Date: 2016-07-24T16:58:19+00:00

Actual source code: chaco.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: /* Chaco does not have an include file */
      9: PETSC_EXTERN int interface(int nvtxs, int *start, int *adjacency, int *vwgts,
     10:                      float *ewgts, float *x, float *y, float *z, char *outassignname,
     11:                      char *outfilename, short *assignment, int architecture, int ndims_tot,
     12:                      int mesh_dims[3], double *goal, int global_method, int local_method,
     13:                      int rqi_flag, int vmax, int ndims, double eigtol, long seed);

     15: extern int FREE_GRAPH;

     17: /*
     18: int       nvtxs;                number of vertices in full graph
     19: int      *start;                start of edge list for each vertex
     20: int      *adjacency;            edge list data
     21: int      *vwgts;                weights for all vertices
     22: float    *ewgts;                weights for all edges
     23: float    *x, *y, *z;            coordinates for inertial method
     24: char     *outassignname;        name of assignment output file
     25: char     *outfilename;          output file name
     26: short    *assignment;           set number of each vtx (length n)
     27: int       architecture;         0 => hypercube, d => d-dimensional mesh
     28: int       ndims_tot;            total number of cube dimensions to divide
     29: int       mesh_dims[3];         dimensions of mesh of processors
     30: double   *goal;                 desired set sizes for each set
     31: int       global_method;        global partitioning algorithm
     32: int       local_method;         local partitioning algorithm
     33: int       rqi_flag;             should I use RQI/Symmlq eigensolver?
     34: int       vmax;                 how many vertices to coarsen down to?
     35: int       ndims;                number of eigenvectors (2^d sets)
     36: double    eigtol;               tolerance on eigenvectors
     37: long      seed;                 for random graph mutations
     38: */

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

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

     54: static PetscErrorCode MatPartitioningApply_Chaco(MatPartitioning part,IS *partitioning)
     55: {
     56:   PetscErrorCode        ierr;
     57:   PetscInt              *parttab,*locals,i,nb_locals,M,N;
     58:   PetscMPIInt           size,rank;
     59:   Mat                   mat = part->adj,matAdj,matSeq,*A;
     60:   Mat_MPIAdj            *adj;
     61:   MatPartitioning_Chaco *chaco = (MatPartitioning_Chaco*)part->data;
     62:   PetscBool             flg;
     63:   IS                    isrow, iscol;
     64:   int                   nvtxs,*start,*adjacency,*vwgts,architecture,ndims_tot;
     65:   int                   mesh_dims[3],global_method,local_method,rqi_flag,vmax,ndims;
     66:   short                 *assignment;
     67:   double                eigtol;
     68:   long                  seed;
     69:   char                  *mesg_log;
     70: #if defined(PETSC_HAVE_UNISTD_H)
     71:   int                   fd_stdout,fd_pipe[2],count,err;
     72: #endif

     75:   FREE_GRAPH = 0; /* otherwise Chaco will attempt to free memory for adjacency graph */
     76:   MPI_Comm_size(PetscObjectComm((PetscObject)mat),&size);
     77:   MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);
     78:   PetscObjectTypeCompare((PetscObject)mat,MATMPIADJ,&flg);
     79:   if (size>1) {
     80:     if (flg) SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_SUP,"Distributed matrix format MPIAdj is not supported for sequential partitioners");
     81:     PetscInfo(part,"Converting distributed matrix to sequential: this could be a performance loss\n");
     82:     MatGetSize(mat,&M,&N);
     83:     ISCreateStride(PETSC_COMM_SELF,M,0,1,&isrow);
     84:     ISCreateStride(PETSC_COMM_SELF,N,0,1,&iscol);
     85:     MatGetSubMatrices(mat,1,&isrow,&iscol,MAT_INITIAL_MATRIX,&A);
     86:     ISDestroy(&isrow);
     87:     ISDestroy(&iscol);
     88:     matSeq = *A;
     89:     PetscFree(A);
     90:   } else {
     91:     PetscObjectReference((PetscObject)mat);
     92:     matSeq = mat;
     93:   }

     95:   if (!flg) { /* convert regular matrix to MPIADJ */
     96:     MatConvert(matSeq,MATMPIADJ,MAT_INITIAL_MATRIX,&matAdj);
     97:   } else {
     98:     PetscObjectReference((PetscObject)matSeq);
     99:     matAdj = matSeq;
    100:   }

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

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

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

    123:   /* redirect output to buffer */
    124: #if defined(PETSC_HAVE_UNISTD_H)
    125:   fd_stdout = dup(1);
    126:   if (pipe(fd_pipe)) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SYS,"Could not open pipe");
    127:   close(1);
    128:   dup2(fd_pipe[1],1);
    129:   PetscMalloc1(SIZE_LOG,&mesg_log);
    130: #endif

    132:   /* library call */
    133:   interface(nvtxs,start,adjacency,vwgts,NULL,NULL,NULL,NULL,
    134:                    NULL,NULL,assignment,architecture,ndims_tot,mesh_dims,
    135:                    NULL,global_method,local_method,rqi_flag,vmax,ndims,eigtol,seed);

    137: #if defined(PETSC_HAVE_UNISTD_H)
    138:   err = fflush(stdout);
    139:   if (err) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SYS,"fflush() failed on stdout");
    140:   count = read(fd_pipe[0],mesg_log,(SIZE_LOG-1)*sizeof(char));
    141:   if (count<0) count = 0;
    142:   mesg_log[count] = 0;
    143:   close(1);
    144:   dup2(fd_stdout,1);
    145:   close(fd_stdout);
    146:   close(fd_pipe[0]);
    147:   close(fd_pipe[1]);
    148:   if (chaco->verbose) {
    149:     PetscPrintf(PetscObjectComm((PetscObject)mat),mesg_log);
    150:   }
    151:   PetscFree(mesg_log);
    152: #endif
    153:   if (ierr) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_LIB,"Chaco failed");

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

    158:   /* creation of the index set */
    159:   nb_locals = mat->rmap->N / size;
    160:   locals    = parttab + rank*nb_locals;
    161:   if (rank < mat->rmap->N % size) {
    162:     nb_locals++;
    163:     locals += rank;
    164:   } else locals += mat->rmap->N % size;

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

    168:   /* clean up */
    169:   PetscFree(parttab);
    170:   PetscFree(adjacency);
    171:   PetscFree(assignment);
    172:   MatDestroy(&matSeq);
    173:   MatDestroy(&matAdj);
    174:   return(0);
    175: }

    179: PetscErrorCode MatPartitioningView_Chaco(MatPartitioning part, PetscViewer viewer)
    180: {
    181:   MatPartitioning_Chaco *chaco = (MatPartitioning_Chaco*)part->data;
    182:   PetscErrorCode        ierr;
    183:   PetscBool             isascii;

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

    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: }

    234: PetscErrorCode MatPartitioningChacoSetGlobal_Chaco(MatPartitioning part,MPChacoGlobalType method)
    235: {
    236:   MatPartitioning_Chaco *chaco = (MatPartitioning_Chaco*)part->data;

    239:   switch (method) {
    240:   case MP_CHACO_MULTILEVEL:
    241:   case MP_CHACO_SPECTRAL:
    242:   case MP_CHACO_LINEAR:
    243:   case MP_CHACO_RANDOM:
    244:   case MP_CHACO_SCATTERED:
    245:     chaco->global_method = method; break;
    246:   default:
    247:     SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Chaco: Unknown or unsupported option");
    248:   }
    249:   return(0);
    250: }

    254: /*@
    255:    MatPartitioningChacoGetGlobal - Get global method for Chaco partitioner.

    257:    Not Collective

    259:    Input Parameter:
    260: .  part - the partitioning context

    262:    Output Parameter:
    263: .  method - the method

    265:    Level: advanced

    267: .seealso: MatPartitioningChacoSetGlobal()
    268: @*/
    269: PetscErrorCode MatPartitioningChacoGetGlobal(MatPartitioning part,MPChacoGlobalType *method)
    270: {

    276:   PetscTryMethod(part,"MatPartitioningChacoGetGlobal_C",(MatPartitioning,MPChacoGlobalType*),(part,method));
    277:   return(0);
    278: }

    282: PetscErrorCode MatPartitioningChacoGetGlobal_Chaco(MatPartitioning part,MPChacoGlobalType *method)
    283: {
    284:   MatPartitioning_Chaco *chaco = (MatPartitioning_Chaco*)part->data;

    287:   *method = chaco->global_method;
    288:   return(0);
    289: }

    293: /*@
    294:    MatPartitioningChacoSetLocal - Set local method for Chaco partitioner.

    296:    Collective on MatPartitioning

    298:    Input Parameters:
    299: +  part - the partitioning context
    300: -  method - one of MP_CHACO_KERNIGHAN or MP_CHACO_NONE

    302:    Options Database:
    303: .  -mat_partitioning_chaco_local <method> - the local method

    305:    Level: advanced

    307:    Notes:
    308:    The default is to apply the Kernighan-Lin heuristic. See Chaco documentation
    309:    for additional details.

    311: .seealso: MatPartitioningChacoSetGlobal(),MatPartitioningChacoGetLocal()
    312: @*/
    313: PetscErrorCode MatPartitioningChacoSetLocal(MatPartitioning part,MPChacoLocalType method)
    314: {

    320:   PetscTryMethod(part,"MatPartitioningChacoSetLocal_C",(MatPartitioning,MPChacoLocalType),(part,method));
    321:   return(0);
    322: }

    326: PetscErrorCode MatPartitioningChacoSetLocal_Chaco(MatPartitioning part,MPChacoLocalType method)
    327: {
    328:   MatPartitioning_Chaco *chaco = (MatPartitioning_Chaco*)part->data;

    331:   switch (method) {
    332:   case MP_CHACO_KERNIGHAN:
    333:   case MP_CHACO_NONE:
    334:     chaco->local_method = method; break;
    335:   default:
    336:     SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Chaco: Unknown or unsupported option");
    337:   }
    338:   return(0);
    339: }

    343: /*@
    344:    MatPartitioningChacoGetLocal - Get local method for Chaco partitioner.

    346:    Not Collective

    348:    Input Parameter:
    349: .  part - the partitioning context

    351:    Output Parameter:
    352: .  method - the method

    354:    Level: advanced

    356: .seealso: MatPartitioningChacoSetLocal()
    357: @*/
    358: PetscErrorCode MatPartitioningChacoGetLocal(MatPartitioning part,MPChacoLocalType *method)
    359: {

    365:   PetscUseMethod(part,"MatPartitioningChacoGetLocal_C",(MatPartitioning,MPChacoLocalType*),(part,method));
    366:   return(0);
    367: }

    371: PetscErrorCode MatPartitioningChacoGetLocal_Chaco(MatPartitioning part,MPChacoLocalType *method)
    372: {
    373:   MatPartitioning_Chaco *chaco = (MatPartitioning_Chaco*)part->data;

    376:   *method = chaco->local_method;
    377:   return(0);
    378: }

    382: /*@
    383:    MatPartitioningChacoSetCoarseLevel - Set the coarse level parameter for the
    384:    Chaco partitioner.

    386:    Collective on MatPartitioning

    388:    Input Parameters:
    389: +  part - the partitioning context
    390: -  level - the coarse level in range [0.0,1.0]

    392:    Options Database:
    393: .  -mat_partitioning_chaco_coarse <l> - Coarse level

    395:    Level: advanced
    396: @*/
    397: PetscErrorCode MatPartitioningChacoSetCoarseLevel(MatPartitioning part,PetscReal level)
    398: {

    404:   PetscTryMethod(part,"MatPartitioningChacoSetCoarseLevel_C",(MatPartitioning,PetscReal),(part,level));
    405:   return(0);
    406: }

    410: PetscErrorCode MatPartitioningChacoSetCoarseLevel_Chaco(MatPartitioning part,PetscReal level)
    411: {
    412:   MatPartitioning_Chaco *chaco = (MatPartitioning_Chaco*)part->data;

    415:   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]");
    416:   chaco->nbvtxcoarsed = (PetscInt)(part->adj->cmap->N * level);
    417:   if (chaco->nbvtxcoarsed < 20) chaco->nbvtxcoarsed = 20;
    418:   return(0);
    419: }

    423: /*@
    424:    MatPartitioningChacoSetEigenSolver - Set eigensolver method for Chaco partitioner.

    426:    Collective on MatPartitioning

    428:    Input Parameters:
    429: +  part - the partitioning context
    430: -  method - one of MP_CHACO_LANCZOS or MP_CHACO_RQI

    432:    Options Database:
    433: .  -mat_partitioning_chaco_eigen_solver <method> - the eigensolver

    435:    Level: advanced

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

    440: .seealso: MatPartitioningChacoSetEigenTol(),MatPartitioningChacoSetEigenNumber(),
    441:           MatPartitioningChacoGetEigenSolver()
    442: @*/
    443: PetscErrorCode MatPartitioningChacoSetEigenSolver(MatPartitioning part,MPChacoEigenType method)
    444: {

    450:   PetscTryMethod(part,"MatPartitioningChacoSetEigenSolver_C",(MatPartitioning,MPChacoEigenType),(part,method));
    451:   return(0);
    452: }

    456: PetscErrorCode MatPartitioningChacoSetEigenSolver_Chaco(MatPartitioning part,MPChacoEigenType method)
    457: {
    458:   MatPartitioning_Chaco *chaco = (MatPartitioning_Chaco*)part->data;

    461:   switch (method) {
    462:   case MP_CHACO_LANCZOS:
    463:   case MP_CHACO_RQI:
    464:     chaco->eigen_method = method; break;
    465:   default:
    466:     SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Chaco: Unknown or unsupported option");
    467:   }
    468:   return(0);
    469: }

    473: /*@
    474:    MatPartitioningChacoGetEigenSolver - Get local method for Chaco partitioner.

    476:    Not Collective

    478:    Input Parameter:
    479: .  part - the partitioning context

    481:    Output Parameter:
    482: .  method - the method

    484:    Level: advanced

    486: .seealso: MatPartitioningChacoSetEigenSolver()
    487: @*/
    488: PetscErrorCode MatPartitioningChacoGetEigenSolver(MatPartitioning part,MPChacoEigenType *method)
    489: {

    495:   PetscUseMethod(part,"MatPartitioningChacoGetEigenSolver_C",(MatPartitioning,MPChacoEigenType*),(part,method));
    496:   return(0);
    497: }

    501: PetscErrorCode MatPartitioningChacoGetEigenSolver_Chaco(MatPartitioning part,MPChacoEigenType *method)
    502: {
    503:   MatPartitioning_Chaco *chaco = (MatPartitioning_Chaco*)part->data;

    506:   *method = chaco->eigen_method;
    507:   return(0);
    508: }

    512: /*@
    513:    MatPartitioningChacoSetEigenTol - Sets the tolerance for the eigensolver.

    515:    Collective on MatPartitioning

    517:    Input Parameters:
    518: +  part - the partitioning context
    519: -  tol  - the tolerance

    521:    Options Database:
    522: .  -mat_partitioning_chaco_eigen_tol <tol>: Tolerance for eigensolver

    524:    Note:
    525:    Must be positive. The default value is 0.001.

    527:    Level: advanced

    529: .seealso: MatPartitioningChacoSetEigenSolver(), MatPartitioningChacoGetEigenTol()
    530: @*/
    531: PetscErrorCode MatPartitioningChacoSetEigenTol(MatPartitioning part,PetscReal tol)
    532: {

    538:   PetscTryMethod(part,"MatPartitioningChacoSetEigenTol_C",(MatPartitioning,PetscReal),(part,tol));
    539:   return(0);
    540: }

    544: PetscErrorCode MatPartitioningChacoSetEigenTol_Chaco(MatPartitioning part,PetscReal tol)
    545: {
    546:   MatPartitioning_Chaco *chaco = (MatPartitioning_Chaco*)part->data;

    549:   if (tol==PETSC_DEFAULT) chaco->eigtol = 0.001;
    550:   else {
    551:     if (tol<=0.0) SETERRQ(PetscObjectComm((PetscObject)part),PETSC_ERR_ARG_OUTOFRANGE,"Tolerance must be positive");
    552:     chaco->eigtol = tol;
    553:   }
    554:   return(0);
    555: }

    559: /*@
    560:    MatPartitioningChacoGetEigenTol - Gets the eigensolver tolerance.

    562:    Not Collective

    564:    Input Parameter:
    565: .  part - the partitioning context

    567:    Output Parameter:
    568: .  tol  - the tolerance

    570:    Level: advanced

    572: .seealso: MatPartitioningChacoSetEigenTol()
    573: @*/
    574: PetscErrorCode MatPartitioningChacoGetEigenTol(MatPartitioning part,PetscReal *tol)
    575: {

    581:   PetscUseMethod(part,"MatPartitioningChacoGetEigenTol_C",(MatPartitioning,PetscReal*),(part,tol));
    582:   return(0);
    583: }

    587: PetscErrorCode MatPartitioningChacoGetEigenTol_Chaco(MatPartitioning part,PetscReal *tol)
    588: {
    589:   MatPartitioning_Chaco *chaco = (MatPartitioning_Chaco*)part->data;

    592:   *tol = chaco->eigtol;
    593:   return(0);
    594: }

    598: /*@
    599:    MatPartitioningChacoSetEigenNumber - Sets the number of eigenvectors to compute
    600:    during partitioning.

    602:    Collective on MatPartitioning

    604:    Input Parameters:
    605: +  part - the partitioning context
    606: -  num  - the number of eigenvectors

    608:    Options Database:
    609: .  -mat_partitioning_chaco_eigen_number <n>: Number of eigenvectors

    611:    Note:
    612:    Accepted values are 1, 2 or 3, indicating partitioning by bisection,
    613:    quadrisection, or octosection.

    615:    Level: advanced

    617: .seealso: MatPartitioningChacoSetEigenSolver(), MatPartitioningChacoGetEigenTol()
    618: @*/
    619: PetscErrorCode MatPartitioningChacoSetEigenNumber(MatPartitioning part,PetscInt num)
    620: {

    626:   PetscTryMethod(part,"MatPartitioningChacoSetEigenNumber_C",(MatPartitioning,PetscInt),(part,num));
    627:   return(0);
    628: }

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

    637:   if (num==PETSC_DEFAULT) chaco->eignum = 1;
    638:   else {
    639:     if (num<1 || num>3) SETERRQ(PetscObjectComm((PetscObject)part),PETSC_ERR_ARG_OUTOFRANGE,"Can only specify 1, 2 or 3 eigenvectors");
    640:     chaco->eignum = num;
    641:   }
    642:   return(0);
    643: }

    647: /*@
    648:    MatPartitioningChacoGetEigenNumber - Gets the number of eigenvectors used by Chaco.

    650:    Not Collective

    652:    Input Parameter:
    653: .  part - the partitioning context

    655:    Output Parameter:
    656: .  num  - number of eigenvectors

    658:    Level: advanced

    660: .seealso: MatPartitioningChacoSetEigenNumber()
    661: @*/
    662: PetscErrorCode MatPartitioningChacoGetEigenNumber(MatPartitioning part,PetscInt *num)
    663: {

    669:   PetscUseMethod(part,"MatPartitioningChacoGetEigenNumber_C",(MatPartitioning,PetscInt*),(part,num));
    670:   return(0);
    671: }

    675: PetscErrorCode MatPartitioningChacoGetEigenNumber_Chaco(MatPartitioning part,PetscInt *num)
    676: {
    677:   MatPartitioning_Chaco *chaco = (MatPartitioning_Chaco*)part->data;

    680:   *num = chaco->eignum;
    681:   return(0);
    682: }

    686: PetscErrorCode MatPartitioningSetFromOptions_Chaco(PetscOptionItems *PetscOptionsObject,MatPartitioning part)
    687: {
    688:   PetscErrorCode        ierr;
    689:   PetscInt              i;
    690:   PetscReal             r;
    691:   PetscBool             flag;
    692:   MatPartitioning_Chaco *chaco = (MatPartitioning_Chaco*)part->data;
    693:   MPChacoGlobalType     global;
    694:   MPChacoLocalType      local;
    695:   MPChacoEigenType      eigen;

    698:   PetscOptionsHead(PetscOptionsObject,"Chaco partitioning options");
    699:   PetscOptionsEnum("-mat_partitioning_chaco_global","Global method","MatPartitioningChacoSetGlobal",MPChacoGlobalTypes,(PetscEnum)chaco->global_method,(PetscEnum*)&global,&flag);
    700:   if (flag) { MatPartitioningChacoSetGlobal(part,global); }
    701:   PetscOptionsEnum("-mat_partitioning_chaco_local","Local method","MatPartitioningChacoSetLocal",MPChacoLocalTypes,(PetscEnum)chaco->local_method,(PetscEnum*)&local,&flag);
    702:   if (flag) { MatPartitioningChacoSetLocal(part,local); }
    703:   PetscOptionsReal("-mat_partitioning_chaco_coarse","Coarse level","MatPartitioningChacoSetCoarseLevel",0.0,&r,&flag);
    704:   if (flag) { MatPartitioningChacoSetCoarseLevel(part,r); }
    705:   PetscOptionsEnum("-mat_partitioning_chaco_eigen_solver","Eigensolver method","MatPartitioningChacoSetEigenSolver",MPChacoEigenTypes,(PetscEnum)chaco->eigen_method,(PetscEnum*)&eigen,&flag);
    706:   if (flag) { MatPartitioningChacoSetEigenSolver(part,eigen); }
    707:   PetscOptionsReal("-mat_partitioning_chaco_eigen_tol","Eigensolver tolerance","MatPartitioningChacoSetEigenTol",chaco->eigtol,&r,&flag);
    708:   if (flag) { MatPartitioningChacoSetEigenTol(part,r); }
    709:   PetscOptionsInt("-mat_partitioning_chaco_eigen_number","Number of eigenvectors: 1, 2, or 3 (bi-, quadri-, or octosection)","MatPartitioningChacoSetEigenNumber",chaco->eignum,&i,&flag);
    710:   if (flag) { MatPartitioningChacoSetEigenNumber(part,i); }
    711:   PetscOptionsBool("-mat_partitioning_chaco_verbose","Show library output","",chaco->verbose,&chaco->verbose,NULL);
    712:   PetscOptionsTail();
    713:   return(0);
    714: }

    718: PetscErrorCode MatPartitioningDestroy_Chaco(MatPartitioning part)
    719: {
    720:   MatPartitioning_Chaco *chaco = (MatPartitioning_Chaco*) part->data;
    721:   PetscErrorCode        ierr;

    724:   PetscFree(chaco);
    725:   /* clear composed functions */
    726:   PetscObjectComposeFunction((PetscObject)part,"MatPartitioningChacoSetGlobal_C",NULL);
    727:   PetscObjectComposeFunction((PetscObject)part,"MatPartitioningChacoGetGlobal_C",NULL);
    728:   PetscObjectComposeFunction((PetscObject)part,"MatPartitioningChacoSetLocal_C",NULL);
    729:   PetscObjectComposeFunction((PetscObject)part,"MatPartitioningChacoGetLocal_C",NULL);
    730:   PetscObjectComposeFunction((PetscObject)part,"MatPartitioningChacoSetCoarseLevel_C",NULL);
    731:   PetscObjectComposeFunction((PetscObject)part,"MatPartitioningChacoSetEigenSolver_C",NULL);
    732:   PetscObjectComposeFunction((PetscObject)part,"MatPartitioningChacoGetEigenSolver_C",NULL);
    733:   PetscObjectComposeFunction((PetscObject)part,"MatPartitioningChacoSetEigenTol_C",NULL);
    734:   PetscObjectComposeFunction((PetscObject)part,"MatPartitioningChacoGetEigenTol_C",NULL);
    735:   PetscObjectComposeFunction((PetscObject)part,"MatPartitioningChacoSetEigenNumber_C",NULL);
    736:   PetscObjectComposeFunction((PetscObject)part,"MatPartitioningChacoGetEigenNumber_C",NULL);
    737:   return(0);
    738: }

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

    743:    Level: beginner

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

    747: .keywords: Partitioning, create, context

    749: .seealso: MatPartitioningSetType(), MatPartitioningType
    750: M*/

    754: PETSC_EXTERN PetscErrorCode MatPartitioningCreate_Chaco(MatPartitioning part)
    755: {
    756:   PetscErrorCode        ierr;
    757:   MatPartitioning_Chaco *chaco;

    760:   PetscNewLog(part,&chaco);
    761:   part->data = (void*)chaco;

    763:   chaco->global_method = MP_CHACO_MULTILEVEL;
    764:   chaco->local_method  = MP_CHACO_KERNIGHAN;
    765:   chaco->eigen_method  = MP_CHACO_LANCZOS;
    766:   chaco->nbvtxcoarsed  = 200;
    767:   chaco->eignum        = 1;
    768:   chaco->eigtol        = 0.001;
    769:   chaco->verbose       = PETSC_FALSE;

    771:   part->ops->apply          = MatPartitioningApply_Chaco;
    772:   part->ops->view           = MatPartitioningView_Chaco;
    773:   part->ops->destroy        = MatPartitioningDestroy_Chaco;
    774:   part->ops->setfromoptions = MatPartitioningSetFromOptions_Chaco;

    776:   PetscObjectComposeFunction((PetscObject)part,"MatPartitioningChacoSetGlobal_C",MatPartitioningChacoSetGlobal_Chaco);
    777:   PetscObjectComposeFunction((PetscObject)part,"MatPartitioningChacoGetGlobal_C",MatPartitioningChacoGetGlobal_Chaco);
    778:   PetscObjectComposeFunction((PetscObject)part,"MatPartitioningChacoSetLocal_C",MatPartitioningChacoSetLocal_Chaco);
    779:   PetscObjectComposeFunction((PetscObject)part,"MatPartitioningChacoGetLocal_C",MatPartitioningChacoGetLocal_Chaco);
    780:   PetscObjectComposeFunction((PetscObject)part,"MatPartitioningChacoSetCoarseLevel_C",MatPartitioningChacoSetCoarseLevel_Chaco);
    781:   PetscObjectComposeFunction((PetscObject)part,"MatPartitioningChacoSetEigenSolver_C",MatPartitioningChacoSetEigenSolver_Chaco);
    782:   PetscObjectComposeFunction((PetscObject)part,"MatPartitioningChacoGetEigenSolver_C",MatPartitioningChacoGetEigenSolver_Chaco);
    783:   PetscObjectComposeFunction((PetscObject)part,"MatPartitioningChacoSetEigenTol_C",MatPartitioningChacoSetEigenTol_Chaco);
    784:   PetscObjectComposeFunction((PetscObject)part,"MatPartitioningChacoGetEigenTol_C",MatPartitioningChacoGetEigenTol_Chaco);
    785:   PetscObjectComposeFunction((PetscObject)part,"MatPartitioningChacoSetEigenNumber_C",MatPartitioningChacoSetEigenNumber_Chaco);
    786:   PetscObjectComposeFunction((PetscObject)part,"MatPartitioningChacoGetEigenNumber_C",MatPartitioningChacoGetEigenNumber_Chaco);
    787:   return(0);
    788: }