Actual source code: pmetis.c

petsc-3.10.4 2019-02-26
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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);status = func args;PetscStackPop; CHKERRQPARMETIS(status,#func);} while (0)

 29: static PetscErrorCode MatPartitioningApply_Parmetis_Private(MatPartitioning part, PetscBool useND, 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;

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

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

 63:     PetscObjectGetComm((PetscObject)pmat,&pcomm);
 64: #if defined(PETSC_USE_DEBUG)
 65:     /* check that matrix has no diagonal entries */
 66:     {
 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:     }
 75: #endif

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

 79:     if (adj->values && !part->vertex_weights)
 80:       wgtflag = 1;
 81:     if (part->vertex_weights && !adj->values)
 82:       wgtflag = 2;
 83:     if (part->vertex_weights && adj->values)
 84:       wgtflag = 3;

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

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

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

146:     PetscFree(tpwgts);
147:     PetscFree(ubvec);
148:     if (PetscLogPrintInfo) pmetis->printout = itmp;

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

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

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

195: /*
196:    Uses the ParMETIS parallel matrix partitioner to compute a nested dissection ordering of the matrix in parallel
197: */
198: static PetscErrorCode MatPartitioningApplyND_Parmetis(MatPartitioning part, IS *partitioning)
199: {

203:   MatPartitioningApply_Parmetis_Private(part, PETSC_TRUE, partitioning);
204:   return(0);
205: }

207: /*
208:    Uses the ParMETIS parallel matrix partitioner to partition the matrix in parallel
209: */
210: static PetscErrorCode MatPartitioningApply_Parmetis(MatPartitioning part, IS *partitioning)
211: {

215:   MatPartitioningApply_Parmetis_Private(part, PETSC_FALSE, partitioning);
216:   return(0);
217: }

219: PetscErrorCode MatPartitioningView_Parmetis(MatPartitioning part,PetscViewer viewer)
220: {
221:   MatPartitioning_Parmetis *pmetis = (MatPartitioning_Parmetis*)part->data;
222:   PetscErrorCode           ierr;
223:   int                      rank;
224:   PetscBool                iascii;

227:   MPI_Comm_rank(PetscObjectComm((PetscObject)part),&rank);
228:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
229:   if (iascii) {
230:     if (pmetis->parallel == 2) {
231:       PetscViewerASCIIPrintf(viewer,"  Using parallel coarse grid partitioner\n");
232:     } else {
233:       PetscViewerASCIIPrintf(viewer,"  Using sequential coarse grid partitioner\n");
234:     }
235:     PetscViewerASCIIPrintf(viewer,"  Using %d fold factor\n",pmetis->foldfactor);
236:     PetscViewerASCIIPushSynchronized(viewer);
237:     PetscViewerASCIISynchronizedPrintf(viewer,"  [%d]Number of cuts found %d\n",rank,pmetis->cuts);
238:     PetscViewerFlush(viewer);
239:     PetscViewerASCIIPopSynchronized(viewer);
240:   }
241:   return(0);
242: }

244: /*@
245:      MatPartitioningParmetisSetCoarseSequential - Use the sequential code to
246:          do the partitioning of the coarse grid.

248:   Logically Collective on MatPartitioning

250:   Input Parameter:
251: .  part - the partitioning context

253:    Level: advanced

255: @*/
256: PetscErrorCode  MatPartitioningParmetisSetCoarseSequential(MatPartitioning part)
257: {
258:   MatPartitioning_Parmetis *pmetis = (MatPartitioning_Parmetis*)part->data;

261:   pmetis->parallel = 1;
262:   return(0);
263: }

265: /*@
266:      MatPartitioningParmetisSetRepartition - Repartition
267:      current mesh to rebalance computation.

269:   Logically Collective on MatPartitioning

271:   Input Parameter:
272: .  part - the partitioning context

274:    Level: advanced

276: @*/
277: PetscErrorCode  MatPartitioningParmetisSetRepartition(MatPartitioning part)
278: {
279:   MatPartitioning_Parmetis *pmetis = (MatPartitioning_Parmetis*)part->data;

282:   pmetis->repartition = PETSC_TRUE;
283:   return(0);
284: }

286: /*@
287:   MatPartitioningParmetisGetEdgeCut - Returns the number of edge cuts in the vertex partition.

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

292:   Output Parameter:
293: . cut - the edge cut

295:    Level: advanced

297: @*/
298: PetscErrorCode  MatPartitioningParmetisGetEdgeCut(MatPartitioning part, PetscInt *cut)
299: {
300:   MatPartitioning_Parmetis *pmetis = (MatPartitioning_Parmetis*) part->data;

303:   *cut = pmetis->cuts;
304:   return(0);
305: }

307: PetscErrorCode MatPartitioningSetFromOptions_Parmetis(PetscOptionItems *PetscOptionsObject,MatPartitioning part)
308: {
310:   PetscBool      flag = PETSC_FALSE;

313:   PetscOptionsHead(PetscOptionsObject,"Set ParMeTiS partitioning options");
314:   PetscOptionsBool("-mat_partitioning_parmetis_coarse_sequential","Use sequential coarse partitioner","MatPartitioningParmetisSetCoarseSequential",flag,&flag,NULL);
315:   if (flag) {
316:     MatPartitioningParmetisSetCoarseSequential(part);
317:   }
318:   PetscOptionsBool("-mat_partitioning_parmetis_repartition","","MatPartitioningParmetisSetRepartition",flag,&flag,NULL);
319:   if(flag){
320:      MatPartitioningParmetisSetRepartition(part);
321:   }
322:   PetscOptionsTail();
323:   return(0);
324: }


327: PetscErrorCode MatPartitioningDestroy_Parmetis(MatPartitioning part)
328: {
329:   MatPartitioning_Parmetis *pmetis = (MatPartitioning_Parmetis*)part->data;
330:   PetscErrorCode           ierr;

333:   PetscFree(pmetis);
334:   return(0);
335: }


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

341:    Collective on MPI_Comm

343:    Input Parameter:
344: .  part - the partitioning context

346:    Options Database Keys:
347: +  -mat_partitioning_parmetis_coarse_sequential - use sequential PARMETIS coarse partitioner

349:    Level: beginner

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

354: .keywords: Partitioning, create, context

356: .seealso: MatPartitioningSetType(), MatPartitioningType

358: M*/

360: PETSC_EXTERN PetscErrorCode MatPartitioningCreate_Parmetis(MatPartitioning part)
361: {
362:   PetscErrorCode           ierr;
363:   MatPartitioning_Parmetis *pmetis;

366:   PetscNewLog(part,&pmetis);
367:   part->data = (void*)pmetis;

369:   pmetis->cuts       = 0;   /* output variable */
370:   pmetis->foldfactor = 150; /*folding factor */
371:   pmetis->parallel   = 2;   /* use parallel partitioner for coarse grid */
372:   pmetis->indexing   = 0;   /* index numbering starts from 0 */
373:   pmetis->printout   = 0;   /* print no output while running */
374:   pmetis->repartition      = PETSC_FALSE;

376:   part->ops->apply          = MatPartitioningApply_Parmetis;
377:   part->ops->applynd        = MatPartitioningApplyND_Parmetis;
378:   part->ops->view           = MatPartitioningView_Parmetis;
379:   part->ops->destroy        = MatPartitioningDestroy_Parmetis;
380:   part->ops->setfromoptions = MatPartitioningSetFromOptions_Parmetis;
381:   return(0);
382: }

384: /*@
385:  MatMeshToVertexGraph -   This routine does not exist because ParMETIS does not provide the functionality.  Uses the ParMETIS package to
386:                        convert a Mat that represents a mesh to a Mat the represents the graph of the coupling
387:                        between vertices of the cells and is suitable for partitioning with the MatPartitioning object. Use this to partition
388:                        vertices of a mesh. More likely you should use MatMeshToCellGraph()

390:    Collective on Mat

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

397:    Output Parameter:
398: .     dual - the dual graph

400:    Notes:
401:      Currently requires ParMetis to be installed and uses ParMETIS_V3_Mesh2Dual()

403:      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
404:      number of cells, the number of columns is the number of vertices.

406:    Level: advanced

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

410: @*/
411: PetscErrorCode MatMeshToVertexGraph(Mat mesh,PetscInt ncommonnodes,Mat *dual)
412: {
414:   SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"ParMETIS does not provide this functionality");
415:   return(0);
416: }

418: /*@
419:      MatMeshToCellGraph -   Uses the ParMETIS package to convert a Mat that represents a mesh to a Mat the represents the graph of the coupling
420:                        between cells (the "dual" graph) and is suitable for partitioning with the MatPartitioning object. Use this to partition
421:                        cells of a mesh.

423:    Collective on Mat

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

430:    Output Parameter:
431: .     dual - the dual graph

433:    Notes:
434:      Currently requires ParMetis to be installed and uses ParMETIS_V3_Mesh2Dual()

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


443:    Level: advanced

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


448: @*/
449: PetscErrorCode MatMeshToCellGraph(Mat mesh,PetscInt ncommonnodes,Mat *dual)
450: {
452:   PetscInt       *newxadj,*newadjncy;
453:   PetscInt       numflag=0;
454:   Mat_MPIAdj     *adj   = (Mat_MPIAdj*)mesh->data,*newadj;
455:   PetscBool      flg;
456:   int            status;
457:   MPI_Comm       comm;

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

463:   PetscObjectGetComm((PetscObject)mesh,&comm);
464:   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));
465:   MatCreateMPIAdj(PetscObjectComm((PetscObject)mesh),mesh->rmap->n,mesh->rmap->N,newxadj,newadjncy,NULL,dual);
466:   newadj = (Mat_MPIAdj*)(*dual)->data;

468:   newadj->freeaijwithfree = PETSC_TRUE; /* signal the matrix should be freed with system free since space was allocated by ParMETIS */
469:   return(0);
470: }