Actual source code: chaco.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: #if defined(PETSC_HAVE_CHACO_INT_ASSIGNMENT)
9: #include <chaco.h>
10: #else
11: /* Older versions of Chaco do not have an include file */
12: PETSC_EXTERN int interface(int nvtxs, int *start, int *adjacency, int *vwgts,
13: float *ewgts, float *x, float *y, float *z, char *outassignname,
14: char *outfilename, short *assignment, int architecture, int ndims_tot,
15: int mesh_dims[3], double *goal, int global_method, int local_method,
16: int rqi_flag, int vmax, int ndims, double eigtol, long seed);
17: #endif
19: extern int FREE_GRAPH;
21: /*
22: int nvtxs; number of vertices in full graph
23: int *start; start of edge list for each vertex
24: int *adjacency; edge list data
25: int *vwgts; weights for all vertices
26: float *ewgts; weights for all edges
27: float *x, *y, *z; coordinates for inertial method
28: char *outassignname; name of assignment output file
29: char *outfilename; output file name
30: short *assignment; set number of each vtx (length n)
31: int architecture; 0 => hypercube, d => d-dimensional mesh
32: int ndims_tot; total number of cube dimensions to divide
33: int mesh_dims[3]; dimensions of mesh of processors
34: double *goal; desired set sizes for each set
35: int global_method; global partitioning algorithm
36: int local_method; local partitioning algorithm
37: int rqi_flag; should I use RQI/Symmlq eigensolver?
38: int vmax; how many vertices to coarsen down to?
39: int ndims; number of eigenvectors (2^d sets)
40: double eigtol; tolerance on eigenvectors
41: long seed; for random graph mutations
42: */
44: typedef struct {
45: PetscBool verbose;
46: PetscInt eignum;
47: PetscReal eigtol;
48: MPChacoGlobalType global_method; /* global method */
49: MPChacoLocalType local_method; /* local method */
50: MPChacoEigenType eigen_method; /* eigensolver */
51: PetscInt nbvtxcoarsed; /* number of vertices for the coarse graph */
52: } MatPartitioning_Chaco;
54: #define SIZE_LOG 10000 /* size of buffer for mesg_log */
56: static PetscErrorCode MatPartitioningApply_Chaco(MatPartitioning part,IS *partitioning)
57: {
58: PetscErrorCode ierr;
59: PetscInt *parttab,*locals,i,nb_locals,M,N;
60: PetscMPIInt size,rank;
61: Mat mat = part->adj,matAdj,matSeq,*A;
62: Mat_MPIAdj *adj;
63: MatPartitioning_Chaco *chaco = (MatPartitioning_Chaco*)part->data;
64: PetscBool flg;
65: IS isrow, iscol;
66: int nvtxs,*start,*adjacency,*vwgts,architecture,ndims_tot;
67: int mesh_dims[3],global_method,local_method,rqi_flag,vmax,ndims;
68: #if defined(PETSC_HAVE_CHACO_INT_ASSIGNMENT)
69: int *assignment;
70: #else
71: short *assignment;
72: #endif
73: double eigtol;
74: long seed;
75: char *mesg_log;
76: #if defined(PETSC_HAVE_UNISTD_H)
77: int fd_stdout,fd_pipe[2],count,err;
78: #endif
81: FREE_GRAPH = 0; /* otherwise Chaco will attempt to free memory for adjacency graph */
82: MPI_Comm_size(PetscObjectComm((PetscObject)mat),&size);
83: MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);
84: PetscObjectTypeCompare((PetscObject)mat,MATMPIADJ,&flg);
85: if (size>1) {
86: if (flg) {
87: MatMPIAdjToSeq(mat,&matSeq);
88: } else {
89: PetscInfo(part,"Converting distributed matrix to sequential: this could be a performance loss\n");
90: MatGetSize(mat,&M,&N);
91: ISCreateStride(PETSC_COMM_SELF,M,0,1,&isrow);
92: ISCreateStride(PETSC_COMM_SELF,N,0,1,&iscol);
93: MatCreateSubMatrices(mat,1,&isrow,&iscol,MAT_INITIAL_MATRIX,&A);
94: ISDestroy(&isrow);
95: ISDestroy(&iscol);
96: matSeq = *A;
97: PetscFree(A);
98: }
99: } else {
100: PetscObjectReference((PetscObject)mat);
101: matSeq = mat;
102: }
104: if (!flg) { /* convert regular matrix to MPIADJ */
105: MatConvert(matSeq,MATMPIADJ,MAT_INITIAL_MATRIX,&matAdj);
106: } else {
107: PetscObjectReference((PetscObject)matSeq);
108: matAdj = matSeq;
109: }
111: adj = (Mat_MPIAdj*)matAdj->data; /* finaly adj contains adjacency graph */
113: /* arguments for Chaco library */
114: nvtxs = mat->rmap->N; /* number of vertices in full graph */
115: start = adj->i; /* start of edge list for each vertex */
116: vwgts = part->vertex_weights; /* weights for all vertices */
117: architecture = 1; /* 0 => hypercube, d => d-dimensional mesh */
118: ndims_tot = 0; /* total number of cube dimensions to divide */
119: mesh_dims[0] = part->n; /* dimensions of mesh of processors */
120: global_method = chaco->global_method; /* global partitioning algorithm */
121: local_method = chaco->local_method; /* local partitioning algorithm */
122: rqi_flag = chaco->eigen_method; /* should I use RQI/Symmlq eigensolver? */
123: vmax = chaco->nbvtxcoarsed; /* how many vertices to coarsen down to? */
124: ndims = chaco->eignum; /* number of eigenvectors (2^d sets) */
125: eigtol = chaco->eigtol; /* tolerance on eigenvectors */
126: seed = 123636512; /* for random graph mutations */
128: PetscMalloc1(mat->rmap->N,&assignment);
129: PetscMalloc1(start[nvtxs],&adjacency);
130: for (i=0; i<start[nvtxs]; i++) adjacency[i] = (adj->j)[i] + 1; /* 1-based indexing */
132: /* redirect output to buffer */
133: #if defined(PETSC_HAVE_UNISTD_H)
134: fd_stdout = dup(1);
135: if (pipe(fd_pipe)) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SYS,"Could not open pipe");
136: close(1);
137: dup2(fd_pipe[1],1);
138: PetscMalloc1(SIZE_LOG,&mesg_log);
139: #endif
141: /* library call */
142: interface(nvtxs,start,adjacency,vwgts,NULL,NULL,NULL,NULL,
143: NULL,NULL,assignment,architecture,ndims_tot,mesh_dims,
144: NULL,global_method,local_method,rqi_flag,vmax,ndims,eigtol,seed);
146: #if defined(PETSC_HAVE_UNISTD_H)
147: err = fflush(stdout);
148: if (err) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SYS,"fflush() failed on stdout");
149: count = read(fd_pipe[0],mesg_log,(SIZE_LOG-1)*sizeof(char));
150: if (count<0) count = 0;
151: mesg_log[count] = 0;
152: close(1);
153: dup2(fd_stdout,1);
154: close(fd_stdout);
155: close(fd_pipe[0]);
156: close(fd_pipe[1]);
157: if (chaco->verbose) {
158: PetscPrintf(PetscObjectComm((PetscObject)mat),mesg_log);
159: }
160: PetscFree(mesg_log);
161: #endif
162: if (ierr) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_LIB,"Chaco failed");
164: PetscMalloc1(mat->rmap->N,&parttab);
165: for (i=0; i<nvtxs; i++) parttab[i] = assignment[i];
167: /* creation of the index set */
168: nb_locals = mat->rmap->n;
169: locals = parttab + mat->rmap->rstart;
170: ISCreateGeneral(PetscObjectComm((PetscObject)part),nb_locals,locals,PETSC_COPY_VALUES,partitioning);
172: /* clean up */
173: PetscFree(parttab);
174: PetscFree(adjacency);
175: PetscFree(assignment);
176: MatDestroy(&matSeq);
177: MatDestroy(&matAdj);
178: return(0);
179: }
181: PetscErrorCode MatPartitioningView_Chaco(MatPartitioning part, PetscViewer viewer)
182: {
183: MatPartitioning_Chaco *chaco = (MatPartitioning_Chaco*)part->data;
184: PetscErrorCode ierr;
185: PetscBool isascii;
188: PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&isascii);
189: if (isascii) {
190: PetscViewerASCIIPrintf(viewer," Global method: %s\n",MPChacoGlobalTypes[chaco->global_method]);
191: PetscViewerASCIIPrintf(viewer," Local method: %s\n",MPChacoLocalTypes[chaco->local_method]);
192: PetscViewerASCIIPrintf(viewer," Number of vertices for the coarse graph: %d\n",chaco->nbvtxcoarsed);
193: PetscViewerASCIIPrintf(viewer," Eigensolver: %s\n",MPChacoEigenTypes[chaco->eigen_method]);
194: PetscViewerASCIIPrintf(viewer," Tolerance for eigensolver: %g\n",chaco->eigtol);
195: PetscViewerASCIIPrintf(viewer," Number of eigenvectors: %d\n",chaco->eignum);
196: }
197: return(0);
198: }
200: /*@
201: MatPartitioningChacoSetGlobal - Set global method for Chaco partitioner.
203: Collective on MatPartitioning
205: Input Parameters:
206: + part - the partitioning context
207: - method - one of MP_CHACO_MULTILEVEL, MP_CHACO_SPECTRAL, MP_CHACO_LINEAR,
208: MP_CHACO_RANDOM or MP_CHACO_SCATTERED
210: Options Database:
211: . -mat_partitioning_chaco_global <method> - the global method
213: Level: advanced
215: Notes:
216: The default is the multi-level method. See Chaco documentation for
217: additional details.
219: .seealso: MatPartitioningChacoSetLocal(),MatPartitioningChacoGetGlobal()
220: @*/
221: PetscErrorCode MatPartitioningChacoSetGlobal(MatPartitioning part,MPChacoGlobalType method)
222: {
228: PetscTryMethod(part,"MatPartitioningChacoSetGlobal_C",(MatPartitioning,MPChacoGlobalType),(part,method));
229: return(0);
230: }
232: PetscErrorCode MatPartitioningChacoSetGlobal_Chaco(MatPartitioning part,MPChacoGlobalType method)
233: {
234: MatPartitioning_Chaco *chaco = (MatPartitioning_Chaco*)part->data;
237: switch (method) {
238: case MP_CHACO_MULTILEVEL:
239: case MP_CHACO_SPECTRAL:
240: case MP_CHACO_LINEAR:
241: case MP_CHACO_RANDOM:
242: case MP_CHACO_SCATTERED:
243: chaco->global_method = method; break;
244: default:
245: SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Chaco: Unknown or unsupported option");
246: }
247: return(0);
248: }
250: /*@
251: MatPartitioningChacoGetGlobal - Get global method for Chaco partitioner.
253: Not Collective
255: Input Parameter:
256: . part - the partitioning context
258: Output Parameter:
259: . method - the method
261: Level: advanced
263: .seealso: MatPartitioningChacoSetGlobal()
264: @*/
265: PetscErrorCode MatPartitioningChacoGetGlobal(MatPartitioning part,MPChacoGlobalType *method)
266: {
272: PetscTryMethod(part,"MatPartitioningChacoGetGlobal_C",(MatPartitioning,MPChacoGlobalType*),(part,method));
273: return(0);
274: }
276: PetscErrorCode MatPartitioningChacoGetGlobal_Chaco(MatPartitioning part,MPChacoGlobalType *method)
277: {
278: MatPartitioning_Chaco *chaco = (MatPartitioning_Chaco*)part->data;
281: *method = chaco->global_method;
282: return(0);
283: }
285: /*@
286: MatPartitioningChacoSetLocal - Set local method for Chaco partitioner.
288: Collective on MatPartitioning
290: Input Parameters:
291: + part - the partitioning context
292: - method - one of MP_CHACO_KERNIGHAN or MP_CHACO_NONE
294: Options Database:
295: . -mat_partitioning_chaco_local <method> - the local method
297: Level: advanced
299: Notes:
300: The default is to apply the Kernighan-Lin heuristic. See Chaco documentation
301: for additional details.
303: .seealso: MatPartitioningChacoSetGlobal(),MatPartitioningChacoGetLocal()
304: @*/
305: PetscErrorCode MatPartitioningChacoSetLocal(MatPartitioning part,MPChacoLocalType method)
306: {
312: PetscTryMethod(part,"MatPartitioningChacoSetLocal_C",(MatPartitioning,MPChacoLocalType),(part,method));
313: return(0);
314: }
316: PetscErrorCode MatPartitioningChacoSetLocal_Chaco(MatPartitioning part,MPChacoLocalType method)
317: {
318: MatPartitioning_Chaco *chaco = (MatPartitioning_Chaco*)part->data;
321: switch (method) {
322: case MP_CHACO_KERNIGHAN:
323: case MP_CHACO_NONE:
324: chaco->local_method = method; break;
325: default:
326: SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Chaco: Unknown or unsupported option");
327: }
328: return(0);
329: }
331: /*@
332: MatPartitioningChacoGetLocal - Get local method for Chaco partitioner.
334: Not Collective
336: Input Parameter:
337: . part - the partitioning context
339: Output Parameter:
340: . method - the method
342: Level: advanced
344: .seealso: MatPartitioningChacoSetLocal()
345: @*/
346: PetscErrorCode MatPartitioningChacoGetLocal(MatPartitioning part,MPChacoLocalType *method)
347: {
353: PetscUseMethod(part,"MatPartitioningChacoGetLocal_C",(MatPartitioning,MPChacoLocalType*),(part,method));
354: return(0);
355: }
357: PetscErrorCode MatPartitioningChacoGetLocal_Chaco(MatPartitioning part,MPChacoLocalType *method)
358: {
359: MatPartitioning_Chaco *chaco = (MatPartitioning_Chaco*)part->data;
362: *method = chaco->local_method;
363: return(0);
364: }
366: /*@
367: MatPartitioningChacoSetCoarseLevel - Set the coarse level parameter for the
368: Chaco partitioner.
370: Collective on MatPartitioning
372: Input Parameters:
373: + part - the partitioning context
374: - level - the coarse level in range [0.0,1.0]
376: Options Database:
377: . -mat_partitioning_chaco_coarse <l> - Coarse level
379: Level: advanced
380: @*/
381: PetscErrorCode MatPartitioningChacoSetCoarseLevel(MatPartitioning part,PetscReal level)
382: {
388: PetscTryMethod(part,"MatPartitioningChacoSetCoarseLevel_C",(MatPartitioning,PetscReal),(part,level));
389: return(0);
390: }
392: PetscErrorCode MatPartitioningChacoSetCoarseLevel_Chaco(MatPartitioning part,PetscReal level)
393: {
394: MatPartitioning_Chaco *chaco = (MatPartitioning_Chaco*)part->data;
397: if (level<0.0 || level>1.0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Chaco: level of coarsening out of range [0.0-1.0]");
398: chaco->nbvtxcoarsed = (PetscInt)(part->adj->cmap->N * level);
399: if (chaco->nbvtxcoarsed < 20) chaco->nbvtxcoarsed = 20;
400: return(0);
401: }
403: /*@
404: MatPartitioningChacoSetEigenSolver - Set eigensolver method for Chaco partitioner.
406: Collective on MatPartitioning
408: Input Parameters:
409: + part - the partitioning context
410: - method - one of MP_CHACO_LANCZOS or MP_CHACO_RQI
412: Options Database:
413: . -mat_partitioning_chaco_eigen_solver <method> - the eigensolver
415: Level: advanced
417: Notes:
418: The default is to use a Lanczos method. See Chaco documentation for details.
420: .seealso: MatPartitioningChacoSetEigenTol(),MatPartitioningChacoSetEigenNumber(),
421: MatPartitioningChacoGetEigenSolver()
422: @*/
423: PetscErrorCode MatPartitioningChacoSetEigenSolver(MatPartitioning part,MPChacoEigenType method)
424: {
430: PetscTryMethod(part,"MatPartitioningChacoSetEigenSolver_C",(MatPartitioning,MPChacoEigenType),(part,method));
431: return(0);
432: }
434: PetscErrorCode MatPartitioningChacoSetEigenSolver_Chaco(MatPartitioning part,MPChacoEigenType method)
435: {
436: MatPartitioning_Chaco *chaco = (MatPartitioning_Chaco*)part->data;
439: switch (method) {
440: case MP_CHACO_LANCZOS:
441: case MP_CHACO_RQI:
442: chaco->eigen_method = method; break;
443: default:
444: SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Chaco: Unknown or unsupported option");
445: }
446: return(0);
447: }
449: /*@
450: MatPartitioningChacoGetEigenSolver - Get local method for Chaco partitioner.
452: Not Collective
454: Input Parameter:
455: . part - the partitioning context
457: Output Parameter:
458: . method - the method
460: Level: advanced
462: .seealso: MatPartitioningChacoSetEigenSolver()
463: @*/
464: PetscErrorCode MatPartitioningChacoGetEigenSolver(MatPartitioning part,MPChacoEigenType *method)
465: {
471: PetscUseMethod(part,"MatPartitioningChacoGetEigenSolver_C",(MatPartitioning,MPChacoEigenType*),(part,method));
472: return(0);
473: }
475: PetscErrorCode MatPartitioningChacoGetEigenSolver_Chaco(MatPartitioning part,MPChacoEigenType *method)
476: {
477: MatPartitioning_Chaco *chaco = (MatPartitioning_Chaco*)part->data;
480: *method = chaco->eigen_method;
481: return(0);
482: }
484: /*@
485: MatPartitioningChacoSetEigenTol - Sets the tolerance for the eigensolver.
487: Collective on MatPartitioning
489: Input Parameters:
490: + part - the partitioning context
491: - tol - the tolerance
493: Options Database:
494: . -mat_partitioning_chaco_eigen_tol <tol>: Tolerance for eigensolver
496: Note:
497: Must be positive. The default value is 0.001.
499: Level: advanced
501: .seealso: MatPartitioningChacoSetEigenSolver(), MatPartitioningChacoGetEigenTol()
502: @*/
503: PetscErrorCode MatPartitioningChacoSetEigenTol(MatPartitioning part,PetscReal tol)
504: {
510: PetscTryMethod(part,"MatPartitioningChacoSetEigenTol_C",(MatPartitioning,PetscReal),(part,tol));
511: return(0);
512: }
514: PetscErrorCode MatPartitioningChacoSetEigenTol_Chaco(MatPartitioning part,PetscReal tol)
515: {
516: MatPartitioning_Chaco *chaco = (MatPartitioning_Chaco*)part->data;
519: if (tol==PETSC_DEFAULT) chaco->eigtol = 0.001;
520: else {
521: if (tol<=0.0) SETERRQ(PetscObjectComm((PetscObject)part),PETSC_ERR_ARG_OUTOFRANGE,"Tolerance must be positive");
522: chaco->eigtol = tol;
523: }
524: return(0);
525: }
527: /*@
528: MatPartitioningChacoGetEigenTol - Gets the eigensolver tolerance.
530: Not Collective
532: Input Parameter:
533: . part - the partitioning context
535: Output Parameter:
536: . tol - the tolerance
538: Level: advanced
540: .seealso: MatPartitioningChacoSetEigenTol()
541: @*/
542: PetscErrorCode MatPartitioningChacoGetEigenTol(MatPartitioning part,PetscReal *tol)
543: {
549: PetscUseMethod(part,"MatPartitioningChacoGetEigenTol_C",(MatPartitioning,PetscReal*),(part,tol));
550: return(0);
551: }
553: PetscErrorCode MatPartitioningChacoGetEigenTol_Chaco(MatPartitioning part,PetscReal *tol)
554: {
555: MatPartitioning_Chaco *chaco = (MatPartitioning_Chaco*)part->data;
558: *tol = chaco->eigtol;
559: return(0);
560: }
562: /*@
563: MatPartitioningChacoSetEigenNumber - Sets the number of eigenvectors to compute
564: during partitioning.
566: Collective on MatPartitioning
568: Input Parameters:
569: + part - the partitioning context
570: - num - the number of eigenvectors
572: Options Database:
573: . -mat_partitioning_chaco_eigen_number <n>: Number of eigenvectors
575: Note:
576: Accepted values are 1, 2 or 3, indicating partitioning by bisection,
577: quadrisection, or octosection.
579: Level: advanced
581: .seealso: MatPartitioningChacoSetEigenSolver(), MatPartitioningChacoGetEigenTol()
582: @*/
583: PetscErrorCode MatPartitioningChacoSetEigenNumber(MatPartitioning part,PetscInt num)
584: {
590: PetscTryMethod(part,"MatPartitioningChacoSetEigenNumber_C",(MatPartitioning,PetscInt),(part,num));
591: return(0);
592: }
594: PetscErrorCode MatPartitioningChacoSetEigenNumber_Chaco(MatPartitioning part,PetscInt num)
595: {
596: MatPartitioning_Chaco *chaco = (MatPartitioning_Chaco*)part->data;
599: if (num==PETSC_DEFAULT) chaco->eignum = 1;
600: else {
601: if (num<1 || num>3) SETERRQ(PetscObjectComm((PetscObject)part),PETSC_ERR_ARG_OUTOFRANGE,"Can only specify 1, 2 or 3 eigenvectors");
602: chaco->eignum = num;
603: }
604: return(0);
605: }
607: /*@
608: MatPartitioningChacoGetEigenNumber - Gets the number of eigenvectors used by Chaco.
610: Not Collective
612: Input Parameter:
613: . part - the partitioning context
615: Output Parameter:
616: . num - number of eigenvectors
618: Level: advanced
620: .seealso: MatPartitioningChacoSetEigenNumber()
621: @*/
622: PetscErrorCode MatPartitioningChacoGetEigenNumber(MatPartitioning part,PetscInt *num)
623: {
629: PetscUseMethod(part,"MatPartitioningChacoGetEigenNumber_C",(MatPartitioning,PetscInt*),(part,num));
630: return(0);
631: }
633: PetscErrorCode MatPartitioningChacoGetEigenNumber_Chaco(MatPartitioning part,PetscInt *num)
634: {
635: MatPartitioning_Chaco *chaco = (MatPartitioning_Chaco*)part->data;
638: *num = chaco->eignum;
639: return(0);
640: }
642: PetscErrorCode MatPartitioningSetFromOptions_Chaco(PetscOptionItems *PetscOptionsObject,MatPartitioning part)
643: {
644: PetscErrorCode ierr;
645: PetscInt i;
646: PetscReal r;
647: PetscBool flag;
648: MatPartitioning_Chaco *chaco = (MatPartitioning_Chaco*)part->data;
649: MPChacoGlobalType global;
650: MPChacoLocalType local;
651: MPChacoEigenType eigen;
654: PetscOptionsHead(PetscOptionsObject,"Chaco partitioning options");
655: PetscOptionsEnum("-mat_partitioning_chaco_global","Global method","MatPartitioningChacoSetGlobal",MPChacoGlobalTypes,(PetscEnum)chaco->global_method,(PetscEnum*)&global,&flag);
656: if (flag) { MatPartitioningChacoSetGlobal(part,global); }
657: PetscOptionsEnum("-mat_partitioning_chaco_local","Local method","MatPartitioningChacoSetLocal",MPChacoLocalTypes,(PetscEnum)chaco->local_method,(PetscEnum*)&local,&flag);
658: if (flag) { MatPartitioningChacoSetLocal(part,local); }
659: PetscOptionsReal("-mat_partitioning_chaco_coarse","Coarse level","MatPartitioningChacoSetCoarseLevel",0.0,&r,&flag);
660: if (flag) { MatPartitioningChacoSetCoarseLevel(part,r); }
661: PetscOptionsEnum("-mat_partitioning_chaco_eigen_solver","Eigensolver method","MatPartitioningChacoSetEigenSolver",MPChacoEigenTypes,(PetscEnum)chaco->eigen_method,(PetscEnum*)&eigen,&flag);
662: if (flag) { MatPartitioningChacoSetEigenSolver(part,eigen); }
663: PetscOptionsReal("-mat_partitioning_chaco_eigen_tol","Eigensolver tolerance","MatPartitioningChacoSetEigenTol",chaco->eigtol,&r,&flag);
664: if (flag) { MatPartitioningChacoSetEigenTol(part,r); }
665: PetscOptionsInt("-mat_partitioning_chaco_eigen_number","Number of eigenvectors: 1, 2, or 3 (bi-, quadri-, or octosection)","MatPartitioningChacoSetEigenNumber",chaco->eignum,&i,&flag);
666: if (flag) { MatPartitioningChacoSetEigenNumber(part,i); }
667: PetscOptionsBool("-mat_partitioning_chaco_verbose","Show library output","",chaco->verbose,&chaco->verbose,NULL);
668: PetscOptionsTail();
669: return(0);
670: }
672: PetscErrorCode MatPartitioningDestroy_Chaco(MatPartitioning part)
673: {
674: MatPartitioning_Chaco *chaco = (MatPartitioning_Chaco*) part->data;
675: PetscErrorCode ierr;
678: PetscFree(chaco);
679: /* clear composed functions */
680: PetscObjectComposeFunction((PetscObject)part,"MatPartitioningChacoSetGlobal_C",NULL);
681: PetscObjectComposeFunction((PetscObject)part,"MatPartitioningChacoGetGlobal_C",NULL);
682: PetscObjectComposeFunction((PetscObject)part,"MatPartitioningChacoSetLocal_C",NULL);
683: PetscObjectComposeFunction((PetscObject)part,"MatPartitioningChacoGetLocal_C",NULL);
684: PetscObjectComposeFunction((PetscObject)part,"MatPartitioningChacoSetCoarseLevel_C",NULL);
685: PetscObjectComposeFunction((PetscObject)part,"MatPartitioningChacoSetEigenSolver_C",NULL);
686: PetscObjectComposeFunction((PetscObject)part,"MatPartitioningChacoGetEigenSolver_C",NULL);
687: PetscObjectComposeFunction((PetscObject)part,"MatPartitioningChacoSetEigenTol_C",NULL);
688: PetscObjectComposeFunction((PetscObject)part,"MatPartitioningChacoGetEigenTol_C",NULL);
689: PetscObjectComposeFunction((PetscObject)part,"MatPartitioningChacoSetEigenNumber_C",NULL);
690: PetscObjectComposeFunction((PetscObject)part,"MatPartitioningChacoGetEigenNumber_C",NULL);
691: return(0);
692: }
694: /*MC
695: MATPARTITIONINGCHACO - Creates a partitioning context via the external package Chaco.
697: Level: beginner
699: Notes: See http://www.cs.sandia.gov/CRF/chac.html
701: .keywords: Partitioning, create, context
703: .seealso: MatPartitioningSetType(), MatPartitioningType
704: M*/
706: PETSC_EXTERN PetscErrorCode MatPartitioningCreate_Chaco(MatPartitioning part)
707: {
708: PetscErrorCode ierr;
709: MatPartitioning_Chaco *chaco;
712: PetscNewLog(part,&chaco);
713: part->data = (void*)chaco;
715: chaco->global_method = MP_CHACO_MULTILEVEL;
716: chaco->local_method = MP_CHACO_KERNIGHAN;
717: chaco->eigen_method = MP_CHACO_LANCZOS;
718: chaco->nbvtxcoarsed = 200;
719: chaco->eignum = 1;
720: chaco->eigtol = 0.001;
721: chaco->verbose = PETSC_FALSE;
723: part->ops->apply = MatPartitioningApply_Chaco;
724: part->ops->view = MatPartitioningView_Chaco;
725: part->ops->destroy = MatPartitioningDestroy_Chaco;
726: part->ops->setfromoptions = MatPartitioningSetFromOptions_Chaco;
728: PetscObjectComposeFunction((PetscObject)part,"MatPartitioningChacoSetGlobal_C",MatPartitioningChacoSetGlobal_Chaco);
729: PetscObjectComposeFunction((PetscObject)part,"MatPartitioningChacoGetGlobal_C",MatPartitioningChacoGetGlobal_Chaco);
730: PetscObjectComposeFunction((PetscObject)part,"MatPartitioningChacoSetLocal_C",MatPartitioningChacoSetLocal_Chaco);
731: PetscObjectComposeFunction((PetscObject)part,"MatPartitioningChacoGetLocal_C",MatPartitioningChacoGetLocal_Chaco);
732: PetscObjectComposeFunction((PetscObject)part,"MatPartitioningChacoSetCoarseLevel_C",MatPartitioningChacoSetCoarseLevel_Chaco);
733: PetscObjectComposeFunction((PetscObject)part,"MatPartitioningChacoSetEigenSolver_C",MatPartitioningChacoSetEigenSolver_Chaco);
734: PetscObjectComposeFunction((PetscObject)part,"MatPartitioningChacoGetEigenSolver_C",MatPartitioningChacoGetEigenSolver_Chaco);
735: PetscObjectComposeFunction((PetscObject)part,"MatPartitioningChacoSetEigenTol_C",MatPartitioningChacoSetEigenTol_Chaco);
736: PetscObjectComposeFunction((PetscObject)part,"MatPartitioningChacoGetEigenTol_C",MatPartitioningChacoGetEigenTol_Chaco);
737: PetscObjectComposeFunction((PetscObject)part,"MatPartitioningChacoSetEigenNumber_C",MatPartitioningChacoSetEigenNumber_Chaco);
738: PetscObjectComposeFunction((PetscObject)part,"MatPartitioningChacoGetEigenNumber_C",MatPartitioningChacoGetEigenNumber_Chaco);
739: return(0);
740: }