Actual source code: redistribute.c
petsc-3.10.5 2019-03-28
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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:
    311:     Usually run this with -ksp_type preonly

    313:      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
    314:      -pc_type redistribute -redistribute_ksp_type cg -redistribute_pc_type bjacobi -redistribute_sub_pc_type icc to take advantage of the symmetry.

    316:      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.

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

    321:    Level: intermediate

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

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

    333:   PetscNewLog(pc,&red);
    334:   pc->data = (void*)red;

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

    343:   KSPCreate(PetscObjectComm((PetscObject)pc),&red->ksp);
    344:   KSPSetErrorIfNotConverged(red->ksp,pc->erroriffailure);
    345:   PetscObjectIncrementTabLevel((PetscObject)red->ksp,(PetscObject)pc,1);
    346:   PetscLogObjectParent((PetscObject)pc,(PetscObject)red->ksp);
    347:   PCGetOptionsPrefix(pc,&prefix);
    348:   KSPSetOptionsPrefix(red->ksp,prefix);
    349:   KSPAppendOptionsPrefix(red->ksp,"redistribute_");
    350:   return(0);
    351: }