Actual source code: pmetis.c
petsc-3.13.6 2020-09-29
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      2:  #include <../src/mat/impls/adj/mpi/mpiadj.h>

      4: /*
      5:    Currently using ParMetis-4.0.2
      6: */

      8: #include <parmetis.h>

     10: /*
     11:       The first 5 elements of this structure are the input control array to Metis
     12: */
     13: typedef struct {
     14:   PetscInt  cuts;         /* number of cuts made (output) */
     15:   PetscInt  foldfactor;
     16:   PetscInt  parallel;     /* use parallel partitioner for coarse problem */
     17:   PetscInt  indexing;     /* 0 indicates C indexing, 1 Fortran */
     18:   PetscInt  printout;     /* indicates if one wishes Metis to print info */
     19:   PetscBool repartition;
     20: } MatPartitioning_Parmetis;

     22: #define CHKERRQPARMETIS(n,func)                                             \
     23:   if (n == METIS_ERROR_INPUT) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"ParMETIS error due to wrong inputs and/or options for %s",func); \
     24:   else if (n == METIS_ERROR_MEMORY) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"ParMETIS error due to insufficient memory in %s",func); \
     25:   else if (n == METIS_ERROR) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"ParMETIS general error in %s",func); \

     27: #define PetscStackCallParmetis(func,args) do {PetscStackPush(#func);int status = func args;PetscStackPop; CHKERRQPARMETIS(status,#func);} while (0)

     29: static PetscErrorCode MatPartitioningApply_Parmetis_Private(MatPartitioning part, PetscBool useND, PetscBool isImprove, IS *partitioning)
     30: {
     31:   MatPartitioning_Parmetis *pmetis = (MatPartitioning_Parmetis*)part->data;
     32:   PetscErrorCode           ierr;
     33:   PetscInt                 *locals = NULL;
     34:   Mat                      mat     = part->adj,amat,pmat;
     35:   PetscBool                flg;
     36:   PetscInt                 bs = 1;

     41:   PetscObjectTypeCompare((PetscObject)mat,MATMPIADJ,&flg);
     42:   if (flg) {
     43:     amat = mat;
     44:     PetscObjectReference((PetscObject)amat);
     45:   } else {
     46:     /* bs indicates if the converted matrix is "reduced" from the original and hence the
     47:        resulting partition results need to be stretched to match the original matrix */
     48:     MatConvert(mat,MATMPIADJ,MAT_INITIAL_MATRIX,&amat);
     49:     if (amat->rmap->n > 0) bs = mat->rmap->n/amat->rmap->n;
     50:   }
     51:   MatMPIAdjCreateNonemptySubcommMat(amat,&pmat);
     52:   MPI_Barrier(PetscObjectComm((PetscObject)part));

     54:   if (pmat) {
     55:     MPI_Comm   pcomm,comm;
     56:     Mat_MPIAdj *adj     = (Mat_MPIAdj*)pmat->data;
     57:     PetscInt   *vtxdist = pmat->rmap->range;
     58:     PetscInt   *xadj    = adj->i;
     59:     PetscInt   *adjncy  = adj->j;
     60:     PetscInt   *NDorder = NULL;
     61:     PetscInt   itmp     = 0,wgtflag=0, numflag=0, ncon=1, nparts=part->n, options[24], i, j;
     62:     real_t     *tpwgts,*ubvec,itr=0.1;

     64:     PetscObjectGetComm((PetscObject)pmat,&pcomm);
     65: #if defined(PETSC_USE_DEBUG)
     66:     /* check that matrix has no diagonal entries */
     67:     {
     68:       PetscInt rstart;
     69:       MatGetOwnershipRange(pmat,&rstart,NULL);
     70:       for (i=0; i<pmat->rmap->n; i++) {
     71:         for (j=xadj[i]; j<xadj[i+1]; j++) {
     72:           if (adjncy[j] == i+rstart) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Row %D has diagonal entry; Parmetis forbids diagonal entry",i+rstart);
     73:         }
     74:       }
     75:     }
     76: #endif

     78:     PetscMalloc1(pmat->rmap->n,&locals);

     80:     if (isImprove) {
     81:       PetscInt       i;
     82:       const PetscInt *part_indices;
     84:       ISGetIndices(*partitioning,&part_indices);
     85:       for (i=0; i<pmat->rmap->n; i++) locals[i] = part_indices[i*bs];
     86:       ISRestoreIndices(*partitioning,&part_indices);
     87:       ISDestroy(partitioning);
     88:     }

     90:     if (adj->values && part->use_edge_weights && !part->vertex_weights) wgtflag = 1;
     91:     if (part->vertex_weights && !adj->values) wgtflag = 2;
     92:     if (part->vertex_weights && adj->values && part->use_edge_weights) wgtflag = 3;

     94:     if (PetscLogPrintInfo) {itmp = pmetis->printout; pmetis->printout = 127;}
     95:     PetscMalloc1(ncon*nparts,&tpwgts);
     96:     for (i=0; i<ncon; i++) {
     97:       for (j=0; j<nparts; j++) {
     98:         if (part->part_weights) {
     99:           tpwgts[i*nparts+j] = part->part_weights[i*nparts+j];
    100:         } else {
    101:           tpwgts[i*nparts+j] = 1./nparts;
    102:         }
    103:       }
    104:     }
    105:     PetscMalloc1(ncon,&ubvec);
    106:     for (i=0; i<ncon; i++) ubvec[i] = 1.05;
    107:     /* This sets the defaults */
    108:     options[0] = 0;
    109:     for (i=1; i<24; i++) options[i] = -1;
    110:     /* Duplicate the communicator to be sure that ParMETIS attribute caching does not interfere with PETSc. */
    111:     MPI_Comm_dup(pcomm,&comm);
    112:     if (useND) {
    113:       PetscInt    *sizes, *seps, log2size, subd, *level;
    114:       PetscMPIInt size;
    115:       idx_t       mtype = PARMETIS_MTYPE_GLOBAL, rtype = PARMETIS_SRTYPE_2PHASE, p_nseps = 1, s_nseps = 1;
    116:       real_t      ubfrac = 1.05;

    118:       MPI_Comm_size(comm,&size);
    119:       PetscMalloc1(pmat->rmap->n,&NDorder);
    120:       PetscMalloc3(2*size,&sizes,4*size,&seps,size,&level);
    121:       PetscStackCallParmetis(ParMETIS_V32_NodeND,((idx_t*)vtxdist,(idx_t*)xadj,(idx_t*)adjncy,(idx_t*)part->vertex_weights,(idx_t*)&numflag,&mtype,&rtype,&p_nseps,&s_nseps,&ubfrac,NULL/* seed */,NULL/* dbglvl */,(idx_t*)NDorder,(idx_t*)(sizes),&comm));
    122:       log2size = PetscLog2Real(size);
    123:       subd = PetscPowInt(2,log2size);
    124:       MatPartitioningSizesToSep_Private(subd,sizes,seps,level);
    125:       for (i=0;i<pmat->rmap->n;i++) {
    126:         PetscInt loc;

    128:         PetscFindInt(NDorder[i],2*subd,seps,&loc);
    129:         if (loc < 0) {
    130:           loc = -(loc+1);
    131:           if (loc%2) { /* part of subdomain */
    132:             locals[i] = loc/2;
    133:           } else {
    134:             PetscFindInt(NDorder[i],2*(subd-1),seps+2*subd,&loc);
    135:             loc = loc < 0 ? -(loc+1)/2 : loc/2;
    136:             locals[i] = level[loc];
    137:           }
    138:         } else locals[i] = loc/2;
    139:       }
    140:       PetscFree3(sizes,seps,level);
    141:     } else {
    142:       if (pmetis->repartition) {
    143:         PetscStackCallParmetis(ParMETIS_V3_AdaptiveRepart,((idx_t*)vtxdist,(idx_t*)xadj,(idx_t*)adjncy,(idx_t*)part->vertex_weights,(idx_t*)part->vertex_weights,(idx_t*)adj->values,(idx_t*)&wgtflag,(idx_t*)&numflag,(idx_t*)&ncon,(idx_t*)&nparts,tpwgts,ubvec,&itr,(idx_t*)options,(idx_t*)&pmetis->cuts,(idx_t*)locals,&comm));
    144:       } else if (isImprove) {
    145:         PetscStackCallParmetis(ParMETIS_V3_RefineKway,((idx_t*)vtxdist,(idx_t*)xadj,(idx_t*)adjncy,(idx_t*)part->vertex_weights,(idx_t*)adj->values,(idx_t*)&wgtflag,(idx_t*)&numflag,(idx_t*)&ncon,(idx_t*)&nparts,tpwgts,ubvec,(idx_t*)options,(idx_t*)&pmetis->cuts,(idx_t*)locals,&comm));
    146:       } else {
    147:         PetscStackCallParmetis(ParMETIS_V3_PartKway,((idx_t*)vtxdist,(idx_t*)xadj,(idx_t*)adjncy,(idx_t*)part->vertex_weights,(idx_t*)adj->values,(idx_t*)&wgtflag,(idx_t*)&numflag,(idx_t*)&ncon,(idx_t*)&nparts,tpwgts,ubvec,(idx_t*)options,(idx_t*)&pmetis->cuts,(idx_t*)locals,&comm));
    148:       }
    149:     }
    150:     MPI_Comm_free(&comm);

    152:     PetscFree(tpwgts);
    153:     PetscFree(ubvec);
    154:     if (PetscLogPrintInfo) pmetis->printout = itmp;

    156:     if (bs > 1) {
    157:       PetscInt i,j,*newlocals;
    158:       PetscMalloc1(bs*pmat->rmap->n,&newlocals);
    159:       for (i=0; i<pmat->rmap->n; i++) {
    160:         for (j=0; j<bs; j++) {
    161:           newlocals[bs*i + j] = locals[i];
    162:         }
    163:       }
    164:       PetscFree(locals);
    165:       ISCreateGeneral(PetscObjectComm((PetscObject)part),bs*pmat->rmap->n,newlocals,PETSC_OWN_POINTER,partitioning);
    166:     } else {
    167:       ISCreateGeneral(PetscObjectComm((PetscObject)part),pmat->rmap->n,locals,PETSC_OWN_POINTER,partitioning);
    168:     }
    169:     if (useND) {
    170:       IS ndis;

    172:       if (bs > 1) {
    173:         ISCreateBlock(PetscObjectComm((PetscObject)part),bs,pmat->rmap->n,NDorder,PETSC_OWN_POINTER,&ndis);
    174:       } else {
    175:         ISCreateGeneral(PetscObjectComm((PetscObject)part),pmat->rmap->n,NDorder,PETSC_OWN_POINTER,&ndis);
    176:       }
    177:       ISSetPermutation(ndis);
    178:       PetscObjectCompose((PetscObject)(*partitioning),"_petsc_matpartitioning_ndorder",(PetscObject)ndis);
    179:       ISDestroy(&ndis);
    180:     }
    181:   } else {
    182:     ISCreateGeneral(PetscObjectComm((PetscObject)part),0,NULL,PETSC_COPY_VALUES,partitioning);
    183:     if (useND) {
    184:       IS ndis;

    186:       if (bs > 1) {
    187:         ISCreateBlock(PetscObjectComm((PetscObject)part),bs,0,NULL,PETSC_COPY_VALUES,&ndis);
    188:       } else {
    189:         ISCreateGeneral(PetscObjectComm((PetscObject)part),0,NULL,PETSC_COPY_VALUES,&ndis);
    190:       }
    191:       ISSetPermutation(ndis);
    192:       PetscObjectCompose((PetscObject)(*partitioning),"_petsc_matpartitioning_ndorder",(PetscObject)ndis);
    193:       ISDestroy(&ndis);
    194:     }
    195:   }
    196:   MatDestroy(&pmat);
    197:   MatDestroy(&amat);
    198:   return(0);
    199: }

    201: /*
    202:    Uses the ParMETIS parallel matrix partitioner to compute a nested dissection ordering of the matrix in parallel
    203: */
    204: static PetscErrorCode MatPartitioningApplyND_Parmetis(MatPartitioning part, IS *partitioning)
    205: {

    209:   MatPartitioningApply_Parmetis_Private(part, PETSC_TRUE, PETSC_FALSE, partitioning);
    210:   return(0);
    211: }

    213: /*
    214:    Uses the ParMETIS parallel matrix partitioner to partition the matrix in parallel
    215: */
    216: static PetscErrorCode MatPartitioningApply_Parmetis(MatPartitioning part, IS *partitioning)
    217: {

    221:   MatPartitioningApply_Parmetis_Private(part, PETSC_FALSE, PETSC_FALSE, partitioning);
    222:   return(0);
    223: }

    225: /*
    226:    Uses the ParMETIS to improve the quality  of a partition
    227: */
    228: static PetscErrorCode MatPartitioningImprove_Parmetis(MatPartitioning part, IS *partitioning)
    229: {

    233:   MatPartitioningApply_Parmetis_Private(part, PETSC_FALSE, PETSC_TRUE, partitioning);
    234:   return(0);
    235: }

    237: PetscErrorCode MatPartitioningView_Parmetis(MatPartitioning part,PetscViewer viewer)
    238: {
    239:   MatPartitioning_Parmetis *pmetis = (MatPartitioning_Parmetis*)part->data;
    240:   PetscErrorCode           ierr;
    241:   PetscMPIInt              rank;
    242:   PetscBool                iascii;

    245:   MPI_Comm_rank(PetscObjectComm((PetscObject)part),&rank);
    246:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
    247:   if (iascii) {
    248:     if (pmetis->parallel == 2) {
    249:       PetscViewerASCIIPrintf(viewer,"  Using parallel coarse grid partitioner\n");
    250:     } else {
    251:       PetscViewerASCIIPrintf(viewer,"  Using sequential coarse grid partitioner\n");
    252:     }
    253:     PetscViewerASCIIPrintf(viewer,"  Using %D fold factor\n",pmetis->foldfactor);
    254:     PetscViewerASCIIPushSynchronized(viewer);
    255:     PetscViewerASCIISynchronizedPrintf(viewer,"  [%d]Number of cuts found %D\n",rank,pmetis->cuts);
    256:     PetscViewerFlush(viewer);
    257:     PetscViewerASCIIPopSynchronized(viewer);
    258:   }
    259:   return(0);
    260: }

    262: /*@
    263:      MatPartitioningParmetisSetCoarseSequential - Use the sequential code to
    264:          do the partitioning of the coarse grid.

    266:   Logically Collective on MatPartitioning

    268:   Input Parameter:
    269: .  part - the partitioning context

    271:    Level: advanced

    273: @*/
    274: PetscErrorCode  MatPartitioningParmetisSetCoarseSequential(MatPartitioning part)
    275: {
    276:   MatPartitioning_Parmetis *pmetis = (MatPartitioning_Parmetis*)part->data;

    279:   pmetis->parallel = 1;
    280:   return(0);
    281: }

    283: /*@
    284:      MatPartitioningParmetisSetRepartition - Repartition
    285:      current mesh to rebalance computation.

    287:   Logically Collective on MatPartitioning

    289:   Input Parameter:
    290: .  part - the partitioning context

    292:    Level: advanced

    294: @*/
    295: PetscErrorCode  MatPartitioningParmetisSetRepartition(MatPartitioning part)
    296: {
    297:   MatPartitioning_Parmetis *pmetis = (MatPartitioning_Parmetis*)part->data;

    300:   pmetis->repartition = PETSC_TRUE;
    301:   return(0);
    302: }

    304: /*@
    305:   MatPartitioningParmetisGetEdgeCut - Returns the number of edge cuts in the vertex partition.

    307:   Input Parameter:
    308: . part - the partitioning context

    310:   Output Parameter:
    311: . cut - the edge cut

    313:    Level: advanced

    315: @*/
    316: PetscErrorCode  MatPartitioningParmetisGetEdgeCut(MatPartitioning part, PetscInt *cut)
    317: {
    318:   MatPartitioning_Parmetis *pmetis = (MatPartitioning_Parmetis*) part->data;

    321:   *cut = pmetis->cuts;
    322:   return(0);
    323: }

    325: PetscErrorCode MatPartitioningSetFromOptions_Parmetis(PetscOptionItems *PetscOptionsObject,MatPartitioning part)
    326: {
    328:   PetscBool      flag = PETSC_FALSE;

    331:   PetscOptionsHead(PetscOptionsObject,"Set ParMeTiS partitioning options");
    332:   PetscOptionsBool("-mat_partitioning_parmetis_coarse_sequential","Use sequential coarse partitioner","MatPartitioningParmetisSetCoarseSequential",flag,&flag,NULL);
    333:   if (flag) {
    334:     MatPartitioningParmetisSetCoarseSequential(part);
    335:   }
    336:   PetscOptionsBool("-mat_partitioning_parmetis_repartition","","MatPartitioningParmetisSetRepartition",flag,&flag,NULL);
    337:   if(flag){
    338:      MatPartitioningParmetisSetRepartition(part);
    339:   }
    340:   PetscOptionsTail();
    341:   return(0);
    342: }

    345: PetscErrorCode MatPartitioningDestroy_Parmetis(MatPartitioning part)
    346: {
    347:   MatPartitioning_Parmetis *pmetis = (MatPartitioning_Parmetis*)part->data;
    348:   PetscErrorCode           ierr;

    351:   PetscFree(pmetis);
    352:   return(0);
    353: }

    356: /*MC
    357:    MATPARTITIONINGPARMETIS - Creates a partitioning context via the external package PARMETIS.

    359:    Collective

    361:    Input Parameter:
    362: .  part - the partitioning context

    364:    Options Database Keys:
    365: .  -mat_partitioning_parmetis_coarse_sequential - use sequential PARMETIS coarse partitioner

    367:    Level: beginner

    369:    Notes:
    370:     See https://www-users.cs.umn.edu/~karypis/metis/

    372: .seealso: MatPartitioningSetType(), MatPartitioningType

    374: M*/

    376: PETSC_EXTERN PetscErrorCode MatPartitioningCreate_Parmetis(MatPartitioning part)
    377: {
    378:   PetscErrorCode           ierr;
    379:   MatPartitioning_Parmetis *pmetis;

    382:   PetscNewLog(part,&pmetis);
    383:   part->data = (void*)pmetis;

    385:   pmetis->cuts       = 0;   /* output variable */
    386:   pmetis->foldfactor = 150; /*folding factor */
    387:   pmetis->parallel   = 2;   /* use parallel partitioner for coarse grid */
    388:   pmetis->indexing   = 0;   /* index numbering starts from 0 */
    389:   pmetis->printout   = 0;   /* print no output while running */
    390:   pmetis->repartition      = PETSC_FALSE;

    392:   part->ops->apply          = MatPartitioningApply_Parmetis;
    393:   part->ops->applynd        = MatPartitioningApplyND_Parmetis;
    394:   part->ops->improve        = MatPartitioningImprove_Parmetis;
    395:   part->ops->view           = MatPartitioningView_Parmetis;
    396:   part->ops->destroy        = MatPartitioningDestroy_Parmetis;
    397:   part->ops->setfromoptions = MatPartitioningSetFromOptions_Parmetis;
    398:   return(0);
    399: }

    401: /*@
    402:  MatMeshToVertexGraph -   This routine does not exist because ParMETIS does not provide the functionality.  Uses the ParMETIS package to
    403:                        convert a Mat that represents a mesh to a Mat the represents the graph of the coupling
    404:                        between vertices of the cells and is suitable for partitioning with the MatPartitioning object. Use this to partition
    405:                        vertices of a mesh. More likely you should use MatMeshToCellGraph()

    407:    Collective on Mat

    409:    Input Parameter:
    410: +     mesh - the graph that represents the mesh
    411: -     ncommonnodes - mesh elements that share this number of common nodes are considered neighbors, use 2 for triangles and
    412:                      quadrilaterials, 3 for tetrahedrals and 4 for hexahedrals

    414:    Output Parameter:
    415: .     dual - the dual graph

    417:    Notes:
    418:      Currently requires ParMetis to be installed and uses ParMETIS_V3_Mesh2Dual()

    420:      The columns of each row of the Mat mesh are the global vertex numbers of the vertices of that rows cell. The number of rows in mesh is
    421:      number of cells, the number of columns is the number of vertices.

    423:    Level: advanced

    425: .seealso: MatMeshToCellGraph(), MatCreateMPIAdj(), MatPartitioningCreate()

    427: @*/
    428: PetscErrorCode MatMeshToVertexGraph(Mat mesh,PetscInt ncommonnodes,Mat *dual)
    429: {
    431:   SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"ParMETIS does not provide this functionality");
    432:   return(0);
    433: }

    435: /*@
    436:      MatMeshToCellGraph -   Uses the ParMETIS package to convert a Mat that represents a mesh to a Mat the represents the graph of the coupling
    437:                        between cells (the "dual" graph) and is suitable for partitioning with the MatPartitioning object. Use this to partition
    438:                        cells of a mesh.

    440:    Collective on Mat

    442:    Input Parameter:
    443: +     mesh - the graph that represents the mesh
    444: -     ncommonnodes - mesh elements that share this number of common nodes are considered neighbors, use 2 for triangles and
    445:                      quadrilaterials, 3 for tetrahedrals and 4 for hexahedrals

    447:    Output Parameter:
    448: .     dual - the dual graph

    450:    Notes:
    451:      Currently requires ParMetis to be installed and uses ParMETIS_V3_Mesh2Dual()

    453: $     Each row of the mesh object represents a single cell in the mesh. For triangles it has 3 entries, quadrilaterials 4 entries,
    454: $         tetrahedrals 4 entries and hexahedrals 8 entries. You can mix triangles and quadrilaterals in the same mesh, but cannot
    455: $         mix  tetrahedrals and hexahedrals
    456: $     The columns of each row of the Mat mesh are the global vertex numbers of the vertices of that row's cell.
    457: $     The number of rows in mesh is number of cells, the number of columns is the number of vertices.

    460:    Level: advanced

    462: .seealso: MatMeshToVertexGraph(), MatCreateMPIAdj(), MatPartitioningCreate()

    465: @*/
    466: PetscErrorCode MatMeshToCellGraph(Mat mesh,PetscInt ncommonnodes,Mat *dual)
    467: {
    469:   PetscInt       *newxadj,*newadjncy;
    470:   PetscInt       numflag=0;
    471:   Mat_MPIAdj     *adj   = (Mat_MPIAdj*)mesh->data,*newadj;
    472:   PetscBool      flg;
    473:   MPI_Comm       comm;

    476:   PetscObjectTypeCompare((PetscObject)mesh,MATMPIADJ,&flg);
    477:   if (!flg) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Must use MPIAdj matrix type");

    479:   PetscObjectGetComm((PetscObject)mesh,&comm);
    480:   PetscStackCallParmetis(ParMETIS_V3_Mesh2Dual,((idx_t*)mesh->rmap->range,(idx_t*)adj->i,(idx_t*)adj->j,(idx_t*)&numflag,(idx_t*)&ncommonnodes,(idx_t**)&newxadj,(idx_t**)&newadjncy,&comm));
    481:   MatCreateMPIAdj(PetscObjectComm((PetscObject)mesh),mesh->rmap->n,mesh->rmap->N,newxadj,newadjncy,NULL,dual);
    482:   newadj = (Mat_MPIAdj*)(*dual)->data;

    484:   newadj->freeaijwithfree = PETSC_TRUE; /* signal the matrix should be freed with system free since space was allocated by ParMETIS */
    485:   return(0);
    486: }