . . d d d o o o o  o  o
2544:    row 5  |. . . d d d o o o o  o  o
2545:           --------------------------
2546: .ve

2548:    Thus, any entries in the d locations are stored in the d (diagonal)
2549:    submatrix, and any entries in the o locations are stored in the
2550:    o (off-diagonal) submatrix.  Note that the d matrix is stored in
2551:    MatSeqSBAIJ format and the o submatrix in MATSEQBAIJ format.

2553:    Now d_nz should indicate the number of block nonzeros per row in the upper triangular
2554:    plus the diagonal part of the d matrix,
2555:    and o_nz should indicate the number of block nonzeros per row in the o matrix.
2556:    In general, for PDE problems in which most nonzeros are near the diagonal,
2557:    one expects d_nz >> o_nz.   For large problems you MUST preallocate memory
2558:    or you will get TERRIBLE performance; see the users' manual chapter on
2559:    matrices.

2561:    Level: intermediate

2563: .keywords: matrix, block, aij, compressed row, sparse, parallel

2565: .seealso: MatCreate(), MatCreateSeqSBAIJ(), MatSetValues(), MatCreateBAIJ()
2566: @*/

2568: 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)
2569: {
2571:   PetscMPIInt    size;

2574:   MatCreate(comm,A);
2575:   MatSetSizes(*A,m,n,M,N);
2576:   MPI_Comm_size(comm,&size);
2577:   if (size > 1) {
2578:     MatSetType(*A,MATMPISBAIJ);
2579:     MatMPISBAIJSetPreallocation(*A,bs,d_nz,d_nnz,o_nz,o_nnz);
2580:   } else {
2581:     MatSetType(*A,MATSEQSBAIJ);
2582:     MatSeqSBAIJSetPreallocation(*A,bs,d_nz,d_nnz);
2583:   }
2584:   return(0);
2585: }


2590: static PetscErrorCode MatDuplicate_MPISBAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat)
2591: {
2592:   Mat            mat;
2593:   Mat_MPISBAIJ   *a,*oldmat = (Mat_MPISBAIJ*)matin->data;
2595:   PetscInt       len=0,nt,bs=matin->rmap->bs,mbs=oldmat->mbs;
2596:   PetscScalar    *array;

2599:   *newmat = 0;

2601:   MatCreate(PetscObjectComm((PetscObject)matin),&mat);
2602:   MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);
2603:   MatSetType(mat,((PetscObject)matin)->type_name);
2604:   PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));
2605:   PetscLayoutReference(matin->rmap,&mat->rmap);
2606:   PetscLayoutReference(matin->cmap,&mat->cmap);

2608:   mat->factortype   = matin->factortype;
2609:   mat->preallocated = PETSC_TRUE;
2610:   mat->assembled    = PETSC_TRUE;
2611:   mat->insertmode   = NOT_SET_VALUES;

2613:   a      = (Mat_MPISBAIJ*)mat->data;
2614:   a->bs2 = oldmat->bs2;
2615:   a->mbs = oldmat->mbs;
2616:   a->nbs = oldmat->nbs;
2617:   a->Mbs = oldmat->Mbs;
2618:   a->Nbs = oldmat->Nbs;


2621:   a->size         = oldmat->size;
2622:   a->rank         = oldmat->rank;
2623:   a->donotstash   = oldmat->donotstash;
2624:   a->roworiented  = oldmat->roworiented;
2625:   a->rowindices   = 0;
2626:   a->rowvalues    = 0;
2627:   a->getrowactive = PETSC_FALSE;
2628:   a->barray       = 0;
2629:   a->rstartbs     = oldmat->rstartbs;
2630:   a->rendbs       = oldmat->rendbs;
2631:   a->cstartbs     = oldmat->cstartbs;
2632:   a->cendbs       = oldmat->cendbs;

2634:   /* hash table stuff */
2635:   a->ht           = 0;
2636:   a->hd           = 0;
2637:   a->ht_size      = 0;
2638:   a->ht_flag      = oldmat->ht_flag;
2639:   a->ht_fact      = oldmat->ht_fact;
2640:   a->ht_total_ct  = 0;
2641:   a->ht_insert_ct = 0;

2643:   PetscMemcpy(a->rangebs,oldmat->rangebs,(a->size+2)*sizeof(PetscInt));
2644:   if (oldmat->colmap) {
2645: #if defined(PETSC_USE_CTABLE)
2646:     PetscTableCreateCopy(oldmat->colmap,&a->colmap);
2647: #else
2648:     PetscMalloc1(a->Nbs,&a->colmap);
2649:     PetscLogObjectMemory((PetscObject)mat,(a->Nbs)*sizeof(PetscInt));
2650:     PetscMemcpy(a->colmap,oldmat->colmap,(a->Nbs)*sizeof(PetscInt));
2651: #endif
2652:   } else a->colmap = 0;

2654:   if (oldmat->garray && (len = ((Mat_SeqBAIJ*)(oldmat->B->data))->nbs)) {
2655:     PetscMalloc1(len,&a->garray);
2656:     PetscLogObjectMemory((PetscObject)mat,len*sizeof(PetscInt));
2657:     PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));
2658:   } else a->garray = 0;

2660:   MatStashCreate_Private(PetscObjectComm((PetscObject)matin),matin->rmap->bs,&mat->bstash);
2661:   VecDuplicate(oldmat->lvec,&a->lvec);
2662:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->lvec);
2663:   VecScatterCopy(oldmat->Mvctx,&a->Mvctx);
2664:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->Mvctx);

2666:   VecDuplicate(oldmat->slvec0,&a->slvec0);
2667:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec0);
2668:   VecDuplicate(oldmat->slvec1,&a->slvec1);
2669:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec1);

2671:   VecGetLocalSize(a->slvec1,&nt);
2672:   VecGetArray(a->slvec1,&array);
2673:   VecCreateSeqWithArray(PETSC_COMM_SELF,1,bs*mbs,array,&a->slvec1a);
2674:   VecCreateSeqWithArray(PETSC_COMM_SELF,1,nt-bs*mbs,array+bs*mbs,&a->slvec1b);
2675:   VecRestoreArray(a->slvec1,&array);
2676:   VecGetArray(a->slvec0,&array);
2677:   VecCreateSeqWithArray(PETSC_COMM_SELF,1,nt-bs*mbs,array+bs*mbs,&a->slvec0b);
2678:   VecRestoreArray(a->slvec0,&array);
2679:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec0);
2680:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec1);
2681:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec0b);
2682:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec1a);
2683:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec1b);

2685:   /*  VecScatterCopy(oldmat->sMvctx,&a->sMvctx); - not written yet, replaced by the lazy trick: */
2686:   PetscObjectReference((PetscObject)oldmat->sMvctx);
2687:   a->sMvctx = oldmat->sMvctx;
2688:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->sMvctx);

2690:   MatDuplicate(oldmat->A,cpvalues,&a->A);
2691:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->A);
2692:   MatDuplicate(oldmat->B,cpvalues,&a->B);
2693:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->B);
2694:   PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);
2695:   *newmat = mat;
2696:   return(0);
2697: }

2701: PetscErrorCode MatLoad_MPISBAIJ(Mat newmat,PetscViewer viewer)
2702: {
2704:   PetscInt       i,nz,j,rstart,rend;
2705:   PetscScalar    *vals,*buf;
2706:   MPI_Comm       comm;
2707:   MPI_Status     status;
2708:   PetscMPIInt    rank,size,tag = ((PetscObject)viewer)->tag,*sndcounts = 0,*browners,maxnz,*rowners,mmbs;
2709:   PetscInt       header[4],*rowlengths = 0,M,N,m,*cols,*locrowlens;
2710:   PetscInt       *procsnz = 0,jj,*mycols,*ibuf;
2711:   PetscInt       bs = newmat->rmap->bs,Mbs,mbs,extra_rows;
2712:   PetscInt       *dlens,*odlens,*mask,*masked1,*masked2,rowcount,odcount;
2713:   PetscInt       dcount,kmax,k,nzcount,tmp;
2714:   int            fd;

2717:   /* force binary viewer to load .info file if it has not yet done so */
2718:   PetscViewerSetUp(viewer);
2719:   PetscObjectGetComm((PetscObject)viewer,&comm);
2720:   PetscOptionsBegin(comm,NULL,"Options for loading MPISBAIJ matrix 2","Mat");
2721:   PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);
2722:   PetscOptionsEnd();
2723:   if (bs < 0) bs = 1;

2725:   MPI_Comm_size(comm,&size);
2726:   MPI_Comm_rank(comm,&rank);
2727:   PetscViewerBinaryGetDescriptor(viewer,&fd);
2728:   if (!rank) {
2729:     PetscBinaryRead(fd,(char*)header,4,PETSC_INT);
2730:     if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object");
2731:     if (header[3] < 0) SETERRQ(PetscObjectComm((PetscObject)newmat),PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format, cannot load as MPISBAIJ");
2732:   }

2734:   MPI_Bcast(header+1,3,MPIU_INT,0,comm);
2735:   M    = header[1];
2736:   N    = header[2];

2738:   /* If global sizes are set, check if they are consistent with that given in the file */
2739:   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);
2740:   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);

2742:   if (M != N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Can only do square matrices");

2744:   /*
2745:      This code adds extra rows to make sure the number of rows is
2746:      divisible by the blocksize
2747:   */
2748:   Mbs        = M/bs;
2749:   extra_rows = bs - M + bs*(Mbs);
2750:   if (extra_rows == bs) extra_rows = 0;
2751:   else                  Mbs++;
2752:   if (extra_rows &&!rank) {
2753:     PetscInfo(viewer,"Padding loaded matrix to match blocksize\n");
2754:   }

2756:   /* determine ownership of all rows */
2757:   if (newmat->rmap->n < 0) { /* PETSC_DECIDE */
2758:     mbs = Mbs/size + ((Mbs % size) > rank);
2759:     m   = mbs*bs;
2760:   } else { /* User Set */
2761:     m   = newmat->rmap->n;
2762:     mbs = m/bs;
2763:   }
2764:   PetscMalloc2(size+1,&rowners,size+1,&browners);
2765:   PetscMPIIntCast(mbs,&mmbs);
2766:   MPI_Allgather(&mmbs,1,MPI_INT,rowners+1,1,MPI_INT,comm);
2767:   rowners[0] = 0;
2768:   for (i=2; i<=size; i++) rowners[i] += rowners[i-1];
2769:   for (i=0; i<=size; i++) browners[i] = rowners[i]*bs;
2770:   rstart = rowners[rank];
2771:   rend   = rowners[rank+1];

2773:   /* distribute row lengths to all processors */
2774:   PetscMalloc1((rend-rstart)*bs,&locrowlens);
2775:   if (!rank) {
2776:     PetscMalloc1(M+extra_rows,&rowlengths);
2777:     PetscBinaryRead(fd,rowlengths,M,PETSC_INT);
2778:     for (i=0; i<extra_rows; i++) rowlengths[M+i] = 1;
2779:     PetscMalloc1(size,&sndcounts);
2780:     for (i=0; i<size; i++) sndcounts[i] = browners[i+1] - browners[i];
2781:     MPI_Scatterv(rowlengths,sndcounts,browners,MPIU_INT,locrowlens,(rend-rstart)*bs,MPIU_INT,0,comm);
2782:     PetscFree(sndcounts);
2783:   } else {
2784:     MPI_Scatterv(0,0,0,MPIU_INT,locrowlens,(rend-rstart)*bs,MPIU_INT,0,comm);
2785:   }

2787:   if (!rank) {   /* procs[0] */
2788:     /* calculate the number of nonzeros on each processor */
2789:     PetscMalloc1(size,&procsnz);
2790:     PetscMemzero(procsnz,size*sizeof(PetscInt));
2791:     for (i=0; i<size; i++) {
2792:       for (j=rowners[i]*bs; j< rowners[i+1]*bs; j++) {
2793:         procsnz[i] += rowlengths[j];
2794:       }
2795:     }
2796:     PetscFree(rowlengths);

2798:     /* determine max buffer needed and allocate it */
2799:     maxnz = 0;
2800:     for (i=0; i<size; i++) {
2801:       maxnz = PetscMax(maxnz,procsnz[i]);
2802:     }
2803:     PetscMalloc1(maxnz,&cols);

2805:     /* read in my part of the matrix column indices  */
2806:     nz     = procsnz[0];
2807:     PetscMalloc1(nz,&ibuf);
2808:     mycols = ibuf;
2809:     if (size == 1) nz -= extra_rows;
2810:     PetscBinaryRead(fd,mycols,nz,PETSC_INT);
2811:     if (size == 1) {
2812:       for (i=0; i< extra_rows; i++) mycols[nz+i] = M+i;
2813:     }

2815:     /* read in every ones (except the last) and ship off */
2816:     for (i=1; i<size-1; i++) {
2817:       nz   = procsnz[i];
2818:       PetscBinaryRead(fd,cols,nz,PETSC_INT);
2819:       MPI_Send(cols,nz,MPIU_INT,i,tag,comm);
2820:     }
2821:     /* read in the stuff for the last proc */
2822:     if (size != 1) {
2823:       nz   = procsnz[size-1] - extra_rows;  /* the extra rows are not on the disk */
2824:       PetscBinaryRead(fd,cols,nz,PETSC_INT);
2825:       for (i=0; i<extra_rows; i++) cols[nz+i] = M+i;
2826:       MPI_Send(cols,nz+extra_rows,MPIU_INT,size-1,tag,comm);
2827:     }
2828:     PetscFree(cols);
2829:   } else {  /* procs[i], i>0 */
2830:     /* determine buffer space needed for message */
2831:     nz = 0;
2832:     for (i=0; i<m; i++) nz += locrowlens[i];
2833:     PetscMalloc1(nz,&ibuf);
2834:     mycols = ibuf;
2835:     /* receive message of column indices*/
2836:     MPI_Recv(mycols,nz,MPIU_INT,0,tag,comm,&status);
2837:     MPI_Get_count(&status,MPIU_INT,&maxnz);
2838:     if (maxnz != nz) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file");
2839:   }

2841:   /* loop over local rows, determining number of off diagonal entries */
2842:   PetscMalloc2(rend-rstart,&dlens,rend-rstart,&odlens);
2843:   PetscMalloc3(Mbs,&mask,Mbs,&masked1,Mbs,&masked2);
2844:   PetscMemzero(mask,Mbs*sizeof(PetscInt));
2845:   PetscMemzero(masked1,Mbs*sizeof(PetscInt));
2846:   PetscMemzero(masked2,Mbs*sizeof(PetscInt));
2847:   rowcount = 0;
2848:   nzcount  = 0;
2849:   for (i=0; i<mbs; i++) {
2850:     dcount  = 0;
2851:     odcount = 0;
2852:     for (j=0; j<bs; j++) {
2853:       kmax = locrowlens[rowcount];
2854:       for (k=0; k<kmax; k++) {
2855:         tmp = mycols[nzcount++]/bs; /* block col. index */
2856:         if (!mask[tmp]) {
2857:           mask[tmp] = 1;
2858:           if (tmp < rstart || tmp >= rend) masked2[odcount++] = tmp; /* entry in off-diag portion */
2859:           else masked1[dcount++] = tmp; /* entry in diag portion */
2860:         }
2861:       }
2862:       rowcount++;
2863:     }

2865:     dlens[i]  = dcount;  /* d_nzz[i] */
2866:     odlens[i] = odcount; /* o_nzz[i] */

2868:     /* zero out the mask elements we set */
2869:     for (j=0; j<dcount; j++) mask[masked1[j]] = 0;
2870:     for (j=0; j<odcount; j++) mask[masked2[j]] = 0;
2871:   }
2872:   MatSetSizes(newmat,m,m,M+extra_rows,N+extra_rows);
2873:   MatMPISBAIJSetPreallocation(newmat,bs,0,dlens,0,odlens);
2874:   MatSetOption(newmat,MAT_IGNORE_LOWER_TRIANGULAR,PETSC_TRUE);

2876:   if (!rank) {
2877:     PetscMalloc1(maxnz,&buf);
2878:     /* read in my part of the matrix numerical values  */
2879:     nz     = procsnz[0];
2880:     vals   = buf;
2881:     mycols = ibuf;
2882:     if (size == 1) nz -= extra_rows;
2883:     PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);
2884:     if (size == 1) {
2885:       for (i=0; i< extra_rows; i++) vals[nz+i] = 1.0;
2886:     }

2888:     /* insert into matrix */
2889:     jj = rstart*bs;
2890:     for (i=0; i<m; i++) {
2891:       MatSetValues(newmat,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);
2892:       mycols += locrowlens[i];
2893:       vals   += locrowlens[i];
2894:       jj++;
2895:     }

2897:     /* read in other processors (except the last one) and ship out */
2898:     for (i=1; i<size-1; i++) {
2899:       nz   = procsnz[i];
2900:       vals = buf;
2901:       PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);
2902:       MPI_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newmat)->tag,comm);
2903:     }
2904:     /* the last proc */
2905:     if (size != 1) {
2906:       nz   = procsnz[i] - extra_rows;
2907:       vals = buf;
2908:       PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);
2909:       for (i=0; i<extra_rows; i++) vals[nz+i] = 1.0;
2910:       MPI_Send(vals,nz+extra_rows,MPIU_SCALAR,size-1,((PetscObject)newmat)->tag,comm);
2911:     }
2912:     PetscFree(procsnz);

2914:   } else {
2915:     /* receive numeric values */
2916:     PetscMalloc1(nz,&buf);

2918:     /* receive message of values*/
2919:     vals   = buf;
2920:     mycols = ibuf;
2921:     MPI_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newmat)->tag,comm,&status);
2922:     MPI_Get_count(&status,MPIU_SCALAR,&maxnz);
2923:     if (maxnz != nz) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file");

2925:     /* insert into matrix */
2926:     jj = rstart*bs;
2927:     for (i=0; i<m; i++) {
2928:       MatSetValues_MPISBAIJ(newmat,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);
2929:       mycols += locrowlens[i];
2930:       vals   += locrowlens[i];
2931:       jj++;
2932:     }
2933:   }

2935:   PetscFree(locrowlens);
2936:   PetscFree(buf);
2937:   PetscFree(ibuf);
2938:   PetscFree2(rowners,browners);
2939:   PetscFree2(dlens,odlens);
2940:   PetscFree3(mask,masked1,masked2);
2941:   MatAssemblyBegin(newmat,MAT_FINAL_ASSEMBLY);
2942:   MatAssemblyEnd(newmat,MAT_FINAL_ASSEMBLY);
2943:   return(0);
2944: }

2948: /*XXXXX@
2949:    MatMPISBAIJSetHashTableFactor - Sets the factor required to compute the size of the HashTable.

2951:    Input Parameters:
2952: .  mat  - the matrix
2953: .  fact - factor

2955:    Not Collective on Mat, each process can have a different hash factor

2957:    Level: advanced

2959:   Notes:
2960:    This can also be set by the command line option: -mat_use_hash_table fact

2962: .keywords: matrix, hashtable, factor, HT

2964: .seealso: MatSetOption()
2965: @XXXXX*/


2970: PetscErrorCode MatGetRowMaxAbs_MPISBAIJ(Mat A,Vec v,PetscInt idx[])
2971: {
2972:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;
2973:   Mat_SeqBAIJ    *b = (Mat_SeqBAIJ*)(a->B)->data;
2974:   PetscReal      atmp;
2975:   PetscReal      *work,*svalues,*rvalues;
2977:   PetscInt       i,bs,mbs,*bi,*bj,brow,j,ncols,krow,kcol,col,row,Mbs,bcol;
2978:   PetscMPIInt    rank,size;
2979:   PetscInt       *rowners_bs,dest,count,source;
2980:   PetscScalar    *va;
2981:   MatScalar      *ba;
2982:   MPI_Status     stat;

2985:   if (idx) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Send email to petsc-maint@mcs.anl.gov");
2986:   MatGetRowMaxAbs(a->A,v,NULL);
2987:   VecGetArray(v,&va);

2989:   MPI_Comm_size(PetscObjectComm((PetscObject)A),&size);
2990:   MPI_Comm_rank(PetscObjectComm((PetscObject)A),&rank);

2992:   bs  = A->rmap->bs;
2993:   mbs = a->mbs;
2994:   Mbs = a->Mbs;
2995:   ba  = b->a;
2996:   bi  = b->i;
2997:   bj  = b->j;

2999:   /* find ownerships */
3000:   rowners_bs = A->rmap->range;

3002:   /* each proc creates an array to be distributed */
3003:   PetscMalloc1(bs*Mbs,&work);
3004:   PetscMemzero(work,bs*Mbs*sizeof(PetscReal));

3006:   /* row_max for B */
3007:   if (rank != size-1) {
3008:     for (i=0; i<mbs; i++) {
3009:       ncols = bi[1] - bi[0]; bi++;
3010:       brow  = bs*i;
3011:       for (j=0; j<ncols; j++) {
3012:         bcol = bs*(*bj);
3013:         for (kcol=0; kcol<bs; kcol++) {
3014:           col  = bcol + kcol;                /* local col index */
3015:           col += rowners_bs[rank+1];      /* global col index */
3016:           for (krow=0; krow<bs; krow++) {
3017:             atmp = PetscAbsScalar(*ba); ba++;
3018:             row  = brow + krow;   /* local row index */
3019:             if (PetscRealPart(va[row]) < atmp) va[row] = atmp;
3020:             if (work[col] < atmp) work[col] = atmp;
3021:           }
3022:         }
3023:         bj++;
3024:       }
3025:     }

3027:     /* send values to its owners */
3028:     for (dest=rank+1; dest<size; dest++) {
3029:       svalues = work + rowners_bs[dest];
3030:       count   = rowners_bs[dest+1]-rowners_bs[dest];
3031:       MPI_Send(svalues,count,MPIU_REAL,dest,rank,PetscObjectComm((PetscObject)A));
3032:     }
3033:   }

3035:   /* receive values */
3036:   if (rank) {
3037:     rvalues = work;
3038:     count   = rowners_bs[rank+1]-rowners_bs[rank];
3039:     for (source=0; source<rank; source++) {
3040:       MPI_Recv(rvalues,count,MPIU_REAL,MPI_ANY_SOURCE,MPI_ANY_TAG,PetscObjectComm((PetscObject)A),&stat);
3041:       /* process values */
3042:       for (i=0; i<count; i++) {
3043:         if (PetscRealPart(va[i]) < rvalues[i]) va[i] = rvalues[i];
3044:       }
3045:     }
3046:   }

3048:   VecRestoreArray(v,&va);
3049:   PetscFree(work);
3050:   return(0);
3051: }

3055: PetscErrorCode MatSOR_MPISBAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx)
3056: {
3057:   Mat_MPISBAIJ      *mat = (Mat_MPISBAIJ*)matin->data;
3058:   PetscErrorCode    ierr;
3059:   PetscInt          mbs=mat->mbs,bs=matin->rmap->bs;
3060:   PetscScalar       *x,*ptr,*from;
3061:   Vec               bb1;
3062:   const PetscScalar *b;

3065:   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);
3066:   if (bs > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"SSOR for block size > 1 is not yet implemented");

3068:   if (flag == SOR_APPLY_UPPER) {
3069:     (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
3070:     return(0);
3071:   }

3073:   if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) {
3074:     if (flag & SOR_ZERO_INITIAL_GUESS) {
3075:       (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,lits,xx);
3076:       its--;
3077:     }

3079:     VecDuplicate(bb,&bb1);
3080:     while (its--) {

3082:       /* lower triangular part: slvec0b = - B^T*xx */
3083:       (*mat->B->ops->multtranspose)(mat->B,xx,mat->slvec0b);

3085:       /* copy xx into slvec0a */
3086:       VecGetArray(mat->slvec0,&ptr);
3087:       VecGetArray(xx,&x);
3088:       PetscMemcpy(ptr,x,bs*mbs*sizeof(MatScalar));
3089:       VecRestoreArray(mat->slvec0,&ptr);

3091:       VecScale(mat->slvec0,-1.0);

3093:       /* copy bb into slvec1a */
3094:       VecGetArray(mat->slvec1,&ptr);
3095:       VecGetArrayRead(bb,&b);
3096:       PetscMemcpy(ptr,b,bs*mbs*sizeof(MatScalar));
3097:       VecRestoreArray(mat->slvec1,&ptr);

3099:       /* set slvec1b = 0 */
3100:       VecSet(mat->slvec1b,0.0);

3102:       VecScatterBegin(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);
3103:       VecRestoreArray(xx,&x);
3104:       VecRestoreArrayRead(bb,&b);
3105:       VecScatterEnd(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);

3107:       /* upper triangular part: bb1 = bb1 - B*x */
3108:       (*mat->B->ops->multadd)(mat->B,mat->slvec1b,mat->slvec1a,bb1);

3110:       /* local diagonal sweep */
3111:       (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,lits,xx);
3112:     }
3113:     VecDestroy(&bb1);
3114:   } else if ((flag & SOR_LOCAL_FORWARD_SWEEP) && (its == 1) && (flag & SOR_ZERO_INITIAL_GUESS)) {
3115:     (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
3116:   } else if ((flag & SOR_LOCAL_BACKWARD_SWEEP) && (its == 1) && (flag & SOR_ZERO_INITIAL_GUESS)) {
3117:     (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
3118:   } else if (flag & SOR_EISENSTAT) {
3119:     Vec               xx1;
3120:     PetscBool         hasop;
3121:     const PetscScalar *diag;
3122:     PetscScalar       *sl,scale = (omega - 2.0)/omega;
3123:     PetscInt          i,n;

3125:     if (!mat->xx1) {
3126:       VecDuplicate(bb,&mat->xx1);
3127:       VecDuplicate(bb,&mat->bb1);
3128:     }
3129:     xx1 = mat->xx1;
3130:     bb1 = mat->bb1;

3132:     (*mat->A->ops->sor)(mat->A,bb,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_BACKWARD_SWEEP),fshift,lits,1,xx);

3134:     if (!mat->diag) {
3135:       /* this is wrong for same matrix with new nonzero values */
3136:       MatCreateVecs(matin,&mat->diag,NULL);
3137:       MatGetDiagonal(matin,mat->diag);
3138:     }
3139:     MatHasOperation(matin,MATOP_MULT_DIAGONAL_BLOCK,&hasop);

3141:     if (hasop) {
3142:       MatMultDiagonalBlock(matin,xx,bb1);
3143:       VecAYPX(mat->slvec1a,scale,bb);
3144:     } else {
3145:       /*
3146:           These two lines are replaced by code that may be a bit faster for a good compiler
3147:       VecPointwiseMult(mat->slvec1a,mat->diag,xx);
3148:       VecAYPX(mat->slvec1a,scale,bb);
3149:       */
3150:       VecGetArray(mat->slvec1a,&sl);
3151:       VecGetArrayRead(mat->diag,&diag);
3152:       VecGetArrayRead(bb,&b);
3153:       VecGetArray(xx,&x);
3154:       VecGetLocalSize(xx,&n);
3155:       if (omega == 1.0) {
3156:         for (i=0; i<n; i++) sl[i] = b[i] - diag[i]*x[i];
3157:         PetscLogFlops(2.0*n);
3158:       } else {
3159:         for (i=0; i<n; i++) sl[i] = b[i] + scale*diag[i]*x[i];
3160:         PetscLogFlops(3.0*n);
3161:       }
3162:       VecRestoreArray(mat->slvec1a,&sl);
3163:       VecRestoreArrayRead(mat->diag,&diag);
3164:       VecRestoreArrayRead(bb,&b);
3165:       VecRestoreArray(xx,&x);
3166:     }

3168:     /* multiply off-diagonal portion of matrix */
3169:     VecSet(mat->slvec1b,0.0);
3170:     (*mat->B->ops->multtranspose)(mat->B,xx,mat->slvec0b);
3171:     VecGetArray(mat->slvec0,&from);
3172:     VecGetArray(xx,&x);
3173:     PetscMemcpy(from,x,bs*mbs*sizeof(MatScalar));
3174:     VecRestoreArray(mat->slvec0,&from);
3175:     VecRestoreArray(xx,&x);
3176:     VecScatterBegin(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);
3177:     VecScatterEnd(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);
3178:     (*mat->B->ops->multadd)(mat->B,mat->slvec1b,mat->slvec1a,mat->slvec1a);

3180:     /* local sweep */
3181:     (*mat->A->ops->sor)(mat->A,mat->slvec1a,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_FORWARD_SWEEP),fshift,lits,1,xx1);
3182:     VecAXPY(xx,1.0,xx1);
3183:   } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"MatSORType is not supported for SBAIJ matrix format");
3184:   return(0);
3185: }

3189: PetscErrorCode MatSOR_MPISBAIJ_2comm(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx)
3190: {
3191:   Mat_MPISBAIJ   *mat = (Mat_MPISBAIJ*)matin->data;
3193:   Vec            lvec1,bb1;

3196:   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);
3197:   if (matin->rmap->bs > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"SSOR for block size > 1 is not yet implemented");

3199:   if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) {
3200:     if (flag & SOR_ZERO_INITIAL_GUESS) {
3201:       (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,lits,xx);
3202:       its--;
3203:     }

3205:     VecDuplicate(mat->lvec,&lvec1);
3206:     VecDuplicate(bb,&bb1);
3207:     while (its--) {
3208:       VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);

3210:       /* lower diagonal part: bb1 = bb - B^T*xx */
3211:       (*mat->B->ops->multtranspose)(mat->B,xx,lvec1);
3212:       VecScale(lvec1,-1.0);

3214:       VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
3215:       VecCopy(bb,bb1);
3216:       VecScatterBegin(mat->Mvctx,lvec1,bb1,ADD_VALUES,SCATTER_REVERSE);

3218:       /* upper diagonal part: bb1 = bb1 - B*x */
3219:       VecScale(mat->lvec,-1.0);
3220:       (*mat->B->ops->multadd)(mat->B,mat->lvec,bb1,bb1);

3222:       VecScatterEnd(mat->Mvctx,lvec1,bb1,ADD_VALUES,SCATTER_REVERSE);

3224:       /* diagonal sweep */
3225:       (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,lits,xx);
3226:     }
3227:     VecDestroy(&lvec1);
3228:     VecDestroy(&bb1);
3229:   } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"MatSORType is not supported for SBAIJ matrix format");
3230:   return(0);
3231: }

3235: /*@
3236:      MatCreateMPISBAIJWithArrays - creates a MPI SBAIJ matrix using arrays that contain in standard
3237:          CSR format the local rows.

3239:    Collective on MPI_Comm

3241:    Input Parameters:
3242: +  comm - MPI communicator
3243: .  bs - the block size, only a block size of 1 is supported
3244: .  m - number of local rows (Cannot be PETSC_DECIDE)
3245: .  n - This value should be the same as the local size used in creating the
3246:        x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have
3247:        calculated if N is given) For square matrices n is almost always m.
3248: .  M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
3249: .  N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
3250: .   i - row indices
3251: .   j - column indices
3252: -   a - matrix values

3254:    Output Parameter:
3255: .   mat - the matrix

3257:    Level: intermediate

3259:    Notes:
3260:        The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc;
3261:      thus you CANNOT change the matrix entries by changing the values of a[] after you have
3262:      called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays.

3264:        The i and j indices are 0 based, and i indices are indices corresponding to the local j array.

3266: .keywords: matrix, aij, compressed row, sparse, parallel

3268: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(),
3269:           MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays()
3270: @*/
3271: 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)
3272: {


3277:   if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0");
3278:   if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative");
3279:   MatCreate(comm,mat);
3280:   MatSetSizes(*mat,m,n,M,N);
3281:   MatSetType(*mat,MATMPISBAIJ);
3282:   MatMPISBAIJSetPreallocationCSR(*mat,bs,i,j,a);
3283:   return(0);
3284: }


3289: /*@C
3290:    MatMPISBAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in BAIJ format
3291:    (the default parallel PETSc format).

3293:    Collective on MPI_Comm

3295:    Input Parameters:
3296: +  B - the matrix
3297: .  bs - the block size
3298: .  i - the indices into j for the start of each local row (starts with zero)
3299: .  j - the column indices for each local row (starts with zero) these must be sorted for each row
3300: -  v - optional values in the matrix

3302:    Level: developer

3304: .keywords: matrix, aij, compressed row, sparse, parallel

3306: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIBAIJSetPreallocation(), MatCreateAIJ(), MPIAIJ
3307: @*/
3308: PetscErrorCode  MatMPISBAIJSetPreallocationCSR(Mat B,PetscInt bs,const PetscInt i[],const PetscInt j[], const PetscScalar v[])
3309: {

3313:   PetscTryMethod(B,"MatMPISBAIJSetPreallocationCSR_C",(Mat,PetscInt,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,bs,i,j,v));
3314:   return(0);
3315: }

3319: PetscErrorCode MatCreateMPIMatConcatenateSeqMat_MPISBAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat)
3320: {
3322:   PetscInt       m,N,i,rstart,nnz,Ii,bs,cbs;
3323:   PetscInt       *indx;
3324:   PetscScalar    *values;

3327:   MatGetSize(inmat,&m,&N);
3328:   if (scall == MAT_INITIAL_MATRIX) { /* symbolic phase */
3329:     Mat_SeqSBAIJ   *a = (Mat_SeqSBAIJ*)inmat->data;
3330:     PetscInt       *dnz,*onz,sum,bs,cbs,mbs,Nbs;
3331:     PetscInt       *bindx,rmax=a->rmax,j;
3332: 
3333:     MatGetBlockSizes(inmat,&bs,&cbs);
3334:     mbs = m/bs; Nbs = N/cbs;
3335:     if (n == PETSC_DECIDE) {
3336:       PetscSplitOwnership(comm,&n,&Nbs);
3337:     }
3338:     /* Check sum(n) = Nbs */
3339:     MPIU_Allreduce(&n,&sum,1,MPIU_INT,MPI_SUM,comm);
3340:     if (sum != Nbs) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Sum of local columns != global columns %d",Nbs);

3342:     MPI_Scan(&mbs, &rstart,1,MPIU_INT,MPI_SUM,comm);
3343:     rstart -= mbs;

3345:     PetscMalloc1(rmax,&bindx);
3346:     MatPreallocateInitialize(comm,mbs,n,dnz,onz);
3347:     MatSetOption(inmat,MAT_GETROW_UPPERTRIANGULAR,PETSC_TRUE);
3348:     for (i=0; i<mbs; i++) {
3349:       MatGetRow_SeqSBAIJ(inmat,i*bs,&nnz,&indx,NULL); /* non-blocked nnz and indx */
3350:       nnz = nnz/bs;
3351:       for (j=0; j<nnz; j++) bindx[j] = indx[j*bs]/bs;
3352:       MatPreallocateSet(i+rstart,nnz,bindx,dnz,onz);
3353:       MatRestoreRow_SeqSBAIJ(inmat,i*bs,&nnz,&indx,NULL);
3354:     }
3355:     MatSetOption(inmat,MAT_GETROW_UPPERTRIANGULAR,PETSC_FALSE);
3356:     PetscFree(bindx);

3358:     MatCreate(comm,outmat);
3359:     MatSetSizes(*outmat,m,n*bs,PETSC_DETERMINE,PETSC_DETERMINE);
3360:     MatSetBlockSizes(*outmat,bs,cbs);
3361:     MatSetType(*outmat,MATMPISBAIJ);
3362:     MatMPISBAIJSetPreallocation(*outmat,bs,0,dnz,0,onz);
3363:     MatPreallocateFinalize(dnz,onz);
3364:   }
3365: 
3366:   /* numeric phase */
3367:   MatGetBlockSizes(inmat,&bs,&cbs);
3368:   MatGetOwnershipRange(*outmat,&rstart,NULL);

3370:   MatSetOption(inmat,MAT_GETROW_UPPERTRIANGULAR,PETSC_TRUE);
3371:   for (i=0; i<m; i++) {
3372:     MatGetRow_SeqSBAIJ(inmat,i,&nnz,&indx,&values);
3373:     Ii   = i + rstart;
3374:     MatSetValues(*outmat,1,&Ii,nnz,indx,values,INSERT_VALUES);
3375:     MatRestoreRow_SeqSBAIJ(inmat,i,&nnz,&indx,&values);
3376:   }
3377:   MatSetOption(inmat,MAT_GETROW_UPPERTRIANGULAR,PETSC_FALSE);
3378:   MatAssemblyBegin(*outmat,MAT_FINAL_ASSEMBLY);
3379:   MatAssemblyEnd(*outmat,MAT_FINAL_ASSEMBLY);
3380:   return(0);
3381: }