Actual source code: mpisell.c

petsc-main 2021-03-06
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  1: #include <../src/mat/impls/aij/mpi/mpiaij.h>
  2: #include <../src/mat/impls/sell/mpi/mpisell.h>
  3: #include <petsc/private/vecimpl.h>
  4: #include <petsc/private/isimpl.h>
  5: #include <petscblaslapack.h>
  6: #include <petscsf.h>

  8: /*MC
  9:    MATSELL - MATSELL = "sell" - A matrix type to be used for sparse matrices.

 11:    This matrix type is identical to MATSEQSELL when constructed with a single process communicator,
 12:    and MATMPISELL otherwise.  As a result, for single process communicators,
 13:   MatSeqSELLSetPreallocation is supported, and similarly MatMPISELLSetPreallocation is supported
 14:   for communicators controlling multiple processes.  It is recommended that you call both of
 15:   the above preallocation routines for simplicity.

 17:    Options Database Keys:
 18: . -mat_type sell - sets the matrix type to "sell" during a call to MatSetFromOptions()

 20:   Level: beginner

 22: .seealso: MatCreateSELL(), MatCreateSeqSELL(), MATSEQSELL, MATMPISELL
 23: M*/

 25: PetscErrorCode MatDiagonalSet_MPISELL(Mat Y,Vec D,InsertMode is)
 26: {
 28:   Mat_MPISELL    *sell=(Mat_MPISELL*)Y->data;

 31:   if (Y->assembled && Y->rmap->rstart == Y->cmap->rstart && Y->rmap->rend == Y->cmap->rend) {
 32:     MatDiagonalSet(sell->A,D,is);
 33:   } else {
 34:     MatDiagonalSet_Default(Y,D,is);
 35:   }
 36:   return(0);
 37: }

 39: /*
 40:   Local utility routine that creates a mapping from the global column
 41: number to the local number in the off-diagonal part of the local
 42: storage of the matrix.  When PETSC_USE_CTABLE is used this is scalable at
 43: a slightly higher hash table cost; without it it is not scalable (each processor
 44: has an order N integer array but is fast to acess.
 45: */
 46: PetscErrorCode MatCreateColmap_MPISELL_Private(Mat mat)
 47: {
 48:   Mat_MPISELL    *sell=(Mat_MPISELL*)mat->data;
 50:   PetscInt       n=sell->B->cmap->n,i;

 53:   if (!sell->garray) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"MPISELL Matrix was assembled but is missing garray");
 54: #if defined(PETSC_USE_CTABLE)
 55:   PetscTableCreate(n,mat->cmap->N+1,&sell->colmap);
 56:   for (i=0; i<n; i++) {
 57:     PetscTableAdd(sell->colmap,sell->garray[i]+1,i+1,INSERT_VALUES);
 58:   }
 59: #else
 60:   PetscCalloc1(mat->cmap->N+1,&sell->colmap);
 61:   PetscLogObjectMemory((PetscObject)mat,(mat->cmap->N+1)*sizeof(PetscInt));
 62:   for (i=0; i<n; i++) sell->colmap[sell->garray[i]] = i+1;
 63: #endif
 64:   return(0);
 65: }

 67: #define MatSetValues_SeqSELL_A_Private(row,col,value,addv,orow,ocol) \
 68:   { \
 69:     if (col <= lastcol1) low1 = 0; \
 70:     else                high1 = nrow1; \
 71:     lastcol1 = col; \
 72:     while (high1-low1 > 5) { \
 73:       t = (low1+high1)/2; \
 74:       if (*(cp1+8*t) > col) high1 = t; \
 75:       else                   low1 = t; \
 76:     } \
 77:     for (_i=low1; _i<high1; _i++) { \
 78:       if (*(cp1+8*_i) > col) break; \
 79:       if (*(cp1+8*_i) == col) { \
 80:         if (addv == ADD_VALUES) *(vp1+8*_i) += value;   \
 81:         else                     *(vp1+8*_i) = value; \
 82:         goto a_noinsert; \
 83:       } \
 84:     }  \
 85:     if (value == 0.0 && ignorezeroentries) {low1 = 0; high1 = nrow1;goto a_noinsert;} \
 86:     if (nonew == 1) {low1 = 0; high1 = nrow1; goto a_noinsert;} \
 87:     if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero at global row/column (%D, %D) into matrix", orow, ocol); \
 88:     MatSeqXSELLReallocateSELL(A,am,1,nrow1,a->sliidx,row/8,row,col,a->colidx,a->val,cp1,vp1,nonew,MatScalar); \
 89:     /* shift up all the later entries in this row */ \
 90:     for (ii=nrow1-1; ii>=_i; ii--) { \
 91:       *(cp1+8*(ii+1)) = *(cp1+8*ii); \
 92:       *(vp1+8*(ii+1)) = *(vp1+8*ii); \
 93:     } \
 94:     *(cp1+8*_i) = col; \
 95:     *(vp1+8*_i) = value; \
 96:     a->nz++; nrow1++; A->nonzerostate++; \
 97:     a_noinsert: ; \
 98:     a->rlen[row] = nrow1; \
 99:   }

101: #define MatSetValues_SeqSELL_B_Private(row,col,value,addv,orow,ocol) \
102:   { \
103:     if (col <= lastcol2) low2 = 0; \
104:     else                high2 = nrow2; \
105:     lastcol2 = col; \
106:     while (high2-low2 > 5) { \
107:       t = (low2+high2)/2; \
108:       if (*(cp2+8*t) > col) high2 = t; \
109:       else low2  = t; \
110:     } \
111:     for (_i=low2; _i<high2; _i++) { \
112:       if (*(cp2+8*_i) > col) break; \
113:       if (*(cp2+8*_i) == col) { \
114:         if (addv == ADD_VALUES) *(vp2+8*_i) += value; \
115:         else                     *(vp2+8*_i) = value; \
116:         goto b_noinsert; \
117:       } \
118:     } \
119:     if (value == 0.0 && ignorezeroentries) {low2 = 0; high2 = nrow2; goto b_noinsert;} \
120:     if (nonew == 1) {low2 = 0; high2 = nrow2; goto b_noinsert;} \
121:     if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero at global row/column (%D, %D) into matrix", orow, ocol); \
122:     MatSeqXSELLReallocateSELL(B,bm,1,nrow2,b->sliidx,row/8,row,col,b->colidx,b->val,cp2,vp2,nonew,MatScalar); \
123:     /* shift up all the later entries in this row */ \
124:     for (ii=nrow2-1; ii>=_i; ii--) { \
125:       *(cp2+8*(ii+1)) = *(cp2+8*ii); \
126:       *(vp2+8*(ii+1)) = *(vp2+8*ii); \
127:     } \
128:     *(cp2+8*_i) = col; \
129:     *(vp2+8*_i) = value; \
130:     b->nz++; nrow2++; B->nonzerostate++; \
131:     b_noinsert: ; \
132:     b->rlen[row] = nrow2; \
133:   }

135: PetscErrorCode MatSetValues_MPISELL(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv)
136: {
137:   Mat_MPISELL    *sell=(Mat_MPISELL*)mat->data;
138:   PetscScalar    value;
140:   PetscInt       i,j,rstart=mat->rmap->rstart,rend=mat->rmap->rend,shift1,shift2;
141:   PetscInt       cstart=mat->cmap->rstart,cend=mat->cmap->rend,row,col;
142:   PetscBool      roworiented=sell->roworiented;

144:   /* Some Variables required in the macro */
145:   Mat            A=sell->A;
146:   Mat_SeqSELL    *a=(Mat_SeqSELL*)A->data;
147:   PetscBool      ignorezeroentries=a->ignorezeroentries,found;
148:   Mat            B=sell->B;
149:   Mat_SeqSELL    *b=(Mat_SeqSELL*)B->data;
150:   PetscInt       *cp1,*cp2,ii,_i,nrow1,nrow2,low1,high1,low2,high2,t,lastcol1,lastcol2;
151:   MatScalar      *vp1,*vp2;

154:   for (i=0; i<m; i++) {
155:     if (im[i] < 0) continue;
156:     if (PetscUnlikelyDebug(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);
157:     if (im[i] >= rstart && im[i] < rend) {
158:       row      = im[i] - rstart;
159:       lastcol1 = -1;
160:       shift1   = a->sliidx[row>>3]+(row&0x07); /* starting index of the row */
161:       cp1      = a->colidx+shift1;
162:       vp1      = a->val+shift1;
163:       nrow1    = a->rlen[row];
164:       low1     = 0;
165:       high1    = nrow1;
166:       lastcol2 = -1;
167:       shift2   = b->sliidx[row>>3]+(row&0x07); /* starting index of the row */
168:       cp2      = b->colidx+shift2;
169:       vp2      = b->val+shift2;
170:       nrow2    = b->rlen[row];
171:       low2     = 0;
172:       high2    = nrow2;

174:       for (j=0; j<n; j++) {
175:         if (roworiented) value = v[i*n+j];
176:         else             value = v[i+j*m];
177:         if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES)) continue;
178:         if (in[j] >= cstart && in[j] < cend) {
179:           col   = in[j] - cstart;
180:           MatSetValue_SeqSELL_Private(A,row,col,value,addv,im[i],in[j],cp1,vp1,lastcol1,low1,high1); /* set one value */
181:         } else if (in[j] < 0) continue;
182:         else if (PetscUnlikelyDebug(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);
183:         else {
184:           if (mat->was_assembled) {
185:             if (!sell->colmap) {
186:               MatCreateColmap_MPISELL_Private(mat);
187:             }
188: #if defined(PETSC_USE_CTABLE)
189:             PetscTableFind(sell->colmap,in[j]+1,&col);
190:             col--;
191: #else
192:             col = sell->colmap[in[j]] - 1;
193: #endif
194:             if (col < 0 && !((Mat_SeqSELL*)(sell->B->data))->nonew) {
195:               MatDisAssemble_MPISELL(mat);
196:               col    = in[j];
197:               /* Reinitialize the variables required by MatSetValues_SeqSELL_B_Private() */
198:               B      = sell->B;
199:               b      = (Mat_SeqSELL*)B->data;
200:               shift2 = b->sliidx[row>>3]+(row&0x07); /* starting index of the row */
201:               cp2    = b->colidx+shift2;
202:               vp2    = b->val+shift2;
203:               nrow2  = b->rlen[row];
204:               low2   = 0;
205:               high2  = nrow2;
206:             } else if (col < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero at global row/column (%D, %D) into matrix", im[i], in[j]);
207:           } else col = in[j];
208:           MatSetValue_SeqSELL_Private(B,row,col,value,addv,im[i],in[j],cp2,vp2,lastcol2,low2,high2); /* set one value */
209:         }
210:       }
211:     } else {
212:       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]);
213:       if (!sell->donotstash) {
214:         mat->assembled = PETSC_FALSE;
215:         if (roworiented) {
216:           MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));
217:         } else {
218:           MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));
219:         }
220:       }
221:     }
222:   }
223:   return(0);
224: }

226: PetscErrorCode MatGetValues_MPISELL(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[])
227: {
228:   Mat_MPISELL    *sell=(Mat_MPISELL*)mat->data;
230:   PetscInt       i,j,rstart=mat->rmap->rstart,rend=mat->rmap->rend;
231:   PetscInt       cstart=mat->cmap->rstart,cend=mat->cmap->rend,row,col;

234:   for (i=0; i<m; i++) {
235:     if (idxm[i] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",idxm[i]);*/
236:     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);
237:     if (idxm[i] >= rstart && idxm[i] < rend) {
238:       row = idxm[i] - rstart;
239:       for (j=0; j<n; j++) {
240:         if (idxn[j] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column: %D",idxn[j]); */
241:         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);
242:         if (idxn[j] >= cstart && idxn[j] < cend) {
243:           col  = idxn[j] - cstart;
244:           MatGetValues(sell->A,1,&row,1,&col,v+i*n+j);
245:         } else {
246:           if (!sell->colmap) {
247:             MatCreateColmap_MPISELL_Private(mat);
248:           }
249: #if defined(PETSC_USE_CTABLE)
250:           PetscTableFind(sell->colmap,idxn[j]+1,&col);
251:           col--;
252: #else
253:           col = sell->colmap[idxn[j]] - 1;
254: #endif
255:           if ((col < 0) || (sell->garray[col] != idxn[j])) *(v+i*n+j) = 0.0;
256:           else {
257:             MatGetValues(sell->B,1,&row,1,&col,v+i*n+j);
258:           }
259:         }
260:       }
261:     } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local values currently supported");
262:   }
263:   return(0);
264: }

266: extern PetscErrorCode MatMultDiagonalBlock_MPISELL(Mat,Vec,Vec);

268: PetscErrorCode MatAssemblyBegin_MPISELL(Mat mat,MatAssemblyType mode)
269: {
270:   Mat_MPISELL    *sell=(Mat_MPISELL*)mat->data;
272:   PetscInt       nstash,reallocs;

275:   if (sell->donotstash || mat->nooffprocentries) return(0);

277:   MatStashScatterBegin_Private(mat,&mat->stash,mat->rmap->range);
278:   MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);
279:   PetscInfo2(sell->A,"Stash has %D entries, uses %D mallocs.\n",nstash,reallocs);
280:   return(0);
281: }

283: PetscErrorCode MatAssemblyEnd_MPISELL(Mat mat,MatAssemblyType mode)
284: {
285:   Mat_MPISELL    *sell=(Mat_MPISELL*)mat->data;
287:   PetscMPIInt    n;
288:   PetscInt       i,flg;
289:   PetscInt       *row,*col;
290:   PetscScalar    *val;
291:   PetscBool      other_disassembled;
292:   /* do not use 'b = (Mat_SeqSELL*)sell->B->data' as B can be reset in disassembly */
294:   if (!sell->donotstash && !mat->nooffprocentries) {
295:     while (1) {
296:       MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);
297:       if (!flg) break;

299:       for (i=0; i<n; i++) { /* assemble one by one */
300:         MatSetValues_MPISELL(mat,1,row+i,1,col+i,val+i,mat->insertmode);
301:       }
302:     }
303:     MatStashScatterEnd_Private(&mat->stash);
304:   }
305:   MatAssemblyBegin(sell->A,mode);
306:   MatAssemblyEnd(sell->A,mode);

308:   /*
309:      determine if any processor has disassembled, if so we must
310:      also disassemble ourselfs, in order that we may reassemble.
311:   */
312:   /*
313:      if nonzero structure of submatrix B cannot change then we know that
314:      no processor disassembled thus we can skip this stuff
315:   */
316:   if (!((Mat_SeqSELL*)sell->B->data)->nonew) {
317:     MPIU_Allreduce(&mat->was_assembled,&other_disassembled,1,MPIU_BOOL,MPI_PROD,PetscObjectComm((PetscObject)mat));
318:     if (mat->was_assembled && !other_disassembled) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"MatDisAssemble not implemented yet\n");
319:   }
320:   if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) {
321:     MatSetUpMultiply_MPISELL(mat);
322:   }
323:   /*
324:   MatSetOption(sell->B,MAT_USE_INODES,PETSC_FALSE);
325:   */
326:   MatAssemblyBegin(sell->B,mode);
327:   MatAssemblyEnd(sell->B,mode);
328:   PetscFree2(sell->rowvalues,sell->rowindices);
329:   sell->rowvalues = NULL;
330:   VecDestroy(&sell->diag);

332:   /* if no new nonzero locations are allowed in matrix then only set the matrix state the first time through */
333:   if ((!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) || !((Mat_SeqSELL*)(sell->A->data))->nonew) {
334:     PetscObjectState state = sell->A->nonzerostate + sell->B->nonzerostate;
335:     MPIU_Allreduce(&state,&mat->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)mat));
336:   }
337:   return(0);
338: }

340: PetscErrorCode MatZeroEntries_MPISELL(Mat A)
341: {
342:   Mat_MPISELL    *l=(Mat_MPISELL*)A->data;

346:   MatZeroEntries(l->A);
347:   MatZeroEntries(l->B);
348:   return(0);
349: }

351: PetscErrorCode MatMult_MPISELL(Mat A,Vec xx,Vec yy)
352: {
353:   Mat_MPISELL    *a=(Mat_MPISELL*)A->data;
355:   PetscInt       nt;

358:   VecGetLocalSize(xx,&nt);
359:   if (nt != A->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible partition of A (%D) and xx (%D)",A->cmap->n,nt);
360:   VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
361:   (*a->A->ops->mult)(a->A,xx,yy);
362:   VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
363:   (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);
364:   return(0);
365: }

367: PetscErrorCode MatMultDiagonalBlock_MPISELL(Mat A,Vec bb,Vec xx)
368: {
369:   Mat_MPISELL    *a=(Mat_MPISELL*)A->data;

373:   MatMultDiagonalBlock(a->A,bb,xx);
374:   return(0);
375: }

377: PetscErrorCode MatMultAdd_MPISELL(Mat A,Vec xx,Vec yy,Vec zz)
378: {
379:   Mat_MPISELL    *a=(Mat_MPISELL*)A->data;

383:   VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
384:   (*a->A->ops->multadd)(a->A,xx,yy,zz);
385:   VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
386:   (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);
387:   return(0);
388: }

390: PetscErrorCode MatMultTranspose_MPISELL(Mat A,Vec xx,Vec yy)
391: {
392:   Mat_MPISELL    *a=(Mat_MPISELL*)A->data;

396:   /* do nondiagonal part */
397:   (*a->B->ops->multtranspose)(a->B,xx,a->lvec);
398:   /* do local part */
399:   (*a->A->ops->multtranspose)(a->A,xx,yy);
400:   /* add partial results together */
401:   VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
402:   VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
403:   return(0);
404: }

406: PetscErrorCode MatIsTranspose_MPISELL(Mat Amat,Mat Bmat,PetscReal tol,PetscBool *f)
407: {
408:   MPI_Comm       comm;
409:   Mat_MPISELL    *Asell=(Mat_MPISELL*)Amat->data,*Bsell;
410:   Mat            Adia=Asell->A,Bdia,Aoff,Boff,*Aoffs,*Boffs;
411:   IS             Me,Notme;
413:   PetscInt       M,N,first,last,*notme,i;
414:   PetscMPIInt    size;

417:   /* Easy test: symmetric diagonal block */
418:   Bsell = (Mat_MPISELL*)Bmat->data; Bdia = Bsell->A;
419:   MatIsTranspose(Adia,Bdia,tol,f);
420:   if (!*f) return(0);
421:   PetscObjectGetComm((PetscObject)Amat,&comm);
422:   MPI_Comm_size(comm,&size);
423:   if (size == 1) return(0);

425:   /* Hard test: off-diagonal block. This takes a MatCreateSubMatrix. */
426:   MatGetSize(Amat,&M,&N);
427:   MatGetOwnershipRange(Amat,&first,&last);
428:   PetscMalloc1(N-last+first,&notme);
429:   for (i=0; i<first; i++) notme[i] = i;
430:   for (i=last; i<M; i++) notme[i-last+first] = i;
431:   ISCreateGeneral(MPI_COMM_SELF,N-last+first,notme,PETSC_COPY_VALUES,&Notme);
432:   ISCreateStride(MPI_COMM_SELF,last-first,first,1,&Me);
433:   MatCreateSubMatrices(Amat,1,&Me,&Notme,MAT_INITIAL_MATRIX,&Aoffs);
434:   Aoff = Aoffs[0];
435:   MatCreateSubMatrices(Bmat,1,&Notme,&Me,MAT_INITIAL_MATRIX,&Boffs);
436:   Boff = Boffs[0];
437:   MatIsTranspose(Aoff,Boff,tol,f);
438:   MatDestroyMatrices(1,&Aoffs);
439:   MatDestroyMatrices(1,&Boffs);
440:   ISDestroy(&Me);
441:   ISDestroy(&Notme);
442:   PetscFree(notme);
443:   return(0);
444: }

446: PetscErrorCode MatMultTransposeAdd_MPISELL(Mat A,Vec xx,Vec yy,Vec zz)
447: {
448:   Mat_MPISELL    *a=(Mat_MPISELL*)A->data;

452:   /* do nondiagonal part */
453:   (*a->B->ops->multtranspose)(a->B,xx,a->lvec);
454:   /* do local part */
455:   (*a->A->ops->multtransposeadd)(a->A,xx,yy,zz);
456:   /* add partial results together */
457:   VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);
458:   VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);
459:   return(0);
460: }

462: /*
463:   This only works correctly for square matrices where the subblock A->A is the
464:    diagonal block
465: */
466: PetscErrorCode MatGetDiagonal_MPISELL(Mat A,Vec v)
467: {
469:   Mat_MPISELL    *a=(Mat_MPISELL*)A->data;

472:   if (A->rmap->N != A->cmap->N) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block");
473:   if (A->rmap->rstart != A->cmap->rstart || A->rmap->rend != A->cmap->rend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"row partition must equal col partition");
474:   MatGetDiagonal(a->A,v);
475:   return(0);
476: }

478: PetscErrorCode MatScale_MPISELL(Mat A,PetscScalar aa)
479: {
480:   Mat_MPISELL    *a=(Mat_MPISELL*)A->data;

484:   MatScale(a->A,aa);
485:   MatScale(a->B,aa);
486:   return(0);
487: }

489: PetscErrorCode MatDestroy_MPISELL(Mat mat)
490: {
491:   Mat_MPISELL    *sell=(Mat_MPISELL*)mat->data;

495: #if defined(PETSC_USE_LOG)
496:   PetscLogObjectState((PetscObject)mat,"Rows=%D, Cols=%D",mat->rmap->N,mat->cmap->N);
497: #endif
498:   MatStashDestroy_Private(&mat->stash);
499:   VecDestroy(&sell->diag);
500:   MatDestroy(&sell->A);
501:   MatDestroy(&sell->B);
502: #if defined(PETSC_USE_CTABLE)
503:   PetscTableDestroy(&sell->colmap);
504: #else
505:   PetscFree(sell->colmap);
506: #endif
507:   PetscFree(sell->garray);
508:   VecDestroy(&sell->lvec);
509:   VecScatterDestroy(&sell->Mvctx);
510:   PetscFree2(sell->rowvalues,sell->rowindices);
511:   PetscFree(sell->ld);
512:   PetscFree(mat->data);

514:   PetscObjectChangeTypeName((PetscObject)mat,NULL);
515:   PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C",NULL);
516:   PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C",NULL);
517:   PetscObjectComposeFunction((PetscObject)mat,"MatIsTranspose_C",NULL);
518:   PetscObjectComposeFunction((PetscObject)mat,"MatMPISELLSetPreallocation_C",NULL);
519:   PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpisell_mpiaij_C",NULL);
520:   PetscObjectComposeFunction((PetscObject)mat,"MatDiagonalScaleLocal_C",NULL);
521:   return(0);
522: }

524: #include <petscdraw.h>
525: PetscErrorCode MatView_MPISELL_ASCIIorDraworSocket(Mat mat,PetscViewer viewer)
526: {
527:   Mat_MPISELL       *sell=(Mat_MPISELL*)mat->data;
528:   PetscErrorCode    ierr;
529:   PetscMPIInt       rank=sell->rank,size=sell->size;
530:   PetscBool         isdraw,iascii,isbinary;
531:   PetscViewer       sviewer;
532:   PetscViewerFormat format;

535:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);
536:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
537:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);
538:   if (iascii) {
539:     PetscViewerGetFormat(viewer,&format);
540:     if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) {
541:       MatInfo   info;
542:       PetscBool inodes;

544:       MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);
545:       MatGetInfo(mat,MAT_LOCAL,&info);
546:       MatInodeGetInodeSizes(sell->A,NULL,(PetscInt**)&inodes,NULL);
547:       PetscViewerASCIIPushSynchronized(viewer);
548:       if (!inodes) {
549:         PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D mem %D, not using I-node routines\n",
550:                                                   rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(PetscInt)info.memory);
551:       } else {
552:         PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D mem %D, using I-node routines\n",
553:                                                   rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(PetscInt)info.memory);
554:       }
555:       MatGetInfo(sell->A,MAT_LOCAL,&info);
556:       PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);
557:       MatGetInfo(sell->B,MAT_LOCAL,&info);
558:       PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);
559:       PetscViewerFlush(viewer);
560:       PetscViewerASCIIPopSynchronized(viewer);
561:       PetscViewerASCIIPrintf(viewer,"Information on VecScatter used in matrix-vector product: \n");
562:       VecScatterView(sell->Mvctx,viewer);
563:       return(0);
564:     } else if (format == PETSC_VIEWER_ASCII_INFO) {
565:       PetscInt inodecount,inodelimit,*inodes;
566:       MatInodeGetInodeSizes(sell->A,&inodecount,&inodes,&inodelimit);
567:       if (inodes) {
568:         PetscViewerASCIIPrintf(viewer,"using I-node (on process 0) routines: found %D nodes, limit used is %D\n",inodecount,inodelimit);
569:       } else {
570:         PetscViewerASCIIPrintf(viewer,"not using I-node (on process 0) routines\n");
571:       }
572:       return(0);
573:     } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) {
574:       return(0);
575:     }
576:   } else if (isbinary) {
577:     if (size == 1) {
578:       PetscObjectSetName((PetscObject)sell->A,((PetscObject)mat)->name);
579:       MatView(sell->A,viewer);
580:     } else {
581:       /* MatView_MPISELL_Binary(mat,viewer); */
582:     }
583:     return(0);
584:   } else if (isdraw) {
585:     PetscDraw draw;
586:     PetscBool isnull;
587:     PetscViewerDrawGetDraw(viewer,0,&draw);
588:     PetscDrawIsNull(draw,&isnull);
589:     if (isnull) return(0);
590:   }

592:   {
593:     /* assemble the entire matrix onto first processor. */
594:     Mat         A;
595:     Mat_SeqSELL *Aloc;
596:     PetscInt    M=mat->rmap->N,N=mat->cmap->N,*acolidx,row,col,i,j;
597:     MatScalar   *aval;
598:     PetscBool   isnonzero;

600:     MatCreate(PetscObjectComm((PetscObject)mat),&A);
601:     if (!rank) {
602:       MatSetSizes(A,M,N,M,N);
603:     } else {
604:       MatSetSizes(A,0,0,M,N);
605:     }
606:     /* This is just a temporary matrix, so explicitly using MATMPISELL is probably best */
607:     MatSetType(A,MATMPISELL);
608:     MatMPISELLSetPreallocation(A,0,NULL,0,NULL);
609:     MatSetOption(A,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_FALSE);
610:     PetscLogObjectParent((PetscObject)mat,(PetscObject)A);

612:     /* copy over the A part */
613:     Aloc = (Mat_SeqSELL*)sell->A->data;
614:     acolidx = Aloc->colidx; aval = Aloc->val;
615:     for (i=0; i<Aloc->totalslices; i++) { /* loop over slices */
616:       for (j=Aloc->sliidx[i]; j<Aloc->sliidx[i+1]; j++) {
617:         isnonzero = (PetscBool)((j-Aloc->sliidx[i])/8 < Aloc->rlen[(i<<3)+(j&0x07)]);
618:         if (isnonzero) { /* check the mask bit */
619:           row  = (i<<3)+(j&0x07) + mat->rmap->rstart; /* i<<3 is the starting row of this slice */
620:           col  = *acolidx + mat->rmap->rstart;
621:           MatSetValues(A,1,&row,1,&col,aval,INSERT_VALUES);
622:         }
623:         aval++; acolidx++;
624:       }
625:     }

627:     /* copy over the B part */
628:     Aloc = (Mat_SeqSELL*)sell->B->data;
629:     acolidx = Aloc->colidx; aval = Aloc->val;
630:     for (i=0; i<Aloc->totalslices; i++) {
631:       for (j=Aloc->sliidx[i]; j<Aloc->sliidx[i+1]; j++) {
632:         isnonzero = (PetscBool)((j-Aloc->sliidx[i])/8 < Aloc->rlen[(i<<3)+(j&0x07)]);
633:         if (isnonzero) {
634:           row  = (i<<3)+(j&0x07) + mat->rmap->rstart;
635:           col  = sell->garray[*acolidx];
636:           MatSetValues(A,1,&row,1,&col,aval,INSERT_VALUES);
637:         }
638:         aval++; acolidx++;
639:       }
640:     }

642:     MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);
643:     MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);
644:     /*
645:        Everyone has to call to draw the matrix since the graphics waits are
646:        synchronized across all processors that share the PetscDraw object
647:     */
648:     PetscViewerGetSubViewer(viewer,PETSC_COMM_SELF,&sviewer);
649:     if (!rank) {
650:       PetscObjectSetName((PetscObject)((Mat_MPISELL*)(A->data))->A,((PetscObject)mat)->name);
651:       MatView_SeqSELL(((Mat_MPISELL*)(A->data))->A,sviewer);
652:     }
653:     PetscViewerRestoreSubViewer(viewer,PETSC_COMM_SELF,&sviewer);
654:     PetscViewerFlush(viewer);
655:     MatDestroy(&A);
656:   }
657:   return(0);
658: }

660: PetscErrorCode MatView_MPISELL(Mat mat,PetscViewer viewer)
661: {
663:   PetscBool      iascii,isdraw,issocket,isbinary;

666:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
667:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);
668:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);
669:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSOCKET,&issocket);
670:   if (iascii || isdraw || isbinary || issocket) {
671:     MatView_MPISELL_ASCIIorDraworSocket(mat,viewer);
672:   }
673:   return(0);
674: }

676: PetscErrorCode MatGetGhosts_MPISELL(Mat mat,PetscInt *nghosts,const PetscInt *ghosts[])
677: {
678:   Mat_MPISELL    *sell=(Mat_MPISELL*)mat->data;

682:   MatGetSize(sell->B,NULL,nghosts);
683:   if (ghosts) *ghosts = sell->garray;
684:   return(0);
685: }

687: PetscErrorCode MatGetInfo_MPISELL(Mat matin,MatInfoType flag,MatInfo *info)
688: {
689:   Mat_MPISELL    *mat=(Mat_MPISELL*)matin->data;
690:   Mat            A=mat->A,B=mat->B;
692:   PetscLogDouble isend[5],irecv[5];

695:   info->block_size = 1.0;
696:   MatGetInfo(A,MAT_LOCAL,info);

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

701:   MatGetInfo(B,MAT_LOCAL,info);

703:   isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded;
704:   isend[3] += info->memory;  isend[4] += info->mallocs;
705:   if (flag == MAT_LOCAL) {
706:     info->nz_used      = isend[0];
707:     info->nz_allocated = isend[1];
708:     info->nz_unneeded  = isend[2];
709:     info->memory       = isend[3];
710:     info->mallocs      = isend[4];
711:   } else if (flag == MAT_GLOBAL_MAX) {
712:     MPIU_Allreduce(isend,irecv,5,MPIU_PETSCLOGDOUBLE,MPI_MAX,PetscObjectComm((PetscObject)matin));

714:     info->nz_used      = irecv[0];
715:     info->nz_allocated = irecv[1];
716:     info->nz_unneeded  = irecv[2];
717:     info->memory       = irecv[3];
718:     info->mallocs      = irecv[4];
719:   } else if (flag == MAT_GLOBAL_SUM) {
720:     MPIU_Allreduce(isend,irecv,5,MPIU_PETSCLOGDOUBLE,MPI_SUM,PetscObjectComm((PetscObject)matin));

722:     info->nz_used      = irecv[0];
723:     info->nz_allocated = irecv[1];
724:     info->nz_unneeded  = irecv[2];
725:     info->memory       = irecv[3];
726:     info->mallocs      = irecv[4];
727:   }
728:   info->fill_ratio_given  = 0; /* no parallel LU/ILU/Cholesky */
729:   info->fill_ratio_needed = 0;
730:   info->factor_mallocs    = 0;
731:   return(0);
732: }

734: PetscErrorCode MatSetOption_MPISELL(Mat A,MatOption op,PetscBool flg)
735: {
736:   Mat_MPISELL    *a=(Mat_MPISELL*)A->data;

740:   switch (op) {
741:   case MAT_NEW_NONZERO_LOCATIONS:
742:   case MAT_NEW_NONZERO_ALLOCATION_ERR:
743:   case MAT_UNUSED_NONZERO_LOCATION_ERR:
744:   case MAT_KEEP_NONZERO_PATTERN:
745:   case MAT_NEW_NONZERO_LOCATION_ERR:
746:   case MAT_USE_INODES:
747:   case MAT_IGNORE_ZERO_ENTRIES:
748:     MatCheckPreallocated(A,1);
749:     MatSetOption(a->A,op,flg);
750:     MatSetOption(a->B,op,flg);
751:     break;
752:   case MAT_ROW_ORIENTED:
753:     MatCheckPreallocated(A,1);
754:     a->roworiented = flg;

756:     MatSetOption(a->A,op,flg);
757:     MatSetOption(a->B,op,flg);
758:     break;
759:   case MAT_FORCE_DIAGONAL_ENTRIES:
760:   case MAT_SORTED_FULL:
761:     PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);
762:     break;
763:   case MAT_IGNORE_OFF_PROC_ENTRIES:
764:     a->donotstash = flg;
765:     break;
766:   case MAT_SPD:
767:     A->spd_set = PETSC_TRUE;
768:     A->spd     = flg;
769:     if (flg) {
770:       A->symmetric                  = PETSC_TRUE;
771:       A->structurally_symmetric     = PETSC_TRUE;
772:       A->symmetric_set              = PETSC_TRUE;
773:       A->structurally_symmetric_set = PETSC_TRUE;
774:     }
775:     break;
776:   case MAT_SYMMETRIC:
777:     MatCheckPreallocated(A,1);
778:     MatSetOption(a->A,op,flg);
779:     break;
780:   case MAT_STRUCTURALLY_SYMMETRIC:
781:     MatCheckPreallocated(A,1);
782:     MatSetOption(a->A,op,flg);
783:     break;
784:   case MAT_HERMITIAN:
785:     MatCheckPreallocated(A,1);
786:     MatSetOption(a->A,op,flg);
787:     break;
788:   case MAT_SYMMETRY_ETERNAL:
789:     MatCheckPreallocated(A,1);
790:     MatSetOption(a->A,op,flg);
791:     break;
792:   default:
793:     SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %d",op);
794:   }
795:   return(0);
796: }


799: PetscErrorCode MatDiagonalScale_MPISELL(Mat mat,Vec ll,Vec rr)
800: {
801:   Mat_MPISELL    *sell=(Mat_MPISELL*)mat->data;
802:   Mat            a=sell->A,b=sell->B;
804:   PetscInt       s1,s2,s3;

807:   MatGetLocalSize(mat,&s2,&s3);
808:   if (rr) {
809:     VecGetLocalSize(rr,&s1);
810:     if (s1!=s3) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"right vector non-conforming local size");
811:     /* Overlap communication with computation. */
812:     VecScatterBegin(sell->Mvctx,rr,sell->lvec,INSERT_VALUES,SCATTER_FORWARD);
813:   }
814:   if (ll) {
815:     VecGetLocalSize(ll,&s1);
816:     if (s1!=s2) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"left vector non-conforming local size");
817:     (*b->ops->diagonalscale)(b,ll,NULL);
818:   }
819:   /* scale  the diagonal block */
820:   (*a->ops->diagonalscale)(a,ll,rr);

822:   if (rr) {
823:     /* Do a scatter end and then right scale the off-diagonal block */
824:     VecScatterEnd(sell->Mvctx,rr,sell->lvec,INSERT_VALUES,SCATTER_FORWARD);
825:     (*b->ops->diagonalscale)(b,NULL,sell->lvec);
826:   }
827:   return(0);
828: }

830: PetscErrorCode MatSetUnfactored_MPISELL(Mat A)
831: {
832:   Mat_MPISELL    *a=(Mat_MPISELL*)A->data;

836:   MatSetUnfactored(a->A);
837:   return(0);
838: }

840: PetscErrorCode MatEqual_MPISELL(Mat A,Mat B,PetscBool  *flag)
841: {
842:   Mat_MPISELL    *matB=(Mat_MPISELL*)B->data,*matA=(Mat_MPISELL*)A->data;
843:   Mat            a,b,c,d;
844:   PetscBool      flg;

848:   a = matA->A; b = matA->B;
849:   c = matB->A; d = matB->B;

851:   MatEqual(a,c,&flg);
852:   if (flg) {
853:     MatEqual(b,d,&flg);
854:   }
855:   MPIU_Allreduce(&flg,flag,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)A));
856:   return(0);
857: }

859: PetscErrorCode MatCopy_MPISELL(Mat A,Mat B,MatStructure str)
860: {
862:   Mat_MPISELL    *a=(Mat_MPISELL*)A->data;
863:   Mat_MPISELL    *b=(Mat_MPISELL*)B->data;

866:   /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */
867:   if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) {
868:     /* because of the column compression in the off-processor part of the matrix a->B,
869:        the number of columns in a->B and b->B may be different, hence we cannot call
870:        the MatCopy() directly on the two parts. If need be, we can provide a more
871:        efficient copy than the MatCopy_Basic() by first uncompressing the a->B matrices
872:        then copying the submatrices */
873:     MatCopy_Basic(A,B,str);
874:   } else {
875:     MatCopy(a->A,b->A,str);
876:     MatCopy(a->B,b->B,str);
877:   }
878:   return(0);
879: }

881: PetscErrorCode MatSetUp_MPISELL(Mat A)
882: {

886:    MatMPISELLSetPreallocation(A,PETSC_DEFAULT,NULL,PETSC_DEFAULT,NULL);
887:   return(0);
888: }


891: extern PetscErrorCode MatConjugate_SeqSELL(Mat);

893: PetscErrorCode MatConjugate_MPISELL(Mat mat)
894: {
895: #if defined(PETSC_USE_COMPLEX)
897:   Mat_MPISELL    *sell=(Mat_MPISELL*)mat->data;

900:   MatConjugate_SeqSELL(sell->A);
901:   MatConjugate_SeqSELL(sell->B);
902: #else
904: #endif
905:   return(0);
906: }

908: PetscErrorCode MatRealPart_MPISELL(Mat A)
909: {
910:   Mat_MPISELL    *a=(Mat_MPISELL*)A->data;

914:   MatRealPart(a->A);
915:   MatRealPart(a->B);
916:   return(0);
917: }

919: PetscErrorCode MatImaginaryPart_MPISELL(Mat A)
920: {
921:   Mat_MPISELL    *a=(Mat_MPISELL*)A->data;

925:   MatImaginaryPart(a->A);
926:   MatImaginaryPart(a->B);
927:   return(0);
928: }

930: PetscErrorCode MatInvertBlockDiagonal_MPISELL(Mat A,const PetscScalar **values)
931: {
932:   Mat_MPISELL    *a=(Mat_MPISELL*)A->data;

936:   MatInvertBlockDiagonal(a->A,values);
937:   A->factorerrortype = a->A->factorerrortype;
938:   return(0);
939: }

941: static PetscErrorCode MatSetRandom_MPISELL(Mat x,PetscRandom rctx)
942: {
944:   Mat_MPISELL    *sell=(Mat_MPISELL*)x->data;

947:   MatSetRandom(sell->A,rctx);
948:   MatSetRandom(sell->B,rctx);
949:   MatAssemblyBegin(x,MAT_FINAL_ASSEMBLY);
950:   MatAssemblyEnd(x,MAT_FINAL_ASSEMBLY);
951:   return(0);
952: }

954: PetscErrorCode MatSetFromOptions_MPISELL(PetscOptionItems *PetscOptionsObject,Mat A)
955: {

959:   PetscOptionsHead(PetscOptionsObject,"MPISELL options");
960:   PetscOptionsTail();
961:   return(0);
962: }

964: PetscErrorCode MatShift_MPISELL(Mat Y,PetscScalar a)
965: {
967:   Mat_MPISELL    *msell=(Mat_MPISELL*)Y->data;
968:   Mat_SeqSELL    *sell=(Mat_SeqSELL*)msell->A->data;

971:   if (!Y->preallocated) {
972:     MatMPISELLSetPreallocation(Y,1,NULL,0,NULL);
973:   } else if (!sell->nz) {
974:     PetscInt nonew = sell->nonew;
975:     MatSeqSELLSetPreallocation(msell->A,1,NULL);
976:     sell->nonew = nonew;
977:   }
978:   MatShift_Basic(Y,a);
979:   return(0);
980: }

982: PetscErrorCode MatMissingDiagonal_MPISELL(Mat A,PetscBool  *missing,PetscInt *d)
983: {
984:   Mat_MPISELL    *a=(Mat_MPISELL*)A->data;

988:   if (A->rmap->n != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only works for square matrices");
989:   MatMissingDiagonal(a->A,missing,d);
990:   if (d) {
991:     PetscInt rstart;
992:     MatGetOwnershipRange(A,&rstart,NULL);
993:     *d += rstart;

995:   }
996:   return(0);
997: }

999: PetscErrorCode MatGetDiagonalBlock_MPISELL(Mat A,Mat *a)
1000: {
1002:   *a = ((Mat_MPISELL*)A->data)->A;
1003:   return(0);
1004: }

1006: /* -------------------------------------------------------------------*/
1007: static struct _MatOps MatOps_Values = {MatSetValues_MPISELL,
1008:                                        NULL,
1009:                                        NULL,
1010:                                        MatMult_MPISELL,
1011:                                 /* 4*/ MatMultAdd_MPISELL,
1012:                                        MatMultTranspose_MPISELL,
1013:                                        MatMultTransposeAdd_MPISELL,
1014:                                        NULL,
1015:                                        NULL,
1016:                                        NULL,
1017:                                 /*10*/ NULL,
1018:                                        NULL,
1019:                                        NULL,
1020:                                        MatSOR_MPISELL,
1021:                                        NULL,
1022:                                 /*15*/ MatGetInfo_MPISELL,
1023:                                        MatEqual_MPISELL,
1024:                                        MatGetDiagonal_MPISELL,
1025:                                        MatDiagonalScale_MPISELL,
1026:                                        NULL,
1027:                                 /*20*/ MatAssemblyBegin_MPISELL,
1028:                                        MatAssemblyEnd_MPISELL,
1029:                                        MatSetOption_MPISELL,
1030:                                        MatZeroEntries_MPISELL,
1031:                                 /*24*/ NULL,
1032:                                        NULL,
1033:                                        NULL,
1034:                                        NULL,
1035:                                        NULL,
1036:                                 /*29*/ MatSetUp_MPISELL,
1037:                                        NULL,
1038:                                        NULL,
1039:                                        MatGetDiagonalBlock_MPISELL,
1040:                                        NULL,
1041:                                 /*34*/ MatDuplicate_MPISELL,
1042:                                        NULL,
1043:                                        NULL,
1044:                                        NULL,
1045:                                        NULL,
1046:                                 /*39*/ NULL,
1047:                                        NULL,
1048:                                        NULL,
1049:                                        MatGetValues_MPISELL,
1050:                                        MatCopy_MPISELL,
1051:                                 /*44*/ NULL,
1052:                                        MatScale_MPISELL,
1053:                                        MatShift_MPISELL,
1054:                                        MatDiagonalSet_MPISELL,
1055:                                        NULL,
1056:                                 /*49*/ MatSetRandom_MPISELL,
1057:                                        NULL,
1058:                                        NULL,
1059:                                        NULL,
1060:                                        NULL,
1061:                                 /*54*/ MatFDColoringCreate_MPIXAIJ,
1062:                                        NULL,
1063:                                        MatSetUnfactored_MPISELL,
1064:                                        NULL,
1065:                                        NULL,
1066:                                 /*59*/ NULL,
1067:                                        MatDestroy_MPISELL,
1068:                                        MatView_MPISELL,
1069:                                        NULL,
1070:                                        NULL,
1071:                                 /*64*/ NULL,
1072:                                        NULL,
1073:                                        NULL,
1074:                                        NULL,
1075:                                        NULL,
1076:                                 /*69*/ NULL,
1077:                                        NULL,
1078:                                        NULL,
1079:                                        NULL,
1080:                                        NULL,
1081:                                        NULL,
1082:                                 /*75*/ MatFDColoringApply_AIJ, /* reuse AIJ function */
1083:                                        MatSetFromOptions_MPISELL,
1084:                                        NULL,
1085:                                        NULL,
1086:                                        NULL,
1087:                                 /*80*/ NULL,
1088:                                        NULL,
1089:                                        NULL,
1090:                                 /*83*/ NULL,
1091:                                        NULL,
1092:                                        NULL,
1093:                                        NULL,
1094:                                        NULL,
1095:                                        NULL,
1096:                                 /*89*/ NULL,
1097:                                        NULL,
1098:                                        NULL,
1099:                                        NULL,
1100:                                        NULL,
1101:                                 /*94*/ NULL,
1102:                                        NULL,
1103:                                        NULL,
1104:                                        NULL,
1105:                                        NULL,
1106:                                 /*99*/ NULL,
1107:                                        NULL,
1108:                                        NULL,
1109:                                        MatConjugate_MPISELL,
1110:                                        NULL,
1111:                                 /*104*/NULL,
1112:                                        MatRealPart_MPISELL,
1113:                                        MatImaginaryPart_MPISELL,
1114:                                        NULL,
1115:                                        NULL,
1116:                                 /*109*/NULL,
1117:                                        NULL,
1118:                                        NULL,
1119:                                        NULL,
1120:                                        MatMissingDiagonal_MPISELL,
1121:                                 /*114*/NULL,
1122:                                        NULL,
1123:                                        MatGetGhosts_MPISELL,
1124:                                        NULL,
1125:                                        NULL,
1126:                                 /*119*/NULL,
1127:                                        NULL,
1128:                                        NULL,
1129:                                        NULL,
1130:                                        NULL,
1131:                                 /*124*/NULL,
1132:                                        NULL,
1133:                                        MatInvertBlockDiagonal_MPISELL,
1134:                                        NULL,
1135:                                        NULL,
1136:                                 /*129*/NULL,
1137:                                        NULL,
1138:                                        NULL,
1139:                                        NULL,
1140:                                        NULL,
1141:                                 /*134*/NULL,
1142:                                        NULL,
1143:                                        NULL,
1144:                                        NULL,
1145:                                        NULL,
1146:                                 /*139*/NULL,
1147:                                        NULL,
1148:                                        NULL,
1149:                                        MatFDColoringSetUp_MPIXAIJ,
1150:                                        NULL,
1151:                                 /*144*/NULL
1152: };

1154: /* ----------------------------------------------------------------------------------------*/

1156: PetscErrorCode MatStoreValues_MPISELL(Mat mat)
1157: {
1158:   Mat_MPISELL    *sell=(Mat_MPISELL*)mat->data;

1162:   MatStoreValues(sell->A);
1163:   MatStoreValues(sell->B);
1164:   return(0);
1165: }

1167: PetscErrorCode MatRetrieveValues_MPISELL(Mat mat)
1168: {
1169:   Mat_MPISELL    *sell=(Mat_MPISELL*)mat->data;

1173:   MatRetrieveValues(sell->A);
1174:   MatRetrieveValues(sell->B);
1175:   return(0);
1176: }

1178: PetscErrorCode MatMPISELLSetPreallocation_MPISELL(Mat B,PetscInt d_rlenmax,const PetscInt d_rlen[],PetscInt o_rlenmax,const PetscInt o_rlen[])
1179: {
1180:   Mat_MPISELL    *b;

1184:   PetscLayoutSetUp(B->rmap);
1185:   PetscLayoutSetUp(B->cmap);
1186:   b = (Mat_MPISELL*)B->data;

1188:   if (!B->preallocated) {
1189:     /* Explicitly create 2 MATSEQSELL matrices. */
1190:     MatCreate(PETSC_COMM_SELF,&b->A);
1191:     MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);
1192:     MatSetBlockSizesFromMats(b->A,B,B);
1193:     MatSetType(b->A,MATSEQSELL);
1194:     PetscLogObjectParent((PetscObject)B,(PetscObject)b->A);
1195:     MatCreate(PETSC_COMM_SELF,&b->B);
1196:     MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);
1197:     MatSetBlockSizesFromMats(b->B,B,B);
1198:     MatSetType(b->B,MATSEQSELL);
1199:     PetscLogObjectParent((PetscObject)B,(PetscObject)b->B);
1200:   }

1202:   MatSeqSELLSetPreallocation(b->A,d_rlenmax,d_rlen);
1203:   MatSeqSELLSetPreallocation(b->B,o_rlenmax,o_rlen);
1204:   B->preallocated  = PETSC_TRUE;
1205:   B->was_assembled = PETSC_FALSE;
1206:   /*
1207:     critical for MatAssemblyEnd to work.
1208:     MatAssemblyBegin checks it to set up was_assembled
1209:     and MatAssemblyEnd checks was_assembled to determine whether to build garray
1210:   */
1211:   B->assembled     = PETSC_FALSE;
1212:   return(0);
1213: }

1215: PetscErrorCode MatDuplicate_MPISELL(Mat matin,MatDuplicateOption cpvalues,Mat *newmat)
1216: {
1217:   Mat            mat;
1218:   Mat_MPISELL    *a,*oldmat=(Mat_MPISELL*)matin->data;

1222:   *newmat = NULL;
1223:   MatCreate(PetscObjectComm((PetscObject)matin),&mat);
1224:   MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);
1225:   MatSetBlockSizesFromMats(mat,matin,matin);
1226:   MatSetType(mat,((PetscObject)matin)->type_name);
1227:   a       = (Mat_MPISELL*)mat->data;

1229:   mat->factortype   = matin->factortype;
1230:   mat->assembled    = PETSC_TRUE;
1231:   mat->insertmode   = NOT_SET_VALUES;
1232:   mat->preallocated = PETSC_TRUE;

1234:   a->size         = oldmat->size;
1235:   a->rank         = oldmat->rank;
1236:   a->donotstash   = oldmat->donotstash;
1237:   a->roworiented  = oldmat->roworiented;
1238:   a->rowindices   = NULL;
1239:   a->rowvalues    = NULL;
1240:   a->getrowactive = PETSC_FALSE;

1242:   PetscLayoutReference(matin->rmap,&mat->rmap);
1243:   PetscLayoutReference(matin->cmap,&mat->cmap);

1245:   if (oldmat->colmap) {
1246: #if defined(PETSC_USE_CTABLE)
1247:     PetscTableCreateCopy(oldmat->colmap,&a->colmap);
1248: #else
1249:     PetscMalloc1(mat->cmap->N,&a->colmap);
1250:     PetscLogObjectMemory((PetscObject)mat,(mat->cmap->N)*sizeof(PetscInt));
1251:     PetscArraycpy(a->colmap,oldmat->colmap,mat->cmap->N);
1252: #endif
1253:   } else a->colmap = NULL;
1254:   if (oldmat->garray) {
1255:     PetscInt len;
1256:     len  = oldmat->B->cmap->n;
1257:     PetscMalloc1(len+1,&a->garray);
1258:     PetscLogObjectMemory((PetscObject)mat,len*sizeof(PetscInt));
1259:     if (len) { PetscArraycpy(a->garray,oldmat->garray,len); }
1260:   } else a->garray = NULL;

1262:   VecDuplicate(oldmat->lvec,&a->lvec);
1263:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->lvec);
1264:   VecScatterCopy(oldmat->Mvctx,&a->Mvctx);
1265:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->Mvctx);
1266:   MatDuplicate(oldmat->A,cpvalues,&a->A);
1267:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->A);
1268:   MatDuplicate(oldmat->B,cpvalues,&a->B);
1269:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->B);
1270:   PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);
1271:   *newmat = mat;
1272:   return(0);
1273: }

1275: /*@C
1276:    MatMPISELLSetPreallocation - Preallocates memory for a sparse parallel matrix in sell format.
1277:    For good matrix assembly performance the user should preallocate the matrix storage by
1278:    setting the parameters d_nz (or d_nnz) and o_nz (or o_nnz).

1280:    Collective

1282:    Input Parameters:
1283: +  B - the matrix
1284: .  d_nz  - number of nonzeros per row in DIAGONAL portion of local submatrix
1285:            (same value is used for all local rows)
1286: .  d_nnz - array containing the number of nonzeros in the various rows of the
1287:            DIAGONAL portion of the local submatrix (possibly different for each row)
1288:            or NULL (PETSC_NULL_INTEGER in Fortran), if d_nz is used to specify the nonzero structure.
1289:            The size of this array is equal to the number of local rows, i.e 'm'.
1290:            For matrices that will be factored, you must leave room for (and set)
1291:            the diagonal entry even if it is zero.
1292: .  o_nz  - number of nonzeros per row in the OFF-DIAGONAL portion of local
1293:            submatrix (same value is used for all local rows).
1294: -  o_nnz - array containing the number of nonzeros in the various rows of the
1295:            OFF-DIAGONAL portion of the local submatrix (possibly different for
1296:            each row) or NULL (PETSC_NULL_INTEGER in Fortran), if o_nz is used to specify the nonzero
1297:            structure. The size of this array is equal to the number
1298:            of local rows, i.e 'm'.

1300:    If the *_nnz parameter is given then the *_nz parameter is ignored

1302:    The stored row and column indices begin with zero.

1304:    The parallel matrix is partitioned such that the first m0 rows belong to
1305:    process 0, the next m1 rows belong to process 1, the next m2 rows belong
1306:    to process 2 etc.. where m0,m1,m2... are the input parameter 'm'.

1308:    The DIAGONAL portion of the local submatrix of a processor can be defined
1309:    as the submatrix which is obtained by extraction the part corresponding to
1310:    the rows r1-r2 and columns c1-c2 of the global matrix, where r1 is the
1311:    first row that belongs to the processor, r2 is the last row belonging to
1312:    the this processor, and c1-c2 is range of indices of the local part of a
1313:    vector suitable for applying the matrix to.  This is an mxn matrix.  In the
1314:    common case of a square matrix, the row and column ranges are the same and
1315:    the DIAGONAL part is also square. The remaining portion of the local
1316:    submatrix (mxN) constitute the OFF-DIAGONAL portion.

1318:    If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored.

1320:    You can call MatGetInfo() to get information on how effective the preallocation was;
1321:    for example the fields mallocs,nz_allocated,nz_used,nz_unneeded;
1322:    You can also run with the option -info and look for messages with the string
1323:    malloc in them to see if additional memory allocation was needed.

1325:    Example usage:

1327:    Consider the following 8x8 matrix with 34 non-zero values, that is
1328:    assembled across 3 processors. Lets assume that proc0 owns 3 rows,
1329:    proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown
1330:    as follows:

1332: .vb
1333:             1  2  0  |  0  3  0  |  0  4
1334:     Proc0   0  5  6  |  7  0  0  |  8  0
1335:             9  0 10  | 11  0  0  | 12  0
1336:     -------------------------------------
1337:            13  0 14  | 15 16 17  |  0  0
1338:     Proc1   0 18  0  | 19 20 21  |  0  0
1339:             0  0  0  | 22 23  0  | 24  0
1340:     -------------------------------------
1341:     Proc2  25 26 27  |  0  0 28  | 29  0
1342:            30  0  0  | 31 32 33  |  0 34
1343: .ve

1345:    This can be represented as a collection of submatrices as:

1347: .vb
1348:       A B C
1349:       D E F
1350:       G H I
1351: .ve

1353:    Where the submatrices A,B,C are owned by proc0, D,E,F are
1354:    owned by proc1, G,H,I are owned by proc2.

1356:    The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively.
1357:    The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively.
1358:    The 'M','N' parameters are 8,8, and have the same values on all procs.

1360:    The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are
1361:    submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices
1362:    corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively.
1363:    Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL
1364:    part as SeqSELL matrices. for eg: proc1 will store [E] as a SeqSELL
1365:    matrix, ans [DF] as another SeqSELL matrix.

1367:    When d_nz, o_nz parameters are specified, d_nz storage elements are
1368:    allocated for every row of the local diagonal submatrix, and o_nz
1369:    storage locations are allocated for every row of the OFF-DIAGONAL submat.
1370:    One way to choose d_nz and o_nz is to use the max nonzerors per local
1371:    rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices.
1372:    In this case, the values of d_nz,o_nz are:
1373: .vb
1374:      proc0 : dnz = 2, o_nz = 2
1375:      proc1 : dnz = 3, o_nz = 2
1376:      proc2 : dnz = 1, o_nz = 4
1377: .ve
1378:    We are allocating m*(d_nz+o_nz) storage locations for every proc. This
1379:    translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10
1380:    for proc3. i.e we are using 12+15+10=37 storage locations to store
1381:    34 values.

1383:    When d_nnz, o_nnz parameters are specified, the storage is specified
1384:    for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices.
1385:    In the above case the values for d_nnz,o_nnz are:
1386: .vb
1387:      proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2]
1388:      proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1]
1389:      proc2: d_nnz = [1,1]   and o_nnz = [4,4]
1390: .ve
1391:    Here the space allocated is according to nz (or maximum values in the nnz
1392:    if nnz is provided) for DIAGONAL and OFF-DIAGONAL submatrices, i.e (2+2+3+2)*3+(1+4)*2=37

1394:    Level: intermediate

1396: .seealso: MatCreate(), MatCreateSeqSELL(), MatSetValues(), MatCreatesell(),
1397:           MATMPISELL, MatGetInfo(), PetscSplitOwnership()
1398: @*/
1399: PetscErrorCode MatMPISELLSetPreallocation(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[])
1400: {

1406:   PetscTryMethod(B,"MatMPISELLSetPreallocation_C",(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[]),(B,d_nz,d_nnz,o_nz,o_nnz));
1407:   return(0);
1408: }

1410: /*@C
1411:    MatCreateSELL - Creates a sparse parallel matrix in SELL format.

1413:    Collective

1415:    Input Parameters:
1416: +  comm - MPI communicator
1417: .  m - number of local rows (or PETSC_DECIDE to have calculated if M is given)
1418:            This value should be the same as the local size used in creating the
1419:            y vector for the matrix-vector product y = Ax.
1420: .  n - This value should be the same as the local size used in creating the
1421:        x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have
1422:        calculated if N is given) For square matrices n is almost always m.
1423: .  M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
1424: .  N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
1425: .  d_rlenmax - max number of nonzeros per row in DIAGONAL portion of local submatrix
1426:                (same value is used for all local rows)
1427: .  d_rlen - array containing the number of nonzeros in the various rows of the
1428:             DIAGONAL portion of the local submatrix (possibly different for each row)
1429:             or NULL, if d_rlenmax is used to specify the nonzero structure.
1430:             The size of this array is equal to the number of local rows, i.e 'm'.
1431: .  o_rlenmax - max number of nonzeros per row in the OFF-DIAGONAL portion of local
1432:                submatrix (same value is used for all local rows).
1433: -  o_rlen - array containing the number of nonzeros in the various rows of the
1434:             OFF-DIAGONAL portion of the local submatrix (possibly different for
1435:             each row) or NULL, if o_rlenmax is used to specify the nonzero
1436:             structure. The size of this array is equal to the number
1437:             of local rows, i.e 'm'.

1439:    Output Parameter:
1440: .  A - the matrix

1442:    It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(),
1443:    MatXXXXSetPreallocation() paradigm instead of this routine directly.
1444:    [MatXXXXSetPreallocation() is, for example, MatSeqSELLSetPreallocation]

1446:    Notes:
1447:    If the *_rlen parameter is given then the *_rlenmax parameter is ignored

1449:    m,n,M,N parameters specify the size of the matrix, and its partitioning across
1450:    processors, while d_rlenmax,d_rlen,o_rlenmax,o_rlen parameters specify the approximate
1451:    storage requirements for this matrix.

1453:    If PETSC_DECIDE or  PETSC_DETERMINE is used for a particular argument on one
1454:    processor than it must be used on all processors that share the object for
1455:    that argument.

1457:    The user MUST specify either the local or global matrix dimensions
1458:    (possibly both).

1460:    The parallel matrix is partitioned across processors such that the
1461:    first m0 rows belong to process 0, the next m1 rows belong to
1462:    process 1, the next m2 rows belong to process 2 etc.. where
1463:    m0,m1,m2,.. are the input parameter 'm'. i.e each processor stores
1464:    values corresponding to [m x N] submatrix.

1466:    The columns are logically partitioned with the n0 columns belonging
1467:    to 0th partition, the next n1 columns belonging to the next
1468:    partition etc.. where n0,n1,n2... are the input parameter 'n'.

1470:    The DIAGONAL portion of the local submatrix on any given processor
1471:    is the submatrix corresponding to the rows and columns m,n
1472:    corresponding to the given processor. i.e diagonal matrix on
1473:    process 0 is [m0 x n0], diagonal matrix on process 1 is [m1 x n1]
1474:    etc. The remaining portion of the local submatrix [m x (N-n)]
1475:    constitute the OFF-DIAGONAL portion. The example below better
1476:    illustrates this concept.

1478:    For a square global matrix we define each processor's diagonal portion
1479:    to be its local rows and the corresponding columns (a square submatrix);
1480:    each processor's off-diagonal portion encompasses the remainder of the
1481:    local matrix (a rectangular submatrix).

1483:    If o_rlen, d_rlen are specified, then o_rlenmax, and d_rlenmax are ignored.

1485:    When calling this routine with a single process communicator, a matrix of
1486:    type SEQSELL is returned.  If a matrix of type MATMPISELL is desired for this
1487:    type of communicator, use the construction mechanism:
1488:      MatCreate(...,&A); MatSetType(A,MATMPISELL); MatSetSizes(A, m,n,M,N); MatMPISELLSetPreallocation(A,...);

1490:    Options Database Keys:
1491: -  -mat_sell_oneindex - Internally use indexing starting at 1
1492:         rather than 0.  Note that when calling MatSetValues(),
1493:         the user still MUST index entries starting at 0!


1496:    Example usage:

1498:    Consider the following 8x8 matrix with 34 non-zero values, that is
1499:    assembled across 3 processors. Lets assume that proc0 owns 3 rows,
1500:    proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown
1501:    as follows:

1503: .vb
1504:             1  2  0  |  0  3  0  |  0  4
1505:     Proc0   0  5  6  |  7  0  0  |  8  0
1506:             9  0 10  | 11  0  0  | 12  0
1507:     -------------------------------------
1508:            13  0 14  | 15 16 17  |  0  0
1509:     Proc1   0 18  0  | 19 20 21  |  0  0
1510:             0  0  0  | 22 23  0  | 24  0
1511:     -------------------------------------
1512:     Proc2  25 26 27  |  0  0 28  | 29  0
1513:            30  0  0  | 31 32 33  |  0 34
1514: .ve

1516:    This can be represented as a collection of submatrices as:

1518: .vb
1519:       A B C
1520:       D E F
1521:       G H I
1522: .ve

1524:    Where the submatrices A,B,C are owned by proc0, D,E,F are
1525:    owned by proc1, G,H,I are owned by proc2.

1527:    The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively.
1528:    The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively.
1529:    The 'M','N' parameters are 8,8, and have the same values on all procs.

1531:    The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are
1532:    submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices
1533:    corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively.
1534:    Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL
1535:    part as SeqSELL matrices. for eg: proc1 will store [E] as a SeqSELL
1536:    matrix, ans [DF] as another SeqSELL matrix.

1538:    When d_rlenmax, o_rlenmax parameters are specified, d_rlenmax storage elements are
1539:    allocated for every row of the local diagonal submatrix, and o_rlenmax
1540:    storage locations are allocated for every row of the OFF-DIAGONAL submat.
1541:    One way to choose d_rlenmax and o_rlenmax is to use the max nonzerors per local
1542:    rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices.
1543:    In this case, the values of d_rlenmax,o_rlenmax are:
1544: .vb
1545:      proc0 : d_rlenmax = 2, o_rlenmax = 2
1546:      proc1 : d_rlenmax = 3, o_rlenmax = 2
1547:      proc2 : d_rlenmax = 1, o_rlenmax = 4
1548: .ve
1549:    We are allocating m*(d_rlenmax+o_rlenmax) storage locations for every proc. This
1550:    translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10
1551:    for proc3. i.e we are using 12+15+10=37 storage locations to store
1552:    34 values.

1554:    When d_rlen, o_rlen parameters are specified, the storage is specified
1555:    for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices.
1556:    In the above case the values for d_nnz,o_nnz are:
1557: .vb
1558:      proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2]
1559:      proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1]
1560:      proc2: d_nnz = [1,1]   and o_nnz = [4,4]
1561: .ve
1562:    Here the space allocated is still 37 though there are 34 nonzeros because
1563:    the allocation is always done according to rlenmax.

1565:    Level: intermediate

1567: .seealso: MatCreate(), MatCreateSeqSELL(), MatSetValues(), MatMPISELLSetPreallocation(), MatMPISELLSetPreallocationSELL(),
1568:           MATMPISELL, MatCreateMPISELLWithArrays()
1569: @*/
1570: PetscErrorCode MatCreateSELL(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,PetscInt d_rlenmax,const PetscInt d_rlen[],PetscInt o_rlenmax,const PetscInt o_rlen[],Mat *A)
1571: {
1573:   PetscMPIInt    size;

1576:   MatCreate(comm,A);
1577:   MatSetSizes(*A,m,n,M,N);
1578:   MPI_Comm_size(comm,&size);
1579:   if (size > 1) {
1580:     MatSetType(*A,MATMPISELL);
1581:     MatMPISELLSetPreallocation(*A,d_rlenmax,d_rlen,o_rlenmax,o_rlen);
1582:   } else {
1583:     MatSetType(*A,MATSEQSELL);
1584:     MatSeqSELLSetPreallocation(*A,d_rlenmax,d_rlen);
1585:   }
1586:   return(0);
1587: }

1589: PetscErrorCode MatMPISELLGetSeqSELL(Mat A,Mat *Ad,Mat *Ao,const PetscInt *colmap[])
1590: {
1591:   Mat_MPISELL    *a=(Mat_MPISELL*)A->data;
1592:   PetscBool      flg;

1596:   PetscObjectTypeCompare((PetscObject)A,MATMPISELL,&flg);
1597:   if (!flg) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"This function requires a MATMPISELL matrix as input");
1598:   if (Ad)     *Ad     = a->A;
1599:   if (Ao)     *Ao     = a->B;
1600:   if (colmap) *colmap = a->garray;
1601:   return(0);
1602: }

1604: /*@C
1605:      MatMPISELLGetLocalMatCondensed - Creates a SeqSELL matrix from an MATMPISELL matrix by taking all its local rows and NON-ZERO columns

1607:     Not Collective

1609:    Input Parameters:
1610: +    A - the matrix
1611: .    scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX
1612: -    row, col - index sets of rows and columns to extract (or NULL)

1614:    Output Parameter:
1615: .    A_loc - the local sequential matrix generated

1617:     Level: developer

1619: .seealso: MatGetOwnershipRange(), MatMPISELLGetLocalMat()

1621: @*/
1622: PetscErrorCode MatMPISELLGetLocalMatCondensed(Mat A,MatReuse scall,IS *row,IS *col,Mat *A_loc)
1623: {
1624:   Mat_MPISELL    *a=(Mat_MPISELL*)A->data;
1626:   PetscInt       i,start,end,ncols,nzA,nzB,*cmap,imark,*idx;
1627:   IS             isrowa,iscola;
1628:   Mat            *aloc;
1629:   PetscBool      match;

1632:   PetscObjectTypeCompare((PetscObject)A,MATMPISELL,&match);
1633:   if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MATMPISELL matrix as input");
1634:   PetscLogEventBegin(MAT_Getlocalmatcondensed,A,0,0,0);
1635:   if (!row) {
1636:     start = A->rmap->rstart; end = A->rmap->rend;
1637:     ISCreateStride(PETSC_COMM_SELF,end-start,start,1,&isrowa);
1638:   } else {
1639:     isrowa = *row;
1640:   }
1641:   if (!col) {
1642:     start = A->cmap->rstart;
1643:     cmap  = a->garray;
1644:     nzA   = a->A->cmap->n;
1645:     nzB   = a->B->cmap->n;
1646:     PetscMalloc1(nzA+nzB, &idx);
1647:     ncols = 0;
1648:     for (i=0; i<nzB; i++) {
1649:       if (cmap[i] < start) idx[ncols++] = cmap[i];
1650:       else break;
1651:     }
1652:     imark = i;
1653:     for (i=0; i<nzA; i++) idx[ncols++] = start + i;
1654:     for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i];
1655:     ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&iscola);
1656:   } else {
1657:     iscola = *col;
1658:   }
1659:   if (scall != MAT_INITIAL_MATRIX) {
1660:     PetscMalloc1(1,&aloc);
1661:     aloc[0] = *A_loc;
1662:   }
1663:   MatCreateSubMatrices(A,1,&isrowa,&iscola,scall,&aloc);
1664:   *A_loc = aloc[0];
1665:   PetscFree(aloc);
1666:   if (!row) {
1667:     ISDestroy(&isrowa);
1668:   }
1669:   if (!col) {
1670:     ISDestroy(&iscola);
1671:   }
1672:   PetscLogEventEnd(MAT_Getlocalmatcondensed,A,0,0,0);
1673:   return(0);
1674: }

1676: #include <../src/mat/impls/aij/mpi/mpiaij.h>

1678: PetscErrorCode MatConvert_MPISELL_MPIAIJ(Mat A,MatType newtype,MatReuse reuse,Mat *newmat)
1679: {
1681:   Mat_MPISELL    *a=(Mat_MPISELL*)A->data;
1682:   Mat            B;
1683:   Mat_MPIAIJ     *b;

1686:   if (!A->assembled) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Matrix must be assembled");

1688:   if (reuse == MAT_REUSE_MATRIX) {
1689:     B = *newmat;
1690:   } else {
1691:     MatCreate(PetscObjectComm((PetscObject)A),&B);
1692:     MatSetType(B,MATMPIAIJ);
1693:     MatSetSizes(B,A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N);
1694:     MatSetBlockSizes(B,A->rmap->bs,A->cmap->bs);
1695:     MatSeqAIJSetPreallocation(B,0,NULL);
1696:     MatMPIAIJSetPreallocation(B,0,NULL,0,NULL);
1697:   }
1698:   b    = (Mat_MPIAIJ*) B->data;

1700:   if (reuse == MAT_REUSE_MATRIX) {
1701:     MatConvert_SeqSELL_SeqAIJ(a->A, MATSEQAIJ, MAT_REUSE_MATRIX, &b->A);
1702:     MatConvert_SeqSELL_SeqAIJ(a->B, MATSEQAIJ, MAT_REUSE_MATRIX, &b->B);
1703:   } else {
1704:     MatDestroy(&b->A);
1705:     MatDestroy(&b->B);
1706:     MatDisAssemble_MPISELL(A);
1707:     MatConvert_SeqSELL_SeqAIJ(a->A, MATSEQAIJ, MAT_INITIAL_MATRIX, &b->A);
1708:     MatConvert_SeqSELL_SeqAIJ(a->B, MATSEQAIJ, MAT_INITIAL_MATRIX, &b->B);
1709:     MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
1710:     MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);
1711:     MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);
1712:     MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);
1713:   }

1715:   if (reuse == MAT_INPLACE_MATRIX) {
1716:     MatHeaderReplace(A,&B);
1717:   } else {
1718:     *newmat = B;
1719:   }
1720:   return(0);
1721: }

1723: PetscErrorCode MatConvert_MPIAIJ_MPISELL(Mat A,MatType newtype,MatReuse reuse,Mat *newmat)
1724: {
1726:   Mat_MPIAIJ     *a=(Mat_MPIAIJ*)A->data;
1727:   Mat            B;
1728:   Mat_MPISELL    *b;

1731:   if (!A->assembled) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Matrix must be assembled");

1733:   if (reuse == MAT_REUSE_MATRIX) {
1734:     B = *newmat;
1735:   } else {
1736:     MatCreate(PetscObjectComm((PetscObject)A),&B);
1737:     MatSetType(B,MATMPISELL);
1738:     MatSetSizes(B,A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N);
1739:     MatSetBlockSizes(B,A->rmap->bs,A->cmap->bs);
1740:     MatSeqAIJSetPreallocation(B,0,NULL);
1741:     MatMPIAIJSetPreallocation(B,0,NULL,0,NULL);
1742:   }
1743:   b    = (Mat_MPISELL*) B->data;

1745:   if (reuse == MAT_REUSE_MATRIX) {
1746:     MatConvert_SeqAIJ_SeqSELL(a->A, MATSEQSELL, MAT_REUSE_MATRIX, &b->A);
1747:     MatConvert_SeqAIJ_SeqSELL(a->B, MATSEQSELL, MAT_REUSE_MATRIX, &b->B);
1748:   } else {
1749:     MatDestroy(&b->A);
1750:     MatDestroy(&b->B);
1751:     MatDisAssemble_MPIAIJ(A);
1752:     MatConvert_SeqAIJ_SeqSELL(a->A, MATSEQSELL, MAT_INITIAL_MATRIX, &b->A);
1753:     MatConvert_SeqAIJ_SeqSELL(a->B, MATSEQSELL, MAT_INITIAL_MATRIX, &b->B);
1754:     MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
1755:     MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);
1756:     MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);
1757:     MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);
1758:   }

1760:   if (reuse == MAT_INPLACE_MATRIX) {
1761:     MatHeaderReplace(A,&B);
1762:   } else {
1763:     *newmat = B;
1764:   }
1765:   return(0);
1766: }

1768: PetscErrorCode MatSOR_MPISELL(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx)
1769: {
1770:   Mat_MPISELL    *mat=(Mat_MPISELL*)matin->data;
1772:   Vec            bb1=NULL;

1775:   if (flag == SOR_APPLY_UPPER) {
1776:     (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
1777:     return(0);
1778:   }

1780:   if (its > 1 || ~flag & SOR_ZERO_INITIAL_GUESS || flag & SOR_EISENSTAT) {
1781:     VecDuplicate(bb,&bb1);
1782:   }

1784:   if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) {
1785:     if (flag & SOR_ZERO_INITIAL_GUESS) {
1786:       (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
1787:       its--;
1788:     }

1790:     while (its--) {
1791:       VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
1792:       VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);

1794:       /* update rhs: bb1 = bb - B*x */
1795:       VecScale(mat->lvec,-1.0);
1796:       (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);

1798:       /* local sweep */
1799:       (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,1,xx);
1800:     }
1801:   } else if (flag & SOR_LOCAL_FORWARD_SWEEP) {
1802:     if (flag & SOR_ZERO_INITIAL_GUESS) {
1803:       (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
1804:       its--;
1805:     }
1806:     while (its--) {
1807:       VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
1808:       VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);

1810:       /* update rhs: bb1 = bb - B*x */
1811:       VecScale(mat->lvec,-1.0);
1812:       (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);

1814:       /* local sweep */
1815:       (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_FORWARD_SWEEP,fshift,lits,1,xx);
1816:     }
1817:   } else if (flag & SOR_LOCAL_BACKWARD_SWEEP) {
1818:     if (flag & SOR_ZERO_INITIAL_GUESS) {
1819:       (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
1820:       its--;
1821:     }
1822:     while (its--) {
1823:       VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
1824:       VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);

1826:       /* update rhs: bb1 = bb - B*x */
1827:       VecScale(mat->lvec,-1.0);
1828:       (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);

1830:       /* local sweep */
1831:       (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_BACKWARD_SWEEP,fshift,lits,1,xx);
1832:     }
1833:   } else SETERRQ(PetscObjectComm((PetscObject)matin),PETSC_ERR_SUP,"Parallel SOR not supported");

1835:   VecDestroy(&bb1);

1837:   matin->factorerrortype = mat->A->factorerrortype;
1838:   return(0);
1839: }

1841: /*MC
1842:    MATMPISELL - MATMPISELL = "MPISELL" - A matrix type to be used for parallel sparse matrices.

1844:    Options Database Keys:
1845: . -mat_type MPISELL - sets the matrix type to "MPISELL" during a call to MatSetFromOptions()

1847:   Level: beginner

1849: .seealso: MatCreateSELL()
1850: M*/
1851: PETSC_EXTERN PetscErrorCode MatCreate_MPISELL(Mat B)
1852: {
1853:   Mat_MPISELL    *b;
1855:   PetscMPIInt    size;

1858:   MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);
1859:   PetscNewLog(B,&b);
1860:   B->data       = (void*)b;
1861:   PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));
1862:   B->assembled  = PETSC_FALSE;
1863:   B->insertmode = NOT_SET_VALUES;
1864:   b->size       = size;
1865:   MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);
1866:   /* build cache for off array entries formed */
1867:   MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);

1869:   b->donotstash  = PETSC_FALSE;
1870:   b->colmap      = NULL;
1871:   b->garray      = NULL;
1872:   b->roworiented = PETSC_TRUE;

1874:   /* stuff used for matrix vector multiply */
1875:   b->lvec  = NULL;
1876:   b->Mvctx = NULL;

1878:   /* stuff for MatGetRow() */
1879:   b->rowindices   = NULL;
1880:   b->rowvalues    = NULL;
1881:   b->getrowactive = PETSC_FALSE;

1883:   PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPISELL);
1884:   PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPISELL);
1885:   PetscObjectComposeFunction((PetscObject)B,"MatIsTranspose_C",MatIsTranspose_MPISELL);
1886:   PetscObjectComposeFunction((PetscObject)B,"MatMPISELLSetPreallocation_C",MatMPISELLSetPreallocation_MPISELL);
1887:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpisell_mpiaij_C",MatConvert_MPISELL_MPIAIJ);
1888:   PetscObjectComposeFunction((PetscObject)B,"MatDiagonalScaleLocal_C",MatDiagonalScaleLocal_MPISELL);
1889:   PetscObjectChangeTypeName((PetscObject)B,MATMPISELL);
1890:   return(0);
1891: }