Actual source code: mpisbaij.c

  2: #include <../src/mat/impls/baij/mpi/mpibaij.h>    /*I "petscmat.h" I*/
  3: #include <../src/mat/impls/sbaij/mpi/mpisbaij.h>
  4: #include <../src/mat/impls/sbaij/seq/sbaij.h>
  5: #include <petscblaslapack.h>


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

 32:   MatStoreValues(aij->A);
 33:   MatStoreValues(aij->B);
 34:   return(0);
 35: }

 41: PetscErrorCode  MatRetrieveValues_MPISBAIJ(Mat mat)
 42: {
 43:   Mat_MPISBAIJ   *aij = (Mat_MPISBAIJ *)mat->data;

 47:   MatRetrieveValues(aij->A);
 48:   MatRetrieveValues(aij->B);
 49:   return(0);
 50: }


 54: #define  MatSetValues_SeqSBAIJ_A_Private(row,col,value,addv) \
 55: { \
 56:  \
 57:     brow = row/bs;  \
 58:     rp   = aj + ai[brow]; ap = aa + bs2*ai[brow]; \
 59:     rmax = aimax[brow]; nrow = ailen[brow]; \
 60:       bcol = col/bs; \
 61:       ridx = row % bs; cidx = col % bs; \
 62:       low = 0; high = nrow; \
 63:       while (high-low > 3) { \
 64:         t = (low+high)/2; \
 65:         if (rp[t] > bcol) high = t; \
 66:         else              low  = t; \
 67:       } \
 68:       for (_i=low; _i<high; _i++) { \
 69:         if (rp[_i] > bcol) break; \
 70:         if (rp[_i] == bcol) { \
 71:           bap  = ap +  bs2*_i + bs*cidx + ridx; \
 72:           if (addv == ADD_VALUES) *bap += value;  \
 73:           else                    *bap  = value;  \
 74:           goto a_noinsert; \
 75:         } \
 76:       } \
 77:       if (a->nonew == 1) goto a_noinsert; \
 78:       if (a->nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \
 79:       MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,brow,bcol,rmax,aa,ai,aj,rp,ap,aimax,a->nonew,MatScalar); \
 80:       N = nrow++ - 1;  \
 81:       /* shift up all the later entries in this row */ \
 82:       for (ii=N; ii>=_i; ii--) { \
 83:         rp[ii+1] = rp[ii]; \
 84:         PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar)); \
 85:       } \
 86:       if (N>=_i) { PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar)); }  \
 87:       rp[_i]                      = bcol;  \
 88:       ap[bs2*_i + bs*cidx + ridx] = value;  \
 89:       a_noinsert:; \
 90:     ailen[brow] = nrow; \
 91: } 

 93: #define  MatSetValues_SeqSBAIJ_B_Private(row,col,value,addv) \
 94: { \
 95:     brow = row/bs;  \
 96:     rp   = bj + bi[brow]; ap = ba + bs2*bi[brow]; \
 97:     rmax = bimax[brow]; nrow = bilen[brow]; \
 98:       bcol = col/bs; \
 99:       ridx = row % bs; cidx = col % bs; \
100:       low = 0; high = nrow; \
101:       while (high-low > 3) { \
102:         t = (low+high)/2; \
103:         if (rp[t] > bcol) high = t; \
104:         else              low  = t; \
105:       } \
106:       for (_i=low; _i<high; _i++) { \
107:         if (rp[_i] > bcol) break; \
108:         if (rp[_i] == bcol) { \
109:           bap  = ap +  bs2*_i + bs*cidx + ridx; \
110:           if (addv == ADD_VALUES) *bap += value;  \
111:           else                    *bap  = value;  \
112:           goto b_noinsert; \
113:         } \
114:       } \
115:       if (b->nonew == 1) goto b_noinsert; \
116:       if (b->nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \
117:       MatSeqXAIJReallocateAIJ(B,b->mbs,bs2,nrow,brow,bcol,rmax,ba,bi,bj,rp,ap,bimax,b->nonew,MatScalar); \
118:       N = nrow++ - 1;  \
119:       /* shift up all the later entries in this row */ \
120:       for (ii=N; ii>=_i; ii--) { \
121:         rp[ii+1] = rp[ii]; \
122:         PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar)); \
123:       } \
124:       if (N>=_i) { PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar));}  \
125:       rp[_i]                      = bcol;  \
126:       ap[bs2*_i + bs*cidx + ridx] = value;  \
127:       b_noinsert:; \
128:     bilen[brow] = nrow; \
129: } 

131: /* Only add/insert a(i,j) with i<=j (blocks). 
132:    Any a(i,j) with i>j input by user is ingored. 
133: */
136: PetscErrorCode MatSetValues_MPISBAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv)
137: {
138:   Mat_MPISBAIJ   *baij = (Mat_MPISBAIJ*)mat->data;
139:   MatScalar      value;
140:   PetscBool      roworiented = baij->roworiented;
142:   PetscInt       i,j,row,col;
143:   PetscInt       rstart_orig=mat->rmap->rstart;
144:   PetscInt       rend_orig=mat->rmap->rend,cstart_orig=mat->cmap->rstart;
145:   PetscInt       cend_orig=mat->cmap->rend,bs=mat->rmap->bs;

147:   /* Some Variables required in the macro */
148:   Mat            A = baij->A;
149:   Mat_SeqSBAIJ   *a = (Mat_SeqSBAIJ*)(A)->data;
150:   PetscInt       *aimax=a->imax,*ai=a->i,*ailen=a->ilen,*aj=a->j;
151:   MatScalar      *aa=a->a;

153:   Mat            B = baij->B;
154:   Mat_SeqBAIJ   *b = (Mat_SeqBAIJ*)(B)->data;
155:   PetscInt      *bimax=b->imax,*bi=b->i,*bilen=b->ilen,*bj=b->j;
156:   MatScalar     *ba=b->a;

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

162:   /* for stash */
163:   PetscInt      n_loc, *in_loc = PETSC_NULL;
164:   MatScalar     *v_loc = PETSC_NULL;

168:   if (!baij->donotstash){
169:     if (n > baij->n_loc) {
170:       PetscFree(baij->in_loc);
171:       PetscFree(baij->v_loc);
172:       PetscMalloc(n*sizeof(PetscInt),&baij->in_loc);
173:       PetscMalloc(n*sizeof(MatScalar),&baij->v_loc);
174:       baij->n_loc = n;
175:     }
176:     in_loc = baij->in_loc;
177:     v_loc  = baij->v_loc;
178:   }

180:   for (i=0; i<m; i++) {
181:     if (im[i] < 0) continue;
182: #if defined(PETSC_USE_DEBUG)
183:     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);
184: #endif
185:     if (im[i] >= rstart_orig && im[i] < rend_orig) { /* this processor entry */
186:       row = im[i] - rstart_orig;              /* local row index */
187:       for (j=0; j<n; j++) {
188:         if (im[i]/bs > in[j]/bs){
189:           if (a->ignore_ltriangular){
190:             continue;    /* ignore lower triangular blocks */
191:           } else {
192:             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)");
193:           }
194:         }
195:         if (in[j] >= cstart_orig && in[j] < cend_orig){  /* diag entry (A) */
196:           col = in[j] - cstart_orig;          /* local col index */
197:           brow = row/bs; bcol = col/bs;
198:           if (brow > bcol) continue;  /* ignore lower triangular blocks of A */
199:           if (roworiented) value = v[i*n+j]; else value = v[i+j*m];
200:           MatSetValues_SeqSBAIJ_A_Private(row,col,value,addv);
201:           /* MatSetValues_SeqBAIJ(baij->A,1,&row,1,&col,&value,addv); */
202:         } else if (in[j] < 0) continue;
203: #if defined(PETSC_USE_DEBUG)
204:         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);
205: #endif
206:         else {  /* off-diag entry (B) */
207:           if (mat->was_assembled) {
208:             if (!baij->colmap) {
209:               CreateColmap_MPIBAIJ_Private(mat);
210:             }
211: #if defined (PETSC_USE_CTABLE)
212:             PetscTableFind(baij->colmap,in[j]/bs + 1,&col);
213:             col  = col - 1;
214: #else
215:             col = baij->colmap[in[j]/bs] - 1;
216: #endif
217:             if (col < 0 && !((Mat_SeqSBAIJ*)(baij->A->data))->nonew) {
218:               DisAssemble_MPISBAIJ(mat);
219:               col =  in[j];
220:               /* Reinitialize the variables required by MatSetValues_SeqBAIJ_B_Private() */
221:               B = baij->B;
222:               b = (Mat_SeqBAIJ*)(B)->data;
223:               bimax=b->imax;bi=b->i;bilen=b->ilen;bj=b->j;
224:               ba=b->a;
225:             } else col += in[j]%bs;
226:           } else col = in[j];
227:           if (roworiented) value = v[i*n+j]; else value = v[i+j*m];
228:           MatSetValues_SeqSBAIJ_B_Private(row,col,value,addv);
229:           /* MatSetValues_SeqBAIJ(baij->B,1,&row,1,&col,&value,addv); */
230:         }
231:       }
232:     } else {  /* off processor entry */
233:       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]);
234:       if (!baij->donotstash) {
235:         n_loc = 0;
236:         for (j=0; j<n; j++){
237:           if (im[i]/bs > in[j]/bs) continue; /* ignore lower triangular blocks */
238:           in_loc[n_loc] = in[j];
239:           if (roworiented) {
240:             v_loc[n_loc] = v[i*n+j];
241:           } else {
242:             v_loc[n_loc] = v[j*m+i];
243:           }
244:           n_loc++;
245:         }
246:         MatStashValuesRow_Private(&mat->stash,im[i],n_loc,in_loc,v_loc,PETSC_FALSE);
247:       }
248:     }
249:   }
250:   return(0);
251: }

255: PetscErrorCode MatSetValuesBlocked_MPISBAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const MatScalar v[],InsertMode addv)
256: {
257:   Mat_MPISBAIJ    *baij = (Mat_MPISBAIJ*)mat->data;
258:   const MatScalar *value;
259:   MatScalar       *barray=baij->barray;
260:   PetscBool       roworiented = baij->roworiented,ignore_ltriangular = ((Mat_SeqSBAIJ*)baij->A->data)->ignore_ltriangular;
261:   PetscErrorCode  ierr;
262:   PetscInt        i,j,ii,jj,row,col,rstart=baij->rstartbs;
263:   PetscInt        rend=baij->rendbs,cstart=baij->rstartbs,stepval;
264:   PetscInt        cend=baij->rendbs,bs=mat->rmap->bs,bs2=baij->bs2;

267:   if(!barray) {
268:     PetscMalloc(bs2*sizeof(MatScalar),&barray);
269:     baij->barray = barray;
270:   }

272:   if (roworiented) {
273:     stepval = (n-1)*bs;
274:   } else {
275:     stepval = (m-1)*bs;
276:   }
277:   for (i=0; i<m; i++) {
278:     if (im[i] < 0) continue;
279: #if defined(PETSC_USE_DEBUG)
280:     if (im[i] >= baij->Mbs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large, row %D max %D",im[i],baij->Mbs-1);
281: #endif
282:     if (im[i] >= rstart && im[i] < rend) {
283:       row = im[i] - rstart;
284:       for (j=0; j<n; j++) {
285:         if (im[i] > in[j]) {
286:           if (ignore_ltriangular) continue; /* ignore lower triangular blocks */
287:           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)");
288:         }
289:         /* If NumCol = 1 then a copy is not required */
290:         if ((roworiented) && (n == 1)) {
291:           barray = (MatScalar*) v + i*bs2;
292:         } else if((!roworiented) && (m == 1)) {
293:           barray = (MatScalar*) v + j*bs2;
294:         } else { /* Here a copy is required */
295:           if (roworiented) {
296:             value = v + i*(stepval+bs)*bs + j*bs;
297:           } else {
298:             value = v + j*(stepval+bs)*bs + i*bs;
299:           }
300:           for (ii=0; ii<bs; ii++,value+=stepval) {
301:             for (jj=0; jj<bs; jj++) {
302:               *barray++  = *value++;
303:             }
304:           }
305:           barray -=bs2;
306:         }
307: 
308:         if (in[j] >= cstart && in[j] < cend){
309:           col  = in[j] - cstart;
310:           MatSetValuesBlocked_SeqSBAIJ(baij->A,1,&row,1,&col,barray,addv);
311:         }
312:         else if (in[j] < 0) continue;
313: #if defined(PETSC_USE_DEBUG)
314:         else if (in[j] >= baij->Nbs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large, col %D max %D",in[j],baij->Nbs-1);
315: #endif
316:         else {
317:           if (mat->was_assembled) {
318:             if (!baij->colmap) {
319:               CreateColmap_MPIBAIJ_Private(mat);
320:             }

322: #if defined(PETSC_USE_DEBUG)
323: #if defined (PETSC_USE_CTABLE)
324:             { PetscInt data;
325:               PetscTableFind(baij->colmap,in[j]+1,&data);
326:               if ((data - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap");
327:             }
328: #else
329:             if ((baij->colmap[in[j]] - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap");
330: #endif
331: #endif
332: #if defined (PETSC_USE_CTABLE)
333:             PetscTableFind(baij->colmap,in[j]+1,&col);
334:             col  = (col - 1)/bs;
335: #else
336:             col = (baij->colmap[in[j]] - 1)/bs;
337: #endif
338:             if (col < 0 && !((Mat_SeqBAIJ*)(baij->A->data))->nonew) {
339:               DisAssemble_MPISBAIJ(mat);
340:               col =  in[j];
341:             }
342:           }
343:           else col = in[j];
344:           MatSetValuesBlocked_SeqBAIJ(baij->B,1,&row,1,&col,barray,addv);
345:         }
346:       }
347:     } else {
348:       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]);
349:       if (!baij->donotstash) {
350:         if (roworiented) {
351:           MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);
352:         } else {
353:           MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);
354:         }
355:       }
356:     }
357:   }
358:   return(0);
359: }

363: PetscErrorCode MatGetValues_MPISBAIJ(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[])
364: {
365:   Mat_MPISBAIJ   *baij = (Mat_MPISBAIJ*)mat->data;
367:   PetscInt       bs=mat->rmap->bs,i,j,bsrstart = mat->rmap->rstart,bsrend = mat->rmap->rend;
368:   PetscInt       bscstart = mat->cmap->rstart,bscend = mat->cmap->rend,row,col,data;

371:   for (i=0; i<m; i++) {
372:     if (idxm[i] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",idxm[i]); */
373:     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);
374:     if (idxm[i] >= bsrstart && idxm[i] < bsrend) {
375:       row = idxm[i] - bsrstart;
376:       for (j=0; j<n; j++) {
377:         if (idxn[j] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column %D",idxn[j]); */
378:         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);
379:         if (idxn[j] >= bscstart && idxn[j] < bscend){
380:           col = idxn[j] - bscstart;
381:           MatGetValues_SeqSBAIJ(baij->A,1,&row,1,&col,v+i*n+j);
382:         } else {
383:           if (!baij->colmap) {
384:             CreateColmap_MPIBAIJ_Private(mat);
385:           }
386: #if defined (PETSC_USE_CTABLE)
387:           PetscTableFind(baij->colmap,idxn[j]/bs+1,&data);
388:           data --;
389: #else
390:           data = baij->colmap[idxn[j]/bs]-1;
391: #endif
392:           if((data < 0) || (baij->garray[data/bs] != idxn[j]/bs)) *(v+i*n+j) = 0.0;
393:           else {
394:             col  = data + idxn[j]%bs;
395:             MatGetValues_SeqBAIJ(baij->B,1,&row,1,&col,v+i*n+j);
396:           }
397:         }
398:       }
399:     } else {
400:       SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local values currently supported");
401:     }
402:   }
403:  return(0);
404: }

408: PetscErrorCode MatNorm_MPISBAIJ(Mat mat,NormType type,PetscReal *norm)
409: {
410:   Mat_MPISBAIJ   *baij = (Mat_MPISBAIJ*)mat->data;
412:   PetscReal      sum[2],*lnorm2;

415:   if (baij->size == 1) {
416:      MatNorm(baij->A,type,norm);
417:   } else {
418:     if (type == NORM_FROBENIUS) {
419:       PetscMalloc(2*sizeof(PetscReal),&lnorm2);
420:        MatNorm(baij->A,type,lnorm2);
421:       *lnorm2 = (*lnorm2)*(*lnorm2); lnorm2++;            /* squar power of norm(A) */
422:        MatNorm(baij->B,type,lnorm2);
423:       *lnorm2 = (*lnorm2)*(*lnorm2); lnorm2--;             /* squar power of norm(B) */
424:       MPI_Allreduce(lnorm2,&sum,2,MPIU_REAL,MPIU_SUM,((PetscObject)mat)->comm);
425:       *norm = PetscSqrtReal(sum[0] + 2*sum[1]);
426:       PetscFree(lnorm2);
427:     } else if (type == NORM_INFINITY || type == NORM_1) { /* max row/column sum */
428:       Mat_SeqSBAIJ *amat=(Mat_SeqSBAIJ*)baij->A->data;
429:       Mat_SeqBAIJ  *bmat=(Mat_SeqBAIJ*)baij->B->data;
430:       PetscReal    *rsum,*rsum2,vabs;
431:       PetscInt     *jj,*garray=baij->garray,rstart=baij->rstartbs,nz;
432:       PetscInt     brow,bcol,col,bs=baij->A->rmap->bs,row,grow,gcol,mbs=amat->mbs;
433:       MatScalar    *v;

435:       PetscMalloc2(mat->cmap->N,PetscReal,&rsum,mat->cmap->N,PetscReal,&rsum2);
436:       PetscMemzero(rsum,mat->cmap->N*sizeof(PetscReal));
437:       /* Amat */
438:       v = amat->a; jj = amat->j;
439:       for (brow=0; brow<mbs; brow++) {
440:         grow = bs*(rstart + brow);
441:         nz = amat->i[brow+1] - amat->i[brow];
442:         for (bcol=0; bcol<nz; bcol++){
443:           gcol = bs*(rstart + *jj); jj++;
444:           for (col=0; col<bs; col++){
445:             for (row=0; row<bs; row++){
446:               vabs = PetscAbsScalar(*v); v++;
447:               rsum[gcol+col] += vabs;
448:               /* non-diagonal block */
449:               if (bcol > 0 && vabs > 0.0) rsum[grow+row] += vabs;
450:             }
451:           }
452:         }
453:       }
454:       /* Bmat */
455:       v = bmat->a; jj = bmat->j;
456:       for (brow=0; brow<mbs; brow++) {
457:         grow = bs*(rstart + brow);
458:         nz = bmat->i[brow+1] - bmat->i[brow];
459:         for (bcol=0; bcol<nz; bcol++){
460:           gcol = bs*garray[*jj]; jj++;
461:           for (col=0; col<bs; col++){
462:             for (row=0; row<bs; row++){
463:               vabs = PetscAbsScalar(*v); v++;
464:               rsum[gcol+col] += vabs;
465:               rsum[grow+row] += vabs;
466:             }
467:           }
468:         }
469:       }
470:       MPI_Allreduce(rsum,rsum2,mat->cmap->N,MPIU_REAL,MPIU_SUM,((PetscObject)mat)->comm);
471:       *norm = 0.0;
472:       for (col=0; col<mat->cmap->N; col++) {
473:         if (rsum2[col] > *norm) *norm = rsum2[col];
474:       }
475:       PetscFree2(rsum,rsum2);
476:     } else {
477:       SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support for this norm yet");
478:     }
479:   }
480:   return(0);
481: }

485: PetscErrorCode MatAssemblyBegin_MPISBAIJ(Mat mat,MatAssemblyType mode)
486: {
487:   Mat_MPISBAIJ   *baij = (Mat_MPISBAIJ*)mat->data;
489:   PetscInt       nstash,reallocs;
490:   InsertMode     addv;

493:   if (baij->donotstash || mat->nooffprocentries) {
494:     return(0);
495:   }

497:   /* make sure all processors are either in INSERTMODE or ADDMODE */
498:   MPI_Allreduce(&mat->insertmode,&addv,1,MPI_INT,MPI_BOR,((PetscObject)mat)->comm);
499:   if (addv == (ADD_VALUES|INSERT_VALUES)) SETERRQ(((PetscObject)mat)->comm,PETSC_ERR_ARG_WRONGSTATE,"Some processors inserted others added");
500:   mat->insertmode = addv; /* in case this processor had no cache */

502:   MatStashScatterBegin_Private(mat,&mat->stash,mat->rmap->range);
503:   MatStashScatterBegin_Private(mat,&mat->bstash,baij->rangebs);
504:   MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);
505:   PetscInfo2(mat,"Stash has %D entries,uses %D mallocs.\n",nstash,reallocs);
506:   MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);
507:   PetscInfo2(mat,"Block-Stash has %D entries, uses %D mallocs.\n",nstash,reallocs);
508:   return(0);
509: }

513: PetscErrorCode MatAssemblyEnd_MPISBAIJ(Mat mat,MatAssemblyType mode)
514: {
515:   Mat_MPISBAIJ   *baij=(Mat_MPISBAIJ*)mat->data;
516:   Mat_SeqSBAIJ   *a=(Mat_SeqSBAIJ*)baij->A->data;
518:   PetscInt       i,j,rstart,ncols,flg,bs2=baij->bs2;
519:   PetscInt       *row,*col;
520:   PetscBool      other_disassembled;
521:   PetscMPIInt    n;
522:   PetscBool      r1,r2,r3;
523:   MatScalar      *val;
524:   InsertMode     addv = mat->insertmode;

526:   /* do not use 'b=(Mat_SeqBAIJ*)baij->B->data' as B can be reset in disassembly */

529:   if (!baij->donotstash &&  !mat->nooffprocentries) {
530:     while (1) {
531:       MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);
532:       if (!flg) break;

534:       for (i=0; i<n;) {
535:         /* Now identify the consecutive vals belonging to the same row */
536:         for (j=i,rstart=row[j]; j<n; j++) { if (row[j] != rstart) break; }
537:         if (j < n) ncols = j-i;
538:         else       ncols = n-i;
539:         /* Now assemble all these values with a single function call */
540:         MatSetValues_MPISBAIJ(mat,1,row+i,ncols,col+i,val+i,addv);
541:         i = j;
542:       }
543:     }
544:     MatStashScatterEnd_Private(&mat->stash);
545:     /* Now process the block-stash. Since the values are stashed column-oriented,
546:        set the roworiented flag to column oriented, and after MatSetValues() 
547:        restore the original flags */
548:     r1 = baij->roworiented;
549:     r2 = a->roworiented;
550:     r3 = ((Mat_SeqBAIJ*)baij->B->data)->roworiented;
551:     baij->roworiented = PETSC_FALSE;
552:     a->roworiented    = PETSC_FALSE;
553:     ((Mat_SeqBAIJ*)baij->B->data)->roworiented    = PETSC_FALSE; /* b->roworinted */
554:     while (1) {
555:       MatStashScatterGetMesg_Private(&mat->bstash,&n,&row,&col,&val,&flg);
556:       if (!flg) break;
557: 
558:       for (i=0; i<n;) {
559:         /* Now identify the consecutive vals belonging to the same row */
560:         for (j=i,rstart=row[j]; j<n; j++) { if (row[j] != rstart) break; }
561:         if (j < n) ncols = j-i;
562:         else       ncols = n-i;
563:         MatSetValuesBlocked_MPISBAIJ(mat,1,row+i,ncols,col+i,val+i*bs2,addv);
564:         i = j;
565:       }
566:     }
567:     MatStashScatterEnd_Private(&mat->bstash);
568:     baij->roworiented = r1;
569:     a->roworiented    = r2;
570:     ((Mat_SeqBAIJ*)baij->B->data)->roworiented    = r3; /* b->roworinted */
571:   }

573:   MatAssemblyBegin(baij->A,mode);
574:   MatAssemblyEnd(baij->A,mode);

576:   /* determine if any processor has disassembled, if so we must 
577:      also disassemble ourselfs, in order that we may reassemble. */
578:   /*
579:      if nonzero structure of submatrix B cannot change then we know that
580:      no processor disassembled thus we can skip this stuff
581:   */
582:   if (!((Mat_SeqBAIJ*)baij->B->data)->nonew)  {
583:     MPI_Allreduce(&mat->was_assembled,&other_disassembled,1,MPI_INT,MPI_PROD,((PetscObject)mat)->comm);
584:     if (mat->was_assembled && !other_disassembled) {
585:       DisAssemble_MPISBAIJ(mat);
586:     }
587:   }

589:   if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) {
590:     MatSetUpMultiply_MPISBAIJ(mat); /* setup Mvctx and sMvctx */
591:   }
592:   MatSetOption(baij->B,MAT_CHECK_COMPRESSED_ROW,PETSC_TRUE);
593:   MatAssemblyBegin(baij->B,mode);
594:   MatAssemblyEnd(baij->B,mode);
595: 
596:   PetscFree2(baij->rowvalues,baij->rowindices);
597:   baij->rowvalues = 0;

599:   return(0);
600: }

605: static PetscErrorCode MatView_MPISBAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer)
606: {
607:   Mat_MPISBAIJ      *baij = (Mat_MPISBAIJ*)mat->data;
608:   PetscErrorCode    ierr;
609:   PetscInt          bs = mat->rmap->bs;
610:   PetscMPIInt       size = baij->size,rank = baij->rank;
611:   PetscBool         iascii,isdraw;
612:   PetscViewer       sviewer;
613:   PetscViewerFormat format;

616:   PetscTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
617:   PetscTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);
618:   if (iascii) {
619:     PetscViewerGetFormat(viewer,&format);
620:     if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) {
621:       MatInfo info;
622:       MPI_Comm_rank(((PetscObject)mat)->comm,&rank);
623:       MatGetInfo(mat,MAT_LOCAL,&info);
624:       PetscViewerASCIISynchronizedAllow(viewer,PETSC_TRUE);
625:       PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D bs %D mem %D\n",rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,mat->rmap->bs,(PetscInt)info.memory);
626:       MatGetInfo(baij->A,MAT_LOCAL,&info);
627:       PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);
628:       MatGetInfo(baij->B,MAT_LOCAL,&info);
629:       PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);
630:       PetscViewerFlush(viewer);
631:       PetscViewerASCIISynchronizedAllow(viewer,PETSC_FALSE);
632:       PetscViewerASCIIPrintf(viewer,"Information on VecScatter used in matrix-vector product: \n");
633:       VecScatterView(baij->Mvctx,viewer);
634:       return(0);
635:     } else if (format == PETSC_VIEWER_ASCII_INFO) {
636:       PetscViewerASCIIPrintf(viewer,"  block size is %D\n",bs);
637:       return(0);
638:     } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) {
639:       return(0);
640:     }
641:   }

643:   if (isdraw) {
644:     PetscDraw  draw;
645:     PetscBool  isnull;
646:     PetscViewerDrawGetDraw(viewer,0,&draw);
647:     PetscDrawIsNull(draw,&isnull); if (isnull) return(0);
648:   }

650:   if (size == 1) {
651:     PetscObjectSetName((PetscObject)baij->A,((PetscObject)mat)->name);
652:     MatView(baij->A,viewer);
653:   } else {
654:     /* assemble the entire matrix onto first processor. */
655:     Mat          A;
656:     Mat_SeqSBAIJ *Aloc;
657:     Mat_SeqBAIJ  *Bloc;
658:     PetscInt     M = mat->rmap->N,N = mat->cmap->N,*ai,*aj,col,i,j,k,*rvals,mbs = baij->mbs;
659:     MatScalar    *a;

661:     /* Should this be the same type as mat? */
662:     MatCreate(((PetscObject)mat)->comm,&A);
663:     if (!rank) {
664:       MatSetSizes(A,M,N,M,N);
665:     } else {
666:       MatSetSizes(A,0,0,M,N);
667:     }
668:     MatSetType(A,MATMPISBAIJ);
669:     MatMPISBAIJSetPreallocation(A,mat->rmap->bs,0,PETSC_NULL,0,PETSC_NULL);
670:     PetscLogObjectParent(mat,A);

672:     /* copy over the A part */
673:     Aloc  = (Mat_SeqSBAIJ*)baij->A->data;
674:     ai    = Aloc->i; aj = Aloc->j; a = Aloc->a;
675:     PetscMalloc(bs*sizeof(PetscInt),&rvals);

677:     for (i=0; i<mbs; i++) {
678:       rvals[0] = bs*(baij->rstartbs + i);
679:       for (j=1; j<bs; j++) { rvals[j] = rvals[j-1] + 1; }
680:       for (j=ai[i]; j<ai[i+1]; j++) {
681:         col = (baij->cstartbs+aj[j])*bs;
682:         for (k=0; k<bs; k++) {
683:           MatSetValues_MPISBAIJ(A,bs,rvals,1,&col,a,INSERT_VALUES);
684:           col++; a += bs;
685:         }
686:       }
687:     }
688:     /* copy over the B part */
689:     Bloc = (Mat_SeqBAIJ*)baij->B->data;
690:     ai = Bloc->i; aj = Bloc->j; a = Bloc->a;
691:     for (i=0; i<mbs; i++) {
692: 
693:       rvals[0] = bs*(baij->rstartbs + i);
694:       for (j=1; j<bs; j++) { rvals[j] = rvals[j-1] + 1; }
695:       for (j=ai[i]; j<ai[i+1]; j++) {
696:         col = baij->garray[aj[j]]*bs;
697:         for (k=0; k<bs; k++) {
698:           MatSetValues_MPIBAIJ(A,bs,rvals,1,&col,a,INSERT_VALUES);
699:           col++; a += bs;
700:         }
701:       }
702:     }
703:     PetscFree(rvals);
704:     MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);
705:     MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);
706:     /* 
707:        Everyone has to call to draw the matrix since the graphics waits are
708:        synchronized across all processors that share the PetscDraw object
709:     */
710:     PetscViewerGetSingleton(viewer,&sviewer);
711:     if (!rank) {
712:       PetscObjectSetName((PetscObject)((Mat_MPISBAIJ*)(A->data))->A,((PetscObject)mat)->name);
713:           /* Set the type name to MATMPISBAIJ so that the correct type can be printed out by PetscObjectPrintClassNamePrefixType() in MatView_SeqSBAIJ_ASCII()*/
714:       PetscStrcpy(((PetscObject)((Mat_MPISBAIJ*)(A->data))->A)->type_name,MATMPISBAIJ);
715:       MatView(((Mat_MPISBAIJ*)(A->data))->A,sviewer);
716:     }
717:     PetscViewerRestoreSingleton(viewer,&sviewer);
718:     MatDestroy(&A);
719:   }
720:   return(0);
721: }

725: PetscErrorCode MatView_MPISBAIJ(Mat mat,PetscViewer viewer)
726: {
728:   PetscBool      iascii,isdraw,issocket,isbinary;

731:   PetscTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
732:   PetscTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);
733:   PetscTypeCompare((PetscObject)viewer,PETSCVIEWERSOCKET,&issocket);
734:   PetscTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);
735:   if (iascii || isdraw || issocket || isbinary) {
736:     MatView_MPISBAIJ_ASCIIorDraworSocket(mat,viewer);
737:   } else {
738:     SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"Viewer type %s not supported by MPISBAIJ matrices",((PetscObject)viewer)->type_name);
739:   }
740:   return(0);
741: }

745: PetscErrorCode MatDestroy_MPISBAIJ(Mat mat)
746: {
747:   Mat_MPISBAIJ   *baij = (Mat_MPISBAIJ*)mat->data;

751: #if defined(PETSC_USE_LOG)
752:   PetscLogObjectState((PetscObject)mat,"Rows=%D,Cols=%D",mat->rmap->N,mat->cmap->N);
753: #endif
754:   MatStashDestroy_Private(&mat->stash);
755:   MatStashDestroy_Private(&mat->bstash);
756:   MatDestroy(&baij->A);
757:   MatDestroy(&baij->B);
758: #if defined (PETSC_USE_CTABLE)
759:   PetscTableDestroy(&baij->colmap);
760: #else
761:   PetscFree(baij->colmap);
762: #endif
763:   PetscFree(baij->garray);
764:   VecDestroy(&baij->lvec);
765:   VecScatterDestroy(&baij->Mvctx);
766:   VecDestroy(&baij->slvec0);
767:   VecDestroy(&baij->slvec0b);
768:   VecDestroy(&baij->slvec1);
769:   VecDestroy(&baij->slvec1a);
770:   VecDestroy(&baij->slvec1b);
771:   VecScatterDestroy(&baij->sMvctx);
772:   PetscFree2(baij->rowvalues,baij->rowindices);
773:   PetscFree(baij->barray);
774:   PetscFree(baij->hd);
775:   VecDestroy(&baij->diag);
776:   VecDestroy(&baij->bb1);
777:   VecDestroy(&baij->xx1);
778: #if defined(PETSC_USE_REAL_MAT_SINGLE)
779:   PetscFree(baij->setvaluescopy);
780: #endif
781:   PetscFree(baij->in_loc);
782:   PetscFree(baij->v_loc);
783:   PetscFree(baij->rangebs);
784:   PetscFree(mat->data);

786:   PetscObjectChangeTypeName((PetscObject)mat,0);
787:   PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C","",PETSC_NULL);
788:   PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C","",PETSC_NULL);
789:   PetscObjectComposeFunction((PetscObject)mat,"MatGetDiagonalBlock_C","",PETSC_NULL);
790:   PetscObjectComposeFunction((PetscObject)mat,"MatMPISBAIJSetPreallocation_C","",PETSC_NULL);
791:   PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpisbaij_mpisbstrm_C","",PETSC_NULL);
792:   return(0);
793: }

797: PetscErrorCode MatMult_MPISBAIJ_Hermitian(Mat A,Vec xx,Vec yy)
798: {
799:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;
801:   PetscInt       nt,mbs=a->mbs,bs=A->rmap->bs;
802:   PetscScalar    *x,*from;
803: 
805:   VecGetLocalSize(xx,&nt);
806:   if (nt != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx");

808:   /* diagonal part */
809:   (*a->A->ops->mult)(a->A,xx,a->slvec1a);
810:   VecSet(a->slvec1b,0.0);

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

815:   /* copy x into the vec slvec0 */
816:   VecGetArray(a->slvec0,&from);
817:   VecGetArray(xx,&x);

819:   PetscMemcpy(from,x,bs*mbs*sizeof(MatScalar));
820:   VecRestoreArray(a->slvec0,&from);
821:   VecRestoreArray(xx,&x);
822: 
823:   VecScatterBegin(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);
824:   VecScatterEnd(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);
825:   /* supperdiagonal part */
826:   (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,yy);
827:   return(0);
828: }

832: PetscErrorCode MatMult_MPISBAIJ(Mat A,Vec xx,Vec yy)
833: {
834:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;
836:   PetscInt       nt,mbs=a->mbs,bs=A->rmap->bs;
837:   PetscScalar    *x,*from;
838: 
840:   VecGetLocalSize(xx,&nt);
841:   if (nt != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx");

843:   /* diagonal part */
844:   (*a->A->ops->mult)(a->A,xx,a->slvec1a);
845:   VecSet(a->slvec1b,0.0);

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

850:   /* copy x into the vec slvec0 */
851:   VecGetArray(a->slvec0,&from);
852:   VecGetArray(xx,&x);

854:   PetscMemcpy(from,x,bs*mbs*sizeof(MatScalar));
855:   VecRestoreArray(a->slvec0,&from);
856:   VecRestoreArray(xx,&x);
857: 
858:   VecScatterBegin(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);
859:   VecScatterEnd(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);
860:   /* supperdiagonal part */
861:   (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,yy);
862:   return(0);
863: }

867: PetscErrorCode MatMult_MPISBAIJ_2comm(Mat A,Vec xx,Vec yy)
868: {
869:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;
871:   PetscInt       nt;

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

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

880:   VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
881:   /* do diagonal part */
882:   (*a->A->ops->mult)(a->A,xx,yy);
883:   /* do supperdiagonal part */
884:   VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
885:   (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);
886:   /* do subdiagonal part */
887:   (*a->B->ops->multtranspose)(a->B,xx,a->lvec);
888:   VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
889:   VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);

891:   return(0);
892: }

896: PetscErrorCode MatMultAdd_MPISBAIJ(Mat A,Vec xx,Vec yy,Vec zz)
897: {
898:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;
900:   PetscInt       mbs=a->mbs,bs=A->rmap->bs;
901:   PetscScalar    *x,*from,zero=0.0;
902: 
904:   /*
905:   PetscSynchronizedPrintf(((PetscObject)A)->comm," MatMultAdd is called ...\n");
906:   PetscSynchronizedFlush(((PetscObject)A)->comm);
907:   */
908:   /* diagonal part */
909:   (*a->A->ops->multadd)(a->A,xx,yy,a->slvec1a);
910:   VecSet(a->slvec1b,zero);

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

915:   /* copy x into the vec slvec0 */
916:   VecGetArray(a->slvec0,&from);
917:   VecGetArray(xx,&x);
918:   PetscMemcpy(from,x,bs*mbs*sizeof(MatScalar));
919:   VecRestoreArray(a->slvec0,&from);
920: 
921:   VecScatterBegin(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);
922:   VecRestoreArray(xx,&x);
923:   VecScatterEnd(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);
924: 
925:   /* supperdiagonal part */
926:   (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,zz);
927: 
928:   return(0);
929: }

933: PetscErrorCode MatMultAdd_MPISBAIJ_2comm(Mat A,Vec xx,Vec yy,Vec zz)
934: {
935:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;

939:   VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
940:   /* do diagonal part */
941:   (*a->A->ops->multadd)(a->A,xx,yy,zz);
942:   /* do supperdiagonal part */
943:   VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
944:   (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);

946:   /* do subdiagonal part */
947:   (*a->B->ops->multtranspose)(a->B,xx,a->lvec);
948:   VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);
949:   VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);

951:   return(0);
952: }

954: /*
955:   This only works correctly for square matrices where the subblock A->A is the 
956:    diagonal block
957: */
960: PetscErrorCode MatGetDiagonal_MPISBAIJ(Mat A,Vec v)
961: {
962:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;

966:   /* if (a->rmap->N != a->cmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block"); */
967:   MatGetDiagonal(a->A,v);
968:   return(0);
969: }

973: PetscErrorCode MatScale_MPISBAIJ(Mat A,PetscScalar aa)
974: {
975:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;

979:   MatScale(a->A,aa);
980:   MatScale(a->B,aa);
981:   return(0);
982: }

986: PetscErrorCode MatGetRow_MPISBAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
987: {
988:   Mat_MPISBAIJ   *mat = (Mat_MPISBAIJ*)matin->data;
989:   PetscScalar    *vworkA,*vworkB,**pvA,**pvB,*v_p;
991:   PetscInt       bs = matin->rmap->bs,bs2 = mat->bs2,i,*cworkA,*cworkB,**pcA,**pcB;
992:   PetscInt       nztot,nzA,nzB,lrow,brstart = matin->rmap->rstart,brend = matin->rmap->rend;
993:   PetscInt       *cmap,*idx_p,cstart = mat->rstartbs;

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

999:   if (!mat->rowvalues && (idx || v)) {
1000:     /*
1001:         allocate enough space to hold information from the longest row.
1002:     */
1003:     Mat_SeqSBAIJ *Aa = (Mat_SeqSBAIJ*)mat->A->data;
1004:     Mat_SeqBAIJ  *Ba = (Mat_SeqBAIJ*)mat->B->data;
1005:     PetscInt     max = 1,mbs = mat->mbs,tmp;
1006:     for (i=0; i<mbs; i++) {
1007:       tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; /* row length */
1008:       if (max < tmp) { max = tmp; }
1009:     }
1010:     PetscMalloc2(max*bs2,PetscScalar,&mat->rowvalues,max*bs2,PetscInt,&mat->rowindices);
1011:   }
1012: 
1013:   if (row < brstart || row >= brend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local rows");
1014:   lrow = row - brstart;  /* local row index */

1016:   pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB;
1017:   if (!v)   {pvA = 0; pvB = 0;}
1018:   if (!idx) {pcA = 0; if (!v) pcB = 0;}
1019:   (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);
1020:   (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);
1021:   nztot = nzA + nzB;

1023:   cmap  = mat->garray;
1024:   if (v  || idx) {
1025:     if (nztot) {
1026:       /* Sort by increasing column numbers, assuming A and B already sorted */
1027:       PetscInt imark = -1;
1028:       if (v) {
1029:         *v = v_p = mat->rowvalues;
1030:         for (i=0; i<nzB; i++) {
1031:           if (cmap[cworkB[i]/bs] < cstart)   v_p[i] = vworkB[i];
1032:           else break;
1033:         }
1034:         imark = i;
1035:         for (i=0; i<nzA; i++)     v_p[imark+i] = vworkA[i];
1036:         for (i=imark; i<nzB; i++) v_p[nzA+i]   = vworkB[i];
1037:       }
1038:       if (idx) {
1039:         *idx = idx_p = mat->rowindices;
1040:         if (imark > -1) {
1041:           for (i=0; i<imark; i++) {
1042:             idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs;
1043:           }
1044:         } else {
1045:           for (i=0; i<nzB; i++) {
1046:             if (cmap[cworkB[i]/bs] < cstart)
1047:               idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ;
1048:             else break;
1049:           }
1050:           imark = i;
1051:         }
1052:         for (i=0; i<nzA; i++)     idx_p[imark+i] = cstart*bs + cworkA[i];
1053:         for (i=imark; i<nzB; i++) idx_p[nzA+i]   = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ;
1054:       }
1055:     } else {
1056:       if (idx) *idx = 0;
1057:       if (v)   *v   = 0;
1058:     }
1059:   }
1060:   *nz = nztot;
1061:   (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);
1062:   (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);
1063:   return(0);
1064: }

1068: PetscErrorCode MatRestoreRow_MPISBAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
1069: {
1070:   Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data;

1073:   if (!baij->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"MatGetRow() must be called first");
1074:   baij->getrowactive = PETSC_FALSE;
1075:   return(0);
1076: }

1080: PetscErrorCode MatGetRowUpperTriangular_MPISBAIJ(Mat A)
1081: {
1082:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;
1083:   Mat_SeqSBAIJ   *aA = (Mat_SeqSBAIJ*)a->A->data;

1086:   aA->getrow_utriangular = PETSC_TRUE;
1087:   return(0);
1088: }
1091: PetscErrorCode MatRestoreRowUpperTriangular_MPISBAIJ(Mat A)
1092: {
1093:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;
1094:   Mat_SeqSBAIJ   *aA = (Mat_SeqSBAIJ*)a->A->data;

1097:   aA->getrow_utriangular = PETSC_FALSE;
1098:   return(0);
1099: }

1103: PetscErrorCode MatRealPart_MPISBAIJ(Mat A)
1104: {
1105:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;

1109:   MatRealPart(a->A);
1110:   MatRealPart(a->B);
1111:   return(0);
1112: }

1116: PetscErrorCode MatImaginaryPart_MPISBAIJ(Mat A)
1117: {
1118:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;

1122:   MatImaginaryPart(a->A);
1123:   MatImaginaryPart(a->B);
1124:   return(0);
1125: }

1129: PetscErrorCode MatZeroEntries_MPISBAIJ(Mat A)
1130: {
1131:   Mat_MPISBAIJ   *l = (Mat_MPISBAIJ*)A->data;

1135:   MatZeroEntries(l->A);
1136:   MatZeroEntries(l->B);
1137:   return(0);
1138: }

1142: PetscErrorCode MatGetInfo_MPISBAIJ(Mat matin,MatInfoType flag,MatInfo *info)
1143: {
1144:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)matin->data;
1145:   Mat            A = a->A,B = a->B;
1147:   PetscReal      isend[5],irecv[5];

1150:   info->block_size     = (PetscReal)matin->rmap->bs;
1151:   MatGetInfo(A,MAT_LOCAL,info);
1152:   isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded;
1153:   isend[3] = info->memory;  isend[4] = info->mallocs;
1154:   MatGetInfo(B,MAT_LOCAL,info);
1155:   isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded;
1156:   isend[3] += info->memory;  isend[4] += info->mallocs;
1157:   if (flag == MAT_LOCAL) {
1158:     info->nz_used      = isend[0];
1159:     info->nz_allocated = isend[1];
1160:     info->nz_unneeded  = isend[2];
1161:     info->memory       = isend[3];
1162:     info->mallocs      = isend[4];
1163:   } else if (flag == MAT_GLOBAL_MAX) {
1164:     MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_MAX,((PetscObject)matin)->comm);
1165:     info->nz_used      = irecv[0];
1166:     info->nz_allocated = irecv[1];
1167:     info->nz_unneeded  = irecv[2];
1168:     info->memory       = irecv[3];
1169:     info->mallocs      = irecv[4];
1170:   } else if (flag == MAT_GLOBAL_SUM) {
1171:     MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_SUM,((PetscObject)matin)->comm);
1172:     info->nz_used      = irecv[0];
1173:     info->nz_allocated = irecv[1];
1174:     info->nz_unneeded  = irecv[2];
1175:     info->memory       = irecv[3];
1176:     info->mallocs      = irecv[4];
1177:   } else {
1178:     SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Unknown MatInfoType argument %d",(int)flag);
1179:   }
1180:   info->fill_ratio_given  = 0; /* no parallel LU/ILU/Cholesky */
1181:   info->fill_ratio_needed = 0;
1182:   info->factor_mallocs    = 0;
1183:   return(0);
1184: }

1188: PetscErrorCode MatSetOption_MPISBAIJ(Mat A,MatOption op,PetscBool  flg)
1189: {
1190:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;
1191:   Mat_SeqSBAIJ   *aA = (Mat_SeqSBAIJ*)a->A->data;

1195:   switch (op) {
1196:   case MAT_NEW_NONZERO_LOCATIONS:
1197:   case MAT_NEW_NONZERO_ALLOCATION_ERR:
1198:   case MAT_UNUSED_NONZERO_LOCATION_ERR:
1199:   case MAT_KEEP_NONZERO_PATTERN:
1200:   case MAT_NEW_NONZERO_LOCATION_ERR:
1201:     MatSetOption(a->A,op,flg);
1202:     MatSetOption(a->B,op,flg);
1203:     break;
1204:   case MAT_ROW_ORIENTED:
1205:     a->roworiented = flg;
1206:     MatSetOption(a->A,op,flg);
1207:     MatSetOption(a->B,op,flg);
1208:     break;
1209:   case MAT_NEW_DIAGONALS:
1210:     PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);
1211:     break;
1212:   case MAT_IGNORE_OFF_PROC_ENTRIES:
1213:     a->donotstash = flg;
1214:     break;
1215:   case MAT_USE_HASH_TABLE:
1216:     a->ht_flag = flg;
1217:     break;
1218:   case MAT_HERMITIAN:
1219:     if (!A->assembled) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Must call MatAssemblyEnd() first");
1220:     MatSetOption(a->A,op,flg);
1221:     A->ops->mult = MatMult_MPISBAIJ_Hermitian;
1222:     break;
1223:   case MAT_SPD:
1224:     A->spd_set                         = PETSC_TRUE;
1225:     A->spd                             = flg;
1226:     if (flg) {
1227:       A->symmetric                     = PETSC_TRUE;
1228:       A->structurally_symmetric        = PETSC_TRUE;
1229:       A->symmetric_set                 = PETSC_TRUE;
1230:       A->structurally_symmetric_set    = PETSC_TRUE;
1231:     }
1232:     break;
1233:   case MAT_SYMMETRIC:
1234:     MatSetOption(a->A,op,flg);
1235:     break;
1236:   case MAT_STRUCTURALLY_SYMMETRIC:
1237:     MatSetOption(a->A,op,flg);
1238:     break;
1239:   case MAT_SYMMETRY_ETERNAL:
1240:     if (!flg) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Matrix must be symmetric");
1241:     PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);
1242:     break;
1243:   case MAT_IGNORE_LOWER_TRIANGULAR:
1244:     aA->ignore_ltriangular = flg;
1245:     break;
1246:   case MAT_ERROR_LOWER_TRIANGULAR:
1247:     aA->ignore_ltriangular = flg;
1248:     break;
1249:   case MAT_GETROW_UPPERTRIANGULAR:
1250:     aA->getrow_utriangular = flg;
1251:     break;
1252:   default:
1253:     SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %d",op);
1254:   }
1255:   return(0);
1256: }

1260: PetscErrorCode MatTranspose_MPISBAIJ(Mat A,MatReuse reuse,Mat *B)
1261: {
1264:   if (MAT_INITIAL_MATRIX || *B != A) {
1265:     MatDuplicate(A,MAT_COPY_VALUES,B);
1266:   }
1267:   return(0);
1268: }

1272: PetscErrorCode MatDiagonalScale_MPISBAIJ(Mat mat,Vec ll,Vec rr)
1273: {
1274:   Mat_MPISBAIJ   *baij = (Mat_MPISBAIJ*)mat->data;
1275:   Mat            a=baij->A, b=baij->B;
1277:   PetscInt       nv,m,n;
1278:   PetscBool      flg;

1281:   if (ll != rr){
1282:     VecEqual(ll,rr,&flg);
1283:     if (!flg) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"For symmetric format, left and right scaling vectors must be same\n");
1284:   }
1285:   if (!ll) return(0);

1287:   MatGetLocalSize(mat,&m,&n);
1288:   if (m != n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"For symmetric format, local size %d %d must be same",m,n);
1289: 
1290:   VecGetLocalSize(rr,&nv);
1291:   if (nv!=n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Left and right vector non-conforming local size");

1293:   VecScatterBegin(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);
1294: 
1295:   /* left diagonalscale the off-diagonal part */
1296:   (*b->ops->diagonalscale)(b,ll,PETSC_NULL);
1297: 
1298:   /* scale the diagonal part */
1299:   (*a->ops->diagonalscale)(a,ll,rr);

1301:   /* right diagonalscale the off-diagonal part */
1302:   VecScatterEnd(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);
1303:   (*b->ops->diagonalscale)(b,PETSC_NULL,baij->lvec);
1304:   return(0);
1305: }

1309: PetscErrorCode MatSetUnfactored_MPISBAIJ(Mat A)
1310: {
1311:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;

1315:   MatSetUnfactored(a->A);
1316:   return(0);
1317: }

1319: static PetscErrorCode MatDuplicate_MPISBAIJ(Mat,MatDuplicateOption,Mat *);

1323: PetscErrorCode MatEqual_MPISBAIJ(Mat A,Mat B,PetscBool  *flag)
1324: {
1325:   Mat_MPISBAIJ   *matB = (Mat_MPISBAIJ*)B->data,*matA = (Mat_MPISBAIJ*)A->data;
1326:   Mat            a,b,c,d;
1327:   PetscBool      flg;

1331:   a = matA->A; b = matA->B;
1332:   c = matB->A; d = matB->B;

1334:   MatEqual(a,c,&flg);
1335:   if (flg) {
1336:     MatEqual(b,d,&flg);
1337:   }
1338:   MPI_Allreduce(&flg,flag,1,MPI_INT,MPI_LAND,((PetscObject)A)->comm);
1339:   return(0);
1340: }

1344: PetscErrorCode MatCopy_MPISBAIJ(Mat A,Mat B,MatStructure str)
1345: {
1347:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ *)A->data;
1348:   Mat_MPISBAIJ   *b = (Mat_MPISBAIJ *)B->data;

1351:   /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */
1352:   if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) {
1353:     MatGetRowUpperTriangular(A);
1354:     MatCopy_Basic(A,B,str);
1355:     MatRestoreRowUpperTriangular(A);
1356:   } else {
1357:     MatCopy(a->A,b->A,str);
1358:     MatCopy(a->B,b->B,str);
1359:   }
1360:   return(0);
1361: }

1365: PetscErrorCode MatSetUpPreallocation_MPISBAIJ(Mat A)
1366: {

1370:   MatMPISBAIJSetPreallocation(A,-PetscMax(A->rmap->bs,1),PETSC_DEFAULT,0,PETSC_DEFAULT,0);
1371:   return(0);
1372: }

1376: PetscErrorCode MatAXPY_MPISBAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str)
1377: {
1379:   Mat_MPISBAIJ   *xx=(Mat_MPISBAIJ *)X->data,*yy=(Mat_MPISBAIJ *)Y->data;
1380:   PetscBLASInt   bnz,one=1;
1381:   Mat_SeqSBAIJ   *xa,*ya;
1382:   Mat_SeqBAIJ    *xb,*yb;

1385:   if (str == SAME_NONZERO_PATTERN) {
1386:     PetscScalar alpha = a;
1387:     xa = (Mat_SeqSBAIJ *)xx->A->data;
1388:     ya = (Mat_SeqSBAIJ *)yy->A->data;
1389:     bnz = PetscBLASIntCast(xa->nz);
1390:     BLASaxpy_(&bnz,&alpha,xa->a,&one,ya->a,&one);
1391:     xb = (Mat_SeqBAIJ *)xx->B->data;
1392:     yb = (Mat_SeqBAIJ *)yy->B->data;
1393:     bnz = PetscBLASIntCast(xb->nz);
1394:     BLASaxpy_(&bnz,&alpha,xb->a,&one,yb->a,&one);
1395:   } else {
1396:     MatGetRowUpperTriangular(X);
1397:     MatAXPY_Basic(Y,a,X,str);
1398:     MatRestoreRowUpperTriangular(X);
1399:   }
1400:   return(0);
1401: }

1405: PetscErrorCode MatSetBlockSize_MPISBAIJ(Mat A,PetscInt bs)
1406: {
1407:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;
1408:   PetscInt        rbs,cbs;
1409:   PetscErrorCode  ierr;

1412:   MatSetBlockSize(a->A,bs);
1413:   MatSetBlockSize(a->B,bs);
1414:   PetscLayoutGetBlockSize(A->rmap,&rbs);
1415:   PetscLayoutGetBlockSize(A->cmap,&cbs);
1416:   if (rbs != bs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Attempt to set block size %d with SBAIJ %d",bs,rbs);
1417:   if (cbs != bs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Attempt to set block size %d with SBAIJ %d",bs,cbs);
1418:   return(0);
1419: }

1423: PetscErrorCode MatGetSubMatrices_MPISBAIJ(Mat A,PetscInt n,const IS irow[],const IS icol[],MatReuse scall,Mat *B[])
1424: {
1426:   PetscInt       i;
1427:   PetscBool      flg;

1430:   for (i=0; i<n; i++) {
1431:     ISEqual(irow[i],icol[i],&flg);
1432:     if (!flg) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Can only get symmetric submatrix for MPISBAIJ matrices");
1433:   }
1434:   MatGetSubMatrices_MPIBAIJ(A,n,irow,icol,scall,B);
1435:   return(0);
1436: }
1437: 

1439: /* -------------------------------------------------------------------*/
1440: static struct _MatOps MatOps_Values = {
1441:        MatSetValues_MPISBAIJ,
1442:        MatGetRow_MPISBAIJ,
1443:        MatRestoreRow_MPISBAIJ,
1444:        MatMult_MPISBAIJ,
1445: /* 4*/ MatMultAdd_MPISBAIJ,
1446:        MatMult_MPISBAIJ,       /* transpose versions are same as non-transpose */
1447:        MatMultAdd_MPISBAIJ,
1448:        0,
1449:        0,
1450:        0,
1451: /*10*/ 0,
1452:        0,
1453:        0,
1454:        MatSOR_MPISBAIJ,
1455:        MatTranspose_MPISBAIJ,
1456: /*15*/ MatGetInfo_MPISBAIJ,
1457:        MatEqual_MPISBAIJ,
1458:        MatGetDiagonal_MPISBAIJ,
1459:        MatDiagonalScale_MPISBAIJ,
1460:        MatNorm_MPISBAIJ,
1461: /*20*/ MatAssemblyBegin_MPISBAIJ,
1462:        MatAssemblyEnd_MPISBAIJ,
1463:        MatSetOption_MPISBAIJ,
1464:        MatZeroEntries_MPISBAIJ,
1465: /*24*/ 0,
1466:        0,
1467:        0,
1468:        0,
1469:        0,
1470: /*29*/ MatSetUpPreallocation_MPISBAIJ,
1471:        0,
1472:        0,
1473:        0,
1474:        0,
1475: /*34*/ MatDuplicate_MPISBAIJ,
1476:        0,
1477:        0,
1478:        0,
1479:        0,
1480: /*39*/ MatAXPY_MPISBAIJ,
1481:        MatGetSubMatrices_MPISBAIJ,
1482:        MatIncreaseOverlap_MPISBAIJ,
1483:        MatGetValues_MPISBAIJ,
1484:        MatCopy_MPISBAIJ,
1485: /*44*/ 0,
1486:        MatScale_MPISBAIJ,
1487:        0,
1488:        0,
1489:        0,
1490: /*49*/ MatSetBlockSize_MPISBAIJ,
1491:        0,
1492:        0,
1493:        0,
1494:        0,
1495: /*54*/ 0,
1496:        0,
1497:        MatSetUnfactored_MPISBAIJ,
1498:        0,
1499:        MatSetValuesBlocked_MPISBAIJ,
1500: /*59*/ 0,
1501:        0,
1502:        0,
1503:        0,
1504:        0,
1505: /*64*/ 0,
1506:        0,
1507:        0,
1508:        0,
1509:        0,
1510: /*69*/ MatGetRowMaxAbs_MPISBAIJ,
1511:        0,
1512:        0,
1513:        0,
1514:        0,
1515: /*74*/ 0,
1516:        0,
1517:        0,
1518:        0,
1519:        0,
1520: /*79*/ 0,
1521:        0,
1522:        0,
1523:        0,
1524:        MatLoad_MPISBAIJ,
1525: /*84*/ 0,
1526:        0,
1527:        0,
1528:        0,
1529:        0,
1530: /*89*/ 0,
1531:        0,
1532:        0,
1533:        0,
1534:        0,
1535: /*94*/ 0,
1536:        0,
1537:        0,
1538:        0,
1539:        0,
1540: /*99*/ 0,
1541:        0,
1542:        0,
1543:        0,
1544:        0,
1545: /*104*/0,
1546:        MatRealPart_MPISBAIJ,
1547:        MatImaginaryPart_MPISBAIJ,
1548:        MatGetRowUpperTriangular_MPISBAIJ,
1549:        MatRestoreRowUpperTriangular_MPISBAIJ,
1550: /*109*/0,
1551:        0,
1552:        0,
1553:        0,
1554:        0,
1555: /*114*/0,
1556:        0,
1557:        0,
1558:        0,
1559:        0,
1560: /*119*/0,
1561:        0,
1562:        0,
1563:        0
1564: };


1570: PetscErrorCode  MatGetDiagonalBlock_MPISBAIJ(Mat A,Mat *a)
1571: {
1573:   *a = ((Mat_MPISBAIJ *)A->data)->A;
1574:   return(0);
1575: }

1581: PetscErrorCode  MatMPISBAIJSetPreallocation_MPISBAIJ(Mat B,PetscInt bs,PetscInt d_nz,PetscInt *d_nnz,PetscInt o_nz,PetscInt *o_nnz)
1582: {
1583:   Mat_MPISBAIJ   *b;
1585:   PetscInt       i,mbs,Mbs,newbs = PetscAbs(bs);

1588:   if (bs < 0){
1589:     PetscOptionsBegin(((PetscObject)B)->comm,((PetscObject)B)->prefix,"Options for MPISBAIJ matrix","Mat");
1590:       PetscOptionsInt("-mat_block_size","Set the blocksize used to store the matrix","MatMPIBAIJSetPreallocation",newbs,&newbs,PETSC_NULL);
1591:     PetscOptionsEnd();
1592:     bs   = PetscAbs(bs);
1593:   }
1594:   if ((d_nnz || o_nnz) && newbs != bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Cannot change blocksize from command line if setting d_nnz or o_nnz");
1595:   bs = newbs;

1597:   if (d_nz == PETSC_DECIDE || d_nz == PETSC_DEFAULT) d_nz = 3;
1598:   if (o_nz == PETSC_DECIDE || o_nz == PETSC_DEFAULT) o_nz = 1;
1599:   if (d_nz < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"d_nz cannot be less than 0: value %D",d_nz);
1600:   if (o_nz < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"o_nz cannot be less than 0: value %D",o_nz);

1602:   B->rmap->bs = B->cmap->bs = bs;
1603:   PetscLayoutSetUp(B->rmap);
1604:   PetscLayoutSetUp(B->cmap);

1606:   if (d_nnz) {
1607:     for (i=0; i<B->rmap->n/bs; i++) {
1608:       if (d_nnz[i] < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"d_nnz cannot be less than -1: local row %D value %D",i,d_nnz[i]);
1609:     }
1610:   }
1611:   if (o_nnz) {
1612:     for (i=0; i<B->rmap->n/bs; i++) {
1613:       if (o_nnz[i] < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"o_nnz cannot be less than -1: local row %D value %D",i,o_nnz[i]);
1614:     }
1615:   }

1617:   b   = (Mat_MPISBAIJ*)B->data;
1618:   mbs = B->rmap->n/bs;
1619:   Mbs = B->rmap->N/bs;
1620:   if (mbs*bs != B->rmap->n) {
1621:     SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"No of local rows %D must be divisible by blocksize %D",B->rmap->N,bs);
1622:   }

1624:   B->rmap->bs  = bs;
1625:   b->bs2 = bs*bs;
1626:   b->mbs = mbs;
1627:   b->nbs = mbs;
1628:   b->Mbs = Mbs;
1629:   b->Nbs = Mbs;

1631:   for (i=0; i<=b->size; i++) {
1632:     b->rangebs[i] = B->rmap->range[i]/bs;
1633:   }
1634:   b->rstartbs = B->rmap->rstart/bs;
1635:   b->rendbs   = B->rmap->rend/bs;
1636: 
1637:   b->cstartbs = B->cmap->rstart/bs;
1638:   b->cendbs   = B->cmap->rend/bs;

1640:   if (!B->preallocated) {
1641:     MatCreate(PETSC_COMM_SELF,&b->A);
1642:     MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);
1643:     MatSetType(b->A,MATSEQSBAIJ);
1644:     PetscLogObjectParent(B,b->A);
1645:     MatCreate(PETSC_COMM_SELF,&b->B);
1646:     MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);
1647:     MatSetType(b->B,MATSEQBAIJ);
1648:     PetscLogObjectParent(B,b->B);
1649:     MatStashCreate_Private(((PetscObject)B)->comm,bs,&B->bstash);
1650:   }

1652:   MatSeqSBAIJSetPreallocation(b->A,bs,d_nz,d_nnz);
1653:   MatSeqBAIJSetPreallocation(b->B,bs,o_nz,o_nnz);
1654:   B->preallocated = PETSC_TRUE;
1655:   return(0);
1656: }

1662: PetscErrorCode MatMPISBAIJSetPreallocationCSR_MPISBAIJ(Mat B,PetscInt bs,const PetscInt ii[],const PetscInt jj[],const PetscScalar V[])
1663: {
1664:   PetscInt       m,rstart,cstart,cend;
1665:   PetscInt       i,j,d,nz,nz_max=0,*d_nnz=0,*o_nnz=0;
1666:   const PetscInt *JJ=0;
1667:   PetscScalar    *values=0;


1672:   if (bs < 1) SETERRQ1(((PetscObject)B)->comm,PETSC_ERR_ARG_OUTOFRANGE,"Invalid block size specified, must be positive but it is %D",bs);
1673:   PetscLayoutSetBlockSize(B->rmap,bs);
1674:   PetscLayoutSetBlockSize(B->cmap,bs);
1675:   PetscLayoutSetUp(B->rmap);
1676:   PetscLayoutSetUp(B->cmap);
1677:   m      = B->rmap->n/bs;
1678:   rstart = B->rmap->rstart/bs;
1679:   cstart = B->cmap->rstart/bs;
1680:   cend   = B->cmap->rend/bs;

1682:   if (ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"ii[0] must be 0 but it is %D",ii[0]);
1683:   PetscMalloc2(m,PetscInt,&d_nnz,m,PetscInt,&o_nnz);
1684:   for (i=0; i<m; i++) {
1685:     nz = ii[i+1] - ii[i];
1686:     if (nz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative number of columns %D",i,nz);
1687:     nz_max = PetscMax(nz_max,nz);
1688:     JJ  = jj + ii[i];
1689:     for (j=0; j<nz; j++) {
1690:       if (*JJ >= cstart) break;
1691:       JJ++;
1692:     }
1693:     d = 0;
1694:     for (; j<nz; j++) {
1695:       if (*JJ++ >= cend) break;
1696:       d++;
1697:     }
1698:     d_nnz[i] = d;
1699:     o_nnz[i] = nz - d;
1700:   }
1701:   MatMPISBAIJSetPreallocation(B,bs,0,d_nnz,0,o_nnz);
1702:   PetscFree2(d_nnz,o_nnz);

1704:   values = (PetscScalar*)V;
1705:   if (!values) {
1706:     PetscMalloc(bs*bs*nz_max*sizeof(PetscScalar),&values);
1707:     PetscMemzero(values,bs*bs*nz_max*sizeof(PetscScalar));
1708:   }
1709:   for (i=0; i<m; i++) {
1710:     PetscInt          row    = i + rstart;
1711:     PetscInt          ncols  = ii[i+1] - ii[i];
1712:     const PetscInt    *icols = jj + ii[i];
1713:     const PetscScalar *svals = values + (V ? (bs*bs*ii[i]) : 0);
1714:     MatSetValuesBlocked_MPISBAIJ(B,1,&row,ncols,icols,svals,INSERT_VALUES);
1715:   }

1717:   if (!V) { PetscFree(values); }
1718:   MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
1719:   MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);

1721:   return(0);
1722: }

1726: #if defined(PETSC_HAVE_MUMPS)
1728: #endif
1729: #if defined(PETSC_HAVE_SPOOLES)
1731: #endif
1732: #if defined(PETSC_HAVE_PASTIX)
1734: #endif

1737: /*MC
1738:    MATMPISBAIJ - MATMPISBAIJ = "mpisbaij" - A matrix type to be used for distributed symmetric sparse block matrices, 
1739:    based on block compressed sparse row format.  Only the upper triangular portion of the "diagonal" portion of 
1740:    the matrix is stored.

1742:   For complex numbers by default this matrix is symmetric, NOT Hermitian symmetric. To make it Hermitian symmetric you
1743:   can call MatSetOption(Mat, MAT_HERMITIAN); 

1745:    Options Database Keys:
1746: . -mat_type mpisbaij - sets the matrix type to "mpisbaij" during a call to MatSetFromOptions()

1748:   Level: beginner

1750: .seealso: MatCreateMPISBAIJ
1751: M*/


1760: PetscErrorCode  MatCreate_MPISBAIJ(Mat B)
1761: {
1762:   Mat_MPISBAIJ   *b;
1764:   PetscBool      flg;


1768:   PetscNewLog(B,Mat_MPISBAIJ,&b);
1769:   B->data = (void*)b;
1770:   PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));

1772:   B->ops->destroy    = MatDestroy_MPISBAIJ;
1773:   B->ops->view       = MatView_MPISBAIJ;
1774:   B->assembled       = PETSC_FALSE;

1776:   B->insertmode = NOT_SET_VALUES;
1777:   MPI_Comm_rank(((PetscObject)B)->comm,&b->rank);
1778:   MPI_Comm_size(((PetscObject)B)->comm,&b->size);

1780:   /* build local table of row and column ownerships */
1781:   PetscMalloc((b->size+2)*sizeof(PetscInt),&b->rangebs);

1783:   /* build cache for off array entries formed */
1784:   MatStashCreate_Private(((PetscObject)B)->comm,1,&B->stash);
1785:   b->donotstash  = PETSC_FALSE;
1786:   b->colmap      = PETSC_NULL;
1787:   b->garray      = PETSC_NULL;
1788:   b->roworiented = PETSC_TRUE;

1790:   /* stuff used in block assembly */
1791:   b->barray       = 0;

1793:   /* stuff used for matrix vector multiply */
1794:   b->lvec         = 0;
1795:   b->Mvctx        = 0;
1796:   b->slvec0       = 0;
1797:   b->slvec0b      = 0;
1798:   b->slvec1       = 0;
1799:   b->slvec1a      = 0;
1800:   b->slvec1b      = 0;
1801:   b->sMvctx       = 0;

1803:   /* stuff for MatGetRow() */
1804:   b->rowindices   = 0;
1805:   b->rowvalues    = 0;
1806:   b->getrowactive = PETSC_FALSE;

1808:   /* hash table stuff */
1809:   b->ht           = 0;
1810:   b->hd           = 0;
1811:   b->ht_size      = 0;
1812:   b->ht_flag      = PETSC_FALSE;
1813:   b->ht_fact      = 0;
1814:   b->ht_total_ct  = 0;
1815:   b->ht_insert_ct = 0;

1817:   /* stuff for MatGetSubMatrices_MPIBAIJ_local() */
1818:   b->ijonly       = PETSC_FALSE;

1820:   b->in_loc       = 0;
1821:   b->v_loc        = 0;
1822:   b->n_loc        = 0;
1823:   PetscOptionsBegin(((PetscObject)B)->comm,PETSC_NULL,"Options for loading MPISBAIJ matrix 1","Mat");
1824:     PetscOptionsBool("-mat_use_hash_table","Use hash table to save memory in constructing matrix","MatSetOption",PETSC_FALSE,&flg,PETSC_NULL);
1825:     if (flg) {
1826:       PetscReal fact = 1.39;
1827:       MatSetOption(B,MAT_USE_HASH_TABLE,PETSC_TRUE);
1828:       PetscOptionsReal("-mat_use_hash_table","Use hash table factor","MatMPIBAIJSetHashTableFactor",fact,&fact,PETSC_NULL);
1829:       if (fact <= 1.0) fact = 1.39;
1830:       MatMPIBAIJSetHashTableFactor(B,fact);
1831:       PetscInfo1(B,"Hash table Factor used %5.2f\n",fact);
1832:     }
1833:   PetscOptionsEnd();

1835: #if defined(PETSC_HAVE_PASTIX)
1836:   PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_pastix_C",
1837:                                            "MatGetFactor_mpisbaij_pastix",
1838:                                            MatGetFactor_mpisbaij_pastix);
1839: #endif
1840: #if defined(PETSC_HAVE_MUMPS)
1841:   PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_mumps_C",
1842:                                      "MatGetFactor_sbaij_mumps",
1843:                                      MatGetFactor_sbaij_mumps);
1844: #endif
1845: #if defined(PETSC_HAVE_SPOOLES)
1846:   PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_spooles_C",
1847:                                      "MatGetFactor_mpisbaij_spooles",
1848:                                      MatGetFactor_mpisbaij_spooles);
1849: #endif
1850:   PetscObjectComposeFunctionDynamic((PetscObject)B,"MatStoreValues_C",
1851:                                      "MatStoreValues_MPISBAIJ",
1852:                                      MatStoreValues_MPISBAIJ);
1853:   PetscObjectComposeFunctionDynamic((PetscObject)B,"MatRetrieveValues_C",
1854:                                      "MatRetrieveValues_MPISBAIJ",
1855:                                      MatRetrieveValues_MPISBAIJ);
1856:   PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetDiagonalBlock_C",
1857:                                      "MatGetDiagonalBlock_MPISBAIJ",
1858:                                      MatGetDiagonalBlock_MPISBAIJ);
1859:   PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMPISBAIJSetPreallocation_C",
1860:                                      "MatMPISBAIJSetPreallocation_MPISBAIJ",
1861:                                      MatMPISBAIJSetPreallocation_MPISBAIJ);
1862:   PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMPISBAIJSetPreallocationCSR_C",
1863:                                      "MatMPISBAIJSetPreallocationCSR_MPISBAIJ",
1864:                                      MatMPISBAIJSetPreallocationCSR_MPISBAIJ);
1865:   PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_mpisbaij_mpisbstrm_C",
1866:                                      "MatConvert_MPISBAIJ_MPISBSTRM",
1867:                                       MatConvert_MPISBAIJ_MPISBSTRM);

1869:   B->symmetric                  = PETSC_TRUE;
1870:   B->structurally_symmetric     = PETSC_TRUE;
1871:   B->symmetric_set              = PETSC_TRUE;
1872:   B->structurally_symmetric_set = PETSC_TRUE;
1873:   PetscObjectChangeTypeName((PetscObject)B,MATMPISBAIJ);
1874:   return(0);
1875: }

1878: /*MC
1879:    MATSBAIJ - MATSBAIJ = "sbaij" - A matrix type to be used for symmetric block sparse matrices.

1881:    This matrix type is identical to MATSEQSBAIJ when constructed with a single process communicator,
1882:    and MATMPISBAIJ otherwise.

1884:    Options Database Keys:
1885: . -mat_type sbaij - sets the matrix type to "sbaij" during a call to MatSetFromOptions()

1887:   Level: beginner

1889: .seealso: MatCreateMPISBAIJ,MATSEQSBAIJ,MATMPISBAIJ
1890: M*/

1894: /*@C
1895:    MatMPISBAIJSetPreallocation - For good matrix assembly performance
1896:    the user should preallocate the matrix storage by setting the parameters 
1897:    d_nz (or d_nnz) and o_nz (or o_nnz).  By setting these parameters accurately,
1898:    performance can be increased by more than a factor of 50.

1900:    Collective on Mat

1902:    Input Parameters:
1903: +  A - the matrix 
1904: .  bs   - size of blockk
1905: .  d_nz  - number of block nonzeros per block row in diagonal portion of local 
1906:            submatrix  (same for all local rows)
1907: .  d_nnz - array containing the number of block nonzeros in the various block rows 
1908:            in the upper triangular and diagonal part of the in diagonal portion of the local
1909:            (possibly different for each block row) or PETSC_NULL.  You must leave room 
1910:            for the diagonal entry even if it is zero.
1911: .  o_nz  - number of block nonzeros per block row in the off-diagonal portion of local
1912:            submatrix (same for all local rows).
1913: -  o_nnz - array containing the number of nonzeros in the various block rows of the
1914:            off-diagonal portion of the local submatrix (possibly different for
1915:            each block row) or PETSC_NULL.


1918:    Options Database Keys:
1919: .   -mat_no_unroll - uses code that does not unroll the loops in the 
1920:                      block calculations (much slower)
1921: .   -mat_block_size - size of the blocks to use

1923:    Notes:

1925:    If PETSC_DECIDE or  PETSC_DETERMINE is used for a particular argument on one processor
1926:    than it must be used on all processors that share the object for that argument.

1928:    If the *_nnz parameter is given then the *_nz parameter is ignored

1930:    Storage Information:
1931:    For a square global matrix we define each processor's diagonal portion 
1932:    to be its local rows and the corresponding columns (a square submatrix);  
1933:    each processor's off-diagonal portion encompasses the remainder of the
1934:    local matrix (a rectangular submatrix). 

1936:    The user can specify preallocated storage for the diagonal part of
1937:    the local submatrix with either d_nz or d_nnz (not both).  Set 
1938:    d_nz=PETSC_DEFAULT and d_nnz=PETSC_NULL for PETSc to control dynamic
1939:    memory allocation.  Likewise, specify preallocated storage for the
1940:    off-diagonal part of the local submatrix with o_nz or o_nnz (not both).

1942:    You can call MatGetInfo() to get information on how effective the preallocation was;
1943:    for example the fields mallocs,nz_allocated,nz_used,nz_unneeded;
1944:    You can also run with the option -info and look for messages with the string 
1945:    malloc in them to see if additional memory allocation was needed.

1947:    Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In
1948:    the figure below we depict these three local rows and all columns (0-11).

1950: .vb
1951:            0 1 2 3 4 5 6 7 8 9 10 11
1952:           -------------------
1953:    row 3  |  o o o d d d o o o o o o
1954:    row 4  |  o o o d d d o o o o o o
1955:    row 5  |  o o o d d d o o o o o o
1956:           -------------------
1957: .ve
1958:   
1959:    Thus, any entries in the d locations are stored in the d (diagonal) 
1960:    submatrix, and any entries in the o locations are stored in the
1961:    o (off-diagonal) submatrix.  Note that the d matrix is stored in
1962:    MatSeqSBAIJ format and the o submatrix in MATSEQBAIJ format.

1964:    Now d_nz should indicate the number of block nonzeros per row in the upper triangular
1965:    plus the diagonal part of the d matrix,
1966:    and o_nz should indicate the number of block nonzeros per row in the upper triangular
1967:    part of the o matrix.
1968:    In general, for PDE problems in which most nonzeros are near the diagonal,
1969:    one expects d_nz >> o_nz.   For large problems you MUST preallocate memory
1970:    or you will get TERRIBLE performance; see the users' manual chapter on
1971:    matrices.

1973:    Level: intermediate

1975: .keywords: matrix, block, aij, compressed row, sparse, parallel

1977: .seealso: MatCreate(), MatCreateSeqSBAIJ(), MatSetValues(), MatCreateMPIBAIJ()
1978: @*/
1979: PetscErrorCode  MatMPISBAIJSetPreallocation(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[])
1980: {

1984:   PetscTryMethod(B,"MatMPISBAIJSetPreallocation_C",(Mat,PetscInt,PetscInt,const PetscInt[],PetscInt,const PetscInt[]),(B,bs,d_nz,d_nnz,o_nz,o_nnz));
1985:   return(0);
1986: }

1990: /*@C
1991:    MatCreateMPISBAIJ - Creates a sparse parallel matrix in symmetric block AIJ format
1992:    (block compressed row).  For good matrix assembly performance
1993:    the user should preallocate the matrix storage by setting the parameters 
1994:    d_nz (or d_nnz) and o_nz (or o_nnz).  By setting these parameters accurately,
1995:    performance can be increased by more than a factor of 50.

1997:    Collective on MPI_Comm

1999:    Input Parameters:
2000: +  comm - MPI communicator
2001: .  bs   - size of blockk
2002: .  m - number of local rows (or PETSC_DECIDE to have calculated if M is given)
2003:            This value should be the same as the local size used in creating the 
2004:            y vector for the matrix-vector product y = Ax.
2005: .  n - number of local columns (or PETSC_DECIDE to have calculated if N is given)
2006:            This value should be the same as the local size used in creating the 
2007:            x vector for the matrix-vector product y = Ax.
2008: .  M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
2009: .  N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
2010: .  d_nz  - number of block nonzeros per block row in diagonal portion of local 
2011:            submatrix  (same for all local rows)
2012: .  d_nnz - array containing the number of block nonzeros in the various block rows 
2013:            in the upper triangular portion of the in diagonal portion of the local 
2014:            (possibly different for each block block row) or PETSC_NULL.  
2015:            You must leave room for the diagonal entry even if it is zero.
2016: .  o_nz  - number of block nonzeros per block row in the off-diagonal portion of local
2017:            submatrix (same for all local rows).
2018: -  o_nnz - array containing the number of nonzeros in the various block rows of the
2019:            off-diagonal portion of the local submatrix (possibly different for
2020:            each block row) or PETSC_NULL.

2022:    Output Parameter:
2023: .  A - the matrix 

2025:    Options Database Keys:
2026: .   -mat_no_unroll - uses code that does not unroll the loops in the 
2027:                      block calculations (much slower)
2028: .   -mat_block_size - size of the blocks to use
2029: .   -mat_mpi - use the parallel matrix data structures even on one processor 
2030:                (defaults to using SeqBAIJ format on one processor)

2032:    It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(),
2033:    MatXXXXSetPreallocation() paradgm instead of this routine directly. 
2034:    [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation]

2036:    Notes:
2037:    The number of rows and columns must be divisible by blocksize.
2038:    This matrix type does not support complex Hermitian operation.

2040:    The user MUST specify either the local or global matrix dimensions
2041:    (possibly both).

2043:    If PETSC_DECIDE or  PETSC_DETERMINE is used for a particular argument on one processor
2044:    than it must be used on all processors that share the object for that argument.

2046:    If the *_nnz parameter is given then the *_nz parameter is ignored

2048:    Storage Information:
2049:    For a square global matrix we define each processor's diagonal portion 
2050:    to be its local rows and the corresponding columns (a square submatrix);  
2051:    each processor's off-diagonal portion encompasses the remainder of the
2052:    local matrix (a rectangular submatrix). 

2054:    The user can specify preallocated storage for the diagonal part of
2055:    the local submatrix with either d_nz or d_nnz (not both).  Set 
2056:    d_nz=PETSC_DEFAULT and d_nnz=PETSC_NULL for PETSc to control dynamic
2057:    memory allocation.  Likewise, specify preallocated storage for the
2058:    off-diagonal part of the local submatrix with o_nz or o_nnz (not both).

2060:    Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In
2061:    the figure below we depict these three local rows and all columns (0-11).

2063: .vb
2064:            0 1 2 3 4 5 6 7 8 9 10 11
2065:           -------------------
2066:    row 3  |  o o o d d d o o o o o o
2067:    row 4  |  o o o d d d o o o o o o
2068:    row 5  |  o o o d d d o o o o o o
2069:           -------------------
2070: .ve
2071:   
2072:    Thus, any entries in the d locations are stored in the d (diagonal) 
2073:    submatrix, and any entries in the o locations are stored in the
2074:    o (off-diagonal) submatrix.  Note that the d matrix is stored in
2075:    MatSeqSBAIJ format and the o submatrix in MATSEQBAIJ format.

2077:    Now d_nz should indicate the number of block nonzeros per row in the upper triangular
2078:    plus the diagonal part of the d matrix,
2079:    and o_nz should indicate the number of block nonzeros per row in the o matrix.
2080:    In general, for PDE problems in which most nonzeros are near the diagonal,
2081:    one expects d_nz >> o_nz.   For large problems you MUST preallocate memory
2082:    or you will get TERRIBLE performance; see the users' manual chapter on
2083:    matrices.

2085:    Level: intermediate

2087: .keywords: matrix, block, aij, compressed row, sparse, parallel

2089: .seealso: MatCreate(), MatCreateSeqSBAIJ(), MatSetValues(), MatCreateMPIBAIJ()
2090: @*/

2092: PetscErrorCode  MatCreateMPISBAIJ(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)
2093: {
2095:   PetscMPIInt    size;

2098:   MatCreate(comm,A);
2099:   MatSetSizes(*A,m,n,M,N);
2100:   MPI_Comm_size(comm,&size);
2101:   if (size > 1) {
2102:     MatSetType(*A,MATMPISBAIJ);
2103:     MatMPISBAIJSetPreallocation(*A,bs,d_nz,d_nnz,o_nz,o_nnz);
2104:   } else {
2105:     MatSetType(*A,MATSEQSBAIJ);
2106:     MatSeqSBAIJSetPreallocation(*A,bs,d_nz,d_nnz);
2107:   }
2108:   return(0);
2109: }


2114: static PetscErrorCode MatDuplicate_MPISBAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat)
2115: {
2116:   Mat            mat;
2117:   Mat_MPISBAIJ   *a,*oldmat = (Mat_MPISBAIJ*)matin->data;
2119:   PetscInt       len=0,nt,bs=matin->rmap->bs,mbs=oldmat->mbs;
2120:   PetscScalar    *array;

2123:   *newmat       = 0;
2124:   MatCreate(((PetscObject)matin)->comm,&mat);
2125:   MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);
2126:   MatSetType(mat,((PetscObject)matin)->type_name);
2127:   PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));
2128:   PetscLayoutReference(matin->rmap,&mat->rmap);
2129:   PetscLayoutReference(matin->cmap,&mat->cmap);
2130: 
2131:   mat->factortype   = matin->factortype;
2132:   mat->preallocated = PETSC_TRUE;
2133:   mat->assembled    = PETSC_TRUE;
2134:   mat->insertmode   = NOT_SET_VALUES;

2136:   a = (Mat_MPISBAIJ*)mat->data;
2137:   a->bs2   = oldmat->bs2;
2138:   a->mbs   = oldmat->mbs;
2139:   a->nbs   = oldmat->nbs;
2140:   a->Mbs   = oldmat->Mbs;
2141:   a->Nbs   = oldmat->Nbs;


2144:   a->size         = oldmat->size;
2145:   a->rank         = oldmat->rank;
2146:   a->donotstash   = oldmat->donotstash;
2147:   a->roworiented  = oldmat->roworiented;
2148:   a->rowindices   = 0;
2149:   a->rowvalues    = 0;
2150:   a->getrowactive = PETSC_FALSE;
2151:   a->barray       = 0;
2152:   a->rstartbs    = oldmat->rstartbs;
2153:   a->rendbs      = oldmat->rendbs;
2154:   a->cstartbs    = oldmat->cstartbs;
2155:   a->cendbs      = oldmat->cendbs;

2157:   /* hash table stuff */
2158:   a->ht           = 0;
2159:   a->hd           = 0;
2160:   a->ht_size      = 0;
2161:   a->ht_flag      = oldmat->ht_flag;
2162:   a->ht_fact      = oldmat->ht_fact;
2163:   a->ht_total_ct  = 0;
2164:   a->ht_insert_ct = 0;
2165: 
2166:   PetscMemcpy(a->rangebs,oldmat->rangebs,(a->size+2)*sizeof(PetscInt));
2167:   if (oldmat->colmap) {
2168: #if defined (PETSC_USE_CTABLE)
2169:     PetscTableCreateCopy(oldmat->colmap,&a->colmap);
2170: #else
2171:     PetscMalloc((a->Nbs)*sizeof(PetscInt),&a->colmap);
2172:     PetscLogObjectMemory(mat,(a->Nbs)*sizeof(PetscInt));
2173:     PetscMemcpy(a->colmap,oldmat->colmap,(a->Nbs)*sizeof(PetscInt));
2174: #endif
2175:   } else a->colmap = 0;

2177:   if (oldmat->garray && (len = ((Mat_SeqBAIJ*)(oldmat->B->data))->nbs)) {
2178:     PetscMalloc(len*sizeof(PetscInt),&a->garray);
2179:     PetscLogObjectMemory(mat,len*sizeof(PetscInt));
2180:     PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));
2181:   } else a->garray = 0;
2182: 
2183:   MatStashCreate_Private(((PetscObject)matin)->comm,matin->rmap->bs,&mat->bstash);
2184:   VecDuplicate(oldmat->lvec,&a->lvec);
2185:   PetscLogObjectParent(mat,a->lvec);
2186:   VecScatterCopy(oldmat->Mvctx,&a->Mvctx);
2187:   PetscLogObjectParent(mat,a->Mvctx);

2189:    VecDuplicate(oldmat->slvec0,&a->slvec0);
2190:   PetscLogObjectParent(mat,a->slvec0);
2191:    VecDuplicate(oldmat->slvec1,&a->slvec1);
2192:   PetscLogObjectParent(mat,a->slvec1);

2194:   VecGetLocalSize(a->slvec1,&nt);
2195:   VecGetArray(a->slvec1,&array);
2196:   VecCreateSeqWithArray(PETSC_COMM_SELF,bs*mbs,array,&a->slvec1a);
2197:   VecCreateSeqWithArray(PETSC_COMM_SELF,nt-bs*mbs,array+bs*mbs,&a->slvec1b);
2198:   VecRestoreArray(a->slvec1,&array);
2199:   VecGetArray(a->slvec0,&array);
2200:   VecCreateSeqWithArray(PETSC_COMM_SELF,nt-bs*mbs,array+bs*mbs,&a->slvec0b);
2201:   VecRestoreArray(a->slvec0,&array);
2202:   PetscLogObjectParent(mat,a->slvec0);
2203:   PetscLogObjectParent(mat,a->slvec1);
2204:   PetscLogObjectParent(mat,a->slvec0b);
2205:   PetscLogObjectParent(mat,a->slvec1a);
2206:   PetscLogObjectParent(mat,a->slvec1b);

2208:   /*  VecScatterCopy(oldmat->sMvctx,&a->sMvctx); - not written yet, replaced by the lazy trick: */
2209:   PetscObjectReference((PetscObject)oldmat->sMvctx);
2210:   a->sMvctx = oldmat->sMvctx;
2211:   PetscLogObjectParent(mat,a->sMvctx);

2213:    MatDuplicate(oldmat->A,cpvalues,&a->A);
2214:   PetscLogObjectParent(mat,a->A);
2215:    MatDuplicate(oldmat->B,cpvalues,&a->B);
2216:   PetscLogObjectParent(mat,a->B);
2217:   PetscFListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);
2218:   *newmat = mat;
2219:   return(0);
2220: }

2224: PetscErrorCode MatLoad_MPISBAIJ(Mat newmat,PetscViewer viewer)
2225: {
2227:   PetscInt       i,nz,j,rstart,rend;
2228:   PetscScalar    *vals,*buf;
2229:   MPI_Comm       comm = ((PetscObject)viewer)->comm;
2230:   MPI_Status     status;
2231:   PetscMPIInt    rank,size,tag = ((PetscObject)viewer)->tag,*sndcounts = 0,*browners,maxnz,*rowners,*locrowlens,mmbs;
2232:   PetscInt       header[4],*rowlengths = 0,M,N,m,*cols;
2233:   PetscInt       *procsnz = 0,jj,*mycols,*ibuf;
2234:   PetscInt       bs=1,Mbs,mbs,extra_rows;
2235:   PetscInt       *dlens,*odlens,*mask,*masked1,*masked2,rowcount,odcount;
2236:   PetscInt       dcount,kmax,k,nzcount,tmp,sizesset=1,grows,gcols;
2237:   int            fd;
2238: 
2240:   PetscOptionsBegin(comm,PETSC_NULL,"Options for loading MPISBAIJ matrix 2","Mat");
2241:     PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,PETSC_NULL);
2242:   PetscOptionsEnd();

2244:   MPI_Comm_size(comm,&size);
2245:   MPI_Comm_rank(comm,&rank);
2246:   if (!rank) {
2247:     PetscViewerBinaryGetDescriptor(viewer,&fd);
2248:     PetscBinaryRead(fd,(char *)header,4,PETSC_INT);
2249:     if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object");
2250:     if (header[3] < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format, cannot load as MPISBAIJ");
2251:   }

2253:   if (newmat->rmap->n < 0 && newmat->rmap->N < 0 && newmat->cmap->n < 0 && newmat->cmap->N < 0) sizesset = 0;

2255:   MPI_Bcast(header+1,3,MPIU_INT,0,comm);
2256:   M = header[1]; N = header[2];

2258:   /* If global rows/cols are set to PETSC_DECIDE, set it to the sizes given in the file */
2259:   if (sizesset && newmat->rmap->N < 0) newmat->rmap->N = M;
2260:   if (sizesset && newmat->cmap->N < 0) newmat->cmap->N = N;
2261: 
2262:   /* If global sizes are set, check if they are consistent with that given in the file */
2263:   if (sizesset) {
2264:     MatGetSize(newmat,&grows,&gcols);
2265:   }
2266:   if (sizesset && newmat->rmap->N != grows) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED, "Inconsistent # of rows:Matrix in file has (%d) and input matrix has (%d)",M,grows);
2267:   if (sizesset && newmat->cmap->N != gcols) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED, "Inconsistent # of cols:Matrix in file has (%d) and input matrix has (%d)",N,gcols);

2269:   if (M != N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Can only do square matrices");

2271:   /* 
2272:      This code adds extra rows to make sure the number of rows is 
2273:      divisible by the blocksize
2274:   */
2275:   Mbs        = M/bs;
2276:   extra_rows = bs - M + bs*(Mbs);
2277:   if (extra_rows == bs) extra_rows = 0;
2278:   else                  Mbs++;
2279:   if (extra_rows &&!rank) {
2280:     PetscInfo(viewer,"Padding loaded matrix to match blocksize\n");
2281:   }

2283:   /* determine ownership of all rows */
2284:   if (newmat->rmap->n < 0) { /* PETSC_DECIDE */
2285:     mbs        = Mbs/size + ((Mbs % size) > rank);
2286:     m          = mbs*bs;
2287:   } else { /* User Set */
2288:     m          = newmat->rmap->n;
2289:     mbs        = m/bs;
2290:   }
2291:   PetscMalloc2(size+1,PetscMPIInt,&rowners,size+1,PetscMPIInt,&browners);
2292:   mmbs       = PetscMPIIntCast(mbs);
2293:   MPI_Allgather(&mmbs,1,MPI_INT,rowners+1,1,MPI_INT,comm);
2294:   rowners[0] = 0;
2295:   for (i=2; i<=size; i++) rowners[i] += rowners[i-1];
2296:   for (i=0; i<=size;  i++) browners[i] = rowners[i]*bs;
2297:   rstart = rowners[rank];
2298:   rend   = rowners[rank+1];
2299: 
2300:   /* distribute row lengths to all processors */
2301:   PetscMalloc((rend-rstart)*bs*sizeof(PetscMPIInt),&locrowlens);
2302:   if (!rank) {
2303:     PetscMalloc((M+extra_rows)*sizeof(PetscInt),&rowlengths);
2304:     PetscBinaryRead(fd,rowlengths,M,PETSC_INT);
2305:     for (i=0; i<extra_rows; i++) rowlengths[M+i] = 1;
2306:     PetscMalloc(size*sizeof(PetscMPIInt),&sndcounts);
2307:     for (i=0; i<size; i++) sndcounts[i] = browners[i+1] - browners[i];
2308:     MPI_Scatterv(rowlengths,sndcounts,browners,MPIU_INT,locrowlens,(rend-rstart)*bs,MPIU_INT,0,comm);
2309:     PetscFree(sndcounts);
2310:   } else {
2311:     MPI_Scatterv(0,0,0,MPIU_INT,locrowlens,(rend-rstart)*bs,MPIU_INT,0,comm);
2312:   }
2313: 
2314:   if (!rank) {   /* procs[0] */
2315:     /* calculate the number of nonzeros on each processor */
2316:     PetscMalloc(size*sizeof(PetscInt),&procsnz);
2317:     PetscMemzero(procsnz,size*sizeof(PetscInt));
2318:     for (i=0; i<size; i++) {
2319:       for (j=rowners[i]*bs; j< rowners[i+1]*bs; j++) {
2320:         procsnz[i] += rowlengths[j];
2321:       }
2322:     }
2323:     PetscFree(rowlengths);
2324: 
2325:     /* determine max buffer needed and allocate it */
2326:     maxnz = 0;
2327:     for (i=0; i<size; i++) {
2328:       maxnz = PetscMax(maxnz,procsnz[i]);
2329:     }
2330:     PetscMalloc(maxnz*sizeof(PetscInt),&cols);

2332:     /* read in my part of the matrix column indices  */
2333:     nz     = procsnz[0];
2334:     PetscMalloc(nz*sizeof(PetscInt),&ibuf);
2335:     mycols = ibuf;
2336:     if (size == 1)  nz -= extra_rows;
2337:     PetscBinaryRead(fd,mycols,nz,PETSC_INT);
2338:     if (size == 1)  for (i=0; i< extra_rows; i++) { mycols[nz+i] = M+i; }

2340:     /* read in every ones (except the last) and ship off */
2341:     for (i=1; i<size-1; i++) {
2342:       nz   = procsnz[i];
2343:       PetscBinaryRead(fd,cols,nz,PETSC_INT);
2344:       MPI_Send(cols,nz,MPIU_INT,i,tag,comm);
2345:     }
2346:     /* read in the stuff for the last proc */
2347:     if (size != 1) {
2348:       nz   = procsnz[size-1] - extra_rows;  /* the extra rows are not on the disk */
2349:       PetscBinaryRead(fd,cols,nz,PETSC_INT);
2350:       for (i=0; i<extra_rows; i++) cols[nz+i] = M+i;
2351:       MPI_Send(cols,nz+extra_rows,MPIU_INT,size-1,tag,comm);
2352:     }
2353:     PetscFree(cols);
2354:   } else {  /* procs[i], i>0 */
2355:     /* determine buffer space needed for message */
2356:     nz = 0;
2357:     for (i=0; i<m; i++) {
2358:       nz += locrowlens[i];
2359:     }
2360:     PetscMalloc(nz*sizeof(PetscInt),&ibuf);
2361:     mycols = ibuf;
2362:     /* receive message of column indices*/
2363:     MPI_Recv(mycols,nz,MPIU_INT,0,tag,comm,&status);
2364:     MPI_Get_count(&status,MPIU_INT,&maxnz);
2365:     if (maxnz != nz) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file");
2366:   }

2368:   /* loop over local rows, determining number of off diagonal entries */
2369:   PetscMalloc2(rend-rstart,PetscInt,&dlens,rend-rstart,PetscInt,&odlens);
2370:   PetscMalloc3(Mbs,PetscInt,&mask,Mbs,PetscInt,&masked1,Mbs,PetscInt,&masked2);
2371:   PetscMemzero(mask,Mbs*sizeof(PetscInt));
2372:   PetscMemzero(masked1,Mbs*sizeof(PetscInt));
2373:   PetscMemzero(masked2,Mbs*sizeof(PetscInt));
2374:   rowcount = 0;
2375:   nzcount  = 0;
2376:   for (i=0; i<mbs; i++) {
2377:     dcount  = 0;
2378:     odcount = 0;
2379:     for (j=0; j<bs; j++) {
2380:       kmax = locrowlens[rowcount];
2381:       for (k=0; k<kmax; k++) {
2382:         tmp = mycols[nzcount++]/bs; /* block col. index */
2383:         if (!mask[tmp]) {
2384:           mask[tmp] = 1;
2385:           if (tmp < rstart || tmp >= rend) masked2[odcount++] = tmp; /* entry in off-diag portion */
2386:           else masked1[dcount++] = tmp; /* entry in diag portion */
2387:         }
2388:       }
2389:       rowcount++;
2390:     }
2391: 
2392:     dlens[i]  = dcount;  /* d_nzz[i] */
2393:     odlens[i] = odcount; /* o_nzz[i] */

2395:     /* zero out the mask elements we set */
2396:     for (j=0; j<dcount; j++) mask[masked1[j]] = 0;
2397:     for (j=0; j<odcount; j++) mask[masked2[j]] = 0;
2398:   }
2399:     if (!sizesset) {
2400:     MatSetSizes(newmat,m,m,M+extra_rows,N+extra_rows);
2401:   }
2402:   MatSetOption(newmat,MAT_IGNORE_LOWER_TRIANGULAR,PETSC_TRUE);
2403:   MatMPISBAIJSetPreallocation(newmat,bs,0,dlens,0,odlens);
2404: 
2405:   if (!rank) {
2406:     PetscMalloc(maxnz*sizeof(PetscScalar),&buf);
2407:     /* read in my part of the matrix numerical values  */
2408:     nz = procsnz[0];
2409:     vals = buf;
2410:     mycols = ibuf;
2411:     if (size == 1)  nz -= extra_rows;
2412:     PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);
2413:     if (size == 1)  for (i=0; i< extra_rows; i++) { vals[nz+i] = 1.0; }

2415:     /* insert into matrix */
2416:     jj      = rstart*bs;
2417:     for (i=0; i<m; i++) {
2418:       MatSetValues(newmat,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);
2419:       mycols += locrowlens[i];
2420:       vals   += locrowlens[i];
2421:       jj++;
2422:     }

2424:     /* read in other processors (except the last one) and ship out */
2425:     for (i=1; i<size-1; i++) {
2426:       nz   = procsnz[i];
2427:       vals = buf;
2428:       PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);
2429:       MPI_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newmat)->tag,comm);
2430:     }
2431:     /* the last proc */
2432:     if (size != 1){
2433:       nz   = procsnz[i] - extra_rows;
2434:       vals = buf;
2435:       PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);
2436:       for (i=0; i<extra_rows; i++) vals[nz+i] = 1.0;
2437:       MPI_Send(vals,nz+extra_rows,MPIU_SCALAR,size-1,((PetscObject)newmat)->tag,comm);
2438:     }
2439:     PetscFree(procsnz);

2441:   } else {
2442:     /* receive numeric values */
2443:     PetscMalloc(nz*sizeof(PetscScalar),&buf);

2445:     /* receive message of values*/
2446:     vals   = buf;
2447:     mycols = ibuf;
2448:     MPI_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newmat)->tag,comm,&status);
2449:     MPI_Get_count(&status,MPIU_SCALAR,&maxnz);
2450:     if (maxnz != nz) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file");

2452:     /* insert into matrix */
2453:     jj      = rstart*bs;
2454:     for (i=0; i<m; i++) {
2455:       MatSetValues_MPISBAIJ(newmat,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);
2456:       mycols += locrowlens[i];
2457:       vals   += locrowlens[i];
2458:       jj++;
2459:     }
2460:   }

2462:   PetscFree(locrowlens);
2463:   PetscFree(buf);
2464:   PetscFree(ibuf);
2465:   PetscFree2(rowners,browners);
2466:   PetscFree2(dlens,odlens);
2467:   PetscFree3(mask,masked1,masked2);
2468:   MatAssemblyBegin(newmat,MAT_FINAL_ASSEMBLY);
2469:   MatAssemblyEnd(newmat,MAT_FINAL_ASSEMBLY);
2470:   return(0);
2471: }

2475: /*XXXXX@
2476:    MatMPISBAIJSetHashTableFactor - Sets the factor required to compute the size of the HashTable.

2478:    Input Parameters:
2479: .  mat  - the matrix
2480: .  fact - factor

2482:    Not Collective on Mat, each process can have a different hash factor

2484:    Level: advanced

2486:   Notes:
2487:    This can also be set by the command line option: -mat_use_hash_table fact

2489: .keywords: matrix, hashtable, factor, HT

2491: .seealso: MatSetOption()
2492: @XXXXX*/


2497: PetscErrorCode MatGetRowMaxAbs_MPISBAIJ(Mat A,Vec v,PetscInt idx[])
2498: {
2499:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;
2500:   Mat_SeqBAIJ    *b = (Mat_SeqBAIJ*)(a->B)->data;
2501:   PetscReal      atmp;
2502:   PetscReal      *work,*svalues,*rvalues;
2504:   PetscInt       i,bs,mbs,*bi,*bj,brow,j,ncols,krow,kcol,col,row,Mbs,bcol;
2505:   PetscMPIInt    rank,size;
2506:   PetscInt       *rowners_bs,dest,count,source;
2507:   PetscScalar    *va;
2508:   MatScalar      *ba;
2509:   MPI_Status     stat;

2512:   if (idx) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Send email to petsc-maint@mcs.anl.gov");
2513:   MatGetRowMaxAbs(a->A,v,PETSC_NULL);
2514:   VecGetArray(v,&va);

2516:   MPI_Comm_size(((PetscObject)A)->comm,&size);
2517:   MPI_Comm_rank(((PetscObject)A)->comm,&rank);

2519:   bs   = A->rmap->bs;
2520:   mbs  = a->mbs;
2521:   Mbs  = a->Mbs;
2522:   ba   = b->a;
2523:   bi   = b->i;
2524:   bj   = b->j;

2526:   /* find ownerships */
2527:   rowners_bs = A->rmap->range;

2529:   /* each proc creates an array to be distributed */
2530:   PetscMalloc(bs*Mbs*sizeof(PetscReal),&work);
2531:   PetscMemzero(work,bs*Mbs*sizeof(PetscReal));

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

2554:     /* send values to its owners */
2555:     for (dest=rank+1; dest<size; dest++){
2556:       svalues = work + rowners_bs[dest];
2557:       count   = rowners_bs[dest+1]-rowners_bs[dest];
2558:       MPI_Send(svalues,count,MPIU_REAL,dest,rank,((PetscObject)A)->comm);
2559:     }
2560:   }
2561: 
2562:   /* receive values */
2563:   if (rank){
2564:     rvalues = work;
2565:     count   = rowners_bs[rank+1]-rowners_bs[rank];
2566:     for (source=0; source<rank; source++){
2567:       MPI_Recv(rvalues,count,MPIU_REAL,MPI_ANY_SOURCE,MPI_ANY_TAG,((PetscObject)A)->comm,&stat);
2568:       /* process values */
2569:       for (i=0; i<count; i++){
2570:         if (PetscRealPart(va[i]) < rvalues[i]) va[i] = rvalues[i];
2571:       }
2572:     }
2573:   }

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

2582: PetscErrorCode MatSOR_MPISBAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx)
2583: {
2584:   Mat_MPISBAIJ      *mat = (Mat_MPISBAIJ*)matin->data;
2585:   PetscErrorCode    ierr;
2586:   PetscInt          mbs=mat->mbs,bs=matin->rmap->bs;
2587:   PetscScalar       *x,*ptr,*from;
2588:   Vec               bb1;
2589:   const PetscScalar *b;
2590: 
2592:   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);
2593:   if (bs > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"SSOR for block size > 1 is not yet implemented");

2595:   if (flag == SOR_APPLY_UPPER) {
2596:     (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
2597:     return(0);
2598:   }

2600:   if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP){
2601:     if ( flag & SOR_ZERO_INITIAL_GUESS ) {
2602:       (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,lits,xx);
2603:       its--;
2604:     }

2606:     VecDuplicate(bb,&bb1);
2607:     while (its--){
2608: 
2609:       /* lower triangular part: slvec0b = - B^T*xx */
2610:       (*mat->B->ops->multtranspose)(mat->B,xx,mat->slvec0b);
2611: 
2612:       /* copy xx into slvec0a */
2613:       VecGetArray(mat->slvec0,&ptr);
2614:       VecGetArray(xx,&x);
2615:       PetscMemcpy(ptr,x,bs*mbs*sizeof(MatScalar));
2616:       VecRestoreArray(mat->slvec0,&ptr);

2618:       VecScale(mat->slvec0,-1.0);

2620:       /* copy bb into slvec1a */
2621:       VecGetArray(mat->slvec1,&ptr);
2622:       VecGetArrayRead(bb,&b);
2623:       PetscMemcpy(ptr,b,bs*mbs*sizeof(MatScalar));
2624:       VecRestoreArray(mat->slvec1,&ptr);

2626:       /* set slvec1b = 0 */
2627:       VecSet(mat->slvec1b,0.0);

2629:       VecScatterBegin(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);
2630:       VecRestoreArray(xx,&x);
2631:       VecRestoreArrayRead(bb,&b);
2632:       VecScatterEnd(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);

2634:       /* upper triangular part: bb1 = bb1 - B*x */
2635:       (*mat->B->ops->multadd)(mat->B,mat->slvec1b,mat->slvec1a,bb1);
2636: 
2637:       /* local diagonal sweep */
2638:       (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,lits,xx);
2639:     }
2640:     VecDestroy(&bb1);
2641:   } else if ((flag & SOR_LOCAL_FORWARD_SWEEP) && (its == 1) && (flag & SOR_ZERO_INITIAL_GUESS)){
2642:     (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
2643:   } else if ((flag & SOR_LOCAL_BACKWARD_SWEEP) && (its == 1) && (flag & SOR_ZERO_INITIAL_GUESS)){
2644:     (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
2645:   } else if (flag & SOR_EISENSTAT) {
2646:     Vec               xx1;
2647:     PetscBool         hasop;
2648:     const PetscScalar *diag;
2649:     PetscScalar       *sl,scale = (omega - 2.0)/omega;
2650:     PetscInt          i,n;

2652:     if (!mat->xx1) {
2653:       VecDuplicate(bb,&mat->xx1);
2654:       VecDuplicate(bb,&mat->bb1);
2655:     }
2656:     xx1 = mat->xx1;
2657:     bb1 = mat->bb1;

2659:     (*mat->A->ops->sor)(mat->A,bb,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_BACKWARD_SWEEP),fshift,lits,1,xx);

2661:     if (!mat->diag) {
2662:       /* this is wrong for same matrix with new nonzero values */
2663:       MatGetVecs(matin,&mat->diag,PETSC_NULL);
2664:       MatGetDiagonal(matin,mat->diag);
2665:     }
2666:     MatHasOperation(matin,MATOP_MULT_DIAGONAL_BLOCK,&hasop);

2668:     if (hasop) {
2669:       MatMultDiagonalBlock(matin,xx,bb1);
2670:       VecAYPX(mat->slvec1a,scale,bb);
2671:     } else {
2672:       /*
2673:           These two lines are replaced by code that may be a bit faster for a good compiler
2674:       VecPointwiseMult(mat->slvec1a,mat->diag,xx);
2675:       VecAYPX(mat->slvec1a,scale,bb);
2676:       */
2677:       VecGetArray(mat->slvec1a,&sl);
2678:       VecGetArrayRead(mat->diag,&diag);
2679:       VecGetArrayRead(bb,&b);
2680:       VecGetArray(xx,&x);
2681:       VecGetLocalSize(xx,&n);
2682:       if (omega == 1.0) {
2683:         for (i=0; i<n; i++) {
2684:           sl[i] = b[i] - diag[i]*x[i];
2685:         }
2686:         PetscLogFlops(2.0*n);
2687:       } else {
2688:         for (i=0; i<n; i++) {
2689:           sl[i] = b[i] + scale*diag[i]*x[i];
2690:         }
2691:         PetscLogFlops(3.0*n);
2692:       }
2693:       VecRestoreArray(mat->slvec1a,&sl);
2694:       VecRestoreArrayRead(mat->diag,&diag);
2695:       VecRestoreArrayRead(bb,&b);
2696:       VecRestoreArray(xx,&x);
2697:     }

2699:     /* multiply off-diagonal portion of matrix */
2700:     VecSet(mat->slvec1b,0.0);
2701:     (*mat->B->ops->multtranspose)(mat->B,xx,mat->slvec0b);
2702:     VecGetArray(mat->slvec0,&from);
2703:     VecGetArray(xx,&x);
2704:     PetscMemcpy(from,x,bs*mbs*sizeof(MatScalar));
2705:     VecRestoreArray(mat->slvec0,&from);
2706:     VecRestoreArray(xx,&x);
2707:     VecScatterBegin(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);
2708:     VecScatterEnd(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);
2709:     (*mat->B->ops->multadd)(mat->B,mat->slvec1b,mat->slvec1a,mat->slvec1a);

2711:     /* local sweep */
2712:     (*mat->A->ops->sor)(mat->A,mat->slvec1a,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_FORWARD_SWEEP),fshift,lits,1,xx1);
2713:     VecAXPY(xx,1.0,xx1);
2714:   } else {
2715:     SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"MatSORType is not supported for SBAIJ matrix format");
2716:   }
2717:   return(0);
2718: }

2722: PetscErrorCode MatSOR_MPISBAIJ_2comm(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx)
2723: {
2724:   Mat_MPISBAIJ   *mat = (Mat_MPISBAIJ*)matin->data;
2726:   Vec            lvec1,bb1;
2727: 
2729:   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);
2730:   if (matin->rmap->bs > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"SSOR for block size > 1 is not yet implemented");

2732:   if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP){
2733:     if ( flag & SOR_ZERO_INITIAL_GUESS ) {
2734:       (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,lits,xx);
2735:       its--;
2736:     }

2738:     VecDuplicate(mat->lvec,&lvec1);
2739:     VecDuplicate(bb,&bb1);
2740:     while (its--){
2741:       VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
2742: 
2743:       /* lower diagonal part: bb1 = bb - B^T*xx */
2744:       (*mat->B->ops->multtranspose)(mat->B,xx,lvec1);
2745:       VecScale(lvec1,-1.0);

2747:       VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
2748:       VecCopy(bb,bb1);
2749:       VecScatterBegin(mat->Mvctx,lvec1,bb1,ADD_VALUES,SCATTER_REVERSE);

2751:       /* upper diagonal part: bb1 = bb1 - B*x */
2752:       VecScale(mat->lvec,-1.0);
2753:       (*mat->B->ops->multadd)(mat->B,mat->lvec,bb1,bb1);

2755:       VecScatterEnd(mat->Mvctx,lvec1,bb1,ADD_VALUES,SCATTER_REVERSE);
2756: 
2757:       /* diagonal sweep */
2758:       (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,lits,xx);
2759:     }
2760:     VecDestroy(&lvec1);
2761:     VecDestroy(&bb1);
2762:   } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"MatSORType is not supported for SBAIJ matrix format");
2763:   return(0);
2764: }

2768: /*@
2769:      MatCreateMPISBAIJWithArrays - creates a MPI SBAIJ matrix using arrays that contain in standard
2770:          CSR format the local rows. 

2772:    Collective on MPI_Comm

2774:    Input Parameters:
2775: +  comm - MPI communicator
2776: .  bs - the block size, only a block size of 1 is supported
2777: .  m - number of local rows (Cannot be PETSC_DECIDE)
2778: .  n - This value should be the same as the local size used in creating the 
2779:        x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have
2780:        calculated if N is given) For square matrices n is almost always m.
2781: .  M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
2782: .  N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
2783: .   i - row indices
2784: .   j - column indices
2785: -   a - matrix values

2787:    Output Parameter:
2788: .   mat - the matrix

2790:    Level: intermediate

2792:    Notes:
2793:        The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc;
2794:      thus you CANNOT change the matrix entries by changing the values of a[] after you have 
2795:      called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays.

2797:        The i and j indices are 0 based, and i indices are indices corresponding to the local j array.

2799: .keywords: matrix, aij, compressed row, sparse, parallel

2801: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(),
2802:           MPIAIJ, MatCreateMPIAIJ(), MatCreateMPIAIJWithSplitArrays()
2803: @*/
2804: 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)
2805: {


2810:   if (i[0]) {
2811:     SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0");
2812:   }
2813:   if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative");
2814:   MatCreate(comm,mat);
2815:   MatSetSizes(*mat,m,n,M,N);
2816:   MatSetType(*mat,MATMPISBAIJ);
2817:   MatMPISBAIJSetPreallocationCSR(*mat,bs,i,j,a);
2818:   return(0);
2819: }


2824: /*@C
2825:    MatMPISBAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in BAIJ format
2826:    (the default parallel PETSc format).  

2828:    Collective on MPI_Comm

2830:    Input Parameters:
2831: +  A - the matrix 
2832: .  bs - the block size
2833: .  i - the indices into j for the start of each local row (starts with zero)
2834: .  j - the column indices for each local row (starts with zero) these must be sorted for each row
2835: -  v - optional values in the matrix

2837:    Level: developer

2839: .keywords: matrix, aij, compressed row, sparse, parallel

2841: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIBAIJSetPreallocation(), MatCreateMPIAIJ(), MPIAIJ
2842: @*/
2843: PetscErrorCode  MatMPISBAIJSetPreallocationCSR(Mat B,PetscInt bs,const PetscInt i[],const PetscInt j[], const PetscScalar v[])
2844: {

2848:   PetscTryMethod(B,"MatMPISBAIJSetPreallocationCSR_C",(Mat,PetscInt,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,bs,i,j,v));
2849:   return(0);
2850: }