Actual source code: party.c
petsc-3.9.4 2018-09-11
2: #include <../src/mat/impls/adj/mpi/mpiadj.h>
4: #if defined(PETSC_HAVE_UNISTD_H)
5: #include <unistd.h>
6: #endif
8: /*
9: Currently using Party-1.99
10: */
11: EXTERN_C_BEGIN
12: #include <party_lib.h>
13: EXTERN_C_END
15: typedef struct {
16: PetscBool redm;
17: PetscBool redo;
18: PetscBool recursive;
19: PetscBool verbose;
20: char global[15]; /* global method */
21: char local[15]; /* local method */
22: PetscInt nbvtxcoarsed; /* number of vertices for the coarse graph */
23: } MatPartitioning_Party;
25: #define SIZE_LOG 10000 /* size of buffer for mesg_log */
27: static PetscErrorCode MatPartitioningApply_Party(MatPartitioning part,IS *partitioning)
28: {
29: PetscErrorCode ierr;
30: PetscInt i,*parttab,*locals,nb_locals,M,N;
31: PetscMPIInt size,rank;
32: Mat mat = part->adj,matAdj,matSeq,*A;
33: Mat_MPIAdj *adj;
34: MatPartitioning_Party *party = (MatPartitioning_Party*)part->data;
35: PetscBool flg;
36: IS isrow, iscol;
37: int n,*edge_p,*edge,*vertex_w,p,*part_party,cutsize,redl,rec;
38: const char *redm,*redo;
39: char *mesg_log;
40: #if defined(PETSC_HAVE_UNISTD_H)
41: int fd_stdout,fd_pipe[2],count,err;
42: #endif
45: MPI_Comm_size(PetscObjectComm((PetscObject)mat),&size);
46: MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);
47: PetscObjectTypeCompare((PetscObject)mat,MATMPIADJ,&flg);
48: if (size>1) {
49: if (flg) {
50: MatMPIAdjToSeq(mat,&matSeq);
51: } else {
52: PetscInfo(part,"Converting distributed matrix to sequential: this could be a performance loss\n");
53: MatGetSize(mat,&M,&N);
54: ISCreateStride(PETSC_COMM_SELF,M,0,1,&isrow);
55: ISCreateStride(PETSC_COMM_SELF,N,0,1,&iscol);
56: MatCreateSubMatrices(mat,1,&isrow,&iscol,MAT_INITIAL_MATRIX,&A);
57: ISDestroy(&isrow);
58: ISDestroy(&iscol);
59: matSeq = *A;
60: PetscFree(A);
61: }
62: } else {
63: PetscObjectReference((PetscObject)mat);
64: matSeq = mat;
65: }
67: if (!flg) { /* convert regular matrix to MPIADJ */
68: MatConvert(matSeq,MATMPIADJ,MAT_INITIAL_MATRIX,&matAdj);
69: } else {
70: PetscObjectReference((PetscObject)matSeq);
71: matAdj = matSeq;
72: }
74: adj = (Mat_MPIAdj*)matAdj->data; /* finaly adj contains adjacency graph */
76: /* arguments for Party library */
77: n = mat->rmap->N; /* number of vertices in full graph */
78: edge_p = adj->i; /* start of edge list for each vertex */
79: edge = adj->j; /* edge list data */
80: vertex_w = part->vertex_weights; /* weights for all vertices */
81: p = part->n; /* number of parts to create */
82: redl = party->nbvtxcoarsed; /* how many vertices to coarsen down to? */
83: rec = party->recursive ? 1 : 0; /* recursive bisection */
84: redm = party->redm ? "lam" : ""; /* matching method */
85: redo = party->redo ? "w3" : ""; /* matching optimization method */
87: PetscMalloc1(mat->rmap->N,&part_party);
89: /* redirect output to buffer */
90: #if defined(PETSC_HAVE_UNISTD_H)
91: fd_stdout = dup(1);
92: if (pipe(fd_pipe)) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SYS,"Could not open pipe");
93: close(1);
94: dup2(fd_pipe[1],1);
95: PetscMalloc1(SIZE_LOG,&mesg_log);
96: #endif
98: /* library call */
99: party_lib_times_start();
100: party_lib(n,vertex_w,NULL,NULL,NULL,edge_p,edge,NULL,p,part_party,&cutsize,redl,(char*)redm,(char*)redo,party->global,party->local,rec,1);
102: party_lib_times_output(1);
103: part_info(n,vertex_w,edge_p,edge,NULL,p,part_party,1);
105: #if defined(PETSC_HAVE_UNISTD_H)
106: err = fflush(stdout);
107: if (err) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SYS,"fflush() failed on stdout");
108: count = read(fd_pipe[0],mesg_log,(SIZE_LOG-1)*sizeof(char));
109: if (count<0) count = 0;
110: mesg_log[count] = 0;
111: close(1);
112: dup2(fd_stdout,1);
113: close(fd_stdout);
114: close(fd_pipe[0]);
115: close(fd_pipe[1]);
116: if (party->verbose) {
117: PetscPrintf(PetscObjectComm((PetscObject)mat),mesg_log);
118: }
119: PetscFree(mesg_log);
120: #endif
121: if (ierr) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_LIB,"Party failed");
123: PetscMalloc1(mat->rmap->N,&parttab);
124: for (i=0; i<mat->rmap->N; i++) parttab[i] = part_party[i];
126: /* creation of the index set */
127: nb_locals = mat->rmap->n;
128: locals = parttab + mat->rmap->rstart;
130: ISCreateGeneral(PetscObjectComm((PetscObject)part),nb_locals,locals,PETSC_COPY_VALUES,partitioning);
132: /* clean up */
133: PetscFree(parttab);
134: PetscFree(part_party);
135: MatDestroy(&matSeq);
136: MatDestroy(&matAdj);
137: return(0);
138: }
140: PetscErrorCode MatPartitioningView_Party(MatPartitioning part,PetscViewer viewer)
141: {
142: MatPartitioning_Party *party = (MatPartitioning_Party*)part->data;
143: PetscErrorCode ierr;
144: PetscBool isascii;
147: PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&isascii);
148: if (isascii) {
149: PetscViewerASCIIPrintf(viewer," Global method: %s\n",party->global);
150: PetscViewerASCIIPrintf(viewer," Local method: %s\n",party->local);
151: PetscViewerASCIIPrintf(viewer," Number of vertices for the coarse graph: %d\n",party->nbvtxcoarsed);
152: if (party->redm) {
153: PetscViewerASCIIPrintf(viewer," Using matching method for graph reduction\n");
154: }
155: if (party->redo) {
156: PetscViewerASCIIPrintf(viewer," Using matching optimization\n");
157: }
158: if (party->recursive) {
159: PetscViewerASCIIPrintf(viewer," Using recursive bipartitioning\n");
160: }
161: }
162: return(0);
163: }
165: /*@C
166: MatPartitioningPartySetGlobal - Set global method for Party partitioner.
168: Collective on MatPartitioning
170: Input Parameters:
171: + part - the partitioning context
172: - method - a string representing the method
174: Options Database:
175: . -mat_partitioning_party_global <method> - the global method
177: Level: advanced
179: Notes:
180: The method may be one of MP_PARTY_OPT, MP_PARTY_LIN, MP_PARTY_SCA,
181: MP_PARTY_RAN, MP_PARTY_GBF, MP_PARTY_GCF, MP_PARTY_BUB or MP_PARTY_DEF, or
182: alternatively a string describing the method. Two or more methods can be
183: combined like "gbf,gcf". Check the Party Library Users Manual for details.
185: .seealso: MatPartitioningPartySetLocal()
186: @*/
187: PetscErrorCode MatPartitioningPartySetGlobal(MatPartitioning part,const char *global)
188: {
193: PetscTryMethod(part,"MatPartitioningPartySetGlobal_C",(MatPartitioning,const char*),(part,global));
194: return(0);
195: }
197: PetscErrorCode MatPartitioningPartySetGlobal_Party(MatPartitioning part,const char *global)
198: {
199: MatPartitioning_Party *party = (MatPartitioning_Party*)part->data;
200: PetscErrorCode ierr;
203: PetscStrncpy(party->global,global,15);
204: return(0);
205: }
207: /*@C
208: MatPartitioningPartySetLocal - Set local method for Party partitioner.
210: Collective on MatPartitioning
212: Input Parameters:
213: + part - the partitioning context
214: - method - a string representing the method
216: Options Database:
217: . -mat_partitioning_party_local <method> - the local method
219: Level: advanced
221: Notes:
222: The method may be one of MP_PARTY_HELPFUL_SETS, MP_PARTY_KERNIGHAN_LIN, or
223: MP_PARTY_NONE. Check the Party Library Users Manual for details.
225: .seealso: MatPartitioningPartySetGlobal()
226: @*/
227: PetscErrorCode MatPartitioningPartySetLocal(MatPartitioning part,const char *local)
228: {
233: PetscTryMethod(part,"MatPartitioningPartySetLocal_C",(MatPartitioning,const char*),(part,local));
234: return(0);
235: }
237: PetscErrorCode MatPartitioningPartySetLocal_Party(MatPartitioning part,const char *local)
239: {
240: MatPartitioning_Party *party = (MatPartitioning_Party*)part->data;
241: PetscErrorCode ierr;
244: PetscStrncpy(party->local,local,15);
245: return(0);
246: }
248: /*@
249: MatPartitioningPartySetCoarseLevel - Set the coarse level parameter for the
250: Party partitioner.
252: Collective on MatPartitioning
254: Input Parameters:
255: + part - the partitioning context
256: - level - the coarse level in range [0.0,1.0]
258: Options Database:
259: . -mat_partitioning_party_coarse <l> - Coarse level
261: Level: advanced
262: @*/
263: PetscErrorCode MatPartitioningPartySetCoarseLevel(MatPartitioning part,PetscReal level)
264: {
270: PetscTryMethod(part,"MatPartitioningPartySetCoarseLevel_C",(MatPartitioning,PetscReal),(part,level));
271: return(0);
272: }
274: PetscErrorCode MatPartitioningPartySetCoarseLevel_Party(MatPartitioning part,PetscReal level)
275: {
276: MatPartitioning_Party *party = (MatPartitioning_Party*)part->data;
279: if (level<0.0 || level>1.0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Party: level of coarsening out of range [0.0-1.0]");
280: party->nbvtxcoarsed = (PetscInt)(part->adj->cmap->N * level);
281: if (party->nbvtxcoarsed < 20) party->nbvtxcoarsed = 20;
282: return(0);
283: }
285: /*@
286: MatPartitioningPartySetMatchOptimization - Activate matching optimization for
287: graph reduction.
289: Collective on MatPartitioning
291: Input Parameters:
292: + part - the partitioning context
293: - opt - boolean flag
295: Options Database:
296: . -mat_partitioning_party_match_optimization - Matching optimization on/off
298: Level: advanced
299: @*/
300: PetscErrorCode MatPartitioningPartySetMatchOptimization(MatPartitioning part,PetscBool opt)
301: {
307: PetscTryMethod(part,"MatPartitioningPartySetMatchOptimization_C",(MatPartitioning,PetscBool),(part,opt));
308: return(0);
309: }
311: PetscErrorCode MatPartitioningPartySetMatchOptimization_Party(MatPartitioning part,PetscBool opt)
312: {
313: MatPartitioning_Party *party = (MatPartitioning_Party*)part->data;
316: party->redo = opt;
317: return(0);
318: }
320: /*@
321: MatPartitioningPartySetBipart - Activate or deactivate recursive bisection.
323: Collective on MatPartitioning
325: Input Parameters:
326: + part - the partitioning context
327: - bp - boolean flag
329: Options Database:
330: - -mat_partitioning_party_bipart - Bipartitioning option on/off
332: Level: advanced
333: @*/
334: PetscErrorCode MatPartitioningPartySetBipart(MatPartitioning part,PetscBool bp)
335: {
341: PetscTryMethod(part,"MatPartitioningPartySetBipart_C",(MatPartitioning,PetscBool),(part,bp));
342: return(0);
343: }
345: PetscErrorCode MatPartitioningPartySetBipart_Party(MatPartitioning part,PetscBool bp)
346: {
347: MatPartitioning_Party *party = (MatPartitioning_Party*)part->data;
350: party->recursive = bp;
351: return(0);
352: }
354: PetscErrorCode MatPartitioningSetFromOptions_Party(PetscOptionItems *PetscOptionsObject,MatPartitioning part)
355: {
356: PetscErrorCode ierr;
357: PetscBool flag;
358: char value[256];
359: PetscReal r;
360: MatPartitioning_Party *party = (MatPartitioning_Party*)part->data;
363: PetscOptionsHead(PetscOptionsObject,"Set Party partitioning options");
364: PetscOptionsString("-mat_partitioning_party_global","Global method","MatPartitioningPartySetGlobal",party->global,value,256,&flag);
365: if (flag) { MatPartitioningPartySetGlobal(part,value); }
366: PetscOptionsString("-mat_partitioning_party_local","Local method","MatPartitioningPartySetLocal",party->local,value,256,&flag);
367: if (flag) { MatPartitioningPartySetLocal(part,value); }
368: PetscOptionsReal("-mat_partitioning_party_coarse","Coarse level","MatPartitioningPartySetCoarseLevel",0.0,&r,&flag);
369: if (flag) { MatPartitioningPartySetCoarseLevel(part,r); }
370: PetscOptionsBool("-mat_partitioning_party_match_optimization","Matching optimization on/off","MatPartitioningPartySetMatchOptimization",party->redo,&party->redo,NULL);
371: PetscOptionsBool("-mat_partitioning_party_bipart","Bipartitioning on/off","MatPartitioningPartySetBipart",party->recursive,&party->recursive,NULL);
372: PetscOptionsBool("-mat_partitioning_party_verbose","Show library output","",party->verbose,&party->verbose,NULL);
373: PetscOptionsTail();
374: return(0);
375: }
377: PetscErrorCode MatPartitioningDestroy_Party(MatPartitioning part)
378: {
379: MatPartitioning_Party *party = (MatPartitioning_Party*)part->data;
380: PetscErrorCode ierr;
383: PetscFree(party);
384: /* clear composed functions */
385: PetscObjectComposeFunction((PetscObject)part,"MatPartitioningPartySetGlobal_C",NULL);
386: PetscObjectComposeFunction((PetscObject)part,"MatPartitioningPartySetLocal_C",NULL);
387: PetscObjectComposeFunction((PetscObject)part,"MatPartitioningPartySetCoarseLevel_C",NULL);
388: PetscObjectComposeFunction((PetscObject)part,"MatPartitioningPartySetMatchOptimization_C",NULL);
389: PetscObjectComposeFunction((PetscObject)part,"MatPartitioningPartySetBipart_C",NULL);
390: return(0);
391: }
393: /*MC
394: MATPARTITIONINGPARTY - Creates a partitioning context via the external package Party.
396: Level: beginner
398: Notes: See http://wwwcs.upb.de/fachbereich/AG/monien/RESEARCH/PART/party.html
400: .keywords: Partitioning, create, context
402: .seealso: MatPartitioningSetType(), MatPartitioningType
404: M*/
406: PETSC_EXTERN PetscErrorCode MatPartitioningCreate_Party(MatPartitioning part)
407: {
408: PetscErrorCode ierr;
409: MatPartitioning_Party *party;
412: PetscNewLog(part,&party);
413: part->data = (void*)party;
415: PetscStrcpy(party->global,"gcf,gbf");
416: PetscStrcpy(party->local,"kl");
418: party->redm = PETSC_TRUE;
419: party->redo = PETSC_TRUE;
420: party->recursive = PETSC_TRUE;
421: party->verbose = PETSC_FALSE;
422: party->nbvtxcoarsed = 200;
424: part->ops->apply = MatPartitioningApply_Party;
425: part->ops->view = MatPartitioningView_Party;
426: part->ops->destroy = MatPartitioningDestroy_Party;
427: part->ops->setfromoptions = MatPartitioningSetFromOptions_Party;
429: PetscObjectComposeFunction((PetscObject)part,"MatPartitioningPartySetGlobal_C",MatPartitioningPartySetGlobal_Party);
430: PetscObjectComposeFunction((PetscObject)part,"MatPartitioningPartySetLocal_C",MatPartitioningPartySetLocal_Party);
431: PetscObjectComposeFunction((PetscObject)part,"MatPartitioningPartySetCoarseLevel_C",MatPartitioningPartySetCoarseLevel_Party);
432: PetscObjectComposeFunction((PetscObject)part,"MatPartitioningPartySetMatchOptimization_C",MatPartitioningPartySetMatchOptimization_Party);
433: PetscObjectComposeFunction((PetscObject)part,"MatPartitioningPartySetBipart_C",MatPartitioningPartySetBipart_Party);
434: return(0);
435: }