Actual source code: mmbaij.c

  1: #define PETSCMAT_DLL

  3: /*
  4:    Support for the parallel BAIJ matrix vector multiply
  5: */
 6:  #include src/mat/impls/baij/mpi/mpibaij.h

  8: EXTERN PetscErrorCode MatSetValuesBlocked_SeqBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const PetscScalar[],InsertMode);

 12: PetscErrorCode MatSetUpMultiply_MPIBAIJ(Mat mat)
 13: {
 14:   Mat_MPIBAIJ    *baij = (Mat_MPIBAIJ*)mat->data;
 15:   Mat_SeqBAIJ    *B = (Mat_SeqBAIJ*)(baij->B->data);
 17:   PetscInt       i,j,*aj = B->j,ec = 0,*garray;
 18:   PetscInt       bs = mat->bs,*stmp;
 19:   IS             from,to;
 20:   Vec            gvec;
 21: #if defined (PETSC_USE_CTABLE)
 22:   PetscTable     gid1_lid1;
 23:   PetscTablePosition tpos;
 24:   PetscInt       gid,lid;
 25: #else
 26:   PetscInt       Nbs = baij->Nbs,*indices;
 27: #endif  


 31: #if defined (PETSC_USE_CTABLE)
 32:   /* use a table - Mark Adams */
 33:   PetscTableCreate(B->mbs,&gid1_lid1);
 34:   for (i=0; i<B->mbs; i++) {
 35:     for (j=0; j<B->ilen[i]; j++) {
 36:       PetscInt data,gid1 = aj[B->i[i]+j] + 1;
 37:       PetscTableFind(gid1_lid1,gid1,&data);
 38:       if (!data) {
 39:         /* one based table */
 40:         PetscTableAdd(gid1_lid1,gid1,++ec);
 41:       }
 42:     }
 43:   }
 44:   /* form array of columns we need */
 45:   PetscMalloc((ec+1)*sizeof(PetscInt),&garray);
 46:   PetscTableGetHeadPosition(gid1_lid1,&tpos);
 47:   while (tpos) {
 48:     PetscTableGetNext(gid1_lid1,&tpos,&gid,&lid);
 49:     gid--; lid--;
 50:     garray[lid] = gid;
 51:   }
 52:   PetscSortInt(ec,garray);
 53:   PetscTableRemoveAll(gid1_lid1);
 54:   for (i=0; i<ec; i++) {
 55:     PetscTableAdd(gid1_lid1,garray[i]+1,i+1);
 56:   }
 57:   /* compact out the extra columns in B */
 58:   for (i=0; i<B->mbs; i++) {
 59:     for (j=0; j<B->ilen[i]; j++) {
 60:       PetscInt gid1 = aj[B->i[i] + j] + 1;
 61:       PetscTableFind(gid1_lid1,gid1,&lid);
 62:       lid --;
 63:       aj[B->i[i]+j] = lid;
 64:     }
 65:   }
 66:   B->nbs     = ec;
 67:   baij->B->n = ec*mat->bs;
 68:   PetscTableDelete(gid1_lid1);
 69:   /* Mark Adams */
 70: #else
 71:   /* Make an array as long as the number of columns */
 72:   /* mark those columns that are in baij->B */
 73:   PetscMalloc((Nbs+1)*sizeof(PetscInt),&indices);
 74:   PetscMemzero(indices,Nbs*sizeof(PetscInt));
 75:   for (i=0; i<B->mbs; i++) {
 76:     for (j=0; j<B->ilen[i]; j++) {
 77:       if (!indices[aj[B->i[i] + j]]) ec++;
 78:       indices[aj[B->i[i] + j]] = 1;
 79:     }
 80:   }

 82:   /* form array of columns we need */
 83:   PetscMalloc((ec+1)*sizeof(PetscInt),&garray);
 84:   ec = 0;
 85:   for (i=0; i<Nbs; i++) {
 86:     if (indices[i]) {
 87:       garray[ec++] = i;
 88:     }
 89:   }

 91:   /* make indices now point into garray */
 92:   for (i=0; i<ec; i++) {
 93:     indices[garray[i]] = i;
 94:   }

 96:   /* compact out the extra columns in B */
 97:   for (i=0; i<B->mbs; i++) {
 98:     for (j=0; j<B->ilen[i]; j++) {
 99:       aj[B->i[i] + j] = indices[aj[B->i[i] + j]];
100:     }
101:   }
102:   B->nbs       = ec;
103:   baij->B->n   = ec*mat->bs;
104:   PetscFree(indices);
105: #endif  

107:   /* create local vector that is used to scatter into */
108:   VecCreateSeq(PETSC_COMM_SELF,ec*bs,&baij->lvec);

110:   /* create two temporary index sets for building scatter-gather */
111:   for (i=0; i<ec; i++) {
112:     garray[i] = bs*garray[i];
113:   }
114:   ISCreateBlock(PETSC_COMM_SELF,bs,ec,garray,&from);
115:   for (i=0; i<ec; i++) {
116:     garray[i] = garray[i]/bs;
117:   }

119:   PetscMalloc((ec+1)*sizeof(PetscInt),&stmp);
120:   for (i=0; i<ec; i++) { stmp[i] = bs*i; }
121:   ISCreateBlock(PETSC_COMM_SELF,bs,ec,stmp,&to);
122:   PetscFree(stmp);

124:   /* create temporary global vector to generate scatter context */
125:   /* this is inefficient, but otherwise we must do either 
126:      1) save garray until the first actual scatter when the vector is known or
127:      2) have another way of generating a scatter context without a vector.*/
128:   VecCreateMPI(mat->comm,mat->n,mat->N,&gvec);

130:   /* gnerate the scatter context */
131:   VecScatterCreate(gvec,from,baij->lvec,to,&baij->Mvctx);

133:   /*
134:       Post the receives for the first matrix vector product. We sync-chronize after
135:     this on the chance that the user immediately calls MatMult() after assemblying 
136:     the matrix.
137:   */
138:   VecScatterPostRecvs(gvec,baij->lvec,INSERT_VALUES,SCATTER_FORWARD,baij->Mvctx);
139:   MPI_Barrier(mat->comm);

141:   PetscLogObjectParent(mat,baij->Mvctx);
142:   PetscLogObjectParent(mat,baij->lvec);
143:   PetscLogObjectParent(mat,from);
144:   PetscLogObjectParent(mat,to);
145:   baij->garray = garray;
146:   PetscLogObjectMemory(mat,(ec+1)*sizeof(PetscInt));
147:   ISDestroy(from);
148:   ISDestroy(to);
149:   VecDestroy(gvec);
150:   return(0);
151: }

153: /*
154:      Takes the local part of an already assembled MPIBAIJ matrix
155:    and disassembles it. This is to allow new nonzeros into the matrix
156:    that require more communication in the matrix vector multiply. 
157:    Thus certain data-structures must be rebuilt.

159:    Kind of slow! But that's what application programmers get when 
160:    they are sloppy.
161: */
164: PetscErrorCode DisAssemble_MPIBAIJ(Mat A)
165: {
166:   Mat_MPIBAIJ    *baij = (Mat_MPIBAIJ*)A->data;
167:   Mat            B = baij->B,Bnew;
168:   Mat_SeqBAIJ    *Bbaij = (Mat_SeqBAIJ*)B->data;
170:   PetscInt       i,j,mbs=Bbaij->mbs,n = A->N,col,*garray=baij->garray;
171:   PetscInt       bs2 = baij->bs2,*nz,ec,m = A->m;
172:   MatScalar      *a = Bbaij->a;
173:   PetscScalar    *atmp;
174: #if defined(PETSC_USE_MAT_SINGLE)
175:   PetscInt       k;
176: #endif

179:   /* free stuff related to matrix-vec multiply */
180:   VecGetSize(baij->lvec,&ec); /* needed for PetscLogObjectMemory below */
181:   VecDestroy(baij->lvec); baij->lvec = 0;
182:   VecScatterDestroy(baij->Mvctx); baij->Mvctx = 0;
183:   if (baij->colmap) {
184: #if defined (PETSC_USE_CTABLE)
185:     PetscTableDelete(baij->colmap); baij->colmap = 0;
186: #else
187:     PetscFree(baij->colmap);
188:     baij->colmap = 0;
189:     PetscLogObjectMemory(A,-Bbaij->nbs*sizeof(PetscInt));
190: #endif
191:   }

193:   /* make sure that B is assembled so we can access its values */
194:   MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
195:   MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);

197:   /* invent new B and copy stuff over */
198:   PetscMalloc(mbs*sizeof(PetscInt),&nz);
199:   for (i=0; i<mbs; i++) {
200:     nz[i] = Bbaij->i[i+1]-Bbaij->i[i];
201:   }
202:   MatCreate(B->comm,&Bnew);
203:   MatSetSizes(Bnew,m,n,m,n);
204:   MatSetType(Bnew,B->type_name);
205:   MatSeqBAIJSetPreallocation(Bnew,B->bs,0,nz);
206:   MatSetOption(Bnew,MAT_COLUMN_ORIENTED);

208: #if defined(PETSC_USE_MAT_SINGLE)
209:   PetscMalloc(bs2*sizeof(PetscScalar),&atmp);
210: #endif
211:     for (i=0; i<mbs; i++) {
212:       for (j=Bbaij->i[i]; j<Bbaij->i[i+1]; j++) {
213:         col  = garray[Bbaij->j[j]];
214: #if defined(PETSC_USE_MAT_SINGLE)
215:         for (k=0; k<bs2; k++) atmp[k] = a[j*bs2+k];
216: #else
217:         atmp = a + j*bs2;
218: #endif
219:         MatSetValuesBlocked_SeqBAIJ(Bnew,1,&i,1,&col,atmp,B->insertmode);
220:       }
221:     }
222:   MatSetOption(Bnew,MAT_ROW_ORIENTED);

224: #if defined(PETSC_USE_MAT_SINGLE)
225:   PetscFree(atmp);
226: #endif

228:   PetscFree(nz);
229:   PetscFree(baij->garray);
230:   baij->garray = 0;
231:   PetscLogObjectMemory(A,-ec*sizeof(PetscInt));
232:   MatDestroy(B);
233:   PetscLogObjectParent(A,Bnew);
234:   baij->B = Bnew;
235:   A->was_assembled = PETSC_FALSE;
236:   return(0);
237: }

239: /*      ugly stuff added for Glenn someday we should fix this up */

241: static PetscInt *uglyrmapd = 0,*uglyrmapo = 0;  /* mapping from the local ordering to the "diagonal" and "off-diagonal"
242:                                       parts of the local matrix */
243: static Vec uglydd = 0,uglyoo = 0;   /* work vectors used to scale the two parts of the local matrix */


248: PetscErrorCode MatMPIBAIJDiagonalScaleLocalSetUp(Mat inA,Vec scale)
249: {
250:   Mat_MPIBAIJ    *ina = (Mat_MPIBAIJ*) inA->data; /*access private part of matrix */
251:   Mat_SeqBAIJ    *B = (Mat_SeqBAIJ*)ina->B->data;
253:   PetscInt       bs = inA->bs,i,n,nt,j,cstart,cend,no,*garray = ina->garray,*lindices;
254:   PetscInt       *r_rmapd,*r_rmapo;
255: 
257:   MatGetOwnershipRange(inA,&cstart,&cend);
258:   MatGetSize(ina->A,PETSC_NULL,&n);
259:   PetscMalloc((inA->bmapping->n+1)*sizeof(PetscInt),&r_rmapd);
260:   PetscMemzero(r_rmapd,inA->bmapping->n*sizeof(PetscInt));
261:   nt   = 0;
262:   for (i=0; i<inA->bmapping->n; i++) {
263:     if (inA->bmapping->indices[i]*bs >= cstart && inA->bmapping->indices[i]*bs < cend) {
264:       nt++;
265:       r_rmapd[i] = inA->bmapping->indices[i] + 1;
266:     }
267:   }
268:   if (nt*bs != n) SETERRQ2(PETSC_ERR_PLIB,"Hmm nt*bs %D n %D",nt*bs,n);
269:   PetscMalloc((n+1)*sizeof(PetscInt),&uglyrmapd);
270:   for (i=0; i<inA->bmapping->n; i++) {
271:     if (r_rmapd[i]){
272:       for (j=0; j<bs; j++) {
273:         uglyrmapd[(r_rmapd[i]-1)*bs+j-cstart] = i*bs + j;
274:       }
275:     }
276:   }
277:   PetscFree(r_rmapd);
278:   VecCreateSeq(PETSC_COMM_SELF,n,&uglydd);

280:   PetscMalloc((ina->Nbs+1)*sizeof(PetscInt),&lindices);
281:   PetscMemzero(lindices,ina->Nbs*sizeof(PetscInt));
282:   for (i=0; i<B->nbs; i++) {
283:     lindices[garray[i]] = i+1;
284:   }
285:   no   = inA->bmapping->n - nt;
286:   PetscMalloc((inA->bmapping->n+1)*sizeof(PetscInt),&r_rmapo);
287:   PetscMemzero(r_rmapo,inA->bmapping->n*sizeof(PetscInt));
288:   nt   = 0;
289:   for (i=0; i<inA->bmapping->n; i++) {
290:     if (lindices[inA->bmapping->indices[i]]) {
291:       nt++;
292:       r_rmapo[i] = lindices[inA->bmapping->indices[i]];
293:     }
294:   }
295:   if (nt > no) SETERRQ2(PETSC_ERR_PLIB,"Hmm nt %D no %D",nt,n);
296:   PetscFree(lindices);
297:   PetscMalloc((nt*bs+1)*sizeof(PetscInt),&uglyrmapo);
298:   for (i=0; i<inA->bmapping->n; i++) {
299:     if (r_rmapo[i]){
300:       for (j=0; j<bs; j++) {
301:         uglyrmapo[(r_rmapo[i]-1)*bs+j] = i*bs + j;
302:       }
303:     }
304:   }
305:   PetscFree(r_rmapo);
306:   VecCreateSeq(PETSC_COMM_SELF,nt*bs,&uglyoo);

308:   return(0);
309: }

313: PetscErrorCode PETSCMAT_DLLEXPORT MatMPIBAIJDiagonalScaleLocal(Mat A,Vec scale)
314: {
315:   /* This routine should really be abandoned as it duplicates MatDiagonalScaleLocal */
316:   PetscErrorCode ierr,(*f)(Mat,Vec);

319:   PetscObjectQueryFunction((PetscObject)A,"MatDiagonalScaleLocal_C",(void (**)(void))&f);
320:   if (f) {
321:     (*f)(A,scale);
322:   }
323:   return(0);
324: }

329: PetscErrorCode PETSCMAT_DLLEXPORT MatDiagonalScaleLocal_MPIBAIJ(Mat A,Vec scale)
330: {
331:   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*) A->data; /*access private part of matrix */
333:   PetscInt       n,i;
334:   PetscScalar    *d,*o,*s;
335: 
337:   if (!uglyrmapd) {
338:     MatMPIBAIJDiagonalScaleLocalSetUp(A,scale);
339:   }

341:   VecGetArray(scale,&s);
342: 
343:   VecGetLocalSize(uglydd,&n);
344:   VecGetArray(uglydd,&d);
345:   for (i=0; i<n; i++) {
346:     d[i] = s[uglyrmapd[i]]; /* copy "diagonal" (true local) portion of scale into dd vector */
347:   }
348:   VecRestoreArray(uglydd,&d);
349:   /* column scale "diagonal" portion of local matrix */
350:   MatDiagonalScale(a->A,PETSC_NULL,uglydd);

352:   VecGetLocalSize(uglyoo,&n);
353:   VecGetArray(uglyoo,&o);
354:   for (i=0; i<n; i++) {
355:     o[i] = s[uglyrmapo[i]]; /* copy "off-diagonal" portion of scale into oo vector */
356:   }
357:   VecRestoreArray(scale,&s);
358:   VecRestoreArray(uglyoo,&o);
359:   /* column scale "off-diagonal" portion of local matrix */
360:   MatDiagonalScale(a->B,PETSC_NULL,uglyoo);

362:   return(0);
363: }