Actual source code: redistribute.c

petsc-3.9.0 2018-04-07
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  2: /*
  3:   This file defines a "solve the problem redistributely on each subgroup of processor" preconditioner.
  4: */
  5:  #include <petsc/private/pcimpl.h>
  6:  #include <petscksp.h>

  8: typedef struct {
  9:   KSP         ksp;
 10:   Vec         x,b;
 11:   VecScatter  scatter;
 12:   IS          is;
 13:   PetscInt    dcnt,*drows;    /* these are the local rows that have only diagonal entry */
 14:   PetscScalar *diag;
 15:   Vec         work;
 16: } PC_Redistribute;

 18: static PetscErrorCode PCView_Redistribute(PC pc,PetscViewer viewer)
 19: {
 20:   PC_Redistribute *red = (PC_Redistribute*)pc->data;
 21:   PetscErrorCode  ierr;
 22:   PetscBool       iascii,isstring;
 23:   PetscInt        ncnt,N;

 26:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
 27:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSTRING,&isstring);
 28:   if (iascii) {
 29:     MPIU_Allreduce(&red->dcnt,&ncnt,1,MPIU_INT,MPI_SUM,PetscObjectComm((PetscObject)pc));
 30:     MatGetSize(pc->pmat,&N,NULL);
 31:     PetscViewerASCIIPrintf(viewer,"    Number rows eliminated %D Percentage rows eliminated %g\n",ncnt,100.0*((PetscReal)ncnt)/((PetscReal)N));
 32:     PetscViewerASCIIPrintf(viewer,"  Redistribute preconditioner: \n");
 33:     KSPView(red->ksp,viewer);
 34:   } else if (isstring) {
 35:     PetscViewerStringSPrintf(viewer," Redistribute preconditioner");
 36:     KSPView(red->ksp,viewer);
 37:   }
 38:   return(0);
 39: }

 41: static PetscErrorCode PCSetUp_Redistribute(PC pc)
 42: {
 43:   PC_Redistribute   *red = (PC_Redistribute*)pc->data;
 44:   PetscErrorCode    ierr;
 45:   MPI_Comm          comm;
 46:   PetscInt          rstart,rend,i,nz,cnt,*rows,ncnt,dcnt,*drows;
 47:   PetscLayout       map,nmap;
 48:   PetscMPIInt       size,imdex,tag,n;
 49:   PetscInt          *source = NULL;
 50:   PetscMPIInt       *sizes = NULL,nrecvs;
 51:   PetscInt          j,nsends;
 52:   PetscInt          *owner = NULL,*starts = NULL,count,slen;
 53:   PetscInt          *rvalues,*svalues,recvtotal;
 54:   PetscMPIInt       *onodes1,*olengths1;
 55:   MPI_Request       *send_waits = NULL,*recv_waits = NULL;
 56:   MPI_Status        recv_status,*send_status;
 57:   Vec               tvec,diag;
 58:   Mat               tmat;
 59:   const PetscScalar *d;

 62:   if (pc->setupcalled) {
 63:     KSPGetOperators(red->ksp,NULL,&tmat);
 64:     MatCreateSubMatrix(pc->pmat,red->is,red->is,MAT_REUSE_MATRIX,&tmat);
 65:     KSPSetOperators(red->ksp,tmat,tmat);
 66:   } else {
 67:     PetscInt NN;

 69:     PetscObjectGetComm((PetscObject)pc,&comm);
 70:     MPI_Comm_size(comm,&size);
 71:     PetscObjectGetNewTag((PetscObject)pc,&tag);

 73:     /* count non-diagonal rows on process */
 74:     MatGetOwnershipRange(pc->mat,&rstart,&rend);
 75:     cnt  = 0;
 76:     for (i=rstart; i<rend; i++) {
 77:       MatGetRow(pc->mat,i,&nz,NULL,NULL);
 78:       if (nz > 1) cnt++;
 79:       MatRestoreRow(pc->mat,i,&nz,NULL,NULL);
 80:     }
 81:     PetscMalloc1(cnt,&rows);
 82:     PetscMalloc1(rend - rstart - cnt,&drows);

 84:     /* list non-diagonal rows on process */
 85:     cnt = 0; dcnt = 0;
 86:     for (i=rstart; i<rend; i++) {
 87:       MatGetRow(pc->mat,i,&nz,NULL,NULL);
 88:       if (nz > 1) rows[cnt++] = i;
 89:       else drows[dcnt++] = i - rstart;
 90:       MatRestoreRow(pc->mat,i,&nz,NULL,NULL);
 91:     }

 93:     /* create PetscLayout for non-diagonal rows on each process */
 94:     PetscLayoutCreate(comm,&map);
 95:     PetscLayoutSetLocalSize(map,cnt);
 96:     PetscLayoutSetBlockSize(map,1);
 97:     PetscLayoutSetUp(map);
 98:     rstart = map->rstart;
 99:     rend   = map->rend;

101:     /* create PetscLayout for load-balanced non-diagonal rows on each process */
102:     PetscLayoutCreate(comm,&nmap);
103:     MPIU_Allreduce(&cnt,&ncnt,1,MPIU_INT,MPI_SUM,comm);
104:     PetscLayoutSetSize(nmap,ncnt);
105:     PetscLayoutSetBlockSize(nmap,1);
106:     PetscLayoutSetUp(nmap);

108:     MatGetSize(pc->pmat,&NN,NULL);
109:     PetscInfo2(pc,"Number of diagonal rows eliminated %d, percentage eliminated %g\n",NN-ncnt,((PetscReal)(NN-ncnt))/((PetscReal)(NN)));
110:     /*
111:         this code is taken from VecScatterCreate_PtoS()
112:         Determines what rows need to be moved where to
113:         load balance the non-diagonal rows
114:     */
115:     /*  count number of contributors to each processor */
116:     PetscMalloc2(size,&sizes,cnt,&owner);
117:     PetscMemzero(sizes,size*sizeof(PetscMPIInt));
118:     j      = 0;
119:     nsends = 0;
120:     for (i=rstart; i<rend; i++) {
121:       if (i < nmap->range[j]) j = 0;
122:       for (; j<size; j++) {
123:         if (i < nmap->range[j+1]) {
124:           if (!sizes[j]++) nsends++;
125:           owner[i-rstart] = j;
126:           break;
127:         }
128:       }
129:     }
130:     /* inform other processors of number of messages and max length*/
131:     PetscGatherNumberOfMessages(comm,NULL,sizes,&nrecvs);
132:     PetscGatherMessageLengths(comm,nsends,nrecvs,sizes,&onodes1,&olengths1);
133:     PetscSortMPIIntWithArray(nrecvs,onodes1,olengths1);
134:     recvtotal = 0; for (i=0; i<nrecvs; i++) recvtotal += olengths1[i];

136:     /* post receives:  rvalues - rows I will own; count - nu */
137:     PetscMalloc3(recvtotal,&rvalues,nrecvs,&source,nrecvs,&recv_waits);
138:     count = 0;
139:     for (i=0; i<nrecvs; i++) {
140:       MPI_Irecv((rvalues+count),olengths1[i],MPIU_INT,onodes1[i],tag,comm,recv_waits+i);
141:       count += olengths1[i];
142:     }

144:     /* do sends:
145:        1) starts[i] gives the starting index in svalues for stuff going to
146:        the ith processor
147:     */
148:     PetscMalloc3(cnt,&svalues,nsends,&send_waits,size,&starts);
149:     starts[0] = 0;
150:     for (i=1; i<size; i++) starts[i] = starts[i-1] + sizes[i-1];
151:     for (i=0; i<cnt; i++)  svalues[starts[owner[i]]++] = rows[i];
152:     for (i=0; i<cnt; i++)  rows[i] = rows[i] - rstart;
153:     red->drows = drows;
154:     red->dcnt  = dcnt;
155:     PetscFree(rows);

157:     starts[0] = 0;
158:     for (i=1; i<size; i++) starts[i] = starts[i-1] + sizes[i-1];
159:     count = 0;
160:     for (i=0; i<size; i++) {
161:       if (sizes[i]) {
162:         MPI_Isend(svalues+starts[i],sizes[i],MPIU_INT,i,tag,comm,send_waits+count++);
163:       }
164:     }

166:     /*  wait on receives */
167:     count = nrecvs;
168:     slen  = 0;
169:     while (count) {
170:       MPI_Waitany(nrecvs,recv_waits,&imdex,&recv_status);
171:       /* unpack receives into our local space */
172:       MPI_Get_count(&recv_status,MPIU_INT,&n);
173:       slen += n;
174:       count--;
175:     }
176:     if (slen != recvtotal) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Total message lengths %D not expected %D",slen,recvtotal);

178:     ISCreateGeneral(comm,slen,rvalues,PETSC_COPY_VALUES,&red->is);

180:     /* free up all work space */
181:     PetscFree(olengths1);
182:     PetscFree(onodes1);
183:     PetscFree3(rvalues,source,recv_waits);
184:     PetscFree2(sizes,owner);
185:     if (nsends) {   /* wait on sends */
186:       PetscMalloc1(nsends,&send_status);
187:       MPI_Waitall(nsends,send_waits,send_status);
188:       PetscFree(send_status);
189:     }
190:     PetscFree3(svalues,send_waits,starts);
191:     PetscLayoutDestroy(&map);
192:     PetscLayoutDestroy(&nmap);

194:     VecCreateMPI(comm,slen,PETSC_DETERMINE,&red->b);
195:     VecDuplicate(red->b,&red->x);
196:     MatCreateVecs(pc->pmat,&tvec,NULL);
197:     VecScatterCreate(tvec,red->is,red->b,NULL,&red->scatter);
198:     VecDestroy(&tvec);
199:     MatCreateSubMatrix(pc->pmat,red->is,red->is,MAT_INITIAL_MATRIX,&tmat);
200:     KSPSetOperators(red->ksp,tmat,tmat);
201:     MatDestroy(&tmat);
202:   }

204:   /* get diagonal portion of matrix */
205:   PetscFree(red->diag);
206:   PetscMalloc1(red->dcnt,&red->diag);
207:   MatCreateVecs(pc->pmat,&diag,NULL);
208:   MatGetDiagonal(pc->pmat,diag);
209:   VecGetArrayRead(diag,&d);
210:   for (i=0; i<red->dcnt; i++) red->diag[i] = 1.0/d[red->drows[i]];
211:   VecRestoreArrayRead(diag,&d);
212:   VecDestroy(&diag);
213:   KSPSetUp(red->ksp);
214:   return(0);
215: }

217: static PetscErrorCode PCApply_Redistribute(PC pc,Vec b,Vec x)
218: {
219:   PC_Redistribute   *red = (PC_Redistribute*)pc->data;
220:   PetscErrorCode    ierr;
221:   PetscInt          dcnt   = red->dcnt,i;
222:   const PetscInt    *drows = red->drows;
223:   PetscScalar       *xwork;
224:   const PetscScalar *bwork,*diag = red->diag;

227:   if (!red->work) {
228:     VecDuplicate(b,&red->work);
229:   }
230:   /* compute the rows of solution that have diagonal entries only */
231:   VecSet(x,0.0);         /* x = diag(A)^{-1} b */
232:   VecGetArray(x,&xwork);
233:   VecGetArrayRead(b,&bwork);
234:   for (i=0; i<dcnt; i++) xwork[drows[i]] = diag[i]*bwork[drows[i]];
235:   PetscLogFlops(dcnt);
236:   VecRestoreArray(red->work,&xwork);
237:   VecRestoreArrayRead(b,&bwork);
238:   /* update the right hand side for the reduced system with diagonal rows (and corresponding columns) removed */
239:   MatMult(pc->pmat,x,red->work);
240:   VecAYPX(red->work,-1.0,b);   /* red->work = b - A x */

242:   VecScatterBegin(red->scatter,red->work,red->b,INSERT_VALUES,SCATTER_FORWARD);
243:   VecScatterEnd(red->scatter,red->work,red->b,INSERT_VALUES,SCATTER_FORWARD);
244:   KSPSolve(red->ksp,red->b,red->x);
245:   VecScatterBegin(red->scatter,red->x,x,INSERT_VALUES,SCATTER_REVERSE);
246:   VecScatterEnd(red->scatter,red->x,x,INSERT_VALUES,SCATTER_REVERSE);
247:   return(0);
248: }

250: static PetscErrorCode PCDestroy_Redistribute(PC pc)
251: {
252:   PC_Redistribute *red = (PC_Redistribute*)pc->data;
253:   PetscErrorCode  ierr;

256:   VecScatterDestroy(&red->scatter);
257:   ISDestroy(&red->is);
258:   VecDestroy(&red->b);
259:   VecDestroy(&red->x);
260:   KSPDestroy(&red->ksp);
261:   VecDestroy(&red->work);
262:   PetscFree(red->drows);
263:   PetscFree(red->diag);
264:   PetscFree(pc->data);
265:   return(0);
266: }

268: static PetscErrorCode PCSetFromOptions_Redistribute(PetscOptionItems *PetscOptionsObject,PC pc)
269: {
270:   PetscErrorCode  ierr;
271:   PC_Redistribute *red = (PC_Redistribute*)pc->data;

274:   KSPSetFromOptions(red->ksp);
275:   return(0);
276: }

278: /*@
279:    PCRedistributeGetKSP - Gets the KSP created by the PCREDISTRIBUTE

281:    Not Collective

283:    Input Parameter:
284: .  pc - the preconditioner context

286:    Output Parameter:
287: .  innerksp - the inner KSP

289:    Level: advanced

291: .keywords: PC, redistribute solve
292: @*/
293: PetscErrorCode  PCRedistributeGetKSP(PC pc,KSP *innerksp)
294: {
295:   PC_Redistribute *red = (PC_Redistribute*)pc->data;

300:   *innerksp = red->ksp;
301:   return(0);
302: }

304: /* -------------------------------------------------------------------------------------*/
305: /*MC
306:      PCREDISTRIBUTE - Redistributes a matrix for load balancing, removing the rows that only have a diagonal entry and then applys a KSP to that new matrix

308:      Options for the redistribute preconditioners can be set with -redistribute_ksp_xxx <values> and -redistribute_pc_xxx <values>

310:      Notes:  Usually run this with -ksp_type preonly

312:      If you have used MatZeroRows() to eliminate (for example, Dirichlet) boundary conditions for a symmetric problem then you can use, for example, -ksp_type preonly
313:      -pc_type redistribute -redistribute_ksp_type cg -redistribute_pc_type bjacobi -redistribute_sub_pc_type icc to take advantage of the symmetry.

315:      This does NOT call a partitioner to reorder rows to lower communication; the ordering of the rows in the original matrix and redistributed matrix is the same.

317:      Developer Notes: Should add an option to this preconditioner to use a partitioner to redistribute the rows to lower communication.

319:    Level: intermediate

321: .seealso:  PCCreate(), PCSetType(), PCType (for list of available types), PCRedistributeGetKSP()
322: M*/

324: PETSC_EXTERN PetscErrorCode PCCreate_Redistribute(PC pc)
325: {
326:   PetscErrorCode  ierr;
327:   PC_Redistribute *red;
328:   const char      *prefix;

331:   PetscNewLog(pc,&red);
332:   pc->data = (void*)red;

334:   pc->ops->apply          = PCApply_Redistribute;
335:   pc->ops->applytranspose = 0;
336:   pc->ops->setup          = PCSetUp_Redistribute;
337:   pc->ops->destroy        = PCDestroy_Redistribute;
338:   pc->ops->setfromoptions = PCSetFromOptions_Redistribute;
339:   pc->ops->view           = PCView_Redistribute;

341:   KSPCreate(PetscObjectComm((PetscObject)pc),&red->ksp);
342:   KSPSetErrorIfNotConverged(red->ksp,pc->erroriffailure);
343:   PetscObjectIncrementTabLevel((PetscObject)red->ksp,(PetscObject)pc,1);
344:   PetscLogObjectParent((PetscObject)pc,(PetscObject)red->ksp);
345:   PCGetOptionsPrefix(pc,&prefix);
346:   KSPSetOptionsPrefix(red->ksp,prefix);
347:   KSPAppendOptionsPrefix(red->ksp,"redistribute_");
348:   return(0);
349: }