Date: 2021-03-03T22:26:41+00:00

Actual source code: party.c
petsc-3.14.5 2021-03-03
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      2: #include <../src/mat/impls/adj/mpi/mpiadj.h>

      4: #if defined(PETSC_HAVE_UNISTD_H)
      5: #include <unistd.h>
      6: #endif

      8: /*
      9:    Currently using Party-1.99
     10: */
     11: EXTERN_C_BEGIN
     12: #include <party_lib.h>
     13: EXTERN_C_END

     15: typedef struct {
     16:   PetscBool redm;
     17:   PetscBool redo;
     18:   PetscBool recursive;
     19:   PetscBool verbose;
     20:   char      global[15];         /* global method */
     21:   char      local[15];          /* local method */
     22:   PetscInt  nbvtxcoarsed;       /* number of vertices for the coarse graph */
     23: } MatPartitioning_Party;

     25: #define SIZE_LOG 10000          /* size of buffer for mesg_log */

     27: static PetscErrorCode MatPartitioningApply_Party(MatPartitioning part,IS *partitioning)
     28: {
     29:   PetscErrorCode        ierr;
     30:   PetscInt              i,*parttab,*locals,nb_locals,M,N;
     31:   PetscMPIInt           size,rank;
     32:   Mat                   mat = part->adj,matAdj,matSeq,*A;
     33:   Mat_MPIAdj            *adj;
     34:   MatPartitioning_Party *party = (MatPartitioning_Party*)part->data;
     35:   PetscBool             flg;
     36:   IS                    isrow, iscol;
     37:   int                   n,*edge_p,*edge,*vertex_w,p,*part_party,cutsize,redl,rec;
     38:   const char            *redm,*redo;
     39:   char                  *mesg_log;
     40: #if defined(PETSC_HAVE_UNISTD_H)
     41:   int                   fd_stdout,fd_pipe[2],count,err;
     42: #endif

     45:   if (part->use_edge_weights) SETERRQ(PetscObjectComm((PetscObject)part),PETSC_ERR_SUP,"Party does not support edge weights");
     46:   MPI_Comm_size(PetscObjectComm((PetscObject)mat),&size);
     47:   MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);
     48:   PetscObjectTypeCompare((PetscObject)mat,MATMPIADJ,&flg);
     49:   if (size>1) {
     50:     if (flg) {
     51:       MatMPIAdjToSeq(mat,&matSeq);
     52:      } else {
     53:       PetscInfo(part,"Converting distributed matrix to sequential: this could be a performance loss\n");
     54:       MatGetSize(mat,&M,&N);
     55:       ISCreateStride(PETSC_COMM_SELF,M,0,1,&isrow);
     56:       ISCreateStride(PETSC_COMM_SELF,N,0,1,&iscol);
     57:       MatCreateSubMatrices(mat,1,&isrow,&iscol,MAT_INITIAL_MATRIX,&A);
     58:       ISDestroy(&isrow);
     59:       ISDestroy(&iscol);
     60:       matSeq = *A;
     61:       PetscFree(A);
     62:      }
     63:   } else {
     64:     PetscObjectReference((PetscObject)mat);
     65:     matSeq = mat;
     66:   }

     68:   if (!flg) { /* convert regular matrix to MPIADJ */
     69:     MatConvert(matSeq,MATMPIADJ,MAT_INITIAL_MATRIX,&matAdj);
     70:   } else {
     71:     PetscObjectReference((PetscObject)matSeq);
     72:     matAdj = matSeq;
     73:   }

     75:   adj = (Mat_MPIAdj*)matAdj->data;  /* finaly adj contains adjacency graph */

     77:   /* arguments for Party library */
     78:   n        = mat->rmap->N;             /* number of vertices in full graph */
     79:   edge_p   = adj->i;                   /* start of edge list for each vertex */
     80:   edge     = adj->j;                   /* edge list data */
     81:   vertex_w = part->vertex_weights;     /* weights for all vertices */
     82:   p        = part->n;                  /* number of parts to create */
     83:   redl     = party->nbvtxcoarsed;      /* how many vertices to coarsen down to? */
     84:   rec      = party->recursive ? 1 : 0; /* recursive bisection */
     85:   redm     = party->redm ? "lam" : ""; /* matching method */
     86:   redo     = party->redo ? "w3" : "";  /* matching optimization method */

     88:   PetscMalloc1(mat->rmap->N,&part_party);

     90:   /* redirect output to buffer */
     91: #if defined(PETSC_HAVE_UNISTD_H)
     92:   fd_stdout = dup(1);
     93:   if (pipe(fd_pipe)) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SYS,"Could not open pipe");
     94:   close(1);
     95:   dup2(fd_pipe[1],1);
     96:   PetscMalloc1(SIZE_LOG,&mesg_log);
     97: #endif

     99:   /* library call */
    100:   party_lib_times_start();
    101:   party_lib(n,vertex_w,NULL,NULL,NULL,edge_p,edge,NULL,p,part_party,&cutsize,redl,(char*)redm,(char*)redo,party->global,party->local,rec,1);

    103:   party_lib_times_output(1);
    104:   part_info(n,vertex_w,edge_p,edge,NULL,p,part_party,1);

    106: #if defined(PETSC_HAVE_UNISTD_H)
    107:   err = fflush(stdout);
    108:   if (err) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SYS,"fflush() failed on stdout");
    109:   count = read(fd_pipe[0],mesg_log,(SIZE_LOG-1)*sizeof(char));
    110:   if (count<0) count = 0;
    111:   mesg_log[count] = 0;
    112:   close(1);
    113:   dup2(fd_stdout,1);
    114:   close(fd_stdout);
    115:   close(fd_pipe[0]);
    116:   close(fd_pipe[1]);
    117:   if (party->verbose) {
    118:     PetscPrintf(PetscObjectComm((PetscObject)mat),mesg_log);
    119:   }
    120:   PetscFree(mesg_log);
    121: #endif
    122:   if (ierr) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_LIB,"Party failed");

    124:   PetscMalloc1(mat->rmap->N,&parttab);
    125:   for (i=0; i<mat->rmap->N; i++) parttab[i] = part_party[i];

    127:   /* creation of the index set */
    128:   nb_locals = mat->rmap->n;
    129:   locals    = parttab + mat->rmap->rstart;

    131:   ISCreateGeneral(PetscObjectComm((PetscObject)part),nb_locals,locals,PETSC_COPY_VALUES,partitioning);

    133:   /* clean up */
    134:   PetscFree(parttab);
    135:   PetscFree(part_party);
    136:   MatDestroy(&matSeq);
    137:   MatDestroy(&matAdj);
    138:   return(0);
    139: }

    141: PetscErrorCode MatPartitioningView_Party(MatPartitioning part,PetscViewer viewer)
    142: {
    143:   MatPartitioning_Party *party = (MatPartitioning_Party*)part->data;
    144:   PetscErrorCode        ierr;
    145:   PetscBool             isascii;

    148:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&isascii);
    149:   if (isascii) {
    150:     PetscViewerASCIIPrintf(viewer,"  Global method: %s\n",party->global);
    151:     PetscViewerASCIIPrintf(viewer,"  Local method: %s\n",party->local);
    152:     PetscViewerASCIIPrintf(viewer,"  Number of vertices for the coarse graph: %d\n",party->nbvtxcoarsed);
    153:     if (party->redm) {
    154:       PetscViewerASCIIPrintf(viewer,"  Using matching method for graph reduction\n");
    155:     }
    156:     if (party->redo) {
    157:       PetscViewerASCIIPrintf(viewer,"  Using matching optimization\n");
    158:     }
    159:     if (party->recursive) {
    160:       PetscViewerASCIIPrintf(viewer,"  Using recursive bipartitioning\n");
    161:     }
    162:   }
    163:   return(0);
    164: }

    166: /*@C
    167:    MatPartitioningPartySetGlobal - Set global method for Party partitioner.

    169:    Collective on MatPartitioning

    171:    Input Parameters:
    172: +  part - the partitioning context
    173: -  method - a string representing the method

    175:    Options Database:
    176: .  -mat_partitioning_party_global <method> - the global method

    178:    Level: advanced

    180:    Notes:
    181:    The method may be one of MP_PARTY_OPT, MP_PARTY_LIN, MP_PARTY_SCA,
    182:    MP_PARTY_RAN, MP_PARTY_GBF, MP_PARTY_GCF, MP_PARTY_BUB or MP_PARTY_DEF, or
    183:    alternatively a string describing the method. Two or more methods can be
    184:    combined like "gbf,gcf". Check the Party Library Users Manual for details.

    186: .seealso: MatPartitioningPartySetLocal()
    187: @*/
    188: PetscErrorCode MatPartitioningPartySetGlobal(MatPartitioning part,const char *global)
    189: {

    194:   PetscTryMethod(part,"MatPartitioningPartySetGlobal_C",(MatPartitioning,const char*),(part,global));
    195:   return(0);
    196: }

    198: PetscErrorCode MatPartitioningPartySetGlobal_Party(MatPartitioning part,const char *global)
    199: {
    200:   MatPartitioning_Party *party = (MatPartitioning_Party*)part->data;
    201:   PetscErrorCode        ierr;

    204:   PetscStrncpy(party->global,global,15);
    205:   return(0);
    206: }

    208: /*@C
    209:    MatPartitioningPartySetLocal - Set local method for Party partitioner.

    211:    Collective on MatPartitioning

    213:    Input Parameters:
    214: +  part - the partitioning context
    215: -  method - a string representing the method

    217:    Options Database:
    218: .  -mat_partitioning_party_local <method> - the local method

    220:    Level: advanced

    222:    Notes:
    223:    The method may be one of MP_PARTY_HELPFUL_SETS, MP_PARTY_KERNIGHAN_LIN, or
    224:    MP_PARTY_NONE. Check the Party Library Users Manual for details.

    226: .seealso: MatPartitioningPartySetGlobal()
    227: @*/
    228: PetscErrorCode MatPartitioningPartySetLocal(MatPartitioning part,const char *local)
    229: {

    234:   PetscTryMethod(part,"MatPartitioningPartySetLocal_C",(MatPartitioning,const char*),(part,local));
    235:   return(0);
    236: }

    238: PetscErrorCode MatPartitioningPartySetLocal_Party(MatPartitioning part,const char *local)

    240: {
    241:   MatPartitioning_Party *party = (MatPartitioning_Party*)part->data;
    242:   PetscErrorCode        ierr;

    245:   PetscStrncpy(party->local,local,15);
    246:   return(0);
    247: }

    249: /*@
    250:    MatPartitioningPartySetCoarseLevel - Set the coarse level parameter for the
    251:    Party partitioner.

    253:    Collective on MatPartitioning

    255:    Input Parameters:
    256: +  part - the partitioning context
    257: -  level - the coarse level in range [0.0,1.0]

    259:    Options Database:
    260: .  -mat_partitioning_party_coarse <l> - Coarse level

    262:    Level: advanced
    263: @*/
    264: PetscErrorCode MatPartitioningPartySetCoarseLevel(MatPartitioning part,PetscReal level)
    265: {

    271:   PetscTryMethod(part,"MatPartitioningPartySetCoarseLevel_C",(MatPartitioning,PetscReal),(part,level));
    272:   return(0);
    273: }

    275: PetscErrorCode MatPartitioningPartySetCoarseLevel_Party(MatPartitioning part,PetscReal level)
    276: {
    277:   MatPartitioning_Party *party = (MatPartitioning_Party*)part->data;

    280:   if (level<0.0 || level>1.0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Party: level of coarsening out of range [0.0-1.0]");
    281:   party->nbvtxcoarsed = (PetscInt)(part->adj->cmap->N * level);
    282:   if (party->nbvtxcoarsed < 20) party->nbvtxcoarsed = 20;
    283:   return(0);
    284: }

    286: /*@
    287:    MatPartitioningPartySetMatchOptimization - Activate matching optimization for
    288:    graph reduction.

    290:    Collective on MatPartitioning

    292:    Input Parameters:
    293: +  part - the partitioning context
    294: -  opt - boolean flag

    296:    Options Database:
    297: .  -mat_partitioning_party_match_optimization - Matching optimization on/off

    299:    Level: advanced
    300: @*/
    301: PetscErrorCode MatPartitioningPartySetMatchOptimization(MatPartitioning part,PetscBool opt)
    302: {

    308:   PetscTryMethod(part,"MatPartitioningPartySetMatchOptimization_C",(MatPartitioning,PetscBool),(part,opt));
    309:   return(0);
    310: }

    312: PetscErrorCode MatPartitioningPartySetMatchOptimization_Party(MatPartitioning part,PetscBool opt)
    313: {
    314:   MatPartitioning_Party *party = (MatPartitioning_Party*)part->data;

    317:   party->redo = opt;
    318:   return(0);
    319: }

    321: /*@
    322:    MatPartitioningPartySetBipart - Activate or deactivate recursive bisection.

    324:    Collective on MatPartitioning

    326:    Input Parameters:
    327: +  part - the partitioning context
    328: -  bp - boolean flag

    330:    Options Database:
    331: -  -mat_partitioning_party_bipart - Bipartitioning option on/off

    333:    Level: advanced
    334: @*/
    335: PetscErrorCode MatPartitioningPartySetBipart(MatPartitioning part,PetscBool bp)
    336: {

    342:   PetscTryMethod(part,"MatPartitioningPartySetBipart_C",(MatPartitioning,PetscBool),(part,bp));
    343:   return(0);
    344: }

    346: PetscErrorCode MatPartitioningPartySetBipart_Party(MatPartitioning part,PetscBool bp)
    347: {
    348:   MatPartitioning_Party *party = (MatPartitioning_Party*)part->data;

    351:   party->recursive = bp;
    352:   return(0);
    353: }

    355: PetscErrorCode MatPartitioningSetFromOptions_Party(PetscOptionItems *PetscOptionsObject,MatPartitioning part)
    356: {
    357:   PetscErrorCode        ierr;
    358:   PetscBool             flag;
    359:   char                  value[256];
    360:   PetscReal             r;
    361:   MatPartitioning_Party *party = (MatPartitioning_Party*)part->data;

    364:   PetscOptionsHead(PetscOptionsObject,"Set Party partitioning options");
    365:   PetscOptionsString("-mat_partitioning_party_global","Global method","MatPartitioningPartySetGlobal",party->global,value,sizeof(value),&flag);
    366:   if (flag) { MatPartitioningPartySetGlobal(part,value); }
    367:   PetscOptionsString("-mat_partitioning_party_local","Local method","MatPartitioningPartySetLocal",party->local,value,sizeof(value),&flag);
    368:   if (flag) { MatPartitioningPartySetLocal(part,value); }
    369:   PetscOptionsReal("-mat_partitioning_party_coarse","Coarse level","MatPartitioningPartySetCoarseLevel",0.0,&r,&flag);
    370:   if (flag) { MatPartitioningPartySetCoarseLevel(part,r); }
    371:   PetscOptionsBool("-mat_partitioning_party_match_optimization","Matching optimization on/off","MatPartitioningPartySetMatchOptimization",party->redo,&party->redo,NULL);
    372:   PetscOptionsBool("-mat_partitioning_party_bipart","Bipartitioning on/off","MatPartitioningPartySetBipart",party->recursive,&party->recursive,NULL);
    373:   PetscOptionsBool("-mat_partitioning_party_verbose","Show library output","",party->verbose,&party->verbose,NULL);
    374:   PetscOptionsTail();
    375:   return(0);
    376: }

    378: PetscErrorCode MatPartitioningDestroy_Party(MatPartitioning part)
    379: {
    380:   MatPartitioning_Party *party = (MatPartitioning_Party*)part->data;
    381:   PetscErrorCode        ierr;

    384:   PetscFree(party);
    385:   /* clear composed functions */
    386:   PetscObjectComposeFunction((PetscObject)part,"MatPartitioningPartySetGlobal_C",NULL);
    387:   PetscObjectComposeFunction((PetscObject)part,"MatPartitioningPartySetLocal_C",NULL);
    388:   PetscObjectComposeFunction((PetscObject)part,"MatPartitioningPartySetCoarseLevel_C",NULL);
    389:   PetscObjectComposeFunction((PetscObject)part,"MatPartitioningPartySetMatchOptimization_C",NULL);
    390:   PetscObjectComposeFunction((PetscObject)part,"MatPartitioningPartySetBipart_C",NULL);
    391:   return(0);
    392: }

    394: /*MC
    395:    MATPARTITIONINGPARTY - Creates a partitioning context via the external package Party.

    397:    Level: beginner

    399:    Notes:
    400:     See http://wwwcs.upb.de/fachbereich/AG/monien/RESEARCH/PART/party.html

    402:     Does not support using MatPartitioningSetUseEdgeWeights()

    404: .seealso: MatPartitioningSetType(), MatPartitioningType

    406: M*/

    408: PETSC_EXTERN PetscErrorCode MatPartitioningCreate_Party(MatPartitioning part)
    409: {
    410:   PetscErrorCode        ierr;
    411:   MatPartitioning_Party *party;

    414:   PetscNewLog(part,&party);
    415:   part->data = (void*)party;

    417:   PetscStrcpy(party->global,"gcf,gbf");
    418:   PetscStrcpy(party->local,"kl");

    420:   party->redm         = PETSC_TRUE;
    421:   party->redo         = PETSC_TRUE;
    422:   party->recursive    = PETSC_TRUE;
    423:   party->verbose      = PETSC_FALSE;
    424:   party->nbvtxcoarsed = 200;

    426:   part->ops->apply          = MatPartitioningApply_Party;
    427:   part->ops->view           = MatPartitioningView_Party;
    428:   part->ops->destroy        = MatPartitioningDestroy_Party;
    429:   part->ops->setfromoptions = MatPartitioningSetFromOptions_Party;

    431:   PetscObjectComposeFunction((PetscObject)part,"MatPartitioningPartySetGlobal_C",MatPartitioningPartySetGlobal_Party);
    432:   PetscObjectComposeFunction((PetscObject)part,"MatPartitioningPartySetLocal_C",MatPartitioningPartySetLocal_Party);
    433:   PetscObjectComposeFunction((PetscObject)part,"MatPartitioningPartySetCoarseLevel_C",MatPartitioningPartySetCoarseLevel_Party);
    434:   PetscObjectComposeFunction((PetscObject)part,"MatPartitioningPartySetMatchOptimization_C",MatPartitioningPartySetMatchOptimization_Party);
    435:   PetscObjectComposeFunction((PetscObject)part,"MatPartitioningPartySetBipart_C",MatPartitioningPartySetBipart_Party);
    436:   return(0);
    437: }