Actual source code: mmaij.c

  2: /*
  3:    Support for the parallel AIJ matrix vector multiply
  4: */
  5: #include <../src/mat/impls/aij/mpi/mpiaij.h>

  9: PetscErrorCode MatSetUpMultiply_MPIAIJ(Mat mat)
 10: {
 11:   Mat_MPIAIJ         *aij = (Mat_MPIAIJ*)mat->data;
 12:   Mat_SeqAIJ         *B = (Mat_SeqAIJ*)(aij->B->data);
 13:   PetscErrorCode     ierr;
 14:   PetscInt           i,j,*aj = B->j,ec = 0,*garray;
 15:   IS                 from,to;
 16:   Vec                gvec;
 17:   PetscBool          useblockis;
 18: #if defined (PETSC_USE_CTABLE)
 19:   PetscTable         gid1_lid1;
 20:   PetscTablePosition tpos;
 21:   PetscInt           gid,lid;
 22: #else
 23:   PetscInt           N = mat->cmap->N,*indices;
 24: #endif


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

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

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

 92:   /* compact out the extra columns in B */
 93:   for (i=0; i<aij->B->rmap->n; i++) {
 94:     for (j=0; j<B->ilen[i]; j++) {
 95:       aj[B->i[i] + j] = indices[aj[B->i[i] + j]];
 96:     }
 97:   }
 98:   aij->B->cmap->n = aij->B->cmap->N = ec;
 99:   PetscLayoutSetUp((aij->B->cmap));
100:   PetscFree(indices);
101: #endif  
102:   /* create local vector that is used to scatter into */
103:   VecCreateSeq(PETSC_COMM_SELF,ec,&aij->lvec);

105:   /* create two temporary Index sets for build scatter gather */
106:   /*  check for the special case where blocks are communicated for faster VecScatterXXX */
107:   useblockis = PETSC_TRUE;
108:   if (mat->rmap->bs > 1) {
109:     PetscInt bs = mat->rmap->bs,ibs,ga;
110:     if (!(ec % bs)) {
111:       for (i=0; i<ec/bs; i++) {
112:         if ((ga = garray[ibs = i*bs]) % bs) {
113:           useblockis = PETSC_FALSE;
114:           break;
115:         }
116:         for (j=1; j<bs; j++) {
117:           if (garray[ibs+j] != ga+j) {
118:             useblockis = PETSC_FALSE;
119:             break;
120:           }
121:         }
122:         if (!useblockis) break;
123:       }
124:     }
125:   }
126:   if (useblockis) {
127:     PetscInt *ga,bs = mat->rmap->bs,iec = ec/bs;
128:     PetscInfo(mat,"Using block index set to define scatter\n");
129:     PetscMalloc((ec/mat->rmap->bs)*sizeof(PetscInt),&ga);
130:     for (i=0; i<iec; i++) ga[i] = garray[i*bs]/bs;
131:     ISCreateBlock(((PetscObject)mat)->comm,bs,iec,ga,PETSC_OWN_POINTER,&from);
132:   } else {
133:     ISCreateGeneral(((PetscObject)mat)->comm,ec,garray,PETSC_COPY_VALUES,&from);
134:   }
135:   ISCreateStride(PETSC_COMM_SELF,ec,0,1,&to);

137:   /* create temporary global vector to generate scatter context */
138:   /* This does not allocate the array's memory so is efficient */
139:   VecCreateMPIWithArray(((PetscObject)mat)->comm,mat->cmap->n,mat->cmap->N,PETSC_NULL,&gvec);

141:   /* generate the scatter context */
142:   VecScatterCreate(gvec,from,aij->lvec,to,&aij->Mvctx);
143:   PetscLogObjectParent(mat,aij->Mvctx);
144:   PetscLogObjectParent(mat,aij->lvec);
145:   PetscLogObjectParent(mat,from);
146:   PetscLogObjectParent(mat,to);
147:   aij->garray = garray;
148:   PetscLogObjectMemory(mat,(ec+1)*sizeof(PetscInt));
149:   ISDestroy(&from);
150:   ISDestroy(&to);
151:   VecDestroy(&gvec);
152:   return(0);
153: }


158: /*
159:      Takes the local part of an already assembled MPIAIJ matrix
160:    and disassembles it. This is to allow new nonzeros into the matrix
161:    that require more communication in the matrix vector multiply. 
162:    Thus certain data-structures must be rebuilt.

164:    Kind of slow! But that's what application programmers get when 
165:    they are sloppy.
166: */
167: PetscErrorCode DisAssemble_MPIAIJ(Mat A)
168: {
169:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)A->data;
170:   Mat            B = aij->B,Bnew;
171:   Mat_SeqAIJ     *Baij = (Mat_SeqAIJ*)B->data;
173:   PetscInt       i,j,m = B->rmap->n,n = A->cmap->N,col,ct = 0,*garray = aij->garray,*nz,ec;
174:   PetscScalar    v;

177:   /* free stuff related to matrix-vec multiply */
178:   VecGetSize(aij->lvec,&ec); /* needed for PetscLogObjectMemory below */
179:   VecDestroy(&aij->lvec); aij->lvec = 0;
180:   VecScatterDestroy(&aij->Mvctx); aij->Mvctx = 0;
181:   if (aij->colmap) {
182: #if defined (PETSC_USE_CTABLE)
183:     PetscTableDestroy(&aij->colmap);
184: #else
185:     PetscFree(aij->colmap);
186:     PetscLogObjectMemory(A,-aij->B->cmap->n*sizeof(PetscInt));
187: #endif
188:   }

190:   /* make sure that B is assembled so we can access its values */
191:   MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
192:   MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);

194:   /* invent new B and copy stuff over */
195:   PetscMalloc((m+1)*sizeof(PetscInt),&nz);
196:   for (i=0; i<m; i++) {
197:     nz[i] = Baij->i[i+1] - Baij->i[i];
198:   }
199:   MatCreate(PETSC_COMM_SELF,&Bnew);
200:   MatSetSizes(Bnew,m,n,m,n);
201:   MatSetType(Bnew,((PetscObject)B)->type_name);
202:   MatSeqAIJSetPreallocation(Bnew,0,nz);
203:   PetscFree(nz);
204:   for (i=0; i<m; i++) {
205:     for (j=Baij->i[i]; j<Baij->i[i+1]; j++) {
206:       col  = garray[Baij->j[ct]];
207:       v    = Baij->a[ct++];
208:       MatSetValues(Bnew,1,&i,1,&col,&v,B->insertmode);
209:     }
210:   }
211:   PetscFree(aij->garray);
212:   PetscLogObjectMemory(A,-ec*sizeof(PetscInt));
213:   MatDestroy(&B);
214:   PetscLogObjectParent(A,Bnew);
215:   aij->B = Bnew;
216:   A->was_assembled = PETSC_FALSE;
217:   return(0);
218: }

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

222: static PetscInt *auglyrmapd = 0,*auglyrmapo = 0;  /* mapping from the local ordering to the "diagonal" and "off-diagonal"
223:                                       parts of the local matrix */
224: static Vec auglydd = 0,auglyoo = 0;   /* work vectors used to scale the two parts of the local matrix */


229: PetscErrorCode MatMPIAIJDiagonalScaleLocalSetUp(Mat inA,Vec scale)
230: {
231:   Mat_MPIAIJ     *ina = (Mat_MPIAIJ*) inA->data; /*access private part of matrix */
233:   PetscInt       i,n,nt,cstart,cend,no,*garray = ina->garray,*lindices;
234:   PetscInt       *r_rmapd,*r_rmapo;
235: 
237:   MatGetOwnershipRange(inA,&cstart,&cend);
238:   MatGetSize(ina->A,PETSC_NULL,&n);
239:   PetscMalloc((inA->rmap->mapping->n+1)*sizeof(PetscInt),&r_rmapd);
240:   PetscMemzero(r_rmapd,inA->rmap->mapping->n*sizeof(PetscInt));
241:   nt   = 0;
242:   for (i=0; i<inA->rmap->mapping->n; i++) {
243:     if (inA->rmap->mapping->indices[i] >= cstart && inA->rmap->mapping->indices[i] < cend) {
244:       nt++;
245:       r_rmapd[i] = inA->rmap->mapping->indices[i] + 1;
246:     }
247:   }
248:   if (nt != n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Hmm nt %D n %D",nt,n);
249:   PetscMalloc((n+1)*sizeof(PetscInt),&auglyrmapd);
250:   for (i=0; i<inA->rmap->mapping->n; i++) {
251:     if (r_rmapd[i]){
252:       auglyrmapd[(r_rmapd[i]-1)-cstart] = i;
253:     }
254:   }
255:   PetscFree(r_rmapd);
256:   VecCreateSeq(PETSC_COMM_SELF,n,&auglydd);

258:   PetscMalloc((inA->cmap->N+1)*sizeof(PetscInt),&lindices);
259:   PetscMemzero(lindices,inA->cmap->N*sizeof(PetscInt));
260:   for (i=0; i<ina->B->cmap->n; i++) {
261:     lindices[garray[i]] = i+1;
262:   }
263:   no   = inA->rmap->mapping->n - nt;
264:   PetscMalloc((inA->rmap->mapping->n+1)*sizeof(PetscInt),&r_rmapo);
265:   PetscMemzero(r_rmapo,inA->rmap->mapping->n*sizeof(PetscInt));
266:   nt   = 0;
267:   for (i=0; i<inA->rmap->mapping->n; i++) {
268:     if (lindices[inA->rmap->mapping->indices[i]]) {
269:       nt++;
270:       r_rmapo[i] = lindices[inA->rmap->mapping->indices[i]];
271:     }
272:   }
273:   if (nt > no) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Hmm nt %D no %D",nt,n);
274:   PetscFree(lindices);
275:   PetscMalloc((nt+1)*sizeof(PetscInt),&auglyrmapo);
276:   for (i=0; i<inA->rmap->mapping->n; i++) {
277:     if (r_rmapo[i]){
278:       auglyrmapo[(r_rmapo[i]-1)] = i;
279:     }
280:   }
281:   PetscFree(r_rmapo);
282:   VecCreateSeq(PETSC_COMM_SELF,nt,&auglyoo);

284:   return(0);
285: }

289: PetscErrorCode MatMPIAIJDiagonalScaleLocal(Mat A,Vec scale)
290: {
291:   /* This routine should really be abandoned as it duplicates MatDiagonalScaleLocal */

295:   PetscTryMethod(A,"MatDiagonalScaleLocal_C",(Mat,Vec),(A,scale));
296:   return(0);
297: }

302: PetscErrorCode  MatDiagonalScaleLocal_MPIAIJ(Mat A,Vec scale)
303: {
304:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*) A->data; /*access private part of matrix */
306:   PetscInt       n,i;
307:   PetscScalar    *d,*o,*s;
308: 
310:   if (!auglyrmapd) {
311:     MatMPIAIJDiagonalScaleLocalSetUp(A,scale);
312:   }

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

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

335:   return(0);
336: }