Actual source code: mpisbaij.c

petsc-master 2019-11-13
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  2:  #include <../src/mat/impls/baij/mpi/mpibaij.h>
  3:  #include <../src/mat/impls/sbaij/mpi/mpisbaij.h>
  4:  #include <../src/mat/impls/sbaij/seq/sbaij.h>
  5:  #include <petscblaslapack.h>

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

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

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

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

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

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

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

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

 96:     MatGetRow(A,r,&ncols,&row,&vals);
 97:     MatSetValues(B,1,&r,ncols,row,vals,INSERT_VALUES);
 98:     MatSetValues(B,ncols,row,1,&r,vals,INSERT_VALUES);
 99:     MatRestoreRow(A,r,&ncols,&row,&vals);
100:   }
101:   MatRestoreRowUpperTriangular(A);
102:   MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
103:   MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);

105:   if (reuse == MAT_INPLACE_MATRIX) {
106:     MatHeaderReplace(A,&B);
107:   } else {
108:     *newmat = B;
109:   }
110:   return(0);
111: }

113: PetscErrorCode  MatStoreValues_MPISBAIJ(Mat mat)
114: {
115:   Mat_MPISBAIJ   *aij = (Mat_MPISBAIJ*)mat->data;

119:   MatStoreValues(aij->A);
120:   MatStoreValues(aij->B);
121:   return(0);
122: }

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

130:   MatRetrieveValues(aij->A);
131:   MatRetrieveValues(aij->B);
132:   return(0);
133: }

135: #define  MatSetValues_SeqSBAIJ_A_Private(row,col,value,addv,orow,ocol)      \
136:   { \
137:     brow = row/bs;  \
138:     rp   = aj + ai[brow]; ap = aa + bs2*ai[brow]; \
139:     rmax = aimax[brow]; nrow = ailen[brow]; \
140:     bcol = col/bs; \
141:     ridx = row % bs; cidx = col % bs; \
142:     low  = 0; high = nrow; \
143:     while (high-low > 3) { \
144:       t = (low+high)/2; \
145:       if (rp[t] > bcol) high = t; \
146:       else              low  = t; \
147:     } \
148:     for (_i=low; _i<high; _i++) { \
149:       if (rp[_i] > bcol) break; \
150:       if (rp[_i] == bcol) { \
151:         bap = ap + bs2*_i + bs*cidx + ridx; \
152:         if (addv == ADD_VALUES) *bap += value;  \
153:         else                    *bap  = value;  \
154:         goto a_noinsert; \
155:       } \
156:     } \
157:     if (a->nonew == 1) goto a_noinsert; \
158:     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); \
159:     MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,brow,bcol,rmax,aa,ai,aj,rp,ap,aimax,a->nonew,MatScalar); \
160:     N = nrow++ - 1;  \
161:     /* shift up all the later entries in this row */ \
162:     PetscArraymove(rp+_i+1,rp+_i,N-_i+1); \
163:     PetscArraymove(ap+bs2*(_i+1),ap+bs2*_i,bs2*(N-_i+1)); \
164:     PetscArrayzero(ap+bs2*_i,bs2);  \
165:     rp[_i]                      = bcol;  \
166:     ap[bs2*_i + bs*cidx + ridx] = value;  \
167:     A->nonzerostate++;\
168: a_noinsert:; \
169:     ailen[brow] = nrow; \
170:   }

172: #define  MatSetValues_SeqSBAIJ_B_Private(row,col,value,addv,orow,ocol) \
173:   { \
174:     brow = row/bs;  \
175:     rp   = bj + bi[brow]; ap = ba + bs2*bi[brow]; \
176:     rmax = bimax[brow]; nrow = bilen[brow]; \
177:     bcol = col/bs; \
178:     ridx = row % bs; cidx = col % bs; \
179:     low  = 0; high = nrow; \
180:     while (high-low > 3) { \
181:       t = (low+high)/2; \
182:       if (rp[t] > bcol) high = t; \
183:       else              low  = t; \
184:     } \
185:     for (_i=low; _i<high; _i++) { \
186:       if (rp[_i] > bcol) break; \
187:       if (rp[_i] == bcol) { \
188:         bap = ap + bs2*_i + bs*cidx + ridx; \
189:         if (addv == ADD_VALUES) *bap += value;  \
190:         else                    *bap  = value;  \
191:         goto b_noinsert; \
192:       } \
193:     } \
194:     if (b->nonew == 1) goto b_noinsert; \
195:     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); \
196:     MatSeqXAIJReallocateAIJ(B,b->mbs,bs2,nrow,brow,bcol,rmax,ba,bi,bj,rp,ap,bimax,b->nonew,MatScalar); \
197:     N = nrow++ - 1;  \
198:     /* shift up all the later entries in this row */ \
199:     PetscArraymove(rp+_i+1,rp+_i,N-_i+1); \
200:     PetscArraymove(ap+bs2*(_i+1),ap+bs2*_i,bs2*(N-_i+1)); \
201:     PetscArrayzero(ap+bs2*_i,bs2); \
202:     rp[_i]                      = bcol;  \
203:     ap[bs2*_i + bs*cidx + ridx] = value;  \
204:     B->nonzerostate++;\
205: b_noinsert:; \
206:     bilen[brow] = nrow; \
207:   }

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

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

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

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

238:   /* for stash */
239:   PetscInt  n_loc, *in_loc = NULL;
240:   MatScalar *v_loc = NULL;

243:   if (!baij->donotstash) {
244:     if (n > baij->n_loc) {
245:       PetscFree(baij->in_loc);
246:       PetscFree(baij->v_loc);
247:       PetscMalloc1(n,&baij->in_loc);
248:       PetscMalloc1(n,&baij->v_loc);

250:       baij->n_loc = n;
251:     }
252:     in_loc = baij->in_loc;
253:     v_loc  = baij->v_loc;
254:   }

256:   for (i=0; i<m; i++) {
257:     if (im[i] < 0) continue;
258: #if defined(PETSC_USE_DEBUG)
259:     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);
260: #endif
261:     if (im[i] >= rstart_orig && im[i] < rend_orig) { /* this processor entry */
262:       row = im[i] - rstart_orig;              /* local row index */
263:       for (j=0; j<n; j++) {
264:         if (im[i]/bs > in[j]/bs) {
265:           if (a->ignore_ltriangular) {
266:             continue;    /* ignore lower triangular blocks */
267:           } 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)");
268:         }
269:         if (in[j] >= cstart_orig && in[j] < cend_orig) {  /* diag entry (A) */
270:           col  = in[j] - cstart_orig;         /* local col index */
271:           brow = row/bs; bcol = col/bs;
272:           if (brow > bcol) continue;  /* ignore lower triangular blocks of A */
273:           if (roworiented) value = v[i*n+j];
274:           else             value = v[i+j*m];
275:           MatSetValues_SeqSBAIJ_A_Private(row,col,value,addv,im[i],in[j]);
276:           /* MatSetValues_SeqBAIJ(baij->A,1,&row,1,&col,&value,addv); */
277:         } else if (in[j] < 0) continue;
278: #if defined(PETSC_USE_DEBUG)
279:         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);
280: #endif
281:         else {  /* off-diag entry (B) */
282:           if (mat->was_assembled) {
283:             if (!baij->colmap) {
284:               MatCreateColmap_MPIBAIJ_Private(mat);
285:             }
286: #if defined(PETSC_USE_CTABLE)
287:             PetscTableFind(baij->colmap,in[j]/bs + 1,&col);
288:             col  = col - 1;
289: #else
290:             col = baij->colmap[in[j]/bs] - 1;
291: #endif
292:             if (col < 0 && !((Mat_SeqSBAIJ*)(baij->A->data))->nonew) {
293:               MatDisAssemble_MPISBAIJ(mat);
294:               col  =  in[j];
295:               /* Reinitialize the variables required by MatSetValues_SeqBAIJ_B_Private() */
296:               B    = baij->B;
297:               b    = (Mat_SeqBAIJ*)(B)->data;
298:               bimax= b->imax;bi=b->i;bilen=b->ilen;bj=b->j;
299:               ba   = b->a;
300:             } else col += in[j]%bs;
301:           } else col = in[j];
302:           if (roworiented) value = v[i*n+j];
303:           else             value = v[i+j*m];
304:           MatSetValues_SeqSBAIJ_B_Private(row,col,value,addv,im[i],in[j]);
305:           /* MatSetValues_SeqBAIJ(baij->B,1,&row,1,&col,&value,addv); */
306:         }
307:       }
308:     } else {  /* off processor entry */
309:       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]);
310:       if (!baij->donotstash) {
311:         mat->assembled = PETSC_FALSE;
312:         n_loc          = 0;
313:         for (j=0; j<n; j++) {
314:           if (im[i]/bs > in[j]/bs) continue; /* ignore lower triangular blocks */
315:           in_loc[n_loc] = in[j];
316:           if (roworiented) {
317:             v_loc[n_loc] = v[i*n+j];
318:           } else {
319:             v_loc[n_loc] = v[j*m+i];
320:           }
321:           n_loc++;
322:         }
323:         MatStashValuesRow_Private(&mat->stash,im[i],n_loc,in_loc,v_loc,PETSC_FALSE);
324:       }
325:     }
326:   }
327:   return(0);
328: }

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

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

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

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

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

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

530:   if (!barray) {
531:     PetscMalloc1(bs2,&barray);
532:     baij->barray = barray;
533:   }

535:   if (roworiented) {
536:     stepval = (n-1)*bs;
537:   } else {
538:     stepval = (m-1)*bs;
539:   }
540:   for (i=0; i<m; i++) {
541:     if (im[i] < 0) continue;
542: #if defined(PETSC_USE_DEBUG)
543:     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);
544: #endif
545:     if (im[i] >= rstart && im[i] < rend) {
546:       row = im[i] - rstart;
547:       for (j=0; j<n; j++) {
548:         if (im[i] > in[j]) {
549:           if (ignore_ltriangular) continue; /* ignore lower triangular blocks */
550:           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)");
551:         }
552:         /* If NumCol = 1 then a copy is not required */
553:         if ((roworiented) && (n == 1)) {
554:           barray = (MatScalar*) v + i*bs2;
555:         } else if ((!roworiented) && (m == 1)) {
556:           barray = (MatScalar*) v + j*bs2;
557:         } else { /* Here a copy is required */
558:           if (roworiented) {
559:             value = v + i*(stepval+bs)*bs + j*bs;
560:           } else {
561:             value = v + j*(stepval+bs)*bs + i*bs;
562:           }
563:           for (ii=0; ii<bs; ii++,value+=stepval) {
564:             for (jj=0; jj<bs; jj++) {
565:               *barray++ = *value++;
566:             }
567:           }
568:           barray -=bs2;
569:         }

571:         if (in[j] >= cstart && in[j] < cend) {
572:           col  = in[j] - cstart;
573:           MatSetValuesBlocked_SeqSBAIJ_Inlined(baij->A,row,col,barray,addv,im[i],in[j]);
574:         } else if (in[j] < 0) continue;
575: #if defined(PETSC_USE_DEBUG)
576:         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);
577: #endif
578:         else {
579:           if (mat->was_assembled) {
580:             if (!baij->colmap) {
581:               MatCreateColmap_MPIBAIJ_Private(mat);
582:             }

584: #if defined(PETSC_USE_DEBUG)
585: #if defined(PETSC_USE_CTABLE)
586:             { PetscInt data;
587:               PetscTableFind(baij->colmap,in[j]+1,&data);
588:               if ((data - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap");
589:             }
590: #else
591:             if ((baij->colmap[in[j]] - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap");
592: #endif
593: #endif
594: #if defined(PETSC_USE_CTABLE)
595:             PetscTableFind(baij->colmap,in[j]+1,&col);
596:             col  = (col - 1)/bs;
597: #else
598:             col = (baij->colmap[in[j]] - 1)/bs;
599: #endif
600:             if (col < 0 && !((Mat_SeqBAIJ*)(baij->A->data))->nonew) {
601:               MatDisAssemble_MPISBAIJ(mat);
602:               col  = in[j];
603:             }
604:           } else col = in[j];
605:           MatSetValuesBlocked_SeqBAIJ_Inlined(baij->B,row,col,barray,addv,im[i],in[j]);
606:         }
607:       }
608:     } else {
609:       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]);
610:       if (!baij->donotstash) {
611:         if (roworiented) {
612:           MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);
613:         } else {
614:           MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);
615:         }
616:       }
617:     }
618:   }
619:   return(0);
620: }

622: PetscErrorCode MatGetValues_MPISBAIJ(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[])
623: {
624:   Mat_MPISBAIJ   *baij = (Mat_MPISBAIJ*)mat->data;
626:   PetscInt       bs       = mat->rmap->bs,i,j,bsrstart = mat->rmap->rstart,bsrend = mat->rmap->rend;
627:   PetscInt       bscstart = mat->cmap->rstart,bscend = mat->cmap->rend,row,col,data;

630:   for (i=0; i<m; i++) {
631:     if (idxm[i] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",idxm[i]); */
632:     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);
633:     if (idxm[i] >= bsrstart && idxm[i] < bsrend) {
634:       row = idxm[i] - bsrstart;
635:       for (j=0; j<n; j++) {
636:         if (idxn[j] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column %D",idxn[j]); */
637:         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);
638:         if (idxn[j] >= bscstart && idxn[j] < bscend) {
639:           col  = idxn[j] - bscstart;
640:           MatGetValues_SeqSBAIJ(baij->A,1,&row,1,&col,v+i*n+j);
641:         } else {
642:           if (!baij->colmap) {
643:             MatCreateColmap_MPIBAIJ_Private(mat);
644:           }
645: #if defined(PETSC_USE_CTABLE)
646:           PetscTableFind(baij->colmap,idxn[j]/bs+1,&data);
647:           data--;
648: #else
649:           data = baij->colmap[idxn[j]/bs]-1;
650: #endif
651:           if ((data < 0) || (baij->garray[data/bs] != idxn[j]/bs)) *(v+i*n+j) = 0.0;
652:           else {
653:             col  = data + idxn[j]%bs;
654:             MatGetValues_SeqBAIJ(baij->B,1,&row,1,&col,v+i*n+j);
655:           }
656:         }
657:       }
658:     } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local values currently supported");
659:   }
660:   return(0);
661: }

663: PetscErrorCode MatNorm_MPISBAIJ(Mat mat,NormType type,PetscReal *norm)
664: {
665:   Mat_MPISBAIJ   *baij = (Mat_MPISBAIJ*)mat->data;
667:   PetscReal      sum[2],*lnorm2;

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

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

738: PetscErrorCode MatAssemblyBegin_MPISBAIJ(Mat mat,MatAssemblyType mode)
739: {
740:   Mat_MPISBAIJ   *baij = (Mat_MPISBAIJ*)mat->data;
742:   PetscInt       nstash,reallocs;

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

747:   MatStashScatterBegin_Private(mat,&mat->stash,mat->rmap->range);
748:   MatStashScatterBegin_Private(mat,&mat->bstash,baij->rangebs);
749:   MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);
750:   PetscInfo2(mat,"Stash has %D entries,uses %D mallocs.\n",nstash,reallocs);
751:   MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);
752:   PetscInfo2(mat,"Block-Stash has %D entries, uses %D mallocs.\n",nstash,reallocs);
753:   return(0);
754: }

756: PetscErrorCode MatAssemblyEnd_MPISBAIJ(Mat mat,MatAssemblyType mode)
757: {
758:   Mat_MPISBAIJ   *baij=(Mat_MPISBAIJ*)mat->data;
759:   Mat_SeqSBAIJ   *a   =(Mat_SeqSBAIJ*)baij->A->data;
761:   PetscInt       i,j,rstart,ncols,flg,bs2=baij->bs2;
762:   PetscInt       *row,*col;
763:   PetscBool      other_disassembled;
764:   PetscMPIInt    n;
765:   PetscBool      r1,r2,r3;
766:   MatScalar      *val;

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

775:       for (i=0; i<n;) {
776:         /* Now identify the consecutive vals belonging to the same row */
777:         for (j=i,rstart=row[j]; j<n; j++) {
778:           if (row[j] != rstart) break;
779:         }
780:         if (j < n) ncols = j-i;
781:         else       ncols = n-i;
782:         /* Now assemble all these values with a single function call */
783:         MatSetValues_MPISBAIJ(mat,1,row+i,ncols,col+i,val+i,mat->insertmode);
784:         i    = j;
785:       }
786:     }
787:     MatStashScatterEnd_Private(&mat->stash);
788:     /* Now process the block-stash. Since the values are stashed column-oriented,
789:        set the roworiented flag to column oriented, and after MatSetValues()
790:        restore the original flags */
791:     r1 = baij->roworiented;
792:     r2 = a->roworiented;
793:     r3 = ((Mat_SeqBAIJ*)baij->B->data)->roworiented;

795:     baij->roworiented = PETSC_FALSE;
796:     a->roworiented    = PETSC_FALSE;

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

803:       for (i=0; i<n;) {
804:         /* Now identify the consecutive vals belonging to the same row */
805:         for (j=i,rstart=row[j]; j<n; j++) {
806:           if (row[j] != rstart) break;
807:         }
808:         if (j < n) ncols = j-i;
809:         else       ncols = n-i;
810:         MatSetValuesBlocked_MPISBAIJ(mat,1,row+i,ncols,col+i,val+i*bs2,mat->insertmode);
811:         i    = j;
812:       }
813:     }
814:     MatStashScatterEnd_Private(&mat->bstash);

816:     baij->roworiented = r1;
817:     a->roworiented    = r2;

819:     ((Mat_SeqBAIJ*)baij->B->data)->roworiented = r3; /* b->roworinted */
820:   }

822:   MatAssemblyBegin(baij->A,mode);
823:   MatAssemblyEnd(baij->A,mode);

825:   /* determine if any processor has disassembled, if so we must
826:      also disassemble ourselfs, in order that we may reassemble. */
827:   /*
828:      if nonzero structure of submatrix B cannot change then we know that
829:      no processor disassembled thus we can skip this stuff
830:   */
831:   if (!((Mat_SeqBAIJ*)baij->B->data)->nonew) {
832:     MPIU_Allreduce(&mat->was_assembled,&other_disassembled,1,MPIU_BOOL,MPI_PROD,PetscObjectComm((PetscObject)mat));
833:     if (mat->was_assembled && !other_disassembled) {
834:       MatDisAssemble_MPISBAIJ(mat);
835:     }
836:   }

838:   if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) {
839:     MatSetUpMultiply_MPISBAIJ(mat); /* setup Mvctx and sMvctx */
840:   }
841:   MatAssemblyBegin(baij->B,mode);
842:   MatAssemblyEnd(baij->B,mode);

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

846:   baij->rowvalues = 0;

848:   /* if no new nonzero locations are allowed in matrix then only set the matrix state the first time through */
849:   if ((!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) || !((Mat_SeqBAIJ*)(baij->A->data))->nonew) {
850:     PetscObjectState state = baij->A->nonzerostate + baij->B->nonzerostate;
851:     MPIU_Allreduce(&state,&mat->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)mat));
852:   }
853:   return(0);
854: }

856: extern PetscErrorCode MatSetValues_MPIBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const PetscScalar[],InsertMode);
857:  #include <petscdraw.h>
858: static PetscErrorCode MatView_MPISBAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer)
859: {
860:   Mat_MPISBAIJ      *baij = (Mat_MPISBAIJ*)mat->data;
861:   PetscErrorCode    ierr;
862:   PetscInt          bs   = mat->rmap->bs;
863:   PetscMPIInt       rank = baij->rank;
864:   PetscBool         iascii,isdraw;
865:   PetscViewer       sviewer;
866:   PetscViewerFormat format;

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

896:   if (isdraw) {
897:     PetscDraw draw;
898:     PetscBool isnull;
899:     PetscViewerDrawGetDraw(viewer,0,&draw);
900:     PetscDrawIsNull(draw,&isnull);
901:     if (isnull) return(0);
902:   }

904:   {
905:     /* assemble the entire matrix onto first processor. */
906:     Mat          A;
907:     Mat_SeqSBAIJ *Aloc;
908:     Mat_SeqBAIJ  *Bloc;
909:     PetscInt     M = mat->rmap->N,N = mat->cmap->N,*ai,*aj,col,i,j,k,*rvals,mbs = baij->mbs;
910:     MatScalar    *a;
911:     const char   *matname;

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

925:     /* copy over the A part */
926:     Aloc = (Mat_SeqSBAIJ*)baij->A->data;
927:     ai   = Aloc->i; aj = Aloc->j; a = Aloc->a;
928:     PetscMalloc1(bs,&rvals);

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

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

978: static PetscErrorCode MatView_MPISBAIJ_Binary(Mat mat,PetscViewer viewer)
979: {
980:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)mat->data;
981:   Mat_SeqSBAIJ   *A = (Mat_SeqSBAIJ*)a->A->data;
982:   Mat_SeqBAIJ    *B = (Mat_SeqBAIJ*)a->B->data;
984:   PetscInt       i,*row_lens,*crow_lens,bs = mat->rmap->bs,j,k,bs2=a->bs2,header[4],nz,rlen;
985:   PetscInt       *range=0,nzmax,*column_indices,cnt,col,*garray = a->garray,cstart = mat->cmap->rstart/bs,len,pcnt,l,ll;
986:   int            fd;
987:   PetscScalar    *column_values;
988:   FILE           *file;
989:   PetscMPIInt    rank,size,tag = ((PetscObject)viewer)->tag;
990:   PetscInt       message_count,flowcontrolcount;

993:   MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);
994:   MPI_Comm_size(PetscObjectComm((PetscObject)mat),&size);
995:   nz   = bs2*(A->nz + B->nz);
996:   rlen = mat->rmap->n;
997:   PetscViewerBinaryGetDescriptor(viewer,&fd);
998:   if (!rank) {
999:     header[0] = MAT_FILE_CLASSID;
1000:     header[1] = mat->rmap->N;
1001:     header[2] = mat->cmap->N;

1003:     MPI_Reduce(&nz,&header[3],1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));
1004:     PetscBinaryWrite(fd,header,4,PETSC_INT,PETSC_TRUE);
1005:     /* get largest number of rows any processor has */
1006:     range = mat->rmap->range;
1007:     for (i=1; i<size; i++) {
1008:       rlen = PetscMax(rlen,range[i+1] - range[i]);
1009:     }
1010:   } else {
1011:     MPI_Reduce(&nz,0,1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));
1012:   }

1014:   PetscMalloc1(rlen/bs,&crow_lens);
1015:   /* compute lengths of each row  */
1016:   for (i=0; i<a->mbs; i++) {
1017:     crow_lens[i] = A->i[i+1] - A->i[i] + B->i[i+1] - B->i[i];
1018:   }
1019:   /* store the row lengths to the file */
1020:   PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);
1021:   if (!rank) {
1022:     MPI_Status status;
1023:     PetscMalloc1(rlen,&row_lens);
1024:     rlen = (range[1] - range[0])/bs;
1025:     for (i=0; i<rlen; i++) {
1026:       for (j=0; j<bs; j++) {
1027:         row_lens[i*bs+j] = bs*crow_lens[i];
1028:       }
1029:     }
1030:     PetscBinaryWrite(fd,row_lens,bs*rlen,PETSC_INT,PETSC_TRUE);
1031:     for (i=1; i<size; i++) {
1032:       rlen = (range[i+1] - range[i])/bs;
1033:       PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);
1034:       MPI_Recv(crow_lens,rlen,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);
1035:       for (k=0; k<rlen; k++) {
1036:         for (j=0; j<bs; j++) {
1037:           row_lens[k*bs+j] = bs*crow_lens[k];
1038:         }
1039:       }
1040:       PetscBinaryWrite(fd,row_lens,bs*rlen,PETSC_INT,PETSC_TRUE);
1041:     }
1042:     PetscViewerFlowControlEndMaster(viewer,&message_count);
1043:     PetscFree(row_lens);
1044:   } else {
1045:     PetscViewerFlowControlStepWorker(viewer,rank,&message_count);
1046:     MPI_Send(crow_lens,mat->rmap->n/bs,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));
1047:     PetscViewerFlowControlEndWorker(viewer,&message_count);
1048:   }
1049:   PetscFree(crow_lens);

1051:   /* load up the local column indices. Include for all rows not just one for each block row since process 0 does not have the
1052:      information needed to make it for each row from a block row. This does require more communication but still not more than
1053:      the communication needed for the nonzero values  */
1054:   nzmax = nz; /*  space a largest processor needs */
1055:   MPI_Reduce(&nz,&nzmax,1,MPIU_INT,MPI_MAX,0,PetscObjectComm((PetscObject)mat));
1056:   PetscMalloc1(nzmax,&column_indices);
1057:   cnt   = 0;
1058:   for (i=0; i<a->mbs; i++) {
1059:     pcnt = cnt;
1060:     for (j=B->i[i]; j<B->i[i+1]; j++) {
1061:       if ((col = garray[B->j[j]]) > cstart) break;
1062:       for (l=0; l<bs; l++) {
1063:         column_indices[cnt++] = bs*col+l;
1064:       }
1065:     }
1066:     for (k=A->i[i]; k<A->i[i+1]; k++) {
1067:       for (l=0; l<bs; l++) {
1068:         column_indices[cnt++] = bs*(A->j[k] + cstart)+l;
1069:       }
1070:     }
1071:     for (; j<B->i[i+1]; j++) {
1072:       for (l=0; l<bs; l++) {
1073:         column_indices[cnt++] = bs*garray[B->j[j]]+l;
1074:       }
1075:     }
1076:     len = cnt - pcnt;
1077:     for (k=1; k<bs; k++) {
1078:       PetscArraycpy(&column_indices[cnt],&column_indices[pcnt],len);
1079:       cnt += len;
1080:     }
1081:   }
1082:   if (cnt != nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: cnt = %D nz = %D",cnt,nz);

1084:   /* store the columns to the file */
1085:   PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);
1086:   if (!rank) {
1087:     MPI_Status status;
1088:     PetscBinaryWrite(fd,column_indices,nz,PETSC_INT,PETSC_TRUE);
1089:     for (i=1; i<size; i++) {
1090:       PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);
1091:       MPI_Recv(&cnt,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);
1092:       MPI_Recv(column_indices,cnt,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);
1093:       PetscBinaryWrite(fd,column_indices,cnt,PETSC_INT,PETSC_TRUE);
1094:     }
1095:     PetscViewerFlowControlEndMaster(viewer,&message_count);
1096:   } else {
1097:     PetscViewerFlowControlStepWorker(viewer,rank,&message_count);
1098:     MPI_Send(&cnt,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));
1099:     MPI_Send(column_indices,cnt,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));
1100:     PetscViewerFlowControlEndWorker(viewer,&message_count);
1101:   }
1102:   PetscFree(column_indices);

1104:   /* load up the numerical values */
1105:   PetscMalloc1(nzmax,&column_values);
1106:   cnt  = 0;
1107:   for (i=0; i<a->mbs; i++) {
1108:     rlen = bs*(B->i[i+1] - B->i[i] + A->i[i+1] - A->i[i]);
1109:     for (j=B->i[i]; j<B->i[i+1]; j++) {
1110:       if (garray[B->j[j]] > cstart) break;
1111:       for (l=0; l<bs; l++) {
1112:         for (ll=0; ll<bs; ll++) {
1113:           column_values[cnt + l*rlen + ll] = B->a[bs2*j+l+bs*ll];
1114:         }
1115:       }
1116:       cnt += bs;
1117:     }
1118:     for (k=A->i[i]; k<A->i[i+1]; k++) {
1119:       for (l=0; l<bs; l++) {
1120:         for (ll=0; ll<bs; ll++) {
1121:           column_values[cnt + l*rlen + ll] = A->a[bs2*k+l+bs*ll];
1122:         }
1123:       }
1124:       cnt += bs;
1125:     }
1126:     for (; j<B->i[i+1]; j++) {
1127:       for (l=0; l<bs; l++) {
1128:         for (ll=0; ll<bs; ll++) {
1129:           column_values[cnt + l*rlen + ll] = B->a[bs2*j+l+bs*ll];
1130:         }
1131:       }
1132:       cnt += bs;
1133:     }
1134:     cnt += (bs-1)*rlen;
1135:   }
1136:   if (cnt != nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Internal PETSc error: cnt = %D nz = %D",cnt,nz);

1138:   /* store the column values to the file */
1139:   PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);
1140:   if (!rank) {
1141:     MPI_Status status;
1142:     PetscBinaryWrite(fd,column_values,nz,PETSC_SCALAR,PETSC_TRUE);
1143:     for (i=1; i<size; i++) {
1144:       PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);
1145:       MPI_Recv(&cnt,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);
1146:       MPI_Recv(column_values,cnt,MPIU_SCALAR,i,tag,PetscObjectComm((PetscObject)mat),&status);
1147:       PetscBinaryWrite(fd,column_values,cnt,PETSC_SCALAR,PETSC_TRUE);
1148:     }
1149:     PetscViewerFlowControlEndMaster(viewer,&message_count);
1150:   } else {
1151:     PetscViewerFlowControlStepWorker(viewer,rank,&message_count);
1152:     MPI_Send(&nz,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));
1153:     MPI_Send(column_values,nz,MPIU_SCALAR,0,tag,PetscObjectComm((PetscObject)mat));
1154:     PetscViewerFlowControlEndWorker(viewer,&message_count);
1155:   }
1156:   PetscFree(column_values);

1158:   PetscViewerBinaryGetInfoPointer(viewer,&file);
1159:   if (file) {
1160:     fprintf(file,"-matload_block_size %d\n",(int)mat->rmap->bs);
1161:   }
1162:   return(0);
1163: }

1165: PetscErrorCode MatView_MPISBAIJ(Mat mat,PetscViewer viewer)
1166: {
1168:   PetscBool      iascii,isdraw,issocket,isbinary;

1171:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
1172:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);
1173:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSOCKET,&issocket);
1174:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);
1175:   if (iascii || isdraw || issocket) {
1176:     MatView_MPISBAIJ_ASCIIorDraworSocket(mat,viewer);
1177:   } else if (isbinary) {
1178:     MatView_MPISBAIJ_Binary(mat,viewer);
1179:   }
1180:   return(0);
1181: }

1183: PetscErrorCode MatDestroy_MPISBAIJ(Mat mat)
1184: {
1185:   Mat_MPISBAIJ   *baij = (Mat_MPISBAIJ*)mat->data;

1189: #if defined(PETSC_USE_LOG)
1190:   PetscLogObjectState((PetscObject)mat,"Rows=%D,Cols=%D",mat->rmap->N,mat->cmap->N);
1191: #endif
1192:   MatStashDestroy_Private(&mat->stash);
1193:   MatStashDestroy_Private(&mat->bstash);
1194:   MatDestroy(&baij->A);
1195:   MatDestroy(&baij->B);
1196: #if defined(PETSC_USE_CTABLE)
1197:   PetscTableDestroy(&baij->colmap);
1198: #else
1199:   PetscFree(baij->colmap);
1200: #endif
1201:   PetscFree(baij->garray);
1202:   VecDestroy(&baij->lvec);
1203:   VecScatterDestroy(&baij->Mvctx);
1204:   VecDestroy(&baij->slvec0);
1205:   VecDestroy(&baij->slvec0b);
1206:   VecDestroy(&baij->slvec1);
1207:   VecDestroy(&baij->slvec1a);
1208:   VecDestroy(&baij->slvec1b);
1209:   VecScatterDestroy(&baij->sMvctx);
1210:   PetscFree2(baij->rowvalues,baij->rowindices);
1211:   PetscFree(baij->barray);
1212:   PetscFree(baij->hd);
1213:   VecDestroy(&baij->diag);
1214:   VecDestroy(&baij->bb1);
1215:   VecDestroy(&baij->xx1);
1216: #if defined(PETSC_USE_REAL_MAT_SINGLE)
1217:   PetscFree(baij->setvaluescopy);
1218: #endif
1219:   PetscFree(baij->in_loc);
1220:   PetscFree(baij->v_loc);
1221:   PetscFree(baij->rangebs);
1222:   PetscFree(mat->data);

1224:   PetscObjectChangeTypeName((PetscObject)mat,0);
1225:   PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C",NULL);
1226:   PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C",NULL);
1227:   PetscObjectComposeFunction((PetscObject)mat,"MatMPISBAIJSetPreallocation_C",NULL);
1228:   PetscObjectComposeFunction((PetscObject)mat,"MatMPISBAIJSetPreallocationCSR_C",NULL);
1229: #if defined(PETSC_HAVE_ELEMENTAL)
1230:   PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpisbaij_elemental_C",NULL);
1231: #endif
1232:   PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpisbaij_mpiaij_C",NULL);
1233:   PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpisbaij_mpibaij_C",NULL);
1234:   return(0);
1235: }

1237: PetscErrorCode MatMult_MPISBAIJ_Hermitian(Mat A,Vec xx,Vec yy)
1238: {
1239:   Mat_MPISBAIJ      *a = (Mat_MPISBAIJ*)A->data;
1240:   PetscErrorCode    ierr;
1241:   PetscInt          nt,mbs=a->mbs,bs=A->rmap->bs;
1242:   PetscScalar       *from;
1243:   const PetscScalar *x;

1246:   VecGetLocalSize(xx,&nt);
1247:   if (nt != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx");

1249:   /* diagonal part */
1250:   (*a->A->ops->mult)(a->A,xx,a->slvec1a);
1251:   VecSet(a->slvec1b,0.0);

1253:   /* subdiagonal part */
1254:   (*a->B->ops->multhermitiantranspose)(a->B,xx,a->slvec0b);

1256:   /* copy x into the vec slvec0 */
1257:   VecGetArray(a->slvec0,&from);
1258:   VecGetArrayRead(xx,&x);

1260:   PetscArraycpy(from,x,bs*mbs);
1261:   VecRestoreArray(a->slvec0,&from);
1262:   VecRestoreArrayRead(xx,&x);

1264:   VecScatterBegin(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);
1265:   VecScatterEnd(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);
1266:   /* supperdiagonal part */
1267:   (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,yy);
1268:   return(0);
1269: }

1271: PetscErrorCode MatMult_MPISBAIJ(Mat A,Vec xx,Vec yy)
1272: {
1273:   Mat_MPISBAIJ      *a = (Mat_MPISBAIJ*)A->data;
1274:   PetscErrorCode    ierr;
1275:   PetscInt          nt,mbs=a->mbs,bs=A->rmap->bs;
1276:   PetscScalar       *from;
1277:   const PetscScalar *x;

1280:   VecGetLocalSize(xx,&nt);
1281:   if (nt != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx");

1283:   /* diagonal part */
1284:   (*a->A->ops->mult)(a->A,xx,a->slvec1a);
1285:   VecSet(a->slvec1b,0.0);

1287:   /* subdiagonal part */
1288:   (*a->B->ops->multtranspose)(a->B,xx,a->slvec0b);

1290:   /* copy x into the vec slvec0 */
1291:   VecGetArray(a->slvec0,&from);
1292:   VecGetArrayRead(xx,&x);

1294:   PetscArraycpy(from,x,bs*mbs);
1295:   VecRestoreArray(a->slvec0,&from);
1296:   VecRestoreArrayRead(xx,&x);

1298:   VecScatterBegin(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);
1299:   VecScatterEnd(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);
1300:   /* supperdiagonal part */
1301:   (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,yy);
1302:   return(0);
1303: }

1305: PetscErrorCode MatMult_MPISBAIJ_2comm(Mat A,Vec xx,Vec yy)
1306: {
1307:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;
1309:   PetscInt       nt;

1312:   VecGetLocalSize(xx,&nt);
1313:   if (nt != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx");

1315:   VecGetLocalSize(yy,&nt);
1316:   if (nt != A->rmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible parition of A and yy");

1318:   VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
1319:   /* do diagonal part */
1320:   (*a->A->ops->mult)(a->A,xx,yy);
1321:   /* do supperdiagonal part */
1322:   VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
1323:   (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);
1324:   /* do subdiagonal part */
1325:   (*a->B->ops->multtranspose)(a->B,xx,a->lvec);
1326:   VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
1327:   VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
1328:   return(0);
1329: }

1331: PetscErrorCode MatMultAdd_MPISBAIJ(Mat A,Vec xx,Vec yy,Vec zz)
1332: {
1333:   Mat_MPISBAIJ      *a = (Mat_MPISBAIJ*)A->data;
1334:   PetscErrorCode    ierr;
1335:   PetscInt          mbs=a->mbs,bs=A->rmap->bs;
1336:   PetscScalar       *from,zero=0.0;
1337:   const PetscScalar *x;

1340:   /*
1341:   PetscSynchronizedPrintf(PetscObjectComm((PetscObject)A)," MatMultAdd is called ...\n");
1342:   PetscSynchronizedFlush(PetscObjectComm((PetscObject)A),PETSC_STDOUT);
1343:   */
1344:   /* diagonal part */
1345:   (*a->A->ops->multadd)(a->A,xx,yy,a->slvec1a);
1346:   VecSet(a->slvec1b,zero);

1348:   /* subdiagonal part */
1349:   (*a->B->ops->multtranspose)(a->B,xx,a->slvec0b);

1351:   /* copy x into the vec slvec0 */
1352:   VecGetArray(a->slvec0,&from);
1353:   VecGetArrayRead(xx,&x);
1354:   PetscArraycpy(from,x,bs*mbs);
1355:   VecRestoreArray(a->slvec0,&from);

1357:   VecScatterBegin(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);
1358:   VecRestoreArrayRead(xx,&x);
1359:   VecScatterEnd(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);

1361:   /* supperdiagonal part */
1362:   (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,zz);
1363:   return(0);
1364: }

1366: PetscErrorCode MatMultAdd_MPISBAIJ_2comm(Mat A,Vec xx,Vec yy,Vec zz)
1367: {
1368:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;

1372:   VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
1373:   /* do diagonal part */
1374:   (*a->A->ops->multadd)(a->A,xx,yy,zz);
1375:   /* do supperdiagonal part */
1376:   VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
1377:   (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);

1379:   /* do subdiagonal part */
1380:   (*a->B->ops->multtranspose)(a->B,xx,a->lvec);
1381:   VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);
1382:   VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);
1383:   return(0);
1384: }

1386: /*
1387:   This only works correctly for square matrices where the subblock A->A is the
1388:    diagonal block
1389: */
1390: PetscErrorCode MatGetDiagonal_MPISBAIJ(Mat A,Vec v)
1391: {
1392:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;

1396:   /* if (a->rmap->N != a->cmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block"); */
1397:   MatGetDiagonal(a->A,v);
1398:   return(0);
1399: }

1401: PetscErrorCode MatScale_MPISBAIJ(Mat A,PetscScalar aa)
1402: {
1403:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;

1407:   MatScale(a->A,aa);
1408:   MatScale(a->B,aa);
1409:   return(0);
1410: }

1412: PetscErrorCode MatGetRow_MPISBAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
1413: {
1414:   Mat_MPISBAIJ   *mat = (Mat_MPISBAIJ*)matin->data;
1415:   PetscScalar    *vworkA,*vworkB,**pvA,**pvB,*v_p;
1417:   PetscInt       bs = matin->rmap->bs,bs2 = mat->bs2,i,*cworkA,*cworkB,**pcA,**pcB;
1418:   PetscInt       nztot,nzA,nzB,lrow,brstart = matin->rmap->rstart,brend = matin->rmap->rend;
1419:   PetscInt       *cmap,*idx_p,cstart = mat->rstartbs;

1422:   if (mat->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Already active");
1423:   mat->getrowactive = PETSC_TRUE;

1425:   if (!mat->rowvalues && (idx || v)) {
1426:     /*
1427:         allocate enough space to hold information from the longest row.
1428:     */
1429:     Mat_SeqSBAIJ *Aa = (Mat_SeqSBAIJ*)mat->A->data;
1430:     Mat_SeqBAIJ  *Ba = (Mat_SeqBAIJ*)mat->B->data;
1431:     PetscInt     max = 1,mbs = mat->mbs,tmp;
1432:     for (i=0; i<mbs; i++) {
1433:       tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; /* row length */
1434:       if (max < tmp) max = tmp;
1435:     }
1436:     PetscMalloc2(max*bs2,&mat->rowvalues,max*bs2,&mat->rowindices);
1437:   }

1439:   if (row < brstart || row >= brend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local rows");
1440:   lrow = row - brstart;  /* local row index */

1442:   pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB;
1443:   if (!v)   {pvA = 0; pvB = 0;}
1444:   if (!idx) {pcA = 0; if (!v) pcB = 0;}
1445:   (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);
1446:   (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);
1447:   nztot = nzA + nzB;

1449:   cmap = mat->garray;
1450:   if (v  || idx) {
1451:     if (nztot) {
1452:       /* Sort by increasing column numbers, assuming A and B already sorted */
1453:       PetscInt imark = -1;
1454:       if (v) {
1455:         *v = v_p = mat->rowvalues;
1456:         for (i=0; i<nzB; i++) {
1457:           if (cmap[cworkB[i]/bs] < cstart) v_p[i] = vworkB[i];
1458:           else break;
1459:         }
1460:         imark = i;
1461:         for (i=0; i<nzA; i++)     v_p[imark+i] = vworkA[i];
1462:         for (i=imark; i<nzB; i++) v_p[nzA+i]   = vworkB[i];
1463:       }
1464:       if (idx) {
1465:         *idx = idx_p = mat->rowindices;
1466:         if (imark > -1) {
1467:           for (i=0; i<imark; i++) {
1468:             idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs;
1469:           }
1470:         } else {
1471:           for (i=0; i<nzB; i++) {
1472:             if (cmap[cworkB[i]/bs] < cstart) idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs;
1473:             else break;
1474:           }
1475:           imark = i;
1476:         }
1477:         for (i=0; i<nzA; i++)     idx_p[imark+i] = cstart*bs + cworkA[i];
1478:         for (i=imark; i<nzB; i++) idx_p[nzA+i]   = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ;
1479:       }
1480:     } else {
1481:       if (idx) *idx = 0;
1482:       if (v)   *v   = 0;
1483:     }
1484:   }
1485:   *nz  = nztot;
1486:   (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);
1487:   (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);
1488:   return(0);
1489: }

1491: PetscErrorCode MatRestoreRow_MPISBAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
1492: {
1493:   Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data;

1496:   if (!baij->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"MatGetRow() must be called first");
1497:   baij->getrowactive = PETSC_FALSE;
1498:   return(0);
1499: }

1501: PetscErrorCode MatGetRowUpperTriangular_MPISBAIJ(Mat A)
1502: {
1503:   Mat_MPISBAIJ *a  = (Mat_MPISBAIJ*)A->data;
1504:   Mat_SeqSBAIJ *aA = (Mat_SeqSBAIJ*)a->A->data;

1507:   aA->getrow_utriangular = PETSC_TRUE;
1508:   return(0);
1509: }
1510: PetscErrorCode MatRestoreRowUpperTriangular_MPISBAIJ(Mat A)
1511: {
1512:   Mat_MPISBAIJ *a  = (Mat_MPISBAIJ*)A->data;
1513:   Mat_SeqSBAIJ *aA = (Mat_SeqSBAIJ*)a->A->data;

1516:   aA->getrow_utriangular = PETSC_FALSE;
1517:   return(0);
1518: }

1520: PetscErrorCode MatRealPart_MPISBAIJ(Mat A)
1521: {
1522:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;

1526:   MatRealPart(a->A);
1527:   MatRealPart(a->B);
1528:   return(0);
1529: }

1531: PetscErrorCode MatImaginaryPart_MPISBAIJ(Mat A)
1532: {
1533:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;

1537:   MatImaginaryPart(a->A);
1538:   MatImaginaryPart(a->B);
1539:   return(0);
1540: }

1542: /* Check if isrow is a subset of iscol_local, called by MatCreateSubMatrix_MPISBAIJ()
1543:    Input: isrow       - distributed(parallel),
1544:           iscol_local - locally owned (seq)
1545: */
1546: PetscErrorCode ISEqual_private(IS isrow,IS iscol_local,PetscBool  *flg)
1547: {
1549:   PetscInt       sz1,sz2,*a1,*a2,i,j,k,nmatch;
1550:   const PetscInt *ptr1,*ptr2;

1553:   ISGetLocalSize(isrow,&sz1);
1554:   ISGetLocalSize(iscol_local,&sz2);
1555:   if (sz1 > sz2) {
1556:     *flg = PETSC_FALSE;
1557:     return(0);
1558:   }

1560:   ISGetIndices(isrow,&ptr1);
1561:   ISGetIndices(iscol_local,&ptr2);

1563:   PetscMalloc1(sz1,&a1);
1564:   PetscMalloc1(sz2,&a2);
1565:   PetscArraycpy(a1,ptr1,sz1);
1566:   PetscArraycpy(a2,ptr2,sz2);
1567:   PetscSortInt(sz1,a1);
1568:   PetscSortInt(sz2,a2);

1570:   nmatch=0;
1571:   k     = 0;
1572:   for (i=0; i<sz1; i++){
1573:     for (j=k; j<sz2; j++){
1574:       if (a1[i] == a2[j]) {
1575:         k = j; nmatch++;
1576:         break;
1577:       }
1578:     }
1579:   }
1580:   ISRestoreIndices(isrow,&ptr1);
1581:   ISRestoreIndices(iscol_local,&ptr2);
1582:   PetscFree(a1);
1583:   PetscFree(a2);
1584:   if (nmatch < sz1) {
1585:     *flg = PETSC_FALSE;
1586:   } else {
1587:     *flg = PETSC_TRUE;
1588:   }
1589:   return(0);
1590: }

1592: PetscErrorCode MatCreateSubMatrix_MPISBAIJ(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat)
1593: {
1595:   IS             iscol_local;
1596:   PetscInt       csize;
1597:   PetscBool      isequal;

1600:   ISGetLocalSize(iscol,&csize);
1601:   if (call == MAT_REUSE_MATRIX) {
1602:     PetscObjectQuery((PetscObject)*newmat,"ISAllGather",(PetscObject*)&iscol_local);
1603:     if (!iscol_local) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse");
1604:   } else {
1605:     ISAllGather(iscol,&iscol_local);
1606:     ISEqual_private(isrow,iscol_local,&isequal);
1607:     if (!isequal) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"For symmetric format, iscol must equal isrow");
1608:   }

1610:   /* now call MatCreateSubMatrix_MPIBAIJ() */
1611:   MatCreateSubMatrix_MPIBAIJ_Private(mat,isrow,iscol_local,csize,call,newmat);
1612:   if (call == MAT_INITIAL_MATRIX) {
1613:     PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);
1614:     ISDestroy(&iscol_local);
1615:   }
1616:   return(0);
1617: }

1619: PetscErrorCode MatZeroEntries_MPISBAIJ(Mat A)
1620: {
1621:   Mat_MPISBAIJ   *l = (Mat_MPISBAIJ*)A->data;

1625:   MatZeroEntries(l->A);
1626:   MatZeroEntries(l->B);
1627:   return(0);
1628: }

1630: PetscErrorCode MatGetInfo_MPISBAIJ(Mat matin,MatInfoType flag,MatInfo *info)
1631: {
1632:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)matin->data;
1633:   Mat            A  = a->A,B = a->B;
1635:   PetscLogDouble isend[5],irecv[5];

1638:   info->block_size = (PetscReal)matin->rmap->bs;

1640:   MatGetInfo(A,MAT_LOCAL,info);

1642:   isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded;
1643:   isend[3] = info->memory;  isend[4] = info->mallocs;

1645:   MatGetInfo(B,MAT_LOCAL,info);

1647:   isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded;
1648:   isend[3] += info->memory;  isend[4] += info->mallocs;
1649:   if (flag == MAT_LOCAL) {
1650:     info->nz_used      = isend[0];
1651:     info->nz_allocated = isend[1];
1652:     info->nz_unneeded  = isend[2];
1653:     info->memory       = isend[3];
1654:     info->mallocs      = isend[4];
1655:   } else if (flag == MAT_GLOBAL_MAX) {
1656:     MPIU_Allreduce(isend,irecv,5,MPIU_PETSCLOGDOUBLE,MPI_MAX,PetscObjectComm((PetscObject)matin));

1658:     info->nz_used      = irecv[0];
1659:     info->nz_allocated = irecv[1];
1660:     info->nz_unneeded  = irecv[2];
1661:     info->memory       = irecv[3];
1662:     info->mallocs      = irecv[4];
1663:   } else if (flag == MAT_GLOBAL_SUM) {
1664:     MPIU_Allreduce(isend,irecv,5,MPIU_PETSCLOGDOUBLE,MPI_SUM,PetscObjectComm((PetscObject)matin));

1666:     info->nz_used      = irecv[0];
1667:     info->nz_allocated = irecv[1];
1668:     info->nz_unneeded  = irecv[2];
1669:     info->memory       = irecv[3];
1670:     info->mallocs      = irecv[4];
1671:   } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Unknown MatInfoType argument %d",(int)flag);
1672:   info->fill_ratio_given  = 0; /* no parallel LU/ILU/Cholesky */
1673:   info->fill_ratio_needed = 0;
1674:   info->factor_mallocs    = 0;
1675:   return(0);
1676: }

1678: PetscErrorCode MatSetOption_MPISBAIJ(Mat A,MatOption op,PetscBool flg)
1679: {
1680:   Mat_MPISBAIJ   *a  = (Mat_MPISBAIJ*)A->data;
1681:   Mat_SeqSBAIJ   *aA = (Mat_SeqSBAIJ*)a->A->data;

1685:   switch (op) {
1686:   case MAT_NEW_NONZERO_LOCATIONS:
1687:   case MAT_NEW_NONZERO_ALLOCATION_ERR:
1688:   case MAT_UNUSED_NONZERO_LOCATION_ERR:
1689:   case MAT_KEEP_NONZERO_PATTERN:
1690:   case MAT_SUBMAT_SINGLEIS:
1691:   case MAT_NEW_NONZERO_LOCATION_ERR:
1692:     MatCheckPreallocated(A,1);
1693:     MatSetOption(a->A,op,flg);
1694:     MatSetOption(a->B,op,flg);
1695:     break;
1696:   case MAT_ROW_ORIENTED:
1697:     MatCheckPreallocated(A,1);
1698:     a->roworiented = flg;

1700:     MatSetOption(a->A,op,flg);
1701:     MatSetOption(a->B,op,flg);
1702:     break;
1703:   case MAT_NEW_DIAGONALS:
1704:   case MAT_SORTED_FULL:
1705:     PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);
1706:     break;
1707:   case MAT_IGNORE_OFF_PROC_ENTRIES:
1708:     a->donotstash = flg;
1709:     break;
1710:   case MAT_USE_HASH_TABLE:
1711:     a->ht_flag = flg;
1712:     break;
1713:   case MAT_HERMITIAN:
1714:     MatCheckPreallocated(A,1);
1715:     if (!A->assembled) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Must call MatAssemblyEnd() first");
1716:     MatSetOption(a->A,op,flg);
1717: #if defined(PETSC_USE_COMPLEX)
1718:     A->ops->mult = MatMult_MPISBAIJ_Hermitian;
1719: #endif
1720:     break;
1721:   case MAT_SPD:
1722:     A->spd_set = PETSC_TRUE;
1723:     A->spd     = flg;
1724:     if (flg) {
1725:       A->symmetric                  = PETSC_TRUE;
1726:       A->structurally_symmetric     = PETSC_TRUE;
1727:       A->symmetric_set              = PETSC_TRUE;
1728:       A->structurally_symmetric_set = PETSC_TRUE;
1729:     }
1730:     break;
1731:   case MAT_SYMMETRIC:
1732:     MatCheckPreallocated(A,1);
1733:     MatSetOption(a->A,op,flg);
1734:     break;
1735:   case MAT_STRUCTURALLY_SYMMETRIC:
1736:     MatCheckPreallocated(A,1);
1737:     MatSetOption(a->A,op,flg);
1738:     break;
1739:   case MAT_SYMMETRY_ETERNAL:
1740:     if (!flg) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Matrix must be symmetric");
1741:     PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);
1742:     break;
1743:   case MAT_IGNORE_LOWER_TRIANGULAR:
1744:     aA->ignore_ltriangular = flg;
1745:     break;
1746:   case MAT_ERROR_LOWER_TRIANGULAR:
1747:     aA->ignore_ltriangular = flg;
1748:     break;
1749:   case MAT_GETROW_UPPERTRIANGULAR:
1750:     aA->getrow_utriangular = flg;
1751:     break;
1752:   default:
1753:     SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %d",op);
1754:   }
1755:   return(0);
1756: }

1758: PetscErrorCode MatTranspose_MPISBAIJ(Mat A,MatReuse reuse,Mat *B)
1759: {

1763:   if (reuse == MAT_INITIAL_MATRIX) {
1764:     MatDuplicate(A,MAT_COPY_VALUES,B);
1765:   }  else if (reuse == MAT_REUSE_MATRIX) {
1766:     MatCopy(A,*B,SAME_NONZERO_PATTERN);
1767:   }
1768:   return(0);
1769: }

1771: PetscErrorCode MatDiagonalScale_MPISBAIJ(Mat mat,Vec ll,Vec rr)
1772: {
1773:   Mat_MPISBAIJ   *baij = (Mat_MPISBAIJ*)mat->data;
1774:   Mat            a     = baij->A, b=baij->B;
1776:   PetscInt       nv,m,n;
1777:   PetscBool      flg;

1780:   if (ll != rr) {
1781:     VecEqual(ll,rr,&flg);
1782:     if (!flg) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"For symmetric format, left and right scaling vectors must be same\n");
1783:   }
1784:   if (!ll) return(0);

1786:   MatGetLocalSize(mat,&m,&n);
1787:   if (m != n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"For symmetric format, local size %d %d must be same",m,n);

1789:   VecGetLocalSize(rr,&nv);
1790:   if (nv!=n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Left and right vector non-conforming local size");

1792:   VecScatterBegin(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);

1794:   /* left diagonalscale the off-diagonal part */
1795:   (*b->ops->diagonalscale)(b,ll,NULL);

1797:   /* scale the diagonal part */
1798:   (*a->ops->diagonalscale)(a,ll,rr);

1800:   /* right diagonalscale the off-diagonal part */
1801:   VecScatterEnd(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);
1802:   (*b->ops->diagonalscale)(b,NULL,baij->lvec);
1803:   return(0);
1804: }

1806: PetscErrorCode MatSetUnfactored_MPISBAIJ(Mat A)
1807: {
1808:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;

1812:   MatSetUnfactored(a->A);
1813:   return(0);
1814: }

1816: static PetscErrorCode MatDuplicate_MPISBAIJ(Mat,MatDuplicateOption,Mat*);

1818: PetscErrorCode MatEqual_MPISBAIJ(Mat A,Mat B,PetscBool  *flag)
1819: {
1820:   Mat_MPISBAIJ   *matB = (Mat_MPISBAIJ*)B->data,*matA = (Mat_MPISBAIJ*)A->data;
1821:   Mat            a,b,c,d;
1822:   PetscBool      flg;

1826:   a = matA->A; b = matA->B;
1827:   c = matB->A; d = matB->B;

1829:   MatEqual(a,c,&flg);
1830:   if (flg) {
1831:     MatEqual(b,d,&flg);
1832:   }
1833:   MPIU_Allreduce(&flg,flag,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)A));
1834:   return(0);
1835: }

1837: PetscErrorCode MatCopy_MPISBAIJ(Mat A,Mat B,MatStructure str)
1838: {
1840:   PetscBool      isbaij;

1843:   PetscObjectTypeCompareAny((PetscObject)B,&isbaij,MATSEQSBAIJ,MATMPISBAIJ,"");
1844:   if (!isbaij) SETERRQ1(PetscObjectComm((PetscObject)B),PETSC_ERR_SUP,"Not for matrix type %s",((PetscObject)B)->type_name);
1845:   /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */
1846:   if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) {
1847:     MatGetRowUpperTriangular(A);
1848:     MatCopy_Basic(A,B,str);
1849:     MatRestoreRowUpperTriangular(A);
1850:   } else {
1851:     Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data;
1852:     Mat_MPISBAIJ *b = (Mat_MPISBAIJ*)B->data;

1854:     MatCopy(a->A,b->A,str);
1855:     MatCopy(a->B,b->B,str);
1856:   }
1857:   PetscObjectStateIncrease((PetscObject)B);
1858:   return(0);
1859: }

1861: PetscErrorCode MatSetUp_MPISBAIJ(Mat A)
1862: {

1866:   MatMPISBAIJSetPreallocation(A,A->rmap->bs,PETSC_DEFAULT,0,PETSC_DEFAULT,0);
1867:   return(0);
1868: }

1870: PetscErrorCode MatAXPY_MPISBAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str)
1871: {
1873:   Mat_MPISBAIJ   *xx=(Mat_MPISBAIJ*)X->data,*yy=(Mat_MPISBAIJ*)Y->data;
1874:   PetscBLASInt   bnz,one=1;
1875:   Mat_SeqSBAIJ   *xa,*ya;
1876:   Mat_SeqBAIJ    *xb,*yb;

1879:   if (str == SAME_NONZERO_PATTERN) {
1880:     PetscScalar alpha = a;
1881:     xa   = (Mat_SeqSBAIJ*)xx->A->data;
1882:     ya   = (Mat_SeqSBAIJ*)yy->A->data;
1883:     PetscBLASIntCast(xa->nz,&bnz);
1884:     PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,xa->a,&one,ya->a,&one));
1885:     xb   = (Mat_SeqBAIJ*)xx->B->data;
1886:     yb   = (Mat_SeqBAIJ*)yy->B->data;
1887:     PetscBLASIntCast(xb->nz,&bnz);
1888:     PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,xb->a,&one,yb->a,&one));
1889:     PetscObjectStateIncrease((PetscObject)Y);
1890:   } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */
1891:     MatSetOption(X,MAT_GETROW_UPPERTRIANGULAR,PETSC_TRUE);
1892:     MatAXPY_Basic(Y,a,X,str);
1893:     MatSetOption(X,MAT_GETROW_UPPERTRIANGULAR,PETSC_FALSE);
1894:   } else {
1895:     Mat      B;
1896:     PetscInt *nnz_d,*nnz_o,bs=Y->rmap->bs;
1897:     if (bs != X->rmap->bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Matrices must have same block size");
1898:     MatGetRowUpperTriangular(X);
1899:     MatGetRowUpperTriangular(Y);
1900:     PetscMalloc1(yy->A->rmap->N,&nnz_d);
1901:     PetscMalloc1(yy->B->rmap->N,&nnz_o);
1902:     MatCreate(PetscObjectComm((PetscObject)Y),&B);
1903:     PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);
1904:     MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);
1905:     MatSetBlockSizesFromMats(B,Y,Y);
1906:     MatSetType(B,MATMPISBAIJ);
1907:     MatAXPYGetPreallocation_SeqSBAIJ(yy->A,xx->A,nnz_d);
1908:     MatAXPYGetPreallocation_MPIBAIJ(yy->B,yy->garray,xx->B,xx->garray,nnz_o);
1909:     MatMPISBAIJSetPreallocation(B,bs,0,nnz_d,0,nnz_o);
1910:     MatAXPY_BasicWithPreallocation(B,Y,a,X,str);
1911:     MatHeaderReplace(Y,&B);
1912:     PetscFree(nnz_d);
1913:     PetscFree(nnz_o);
1914:     MatRestoreRowUpperTriangular(X);
1915:     MatRestoreRowUpperTriangular(Y);
1916:   }
1917:   return(0);
1918: }

1920: PetscErrorCode MatCreateSubMatrices_MPISBAIJ(Mat A,PetscInt n,const IS irow[],const IS icol[],MatReuse scall,Mat *B[])
1921: {
1923:   PetscInt       i;
1924:   PetscBool      flg;

1927:   MatCreateSubMatrices_MPIBAIJ(A,n,irow,icol,scall,B); /* B[] are sbaij matrices */
1928:   for (i=0; i<n; i++) {
1929:     ISEqual(irow[i],icol[i],&flg);
1930:     if (!flg) {
1931:       MatSeqSBAIJZeroOps_Private(*B[i]);
1932:     }
1933:   }
1934:   return(0);
1935: }

1937: PetscErrorCode MatShift_MPISBAIJ(Mat Y,PetscScalar a)
1938: {
1940:   Mat_MPISBAIJ    *maij = (Mat_MPISBAIJ*)Y->data;
1941:   Mat_SeqSBAIJ    *aij = (Mat_SeqSBAIJ*)maij->A->data;

1944:   if (!Y->preallocated) {
1945:     MatMPISBAIJSetPreallocation(Y,Y->rmap->bs,1,NULL,0,NULL);
1946:   } else if (!aij->nz) {
1947:     PetscInt nonew = aij->nonew;
1948:     MatSeqSBAIJSetPreallocation(maij->A,Y->rmap->bs,1,NULL);
1949:     aij->nonew = nonew;
1950:   }
1951:   MatShift_Basic(Y,a);
1952:   return(0);
1953: }

1955: PetscErrorCode MatMissingDiagonal_MPISBAIJ(Mat A,PetscBool  *missing,PetscInt *d)
1956: {
1957:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;

1961:   if (A->rmap->n != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only works for square matrices");
1962:   MatMissingDiagonal(a->A,missing,d);
1963:   if (d) {
1964:     PetscInt rstart;
1965:     MatGetOwnershipRange(A,&rstart,NULL);
1966:     *d += rstart/A->rmap->bs;

1968:   }
1969:   return(0);
1970: }

1972: PetscErrorCode  MatGetDiagonalBlock_MPISBAIJ(Mat A,Mat *a)
1973: {
1975:   *a = ((Mat_MPISBAIJ*)A->data)->A;
1976:   return(0);
1977: }

1979: /* -------------------------------------------------------------------*/
1980: static struct _MatOps MatOps_Values = {MatSetValues_MPISBAIJ,
1981:                                        MatGetRow_MPISBAIJ,
1982:                                        MatRestoreRow_MPISBAIJ,
1983:                                        MatMult_MPISBAIJ,
1984:                                /*  4*/ MatMultAdd_MPISBAIJ,
1985:                                        MatMult_MPISBAIJ,       /* transpose versions are same as non-transpose */
1986:                                        MatMultAdd_MPISBAIJ,
1987:                                        0,
1988:                                        0,
1989:                                        0,
1990:                                /* 10*/ 0,
1991:                                        0,
1992:                                        0,
1993:                                        MatSOR_MPISBAIJ,
1994:                                        MatTranspose_MPISBAIJ,
1995:                                /* 15*/ MatGetInfo_MPISBAIJ,
1996:                                        MatEqual_MPISBAIJ,
1997:                                        MatGetDiagonal_MPISBAIJ,
1998:                                        MatDiagonalScale_MPISBAIJ,
1999:                                        MatNorm_MPISBAIJ,
2000:                                /* 20*/ MatAssemblyBegin_MPISBAIJ,
2001:                                        MatAssemblyEnd_MPISBAIJ,
2002:                                        MatSetOption_MPISBAIJ,
2003:                                        MatZeroEntries_MPISBAIJ,
2004:                                /* 24*/ 0,
2005:                                        0,
2006:                                        0,
2007:                                        0,
2008:                                        0,
2009:                                /* 29*/ MatSetUp_MPISBAIJ,
2010:                                        0,
2011:                                        0,
2012:                                        MatGetDiagonalBlock_MPISBAIJ,
2013:                                        0,
2014:                                /* 34*/ MatDuplicate_MPISBAIJ,
2015:                                        0,
2016:                                        0,
2017:                                        0,
2018:                                        0,
2019:                                /* 39*/ MatAXPY_MPISBAIJ,
2020:                                        MatCreateSubMatrices_MPISBAIJ,
2021:                                        MatIncreaseOverlap_MPISBAIJ,
2022:                                        MatGetValues_MPISBAIJ,
2023:                                        MatCopy_MPISBAIJ,
2024:                                /* 44*/ 0,
2025:                                        MatScale_MPISBAIJ,
2026:                                        MatShift_MPISBAIJ,
2027:                                        0,
2028:                                        0,
2029:                                /* 49*/ 0,
2030:                                        0,
2031:                                        0,
2032:                                        0,
2033:                                        0,
2034:                                /* 54*/ 0,
2035:                                        0,
2036:                                        MatSetUnfactored_MPISBAIJ,
2037:                                        0,
2038:                                        MatSetValuesBlocked_MPISBAIJ,
2039:                                /* 59*/ MatCreateSubMatrix_MPISBAIJ,
2040:                                        0,
2041:                                        0,
2042:                                        0,
2043:                                        0,
2044:                                /* 64*/ 0,
2045:                                        0,
2046:                                        0,
2047:                                        0,
2048:                                        0,
2049:                                /* 69*/ MatGetRowMaxAbs_MPISBAIJ,
2050:                                        0,
2051:                                        MatConvert_MPISBAIJ_Basic,
2052:                                        0,
2053:                                        0,
2054:                                /* 74*/ 0,
2055:                                        0,
2056:                                        0,
2057:                                        0,
2058:                                        0,
2059:                                /* 79*/ 0,
2060:                                        0,
2061:                                        0,
2062:                                        0,
2063:                                        MatLoad_MPISBAIJ,
2064:                                /* 84*/ 0,
2065:                                        0,
2066:                                        0,
2067:                                        0,
2068:                                        0,
2069:                                /* 89*/ 0,
2070:                                        0,
2071:                                        0,
2072:                                        0,
2073:                                        0,
2074:                                /* 94*/ 0,
2075:                                        0,
2076:                                        0,
2077:                                        0,
2078:                                        0,
2079:                                /* 99*/ 0,
2080:                                        0,
2081:                                        0,
2082:                                        0,
2083:                                        0,
2084:                                /*104*/ 0,
2085:                                        MatRealPart_MPISBAIJ,
2086:                                        MatImaginaryPart_MPISBAIJ,
2087:                                        MatGetRowUpperTriangular_MPISBAIJ,
2088:                                        MatRestoreRowUpperTriangular_MPISBAIJ,
2089:                                /*109*/ 0,
2090:                                        0,
2091:                                        0,
2092:                                        0,
2093:                                        MatMissingDiagonal_MPISBAIJ,
2094:                                /*114*/ 0,
2095:                                        0,
2096:                                        0,
2097:                                        0,
2098:                                        0,
2099:                                /*119*/ 0,
2100:                                        0,
2101:                                        0,
2102:                                        0,
2103:                                        0,
2104:                                /*124*/ 0,
2105:                                        0,
2106:                                        0,
2107:                                        0,
2108:                                        0,
2109:                                /*129*/ 0,
2110:                                        0,
2111:                                        0,
2112:                                        0,
2113:                                        0,
2114:                                /*134*/ 0,
2115:                                        0,
2116:                                        0,
2117:                                        0,
2118:                                        0,
2119:                                /*139*/ MatSetBlockSizes_Default,
2120:                                        0,
2121:                                        0,
2122:                                        0,
2123:                                        0,
2124:                                 /*144*/MatCreateMPIMatConcatenateSeqMat_MPISBAIJ
2125: };

2127: PetscErrorCode  MatMPISBAIJSetPreallocation_MPISBAIJ(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt *d_nnz,PetscInt o_nz,const PetscInt *o_nnz)
2128: {
2129:   Mat_MPISBAIJ   *b = (Mat_MPISBAIJ*)B->data;
2131:   PetscInt       i,mbs,Mbs;
2132:   PetscMPIInt    size;

2135:   MatSetBlockSize(B,PetscAbs(bs));
2136:   PetscLayoutSetUp(B->rmap);
2137:   PetscLayoutSetUp(B->cmap);
2138:   PetscLayoutGetBlockSize(B->rmap,&bs);
2139:   if (B->rmap->N > B->cmap->N) SETERRQ2(PetscObjectComm((PetscObject)B),PETSC_ERR_SUP,"MPISBAIJ matrix cannot have more rows %D than columns %D",B->rmap->N,B->cmap->N);
2140:   if (B->rmap->n > B->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_SUP,"MPISBAIJ matrix cannot have more local rows %D than columns %D",B->rmap->n,B->cmap->n);

2142:   mbs = B->rmap->n/bs;
2143:   Mbs = B->rmap->N/bs;
2144:   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);

2146:   B->rmap->bs = bs;
2147:   b->bs2      = bs*bs;
2148:   b->mbs      = mbs;
2149:   b->Mbs      = Mbs;
2150:   b->nbs      = B->cmap->n/bs;
2151:   b->Nbs      = B->cmap->N/bs;

2153:   for (i=0; i<=b->size; i++) {
2154:     b->rangebs[i] = B->rmap->range[i]/bs;
2155:   }
2156:   b->rstartbs = B->rmap->rstart/bs;
2157:   b->rendbs   = B->rmap->rend/bs;

2159:   b->cstartbs = B->cmap->rstart/bs;
2160:   b->cendbs   = B->cmap->rend/bs;

2162: #if defined(PETSC_USE_CTABLE)
2163:   PetscTableDestroy(&b->colmap);
2164: #else
2165:   PetscFree(b->colmap);
2166: #endif
2167:   PetscFree(b->garray);
2168:   VecDestroy(&b->lvec);
2169:   VecScatterDestroy(&b->Mvctx);
2170:   VecDestroy(&b->slvec0);
2171:   VecDestroy(&b->slvec0b);
2172:   VecDestroy(&b->slvec1);
2173:   VecDestroy(&b->slvec1a);
2174:   VecDestroy(&b->slvec1b);
2175:   VecScatterDestroy(&b->sMvctx);

2177:   /* Because the B will have been resized we simply destroy it and create a new one each time */
2178:   MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);
2179:   MatDestroy(&b->B);
2180:   MatCreate(PETSC_COMM_SELF,&b->B);
2181:   MatSetSizes(b->B,B->rmap->n,size > 1 ? B->cmap->N : 0,B->rmap->n,size > 1 ? B->cmap->N : 0);
2182:   MatSetType(b->B,MATSEQBAIJ);
2183:   PetscLogObjectParent((PetscObject)B,(PetscObject)b->B);

2185:   if (!B->preallocated) {
2186:     MatCreate(PETSC_COMM_SELF,&b->A);
2187:     MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);
2188:     MatSetType(b->A,MATSEQSBAIJ);
2189:     PetscLogObjectParent((PetscObject)B,(PetscObject)b->A);
2190:     MatStashCreate_Private(PetscObjectComm((PetscObject)B),bs,&B->bstash);
2191:   }

2193:   MatSeqSBAIJSetPreallocation(b->A,bs,d_nz,d_nnz);
2194:   MatSeqBAIJSetPreallocation(b->B,bs,o_nz,o_nnz);

2196:   B->preallocated  = PETSC_TRUE;
2197:   B->was_assembled = PETSC_FALSE;
2198:   B->assembled     = PETSC_FALSE;
2199:   return(0);
2200: }

2202: PetscErrorCode MatMPISBAIJSetPreallocationCSR_MPISBAIJ(Mat B,PetscInt bs,const PetscInt ii[],const PetscInt jj[],const PetscScalar V[])
2203: {
2204:   PetscInt       m,rstart,cend;
2205:   PetscInt       i,j,d,nz,bd, nz_max=0,*d_nnz=0,*o_nnz=0;
2206:   const PetscInt *JJ    =0;
2207:   PetscScalar    *values=0;
2208:   PetscBool      roworiented = ((Mat_MPISBAIJ*)B->data)->roworiented;
2210:   PetscBool      nooffprocentries;

2213:   if (bs < 1) SETERRQ1(PetscObjectComm((PetscObject)B),PETSC_ERR_ARG_OUTOFRANGE,"Invalid block size specified, must be positive but it is %D",bs);
2214:   PetscLayoutSetBlockSize(B->rmap,bs);
2215:   PetscLayoutSetBlockSize(B->cmap,bs);
2216:   PetscLayoutSetUp(B->rmap);
2217:   PetscLayoutSetUp(B->cmap);
2218:   PetscLayoutGetBlockSize(B->rmap,&bs);
2219:   m      = B->rmap->n/bs;
2220:   rstart = B->rmap->rstart/bs;
2221:   cend   = B->cmap->rend/bs;

2223:   if (ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"ii[0] must be 0 but it is %D",ii[0]);
2224:   PetscMalloc2(m,&d_nnz,m,&o_nnz);
2225:   for (i=0; i<m; i++) {
2226:     nz = ii[i+1] - ii[i];
2227:     if (nz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative number of columns %D",i,nz);
2228:     /* count the ones on the diagonal and above, split into diagonal and off diagonal portions. */
2229:     JJ     = jj + ii[i];
2230:     bd     = 0;
2231:     for (j=0; j<nz; j++) {
2232:       if (*JJ >= i + rstart) break;
2233:       JJ++;
2234:       bd++;
2235:     }
2236:     d  = 0;
2237:     for (; j<nz; j++) {
2238:       if (*JJ++ >= cend) break;
2239:       d++;
2240:     }
2241:     d_nnz[i] = d;
2242:     o_nnz[i] = nz - d - bd;
2243:     nz       = nz - bd;
2244:     nz_max = PetscMax(nz_max,nz);
2245:   }
2246:   MatMPISBAIJSetPreallocation(B,bs,0,d_nnz,0,o_nnz);
2247:   MatSetOption(B,MAT_IGNORE_LOWER_TRIANGULAR,PETSC_TRUE);
2248:   PetscFree2(d_nnz,o_nnz);

2250:   values = (PetscScalar*)V;
2251:   if (!values) {
2252:     PetscCalloc1(bs*bs*nz_max,&values);
2253:   }
2254:   for (i=0; i<m; i++) {
2255:     PetscInt          row    = i + rstart;
2256:     PetscInt          ncols  = ii[i+1] - ii[i];
2257:     const PetscInt    *icols = jj + ii[i];
2258:     if (bs == 1 || !roworiented) {         /* block ordering matches the non-nested layout of MatSetValues so we can insert entire rows */
2259:       const PetscScalar *svals = values + (V ? (bs*bs*ii[i]) : 0);
2260:       MatSetValuesBlocked_MPISBAIJ(B,1,&row,ncols,icols,svals,INSERT_VALUES);
2261:     } else {                    /* block ordering does not match so we can only insert one block at a time. */
2262:       PetscInt j;
2263:       for (j=0; j<ncols; j++) {
2264:         const PetscScalar *svals = values + (V ? (bs*bs*(ii[i]+j)) : 0);
2265:         MatSetValuesBlocked_MPISBAIJ(B,1,&row,1,&icols[j],svals,INSERT_VALUES);
2266:       }
2267:     }
2268:   }

2270:   if (!V) { PetscFree(values); }
2271:   nooffprocentries    = B->nooffprocentries;
2272:   B->nooffprocentries = PETSC_TRUE;
2273:   MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
2274:   MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);
2275:   B->nooffprocentries = nooffprocentries;

2277:   MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);
2278:   return(0);
2279: }

2281: /*MC
2282:    MATMPISBAIJ - MATMPISBAIJ = "mpisbaij" - A matrix type to be used for distributed symmetric sparse block matrices,
2283:    based on block compressed sparse row format.  Only the upper triangular portion of the "diagonal" portion of
2284:    the matrix is stored.

2286:    For complex numbers by default this matrix is symmetric, NOT Hermitian symmetric. To make it Hermitian symmetric you
2287:    can call MatSetOption(Mat, MAT_HERMITIAN);

2289:    Options Database Keys:
2290: . -mat_type mpisbaij - sets the matrix type to "mpisbaij" during a call to MatSetFromOptions()

2292:    Notes:
2293:      The number of rows in the matrix must be less than or equal to the number of columns. Similarly the number of rows in the
2294:      diagonal portion of the matrix of each process has to less than or equal the number of columns.

2296:    Level: beginner

2298: .seealso: MatCreateMPISBAIJ(), MATSEQSBAIJ, MatType
2299: M*/

2301: PETSC_EXTERN PetscErrorCode MatCreate_MPISBAIJ(Mat B)
2302: {
2303:   Mat_MPISBAIJ   *b;
2305:   PetscBool      flg = PETSC_FALSE;

2308:   PetscNewLog(B,&b);
2309:   B->data = (void*)b;
2310:   PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));

2312:   B->ops->destroy = MatDestroy_MPISBAIJ;
2313:   B->ops->view    = MatView_MPISBAIJ;
2314:   B->assembled    = PETSC_FALSE;
2315:   B->insertmode   = NOT_SET_VALUES;

2317:   MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);
2318:   MPI_Comm_size(PetscObjectComm((PetscObject)B),&b->size);

2320:   /* build local table of row and column ownerships */
2321:   PetscMalloc1(b->size+2,&b->rangebs);

2323:   /* build cache for off array entries formed */
2324:   MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);

2326:   b->donotstash  = PETSC_FALSE;
2327:   b->colmap      = NULL;
2328:   b->garray      = NULL;
2329:   b->roworiented = PETSC_TRUE;

2331:   /* stuff used in block assembly */
2332:   b->barray = 0;

2334:   /* stuff used for matrix vector multiply */
2335:   b->lvec    = 0;
2336:   b->Mvctx   = 0;
2337:   b->slvec0  = 0;
2338:   b->slvec0b = 0;
2339:   b->slvec1  = 0;
2340:   b->slvec1a = 0;
2341:   b->slvec1b = 0;
2342:   b->sMvctx  = 0;

2344:   /* stuff for MatGetRow() */
2345:   b->rowindices   = 0;
2346:   b->rowvalues    = 0;
2347:   b->getrowactive = PETSC_FALSE;

2349:   /* hash table stuff */
2350:   b->ht           = 0;
2351:   b->hd           = 0;
2352:   b->ht_size      = 0;
2353:   b->ht_flag      = PETSC_FALSE;
2354:   b->ht_fact      = 0;
2355:   b->ht_total_ct  = 0;
2356:   b->ht_insert_ct = 0;

2358:   /* stuff for MatCreateSubMatrices_MPIBAIJ_local() */
2359:   b->ijonly = PETSC_FALSE;

2361:   b->in_loc = 0;
2362:   b->v_loc  = 0;
2363:   b->n_loc  = 0;

2365:   PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPISBAIJ);
2366:   PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPISBAIJ);
2367:   PetscObjectComposeFunction((PetscObject)B,"MatMPISBAIJSetPreallocation_C",MatMPISBAIJSetPreallocation_MPISBAIJ);
2368:   PetscObjectComposeFunction((PetscObject)B,"MatMPISBAIJSetPreallocationCSR_C",MatMPISBAIJSetPreallocationCSR_MPISBAIJ);
2369: #if defined(PETSC_HAVE_ELEMENTAL)
2370:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpisbaij_elemental_C",MatConvert_MPISBAIJ_Elemental);
2371: #endif
2372:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpisbaij_mpiaij_C",MatConvert_MPISBAIJ_Basic);
2373:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpisbaij_mpibaij_C",MatConvert_MPISBAIJ_Basic);

2375:   B->symmetric                  = PETSC_TRUE;
2376:   B->structurally_symmetric     = PETSC_TRUE;
2377:   B->symmetric_set              = PETSC_TRUE;
2378:   B->structurally_symmetric_set = PETSC_TRUE;
2379:   B->symmetric_eternal          = PETSC_TRUE;

2381:   B->hermitian                  = PETSC_FALSE;
2382:   B->hermitian_set              = PETSC_FALSE;

2384:   PetscObjectChangeTypeName((PetscObject)B,MATMPISBAIJ);
2385:   PetscOptionsBegin(PetscObjectComm((PetscObject)B),NULL,"Options for loading MPISBAIJ matrix 1","Mat");
2386:   PetscOptionsBool("-mat_use_hash_table","Use hash table to save memory in constructing matrix","MatSetOption",flg,&flg,NULL);
2387:   if (flg) {
2388:     PetscReal fact = 1.39;
2389:     MatSetOption(B,MAT_USE_HASH_TABLE,PETSC_TRUE);
2390:     PetscOptionsReal("-mat_use_hash_table","Use hash table factor","MatMPIBAIJSetHashTableFactor",fact,&fact,NULL);
2391:     if (fact <= 1.0) fact = 1.39;
2392:     MatMPIBAIJSetHashTableFactor(B,fact);
2393:     PetscInfo1(B,"Hash table Factor used %5.2f\n",fact);
2394:   }
2395:   PetscOptionsEnd();
2396:   return(0);
2397: }

2399: /*MC
2400:    MATSBAIJ - MATSBAIJ = "sbaij" - A matrix type to be used for symmetric block sparse matrices.

2402:    This matrix type is identical to MATSEQSBAIJ when constructed with a single process communicator,
2403:    and MATMPISBAIJ otherwise.

2405:    Options Database Keys:
2406: . -mat_type sbaij - sets the matrix type to "sbaij" during a call to MatSetFromOptions()

2408:   Level: beginner

2410: .seealso: MatCreateMPISBAIJ,MATSEQSBAIJ,MATMPISBAIJ
2411: M*/

2413: /*@C
2414:    MatMPISBAIJSetPreallocation - For good matrix assembly performance
2415:    the user should preallocate the matrix storage by setting the parameters
2416:    d_nz (or d_nnz) and o_nz (or o_nnz).  By setting these parameters accurately,
2417:    performance can be increased by more than a factor of 50.

2419:    Collective on Mat

2421:    Input Parameters:
2422: +  B - the matrix
2423: .  bs   - size of block, the blocks are ALWAYS square. One can use MatSetBlockSizes() to set a different row and column blocksize but the row
2424:           blocksize always defines the size of the blocks. The column blocksize sets the blocksize of the vectors obtained with MatCreateVecs()
2425: .  d_nz  - number of block nonzeros per block row in diagonal portion of local
2426:            submatrix  (same for all local rows)
2427: .  d_nnz - array containing the number of block nonzeros in the various block rows
2428:            in the upper triangular and diagonal part of the in diagonal portion of the local
2429:            (possibly different for each block row) or NULL.  If you plan to factor the matrix you must leave room
2430:            for the diagonal entry and set a value even if it is zero.
2431: .  o_nz  - number of block nonzeros per block row in the off-diagonal portion of local
2432:            submatrix (same for all local rows).
2433: -  o_nnz - array containing the number of nonzeros in the various block rows of the
2434:            off-diagonal portion of the local submatrix that is right of the diagonal
2435:            (possibly different for each block row) or NULL.


2438:    Options Database Keys:
2439: +   -mat_no_unroll - uses code that does not unroll the loops in the
2440:                      block calculations (much slower)
2441: -   -mat_block_size - size of the blocks to use

2443:    Notes:

2445:    If PETSC_DECIDE or  PETSC_DETERMINE is used for a particular argument on one processor
2446:    than it must be used on all processors that share the object for that argument.

2448:    If the *_nnz parameter is given then the *_nz parameter is ignored

2450:    Storage Information:
2451:    For a square global matrix we define each processor's diagonal portion
2452:    to be its local rows and the corresponding columns (a square submatrix);
2453:    each processor's off-diagonal portion encompasses the remainder of the
2454:    local matrix (a rectangular submatrix).

2456:    The user can specify preallocated storage for the diagonal part of
2457:    the local submatrix with either d_nz or d_nnz (not both).  Set
2458:    d_nz=PETSC_DEFAULT and d_nnz=NULL for PETSc to control dynamic
2459:    memory allocation.  Likewise, specify preallocated storage for the
2460:    off-diagonal part of the local submatrix with o_nz or o_nnz (not both).

2462:    You can call MatGetInfo() to get information on how effective the preallocation was;
2463:    for example the fields mallocs,nz_allocated,nz_used,nz_unneeded;
2464:    You can also run with the option -info and look for messages with the string
2465:    malloc in them to see if additional memory allocation was needed.

2467:    Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In
2468:    the figure below we depict these three local rows and all columns (0-11).

2470: .vb
2471:            0 1 2 3 4 5 6 7 8 9 10 11
2472:           --------------------------
2473:    row 3  |. . . d d d o o o o  o  o
2474:    row 4  |. . . d d d o o o o  o  o
2475:    row 5  |. . . d d d o o o o  o  o
2476:           --------------------------
2477: .ve

2479:    Thus, any entries in the d locations are stored in the d (diagonal)
2480:    submatrix, and any entries in the o locations are stored in the
2481:    o (off-diagonal) submatrix.  Note that the d matrix is stored in
2482:    MatSeqSBAIJ format and the o submatrix in MATSEQBAIJ format.

2484:    Now d_nz should indicate the number of block nonzeros per row in the upper triangular
2485:    plus the diagonal part of the d matrix,
2486:    and o_nz should indicate the number of block nonzeros per row in the o matrix

2488:    In general, for PDE problems in which most nonzeros are near the diagonal,
2489:    one expects d_nz >> o_nz.   For large problems you MUST preallocate memory
2490:    or you will get TERRIBLE performance; see the users' manual chapter on
2491:    matrices.

2493:    Level: intermediate

2495: .seealso: MatCreate(), MatCreateSeqSBAIJ(), MatSetValues(), MatCreateBAIJ(), PetscSplitOwnership()
2496: @*/
2497: PetscErrorCode  MatMPISBAIJSetPreallocation(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[])
2498: {

2505:   PetscTryMethod(B,"MatMPISBAIJSetPreallocation_C",(Mat,PetscInt,PetscInt,const PetscInt[],PetscInt,const PetscInt[]),(B,bs,d_nz,d_nnz,o_nz,o_nnz));
2506:   return(0);
2507: }

2509: /*@C
2510:    MatCreateSBAIJ - Creates a sparse parallel matrix in symmetric block AIJ format
2511:    (block compressed row).  For good matrix assembly performance
2512:    the user should preallocate the matrix storage by setting the parameters
2513:    d_nz (or d_nnz) and o_nz (or o_nnz).  By setting these parameters accurately,
2514:    performance can be increased by more than a factor of 50.

2516:    Collective

2518:    Input Parameters:
2519: +  comm - MPI communicator
2520: .  bs   - size of block, the blocks are ALWAYS square. One can use MatSetBlockSizes() to set a different row and column blocksize but the row
2521:           blocksize always defines the size of the blocks. The column blocksize sets the blocksize of the vectors obtained with MatCreateVecs()
2522: .  m - number of local rows (or PETSC_DECIDE to have calculated if M is given)
2523:            This value should be the same as the local size used in creating the
2524:            y vector for the matrix-vector product y = Ax.
2525: .  n - number of local columns (or PETSC_DECIDE to have calculated if N is given)
2526:            This value should be the same as the local size used in creating the
2527:            x vector for the matrix-vector product y = Ax.
2528: .  M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
2529: .  N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
2530: .  d_nz  - number of block nonzeros per block row in diagonal portion of local
2531:            submatrix  (same for all local rows)
2532: .  d_nnz - array containing the number of block nonzeros in the various block rows
2533:            in the upper triangular portion of the in diagonal portion of the local
2534:            (possibly different for each block block row) or NULL.
2535:            If you plan to factor the matrix you must leave room for the diagonal entry and
2536:            set its value even if it is zero.
2537: .  o_nz  - number of block nonzeros per block row in the off-diagonal portion of local
2538:            submatrix (same for all local rows).
2539: -  o_nnz - array containing the number of nonzeros in the various block rows of the
2540:            off-diagonal portion of the local submatrix (possibly different for
2541:            each block row) or NULL.

2543:    Output Parameter:
2544: .  A - the matrix

2546:    Options Database Keys:
2547: +   -mat_no_unroll - uses code that does not unroll the loops in the
2548:                      block calculations (much slower)
2549: .   -mat_block_size - size of the blocks to use
2550: -   -mat_mpi - use the parallel matrix data structures even on one processor
2551:                (defaults to using SeqBAIJ format on one processor)

2553:    It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(),
2554:    MatXXXXSetPreallocation() paradigm instead of this routine directly.
2555:    [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation]

2557:    Notes:
2558:    The number of rows and columns must be divisible by blocksize.
2559:    This matrix type does not support complex Hermitian operation.

2561:    The user MUST specify either the local or global matrix dimensions
2562:    (possibly both).

2564:    If PETSC_DECIDE or  PETSC_DETERMINE is used for a particular argument on one processor
2565:    than it must be used on all processors that share the object for that argument.

2567:    If the *_nnz parameter is given then the *_nz parameter is ignored

2569:    Storage Information:
2570:    For a square global matrix we define each processor's diagonal portion
2571:    to be its local rows and the corresponding columns (a square submatrix);
2572:    each processor's off-diagonal portion encompasses the remainder of the
2573:    local matrix (a rectangular submatrix).

2575:    The user can specify preallocated storage for the diagonal part of
2576:    the local submatrix with either d_nz or d_nnz (not both).  Set
2577:    d_nz=PETSC_DEFAULT and d_nnz=NULL for PETSc to control dynamic
2578:    memory allocation.  Likewise, specify preallocated storage for the
2579:    off-diagonal part of the local submatrix with o_nz or o_nnz (not both).

2581:    Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In
2582:    the figure below we depict these three local rows and all columns (0-11).

2584: .vb
2585:            0 1 2 3 4 5 6 7 8 9 10 11
2586:           --------------------------
2587:    row 3  |. . . d d d o o o o  o  o
2588:    row 4  |. . . d d d o o o o  o  o
2589:    row 5  |. . . d d d o o o o  o  o
2590:           --------------------------
2591: .ve

2593:    Thus, any entries in the d locations are stored in the d (diagonal)
2594:    submatrix, and any entries in the o locations are stored in the
2595:    o (off-diagonal) submatrix.  Note that the d matrix is stored in
2596:    MatSeqSBAIJ format and the o submatrix in MATSEQBAIJ format.

2598:    Now d_nz should indicate the number of block nonzeros per row in the upper triangular
2599:    plus the diagonal part of the d matrix,
2600:    and o_nz should indicate the number of block nonzeros per row in the o matrix.
2601:    In general, for PDE problems in which most nonzeros are near the diagonal,
2602:    one expects d_nz >> o_nz.   For large problems you MUST preallocate memory
2603:    or you will get TERRIBLE performance; see the users' manual chapter on
2604:    matrices.

2606:    Level: intermediate

2608: .seealso: MatCreate(), MatCreateSeqSBAIJ(), MatSetValues(), MatCreateBAIJ()
2609: @*/

2611: 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)
2612: {
2614:   PetscMPIInt    size;

2617:   MatCreate(comm,A);
2618:   MatSetSizes(*A,m,n,M,N);
2619:   MPI_Comm_size(comm,&size);
2620:   if (size > 1) {
2621:     MatSetType(*A,MATMPISBAIJ);
2622:     MatMPISBAIJSetPreallocation(*A,bs,d_nz,d_nnz,o_nz,o_nnz);
2623:   } else {
2624:     MatSetType(*A,MATSEQSBAIJ);
2625:     MatSeqSBAIJSetPreallocation(*A,bs,d_nz,d_nnz);
2626:   }
2627:   return(0);
2628: }


2631: static PetscErrorCode MatDuplicate_MPISBAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat)
2632: {
2633:   Mat            mat;
2634:   Mat_MPISBAIJ   *a,*oldmat = (Mat_MPISBAIJ*)matin->data;
2636:   PetscInt       len=0,nt,bs=matin->rmap->bs,mbs=oldmat->mbs;
2637:   PetscScalar    *array;

2640:   *newmat = 0;

2642:   MatCreate(PetscObjectComm((PetscObject)matin),&mat);
2643:   MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);
2644:   MatSetType(mat,((PetscObject)matin)->type_name);
2645:   PetscLayoutReference(matin->rmap,&mat->rmap);
2646:   PetscLayoutReference(matin->cmap,&mat->cmap);

2648:   mat->factortype   = matin->factortype;
2649:   mat->preallocated = PETSC_TRUE;
2650:   mat->assembled    = PETSC_TRUE;
2651:   mat->insertmode   = NOT_SET_VALUES;

2653:   a      = (Mat_MPISBAIJ*)mat->data;
2654:   a->bs2 = oldmat->bs2;
2655:   a->mbs = oldmat->mbs;
2656:   a->nbs = oldmat->nbs;
2657:   a->Mbs = oldmat->Mbs;
2658:   a->Nbs = oldmat->Nbs;

2660:   a->size         = oldmat->size;
2661:   a->rank         = oldmat->rank;
2662:   a->donotstash   = oldmat->donotstash;
2663:   a->roworiented  = oldmat->roworiented;
2664:   a->rowindices   = 0;
2665:   a->rowvalues    = 0;
2666:   a->getrowactive = PETSC_FALSE;
2667:   a->barray       = 0;
2668:   a->rstartbs     = oldmat->rstartbs;
2669:   a->rendbs       = oldmat->rendbs;
2670:   a->cstartbs     = oldmat->cstartbs;
2671:   a->cendbs       = oldmat->cendbs;

2673:   /* hash table stuff */
2674:   a->ht           = 0;
2675:   a->hd           = 0;
2676:   a->ht_size      = 0;
2677:   a->ht_flag      = oldmat->ht_flag;
2678:   a->ht_fact      = oldmat->ht_fact;
2679:   a->ht_total_ct  = 0;
2680:   a->ht_insert_ct = 0;

2682:   PetscArraycpy(a->rangebs,oldmat->rangebs,a->size+2);
2683:   if (oldmat->colmap) {
2684: #if defined(PETSC_USE_CTABLE)
2685:     PetscTableCreateCopy(oldmat->colmap,&a->colmap);
2686: #else
2687:     PetscMalloc1(a->Nbs,&a->colmap);
2688:     PetscLogObjectMemory((PetscObject)mat,(a->Nbs)*sizeof(PetscInt));
2689:     PetscArraycpy(a->colmap,oldmat->colmap,a->Nbs);
2690: #endif
2691:   } else a->colmap = 0;

2693:   if (oldmat->garray && (len = ((Mat_SeqBAIJ*)(oldmat->B->data))->nbs)) {
2694:     PetscMalloc1(len,&a->garray);
2695:     PetscLogObjectMemory((PetscObject)mat,len*sizeof(PetscInt));
2696:     PetscArraycpy(a->garray,oldmat->garray,len);
2697:   } else a->garray = 0;

2699:   MatStashCreate_Private(PetscObjectComm((PetscObject)matin),matin->rmap->bs,&mat->bstash);
2700:   VecDuplicate(oldmat->lvec,&a->lvec);
2701:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->lvec);
2702:   VecScatterCopy(oldmat->Mvctx,&a->Mvctx);
2703:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->Mvctx);

2705:   VecDuplicate(oldmat->slvec0,&a->slvec0);
2706:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec0);
2707:   VecDuplicate(oldmat->slvec1,&a->slvec1);
2708:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec1);

2710:   VecGetLocalSize(a->slvec1,&nt);
2711:   VecGetArray(a->slvec1,&array);
2712:   VecCreateSeqWithArray(PETSC_COMM_SELF,1,bs*mbs,array,&a->slvec1a);
2713:   VecCreateSeqWithArray(PETSC_COMM_SELF,1,nt-bs*mbs,array+bs*mbs,&a->slvec1b);
2714:   VecRestoreArray(a->slvec1,&array);
2715:   VecGetArray(a->slvec0,&array);
2716:   VecCreateSeqWithArray(PETSC_COMM_SELF,1,nt-bs*mbs,array+bs*mbs,&a->slvec0b);
2717:   VecRestoreArray(a->slvec0,&array);
2718:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec0);
2719:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec1);
2720:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec0b);
2721:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec1a);
2722:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec1b);

2724:   /*  VecScatterCopy(oldmat->sMvctx,&a->sMvctx); - not written yet, replaced by the lazy trick: */
2725:   PetscObjectReference((PetscObject)oldmat->sMvctx);
2726:   a->sMvctx = oldmat->sMvctx;
2727:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->sMvctx);

2729:   MatDuplicate(oldmat->A,cpvalues,&a->A);
2730:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->A);
2731:   MatDuplicate(oldmat->B,cpvalues,&a->B);
2732:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->B);
2733:   PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);
2734:   *newmat = mat;
2735:   return(0);
2736: }

2738: PetscErrorCode MatLoad_MPISBAIJ(Mat newmat,PetscViewer viewer)
2739: {
2741:   PetscInt       i,nz,j,rstart,rend;
2742:   PetscScalar    *vals,*buf;
2743:   MPI_Comm       comm;
2744:   MPI_Status     status;
2745:   PetscMPIInt    rank,size,tag = ((PetscObject)viewer)->tag,*sndcounts = 0,*browners,maxnz,*rowners,mmbs;
2746:   PetscInt       header[4],*rowlengths = 0,M,N,m,*cols,*locrowlens;
2747:   PetscInt       *procsnz = 0,jj,*mycols,*ibuf;
2748:   PetscInt       bs = newmat->rmap->bs,Mbs,mbs,extra_rows;
2749:   PetscInt       *dlens,*odlens,*mask,*masked1,*masked2,rowcount,odcount;
2750:   PetscInt       dcount,kmax,k,nzcount,tmp;
2751:   int            fd;
2752:   PetscBool      isbinary;

2755:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);
2756:   if (!isbinary) SETERRQ2(PetscObjectComm((PetscObject)newmat),PETSC_ERR_SUP,"Viewer type %s not yet supported for reading %s matrices",((PetscObject)viewer)->type_name,((PetscObject)newmat)->type_name);

2758:   /* force binary viewer to load .info file if it has not yet done so */
2759:   PetscViewerSetUp(viewer);
2760:   PetscObjectGetComm((PetscObject)viewer,&comm);
2761:   PetscOptionsBegin(comm,NULL,"Options for loading MPISBAIJ matrix 2","Mat");
2762:   PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);
2763:   PetscOptionsEnd();
2764:   if (bs < 0) bs = 1;

2766:   MPI_Comm_size(comm,&size);
2767:   MPI_Comm_rank(comm,&rank);
2768:   PetscViewerBinaryGetDescriptor(viewer,&fd);
2769:   if (!rank) {
2770:     PetscBinaryRead(fd,(char*)header,4,NULL,PETSC_INT);
2771:     if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object");
2772:     if (header[3] < 0) SETERRQ(PetscObjectComm((PetscObject)newmat),PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format, cannot load as MPISBAIJ");
2773:   }

2775:   MPI_Bcast(header+1,3,MPIU_INT,0,comm);
2776:   M    = header[1];
2777:   N    = header[2];

2779:   /* If global sizes are set, check if they are consistent with that given in the file */
2780:   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);
2781:   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);

2783:   if (M != N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Can only do square matrices");

2785:   /*
2786:      This code adds extra rows to make sure the number of rows is
2787:      divisible by the blocksize
2788:   */
2789:   Mbs        = M/bs;
2790:   extra_rows = bs - M + bs*(Mbs);
2791:   if (extra_rows == bs) extra_rows = 0;
2792:   else                  Mbs++;
2793:   if (extra_rows &&!rank) {
2794:     PetscInfo(viewer,"Padding loaded matrix to match blocksize\n");
2795:   }

2797:   /* determine ownership of all rows */
2798:   if (newmat->rmap->n < 0) { /* PETSC_DECIDE */
2799:     mbs = Mbs/size + ((Mbs % size) > rank);
2800:     m   = mbs*bs;
2801:   } else { /* User Set */
2802:     m   = newmat->rmap->n;
2803:     mbs = m/bs;
2804:   }
2805:   PetscMalloc2(size+1,&rowners,size+1,&browners);
2806:   PetscMPIIntCast(mbs,&mmbs);
2807:   MPI_Allgather(&mmbs,1,MPI_INT,rowners+1,1,MPI_INT,comm);
2808:   rowners[0] = 0;
2809:   for (i=2; i<=size; i++) rowners[i] += rowners[i-1];
2810:   for (i=0; i<=size; i++) browners[i] = rowners[i]*bs;
2811:   rstart = rowners[rank];
2812:   rend   = rowners[rank+1];

2814:   /* distribute row lengths to all processors */
2815:   PetscMalloc1((rend-rstart)*bs,&locrowlens);
2816:   if (!rank) {
2817:     PetscMalloc1(M+extra_rows,&rowlengths);
2818:     PetscBinaryRead(fd,rowlengths,M,NULL,PETSC_INT);
2819:     for (i=0; i<extra_rows; i++) rowlengths[M+i] = 1;
2820:     PetscMalloc1(size,&sndcounts);
2821:     for (i=0; i<size; i++) sndcounts[i] = browners[i+1] - browners[i];
2822:     MPI_Scatterv(rowlengths,sndcounts,browners,MPIU_INT,locrowlens,(rend-rstart)*bs,MPIU_INT,0,comm);
2823:     PetscFree(sndcounts);
2824:   } else {
2825:     MPI_Scatterv(0,0,0,MPIU_INT,locrowlens,(rend-rstart)*bs,MPIU_INT,0,comm);
2826:   }

2828:   if (!rank) {   /* procs[0] */
2829:     /* calculate the number of nonzeros on each processor */
2830:     PetscCalloc1(size,&procsnz);
2831:     for (i=0; i<size; i++) {
2832:       for (j=rowners[i]*bs; j< rowners[i+1]*bs; j++) {
2833:         procsnz[i] += rowlengths[j];
2834:       }
2835:     }
2836:     PetscFree(rowlengths);

2838:     /* determine max buffer needed and allocate it */
2839:     maxnz = 0;
2840:     for (i=0; i<size; i++) {
2841:       maxnz = PetscMax(maxnz,procsnz[i]);
2842:     }
2843:     PetscMalloc1(maxnz,&cols);

2845:     /* read in my part of the matrix column indices  */
2846:     nz     = procsnz[0];
2847:     PetscMalloc1(nz,&ibuf);
2848:     mycols = ibuf;
2849:     if (size == 1) nz -= extra_rows;
2850:     PetscBinaryRead(fd,mycols,nz,NULL,PETSC_INT);
2851:     if (size == 1) {
2852:       for (i=0; i< extra_rows; i++) mycols[nz+i] = M+i;
2853:     }

2855:     /* read in every ones (except the last) and ship off */
2856:     for (i=1; i<size-1; i++) {
2857:       nz   = procsnz[i];
2858:       PetscBinaryRead(fd,cols,nz,NULL,PETSC_INT);
2859:       MPI_Send(cols,nz,MPIU_INT,i,tag,comm);
2860:     }
2861:     /* read in the stuff for the last proc */
2862:     if (size != 1) {
2863:       nz   = procsnz[size-1] - extra_rows;  /* the extra rows are not on the disk */
2864:       PetscBinaryRead(fd,cols,nz,NULL,PETSC_INT);
2865:       for (i=0; i<extra_rows; i++) cols[nz+i] = M+i;
2866:       MPI_Send(cols,nz+extra_rows,MPIU_INT,size-1,tag,comm);
2867:     }
2868:     PetscFree(cols);
2869:   } else {  /* procs[i], i>0 */
2870:     /* determine buffer space needed for message */
2871:     nz = 0;
2872:     for (i=0; i<m; i++) nz += locrowlens[i];
2873:     PetscMalloc1(nz,&ibuf);
2874:     mycols = ibuf;
2875:     /* receive message of column indices*/
2876:     MPI_Recv(mycols,nz,MPIU_INT,0,tag,comm,&status);
2877:     MPI_Get_count(&status,MPIU_INT,&maxnz);
2878:     if (maxnz != nz) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file");
2879:   }

2881:   /* loop over local rows, determining number of off diagonal entries */
2882:   PetscMalloc2(rend-rstart,&dlens,rend-rstart,&odlens);
2883:   PetscCalloc3(Mbs,&mask,Mbs,&masked1,Mbs,&masked2);
2884:   rowcount = 0;
2885:   nzcount  = 0;
2886:   for (i=0; i<mbs; i++) {
2887:     dcount  = 0;
2888:     odcount = 0;
2889:     for (j=0; j<bs; j++) {
2890:       kmax = locrowlens[rowcount];
2891:       for (k=0; k<kmax; k++) {
2892:         tmp = mycols[nzcount++]/bs; /* block col. index */
2893:         if (!mask[tmp]) {
2894:           mask[tmp] = 1;
2895:           if (tmp < rstart || tmp >= rend) masked2[odcount++] = tmp; /* entry in off-diag portion */
2896:           else masked1[dcount++] = tmp; /* entry in diag portion */
2897:         }
2898:       }
2899:       rowcount++;
2900:     }

2902:     dlens[i]  = dcount;  /* d_nzz[i] */
2903:     odlens[i] = odcount; /* o_nzz[i] */

2905:     /* zero out the mask elements we set */
2906:     for (j=0; j<dcount; j++) mask[masked1[j]] = 0;
2907:     for (j=0; j<odcount; j++) mask[masked2[j]] = 0;
2908:   }
2909:   MatSetSizes(newmat,m,m,M+extra_rows,N+extra_rows);
2910:   MatMPISBAIJSetPreallocation(newmat,bs,0,dlens,0,odlens);
2911:   MatSetOption(newmat,MAT_IGNORE_LOWER_TRIANGULAR,PETSC_TRUE);

2913:   if (!rank) {
2914:     PetscMalloc1(maxnz,&buf);
2915:     /* read in my part of the matrix numerical values  */
2916:     nz     = procsnz[0];
2917:     vals   = buf;
2918:     mycols = ibuf;
2919:     if (size == 1) nz -= extra_rows;
2920:     PetscBinaryRead(fd,vals,nz,NULL,PETSC_SCALAR);
2921:     if (size == 1) {
2922:       for (i=0; i< extra_rows; i++) vals[nz+i] = 1.0;
2923:     }

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

2934:     /* read in other processors (except the last one) and ship out */
2935:     for (i=1; i<size-1; i++) {
2936:       nz   = procsnz[i];
2937:       vals = buf;
2938:       PetscBinaryRead(fd,vals,nz,NULL,PETSC_SCALAR);
2939:       MPI_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newmat)->tag,comm);
2940:     }
2941:     /* the last proc */
2942:     if (size != 1) {
2943:       nz   = procsnz[i] - extra_rows;
2944:       vals = buf;
2945:       PetscBinaryRead(fd,vals,nz,NULL,PETSC_SCALAR);
2946:       for (i=0; i<extra_rows; i++) vals[nz+i] = 1.0;
2947:       MPI_Send(vals,nz+extra_rows,MPIU_SCALAR,size-1,((PetscObject)newmat)->tag,comm);
2948:     }
2949:     PetscFree(procsnz);

2951:   } else {
2952:     /* receive numeric values */
2953:     PetscMalloc1(nz,&buf);

2955:     /* receive message of values*/
2956:     vals   = buf;
2957:     mycols = ibuf;
2958:     MPI_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newmat)->tag,comm,&status);
2959:     MPI_Get_count(&status,MPIU_SCALAR,&maxnz);
2960:     if (maxnz != nz) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file");

2962:     /* insert into matrix */
2963:     jj = rstart*bs;
2964:     for (i=0; i<m; i++) {
2965:       MatSetValues_MPISBAIJ(newmat,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);
2966:       mycols += locrowlens[i];
2967:       vals   += locrowlens[i];
2968:       jj++;
2969:     }
2970:   }

2972:   PetscFree(locrowlens);
2973:   PetscFree(buf);
2974:   PetscFree(ibuf);
2975:   PetscFree2(rowners,browners);
2976:   PetscFree2(dlens,odlens);
2977:   PetscFree3(mask,masked1,masked2);
2978:   MatAssemblyBegin(newmat,MAT_FINAL_ASSEMBLY);
2979:   MatAssemblyEnd(newmat,MAT_FINAL_ASSEMBLY);
2980:   return(0);
2981: }

2983: /*XXXXX@
2984:    MatMPISBAIJSetHashTableFactor - Sets the factor required to compute the size of the HashTable.

2986:    Input Parameters:
2987: .  mat  - the matrix
2988: .  fact - factor

2990:    Not Collective on Mat, each process can have a different hash factor

2992:    Level: advanced

2994:   Notes:
2995:    This can also be set by the command line option: -mat_use_hash_table fact

2997: .seealso: MatSetOption()
2998: @XXXXX*/


3001: PetscErrorCode MatGetRowMaxAbs_MPISBAIJ(Mat A,Vec v,PetscInt idx[])
3002: {
3003:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;
3004:   Mat_SeqBAIJ    *b = (Mat_SeqBAIJ*)(a->B)->data;
3005:   PetscReal      atmp;
3006:   PetscReal      *work,*svalues,*rvalues;
3008:   PetscInt       i,bs,mbs,*bi,*bj,brow,j,ncols,krow,kcol,col,row,Mbs,bcol;
3009:   PetscMPIInt    rank,size;
3010:   PetscInt       *rowners_bs,dest,count,source;
3011:   PetscScalar    *va;
3012:   MatScalar      *ba;
3013:   MPI_Status     stat;

3016:   if (idx) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Send email to petsc-maint@mcs.anl.gov");
3017:   MatGetRowMaxAbs(a->A,v,NULL);
3018:   VecGetArray(v,&va);

3020:   MPI_Comm_size(PetscObjectComm((PetscObject)A),&size);
3021:   MPI_Comm_rank(PetscObjectComm((PetscObject)A),&rank);

3023:   bs  = A->rmap->bs;
3024:   mbs = a->mbs;
3025:   Mbs = a->Mbs;
3026:   ba  = b->a;
3027:   bi  = b->i;
3028:   bj  = b->j;

3030:   /* find ownerships */
3031:   rowners_bs = A->rmap->range;

3033:   /* each proc creates an array to be distributed */
3034:   PetscCalloc1(bs*Mbs,&work);

3036:   /* row_max for B */
3037:   if (rank != size-1) {
3038:     for (i=0; i<mbs; i++) {
3039:       ncols = bi[1] - bi[0]; bi++;
3040:       brow  = bs*i;
3041:       for (j=0; j<ncols; j++) {
3042:         bcol = bs*(*bj);
3043:         for (kcol=0; kcol<bs; kcol++) {
3044:           col  = bcol + kcol;                /* local col index */
3045:           col += rowners_bs[rank+1];      /* global col index */
3046:           for (krow=0; krow<bs; krow++) {
3047:             atmp = PetscAbsScalar(*ba); ba++;
3048:             row  = brow + krow;   /* local row index */
3049:             if (PetscRealPart(va[row]) < atmp) va[row] = atmp;
3050:             if (work[col] < atmp) work[col] = atmp;
3051:           }
3052:         }
3053:         bj++;
3054:       }
3055:     }

3057:     /* send values to its owners */
3058:     for (dest=rank+1; dest<size; dest++) {
3059:       svalues = work + rowners_bs[dest];
3060:       count   = rowners_bs[dest+1]-rowners_bs[dest];
3061:       MPI_Send(svalues,count,MPIU_REAL,dest,rank,PetscObjectComm((PetscObject)A));
3062:     }
3063:   }

3065:   /* receive values */
3066:   if (rank) {
3067:     rvalues = work;
3068:     count   = rowners_bs[rank+1]-rowners_bs[rank];
3069:     for (source=0; source<rank; source++) {
3070:       MPI_Recv(rvalues,count,MPIU_REAL,MPI_ANY_SOURCE,MPI_ANY_TAG,PetscObjectComm((PetscObject)A),&stat);
3071:       /* process values */
3072:       for (i=0; i<count; i++) {
3073:         if (PetscRealPart(va[i]) < rvalues[i]) va[i] = rvalues[i];
3074:       }
3075:     }
3076:   }

3078:   VecRestoreArray(v,&va);
3079:   PetscFree(work);
3080:   return(0);
3081: }

3083: PetscErrorCode MatSOR_MPISBAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx)
3084: {
3085:   Mat_MPISBAIJ      *mat = (Mat_MPISBAIJ*)matin->data;
3086:   PetscErrorCode    ierr;
3087:   PetscInt          mbs=mat->mbs,bs=matin->rmap->bs;
3088:   PetscScalar       *x,*ptr,*from;
3089:   Vec               bb1;
3090:   const PetscScalar *b;

3093:   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);
3094:   if (bs > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"SSOR for block size > 1 is not yet implemented");

3096:   if (flag == SOR_APPLY_UPPER) {
3097:     (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
3098:     return(0);
3099:   }

3101:   if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) {
3102:     if (flag & SOR_ZERO_INITIAL_GUESS) {
3103:       (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,lits,xx);
3104:       its--;
3105:     }

3107:     VecDuplicate(bb,&bb1);
3108:     while (its--) {

3110:       /* lower triangular part: slvec0b = - B^T*xx */
3111:       (*mat->B->ops->multtranspose)(mat->B,xx,mat->slvec0b);

3113:       /* copy xx into slvec0a */
3114:       VecGetArray(mat->slvec0,&ptr);
3115:       VecGetArray(xx,&x);
3116:       PetscArraycpy(ptr,x,bs*mbs);
3117:       VecRestoreArray(mat->slvec0,&ptr);

3119:       VecScale(mat->slvec0,-1.0);

3121:       /* copy bb into slvec1a */
3122:       VecGetArray(mat->slvec1,&ptr);
3123:       VecGetArrayRead(bb,&b);
3124:       PetscArraycpy(ptr,b,bs*mbs);
3125:       VecRestoreArray(mat->slvec1,&ptr);

3127:       /* set slvec1b = 0 */
3128:       VecSet(mat->slvec1b,0.0);

3130:       VecScatterBegin(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);
3131:       VecRestoreArray(xx,&x);
3132:       VecRestoreArrayRead(bb,&b);
3133:       VecScatterEnd(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);

3135:       /* upper triangular part: bb1 = bb1 - B*x */
3136:       (*mat->B->ops->multadd)(mat->B,mat->slvec1b,mat->slvec1a,bb1);

3138:       /* local diagonal sweep */
3139:       (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,lits,xx);
3140:     }
3141:     VecDestroy(&bb1);
3142:   } else if ((flag & SOR_LOCAL_FORWARD_SWEEP) && (its == 1) && (flag & SOR_ZERO_INITIAL_GUESS)) {
3143:     (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
3144:   } else if ((flag & SOR_LOCAL_BACKWARD_SWEEP) && (its == 1) && (flag & SOR_ZERO_INITIAL_GUESS)) {
3145:     (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
3146:   } else if (flag & SOR_EISENSTAT) {
3147:     Vec               xx1;
3148:     PetscBool         hasop;
3149:     const PetscScalar *diag;
3150:     PetscScalar       *sl,scale = (omega - 2.0)/omega;
3151:     PetscInt          i,n;

3153:     if (!mat->xx1) {
3154:       VecDuplicate(bb,&mat->xx1);
3155:       VecDuplicate(bb,&mat->bb1);
3156:     }
3157:     xx1 = mat->xx1;
3158:     bb1 = mat->bb1;

3160:     (*mat->A->ops->sor)(mat->A,bb,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_BACKWARD_SWEEP),fshift,lits,1,xx);

3162:     if (!mat->diag) {
3163:       /* this is wrong for same matrix with new nonzero values */
3164:       MatCreateVecs(matin,&mat->diag,NULL);
3165:       MatGetDiagonal(matin,mat->diag);
3166:     }
3167:     MatHasOperation(matin,MATOP_MULT_DIAGONAL_BLOCK,&hasop);

3169:     if (hasop) {
3170:       MatMultDiagonalBlock(matin,xx,bb1);
3171:       VecAYPX(mat->slvec1a,scale,bb);
3172:     } else {
3173:       /*
3174:           These two lines are replaced by code that may be a bit faster for a good compiler
3175:       VecPointwiseMult(mat->slvec1a,mat->diag,xx);
3176:       VecAYPX(mat->slvec1a,scale,bb);
3177:       */
3178:       VecGetArray(mat->slvec1a,&sl);
3179:       VecGetArrayRead(mat->diag,&diag);
3180:       VecGetArrayRead(bb,&b);
3181:       VecGetArray(xx,&x);
3182:       VecGetLocalSize(xx,&n);
3183:       if (omega == 1.0) {
3184:         for (i=0; i<n; i++) sl[i] = b[i] - diag[i]*x[i];
3185:         PetscLogFlops(2.0*n);
3186:       } else {
3187:         for (i=0; i<n; i++) sl[i] = b[i] + scale*diag[i]*x[i];
3188:         PetscLogFlops(3.0*n);
3189:       }
3190:       VecRestoreArray(mat->slvec1a,&sl);
3191:       VecRestoreArrayRead(mat->diag,&diag);
3192:       VecRestoreArrayRead(bb,&b);
3193:       VecRestoreArray(xx,&x);
3194:     }

3196:     /* multiply off-diagonal portion of matrix */
3197:     VecSet(mat->slvec1b,0.0);
3198:     (*mat->B->ops->multtranspose)(mat->B,xx,mat->slvec0b);
3199:     VecGetArray(mat->slvec0,&from);
3200:     VecGetArray(xx,&x);
3201:     PetscArraycpy(from,x,bs*mbs);
3202:     VecRestoreArray(mat->slvec0,&from);
3203:     VecRestoreArray(xx,&x);
3204:     VecScatterBegin(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);
3205:     VecScatterEnd(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);
3206:     (*mat->B->ops->multadd)(mat->B,mat->slvec1b,mat->slvec1a,mat->slvec1a);

3208:     /* local sweep */
3209:     (*mat->A->ops->sor)(mat->A,mat->slvec1a,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_FORWARD_SWEEP),fshift,lits,1,xx1);
3210:     VecAXPY(xx,1.0,xx1);
3211:   } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"MatSORType is not supported for SBAIJ matrix format");
3212:   return(0);
3213: }

3215: PetscErrorCode MatSOR_MPISBAIJ_2comm(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx)
3216: {
3217:   Mat_MPISBAIJ   *mat = (Mat_MPISBAIJ*)matin->data;
3219:   Vec            lvec1,bb1;

3222:   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);
3223:   if (matin->rmap->bs > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"SSOR for block size > 1 is not yet implemented");

3225:   if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) {
3226:     if (flag & SOR_ZERO_INITIAL_GUESS) {
3227:       (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,lits,xx);
3228:       its--;
3229:     }

3231:     VecDuplicate(mat->lvec,&lvec1);
3232:     VecDuplicate(bb,&bb1);
3233:     while (its--) {
3234:       VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);

3236:       /* lower diagonal part: bb1 = bb - B^T*xx */
3237:       (*mat->B->ops->multtranspose)(mat->B,xx,lvec1);
3238:       VecScale(lvec1,-1.0);

3240:       VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
3241:       VecCopy(bb,bb1);
3242:       VecScatterBegin(mat->Mvctx,lvec1,bb1,ADD_VALUES,SCATTER_REVERSE);

3244:       /* upper diagonal part: bb1 = bb1 - B*x */
3245:       VecScale(mat->lvec,-1.0);
3246:       (*mat->B->ops->multadd)(mat->B,mat->lvec,bb1,bb1);

3248:       VecScatterEnd(mat->Mvctx,lvec1,bb1,ADD_VALUES,SCATTER_REVERSE);

3250:       /* diagonal sweep */
3251:       (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,lits,xx);
3252:     }
3253:     VecDestroy(&lvec1);
3254:     VecDestroy(&bb1);
3255:   } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"MatSORType is not supported for SBAIJ matrix format");
3256:   return(0);
3257: }

3259: /*@
3260:      MatCreateMPISBAIJWithArrays - creates a MPI SBAIJ matrix using arrays that contain in standard
3261:          CSR format the local rows.

3263:    Collective

3265:    Input Parameters:
3266: +  comm - MPI communicator
3267: .  bs - the block size, only a block size of 1 is supported
3268: .  m - number of local rows (Cannot be PETSC_DECIDE)
3269: .  n - This value should be the same as the local size used in creating the
3270:        x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have
3271:        calculated if N is given) For square matrices n is almost always m.
3272: .  M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
3273: .  N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
3274: .   i - row indices; that is i[0] = 0, i[row] = i[row-1] + number of block elements in that row block row of the matrix
3275: .   j - column indices
3276: -   a - matrix values

3278:    Output Parameter:
3279: .   mat - the matrix

3281:    Level: intermediate

3283:    Notes:
3284:        The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc;
3285:      thus you CANNOT change the matrix entries by changing the values of a[] after you have
3286:      called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays.

3288:        The i and j indices are 0 based, and i indices are indices corresponding to the local j array.

3290: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(),
3291:           MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays()
3292: @*/
3293: 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)
3294: {


3299:   if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0");
3300:   if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative");
3301:   MatCreate(comm,mat);
3302:   MatSetSizes(*mat,m,n,M,N);
3303:   MatSetType(*mat,MATMPISBAIJ);
3304:   MatMPISBAIJSetPreallocationCSR(*mat,bs,i,j,a);
3305:   return(0);
3306: }


3309: /*@C
3310:    MatMPISBAIJSetPreallocationCSR - Creates a sparse parallel matrix in SBAIJ format using the given nonzero structure and (optional) numerical values

3312:    Collective

3314:    Input Parameters:
3315: +  B - the matrix
3316: .  bs - the block size
3317: .  i - the indices into j for the start of each local row (starts with zero)
3318: .  j - the column indices for each local row (starts with zero) these must be sorted for each row
3319: -  v - optional values in the matrix

3321:    Level: advanced

3323:    Notes:
3324:    Though this routine has Preallocation() in the name it also sets the exact nonzero locations of the matrix entries
3325:    and usually the numerical values as well

3327:    Any entries below the diagonal are ignored

3329: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIBAIJSetPreallocation(), MatCreateAIJ(), MPIAIJ
3330: @*/
3331: PetscErrorCode  MatMPISBAIJSetPreallocationCSR(Mat B,PetscInt bs,const PetscInt i[],const PetscInt j[], const PetscScalar v[])
3332: {

3336:   PetscTryMethod(B,"MatMPISBAIJSetPreallocationCSR_C",(Mat,PetscInt,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,bs,i,j,v));
3337:   return(0);
3338: }

3340: PetscErrorCode MatCreateMPIMatConcatenateSeqMat_MPISBAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat)
3341: {
3343:   PetscInt       m,N,i,rstart,nnz,Ii,bs,cbs;
3344:   PetscInt       *indx;
3345:   PetscScalar    *values;

3348:   MatGetSize(inmat,&m,&N);
3349:   if (scall == MAT_INITIAL_MATRIX) { /* symbolic phase */
3350:     Mat_SeqSBAIJ   *a = (Mat_SeqSBAIJ*)inmat->data;
3351:     PetscInt       *dnz,*onz,mbs,Nbs,nbs;
3352:     PetscInt       *bindx,rmax=a->rmax,j;
3353:     PetscMPIInt    rank,size;

3355:     MatGetBlockSizes(inmat,&bs,&cbs);
3356:     mbs = m/bs; Nbs = N/cbs;
3357:     if (n == PETSC_DECIDE) {
3358:       PetscSplitOwnershipBlock(comm,cbs,&n,&N);
3359:     }
3360:     nbs = n/cbs;

3362:     PetscMalloc1(rmax,&bindx);
3363:     MatPreallocateInitialize(comm,mbs,nbs,dnz,onz); /* inline function, output __end and __rstart are used below */

3365:     MPI_Comm_rank(comm,&rank);
3366:     MPI_Comm_rank(comm,&size);
3367:     if (rank == size-1) {
3368:       /* Check sum(nbs) = Nbs */
3369:       if (__end != Nbs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Sum of local block columns %D != global block columns %D",__end,Nbs);
3370:     }

3372:     rstart = __rstart; /* block rstart of *outmat; see inline function MatPreallocateInitialize */
3373:     MatSetOption(inmat,MAT_GETROW_UPPERTRIANGULAR,PETSC_TRUE);
3374:     for (i=0; i<mbs; i++) {
3375:       MatGetRow_SeqSBAIJ(inmat,i*bs,&nnz,&indx,NULL); /* non-blocked nnz and indx */
3376:       nnz  = nnz/bs;
3377:       for (j=0; j<nnz; j++) bindx[j] = indx[j*bs]/bs;
3378:       MatPreallocateSet(i+rstart,nnz,bindx,dnz,onz);
3379:       MatRestoreRow_SeqSBAIJ(inmat,i*bs,&nnz,&indx,NULL);
3380:     }
3381:     MatSetOption(inmat,MAT_GETROW_UPPERTRIANGULAR,PETSC_FALSE);
3382:     PetscFree(bindx);

3384:     MatCreate(comm,outmat);
3385:     MatSetSizes(*outmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);
3386:     MatSetBlockSizes(*outmat,bs,cbs);
3387:     MatSetType(*outmat,MATSBAIJ);
3388:     MatSeqSBAIJSetPreallocation(*outmat,bs,0,dnz);
3389:     MatMPISBAIJSetPreallocation(*outmat,bs,0,dnz,0,onz);
3390:     MatPreallocateFinalize(dnz,onz);
3391:   }

3393:   /* numeric phase */
3394:   MatGetBlockSizes(inmat,&bs,&cbs);
3395:   MatGetOwnershipRange(*outmat,&rstart,NULL);

3397:   MatSetOption(inmat,MAT_GETROW_UPPERTRIANGULAR,PETSC_TRUE);
3398:   for (i=0; i<m; i++) {
3399:     MatGetRow_SeqSBAIJ(inmat,i,&nnz,&indx,&values);
3400:     Ii   = i + rstart;
3401:     MatSetValues(*outmat,1,&Ii,nnz,indx,values,INSERT_VALUES);
3402:     MatRestoreRow_SeqSBAIJ(inmat,i,&nnz,&indx,&values);
3403:   }
3404:   MatSetOption(inmat,MAT_GETROW_UPPERTRIANGULAR,PETSC_FALSE);
3405:   MatAssemblyBegin(*outmat,MAT_FINAL_ASSEMBLY);
3406:   MatAssemblyEnd(*outmat,MAT_FINAL_ASSEMBLY);
3407:   return(0);
3408: }