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->rmap.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->cmap.n = baij->B->cmap.N = ec*mat->rmap.bs;
 68:   PetscMapInitialize(baij->B->comm,&(baij->B->cmap));
 69:   PetscTableDelete(gid1_lid1);
 70:   /* Mark Adams */
 71: #else
 72:   /* Make an array as long as the number of columns */
 73:   /* mark those columns that are in baij->B */
 74:   PetscMalloc((Nbs+1)*sizeof(PetscInt),&indices);
 75:   PetscMemzero(indices,Nbs*sizeof(PetscInt));
 76:   for (i=0; i<B->mbs; i++) {
 77:     for (j=0; j<B->ilen[i]; j++) {
 78:       if (!indices[aj[B->i[i] + j]]) ec++;
 79:       indices[aj[B->i[i] + j]] = 1;
 80:     }
 81:   }

 83:   /* form array of columns we need */
 84:   PetscMalloc((ec+1)*sizeof(PetscInt),&garray);
 85:   ec = 0;
 86:   for (i=0; i<Nbs; i++) {
 87:     if (indices[i]) {
 88:       garray[ec++] = i;
 89:     }
 90:   }

 92:   /* make indices now point into garray */
 93:   for (i=0; i<ec; i++) {
 94:     indices[garray[i]] = i;
 95:   }

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

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

112:   /* create two temporary index sets for building scatter-gather */
113:   for (i=0; i<ec; i++) {
114:     garray[i] = bs*garray[i];
115:   }
116:   ISCreateBlock(PETSC_COMM_SELF,bs,ec,garray,&from);
117:   for (i=0; i<ec; i++) {
118:     garray[i] = garray[i]/bs;
119:   }

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

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

132:   VecScatterCreate(gvec,from,baij->lvec,to,&baij->Mvctx);

134:   PetscLogObjectParent(mat,baij->Mvctx);
135:   PetscLogObjectParent(mat,baij->lvec);
136:   PetscLogObjectParent(mat,from);
137:   PetscLogObjectParent(mat,to);
138:   baij->garray = garray;
139:   PetscLogObjectMemory(mat,(ec+1)*sizeof(PetscInt));
140:   ISDestroy(from);
141:   ISDestroy(to);
142:   VecDestroy(gvec);
143:   return(0);
144: }

146: /*
147:      Takes the local part of an already assembled MPIBAIJ matrix
148:    and disassembles it. This is to allow new nonzeros into the matrix
149:    that require more communication in the matrix vector multiply. 
150:    Thus certain data-structures must be rebuilt.

152:    Kind of slow! But that's what application programmers get when 
153:    they are sloppy.
154: */
157: PetscErrorCode DisAssemble_MPIBAIJ(Mat A)
158: {
159:   Mat_MPIBAIJ    *baij = (Mat_MPIBAIJ*)A->data;
160:   Mat            B = baij->B,Bnew;
161:   Mat_SeqBAIJ    *Bbaij = (Mat_SeqBAIJ*)B->data;
163:   PetscInt       i,j,mbs=Bbaij->mbs,n = A->cmap.n,col,*garray=baij->garray;
164:   PetscInt       bs2 = baij->bs2,*nz,ec,m = A->rmap.n;
165:   MatScalar      *a = Bbaij->a;
166:   PetscScalar    *atmp;
167: #if defined(PETSC_USE_MAT_SINGLE)
168:   PetscInt       k;
169: #endif

172:   /* free stuff related to matrix-vec multiply */
173:   VecGetSize(baij->lvec,&ec); /* needed for PetscLogObjectMemory below */
174:   VecDestroy(baij->lvec); baij->lvec = 0;
175:   VecScatterDestroy(baij->Mvctx); baij->Mvctx = 0;
176:   if (baij->colmap) {
177: #if defined (PETSC_USE_CTABLE)
178:     PetscTableDelete(baij->colmap); baij->colmap = 0;
179: #else
180:     PetscFree(baij->colmap);
181:     baij->colmap = 0;
182:     PetscLogObjectMemory(A,-Bbaij->nbs*sizeof(PetscInt));
183: #endif
184:   }

186:   /* make sure that B is assembled so we can access its values */
187:   MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
188:   MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);

190:   /* invent new B and copy stuff over */
191:   PetscMalloc(mbs*sizeof(PetscInt),&nz);
192:   for (i=0; i<mbs; i++) {
193:     nz[i] = Bbaij->i[i+1]-Bbaij->i[i];
194:   }
195:   MatCreate(B->comm,&Bnew);
196:   MatSetSizes(Bnew,m,n,m,n);
197:   MatSetType(Bnew,B->type_name);
198:   MatSeqBAIJSetPreallocation(Bnew,B->rmap.bs,0,nz);
199:   MatSetOption(Bnew,MAT_COLUMN_ORIENTED);

201: #if defined(PETSC_USE_MAT_SINGLE)
202:   PetscMalloc(bs2*sizeof(PetscScalar),&atmp);
203: #endif
204:     for (i=0; i<mbs; i++) {
205:       for (j=Bbaij->i[i]; j<Bbaij->i[i+1]; j++) {
206:         col  = garray[Bbaij->j[j]];
207: #if defined(PETSC_USE_MAT_SINGLE)
208:         for (k=0; k<bs2; k++) atmp[k] = a[j*bs2+k];
209: #else
210:         atmp = a + j*bs2;
211: #endif
212:         MatSetValuesBlocked_SeqBAIJ(Bnew,1,&i,1,&col,atmp,B->insertmode);
213:       }
214:     }
215:   MatSetOption(Bnew,MAT_ROW_ORIENTED);

217: #if defined(PETSC_USE_MAT_SINGLE)
218:   PetscFree(atmp);
219: #endif

221:   PetscFree(nz);
222:   PetscFree(baij->garray);
223:   baij->garray = 0;
224:   PetscLogObjectMemory(A,-ec*sizeof(PetscInt));
225:   MatDestroy(B);
226:   PetscLogObjectParent(A,Bnew);
227:   baij->B = Bnew;
228:   A->was_assembled = PETSC_FALSE;
229:   return(0);
230: }

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

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


241: PetscErrorCode MatMPIBAIJDiagonalScaleLocalSetUp(Mat inA,Vec scale)
242: {
243:   Mat_MPIBAIJ    *ina = (Mat_MPIBAIJ*) inA->data; /*access private part of matrix */
244:   Mat_SeqBAIJ    *B = (Mat_SeqBAIJ*)ina->B->data;
246:   PetscInt       bs = inA->rmap.bs,i,n,nt,j,cstart,cend,no,*garray = ina->garray,*lindices;
247:   PetscInt       *r_rmapd,*r_rmapo;
248: 
250:   MatGetOwnershipRange(inA,&cstart,&cend);
251:   MatGetSize(ina->A,PETSC_NULL,&n);
252:   PetscMalloc((inA->bmapping->n+1)*sizeof(PetscInt),&r_rmapd);
253:   PetscMemzero(r_rmapd,inA->bmapping->n*sizeof(PetscInt));
254:   nt   = 0;
255:   for (i=0; i<inA->bmapping->n; i++) {
256:     if (inA->bmapping->indices[i]*bs >= cstart && inA->bmapping->indices[i]*bs < cend) {
257:       nt++;
258:       r_rmapd[i] = inA->bmapping->indices[i] + 1;
259:     }
260:   }
261:   if (nt*bs != n) SETERRQ2(PETSC_ERR_PLIB,"Hmm nt*bs %D n %D",nt*bs,n);
262:   PetscMalloc((n+1)*sizeof(PetscInt),&uglyrmapd);
263:   for (i=0; i<inA->bmapping->n; i++) {
264:     if (r_rmapd[i]){
265:       for (j=0; j<bs; j++) {
266:         uglyrmapd[(r_rmapd[i]-1)*bs+j-cstart] = i*bs + j;
267:       }
268:     }
269:   }
270:   PetscFree(r_rmapd);
271:   VecCreateSeq(PETSC_COMM_SELF,n,&uglydd);

273:   PetscMalloc((ina->Nbs+1)*sizeof(PetscInt),&lindices);
274:   PetscMemzero(lindices,ina->Nbs*sizeof(PetscInt));
275:   for (i=0; i<B->nbs; i++) {
276:     lindices[garray[i]] = i+1;
277:   }
278:   no   = inA->bmapping->n - nt;
279:   PetscMalloc((inA->bmapping->n+1)*sizeof(PetscInt),&r_rmapo);
280:   PetscMemzero(r_rmapo,inA->bmapping->n*sizeof(PetscInt));
281:   nt   = 0;
282:   for (i=0; i<inA->bmapping->n; i++) {
283:     if (lindices[inA->bmapping->indices[i]]) {
284:       nt++;
285:       r_rmapo[i] = lindices[inA->bmapping->indices[i]];
286:     }
287:   }
288:   if (nt > no) SETERRQ2(PETSC_ERR_PLIB,"Hmm nt %D no %D",nt,n);
289:   PetscFree(lindices);
290:   PetscMalloc((nt*bs+1)*sizeof(PetscInt),&uglyrmapo);
291:   for (i=0; i<inA->bmapping->n; i++) {
292:     if (r_rmapo[i]){
293:       for (j=0; j<bs; j++) {
294:         uglyrmapo[(r_rmapo[i]-1)*bs+j] = i*bs + j;
295:       }
296:     }
297:   }
298:   PetscFree(r_rmapo);
299:   VecCreateSeq(PETSC_COMM_SELF,nt*bs,&uglyoo);

301:   return(0);
302: }

306: PetscErrorCode  MatMPIBAIJDiagonalScaleLocal(Mat A,Vec scale)
307: {
308:   /* This routine should really be abandoned as it duplicates MatDiagonalScaleLocal */
309:   PetscErrorCode ierr,(*f)(Mat,Vec);

312:   PetscObjectQueryFunction((PetscObject)A,"MatDiagonalScaleLocal_C",(void (**)(void))&f);
313:   if (f) {
314:     (*f)(A,scale);
315:   }
316:   return(0);
317: }

322: PetscErrorCode  MatDiagonalScaleLocal_MPIBAIJ(Mat A,Vec scale)
323: {
324:   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*) A->data; /*access private part of matrix */
326:   PetscInt       n,i;
327:   PetscScalar    *d,*o,*s;
328: 
330:   if (!uglyrmapd) {
331:     MatMPIBAIJDiagonalScaleLocalSetUp(A,scale);
332:   }

334:   VecGetArray(scale,&s);
335: 
336:   VecGetLocalSize(uglydd,&n);
337:   VecGetArray(uglydd,&d);
338:   for (i=0; i<n; i++) {
339:     d[i] = s[uglyrmapd[i]]; /* copy "diagonal" (true local) portion of scale into dd vector */
340:   }
341:   VecRestoreArray(uglydd,&d);
342:   /* column scale "diagonal" portion of local matrix */
343:   MatDiagonalScale(a->A,PETSC_NULL,uglydd);

345:   VecGetLocalSize(uglyoo,&n);
346:   VecGetArray(uglyoo,&o);
347:   for (i=0; i<n; i++) {
348:     o[i] = s[uglyrmapo[i]]; /* copy "off-diagonal" portion of scale into oo vector */
349:   }
350:   VecRestoreArray(scale,&s);
351:   VecRestoreArray(uglyoo,&o);
352:   /* column scale "off-diagonal" portion of local matrix */
353:   MatDiagonalScale(a->B,PETSC_NULL,uglyoo);

355:   return(0);
356: }