Actual source code: chaco.c
petsc-3.10.5 2019-03-28
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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: #if defined(PETSC_HAVE_CHACO_INT_ASSIGNMENT)
      9: #include <chaco.h>
     10: #else
     11: /* Older versions of Chaco do not have an include file */
     12: PETSC_EXTERN int interface(int nvtxs, int *start, int *adjacency, int *vwgts,
     13:                      float *ewgts, float *x, float *y, float *z, char *outassignname,
     14:                      char *outfilename, short *assignment, int architecture, int ndims_tot,
     15:                      int mesh_dims[3], double *goal, int global_method, int local_method,
     16:                      int rqi_flag, int vmax, int ndims, double eigtol, long seed);
     17: #endif

     19: extern int FREE_GRAPH;

     21: /*
     22: int       nvtxs;                number of vertices in full graph
     23: int      *start;                start of edge list for each vertex
     24: int      *adjacency;            edge list data
     25: int      *vwgts;                weights for all vertices
     26: float    *ewgts;                weights for all edges
     27: float    *x, *y, *z;            coordinates for inertial method
     28: char     *outassignname;        name of assignment output file
     29: char     *outfilename;          output file name
     30: short    *assignment;           set number of each vtx (length n)
     31: int       architecture;         0 => hypercube, d => d-dimensional mesh
     32: int       ndims_tot;            total number of cube dimensions to divide
     33: int       mesh_dims[3];         dimensions of mesh of processors
     34: double   *goal;                 desired set sizes for each set
     35: int       global_method;        global partitioning algorithm
     36: int       local_method;         local partitioning algorithm
     37: int       rqi_flag;             should I use RQI/Symmlq eigensolver?
     38: int       vmax;                 how many vertices to coarsen down to?
     39: int       ndims;                number of eigenvectors (2^d sets)
     40: double    eigtol;               tolerance on eigenvectors
     41: long      seed;                 for random graph mutations
     42: */

     44: typedef struct {
     45:   PetscBool         verbose;
     46:   PetscInt          eignum;
     47:   PetscReal         eigtol;
     48:   MPChacoGlobalType global_method;          /* global method */
     49:   MPChacoLocalType  local_method;           /* local method */
     50:   MPChacoEigenType  eigen_method;           /* eigensolver */
     51:   PetscInt          nbvtxcoarsed;           /* number of vertices for the coarse graph */
     52: } MatPartitioning_Chaco;

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

     56: static PetscErrorCode MatPartitioningApply_Chaco(MatPartitioning part,IS *partitioning)
     57: {
     58:   PetscErrorCode        ierr;
     59:   PetscInt              *parttab,*locals,i,nb_locals,M,N;
     60:   PetscMPIInt           size,rank;
     61:   Mat                   mat = part->adj,matAdj,matSeq,*A;
     62:   Mat_MPIAdj            *adj;
     63:   MatPartitioning_Chaco *chaco = (MatPartitioning_Chaco*)part->data;
     64:   PetscBool             flg;
     65:   IS                    isrow, iscol;
     66:   int                   nvtxs,*start,*adjacency,*vwgts,architecture,ndims_tot;
     67:   int                   mesh_dims[3],global_method,local_method,rqi_flag,vmax,ndims;
     68: #if defined(PETSC_HAVE_CHACO_INT_ASSIGNMENT)
     69:   int                   *assignment;
     70: #else
     71:   short                 *assignment;
     72: #endif
     73:   double                eigtol;
     74:   long                  seed;
     75:   char                  *mesg_log;
     76: #if defined(PETSC_HAVE_UNISTD_H)
     77:   int                   fd_stdout,fd_pipe[2],count,err;
     78: #endif

     81:   FREE_GRAPH = 0; /* otherwise Chaco will attempt to free memory for adjacency graph */
     82:   MPI_Comm_size(PetscObjectComm((PetscObject)mat),&size);
     83:   MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);
     84:   PetscObjectTypeCompare((PetscObject)mat,MATMPIADJ,&flg);
     85:   if (size>1) {
     86:     if (flg) {
     87:       MatMPIAdjToSeq(mat,&matSeq);
     88:     } else {
     89:       PetscInfo(part,"Converting distributed matrix to sequential: this could be a performance loss\n");
     90:       MatGetSize(mat,&M,&N);
     91:       ISCreateStride(PETSC_COMM_SELF,M,0,1,&isrow);
     92:       ISCreateStride(PETSC_COMM_SELF,N,0,1,&iscol);
     93:       MatCreateSubMatrices(mat,1,&isrow,&iscol,MAT_INITIAL_MATRIX,&A);
     94:       ISDestroy(&isrow);
     95:       ISDestroy(&iscol);
     96:       matSeq = *A;
     97:       PetscFree(A);
     98:     }
     99:   } else {
    100:     PetscObjectReference((PetscObject)mat);
    101:     matSeq = mat;
    102:   }

    104:   if (!flg) { /* convert regular matrix to MPIADJ */
    105:     MatConvert(matSeq,MATMPIADJ,MAT_INITIAL_MATRIX,&matAdj);
    106:   } else {
    107:     PetscObjectReference((PetscObject)matSeq);
    108:     matAdj = matSeq;
    109:   }

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

    113:   /* arguments for Chaco library */
    114:   nvtxs         = mat->rmap->N;           /* number of vertices in full graph */
    115:   start         = adj->i;                 /* start of edge list for each vertex */
    116:   vwgts         = part->vertex_weights;   /* weights for all vertices */
    117:   architecture  = 1;                      /* 0 => hypercube, d => d-dimensional mesh */
    118:   ndims_tot     = 0;                      /* total number of cube dimensions to divide */
    119:   mesh_dims[0]  = part->n;                /* dimensions of mesh of processors */
    120:   global_method = chaco->global_method;   /* global partitioning algorithm */
    121:   local_method  = chaco->local_method;    /* local partitioning algorithm */
    122:   rqi_flag      = chaco->eigen_method;    /* should I use RQI/Symmlq eigensolver? */
    123:   vmax          = chaco->nbvtxcoarsed;    /* how many vertices to coarsen down to? */
    124:   ndims         = chaco->eignum;          /* number of eigenvectors (2^d sets) */
    125:   eigtol        = chaco->eigtol;          /* tolerance on eigenvectors */
    126:   seed          = 123636512;              /* for random graph mutations */

    128:   PetscMalloc1(mat->rmap->N,&assignment);
    129:   PetscMalloc1(start[nvtxs],&adjacency);
    130:   for (i=0; i<start[nvtxs]; i++) adjacency[i] = (adj->j)[i] + 1; /* 1-based indexing */

    132:   /* redirect output to buffer */
    133: #if defined(PETSC_HAVE_UNISTD_H)
    134:   fd_stdout = dup(1);
    135:   if (pipe(fd_pipe)) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SYS,"Could not open pipe");
    136:   close(1);
    137:   dup2(fd_pipe[1],1);
    138:   PetscMalloc1(SIZE_LOG,&mesg_log);
    139: #endif

    141:   /* library call */
    142:   interface(nvtxs,start,adjacency,vwgts,NULL,NULL,NULL,NULL,
    143:                    NULL,NULL,assignment,architecture,ndims_tot,mesh_dims,
    144:                    NULL,global_method,local_method,rqi_flag,vmax,ndims,eigtol,seed);

    146: #if defined(PETSC_HAVE_UNISTD_H)
    147:   err = fflush(stdout);
    148:   if (err) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SYS,"fflush() failed on stdout");
    149:   count = read(fd_pipe[0],mesg_log,(SIZE_LOG-1)*sizeof(char));
    150:   if (count<0) count = 0;
    151:   mesg_log[count] = 0;
    152:   close(1);
    153:   dup2(fd_stdout,1);
    154:   close(fd_stdout);
    155:   close(fd_pipe[0]);
    156:   close(fd_pipe[1]);
    157:   if (chaco->verbose) {
    158:     PetscPrintf(PetscObjectComm((PetscObject)mat),mesg_log);
    159:   }
    160:   PetscFree(mesg_log);
    161: #endif
    162:   if (ierr) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_LIB,"Chaco failed");

    164:   PetscMalloc1(mat->rmap->N,&parttab);
    165:   for (i=0; i<nvtxs; i++) parttab[i] = assignment[i];

    167:   /* creation of the index set */
    168:   nb_locals = mat->rmap->n;
    169:   locals    = parttab + mat->rmap->rstart;
    170:   ISCreateGeneral(PetscObjectComm((PetscObject)part),nb_locals,locals,PETSC_COPY_VALUES,partitioning);

    172:   /* clean up */
    173:   PetscFree(parttab);
    174:   PetscFree(adjacency);
    175:   PetscFree(assignment);
    176:   MatDestroy(&matSeq);
    177:   MatDestroy(&matAdj);
    178:   return(0);
    179: }

    181: PetscErrorCode MatPartitioningView_Chaco(MatPartitioning part, PetscViewer viewer)
    182: {
    183:   MatPartitioning_Chaco *chaco = (MatPartitioning_Chaco*)part->data;
    184:   PetscErrorCode        ierr;
    185:   PetscBool             isascii;

    188:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&isascii);
    189:   if (isascii) {
    190:     PetscViewerASCIIPrintf(viewer,"  Global method: %s\n",MPChacoGlobalTypes[chaco->global_method]);
    191:     PetscViewerASCIIPrintf(viewer,"  Local method: %s\n",MPChacoLocalTypes[chaco->local_method]);
    192:     PetscViewerASCIIPrintf(viewer,"  Number of vertices for the coarse graph: %d\n",chaco->nbvtxcoarsed);
    193:     PetscViewerASCIIPrintf(viewer,"  Eigensolver: %s\n",MPChacoEigenTypes[chaco->eigen_method]);
    194:     PetscViewerASCIIPrintf(viewer,"  Tolerance for eigensolver: %g\n",chaco->eigtol);
    195:     PetscViewerASCIIPrintf(viewer,"  Number of eigenvectors: %d\n",chaco->eignum);
    196:   }
    197:   return(0);
    198: }

    200: /*@
    201:    MatPartitioningChacoSetGlobal - Set global method for Chaco partitioner.

    203:    Collective on MatPartitioning

    205:    Input Parameters:
    206: +  part - the partitioning context
    207: -  method - one of MP_CHACO_MULTILEVEL, MP_CHACO_SPECTRAL, MP_CHACO_LINEAR,
    208:             MP_CHACO_RANDOM or MP_CHACO_SCATTERED

    210:    Options Database:
    211: .  -mat_partitioning_chaco_global <method> - the global method

    213:    Level: advanced

    215:    Notes:
    216:    The default is the multi-level method. See Chaco documentation for
    217:    additional details.

    219: .seealso: MatPartitioningChacoSetLocal(),MatPartitioningChacoGetGlobal()
    220: @*/
    221: PetscErrorCode MatPartitioningChacoSetGlobal(MatPartitioning part,MPChacoGlobalType method)
    222: {

    228:   PetscTryMethod(part,"MatPartitioningChacoSetGlobal_C",(MatPartitioning,MPChacoGlobalType),(part,method));
    229:   return(0);
    230: }

    232: PetscErrorCode MatPartitioningChacoSetGlobal_Chaco(MatPartitioning part,MPChacoGlobalType method)
    233: {
    234:   MatPartitioning_Chaco *chaco = (MatPartitioning_Chaco*)part->data;

    237:   switch (method) {
    238:   case MP_CHACO_MULTILEVEL:
    239:   case MP_CHACO_SPECTRAL:
    240:   case MP_CHACO_LINEAR:
    241:   case MP_CHACO_RANDOM:
    242:   case MP_CHACO_SCATTERED:
    243:     chaco->global_method = method; break;
    244:   default:
    245:     SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Chaco: Unknown or unsupported option");
    246:   }
    247:   return(0);
    248: }

    250: /*@
    251:    MatPartitioningChacoGetGlobal - Get global method for Chaco partitioner.

    253:    Not Collective

    255:    Input Parameter:
    256: .  part - the partitioning context

    258:    Output Parameter:
    259: .  method - the method

    261:    Level: advanced

    263: .seealso: MatPartitioningChacoSetGlobal()
    264: @*/
    265: PetscErrorCode MatPartitioningChacoGetGlobal(MatPartitioning part,MPChacoGlobalType *method)
    266: {

    272:   PetscTryMethod(part,"MatPartitioningChacoGetGlobal_C",(MatPartitioning,MPChacoGlobalType*),(part,method));
    273:   return(0);
    274: }

    276: PetscErrorCode MatPartitioningChacoGetGlobal_Chaco(MatPartitioning part,MPChacoGlobalType *method)
    277: {
    278:   MatPartitioning_Chaco *chaco = (MatPartitioning_Chaco*)part->data;

    281:   *method = chaco->global_method;
    282:   return(0);
    283: }

    285: /*@
    286:    MatPartitioningChacoSetLocal - Set local method for Chaco partitioner.

    288:    Collective on MatPartitioning

    290:    Input Parameters:
    291: +  part - the partitioning context
    292: -  method - one of MP_CHACO_KERNIGHAN or MP_CHACO_NONE

    294:    Options Database:
    295: .  -mat_partitioning_chaco_local <method> - the local method

    297:    Level: advanced

    299:    Notes:
    300:    The default is to apply the Kernighan-Lin heuristic. See Chaco documentation
    301:    for additional details.

    303: .seealso: MatPartitioningChacoSetGlobal(),MatPartitioningChacoGetLocal()
    304: @*/
    305: PetscErrorCode MatPartitioningChacoSetLocal(MatPartitioning part,MPChacoLocalType method)
    306: {

    312:   PetscTryMethod(part,"MatPartitioningChacoSetLocal_C",(MatPartitioning,MPChacoLocalType),(part,method));
    313:   return(0);
    314: }

    316: PetscErrorCode MatPartitioningChacoSetLocal_Chaco(MatPartitioning part,MPChacoLocalType method)
    317: {
    318:   MatPartitioning_Chaco *chaco = (MatPartitioning_Chaco*)part->data;

    321:   switch (method) {
    322:   case MP_CHACO_KERNIGHAN:
    323:   case MP_CHACO_NONE:
    324:     chaco->local_method = method; break;
    325:   default:
    326:     SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Chaco: Unknown or unsupported option");
    327:   }
    328:   return(0);
    329: }

    331: /*@
    332:    MatPartitioningChacoGetLocal - Get local method for Chaco partitioner.

    334:    Not Collective

    336:    Input Parameter:
    337: .  part - the partitioning context

    339:    Output Parameter:
    340: .  method - the method

    342:    Level: advanced

    344: .seealso: MatPartitioningChacoSetLocal()
    345: @*/
    346: PetscErrorCode MatPartitioningChacoGetLocal(MatPartitioning part,MPChacoLocalType *method)
    347: {

    353:   PetscUseMethod(part,"MatPartitioningChacoGetLocal_C",(MatPartitioning,MPChacoLocalType*),(part,method));
    354:   return(0);
    355: }

    357: PetscErrorCode MatPartitioningChacoGetLocal_Chaco(MatPartitioning part,MPChacoLocalType *method)
    358: {
    359:   MatPartitioning_Chaco *chaco = (MatPartitioning_Chaco*)part->data;

    362:   *method = chaco->local_method;
    363:   return(0);
    364: }

    366: /*@
    367:    MatPartitioningChacoSetCoarseLevel - Set the coarse level parameter for the
    368:    Chaco partitioner.

    370:    Collective on MatPartitioning

    372:    Input Parameters:
    373: +  part - the partitioning context
    374: -  level - the coarse level in range [0.0,1.0]

    376:    Options Database:
    377: .  -mat_partitioning_chaco_coarse <l> - Coarse level

    379:    Level: advanced
    380: @*/
    381: PetscErrorCode MatPartitioningChacoSetCoarseLevel(MatPartitioning part,PetscReal level)
    382: {

    388:   PetscTryMethod(part,"MatPartitioningChacoSetCoarseLevel_C",(MatPartitioning,PetscReal),(part,level));
    389:   return(0);
    390: }

    392: PetscErrorCode MatPartitioningChacoSetCoarseLevel_Chaco(MatPartitioning part,PetscReal level)
    393: {
    394:   MatPartitioning_Chaco *chaco = (MatPartitioning_Chaco*)part->data;

    397:   if (level<0.0 || level>1.0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Chaco: level of coarsening out of range [0.0-1.0]");
    398:   chaco->nbvtxcoarsed = (PetscInt)(part->adj->cmap->N * level);
    399:   if (chaco->nbvtxcoarsed < 20) chaco->nbvtxcoarsed = 20;
    400:   return(0);
    401: }

    403: /*@
    404:    MatPartitioningChacoSetEigenSolver - Set eigensolver method for Chaco partitioner.

    406:    Collective on MatPartitioning

    408:    Input Parameters:
    409: +  part - the partitioning context
    410: -  method - one of MP_CHACO_LANCZOS or MP_CHACO_RQI

    412:    Options Database:
    413: .  -mat_partitioning_chaco_eigen_solver <method> - the eigensolver

    415:    Level: advanced

    417:    Notes:
    418:    The default is to use a Lanczos method. See Chaco documentation for details.

    420: .seealso: MatPartitioningChacoSetEigenTol(),MatPartitioningChacoSetEigenNumber(),
    421:           MatPartitioningChacoGetEigenSolver()
    422: @*/
    423: PetscErrorCode MatPartitioningChacoSetEigenSolver(MatPartitioning part,MPChacoEigenType method)
    424: {

    430:   PetscTryMethod(part,"MatPartitioningChacoSetEigenSolver_C",(MatPartitioning,MPChacoEigenType),(part,method));
    431:   return(0);
    432: }

    434: PetscErrorCode MatPartitioningChacoSetEigenSolver_Chaco(MatPartitioning part,MPChacoEigenType method)
    435: {
    436:   MatPartitioning_Chaco *chaco = (MatPartitioning_Chaco*)part->data;

    439:   switch (method) {
    440:   case MP_CHACO_LANCZOS:
    441:   case MP_CHACO_RQI:
    442:     chaco->eigen_method = method; break;
    443:   default:
    444:     SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Chaco: Unknown or unsupported option");
    445:   }
    446:   return(0);
    447: }

    449: /*@
    450:    MatPartitioningChacoGetEigenSolver - Get local method for Chaco partitioner.

    452:    Not Collective

    454:    Input Parameter:
    455: .  part - the partitioning context

    457:    Output Parameter:
    458: .  method - the method

    460:    Level: advanced

    462: .seealso: MatPartitioningChacoSetEigenSolver()
    463: @*/
    464: PetscErrorCode MatPartitioningChacoGetEigenSolver(MatPartitioning part,MPChacoEigenType *method)
    465: {

    471:   PetscUseMethod(part,"MatPartitioningChacoGetEigenSolver_C",(MatPartitioning,MPChacoEigenType*),(part,method));
    472:   return(0);
    473: }

    475: PetscErrorCode MatPartitioningChacoGetEigenSolver_Chaco(MatPartitioning part,MPChacoEigenType *method)
    476: {
    477:   MatPartitioning_Chaco *chaco = (MatPartitioning_Chaco*)part->data;

    480:   *method = chaco->eigen_method;
    481:   return(0);
    482: }

    484: /*@
    485:    MatPartitioningChacoSetEigenTol - Sets the tolerance for the eigensolver.

    487:    Collective on MatPartitioning

    489:    Input Parameters:
    490: +  part - the partitioning context
    491: -  tol  - the tolerance

    493:    Options Database:
    494: .  -mat_partitioning_chaco_eigen_tol <tol>: Tolerance for eigensolver

    496:    Note:
    497:    Must be positive. The default value is 0.001.

    499:    Level: advanced

    501: .seealso: MatPartitioningChacoSetEigenSolver(), MatPartitioningChacoGetEigenTol()
    502: @*/
    503: PetscErrorCode MatPartitioningChacoSetEigenTol(MatPartitioning part,PetscReal tol)
    504: {

    510:   PetscTryMethod(part,"MatPartitioningChacoSetEigenTol_C",(MatPartitioning,PetscReal),(part,tol));
    511:   return(0);
    512: }

    514: PetscErrorCode MatPartitioningChacoSetEigenTol_Chaco(MatPartitioning part,PetscReal tol)
    515: {
    516:   MatPartitioning_Chaco *chaco = (MatPartitioning_Chaco*)part->data;

    519:   if (tol==PETSC_DEFAULT) chaco->eigtol = 0.001;
    520:   else {
    521:     if (tol<=0.0) SETERRQ(PetscObjectComm((PetscObject)part),PETSC_ERR_ARG_OUTOFRANGE,"Tolerance must be positive");
    522:     chaco->eigtol = tol;
    523:   }
    524:   return(0);
    525: }

    527: /*@
    528:    MatPartitioningChacoGetEigenTol - Gets the eigensolver tolerance.

    530:    Not Collective

    532:    Input Parameter:
    533: .  part - the partitioning context

    535:    Output Parameter:
    536: .  tol  - the tolerance

    538:    Level: advanced

    540: .seealso: MatPartitioningChacoSetEigenTol()
    541: @*/
    542: PetscErrorCode MatPartitioningChacoGetEigenTol(MatPartitioning part,PetscReal *tol)
    543: {

    549:   PetscUseMethod(part,"MatPartitioningChacoGetEigenTol_C",(MatPartitioning,PetscReal*),(part,tol));
    550:   return(0);
    551: }

    553: PetscErrorCode MatPartitioningChacoGetEigenTol_Chaco(MatPartitioning part,PetscReal *tol)
    554: {
    555:   MatPartitioning_Chaco *chaco = (MatPartitioning_Chaco*)part->data;

    558:   *tol = chaco->eigtol;
    559:   return(0);
    560: }

    562: /*@
    563:    MatPartitioningChacoSetEigenNumber - Sets the number of eigenvectors to compute
    564:    during partitioning.

    566:    Collective on MatPartitioning

    568:    Input Parameters:
    569: +  part - the partitioning context
    570: -  num  - the number of eigenvectors

    572:    Options Database:
    573: .  -mat_partitioning_chaco_eigen_number <n>: Number of eigenvectors

    575:    Note:
    576:    Accepted values are 1, 2 or 3, indicating partitioning by bisection,
    577:    quadrisection, or octosection.

    579:    Level: advanced

    581: .seealso: MatPartitioningChacoSetEigenSolver(), MatPartitioningChacoGetEigenTol()
    582: @*/
    583: PetscErrorCode MatPartitioningChacoSetEigenNumber(MatPartitioning part,PetscInt num)
    584: {

    590:   PetscTryMethod(part,"MatPartitioningChacoSetEigenNumber_C",(MatPartitioning,PetscInt),(part,num));
    591:   return(0);
    592: }

    594: PetscErrorCode MatPartitioningChacoSetEigenNumber_Chaco(MatPartitioning part,PetscInt num)
    595: {
    596:   MatPartitioning_Chaco *chaco = (MatPartitioning_Chaco*)part->data;

    599:   if (num==PETSC_DEFAULT) chaco->eignum = 1;
    600:   else {
    601:     if (num<1 || num>3) SETERRQ(PetscObjectComm((PetscObject)part),PETSC_ERR_ARG_OUTOFRANGE,"Can only specify 1, 2 or 3 eigenvectors");
    602:     chaco->eignum = num;
    603:   }
    604:   return(0);
    605: }

    607: /*@
    608:    MatPartitioningChacoGetEigenNumber - Gets the number of eigenvectors used by Chaco.

    610:    Not Collective

    612:    Input Parameter:
    613: .  part - the partitioning context

    615:    Output Parameter:
    616: .  num  - number of eigenvectors

    618:    Level: advanced

    620: .seealso: MatPartitioningChacoSetEigenNumber()
    621: @*/
    622: PetscErrorCode MatPartitioningChacoGetEigenNumber(MatPartitioning part,PetscInt *num)
    623: {

    629:   PetscUseMethod(part,"MatPartitioningChacoGetEigenNumber_C",(MatPartitioning,PetscInt*),(part,num));
    630:   return(0);
    631: }

    633: PetscErrorCode MatPartitioningChacoGetEigenNumber_Chaco(MatPartitioning part,PetscInt *num)
    634: {
    635:   MatPartitioning_Chaco *chaco = (MatPartitioning_Chaco*)part->data;

    638:   *num = chaco->eignum;
    639:   return(0);
    640: }

    642: PetscErrorCode MatPartitioningSetFromOptions_Chaco(PetscOptionItems *PetscOptionsObject,MatPartitioning part)
    643: {
    644:   PetscErrorCode        ierr;
    645:   PetscInt              i;
    646:   PetscReal             r;
    647:   PetscBool             flag;
    648:   MatPartitioning_Chaco *chaco = (MatPartitioning_Chaco*)part->data;
    649:   MPChacoGlobalType     global;
    650:   MPChacoLocalType      local;
    651:   MPChacoEigenType      eigen;

    654:   PetscOptionsHead(PetscOptionsObject,"Chaco partitioning options");
    655:   PetscOptionsEnum("-mat_partitioning_chaco_global","Global method","MatPartitioningChacoSetGlobal",MPChacoGlobalTypes,(PetscEnum)chaco->global_method,(PetscEnum*)&global,&flag);
    656:   if (flag) { MatPartitioningChacoSetGlobal(part,global); }
    657:   PetscOptionsEnum("-mat_partitioning_chaco_local","Local method","MatPartitioningChacoSetLocal",MPChacoLocalTypes,(PetscEnum)chaco->local_method,(PetscEnum*)&local,&flag);
    658:   if (flag) { MatPartitioningChacoSetLocal(part,local); }
    659:   PetscOptionsReal("-mat_partitioning_chaco_coarse","Coarse level","MatPartitioningChacoSetCoarseLevel",0.0,&r,&flag);
    660:   if (flag) { MatPartitioningChacoSetCoarseLevel(part,r); }
    661:   PetscOptionsEnum("-mat_partitioning_chaco_eigen_solver","Eigensolver method","MatPartitioningChacoSetEigenSolver",MPChacoEigenTypes,(PetscEnum)chaco->eigen_method,(PetscEnum*)&eigen,&flag);
    662:   if (flag) { MatPartitioningChacoSetEigenSolver(part,eigen); }
    663:   PetscOptionsReal("-mat_partitioning_chaco_eigen_tol","Eigensolver tolerance","MatPartitioningChacoSetEigenTol",chaco->eigtol,&r,&flag);
    664:   if (flag) { MatPartitioningChacoSetEigenTol(part,r); }
    665:   PetscOptionsInt("-mat_partitioning_chaco_eigen_number","Number of eigenvectors: 1, 2, or 3 (bi-, quadri-, or octosection)","MatPartitioningChacoSetEigenNumber",chaco->eignum,&i,&flag);
    666:   if (flag) { MatPartitioningChacoSetEigenNumber(part,i); }
    667:   PetscOptionsBool("-mat_partitioning_chaco_verbose","Show library output","",chaco->verbose,&chaco->verbose,NULL);
    668:   PetscOptionsTail();
    669:   return(0);
    670: }

    672: PetscErrorCode MatPartitioningDestroy_Chaco(MatPartitioning part)
    673: {
    674:   MatPartitioning_Chaco *chaco = (MatPartitioning_Chaco*) part->data;
    675:   PetscErrorCode        ierr;

    678:   PetscFree(chaco);
    679:   /* clear composed functions */
    680:   PetscObjectComposeFunction((PetscObject)part,"MatPartitioningChacoSetGlobal_C",NULL);
    681:   PetscObjectComposeFunction((PetscObject)part,"MatPartitioningChacoGetGlobal_C",NULL);
    682:   PetscObjectComposeFunction((PetscObject)part,"MatPartitioningChacoSetLocal_C",NULL);
    683:   PetscObjectComposeFunction((PetscObject)part,"MatPartitioningChacoGetLocal_C",NULL);
    684:   PetscObjectComposeFunction((PetscObject)part,"MatPartitioningChacoSetCoarseLevel_C",NULL);
    685:   PetscObjectComposeFunction((PetscObject)part,"MatPartitioningChacoSetEigenSolver_C",NULL);
    686:   PetscObjectComposeFunction((PetscObject)part,"MatPartitioningChacoGetEigenSolver_C",NULL);
    687:   PetscObjectComposeFunction((PetscObject)part,"MatPartitioningChacoSetEigenTol_C",NULL);
    688:   PetscObjectComposeFunction((PetscObject)part,"MatPartitioningChacoGetEigenTol_C",NULL);
    689:   PetscObjectComposeFunction((PetscObject)part,"MatPartitioningChacoSetEigenNumber_C",NULL);
    690:   PetscObjectComposeFunction((PetscObject)part,"MatPartitioningChacoGetEigenNumber_C",NULL);
    691:   return(0);
    692: }

    694: /*MC
    695:    MATPARTITIONINGCHACO - Creates a partitioning context via the external package Chaco.

    697:    Level: beginner

    699:    Notes:
    700:     See http://www.cs.sandia.gov/CRF/chac.html

    702: .keywords: Partitioning, create, context

    704: .seealso: MatPartitioningSetType(), MatPartitioningType
    705: M*/

    707: PETSC_EXTERN PetscErrorCode MatPartitioningCreate_Chaco(MatPartitioning part)
    708: {
    709:   PetscErrorCode        ierr;
    710:   MatPartitioning_Chaco *chaco;

    713:   PetscNewLog(part,&chaco);
    714:   part->data = (void*)chaco;

    716:   chaco->global_method = MP_CHACO_MULTILEVEL;
    717:   chaco->local_method  = MP_CHACO_KERNIGHAN;
    718:   chaco->eigen_method  = MP_CHACO_LANCZOS;
    719:   chaco->nbvtxcoarsed  = 200;
    720:   chaco->eignum        = 1;
    721:   chaco->eigtol        = 0.001;
    722:   chaco->verbose       = PETSC_FALSE;

    724:   part->ops->apply          = MatPartitioningApply_Chaco;
    725:   part->ops->view           = MatPartitioningView_Chaco;
    726:   part->ops->destroy        = MatPartitioningDestroy_Chaco;
    727:   part->ops->setfromoptions = MatPartitioningSetFromOptions_Chaco;

    729:   PetscObjectComposeFunction((PetscObject)part,"MatPartitioningChacoSetGlobal_C",MatPartitioningChacoSetGlobal_Chaco);
    730:   PetscObjectComposeFunction((PetscObject)part,"MatPartitioningChacoGetGlobal_C",MatPartitioningChacoGetGlobal_Chaco);
    731:   PetscObjectComposeFunction((PetscObject)part,"MatPartitioningChacoSetLocal_C",MatPartitioningChacoSetLocal_Chaco);
    732:   PetscObjectComposeFunction((PetscObject)part,"MatPartitioningChacoGetLocal_C",MatPartitioningChacoGetLocal_Chaco);
    733:   PetscObjectComposeFunction((PetscObject)part,"MatPartitioningChacoSetCoarseLevel_C",MatPartitioningChacoSetCoarseLevel_Chaco);
    734:   PetscObjectComposeFunction((PetscObject)part,"MatPartitioningChacoSetEigenSolver_C",MatPartitioningChacoSetEigenSolver_Chaco);
    735:   PetscObjectComposeFunction((PetscObject)part,"MatPartitioningChacoGetEigenSolver_C",MatPartitioningChacoGetEigenSolver_Chaco);
    736:   PetscObjectComposeFunction((PetscObject)part,"MatPartitioningChacoSetEigenTol_C",MatPartitioningChacoSetEigenTol_Chaco);
    737:   PetscObjectComposeFunction((PetscObject)part,"MatPartitioningChacoGetEigenTol_C",MatPartitioningChacoGetEigenTol_Chaco);
    738:   PetscObjectComposeFunction((PetscObject)part,"MatPartitioningChacoSetEigenNumber_C",MatPartitioningChacoSetEigenNumber_Chaco);
    739:   PetscObjectComposeFunction((PetscObject)part,"MatPartitioningChacoGetEigenNumber_C",MatPartitioningChacoGetEigenNumber_Chaco);
    740:   return(0);
    741: }