Date: 2022-03-04T17:38:19+00:00

Actual source code: pmetis.c

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

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

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

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

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

    116:       MPI_Comm_size(comm,&size);
    117:       PetscMalloc1(pmat->rmap->n,&NDorder);
    118:       PetscMalloc3(2*size,&sizes,4*size,&seps,size,&level);
    119:       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));
    120:       log2size = PetscLog2Real(size);
    121:       subd = PetscPowInt(2,log2size);
    122:       MatPartitioningSizesToSep_Private(subd,sizes,seps,level);
    123:       for (i=0;i<pmat->rmap->n;i++) {
    124:         PetscInt loc;

    126:         PetscFindInt(NDorder[i],2*subd,seps,&loc);
    127:         if (loc < 0) {
    128:           loc = -(loc+1);
    129:           if (loc%2) { /* part of subdomain */
    130:             locals[i] = loc/2;
    131:           } else {
    132:             PetscFindInt(NDorder[i],2*(subd-1),seps+2*subd,&loc);
    133:             loc = loc < 0 ? -(loc+1)/2 : loc/2;
    134:             locals[i] = level[loc];
    135:           }
    136:         } else locals[i] = loc/2;
    137:       }
    138:       PetscFree3(sizes,seps,level);
    139:     } else {
    140:       if (pmetis->repartition) {
    141:         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));
    142:       } else if (isImprove) {
    143:         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));
    144:       } else {
    145:         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));
    146:       }
    147:     }
    148:     MPI_Comm_free(&comm);

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

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

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

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

    199: /*
    200:    Uses the ParMETIS parallel matrix partitioner to compute a nested dissection ordering of the matrix in parallel
    201: */
    202: static PetscErrorCode MatPartitioningApplyND_Parmetis(MatPartitioning part, IS *partitioning)
    203: {

    207:   MatPartitioningApply_Parmetis_Private(part, PETSC_TRUE, PETSC_FALSE, partitioning);
    208:   return(0);
    209: }

    211: /*
    212:    Uses the ParMETIS parallel matrix partitioner to partition the matrix in parallel
    213: */
    214: static PetscErrorCode MatPartitioningApply_Parmetis(MatPartitioning part, IS *partitioning)
    215: {

    219:   MatPartitioningApply_Parmetis_Private(part, PETSC_FALSE, PETSC_FALSE, partitioning);
    220:   return(0);
    221: }

    223: /*
    224:    Uses the ParMETIS to improve the quality  of a partition
    225: */
    226: static PetscErrorCode MatPartitioningImprove_Parmetis(MatPartitioning part, IS *partitioning)
    227: {

    231:   MatPartitioningApply_Parmetis_Private(part, PETSC_FALSE, PETSC_TRUE, partitioning);
    232:   return(0);
    233: }

    235: PetscErrorCode MatPartitioningView_Parmetis(MatPartitioning part,PetscViewer viewer)
    236: {
    237:   MatPartitioning_Parmetis *pmetis = (MatPartitioning_Parmetis*)part->data;
    238:   PetscErrorCode           ierr;
    239:   PetscMPIInt              rank;
    240:   PetscBool                iascii;

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

    260: /*@
    261:      MatPartitioningParmetisSetCoarseSequential - Use the sequential code to
    262:          do the partitioning of the coarse grid.

    264:   Logically Collective on MatPartitioning

    266:   Input Parameter:
    267: .  part - the partitioning context

    269:    Level: advanced

    271: @*/
    272: PetscErrorCode  MatPartitioningParmetisSetCoarseSequential(MatPartitioning part)
    273: {
    274:   MatPartitioning_Parmetis *pmetis = (MatPartitioning_Parmetis*)part->data;

    277:   pmetis->parallel = 1;
    278:   return(0);
    279: }

    281: /*@
    282:      MatPartitioningParmetisSetRepartition - Repartition
    283:      current mesh to rebalance computation.

    285:   Logically Collective on MatPartitioning

    287:   Input Parameter:
    288: .  part - the partitioning context

    290:    Level: advanced

    292: @*/
    293: PetscErrorCode  MatPartitioningParmetisSetRepartition(MatPartitioning part)
    294: {
    295:   MatPartitioning_Parmetis *pmetis = (MatPartitioning_Parmetis*)part->data;

    298:   pmetis->repartition = PETSC_TRUE;
    299:   return(0);
    300: }

    302: /*@
    303:   MatPartitioningParmetisGetEdgeCut - Returns the number of edge cuts in the vertex partition.

    305:   Input Parameter:
    306: . part - the partitioning context

    308:   Output Parameter:
    309: . cut - the edge cut

    311:    Level: advanced

    313: @*/
    314: PetscErrorCode  MatPartitioningParmetisGetEdgeCut(MatPartitioning part, PetscInt *cut)
    315: {
    316:   MatPartitioning_Parmetis *pmetis = (MatPartitioning_Parmetis*) part->data;

    319:   *cut = pmetis->cuts;
    320:   return(0);
    321: }

    323: PetscErrorCode MatPartitioningSetFromOptions_Parmetis(PetscOptionItems *PetscOptionsObject,MatPartitioning part)
    324: {
    326:   PetscBool      flag = PETSC_FALSE;

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

    342: PetscErrorCode MatPartitioningDestroy_Parmetis(MatPartitioning part)
    343: {
    344:   MatPartitioning_Parmetis *pmetis = (MatPartitioning_Parmetis*)part->data;
    345:   PetscErrorCode           ierr;

    348:   PetscFree(pmetis);
    349:   return(0);
    350: }

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

    355:    Collective

    357:    Input Parameter:
    358: .  part - the partitioning context

    360:    Options Database Keys:
    361: .  -mat_partitioning_parmetis_coarse_sequential - use sequential PARMETIS coarse partitioner

    363:    Level: beginner

    365:    Notes:
    366:     See https://www-users.cs.umn.edu/~karypis/metis/

    368: .seealso: MatPartitioningSetType(), MatPartitioningType

    370: M*/

    372: PETSC_EXTERN PetscErrorCode MatPartitioningCreate_Parmetis(MatPartitioning part)
    373: {
    374:   PetscErrorCode           ierr;
    375:   MatPartitioning_Parmetis *pmetis;

    378:   PetscNewLog(part,&pmetis);
    379:   part->data = (void*)pmetis;

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

    388:   part->ops->apply          = MatPartitioningApply_Parmetis;
    389:   part->ops->applynd        = MatPartitioningApplyND_Parmetis;
    390:   part->ops->improve        = MatPartitioningImprove_Parmetis;
    391:   part->ops->view           = MatPartitioningView_Parmetis;
    392:   part->ops->destroy        = MatPartitioningDestroy_Parmetis;
    393:   part->ops->setfromoptions = MatPartitioningSetFromOptions_Parmetis;
    394:   return(0);
    395: }

    397: /*@
    398:  MatMeshToVertexGraph -   This routine does not exist because ParMETIS does not provide the functionality.  Uses the ParMETIS package to
    399:                        convert a Mat that represents a mesh to a Mat the represents the graph of the coupling
    400:                        between vertices of the cells and is suitable for partitioning with the MatPartitioning object. Use this to partition
    401:                        vertices of a mesh. More likely you should use MatMeshToCellGraph()

    403:    Collective on Mat

    405:    Input Parameters:
    406: +     mesh - the graph that represents the mesh
    407: -     ncommonnodes - mesh elements that share this number of common nodes are considered neighbors, use 2 for triangles and
    408:                      quadrilaterials, 3 for tetrahedrals and 4 for hexahedrals

    410:    Output Parameter:
    411: .     dual - the dual graph

    413:    Notes:
    414:      Currently requires ParMetis to be installed and uses ParMETIS_V3_Mesh2Dual()

    416:      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
    417:      number of cells, the number of columns is the number of vertices.

    419:    Level: advanced

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

    423: @*/
    424: PetscErrorCode MatMeshToVertexGraph(Mat mesh,PetscInt ncommonnodes,Mat *dual)
    425: {
    427:   SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"ParMETIS does not provide this functionality");
    428: }

    430: /*@
    431:      MatMeshToCellGraph -   Uses the ParMETIS package to convert a Mat that represents a mesh to a Mat the represents the graph of the coupling
    432:                        between cells (the "dual" graph) and is suitable for partitioning with the MatPartitioning object. Use this to partition
    433:                        cells of a mesh.

    435:    Collective on Mat

    437:    Input Parameters:
    438: +     mesh - the graph that represents the mesh
    439: -     ncommonnodes - mesh elements that share this number of common nodes are considered neighbors, use 2 for triangles and
    440:                      quadrilaterials, 3 for tetrahedrals and 4 for hexahedrals

    442:    Output Parameter:
    443: .     dual - the dual graph

    445:    Notes:
    446:      Currently requires ParMetis to be installed and uses ParMETIS_V3_Mesh2Dual()

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

    454:    Level: advanced

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

    458: @*/
    459: PetscErrorCode MatMeshToCellGraph(Mat mesh,PetscInt ncommonnodes,Mat *dual)
    460: {
    462:   PetscInt       *newxadj,*newadjncy;
    463:   PetscInt       numflag=0;
    464:   Mat_MPIAdj     *adj   = (Mat_MPIAdj*)mesh->data,*newadj;
    465:   PetscBool      flg;
    466:   MPI_Comm       comm;

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

    472:   PetscObjectGetComm((PetscObject)mesh,&comm);
    473:   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));
    474:   MatCreateMPIAdj(PetscObjectComm((PetscObject)mesh),mesh->rmap->n,mesh->rmap->N,newxadj,newadjncy,NULL,dual);
    475:   newadj = (Mat_MPIAdj*)(*dual)->data;

    477:   newadj->freeaijwithfree = PETSC_TRUE; /* signal the matrix should be freed with system free since space was allocated by ParMETIS */
    478:   return(0);
    479: }