Actual source code: pmetis.c

petsc-3.4.4 2014-03-13
  2: #include <../src/mat/impls/adj/mpi/mpiadj.h>    /*I "petscmat.h" I*/

  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: } MatPartitioning_Parmetis;

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

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

 28: /*
 29:    Uses the ParMETIS parallel matrix partitioner to partition the matrix in parallel
 30: */
 33: static PetscErrorCode MatPartitioningApply_Parmetis(MatPartitioning part,IS *partitioning)
 34: {
 35:   MatPartitioning_Parmetis *pmetis = (MatPartitioning_Parmetis*)part->data;
 36:   PetscErrorCode           ierr;
 37:   PetscInt                 *locals = NULL;
 38:   Mat                      mat     = part->adj,amat,pmat;
 39:   PetscBool                flg;
 40:   PetscInt                 bs = 1;

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

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

 66:     PetscObjectGetComm((PetscObject)pmat,&pcomm);
 67: #if defined(PETSC_USE_DEBUG)
 68:     /* check that matrix has no diagonal entries */
 69:     {
 70:       PetscInt rstart;
 71:       MatGetOwnershipRange(pmat,&rstart,NULL);
 72:       for (i=0; i<pmat->rmap->n; i++) {
 73:         for (j=xadj[i]; j<xadj[i+1]; j++) {
 74:           if (adjncy[j] == i+rstart) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Row %d has diagonal entry; Parmetis forbids diagonal entry",i+rstart);
 75:         }
 76:       }
 77:     }
 78: #endif

 80:     PetscMalloc(amat->rmap->n*sizeof(PetscInt),&locals);

 82:     if (PetscLogPrintInfo) {itmp = pmetis->printout; pmetis->printout = 127;}
 83:     PetscMalloc(ncon*nparts*sizeof(real_t),&tpwgts);
 84:     for (i=0; i<ncon; i++) {
 85:       for (j=0; j<nparts; j++) {
 86:         if (part->part_weights) {
 87:           tpwgts[i*nparts+j] = part->part_weights[i*nparts+j];
 88:         } else {
 89:           tpwgts[i*nparts+j] = 1./nparts;
 90:         }
 91:       }
 92:     }
 93:     PetscMalloc(ncon*sizeof(real_t),&ubvec);
 94:     for (i=0; i<ncon; i++) {
 95:       ubvec[i] = 1.05;
 96:     }
 97:     /* This sets the defaults */
 98:     options[0] = 0;
 99:     for (i=1; i<24; i++) {
100:       options[i] = -1;
101:     }
102:     /* Duplicate the communicator to be sure that ParMETIS attribute caching does not interfere with PETSc. */
103:     MPI_Comm_dup(pcomm,&comm);
104:     PetscStackCallParmetis(ParMETIS_V3_PartKway,(vtxdist,xadj,adjncy,part->vertex_weights,adj->values,&wgtflag,&numflag,&ncon,&nparts,tpwgts,ubvec,options,&pmetis->cuts,locals,&comm));
105:     MPI_Comm_free(&comm);

107:     PetscFree(tpwgts);
108:     PetscFree(ubvec);
109:     if (PetscLogPrintInfo) pmetis->printout = itmp;
110:   }

112:   if (bs > 1) {
113:     PetscInt i,j,*newlocals;
114:     PetscMalloc(bs*amat->rmap->n*sizeof(PetscInt),&newlocals);
115:     for (i=0; i<amat->rmap->n; i++) {
116:       for (j=0; j<bs; j++) {
117:         newlocals[bs*i + j] = locals[i];
118:       }
119:     }
120:     PetscFree(locals);
121:     ISCreateGeneral(PetscObjectComm((PetscObject)part),bs*amat->rmap->n,newlocals,PETSC_OWN_POINTER,partitioning);
122:   } else {
123:     ISCreateGeneral(PetscObjectComm((PetscObject)part),amat->rmap->n,locals,PETSC_OWN_POINTER,partitioning);
124:   }

126:   MatDestroy(&pmat);
127:   MatDestroy(&amat);
128:   return(0);
129: }

133: PetscErrorCode MatPartitioningView_Parmetis(MatPartitioning part,PetscViewer viewer)
134: {
135:   MatPartitioning_Parmetis *pmetis = (MatPartitioning_Parmetis*)part->data;
136:   PetscErrorCode           ierr;
137:   int                      rank;
138:   PetscBool                iascii;

141:   MPI_Comm_rank(PetscObjectComm((PetscObject)part),&rank);
142:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
143:   if (iascii) {
144:     if (pmetis->parallel == 2) {
145:       PetscViewerASCIIPrintf(viewer,"  Using parallel coarse grid partitioner\n");
146:     } else {
147:       PetscViewerASCIIPrintf(viewer,"  Using sequential coarse grid partitioner\n");
148:     }
149:     PetscViewerASCIIPrintf(viewer,"  Using %d fold factor\n",pmetis->foldfactor);
150:     PetscViewerASCIISynchronizedAllow(viewer,PETSC_TRUE);
151:     PetscViewerASCIISynchronizedPrintf(viewer,"  [%d]Number of cuts found %d\n",rank,pmetis->cuts);
152:     PetscViewerFlush(viewer);
153:     PetscViewerASCIISynchronizedAllow(viewer,PETSC_FALSE);
154:   }
155:   return(0);
156: }

160: /*@
161:      MatPartitioningParmetisSetCoarseSequential - Use the sequential code to
162:          do the partitioning of the coarse grid.

164:   Logically Collective on MatPartitioning

166:   Input Parameter:
167: .  part - the partitioning context

169:    Level: advanced

171: @*/
172: PetscErrorCode  MatPartitioningParmetisSetCoarseSequential(MatPartitioning part)
173: {
174:   MatPartitioning_Parmetis *pmetis = (MatPartitioning_Parmetis*)part->data;

177:   pmetis->parallel = 1;
178:   return(0);
179: }

183: /*@
184:   MatPartitioningParmetisGetEdgeCut - Returns the number of edge cuts in the vertex partition.

186:   Input Parameter:
187: . part - the partitioning context

189:   Output Parameter:
190: . cut - the edge cut

192:    Level: advanced

194: @*/
195: PetscErrorCode  MatPartitioningParmetisGetEdgeCut(MatPartitioning part, PetscInt *cut)
196: {
197:   MatPartitioning_Parmetis *pmetis = (MatPartitioning_Parmetis*) part->data;

200:   *cut = pmetis->cuts;
201:   return(0);
202: }

206: PetscErrorCode MatPartitioningSetFromOptions_Parmetis(MatPartitioning part)
207: {
209:   PetscBool      flag = PETSC_FALSE;

212:   PetscOptionsHead("Set ParMeTiS partitioning options");
213:   PetscOptionsBool("-mat_partitioning_parmetis_coarse_sequential","Use sequential coarse partitioner","MatPartitioningParmetisSetCoarseSequential",flag,&flag,NULL);
214:   if (flag) {
215:     MatPartitioningParmetisSetCoarseSequential(part);
216:   }
217:   PetscOptionsTail();
218:   return(0);
219: }


224: PetscErrorCode MatPartitioningDestroy_Parmetis(MatPartitioning part)
225: {
226:   MatPartitioning_Parmetis *pmetis = (MatPartitioning_Parmetis*)part->data;
227:   PetscErrorCode           ierr;

230:   PetscFree(pmetis);
231:   return(0);
232: }


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

238:    Collective on MPI_Comm

240:    Input Parameter:
241: .  part - the partitioning context

243:    Options Database Keys:
244: +  -mat_partitioning_parmetis_coarse_sequential - use sequential PARMETIS coarse partitioner

246:    Level: beginner

248:    Notes: See http://www-users.cs.umn.edu/~karypis/metis/

250: .keywords: Partitioning, create, context

252: .seealso: MatPartitioningSetType(), MatPartitioningType

254: M*/

258: PETSC_EXTERN PetscErrorCode MatPartitioningCreate_Parmetis(MatPartitioning part)
259: {
260:   PetscErrorCode           ierr;
261:   MatPartitioning_Parmetis *pmetis;

264:   PetscNewLog(part,MatPartitioning_Parmetis,&pmetis);
265:   part->data = (void*)pmetis;

267:   pmetis->cuts       = 0;   /* output variable */
268:   pmetis->foldfactor = 150; /*folding factor */
269:   pmetis->parallel   = 2;   /* use parallel partitioner for coarse grid */
270:   pmetis->indexing   = 0;   /* index numbering starts from 0 */
271:   pmetis->printout   = 0;   /* print no output while running */

273:   part->ops->apply          = MatPartitioningApply_Parmetis;
274:   part->ops->view           = MatPartitioningView_Parmetis;
275:   part->ops->destroy        = MatPartitioningDestroy_Parmetis;
276:   part->ops->setfromoptions = MatPartitioningSetFromOptions_Parmetis;
277:   return(0);
278: }

282: /*@
283:  MatMeshToVertexGraph -   This routine does not exist because ParMETIS does not provide the functionality.  Uses the ParMETIS package to
284:                        convert a Mat that represents a mesh to a Mat the represents the graph of the coupling
285:                        between vertices of the cells and is suitable for partitioning with the MatPartitioning object. Use this to partition
286:                        vertices of a mesh. More likely you should use MatMeshToCellGraph()

288:    Collective on Mat

290:    Input Parameter:
291: +     mesh - the graph that represents the mesh
292: -     ncommonnodes - mesh elements that share this number of common nodes are considered neighbors, use 2 for triangules and
293:                      quadralaterials, 3 for tetrahedrals and 4 for hexahedrals

295:    Output Parameter:
296: .     dual - the dual graph

298:    Notes:
299:      Currently requires ParMetis to be installed and uses ParMETIS_V3_Mesh2Dual()

301:      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
302:      number of cells, the number of columns is the number of vertices.

304:    Level: advanced

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

308: @*/
309: PetscErrorCode MatMeshToVertexGraph(Mat mesh,PetscInt ncommonnodes,Mat *dual)
310: {
312:   SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"ParMETIS does not provide this functionality");
313:   return(0);
314: }

318: /*@
319:      MatMeshToCellGraph -   Uses the ParMETIS package to convert a Mat that represents a mesh to a Mat the represents the graph of the coupling
320:                        between cells (the "dual" graph) and is suitable for partitioning with the MatPartitioning object. Use this to partition
321:                        cells of a mesh.

323:    Collective on Mat

325:    Input Parameter:
326: +     mesh - the graph that represents the mesh
327: -     ncommonnodes - mesh elements that share this number of common nodes are considered neighbors, use 2 for triangules and
328:                      quadralaterials, 3 for tetrahedrals and 4 for hexahedrals

330:    Output Parameter:
331: .     dual - the dual graph

333:    Notes:
334:      Currently requires ParMetis to be installed and uses ParMETIS_V3_Mesh2Dual()

336:      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
337:      number of cells, the number of columns is the number of vertices.


340:    Level: advanced

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


345: @*/
346: PetscErrorCode MatMeshToCellGraph(Mat mesh,PetscInt ncommonnodes,Mat *dual)
347: {
349:   PetscInt       *newxadj,*newadjncy;
350:   PetscInt       numflag=0;
351:   Mat_MPIAdj     *adj   = (Mat_MPIAdj*)mesh->data,*newadj;
352:   PetscBool      flg;
353:   int            status;
354:   MPI_Comm       comm;

357:   PetscObjectTypeCompare((PetscObject)mesh,MATMPIADJ,&flg);
358:   if (!flg) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Must use MPIAdj matrix type");
359: 
360:   PetscObjectGetComm((PetscObject)mesh,&comm);
361:   PetscStackCallParmetis(ParMETIS_V3_Mesh2Dual,(mesh->rmap->range,adj->i,adj->j,&numflag,&ncommonnodes,&newxadj,&newadjncy,&comm));
362:   MatCreateMPIAdj(PetscObjectComm((PetscObject)mesh),mesh->rmap->n,mesh->rmap->N,newxadj,newadjncy,NULL,dual);
363:   newadj = (Mat_MPIAdj*)(*dual)->data;

365:   newadj->freeaijwithfree = PETSC_TRUE; /* signal the matrix should be freed with system free since space was allocated by ParMETIS */
366:   return(0);
367: }