Actual source code: mpisell.c

petsc-3.10.2 2018-10-09
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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:   Developer Notes:
 21:     Subclasses include MATSELLCUSP, MATSELLCUSPARSE, MATSELLPERM, MATSELLCRL, and also automatically switches over to use inodes when
 22:    enough exist.

 24:   Level: beginner

 26: .seealso: MatCreateSELL(), MatCreateSeqSELL(), MATSEQSELL, MATMPISELL
 27: M*/

 29: PetscErrorCode MatDiagonalSet_MPISELL(Mat Y,Vec D,InsertMode is)
 30: {
 32:   Mat_MPISELL    *sell=(Mat_MPISELL*)Y->data;

 35:   if (Y->assembled && Y->rmap->rstart == Y->cmap->rstart && Y->rmap->rend == Y->cmap->rend) {
 36:     MatDiagonalSet(sell->A,D,is);
 37:   } else {
 38:     MatDiagonalSet_Default(Y,D,is);
 39:   }
 40:   return(0);
 41: }

 43: /*
 44:   Local utility routine that creates a mapping from the global column
 45: number to the local number in the off-diagonal part of the local
 46: storage of the matrix.  When PETSC_USE_CTABLE is used this is scalable at
 47: a slightly higher hash table cost; without it it is not scalable (each processor
 48: has an order N integer array but is fast to acess.
 49: */
 50: PetscErrorCode MatCreateColmap_MPISELL_Private(Mat mat)
 51: {
 52:   Mat_MPISELL    *sell=(Mat_MPISELL*)mat->data;
 54:   PetscInt       n=sell->B->cmap->n,i;

 57:   if (!sell->garray) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"MPISELL Matrix was assembled but is missing garray");
 58: #if defined(PETSC_USE_CTABLE)
 59:   PetscTableCreate(n,mat->cmap->N+1,&sell->colmap);
 60:   for (i=0; i<n; i++) {
 61:     PetscTableAdd(sell->colmap,sell->garray[i]+1,i+1,INSERT_VALUES);
 62:   }
 63: #else
 64:   PetscCalloc1(mat->cmap->N+1,&sell->colmap);
 65:   PetscLogObjectMemory((PetscObject)mat,(mat->cmap->N+1)*sizeof(PetscInt));
 66:   for (i=0; i<n; i++) sell->colmap[sell->garray[i]] = i+1;
 67: #endif
 68:   return(0);
 69: }

 71: #define MatSetValues_SeqSELL_A_Private(row,col,value,addv,orow,ocol) \
 72:   { \
 73:     if (col <= lastcol1) low1 = 0; \
 74:     else                high1 = nrow1; \
 75:     lastcol1 = col; \
 76:     while (high1-low1 > 5) { \
 77:       t = (low1+high1)/2; \
 78:       if (*(cp1+8*t) > col) high1 = t; \
 79:       else                   low1 = t; \
 80:     } \
 81:     for (_i=low1; _i<high1; _i++) { \
 82:       if (*(cp1+8*_i) > col) break; \
 83:       if (*(cp1+8*_i) == col) { \
 84:         if (addv == ADD_VALUES) *(vp1+8*_i) += value;   \
 85:         else                     *(vp1+8*_i) = value; \
 86:         goto a_noinsert; \
 87:       } \
 88:     }  \
 89:     if (value == 0.0 && ignorezeroentries) {low1 = 0; high1 = nrow1;goto a_noinsert;} \
 90:     if (nonew == 1) {low1 = 0; high1 = nrow1; goto a_noinsert;} \
 91:     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); \
 92:     MatSeqXSELLReallocateSELL(A,am,1,nrow1,a->sliidx,row/8,row,col,a->colidx,a->val,cp1,vp1,nonew,MatScalar); \
 93:     /* shift up all the later entries in this row */ \
 94:     for (ii=nrow1-1; ii>=_i; ii--) { \
 95:       *(cp1+8*(ii+1)) = *(cp1+8*ii); \
 96:       *(vp1+8*(ii+1)) = *(vp1+8*ii); \
 97:     } \
 98:     *(cp1+8*_i) = col; \
 99:     *(vp1+8*_i) = value; \
100:     a->nz++; nrow1++; A->nonzerostate++; \
101:     a_noinsert: ; \
102:     a->rlen[row] = nrow1; \
103:   }

105: #define MatSetValues_SeqSELL_B_Private(row,col,value,addv,orow,ocol) \
106:   { \
107:     if (col <= lastcol2) low2 = 0; \
108:     else                high2 = nrow2; \
109:     lastcol2 = col; \
110:     while (high2-low2 > 5) { \
111:       t = (low2+high2)/2; \
112:       if (*(cp2+8*t) > col) high2 = t; \
113:       else low2  = t; \
114:     } \
115:     for (_i=low2; _i<high2; _i++) { \
116:       if (*(cp2+8*_i) > col) break; \
117:       if (*(cp2+8*_i) == col) { \
118:         if (addv == ADD_VALUES) *(vp2+8*_i) += value; \
119:         else                     *(vp2+8*_i) = value; \
120:         goto b_noinsert; \
121:       } \
122:     } \
123:     if (value == 0.0 && ignorezeroentries) {low2 = 0; high2 = nrow2; goto b_noinsert;} \
124:     if (nonew == 1) {low2 = 0; high2 = nrow2; goto b_noinsert;} \
125:     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); \
126:     MatSeqXSELLReallocateSELL(B,bm,1,nrow2,b->sliidx,row/8,row,col,b->colidx,b->val,cp2,vp2,nonew,MatScalar); \
127:     /* shift up all the later entries in this row */ \
128:     for (ii=nrow2-1; ii>=_i; ii--) { \
129:       *(cp2+8*(ii+1)) = *(cp2+8*ii); \
130:       *(vp2+8*(ii+1)) = *(vp2+8*ii); \
131:     } \
132:     *(cp2+8*_i) = col; \
133:     *(vp2+8*_i) = value; \
134:     b->nz++; nrow2++; B->nonzerostate++; \
135:     b_noinsert: ; \
136:     b->rlen[row] = nrow2; \
137:   }

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

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

158:   for (i=0; i<m; i++) {
159:     if (im[i] < 0) continue;
160: #if defined(PETSC_USE_DEBUG)
161:     if (im[i] >= mat->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],mat->rmap->N-1);
162: #endif
163:     if (im[i] >= rstart && im[i] < rend) {
164:       row      = im[i] - rstart;
165:       lastcol1 = -1;
166:       shift1   = a->sliidx[row>>3]+(row&0x07); /* starting index of the row */
167:       cp1      = a->colidx+shift1;
168:       vp1      = a->val+shift1;
169:       nrow1    = a->rlen[row];
170:       low1     = 0;
171:       high1    = nrow1;
172:       lastcol2 = -1;
173:       shift2   = b->sliidx[row>>3]+(row&0x07); /* starting index of the row */
174:       cp2      = b->colidx+shift2;
175:       vp2      = b->val+shift2;
176:       nrow2    = b->rlen[row];
177:       low2     = 0;
178:       high2    = nrow2;

180:       for (j=0; j<n; j++) {
181:         if (roworiented) value = v[i*n+j];
182:         else             value = v[i+j*m];
183:         if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES)) continue;
184:         if (in[j] >= cstart && in[j] < cend) {
185:           col   = in[j] - cstart;
186:           MatSetValue_SeqSELL_Private(A,row,col,value,addv,im[i],in[j],cp1,vp1,lastcol1,low1,high1); /* set one value */
187:         } else if (in[j] < 0) continue;
188: #if defined(PETSC_USE_DEBUG)
189:         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);
190: #endif
191:         else {
192:           if (mat->was_assembled) {
193:             if (!sell->colmap) {
194:               MatCreateColmap_MPISELL_Private(mat);
195:             }
196: #if defined(PETSC_USE_CTABLE)
197:             PetscTableFind(sell->colmap,in[j]+1,&col);
198:             col--;
199: #else
200:             col = sell->colmap[in[j]] - 1;
201: #endif
202:             if (col < 0 && !((Mat_SeqSELL*)(sell->B->data))->nonew) {
203:               MatDisAssemble_MPISELL(mat);
204:               col    = in[j];
205:               /* Reinitialize the variables required by MatSetValues_SeqSELL_B_Private() */
206:               B      = sell->B;
207:               b      = (Mat_SeqSELL*)B->data;
208:               shift2 = b->sliidx[row>>3]+(row&0x07); /* starting index of the row */
209:               cp2    = b->colidx+shift2;
210:               vp2    = b->val+shift2;
211:               nrow2  = b->rlen[row];
212:               low2   = 0;
213:               high2  = nrow2;
214:             } 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]);
215:           } else col = in[j];
216:           MatSetValue_SeqSELL_Private(B,row,col,value,addv,im[i],in[j],cp2,vp2,lastcol2,low2,high2); /* set one value */
217:         }
218:       }
219:     } else {
220:       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]);
221:       if (!sell->donotstash) {
222:         mat->assembled = PETSC_FALSE;
223:         if (roworiented) {
224:           MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));
225:         } else {
226:           MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));
227:         }
228:       }
229:     }
230:   }
231:   return(0);
232: }

234: PetscErrorCode MatGetValues_MPISELL(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[])
235: {
236:   Mat_MPISELL    *sell=(Mat_MPISELL*)mat->data;
238:   PetscInt       i,j,rstart=mat->rmap->rstart,rend=mat->rmap->rend;
239:   PetscInt       cstart=mat->cmap->rstart,cend=mat->cmap->rend,row,col;

242:   for (i=0; i<m; i++) {
243:     if (idxm[i] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",idxm[i]);*/
244:     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);
245:     if (idxm[i] >= rstart && idxm[i] < rend) {
246:       row = idxm[i] - rstart;
247:       for (j=0; j<n; j++) {
248:         if (idxn[j] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column: %D",idxn[j]); */
249:         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);
250:         if (idxn[j] >= cstart && idxn[j] < cend) {
251:           col  = idxn[j] - cstart;
252:           MatGetValues(sell->A,1,&row,1,&col,v+i*n+j);
253:         } else {
254:           if (!sell->colmap) {
255:             MatCreateColmap_MPISELL_Private(mat);
256:           }
257: #if defined(PETSC_USE_CTABLE)
258:           PetscTableFind(sell->colmap,idxn[j]+1,&col);
259:           col--;
260: #else
261:           col = sell->colmap[idxn[j]] - 1;
262: #endif
263:           if ((col < 0) || (sell->garray[col] != idxn[j])) *(v+i*n+j) = 0.0;
264:           else {
265:             MatGetValues(sell->B,1,&row,1,&col,v+i*n+j);
266:           }
267:         }
268:       }
269:     } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local values currently supported");
270:   }
271:   return(0);
272: }

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

276: PetscErrorCode MatAssemblyBegin_MPISELL(Mat mat,MatAssemblyType mode)
277: {
278:   Mat_MPISELL    *sell=(Mat_MPISELL*)mat->data;
280:   PetscInt       nstash,reallocs;

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

285:   MatStashScatterBegin_Private(mat,&mat->stash,mat->rmap->range);
286:   MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);
287:   PetscInfo2(sell->A,"Stash has %D entries, uses %D mallocs.\n",nstash,reallocs);
288:   return(0);
289: }

291: PetscErrorCode MatAssemblyEnd_MPISELL(Mat mat,MatAssemblyType mode)
292: {
293:   Mat_MPISELL    *sell=(Mat_MPISELL*)mat->data;
295:   PetscMPIInt    n;
296:   PetscInt       i,flg;
297:   PetscInt       *row,*col;
298:   PetscScalar    *val;
299:   PetscBool      other_disassembled;
300:   /* do not use 'b = (Mat_SeqSELL*)sell->B->data' as B can be reset in disassembly */
302:   if (!sell->donotstash && !mat->nooffprocentries) {
303:     while (1) {
304:       MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);
305:       if (!flg) break;

307:       for (i=0; i<n; i++) { /* assemble one by one */
308:         MatSetValues_MPISELL(mat,1,row+i,1,col+i,val+i,mat->insertmode);
309:       }
310:     }
311:     MatStashScatterEnd_Private(&mat->stash);
312:   }
313:   MatAssemblyBegin(sell->A,mode);
314:   MatAssemblyEnd(sell->A,mode);

316:   /*
317:      determine if any processor has disassembled, if so we must
318:      also disassemble ourselfs, in order that we may reassemble.
319:   */
320:   /*
321:      if nonzero structure of submatrix B cannot change then we know that
322:      no processor disassembled thus we can skip this stuff
323:   */
324:   if (!((Mat_SeqSELL*)sell->B->data)->nonew) {
325:     MPIU_Allreduce(&mat->was_assembled,&other_disassembled,1,MPIU_BOOL,MPI_PROD,PetscObjectComm((PetscObject)mat));
326:     if (mat->was_assembled && !other_disassembled) {
327:       SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"MatDisAssemble not implemented yet\n");
328:       MatDisAssemble_MPISELL(mat);
329:     }
330:   }
331:   if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) {
332:     MatSetUpMultiply_MPISELL(mat);
333:   }
334:   /*
335:   MatSetOption(sell->B,MAT_USE_INODES,PETSC_FALSE);
336:   */
337:   MatAssemblyBegin(sell->B,mode);
338:   MatAssemblyEnd(sell->B,mode);
339:   PetscFree2(sell->rowvalues,sell->rowindices);
340:   sell->rowvalues = 0;
341:   VecDestroy(&sell->diag);

343:   /* if no new nonzero locations are allowed in matrix then only set the matrix state the first time through */
344:   if ((!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) || !((Mat_SeqSELL*)(sell->A->data))->nonew) {
345:     PetscObjectState state = sell->A->nonzerostate + sell->B->nonzerostate;
346:     MPIU_Allreduce(&state,&mat->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)mat));
347:   }
348:   return(0);
349: }

351: PetscErrorCode MatZeroEntries_MPISELL(Mat A)
352: {
353:   Mat_MPISELL    *l=(Mat_MPISELL*)A->data;

357:   MatZeroEntries(l->A);
358:   MatZeroEntries(l->B);
359:   return(0);
360: }

362: PetscErrorCode MatMult_MPISELL(Mat A,Vec xx,Vec yy)
363: {
364:   Mat_MPISELL    *a=(Mat_MPISELL*)A->data;
366:   PetscInt       nt;

369:   VecGetLocalSize(xx,&nt);
370:   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);
371:   VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
372:   (*a->A->ops->mult)(a->A,xx,yy);
373:   VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
374:   (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);
375:   return(0);
376: }

378: PetscErrorCode MatMultDiagonalBlock_MPISELL(Mat A,Vec bb,Vec xx)
379: {
380:   Mat_MPISELL    *a=(Mat_MPISELL*)A->data;

384:   MatMultDiagonalBlock(a->A,bb,xx);
385:   return(0);
386: }

388: PetscErrorCode MatMultAdd_MPISELL(Mat A,Vec xx,Vec yy,Vec zz)
389: {
390:   Mat_MPISELL    *a=(Mat_MPISELL*)A->data;

394:   VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
395:   (*a->A->ops->multadd)(a->A,xx,yy,zz);
396:   VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
397:   (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);
398:   return(0);
399: }

401: PetscErrorCode MatMultTranspose_MPISELL(Mat A,Vec xx,Vec yy)
402: {
403:   Mat_MPISELL    *a=(Mat_MPISELL*)A->data;
405:   PetscBool      merged;

408:   VecScatterGetMerged(a->Mvctx,&merged);
409:   /* do nondiagonal part */
410:   (*a->B->ops->multtranspose)(a->B,xx,a->lvec);
411:   if (!merged) {
412:     /* send it on its way */
413:     VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
414:     /* do local part */
415:     (*a->A->ops->multtranspose)(a->A,xx,yy);
416:     /* receive remote parts: note this assumes the values are not actually */
417:     /* added in yy until the next line, */
418:     VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
419:   } else {
420:     /* do local part */
421:     (*a->A->ops->multtranspose)(a->A,xx,yy);
422:     /* send it on its way */
423:     VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
424:     /* values actually were received in the Begin() but we need to call this nop */
425:     VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
426:   }
427:   return(0);
428: }

430: PetscErrorCode MatIsTranspose_MPISELL(Mat Amat,Mat Bmat,PetscReal tol,PetscBool *f)
431: {
432:   MPI_Comm       comm;
433:   Mat_MPISELL    *Asell=(Mat_MPISELL*)Amat->data,*Bsell;
434:   Mat            Adia=Asell->A,Bdia,Aoff,Boff,*Aoffs,*Boffs;
435:   IS             Me,Notme;
437:   PetscInt       M,N,first,last,*notme,i;
438:   PetscMPIInt    size;

441:   /* Easy test: symmetric diagonal block */
442:   Bsell = (Mat_MPISELL*)Bmat->data; Bdia = Bsell->A;
443:   MatIsTranspose(Adia,Bdia,tol,f);
444:   if (!*f) return(0);
445:   PetscObjectGetComm((PetscObject)Amat,&comm);
446:   MPI_Comm_size(comm,&size);
447:   if (size == 1) return(0);

449:   /* Hard test: off-diagonal block. This takes a MatCreateSubMatrix. */
450:   MatGetSize(Amat,&M,&N);
451:   MatGetOwnershipRange(Amat,&first,&last);
452:   PetscMalloc1(N-last+first,&notme);
453:   for (i=0; i<first; i++) notme[i] = i;
454:   for (i=last; i<M; i++) notme[i-last+first] = i;
455:   ISCreateGeneral(MPI_COMM_SELF,N-last+first,notme,PETSC_COPY_VALUES,&Notme);
456:   ISCreateStride(MPI_COMM_SELF,last-first,first,1,&Me);
457:   MatCreateSubMatrices(Amat,1,&Me,&Notme,MAT_INITIAL_MATRIX,&Aoffs);
458:   Aoff = Aoffs[0];
459:   MatCreateSubMatrices(Bmat,1,&Notme,&Me,MAT_INITIAL_MATRIX,&Boffs);
460:   Boff = Boffs[0];
461:   MatIsTranspose(Aoff,Boff,tol,f);
462:   MatDestroyMatrices(1,&Aoffs);
463:   MatDestroyMatrices(1,&Boffs);
464:   ISDestroy(&Me);
465:   ISDestroy(&Notme);
466:   PetscFree(notme);
467:   return(0);
468: }

470: PetscErrorCode MatMultTransposeAdd_MPISELL(Mat A,Vec xx,Vec yy,Vec zz)
471: {
472:   Mat_MPISELL    *a=(Mat_MPISELL*)A->data;

476:   /* do nondiagonal part */
477:   (*a->B->ops->multtranspose)(a->B,xx,a->lvec);
478:   /* send it on its way */
479:   VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);
480:   /* do local part */
481:   (*a->A->ops->multtransposeadd)(a->A,xx,yy,zz);
482:   /* receive remote parts */
483:   VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);
484:   return(0);
485: }

487: /*
488:   This only works correctly for square matrices where the subblock A->A is the
489:    diagonal block
490: */
491: PetscErrorCode MatGetDiagonal_MPISELL(Mat A,Vec v)
492: {
494:   Mat_MPISELL    *a=(Mat_MPISELL*)A->data;

497:   if (A->rmap->N != A->cmap->N) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block");
498:   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");
499:   MatGetDiagonal(a->A,v);
500:   return(0);
501: }

503: PetscErrorCode MatScale_MPISELL(Mat A,PetscScalar aa)
504: {
505:   Mat_MPISELL    *a=(Mat_MPISELL*)A->data;

509:   MatScale(a->A,aa);
510:   MatScale(a->B,aa);
511:   return(0);
512: }

514: PetscErrorCode MatDestroy_MPISELL(Mat mat)
515: {
516:   Mat_MPISELL    *sell=(Mat_MPISELL*)mat->data;

520: #if defined(PETSC_USE_LOG)
521:   PetscLogObjectState((PetscObject)mat,"Rows=%D, Cols=%D",mat->rmap->N,mat->cmap->N);
522: #endif
523:   MatStashDestroy_Private(&mat->stash);
524:   VecDestroy(&sell->diag);
525:   MatDestroy(&sell->A);
526:   MatDestroy(&sell->B);
527: #if defined(PETSC_USE_CTABLE)
528:   PetscTableDestroy(&sell->colmap);
529: #else
530:   PetscFree(sell->colmap);
531: #endif
532:   PetscFree(sell->garray);
533:   VecDestroy(&sell->lvec);
534:   VecScatterDestroy(&sell->Mvctx);
535:   PetscFree2(sell->rowvalues,sell->rowindices);
536:   PetscFree(sell->ld);
537:   PetscFree(mat->data);

539:   PetscObjectChangeTypeName((PetscObject)mat,0);
540:   PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C",NULL);
541:   PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C",NULL);
542:   PetscObjectComposeFunction((PetscObject)mat,"MatIsTranspose_C",NULL);
543:   PetscObjectComposeFunction((PetscObject)mat,"MatMPISELLSetPreallocation_C",NULL);
544:   PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpisell_mpiaij_C",NULL);
545:   PetscObjectComposeFunction((PetscObject)mat,"MatDiagonalScaleLocal_C",NULL);
546:   return(0);
547: }

549:  #include <petscdraw.h>
550: PetscErrorCode MatView_MPISELL_ASCIIorDraworSocket(Mat mat,PetscViewer viewer)
551: {
552:   Mat_MPISELL       *sell=(Mat_MPISELL*)mat->data;
553:   PetscErrorCode    ierr;
554:   PetscMPIInt       rank=sell->rank,size=sell->size;
555:   PetscBool         isdraw,iascii,isbinary;
556:   PetscViewer       sviewer;
557:   PetscViewerFormat format;

560:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);
561:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
562:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);
563:   if (iascii) {
564:     PetscViewerGetFormat(viewer,&format);
565:     if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) {
566:       MatInfo   info;
567:       PetscBool inodes;

569:       MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);
570:       MatGetInfo(mat,MAT_LOCAL,&info);
571:       MatInodeGetInodeSizes(sell->A,NULL,(PetscInt**)&inodes,NULL);
572:       PetscViewerASCIIPushSynchronized(viewer);
573:       if (!inodes) {
574:         PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D mem %D, not using I-node routines\n",
575:                                                   rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(PetscInt)info.memory);
576:       } else {
577:         PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D mem %D, using I-node routines\n",
578:                                                   rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(PetscInt)info.memory);
579:       }
580:       MatGetInfo(sell->A,MAT_LOCAL,&info);
581:       PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);
582:       MatGetInfo(sell->B,MAT_LOCAL,&info);
583:       PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);
584:       PetscViewerFlush(viewer);
585:       PetscViewerASCIIPopSynchronized(viewer);
586:       PetscViewerASCIIPrintf(viewer,"Information on VecScatter used in matrix-vector product: \n");
587:       VecScatterView(sell->Mvctx,viewer);
588:       return(0);
589:     } else if (format == PETSC_VIEWER_ASCII_INFO) {
590:       PetscInt inodecount,inodelimit,*inodes;
591:       MatInodeGetInodeSizes(sell->A,&inodecount,&inodes,&inodelimit);
592:       if (inodes) {
593:         PetscViewerASCIIPrintf(viewer,"using I-node (on process 0) routines: found %D nodes, limit used is %D\n",inodecount,inodelimit);
594:       } else {
595:         PetscViewerASCIIPrintf(viewer,"not using I-node (on process 0) routines\n");
596:       }
597:       return(0);
598:     } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) {
599:       return(0);
600:     }
601:   } else if (isbinary) {
602:     if (size == 1) {
603:       PetscObjectSetName((PetscObject)sell->A,((PetscObject)mat)->name);
604:       MatView(sell->A,viewer);
605:     } else {
606:       /* MatView_MPISELL_Binary(mat,viewer); */
607:     }
608:     return(0);
609:   } else if (isdraw) {
610:     PetscDraw draw;
611:     PetscBool isnull;
612:     PetscViewerDrawGetDraw(viewer,0,&draw);
613:     PetscDrawIsNull(draw,&isnull);
614:     if (isnull) return(0);
615:   }

617:   {
618:     /* assemble the entire matrix onto first processor. */
619:     Mat         A;
620:     Mat_SeqSELL *Aloc;
621:     PetscInt    M=mat->rmap->N,N=mat->cmap->N,*acolidx,row,col,i,j;
622:     MatScalar   *aval;
623:     PetscBool   isnonzero;

625:     MatCreate(PetscObjectComm((PetscObject)mat),&A);
626:     if (!rank) {
627:       MatSetSizes(A,M,N,M,N);
628:     } else {
629:       MatSetSizes(A,0,0,M,N);
630:     }
631:     /* This is just a temporary matrix, so explicitly using MATMPISELL is probably best */
632:     MatSetType(A,MATMPISELL);
633:     MatMPISELLSetPreallocation(A,0,NULL,0,NULL);
634:     MatSetOption(A,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_FALSE);
635:     PetscLogObjectParent((PetscObject)mat,(PetscObject)A);

637:     /* copy over the A part */
638:     Aloc = (Mat_SeqSELL*)sell->A->data;
639:     acolidx = Aloc->colidx; aval = Aloc->val;
640:     for (i=0; i<Aloc->totalslices; i++) { /* loop over slices */
641:       for (j=Aloc->sliidx[i]; j<Aloc->sliidx[i+1]; j++) {
642:         isnonzero = (PetscBool)((j-Aloc->sliidx[i])/8 < Aloc->rlen[(i<<3)+(j&0x07)]);
643:         if (isnonzero) { /* check the mask bit */
644:           row  = (i<<3)+(j&0x07) + mat->rmap->rstart; /* i<<3 is the starting row of this slice */
645:           col  = *acolidx + mat->rmap->rstart;
646:           MatSetValues(A,1,&row,1,&col,aval,INSERT_VALUES);
647:         }
648:         aval++; acolidx++;
649:       }
650:     }

652:     /* copy over the B part */
653:     Aloc = (Mat_SeqSELL*)sell->B->data;
654:     acolidx = Aloc->colidx; aval = Aloc->val;
655:     for (i=0; i<Aloc->totalslices; i++) {
656:       for (j=Aloc->sliidx[i]; j<Aloc->sliidx[i+1]; j++) {
657:         isnonzero = (PetscBool)((j-Aloc->sliidx[i])/8 < Aloc->rlen[(i<<3)+(j&0x07)]);
658:         if (isnonzero) {
659:           row  = (i<<3)+(j&0x07) + mat->rmap->rstart;
660:           col  = sell->garray[*acolidx];
661:           MatSetValues(A,1,&row,1,&col,aval,INSERT_VALUES);
662:         }
663:         aval++; acolidx++;
664:       }
665:     }

667:     MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);
668:     MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);
669:     /*
670:        Everyone has to call to draw the matrix since the graphics waits are
671:        synchronized across all processors that share the PetscDraw object
672:     */
673:     PetscViewerGetSubViewer(viewer,PETSC_COMM_SELF,&sviewer);
674:     if (!rank) {
675:       PetscObjectSetName((PetscObject)((Mat_MPISELL*)(A->data))->A,((PetscObject)mat)->name);
676:       MatView_SeqSELL(((Mat_MPISELL*)(A->data))->A,sviewer);
677:     }
678:     PetscViewerRestoreSubViewer(viewer,PETSC_COMM_SELF,&sviewer);
679:     PetscViewerFlush(viewer);
680:     MatDestroy(&A);
681:   }
682:   return(0);
683: }

685: PetscErrorCode MatView_MPISELL(Mat mat,PetscViewer viewer)
686: {
688:   PetscBool      iascii,isdraw,issocket,isbinary;

691:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
692:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);
693:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);
694:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSOCKET,&issocket);
695:   if (iascii || isdraw || isbinary || issocket) {
696:     MatView_MPISELL_ASCIIorDraworSocket(mat,viewer);
697:   }
698:   return(0);
699: }

701: PetscErrorCode MatGetGhosts_MPISELL(Mat mat,PetscInt *nghosts,const PetscInt *ghosts[])
702: {
703:   Mat_MPISELL    *sell=(Mat_MPISELL*)mat->data;

707:   MatGetSize(sell->B,NULL,nghosts);
708:   if (ghosts) *ghosts = sell->garray;
709:   return(0);
710: }

712: PetscErrorCode MatGetInfo_MPISELL(Mat matin,MatInfoType flag,MatInfo *info)
713: {
714:   Mat_MPISELL    *mat=(Mat_MPISELL*)matin->data;
715:   Mat            A=mat->A,B=mat->B;
717:   PetscReal      isend[5],irecv[5];

720:   info->block_size = 1.0;
721:   MatGetInfo(A,MAT_LOCAL,info);

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

726:   MatGetInfo(B,MAT_LOCAL,info);

728:   isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded;
729:   isend[3] += info->memory;  isend[4] += info->mallocs;
730:   if (flag == MAT_LOCAL) {
731:     info->nz_used      = isend[0];
732:     info->nz_allocated = isend[1];
733:     info->nz_unneeded  = isend[2];
734:     info->memory       = isend[3];
735:     info->mallocs      = isend[4];
736:   } else if (flag == MAT_GLOBAL_MAX) {
737:     MPIU_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)matin));

739:     info->nz_used      = irecv[0];
740:     info->nz_allocated = irecv[1];
741:     info->nz_unneeded  = irecv[2];
742:     info->memory       = irecv[3];
743:     info->mallocs      = irecv[4];
744:   } else if (flag == MAT_GLOBAL_SUM) {
745:     MPIU_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)matin));

747:     info->nz_used      = irecv[0];
748:     info->nz_allocated = irecv[1];
749:     info->nz_unneeded  = irecv[2];
750:     info->memory       = irecv[3];
751:     info->mallocs      = irecv[4];
752:   }
753:   info->fill_ratio_given  = 0; /* no parallel LU/ILU/Cholesky */
754:   info->fill_ratio_needed = 0;
755:   info->factor_mallocs    = 0;
756:   return(0);
757: }

759: PetscErrorCode MatSetOption_MPISELL(Mat A,MatOption op,PetscBool flg)
760: {
761:   Mat_MPISELL    *a=(Mat_MPISELL*)A->data;

765:   switch (op) {
766:   case MAT_NEW_NONZERO_LOCATIONS:
767:   case MAT_NEW_NONZERO_ALLOCATION_ERR:
768:   case MAT_UNUSED_NONZERO_LOCATION_ERR:
769:   case MAT_KEEP_NONZERO_PATTERN:
770:   case MAT_NEW_NONZERO_LOCATION_ERR:
771:   case MAT_USE_INODES:
772:   case MAT_IGNORE_ZERO_ENTRIES:
773:     MatCheckPreallocated(A,1);
774:     MatSetOption(a->A,op,flg);
775:     MatSetOption(a->B,op,flg);
776:     break;
777:   case MAT_ROW_ORIENTED:
778:     MatCheckPreallocated(A,1);
779:     a->roworiented = flg;

781:     MatSetOption(a->A,op,flg);
782:     MatSetOption(a->B,op,flg);
783:     break;
784:   case MAT_NEW_DIAGONALS:
785:     PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);
786:     break;
787:   case MAT_IGNORE_OFF_PROC_ENTRIES:
788:     a->donotstash = flg;
789:     break;
790:   case MAT_SPD:
791:     A->spd_set = PETSC_TRUE;
792:     A->spd     = flg;
793:     if (flg) {
794:       A->symmetric                  = PETSC_TRUE;
795:       A->structurally_symmetric     = PETSC_TRUE;
796:       A->symmetric_set              = PETSC_TRUE;
797:       A->structurally_symmetric_set = PETSC_TRUE;
798:     }
799:     break;
800:   case MAT_SYMMETRIC:
801:     MatCheckPreallocated(A,1);
802:     MatSetOption(a->A,op,flg);
803:     break;
804:   case MAT_STRUCTURALLY_SYMMETRIC:
805:     MatCheckPreallocated(A,1);
806:     MatSetOption(a->A,op,flg);
807:     break;
808:   case MAT_HERMITIAN:
809:     MatCheckPreallocated(A,1);
810:     MatSetOption(a->A,op,flg);
811:     break;
812:   case MAT_SYMMETRY_ETERNAL:
813:     MatCheckPreallocated(A,1);
814:     MatSetOption(a->A,op,flg);
815:     break;
816:   default:
817:     SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %d",op);
818:   }
819:   return(0);
820: }


823: PetscErrorCode MatDiagonalScale_MPISELL(Mat mat,Vec ll,Vec rr)
824: {
825:   Mat_MPISELL    *sell=(Mat_MPISELL*)mat->data;
826:   Mat            a=sell->A,b=sell->B;
828:   PetscInt       s1,s2,s3;

831:   MatGetLocalSize(mat,&s2,&s3);
832:   if (rr) {
833:     VecGetLocalSize(rr,&s1);
834:     if (s1!=s3) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"right vector non-conforming local size");
835:     /* Overlap communication with computation. */
836:     VecScatterBegin(sell->Mvctx,rr,sell->lvec,INSERT_VALUES,SCATTER_FORWARD);
837:   }
838:   if (ll) {
839:     VecGetLocalSize(ll,&s1);
840:     if (s1!=s2) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"left vector non-conforming local size");
841:     (*b->ops->diagonalscale)(b,ll,0);
842:   }
843:   /* scale  the diagonal block */
844:   (*a->ops->diagonalscale)(a,ll,rr);

846:   if (rr) {
847:     /* Do a scatter end and then right scale the off-diagonal block */
848:     VecScatterEnd(sell->Mvctx,rr,sell->lvec,INSERT_VALUES,SCATTER_FORWARD);
849:     (*b->ops->diagonalscale)(b,0,sell->lvec);
850:   }
851:   return(0);
852: }

854: PetscErrorCode MatSetUnfactored_MPISELL(Mat A)
855: {
856:   Mat_MPISELL    *a=(Mat_MPISELL*)A->data;

860:   MatSetUnfactored(a->A);
861:   return(0);
862: }

864: PetscErrorCode MatEqual_MPISELL(Mat A,Mat B,PetscBool  *flag)
865: {
866:   Mat_MPISELL    *matB=(Mat_MPISELL*)B->data,*matA=(Mat_MPISELL*)A->data;
867:   Mat            a,b,c,d;
868:   PetscBool      flg;

872:   a = matA->A; b = matA->B;
873:   c = matB->A; d = matB->B;

875:   MatEqual(a,c,&flg);
876:   if (flg) {
877:     MatEqual(b,d,&flg);
878:   }
879:   MPIU_Allreduce(&flg,flag,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)A));
880:   return(0);
881: }

883: PetscErrorCode MatCopy_MPISELL(Mat A,Mat B,MatStructure str)
884: {
886:   Mat_MPISELL    *a=(Mat_MPISELL*)A->data;
887:   Mat_MPISELL    *b=(Mat_MPISELL*)B->data;

890:   /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */
891:   if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) {
892:     /* because of the column compression in the off-processor part of the matrix a->B,
893:        the number of columns in a->B and b->B may be different, hence we cannot call
894:        the MatCopy() directly on the two parts. If need be, we can provide a more
895:        efficient copy than the MatCopy_Basic() by first uncompressing the a->B matrices
896:        then copying the submatrices */
897:     MatCopy_Basic(A,B,str);
898:   } else {
899:     MatCopy(a->A,b->A,str);
900:     MatCopy(a->B,b->B,str);
901:   }
902:   return(0);
903: }

905: PetscErrorCode MatSetUp_MPISELL(Mat A)
906: {

910:    MatMPISELLSetPreallocation(A,PETSC_DEFAULT,0,PETSC_DEFAULT,0);
911:   return(0);
912: }


915: extern PetscErrorCode MatConjugate_SeqSELL(Mat);

917: PetscErrorCode MatConjugate_MPISELL(Mat mat)
918: {
919: #if defined(PETSC_USE_COMPLEX)
921:   Mat_MPISELL    *sell=(Mat_MPISELL*)mat->data;

924:   MatConjugate_SeqSELL(sell->A);
925:   MatConjugate_SeqSELL(sell->B);
926: #else
928: #endif
929:   return(0);
930: }

932: PetscErrorCode MatRealPart_MPISELL(Mat A)
933: {
934:   Mat_MPISELL    *a=(Mat_MPISELL*)A->data;

938:   MatRealPart(a->A);
939:   MatRealPart(a->B);
940:   return(0);
941: }

943: PetscErrorCode MatImaginaryPart_MPISELL(Mat A)
944: {
945:   Mat_MPISELL    *a=(Mat_MPISELL*)A->data;

949:   MatImaginaryPart(a->A);
950:   MatImaginaryPart(a->B);
951:   return(0);
952: }

954: PetscErrorCode MatInvertBlockDiagonal_MPISELL(Mat A,const PetscScalar **values)
955: {
956:   Mat_MPISELL    *a=(Mat_MPISELL*)A->data;

960:   MatInvertBlockDiagonal(a->A,values);
961:   A->factorerrortype = a->A->factorerrortype;
962:   return(0);
963: }

965: static PetscErrorCode MatSetRandom_MPISELL(Mat x,PetscRandom rctx)
966: {
968:   Mat_MPISELL    *sell=(Mat_MPISELL*)x->data;

971:   MatSetRandom(sell->A,rctx);
972:   MatSetRandom(sell->B,rctx);
973:   MatAssemblyBegin(x,MAT_FINAL_ASSEMBLY);
974:   MatAssemblyEnd(x,MAT_FINAL_ASSEMBLY);
975:   return(0);
976: }

978: PetscErrorCode MatSetFromOptions_MPISELL(PetscOptionItems *PetscOptionsObject,Mat A)
979: {

983:   PetscOptionsHead(PetscOptionsObject,"MPISELL options");
984:   PetscOptionsTail();
985:   return(0);
986: }

988: PetscErrorCode MatShift_MPISELL(Mat Y,PetscScalar a)
989: {
991:   Mat_MPISELL    *msell=(Mat_MPISELL*)Y->data;
992:   Mat_SeqSELL    *sell=(Mat_SeqSELL*)msell->A->data;

995:   if (!Y->preallocated) {
996:     MatMPISELLSetPreallocation(Y,1,NULL,0,NULL);
997:   } else if (!sell->nz) {
998:     PetscInt nonew = sell->nonew;
999:     MatSeqSELLSetPreallocation(msell->A,1,NULL);
1000:     sell->nonew = nonew;
1001:   }
1002:   MatShift_Basic(Y,a);
1003:   return(0);
1004: }

1006: PetscErrorCode MatMissingDiagonal_MPISELL(Mat A,PetscBool  *missing,PetscInt *d)
1007: {
1008:   Mat_MPISELL    *a=(Mat_MPISELL*)A->data;

1012:   if (A->rmap->n != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only works for square matrices");
1013:   MatMissingDiagonal(a->A,missing,d);
1014:   if (d) {
1015:     PetscInt rstart;
1016:     MatGetOwnershipRange(A,&rstart,NULL);
1017:     *d += rstart;

1019:   }
1020:   return(0);
1021: }

1023: PetscErrorCode MatGetDiagonalBlock_MPISELL(Mat A,Mat *a)
1024: {
1026:   *a = ((Mat_MPISELL*)A->data)->A;
1027:   return(0);
1028: }

1030: /* -------------------------------------------------------------------*/
1031: static struct _MatOps MatOps_Values = {MatSetValues_MPISELL,
1032:                                        0,
1033:                                        0,
1034:                                        MatMult_MPISELL,
1035:                                 /* 4*/ MatMultAdd_MPISELL,
1036:                                        MatMultTranspose_MPISELL,
1037:                                        MatMultTransposeAdd_MPISELL,
1038:                                        0,
1039:                                        0,
1040:                                        0,
1041:                                 /*10*/ 0,
1042:                                        0,
1043:                                        0,
1044:                                        MatSOR_MPISELL,
1045:                                        0,
1046:                                 /*15*/ MatGetInfo_MPISELL,
1047:                                        MatEqual_MPISELL,
1048:                                        MatGetDiagonal_MPISELL,
1049:                                        MatDiagonalScale_MPISELL,
1050:                                        0,
1051:                                 /*20*/ MatAssemblyBegin_MPISELL,
1052:                                        MatAssemblyEnd_MPISELL,
1053:                                        MatSetOption_MPISELL,
1054:                                        MatZeroEntries_MPISELL,
1055:                                 /*24*/ 0,
1056:                                        0,
1057:                                        0,
1058:                                        0,
1059:                                        0,
1060:                                 /*29*/ MatSetUp_MPISELL,
1061:                                        0,
1062:                                        0,
1063:                                        MatGetDiagonalBlock_MPISELL,
1064:                                        0,
1065:                                 /*34*/ MatDuplicate_MPISELL,
1066:                                        0,
1067:                                        0,
1068:                                        0,
1069:                                        0,
1070:                                 /*39*/ 0,
1071:                                        0,
1072:                                        0,
1073:                                        MatGetValues_MPISELL,
1074:                                        MatCopy_MPISELL,
1075:                                 /*44*/ 0,
1076:                                        MatScale_MPISELL,
1077:                                        MatShift_MPISELL,
1078:                                        MatDiagonalSet_MPISELL,
1079:                                        0,
1080:                                 /*49*/ MatSetRandom_MPISELL,
1081:                                        0,
1082:                                        0,
1083:                                        0,
1084:                                        0,
1085:                                 /*54*/ MatFDColoringCreate_MPIXAIJ,
1086:                                        0,
1087:                                        MatSetUnfactored_MPISELL,
1088:                                        0,
1089:                                        0,
1090:                                 /*59*/ 0,
1091:                                        MatDestroy_MPISELL,
1092:                                        MatView_MPISELL,
1093:                                        0,
1094:                                        0,
1095:                                 /*64*/ 0,
1096:                                        0,
1097:                                        0,
1098:                                        0,
1099:                                        0,
1100:                                 /*69*/ 0,
1101:                                        0,
1102:                                        0,
1103:                                        0,
1104:                                        0,
1105:                                        0,
1106:                                 /*75*/ MatFDColoringApply_AIJ, /* reuse AIJ function */
1107:                                        MatSetFromOptions_MPISELL,
1108:                                        0,
1109:                                        0,
1110:                                        0,
1111:                                 /*80*/ 0,
1112:                                        0,
1113:                                        0,
1114:                                 /*83*/ 0,
1115:                                        0,
1116:                                        0,
1117:                                        0,
1118:                                        0,
1119:                                        0,
1120:                                 /*89*/ 0,
1121:                                        0,
1122:                                        0,
1123:                                        0,
1124:                                        0,
1125:                                 /*94*/ 0,
1126:                                        0,
1127:                                        0,
1128:                                        0,
1129:                                        0,
1130:                                 /*99*/ 0,
1131:                                        0,
1132:                                        0,
1133:                                        MatConjugate_MPISELL,
1134:                                        0,
1135:                                 /*104*/0,
1136:                                        MatRealPart_MPISELL,
1137:                                        MatImaginaryPart_MPISELL,
1138:                                        0,
1139:                                        0,
1140:                                 /*109*/0,
1141:                                        0,
1142:                                        0,
1143:                                        0,
1144:                                        MatMissingDiagonal_MPISELL,
1145:                                 /*114*/0,
1146:                                        0,
1147:                                        MatGetGhosts_MPISELL,
1148:                                        0,
1149:                                        0,
1150:                                 /*119*/0,
1151:                                        0,
1152:                                        0,
1153:                                        0,
1154:                                        0,
1155:                                 /*124*/0,
1156:                                        0,
1157:                                        MatInvertBlockDiagonal_MPISELL,
1158:                                        0,
1159:                                        0,
1160:                                 /*129*/0,
1161:                                        0,
1162:                                        0,
1163:                                        0,
1164:                                        0,
1165:                                 /*134*/0,
1166:                                        0,
1167:                                        0,
1168:                                        0,
1169:                                        0,
1170:                                 /*139*/0,
1171:                                        0,
1172:                                        0,
1173:                                        MatFDColoringSetUp_MPIXAIJ,
1174:                                        0,
1175:                                 /*144*/0
1176: };

1178: /* ----------------------------------------------------------------------------------------*/

1180: PetscErrorCode MatStoreValues_MPISELL(Mat mat)
1181: {
1182:   Mat_MPISELL    *sell=(Mat_MPISELL*)mat->data;

1186:   MatStoreValues(sell->A);
1187:   MatStoreValues(sell->B);
1188:   return(0);
1189: }

1191: PetscErrorCode MatRetrieveValues_MPISELL(Mat mat)
1192: {
1193:   Mat_MPISELL    *sell=(Mat_MPISELL*)mat->data;

1197:   MatRetrieveValues(sell->A);
1198:   MatRetrieveValues(sell->B);
1199:   return(0);
1200: }

1202: PetscErrorCode MatMPISELLSetPreallocation_MPISELL(Mat B,PetscInt d_rlenmax,const PetscInt d_rlen[],PetscInt o_rlenmax,const PetscInt o_rlen[])
1203: {
1204:   Mat_MPISELL    *b;

1208:   PetscLayoutSetUp(B->rmap);
1209:   PetscLayoutSetUp(B->cmap);
1210:   b = (Mat_MPISELL*)B->data;

1212:   if (!B->preallocated) {
1213:     /* Explicitly create 2 MATSEQSELL matrices. */
1214:     MatCreate(PETSC_COMM_SELF,&b->A);
1215:     MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);
1216:     MatSetBlockSizesFromMats(b->A,B,B);
1217:     MatSetType(b->A,MATSEQSELL);
1218:     PetscLogObjectParent((PetscObject)B,(PetscObject)b->A);
1219:     MatCreate(PETSC_COMM_SELF,&b->B);
1220:     MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);
1221:     MatSetBlockSizesFromMats(b->B,B,B);
1222:     MatSetType(b->B,MATSEQSELL);
1223:     PetscLogObjectParent((PetscObject)B,(PetscObject)b->B);
1224:   }

1226:   MatSeqSELLSetPreallocation(b->A,d_rlenmax,d_rlen);
1227:   MatSeqSELLSetPreallocation(b->B,o_rlenmax,o_rlen);
1228:   B->preallocated  = PETSC_TRUE;
1229:   B->was_assembled = PETSC_FALSE;
1230:   /*
1231:     critical for MatAssemblyEnd to work.
1232:     MatAssemblyBegin checks it to set up was_assembled
1233:     and MatAssemblyEnd checks was_assembled to determine whether to build garray
1234:   */
1235:   B->assembled     = PETSC_FALSE;
1236:   return(0);
1237: }

1239: PetscErrorCode MatDuplicate_MPISELL(Mat matin,MatDuplicateOption cpvalues,Mat *newmat)
1240: {
1241:   Mat            mat;
1242:   Mat_MPISELL    *a,*oldmat=(Mat_MPISELL*)matin->data;

1246:   *newmat = 0;
1247:   MatCreate(PetscObjectComm((PetscObject)matin),&mat);
1248:   MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);
1249:   MatSetBlockSizesFromMats(mat,matin,matin);
1250:   MatSetType(mat,((PetscObject)matin)->type_name);
1251:   PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));
1252:   a       = (Mat_MPISELL*)mat->data;

1254:   mat->factortype   = matin->factortype;
1255:   mat->assembled    = PETSC_TRUE;
1256:   mat->insertmode   = NOT_SET_VALUES;
1257:   mat->preallocated = PETSC_TRUE;

1259:   a->size         = oldmat->size;
1260:   a->rank         = oldmat->rank;
1261:   a->donotstash   = oldmat->donotstash;
1262:   a->roworiented  = oldmat->roworiented;
1263:   a->rowindices   = 0;
1264:   a->rowvalues    = 0;
1265:   a->getrowactive = PETSC_FALSE;

1267:   PetscLayoutReference(matin->rmap,&mat->rmap);
1268:   PetscLayoutReference(matin->cmap,&mat->cmap);

1270:   if (oldmat->colmap) {
1271: #if defined(PETSC_USE_CTABLE)
1272:     PetscTableCreateCopy(oldmat->colmap,&a->colmap);
1273: #else
1274:     PetscMalloc1(mat->cmap->N,&a->colmap);
1275:     PetscLogObjectMemory((PetscObject)mat,(mat->cmap->N)*sizeof(PetscInt));
1276:     PetscMemcpy(a->colmap,oldmat->colmap,(mat->cmap->N)*sizeof(PetscInt));
1277: #endif
1278:   } else a->colmap = 0;
1279:   if (oldmat->garray) {
1280:     PetscInt len;
1281:     len  = oldmat->B->cmap->n;
1282:     PetscMalloc1(len+1,&a->garray);
1283:     PetscLogObjectMemory((PetscObject)mat,len*sizeof(PetscInt));
1284:     if (len) { PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt)); }
1285:   } else a->garray = 0;

1287:   VecDuplicate(oldmat->lvec,&a->lvec);
1288:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->lvec);
1289:   VecScatterCopy(oldmat->Mvctx,&a->Mvctx);
1290:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->Mvctx);
1291:   MatDuplicate(oldmat->A,cpvalues,&a->A);
1292:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->A);
1293:   MatDuplicate(oldmat->B,cpvalues,&a->B);
1294:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->B);
1295:   PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);
1296:   *newmat = mat;
1297:   return(0);
1298: }

1300: /*@C
1301:    MatMPISELLSetPreallocation - Preallocates memory for a sparse parallel matrix in sell format.
1302:    For good matrix assembly performance the user should preallocate the matrix storage by
1303:    setting the parameters d_nz (or d_nnz) and o_nz (or o_nnz).

1305:    Collective on MPI_Comm

1307:    Input Parameters:
1308: +  B - the matrix
1309: .  d_nz  - number of nonzeros per row in DIAGONAL portion of local submatrix
1310:            (same value is used for all local rows)
1311: .  d_nnz - array containing the number of nonzeros in the various rows of the
1312:            DIAGONAL portion of the local submatrix (possibly different for each row)
1313:            or NULL (PETSC_NULL_INTEGER in Fortran), if d_nz is used to specify the nonzero structure.
1314:            The size of this array is equal to the number of local rows, i.e 'm'.
1315:            For matrices that will be factored, you must leave room for (and set)
1316:            the diagonal entry even if it is zero.
1317: .  o_nz  - number of nonzeros per row in the OFF-DIAGONAL portion of local
1318:            submatrix (same value is used for all local rows).
1319: -  o_nnz - array containing the number of nonzeros in the various rows of the
1320:            OFF-DIAGONAL portion of the local submatrix (possibly different for
1321:            each row) or NULL (PETSC_NULL_INTEGER in Fortran), if o_nz is used to specify the nonzero
1322:            structure. The size of this array is equal to the number
1323:            of local rows, i.e 'm'.

1325:    If the *_nnz parameter is given then the *_nz parameter is ignored

1327:    The stored row and column indices begin with zero.

1329:    The parallel matrix is partitioned such that the first m0 rows belong to
1330:    process 0, the next m1 rows belong to process 1, the next m2 rows belong
1331:    to process 2 etc.. where m0,m1,m2... are the input parameter 'm'.

1333:    The DIAGONAL portion of the local submatrix of a processor can be defined
1334:    as the submatrix which is obtained by extraction the part corresponding to
1335:    the rows r1-r2 and columns c1-c2 of the global matrix, where r1 is the
1336:    first row that belongs to the processor, r2 is the last row belonging to
1337:    the this processor, and c1-c2 is range of indices of the local part of a
1338:    vector suitable for applying the matrix to.  This is an mxn matrix.  In the
1339:    common case of a square matrix, the row and column ranges are the same and
1340:    the DIAGONAL part is also square. The remaining portion of the local
1341:    submatrix (mxN) constitute the OFF-DIAGONAL portion.

1343:    If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored.

1345:    You can call MatGetInfo() to get information on how effective the preallocation was;
1346:    for example the fields mallocs,nz_allocated,nz_used,nz_unneeded;
1347:    You can also run with the option -info and look for messages with the string
1348:    malloc in them to see if additional memory allocation was needed.

1350:    Example usage:

1352:    Consider the following 8x8 matrix with 34 non-zero values, that is
1353:    assembled across 3 processors. Lets assume that proc0 owns 3 rows,
1354:    proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown
1355:    as follows:

1357: .vb
1358:             1  2  0  |  0  3  0  |  0  4
1359:     Proc0   0  5  6  |  7  0  0  |  8  0
1360:             9  0 10  | 11  0  0  | 12  0
1361:     -------------------------------------
1362:            13  0 14  | 15 16 17  |  0  0
1363:     Proc1   0 18  0  | 19 20 21  |  0  0
1364:             0  0  0  | 22 23  0  | 24  0
1365:     -------------------------------------
1366:     Proc2  25 26 27  |  0  0 28  | 29  0
1367:            30  0  0  | 31 32 33  |  0 34
1368: .ve

1370:    This can be represented as a collection of submatrices as:

1372: .vb
1373:       A B C
1374:       D E F
1375:       G H I
1376: .ve

1378:    Where the submatrices A,B,C are owned by proc0, D,E,F are
1379:    owned by proc1, G,H,I are owned by proc2.

1381:    The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively.
1382:    The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively.
1383:    The 'M','N' parameters are 8,8, and have the same values on all procs.

1385:    The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are
1386:    submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices
1387:    corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively.
1388:    Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL
1389:    part as SeqSELL matrices. for eg: proc1 will store [E] as a SeqSELL
1390:    matrix, ans [DF] as another SeqSELL matrix.

1392:    When d_nz, o_nz parameters are specified, d_nz storage elements are
1393:    allocated for every row of the local diagonal submatrix, and o_nz
1394:    storage locations are allocated for every row of the OFF-DIAGONAL submat.
1395:    One way to choose d_nz and o_nz is to use the max nonzerors per local
1396:    rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices.
1397:    In this case, the values of d_nz,o_nz are:
1398: .vb
1399:      proc0 : dnz = 2, o_nz = 2
1400:      proc1 : dnz = 3, o_nz = 2
1401:      proc2 : dnz = 1, o_nz = 4
1402: .ve
1403:    We are allocating m*(d_nz+o_nz) storage locations for every proc. This
1404:    translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10
1405:    for proc3. i.e we are using 12+15+10=37 storage locations to store
1406:    34 values.

1408:    When d_nnz, o_nnz parameters are specified, the storage is specified
1409:    for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices.
1410:    In the above case the values for d_nnz,o_nnz are:
1411: .vb
1412:      proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2]
1413:      proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1]
1414:      proc2: d_nnz = [1,1]   and o_nnz = [4,4]
1415: .ve
1416:    Here the space allocated is according to nz (or maximum values in the nnz
1417:    if nnz is provided) for DIAGONAL and OFF-DIAGONAL submatrices, i.e (2+2+3+2)*3+(1+4)*2=37

1419:    Level: intermediate

1421: .keywords: matrix, sell, sparse, parallel

1423: .seealso: MatCreate(), MatCreateSeqSELL(), MatSetValues(), MatCreatesell(),
1424:           MATMPISELL, MatGetInfo(), PetscSplitOwnership()
1425: @*/
1426: PetscErrorCode MatMPISELLSetPreallocation(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[])
1427: {

1433:   PetscTryMethod(B,"MatMPISELLSetPreallocation_C",(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[]),(B,d_nz,d_nnz,o_nz,o_nnz));
1434:   return(0);
1435: }

1437: /*@C
1438:    MatCreateSELL - Creates a sparse parallel matrix in SELL format.

1440:    Collective on MPI_Comm

1442:    Input Parameters:
1443: +  comm - MPI communicator
1444: .  m - number of local rows (or PETSC_DECIDE to have calculated if M is given)
1445:            This value should be the same as the local size used in creating the
1446:            y vector for the matrix-vector product y = Ax.
1447: .  n - This value should be the same as the local size used in creating the
1448:        x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have
1449:        calculated if N is given) For square matrices n is almost always m.
1450: .  M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
1451: .  N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
1452: .  d_rlenmax - max number of nonzeros per row in DIAGONAL portion of local submatrix
1453:                (same value is used for all local rows)
1454: .  d_rlen - array containing the number of nonzeros in the various rows of the
1455:             DIAGONAL portion of the local submatrix (possibly different for each row)
1456:             or NULL, if d_rlenmax is used to specify the nonzero structure.
1457:             The size of this array is equal to the number of local rows, i.e 'm'.
1458: .  o_rlenmax - max number of nonzeros per row in the OFF-DIAGONAL portion of local
1459:                submatrix (same value is used for all local rows).
1460: -  o_rlen - array containing the number of nonzeros in the various rows of the
1461:             OFF-DIAGONAL portion of the local submatrix (possibly different for
1462:             each row) or NULL, if o_rlenmax is used to specify the nonzero
1463:             structure. The size of this array is equal to the number
1464:             of local rows, i.e 'm'.

1466:    Output Parameter:
1467: .  A - the matrix

1469:    It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(),
1470:    MatXXXXSetPreallocation() paradgm instead of this routine directly.
1471:    [MatXXXXSetPreallocation() is, for example, MatSeqSELLSetPreallocation]

1473:    Notes:
1474:    If the *_rlen parameter is given then the *_rlenmax parameter is ignored

1476:    m,n,M,N parameters specify the size of the matrix, and its partitioning across
1477:    processors, while d_rlenmax,d_rlen,o_rlenmax,o_rlen parameters specify the approximate
1478:    storage requirements for this matrix.

1480:    If PETSC_DECIDE or  PETSC_DETERMINE is used for a particular argument on one
1481:    processor than it must be used on all processors that share the object for
1482:    that argument.

1484:    The user MUST specify either the local or global matrix dimensions
1485:    (possibly both).

1487:    The parallel matrix is partitioned across processors such that the
1488:    first m0 rows belong to process 0, the next m1 rows belong to
1489:    process 1, the next m2 rows belong to process 2 etc.. where
1490:    m0,m1,m2,.. are the input parameter 'm'. i.e each processor stores
1491:    values corresponding to [m x N] submatrix.

1493:    The columns are logically partitioned with the n0 columns belonging
1494:    to 0th partition, the next n1 columns belonging to the next
1495:    partition etc.. where n0,n1,n2... are the input parameter 'n'.

1497:    The DIAGONAL portion of the local submatrix on any given processor
1498:    is the submatrix corresponding to the rows and columns m,n
1499:    corresponding to the given processor. i.e diagonal matrix on
1500:    process 0 is [m0 x n0], diagonal matrix on process 1 is [m1 x n1]
1501:    etc. The remaining portion of the local submatrix [m x (N-n)]
1502:    constitute the OFF-DIAGONAL portion. The example below better
1503:    illustrates this concept.

1505:    For a square global matrix we define each processor's diagonal portion
1506:    to be its local rows and the corresponding columns (a square submatrix);
1507:    each processor's off-diagonal portion encompasses the remainder of the
1508:    local matrix (a rectangular submatrix).

1510:    If o_rlen, d_rlen are specified, then o_rlenmax, and d_rlenmax are ignored.

1512:    When calling this routine with a single process communicator, a matrix of
1513:    type SEQSELL is returned.  If a matrix of type MATMPISELL is desired for this
1514:    type of communicator, use the construction mechanism:
1515:      MatCreate(...,&A); MatSetType(A,MATMPISELL); MatSetSizes(A, m,n,M,N); MatMPISELLSetPreallocation(A,...);

1517:    Options Database Keys:
1518: -  -mat_sell_oneindex - Internally use indexing starting at 1
1519:         rather than 0.  Note that when calling MatSetValues(),
1520:         the user still MUST index entries starting at 0!


1523:    Example usage:

1525:    Consider the following 8x8 matrix with 34 non-zero values, that is
1526:    assembled across 3 processors. Lets assume that proc0 owns 3 rows,
1527:    proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown
1528:    as follows:

1530: .vb
1531:             1  2  0  |  0  3  0  |  0  4
1532:     Proc0   0  5  6  |  7  0  0  |  8  0
1533:             9  0 10  | 11  0  0  | 12  0
1534:     -------------------------------------
1535:            13  0 14  | 15 16 17  |  0  0
1536:     Proc1   0 18  0  | 19 20 21  |  0  0
1537:             0  0  0  | 22 23  0  | 24  0
1538:     -------------------------------------
1539:     Proc2  25 26 27  |  0  0 28  | 29  0
1540:            30  0  0  | 31 32 33  |  0 34
1541: .ve

1543:    This can be represented as a collection of submatrices as:

1545: .vb
1546:       A B C
1547:       D E F
1548:       G H I
1549: .ve

1551:    Where the submatrices A,B,C are owned by proc0, D,E,F are
1552:    owned by proc1, G,H,I are owned by proc2.

1554:    The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively.
1555:    The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively.
1556:    The 'M','N' parameters are 8,8, and have the same values on all procs.

1558:    The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are
1559:    submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices
1560:    corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively.
1561:    Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL
1562:    part as SeqSELL matrices. for eg: proc1 will store [E] as a SeqSELL
1563:    matrix, ans [DF] as another SeqSELL matrix.

1565:    When d_rlenmax, o_rlenmax parameters are specified, d_rlenmax storage elements are
1566:    allocated for every row of the local diagonal submatrix, and o_rlenmax
1567:    storage locations are allocated for every row of the OFF-DIAGONAL submat.
1568:    One way to choose d_rlenmax and o_rlenmax is to use the max nonzerors per local
1569:    rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices.
1570:    In this case, the values of d_rlenmax,o_rlenmax are:
1571: .vb
1572:      proc0 : d_rlenmax = 2, o_rlenmax = 2
1573:      proc1 : d_rlenmax = 3, o_rlenmax = 2
1574:      proc2 : d_rlenmax = 1, o_rlenmax = 4
1575: .ve
1576:    We are allocating m*(d_rlenmax+o_rlenmax) storage locations for every proc. This
1577:    translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10
1578:    for proc3. i.e we are using 12+15+10=37 storage locations to store
1579:    34 values.

1581:    When d_rlen, o_rlen parameters are specified, the storage is specified
1582:    for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices.
1583:    In the above case the values for d_nnz,o_nnz are:
1584: .vb
1585:      proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2]
1586:      proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1]
1587:      proc2: d_nnz = [1,1]   and o_nnz = [4,4]
1588: .ve
1589:    Here the space allocated is still 37 though there are 34 nonzeros because 
1590:    the allocation is always done according to rlenmax.

1592:    Level: intermediate

1594: .keywords: matrix, sell, sparse, parallel

1596: .seealso: MatCreate(), MatCreateSeqSELL(), MatSetValues(), MatMPISELLSetPreallocation(), MatMPISELLSetPreallocationSELL(),
1597:           MATMPISELL, MatCreateMPISELLWithArrays()
1598: @*/
1599: 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)
1600: {
1602:   PetscMPIInt    size;

1605:   MatCreate(comm,A);
1606:   MatSetSizes(*A,m,n,M,N);
1607:   MPI_Comm_size(comm,&size);
1608:   if (size > 1) {
1609:     MatSetType(*A,MATMPISELL);
1610:     MatMPISELLSetPreallocation(*A,d_rlenmax,d_rlen,o_rlenmax,o_rlen);
1611:   } else {
1612:     MatSetType(*A,MATSEQSELL);
1613:     MatSeqSELLSetPreallocation(*A,d_rlenmax,d_rlen);
1614:   }
1615:   return(0);
1616: }

1618: PetscErrorCode MatMPISELLGetSeqSELL(Mat A,Mat *Ad,Mat *Ao,const PetscInt *colmap[])
1619: {
1620:   Mat_MPISELL    *a=(Mat_MPISELL*)A->data;
1621:   PetscBool      flg;

1625:   PetscObjectTypeCompare((PetscObject)A,MATMPISELL,&flg);
1626:   if (!flg) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"This function requires a MATMPISELL matrix as input");
1627:   if (Ad)     *Ad     = a->A;
1628:   if (Ao)     *Ao     = a->B;
1629:   if (colmap) *colmap = a->garray;
1630:   return(0);
1631: }

1633: /*@C
1634:      MatMPISELLGetLocalMatCondensed - Creates a SeqSELL matrix from an MATMPISELL matrix by taking all its local rows and NON-ZERO columns

1636:     Not Collective

1638:    Input Parameters:
1639: +    A - the matrix
1640: .    scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX
1641: -    row, col - index sets of rows and columns to extract (or NULL)

1643:    Output Parameter:
1644: .    A_loc - the local sequential matrix generated

1646:     Level: developer

1648: .seealso: MatGetOwnershipRange(), MatMPISELLGetLocalMat()

1650: @*/
1651: PetscErrorCode MatMPISELLGetLocalMatCondensed(Mat A,MatReuse scall,IS *row,IS *col,Mat *A_loc)
1652: {
1653:   Mat_MPISELL    *a=(Mat_MPISELL*)A->data;
1655:   PetscInt       i,start,end,ncols,nzA,nzB,*cmap,imark,*idx;
1656:   IS             isrowa,iscola;
1657:   Mat            *aloc;
1658:   PetscBool      match;

1661:   PetscObjectTypeCompare((PetscObject)A,MATMPISELL,&match);
1662:   if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MATMPISELL matrix as input");
1663:   PetscLogEventBegin(MAT_Getlocalmatcondensed,A,0,0,0);
1664:   if (!row) {
1665:     start = A->rmap->rstart; end = A->rmap->rend;
1666:     ISCreateStride(PETSC_COMM_SELF,end-start,start,1,&isrowa);
1667:   } else {
1668:     isrowa = *row;
1669:   }
1670:   if (!col) {
1671:     start = A->cmap->rstart;
1672:     cmap  = a->garray;
1673:     nzA   = a->A->cmap->n;
1674:     nzB   = a->B->cmap->n;
1675:     PetscMalloc1(nzA+nzB, &idx);
1676:     ncols = 0;
1677:     for (i=0; i<nzB; i++) {
1678:       if (cmap[i] < start) idx[ncols++] = cmap[i];
1679:       else break;
1680:     }
1681:     imark = i;
1682:     for (i=0; i<nzA; i++) idx[ncols++] = start + i;
1683:     for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i];
1684:     ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&iscola);
1685:   } else {
1686:     iscola = *col;
1687:   }
1688:   if (scall != MAT_INITIAL_MATRIX) {
1689:     PetscMalloc1(1,&aloc);
1690:     aloc[0] = *A_loc;
1691:   }
1692:   MatCreateSubMatrices(A,1,&isrowa,&iscola,scall,&aloc);
1693:   *A_loc = aloc[0];
1694:   PetscFree(aloc);
1695:   if (!row) {
1696:     ISDestroy(&isrowa);
1697:   }
1698:   if (!col) {
1699:     ISDestroy(&iscola);
1700:   }
1701:   PetscLogEventEnd(MAT_Getlocalmatcondensed,A,0,0,0);
1702:   return(0);
1703: }

1705:  #include <../src/mat/impls/aij/mpi/mpiaij.h>

1707: PetscErrorCode MatConvert_MPISELL_MPIAIJ(Mat A,MatType newtype,MatReuse reuse,Mat *newmat)
1708: {
1710:   Mat_MPISELL    *a=(Mat_MPISELL*)A->data;
1711:   Mat            B;
1712:   Mat_MPIAIJ     *b;

1715:   if (!A->assembled) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Matrix must be assembled");

1717:   if (reuse == MAT_REUSE_MATRIX) {
1718:     B = *newmat;
1719:   } else {
1720:     MatCreate(PetscObjectComm((PetscObject)A),&B);
1721:     MatSetType(B,MATMPIAIJ);
1722:     MatSetSizes(B,A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N);
1723:     MatSetBlockSizes(B,A->rmap->bs,A->cmap->bs);
1724:     MatSeqAIJSetPreallocation(B,0,NULL);
1725:     MatMPIAIJSetPreallocation(B,0,NULL,0,NULL);
1726:   }
1727:   b    = (Mat_MPIAIJ*) B->data;

1729:   if (reuse == MAT_REUSE_MATRIX) {
1730:     MatConvert_SeqSELL_SeqAIJ(a->A, MATSEQAIJ, MAT_REUSE_MATRIX, &b->A);
1731:     MatConvert_SeqSELL_SeqAIJ(a->B, MATSEQAIJ, MAT_REUSE_MATRIX, &b->B);
1732:   } else {
1733:     MatDestroy(&b->A);
1734:     MatDestroy(&b->B);
1735:     MatDisAssemble_MPISELL(A);
1736:     MatConvert_SeqSELL_SeqAIJ(a->A, MATSEQAIJ, MAT_INITIAL_MATRIX, &b->A);
1737:     MatConvert_SeqSELL_SeqAIJ(a->B, MATSEQAIJ, MAT_INITIAL_MATRIX, &b->B);
1738:     MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
1739:     MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);
1740:     MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);
1741:     MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);
1742:   }

1744:   if (reuse == MAT_INPLACE_MATRIX) {
1745:     MatHeaderReplace(A,&B);
1746:   } else {
1747:     *newmat = B;
1748:   }
1749:   return(0);
1750: }

1752: PetscErrorCode MatConvert_MPIAIJ_MPISELL(Mat A,MatType newtype,MatReuse reuse,Mat *newmat)
1753: {
1755:   Mat_MPIAIJ     *a=(Mat_MPIAIJ*)A->data;
1756:   Mat            B;
1757:   Mat_MPISELL    *b;

1760:   if (!A->assembled) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Matrix must be assembled");

1762:   if (reuse == MAT_REUSE_MATRIX) {
1763:     B = *newmat;
1764:   } else {
1765:     MatCreate(PetscObjectComm((PetscObject)A),&B);
1766:     MatSetType(B,MATMPISELL);
1767:     MatSetSizes(B,A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N);
1768:     MatSetBlockSizes(B,A->rmap->bs,A->cmap->bs);
1769:     MatSeqAIJSetPreallocation(B,0,NULL);
1770:     MatMPIAIJSetPreallocation(B,0,NULL,0,NULL);
1771:   }
1772:   b    = (Mat_MPISELL*) B->data;

1774:   if (reuse == MAT_REUSE_MATRIX) {
1775:     MatConvert_SeqAIJ_SeqSELL(a->A, MATSEQSELL, MAT_REUSE_MATRIX, &b->A);
1776:     MatConvert_SeqAIJ_SeqSELL(a->B, MATSEQSELL, MAT_REUSE_MATRIX, &b->B);
1777:   } else {
1778:     MatDestroy(&b->A);
1779:     MatDestroy(&b->B);
1780:     MatDisAssemble_MPIAIJ(A);
1781:     MatConvert_SeqAIJ_SeqSELL(a->A, MATSEQSELL, MAT_INITIAL_MATRIX, &b->A);
1782:     MatConvert_SeqAIJ_SeqSELL(a->B, MATSEQSELL, MAT_INITIAL_MATRIX, &b->B);
1783:     MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
1784:     MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);
1785:     MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);
1786:     MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);
1787:   }

1789:   if (reuse == MAT_INPLACE_MATRIX) {
1790:     MatHeaderReplace(A,&B);
1791:   } else {
1792:     *newmat = B;
1793:   }
1794:   return(0);
1795: }

1797: PetscErrorCode MatSOR_MPISELL(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx)
1798: {
1799:   Mat_MPISELL    *mat=(Mat_MPISELL*)matin->data;
1801:   Vec            bb1=0;

1804:   if (flag == SOR_APPLY_UPPER) {
1805:     (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
1806:     return(0);
1807:   }

1809:   if (its > 1 || ~flag & SOR_ZERO_INITIAL_GUESS || flag & SOR_EISENSTAT) {
1810:     VecDuplicate(bb,&bb1);
1811:   }

1813:   if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) {
1814:     if (flag & SOR_ZERO_INITIAL_GUESS) {
1815:       (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
1816:       its--;
1817:     }

1819:     while (its--) {
1820:       VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
1821:       VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);

1823:       /* update rhs: bb1 = bb - B*x */
1824:       VecScale(mat->lvec,-1.0);
1825:       (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);

1827:       /* local sweep */
1828:       (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,1,xx);
1829:     }
1830:   } else if (flag & SOR_LOCAL_FORWARD_SWEEP) {
1831:     if (flag & SOR_ZERO_INITIAL_GUESS) {
1832:       (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
1833:       its--;
1834:     }
1835:     while (its--) {
1836:       VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
1837:       VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);

1839:       /* update rhs: bb1 = bb - B*x */
1840:       VecScale(mat->lvec,-1.0);
1841:       (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);

1843:       /* local sweep */
1844:       (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_FORWARD_SWEEP,fshift,lits,1,xx);
1845:     }
1846:   } else if (flag & SOR_LOCAL_BACKWARD_SWEEP) {
1847:     if (flag & SOR_ZERO_INITIAL_GUESS) {
1848:       (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
1849:       its--;
1850:     }
1851:     while (its--) {
1852:       VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
1853:       VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);

1855:       /* update rhs: bb1 = bb - B*x */
1856:       VecScale(mat->lvec,-1.0);
1857:       (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);

1859:       /* local sweep */
1860:       (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_BACKWARD_SWEEP,fshift,lits,1,xx);
1861:     }
1862:   } else SETERRQ(PetscObjectComm((PetscObject)matin),PETSC_ERR_SUP,"Parallel SOR not supported");

1864:   VecDestroy(&bb1);

1866:   matin->factorerrortype = mat->A->factorerrortype;
1867:   return(0);
1868: }

1870: /*MC
1871:    MATMPISELL - MATMPISELL = "MPISELL" - A matrix type to be used for parallel sparse matrices.

1873:    Options Database Keys:
1874: . -mat_type MPISELL - sets the matrix type to "MPISELL" during a call to MatSetFromOptions()

1876:   Level: beginner

1878: .seealso: MatCreateSELL()
1879: M*/
1880: PETSC_EXTERN PetscErrorCode MatCreate_MPISELL(Mat B)
1881: {
1882:   Mat_MPISELL    *b;
1884:   PetscMPIInt    size;

1887:   MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);
1888:   PetscNewLog(B,&b);
1889:   B->data       = (void*)b;
1890:   PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));
1891:   B->assembled  = PETSC_FALSE;
1892:   B->insertmode = NOT_SET_VALUES;
1893:   b->size       = size;
1894:   MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);
1895:   /* build cache for off array entries formed */
1896:   MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);

1898:   b->donotstash  = PETSC_FALSE;
1899:   b->colmap      = 0;
1900:   b->garray      = 0;
1901:   b->roworiented = PETSC_TRUE;

1903:   /* stuff used for matrix vector multiply */
1904:   b->lvec  = NULL;
1905:   b->Mvctx = NULL;

1907:   /* stuff for MatGetRow() */
1908:   b->rowindices   = 0;
1909:   b->rowvalues    = 0;
1910:   b->getrowactive = PETSC_FALSE;

1912:   PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPISELL);
1913:   PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPISELL);
1914:   PetscObjectComposeFunction((PetscObject)B,"MatIsTranspose_C",MatIsTranspose_MPISELL);
1915:   PetscObjectComposeFunction((PetscObject)B,"MatMPISELLSetPreallocation_C",MatMPISELLSetPreallocation_MPISELL);
1916:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpisell_mpiaij_C",MatConvert_MPISELL_MPIAIJ);
1917:   PetscObjectComposeFunction((PetscObject)B,"MatDiagonalScaleLocal_C",MatDiagonalScaleLocal_MPISELL);
1918:   PetscObjectChangeTypeName((PetscObject)B,MATMPISELL);
1919:   return(0);
1920: }