Actual source code: mmbaij.c

  1: /*$Id: mmbaij.c,v 1.46 2001/09/25 00:31:36 balay Exp $*/

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

  9: EXTERN int MatSetValuesBlocked_SeqBAIJ(Mat,int,int*,int,int*,PetscScalar*,InsertMode);

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


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

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

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

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

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

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

116:   PetscMalloc((ec+1)*sizeof(int),&stmp);
117:   for (i=0; i<ec; i++) { stmp[i] = bs*i; }
118:   ISCreateBlock(PETSC_COMM_SELF,bs,ec,stmp,&to);
119:   PetscFree(stmp);

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

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

130:   /*
131:       Post the receives for the first matrix vector product. We sync-chronize after
132:     this on the chance that the user immediately calls MatMult() after assemblying 
133:     the matrix.
134:   */
135:   VecScatterPostRecvs(gvec,baij->lvec,INSERT_VALUES,SCATTER_FORWARD,baij->Mvctx);
136:   MPI_Barrier(mat->comm);

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

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

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

173:   /* free stuff related to matrix-vec multiply */
174:   VecGetSize(baij->lvec,&ec); /* needed for PetscLogObjectMemory below */
175:   VecDestroy(baij->lvec); baij->lvec = 0;
176:   VecScatterDestroy(baij->Mvctx); baij->Mvctx = 0;
177:   if (baij->colmap) {
178: #if defined (PETSC_USE_CTABLE)
179:     PetscTableDelete(baij->colmap); baij->colmap = 0;
180: #else
181:     PetscFree(baij->colmap);
182:     baij->colmap = 0;
183:     PetscLogObjectMemory(A,-Bbaij->nbs*sizeof(int));
184: #endif
185:   }

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

191:   /* invent new B and copy stuff over */
192:   PetscMalloc(mbs*sizeof(int),&nz);
193:   for (i=0; i<mbs; i++) {
194:     nz[i] = Bbaij->i[i+1]-Bbaij->i[i];
195:   }
196:   MatCreateSeqBAIJ(PETSC_COMM_SELF,baij->bs,m,n,0,nz,&Bnew);
197:   MatSetOption(Bnew,MAT_COLUMN_ORIENTED);

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

215: #if defined(PETSC_USE_MAT_SINGLE)
216:   PetscFree(atmp);
217: #endif

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

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

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


237: int MatMPIBAIJDiagonalScaleLocalSetUp(Mat inA,Vec scale)
238: {
239:   Mat_MPIBAIJ  *ina = (Mat_MPIBAIJ*) inA->data; /*access private part of matrix */
240:   Mat_SeqBAIJ  *A = (Mat_SeqBAIJ*)ina->A->data;
241:   Mat_SeqBAIJ  *B = (Mat_SeqBAIJ*)ina->B->data;
242:   int          ierr,bs = A->bs,i,n,nt,j,cstart,cend,no,*garray = ina->garray,*lindices;
243:   int          *r_rmapd,*r_rmapo;
244: 
246:   MatGetOwnershipRange(inA,&cstart,&cend);
247:   MatGetSize(ina->A,PETSC_NULL,&n);
248:   PetscMalloc((inA->bmapping->n+1)*sizeof(int),&r_rmapd);
249:   PetscMemzero(r_rmapd,inA->bmapping->n*sizeof(int));
250:   nt   = 0;
251:   for (i=0; i<inA->bmapping->n; i++) {
252:     if (inA->bmapping->indices[i]*bs >= cstart && inA->bmapping->indices[i]*bs < cend) {
253:       nt++;
254:       r_rmapd[i] = inA->bmapping->indices[i] + 1;
255:     }
256:   }
257:   if (nt*bs != n) SETERRQ2(1,"Hmm nt*bs %d n %d",nt*bs,n);
258:   PetscMalloc((n+1)*sizeof(int),&uglyrmapd);
259:   for (i=0; i<inA->bmapping->n; i++) {
260:     if (r_rmapd[i]){
261:       for (j=0; j<bs; j++) {
262:         uglyrmapd[(r_rmapd[i]-1)*bs+j-cstart] = i*bs + j;
263:       }
264:     }
265:   }
266:   PetscFree(r_rmapd);
267:   VecCreateSeq(PETSC_COMM_SELF,n,&uglydd);

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

297:   return(0);
298: }

300: int MatMPIBAIJDiagonalScaleLocal(Mat A,Vec scale)
301: {
302:   Mat_MPIBAIJ  *a = (Mat_MPIBAIJ*) A->data; /*access private part of matrix */
303:   int          ierr,n,i;
304:   PetscScalar  *d,*o,*s;
305: 
307:   if (!uglyrmapd) {
308:     MatMPIBAIJDiagonalScaleLocalSetUp(A,scale);
309:   }

311:   VecGetArray(scale,&s);
312: 
313:   VecGetLocalSize(uglydd,&n);
314:   VecGetArray(uglydd,&d);
315:   for (i=0; i<n; i++) {
316:     d[i] = s[uglyrmapd[i]]; /* copy "diagonal" (true local) portion of scale into dd vector */
317:   }
318:   VecRestoreArray(uglydd,&d);
319:   /* column scale "diagonal" portion of local matrix */
320:   MatDiagonalScale(a->A,PETSC_NULL,uglydd);

322:   VecGetLocalSize(uglyoo,&n);
323:   VecGetArray(uglyoo,&o);
324:   for (i=0; i<n; i++) {
325:     o[i] = s[uglyrmapo[i]]; /* copy "off-diagonal" portion of scale into oo vector */
326:   }
327:   VecRestoreArray(scale,&s);
328:   VecRestoreArray(uglyoo,&o);
329:   /* column scale "off-diagonal" portion of local matrix */
330:   MatDiagonalScale(a->B,PETSC_NULL,uglyoo);

332:   return(0);
333: }