Date: 2016-07-24T16:58:21+00:00

Actual source code: party.c
petsc-3.7.3 2016-07-24
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      2: #include <../src/mat/impls/adj/mpi/mpiadj.h>       /*I "petscmat.h" I*/

      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 */

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

     47:   MPI_Comm_size(PetscObjectComm((PetscObject)mat),&size);
     48:   MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);
     49:   PetscObjectTypeCompare((PetscObject)mat,MATMPIADJ,&flg);
     50:   if (size>1) {
     51:     if (flg) SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_SUP,"Distributed matrix format MPIAdj is not supported for sequential partitioners");
     52:     PetscInfo(part,"Converting distributed matrix to sequential: this could be a performance loss\n");
     53:     MatGetSize(mat,&M,&N);
     54:     ISCreateStride(PETSC_COMM_SELF,M,0,1,&isrow);
     55:     ISCreateStride(PETSC_COMM_SELF,N,0,1,&iscol);
     56:     MatGetSubMatrices(mat,1,&isrow,&iscol,MAT_INITIAL_MATRIX,&A);
     57:     ISDestroy(&isrow);
     58:     ISDestroy(&iscol);
     59:     matSeq = *A;
     60:     PetscFree(A);
     61:   } else {
     62:     PetscObjectReference((PetscObject)mat);
     63:     matSeq = mat;
     64:   }

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

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

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

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

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

     97:   /* library call */
     98:   party_lib_times_start();
     99:   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);

    101:   party_lib_times_output(1);
    102:   part_info(n,vertex_w,edge_p,edge,NULL,p,part_party,1);

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

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

    125:   /* creation of the index set */
    126:   nb_locals = mat->rmap->N / size;
    127:   locals    = parttab + rank*nb_locals;
    128:   if (rank < mat->rmap->N % size) {
    129:     nb_locals++;
    130:     locals += rank;
    131:   } else locals += mat->rmap->N % size;

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

    135:   /* clean up */
    136:   PetscFree(parttab);
    137:   PetscFree(part_party);
    138:   MatDestroy(&matSeq);
    139:   MatDestroy(&matAdj);
    140:   return(0);
    141: }

    145: PetscErrorCode MatPartitioningView_Party(MatPartitioning part,PetscViewer viewer)
    146: {
    147:   MatPartitioning_Party *party = (MatPartitioning_Party*)part->data;
    148:   PetscErrorCode        ierr;
    149:   PetscBool             isascii;

    152:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&isascii);
    153:   if (isascii) {
    154:     PetscViewerASCIIPrintf(viewer,"  Global method: %s\n",party->global);
    155:     PetscViewerASCIIPrintf(viewer,"  Local method: %s\n",party->local);
    156:     PetscViewerASCIIPrintf(viewer,"  Number of vertices for the coarse graph: %d\n",party->nbvtxcoarsed);
    157:     if (party->redm) {
    158:       PetscViewerASCIIPrintf(viewer,"  Using matching method for graph reduction\n");
    159:     }
    160:     if (party->redo) {
    161:       PetscViewerASCIIPrintf(viewer,"  Using matching optimization\n");
    162:     }
    163:     if (party->recursive) {
    164:       PetscViewerASCIIPrintf(viewer,"  Using recursive bipartitioning\n");
    165:     }
    166:   }
    167:   return(0);
    168: }

    172: /*@C
    173:    MatPartitioningPartySetGlobal - Set global method for Party partitioner.

    175:    Collective on MatPartitioning

    177:    Input Parameters:
    178: +  part - the partitioning context
    179: -  method - a string representing the method

    181:    Options Database:
    182: .  -mat_partitioning_party_global <method> - the global method

    184:    Level: advanced

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

    192: .seealso: MatPartitioningPartySetLocal()
    193: @*/
    194: PetscErrorCode MatPartitioningPartySetGlobal(MatPartitioning part,const char *global)
    195: {

    200:   PetscTryMethod(part,"MatPartitioningPartySetGlobal_C",(MatPartitioning,const char*),(part,global));
    201:   return(0);
    202: }

    206: PetscErrorCode MatPartitioningPartySetGlobal_Party(MatPartitioning part,const char *global)
    207: {
    208:   MatPartitioning_Party *party = (MatPartitioning_Party*)part->data;
    209:   PetscErrorCode        ierr;

    212:   PetscStrncpy(party->global,global,15);
    213:   return(0);
    214: }

    218: /*@C
    219:    MatPartitioningPartySetLocal - Set local method for Party partitioner.

    221:    Collective on MatPartitioning

    223:    Input Parameters:
    224: +  part - the partitioning context
    225: -  method - a string representing the method

    227:    Options Database:
    228: .  -mat_partitioning_party_local <method> - the local method

    230:    Level: advanced

    232:    Notes:
    233:    The method may be one of MP_PARTY_HELPFUL_SETS, MP_PARTY_KERNIGHAN_LIN, or
    234:    MP_PARTY_NONE. Check the Party Library Users Manual for details.

    236: .seealso: MatPartitioningPartySetGlobal()
    237: @*/
    238: PetscErrorCode MatPartitioningPartySetLocal(MatPartitioning part,const char *local)
    239: {

    244:   PetscTryMethod(part,"MatPartitioningPartySetLocal_C",(MatPartitioning,const char*),(part,local));
    245:   return(0);
    246: }

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

    252: {
    253:   MatPartitioning_Party *party = (MatPartitioning_Party*)part->data;
    254:   PetscErrorCode        ierr;

    257:   PetscStrncpy(party->local,local,15);
    258:   return(0);
    259: }

    263: /*@
    264:    MatPartitioningPartySetCoarseLevel - Set the coarse level parameter for the
    265:    Party partitioner.

    267:    Collective on MatPartitioning

    269:    Input Parameters:
    270: +  part - the partitioning context
    271: -  level - the coarse level in range [0.0,1.0]

    273:    Options Database:
    274: .  -mat_partitioning_party_coarse <l> - Coarse level

    276:    Level: advanced
    277: @*/
    278: PetscErrorCode MatPartitioningPartySetCoarseLevel(MatPartitioning part,PetscReal level)
    279: {

    285:   PetscTryMethod(part,"MatPartitioningPartySetCoarseLevel_C",(MatPartitioning,PetscReal),(part,level));
    286:   return(0);
    287: }

    291: PetscErrorCode MatPartitioningPartySetCoarseLevel_Party(MatPartitioning part,PetscReal level)
    292: {
    293:   MatPartitioning_Party *party = (MatPartitioning_Party*)part->data;

    296:   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]");
    297:   party->nbvtxcoarsed = (PetscInt)(part->adj->cmap->N * level);
    298:   if (party->nbvtxcoarsed < 20) party->nbvtxcoarsed = 20;
    299:   return(0);
    300: }

    304: /*@
    305:    MatPartitioningPartySetMatchOptimization - Activate matching optimization for
    306:    graph reduction.

    308:    Collective on MatPartitioning

    310:    Input Parameters:
    311: +  part - the partitioning context
    312: -  opt - boolean flag

    314:    Options Database:
    315: .  -mat_partitioning_party_match_optimization - Matching optimization on/off

    317:    Level: advanced
    318: @*/
    319: PetscErrorCode MatPartitioningPartySetMatchOptimization(MatPartitioning part,PetscBool opt)
    320: {

    326:   PetscTryMethod(part,"MatPartitioningPartySetMatchOptimization_C",(MatPartitioning,PetscBool),(part,opt));
    327:   return(0);
    328: }

    332: PetscErrorCode MatPartitioningPartySetMatchOptimization_Party(MatPartitioning part,PetscBool opt)
    333: {
    334:   MatPartitioning_Party *party = (MatPartitioning_Party*)part->data;

    337:   party->redo = opt;
    338:   return(0);
    339: }

    343: /*@
    344:    MatPartitioningPartySetBipart - Activate or deactivate recursive bisection.

    346:    Collective on MatPartitioning

    348:    Input Parameters:
    349: +  part - the partitioning context
    350: -  bp - boolean flag

    352:    Options Database:
    353: -  -mat_partitioning_party_bipart - Bipartitioning option on/off

    355:    Level: advanced
    356: @*/
    357: PetscErrorCode MatPartitioningPartySetBipart(MatPartitioning part,PetscBool bp)
    358: {

    364:   PetscTryMethod(part,"MatPartitioningPartySetBipart_C",(MatPartitioning,PetscBool),(part,bp));
    365:   return(0);
    366: }

    370: PetscErrorCode MatPartitioningPartySetBipart_Party(MatPartitioning part,PetscBool bp)
    371: {
    372:   MatPartitioning_Party *party = (MatPartitioning_Party*)part->data;

    375:   party->recursive = bp;
    376:   return(0);
    377: }

    381: PetscErrorCode MatPartitioningSetFromOptions_Party(PetscOptionItems *PetscOptionsObject,MatPartitioning part)
    382: {
    383:   PetscErrorCode        ierr;
    384:   PetscBool             flag;
    385:   char                  value[256];
    386:   PetscReal             r;
    387:   MatPartitioning_Party *party = (MatPartitioning_Party*)part->data;

    390:   PetscOptionsHead(PetscOptionsObject,"Set Party partitioning options");
    391:   PetscOptionsString("-mat_partitioning_party_global","Global method","MatPartitioningPartySetGlobal",party->global,value,256,&flag);
    392:   if (flag) { MatPartitioningPartySetGlobal(part,value); }
    393:   PetscOptionsString("-mat_partitioning_party_local","Local method","MatPartitioningPartySetLocal",party->local,value,256,&flag);
    394:   if (flag) { MatPartitioningPartySetLocal(part,value); }
    395:   PetscOptionsReal("-mat_partitioning_party_coarse","Coarse level","MatPartitioningPartySetCoarseLevel",0.0,&r,&flag);
    396:   if (flag) { MatPartitioningPartySetCoarseLevel(part,r); }
    397:   PetscOptionsBool("-mat_partitioning_party_match_optimization","Matching optimization on/off","MatPartitioningPartySetMatchOptimization",party->redo,&party->redo,NULL);
    398:   PetscOptionsBool("-mat_partitioning_party_bipart","Bipartitioning on/off","MatPartitioningPartySetBipart",party->recursive,&party->recursive,NULL);
    399:   PetscOptionsBool("-mat_partitioning_party_verbose","Show library output","",party->verbose,&party->verbose,NULL);
    400:   PetscOptionsTail();
    401:   return(0);
    402: }

    406: PetscErrorCode MatPartitioningDestroy_Party(MatPartitioning part)
    407: {
    408:   MatPartitioning_Party *party = (MatPartitioning_Party*)part->data;
    409:   PetscErrorCode        ierr;

    412:   PetscFree(party);
    413:   /* clear composed functions */
    414:   PetscObjectComposeFunction((PetscObject)part,"MatPartitioningPartySetGlobal_C",NULL);
    415:   PetscObjectComposeFunction((PetscObject)part,"MatPartitioningPartySetLocal_C",NULL);
    416:   PetscObjectComposeFunction((PetscObject)part,"MatPartitioningPartySetCoarseLevel_C",NULL);
    417:   PetscObjectComposeFunction((PetscObject)part,"MatPartitioningPartySetMatchOptimization_C",NULL);
    418:   PetscObjectComposeFunction((PetscObject)part,"MatPartitioningPartySetBipart_C",NULL);
    419:   return(0);
    420: }

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

    425:    Level: beginner

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

    429: .keywords: Partitioning, create, context

    431: .seealso: MatPartitioningSetType(), MatPartitioningType

    433: M*/

    437: PETSC_EXTERN PetscErrorCode MatPartitioningCreate_Party(MatPartitioning part)
    438: {
    439:   PetscErrorCode        ierr;
    440:   MatPartitioning_Party *party;

    443:   PetscNewLog(part,&party);
    444:   part->data = (void*)party;

    446:   PetscStrcpy(party->global,"gcf,gbf");
    447:   PetscStrcpy(party->local,"kl");

    449:   party->redm         = PETSC_TRUE;
    450:   party->redo         = PETSC_TRUE;
    451:   party->recursive    = PETSC_TRUE;
    452:   party->verbose      = PETSC_FALSE;
    453:   party->nbvtxcoarsed = 200;

    455:   part->ops->apply          = MatPartitioningApply_Party;
    456:   part->ops->view           = MatPartitioningView_Party;
    457:   part->ops->destroy        = MatPartitioningDestroy_Party;
    458:   part->ops->setfromoptions = MatPartitioningSetFromOptions_Party;

    460:   PetscObjectComposeFunction((PetscObject)part,"MatPartitioningPartySetGlobal_C",MatPartitioningPartySetGlobal_Party);
    461:   PetscObjectComposeFunction((PetscObject)part,"MatPartitioningPartySetLocal_C",MatPartitioningPartySetLocal_Party);
    462:   PetscObjectComposeFunction((PetscObject)part,"MatPartitioningPartySetCoarseLevel_C",MatPartitioningPartySetCoarseLevel_Party);
    463:   PetscObjectComposeFunction((PetscObject)part,"MatPartitioningPartySetMatchOptimization_C",MatPartitioningPartySetMatchOptimization_Party);
    464:   PetscObjectComposeFunction((PetscObject)part,"MatPartitioningPartySetBipart_C",MatPartitioningPartySetBipart_Party);
    465:   return(0);
    466: }