Actual source code: chaco.c
1: #include <../src/mat/impls/adj/mpi/mpiadj.h>
3: #if defined(PETSC_HAVE_UNISTD_H)
4: #include <unistd.h>
5: #endif
7: #if defined(PETSC_HAVE_CHACO_INT_ASSIGNMENT)
8: #include <chaco.h>
9: #else
10: /* Older versions of Chaco do not have an include file */
11: PETSC_EXTERN int interface(int nvtxs, int *start, int *adjacency, int *vwgts, float *ewgts, float *x, float *y, float *z, char *outassignname, char *outfilename, short *assignment, int architecture, int ndims_tot, int mesh_dims[3], double *goal, int global_method, int local_method, int rqi_flag, int vmax, int ndims, double eigtol, long seed);
12: #endif
14: extern int FREE_GRAPH;
16: /*
17: int nvtxs; number of vertices in full graph
18: int *start; start of edge list for each vertex
19: int *adjacency; edge list data
20: int *vwgts; weights for all vertices
21: float *ewgts; weights for all edges
22: float *x, *y, *z; coordinates for inertial method
23: char *outassignname; name of assignment output file
24: char *outfilename; output file name
25: short *assignment; set number of each vtx (length n)
26: int architecture; 0 => hypercube, d => d-dimensional mesh
27: int ndims_tot; total number of cube dimensions to divide
28: int mesh_dims[3]; dimensions of mesh of processors
29: double *goal; desired set sizes for each set
30: int global_method; global partitioning algorithm
31: int local_method; local partitioning algorithm
32: int rqi_flag; should I use RQI/Symmlq eigensolver?
33: int vmax; how many vertices to coarsen down to?
34: int ndims; number of eigenvectors (2^d sets)
35: double eigtol; tolerance on eigenvectors
36: long seed; for random graph mutations
37: */
39: typedef struct {
40: PetscBool verbose;
41: PetscInt eignum;
42: PetscReal eigtol;
43: MPChacoGlobalType global_method; /* global method */
44: MPChacoLocalType local_method; /* local method */
45: MPChacoEigenType eigen_method; /* eigensolver */
46: PetscInt nbvtxcoarsed; /* number of vertices for the coarse graph */
47: } MatPartitioning_Chaco;
49: #define SIZE_LOG 10000 /* size of buffer for mesg_log */
51: static PetscErrorCode MatPartitioningApply_Chaco(MatPartitioning part, IS *partitioning)
52: {
53: int cerr;
54: PetscInt *parttab, *locals, i, nb_locals, M, N;
55: PetscMPIInt size, rank;
56: Mat mat = part->adj, matAdj, matSeq, *A;
57: Mat_MPIAdj *adj;
58: MatPartitioning_Chaco *chaco = (MatPartitioning_Chaco *)part->data;
59: PetscBool flg;
60: IS isrow, iscol;
61: int nvtxs, *start, *adjacency, *vwgts, architecture, ndims_tot;
62: int mesh_dims[3], global_method, local_method, rqi_flag, vmax, ndims;
63: #if defined(PETSC_HAVE_CHACO_INT_ASSIGNMENT)
64: int *assignment;
65: #else
66: short *assignment;
67: #endif
68: double eigtol;
69: long seed;
70: char *mesg_log;
71: #if defined(PETSC_HAVE_UNISTD_H)
72: int fd_stdout, fd_pipe[2], count;
73: #endif
75: PetscFunctionBegin;
76: PetscCheck(!part->use_edge_weights, PetscObjectComm((PetscObject)part), PETSC_ERR_SUP, "Chaco does not support edge weights");
77: FREE_GRAPH = 0; /* otherwise Chaco will attempt to free memory for adjacency graph */
78: PetscCallMPI(MPI_Comm_size(PetscObjectComm((PetscObject)mat), &size));
79: PetscCallMPI(MPI_Comm_rank(PetscObjectComm((PetscObject)mat), &rank));
80: PetscCall(PetscObjectTypeCompare((PetscObject)mat, MATMPIADJ, &flg));
81: if (size > 1) {
82: if (flg) PetscCall(MatMPIAdjToSeq(mat, &matSeq));
83: else {
84: PetscCall(PetscInfo(part, "Converting distributed matrix to sequential: this could be a performance loss\n"));
85: PetscCall(MatGetSize(mat, &M, &N));
86: PetscCall(ISCreateStride(PETSC_COMM_SELF, M, 0, 1, &isrow));
87: PetscCall(ISCreateStride(PETSC_COMM_SELF, N, 0, 1, &iscol));
88: PetscCall(MatCreateSubMatrices(mat, 1, &isrow, &iscol, MAT_INITIAL_MATRIX, &A));
89: PetscCall(ISDestroy(&isrow));
90: PetscCall(ISDestroy(&iscol));
91: matSeq = *A;
92: PetscCall(PetscFree(A));
93: }
94: } else {
95: PetscCall(PetscObjectReference((PetscObject)mat));
96: matSeq = mat;
97: }
99: if (!flg) { /* convert regular matrix to MPIADJ */
100: PetscCall(MatConvert(matSeq, MATMPIADJ, MAT_INITIAL_MATRIX, &matAdj));
101: } else {
102: PetscCall(PetscObjectReference((PetscObject)matSeq));
103: matAdj = matSeq;
104: }
106: adj = (Mat_MPIAdj *)matAdj->data; /* finally adj contains adjacency graph */
108: /* arguments for Chaco library */
109: nvtxs = mat->rmap->N; /* number of vertices in full graph */
110: start = adj->i; /* start of edge list for each vertex */
111: vwgts = part->vertex_weights; /* weights for all vertices */
112: architecture = 1; /* 0 => hypercube, d => d-dimensional mesh */
113: ndims_tot = 0; /* total number of cube dimensions to divide */
114: mesh_dims[0] = part->n; /* dimensions of mesh of processors */
115: global_method = chaco->global_method; /* global partitioning algorithm */
116: local_method = chaco->local_method; /* local partitioning algorithm */
117: rqi_flag = chaco->eigen_method; /* should I use RQI/Symmlq eigensolver? */
118: vmax = chaco->nbvtxcoarsed; /* how many vertices to coarsen down to? */
119: ndims = chaco->eignum; /* number of eigenvectors (2^d sets) */
120: eigtol = chaco->eigtol; /* tolerance on eigenvectors */
121: seed = 123636512; /* for random graph mutations */
123: PetscCall(PetscMalloc1(mat->rmap->N, &assignment));
124: PetscCall(PetscMalloc1(start[nvtxs], &adjacency));
125: for (i = 0; i < start[nvtxs]; i++) adjacency[i] = (adj->j)[i] + 1; /* 1-based indexing */
127: /* redirect output to buffer */
128: #if defined(PETSC_HAVE_UNISTD_H)
129: fd_stdout = dup(1);
130: PetscCheck(!pipe(fd_pipe), PETSC_COMM_SELF, PETSC_ERR_SYS, "Could not open pipe");
131: close(1);
132: dup2(fd_pipe[1], 1);
133: PetscCall(PetscMalloc1(SIZE_LOG, &mesg_log));
134: #endif
136: /* library call */
137: cerr = interface(nvtxs, start, adjacency, vwgts, NULL, NULL, NULL, NULL, NULL, NULL, assignment, architecture, ndims_tot, mesh_dims, NULL, global_method, local_method, rqi_flag, vmax, ndims, eigtol, seed);
139: #if defined(PETSC_HAVE_UNISTD_H)
140: PetscCall(PetscFFlush(stdout));
141: count = (int)read(fd_pipe[0], mesg_log, (int)((SIZE_LOG - 1) * sizeof(char)));
142: if (count < 0) count = 0;
143: mesg_log[count] = 0;
144: close(1);
145: dup2(fd_stdout, 1);
146: close(fd_stdout);
147: close(fd_pipe[0]);
148: close(fd_pipe[1]);
149: if (chaco->verbose) PetscCall(PetscPrintf(PetscObjectComm((PetscObject)mat), "%s", mesg_log));
150: PetscCall(PetscFree(mesg_log));
151: #endif
152: PetscCheck(!cerr, PETSC_COMM_SELF, PETSC_ERR_LIB, "Chaco failed");
154: PetscCall(PetscMalloc1(mat->rmap->N, &parttab));
155: for (i = 0; i < nvtxs; i++) parttab[i] = assignment[i];
157: /* creation of the index set */
158: nb_locals = mat->rmap->n;
159: locals = parttab + mat->rmap->rstart;
160: PetscCall(ISCreateGeneral(PetscObjectComm((PetscObject)part), nb_locals, locals, PETSC_COPY_VALUES, partitioning));
162: /* clean up */
163: PetscCall(PetscFree(parttab));
164: PetscCall(PetscFree(adjacency));
165: PetscCall(PetscFree(assignment));
166: PetscCall(MatDestroy(&matSeq));
167: PetscCall(MatDestroy(&matAdj));
168: PetscFunctionReturn(PETSC_SUCCESS);
169: }
171: static PetscErrorCode MatPartitioningView_Chaco(MatPartitioning part, PetscViewer viewer)
172: {
173: MatPartitioning_Chaco *chaco = (MatPartitioning_Chaco *)part->data;
174: PetscBool isascii;
176: PetscFunctionBegin;
177: PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERASCII, &isascii));
178: if (isascii) {
179: PetscCall(PetscViewerASCIIPrintf(viewer, " Global method: %s\n", MPChacoGlobalTypes[chaco->global_method]));
180: PetscCall(PetscViewerASCIIPrintf(viewer, " Local method: %s\n", MPChacoLocalTypes[chaco->local_method]));
181: PetscCall(PetscViewerASCIIPrintf(viewer, " Number of vertices for the coarse graph: %" PetscInt_FMT "\n", chaco->nbvtxcoarsed));
182: PetscCall(PetscViewerASCIIPrintf(viewer, " Eigensolver: %s\n", MPChacoEigenTypes[chaco->eigen_method]));
183: PetscCall(PetscViewerASCIIPrintf(viewer, " Tolerance for eigensolver: %g\n", chaco->eigtol));
184: PetscCall(PetscViewerASCIIPrintf(viewer, " Number of eigenvectors: %" PetscInt_FMT "\n", chaco->eignum));
185: }
186: PetscFunctionReturn(PETSC_SUCCESS);
187: }
189: /*@
190: MatPartitioningChacoSetGlobal - Set the global method for Chaco partitioner.
192: Collective
194: Input Parameters:
195: + part - the partitioning context
196: - method - one of `MP_CHACO_MULTILEVEL`, `MP_CHACO_SPECTRAL`, `MP_CHACO_LINEAR`,
197: `MP_CHACO_RANDOM` or `MP_CHACO_SCATTERED`
199: Options Database Key:
200: . -mat_partitioning_chaco_global method - the global method
202: Level: advanced
204: Note:
205: The default is the multi-level method. See Chaco documentation for
206: additional details.
208: .seealso: `MatPartitioning`, `MatPartioningSetType()`, `MatPartitioningType`, `MATPARTITIONINGCHACO`, `MatPartitioningChacoSetLocal()`, `MatPartitioningChacoGetGlobal()`
209: @*/
210: PetscErrorCode MatPartitioningChacoSetGlobal(MatPartitioning part, MPChacoGlobalType method)
211: {
212: PetscFunctionBegin;
215: PetscTryMethod(part, "MatPartitioningChacoSetGlobal_C", (MatPartitioning, MPChacoGlobalType), (part, method));
216: PetscFunctionReturn(PETSC_SUCCESS);
217: }
219: static PetscErrorCode MatPartitioningChacoSetGlobal_Chaco(MatPartitioning part, MPChacoGlobalType method)
220: {
221: MatPartitioning_Chaco *chaco = (MatPartitioning_Chaco *)part->data;
223: PetscFunctionBegin;
224: switch (method) {
225: case MP_CHACO_MULTILEVEL:
226: case MP_CHACO_SPECTRAL:
227: case MP_CHACO_LINEAR:
228: case MP_CHACO_RANDOM:
229: case MP_CHACO_SCATTERED:
230: chaco->global_method = method;
231: break;
232: default:
233: SETERRQ(PETSC_COMM_SELF, PETSC_ERR_ARG_WRONG, "Chaco: Unknown or unsupported option");
234: }
235: PetscFunctionReturn(PETSC_SUCCESS);
236: }
238: /*@
239: MatPartitioningChacoGetGlobal - Get the global method used by the Chaco partitioner.
241: Not Collective
243: Input Parameter:
244: . part - the partitioning context
246: Output Parameter:
247: . method - the method
249: Level: advanced
251: .seealso: `MatPartitioningType`, `MATPARTITIONINGCHACO`, `MatPartitioningChacoSetGlobal()`
252: @*/
253: PetscErrorCode MatPartitioningChacoGetGlobal(MatPartitioning part, MPChacoGlobalType *method)
254: {
255: PetscFunctionBegin;
257: PetscAssertPointer(method, 2);
258: PetscTryMethod(part, "MatPartitioningChacoGetGlobal_C", (MatPartitioning, MPChacoGlobalType *), (part, method));
259: PetscFunctionReturn(PETSC_SUCCESS);
260: }
262: static PetscErrorCode MatPartitioningChacoGetGlobal_Chaco(MatPartitioning part, MPChacoGlobalType *method)
263: {
264: MatPartitioning_Chaco *chaco = (MatPartitioning_Chaco *)part->data;
266: PetscFunctionBegin;
267: *method = chaco->global_method;
268: PetscFunctionReturn(PETSC_SUCCESS);
269: }
271: /*@
272: MatPartitioningChacoSetLocal - Set the local method for the Chaco partitioner.
274: Collective
276: Input Parameters:
277: + part - the partitioning context
278: - method - one of `MP_CHACO_KERNIGHAN` or `MP_CHACO_NONE`
280: Options Database Key:
281: . -mat_partitioning_chaco_local method - the local method
283: Level: advanced
285: Note:
286: The default is to apply the Kernighan-Lin heuristic. See Chaco documentation
287: for additional details.
289: .seealso: `MatPartitioningType`, `MATPARTITIONINGCHACO`, `MatPartitioningChacoSetGlobal()`, `MatPartitioningChacoGetLocal()`
290: @*/
291: PetscErrorCode MatPartitioningChacoSetLocal(MatPartitioning part, MPChacoLocalType method)
292: {
293: PetscFunctionBegin;
296: PetscTryMethod(part, "MatPartitioningChacoSetLocal_C", (MatPartitioning, MPChacoLocalType), (part, method));
297: PetscFunctionReturn(PETSC_SUCCESS);
298: }
300: static PetscErrorCode MatPartitioningChacoSetLocal_Chaco(MatPartitioning part, MPChacoLocalType method)
301: {
302: MatPartitioning_Chaco *chaco = (MatPartitioning_Chaco *)part->data;
304: PetscFunctionBegin;
305: switch (method) {
306: case MP_CHACO_KERNIGHAN:
307: case MP_CHACO_NONE:
308: chaco->local_method = method;
309: break;
310: default:
311: SETERRQ(PETSC_COMM_SELF, PETSC_ERR_ARG_WRONG, "Chaco: Unknown or unsupported option");
312: }
313: PetscFunctionReturn(PETSC_SUCCESS);
314: }
316: /*@
317: MatPartitioningChacoGetLocal - Get local method used by the Chaco partitioner.
319: Not Collective
321: Input Parameter:
322: . part - the partitioning context
324: Output Parameter:
325: . method - the method
327: Level: advanced
329: .seealso: `MatPartitioningType`, `MATPARTITIONINGCHACO`, `MatPartitioningChacoSetLocal()`
330: @*/
331: PetscErrorCode MatPartitioningChacoGetLocal(MatPartitioning part, MPChacoLocalType *method)
332: {
333: PetscFunctionBegin;
335: PetscAssertPointer(method, 2);
336: PetscUseMethod(part, "MatPartitioningChacoGetLocal_C", (MatPartitioning, MPChacoLocalType *), (part, method));
337: PetscFunctionReturn(PETSC_SUCCESS);
338: }
340: static PetscErrorCode MatPartitioningChacoGetLocal_Chaco(MatPartitioning part, MPChacoLocalType *method)
341: {
342: MatPartitioning_Chaco *chaco = (MatPartitioning_Chaco *)part->data;
344: PetscFunctionBegin;
345: *method = chaco->local_method;
346: PetscFunctionReturn(PETSC_SUCCESS);
347: }
349: /*@
350: MatPartitioningChacoSetCoarseLevel - Set the coarse level parameter for the
351: Chaco partitioner.
353: Collective
355: Input Parameters:
356: + part - the partitioning context
357: - level - the coarse level in range [0.0,1.0]
359: Options Database Key:
360: . -mat_partitioning_chaco_coarse l - Coarse level
362: Level: advanced
364: .seealso: `MatPartitioningType`, `MatPartitioning`, `MATPARTITIONINGCHACO`
365: @*/
366: PetscErrorCode MatPartitioningChacoSetCoarseLevel(MatPartitioning part, PetscReal level)
367: {
368: PetscFunctionBegin;
371: PetscTryMethod(part, "MatPartitioningChacoSetCoarseLevel_C", (MatPartitioning, PetscReal), (part, level));
372: PetscFunctionReturn(PETSC_SUCCESS);
373: }
375: static PetscErrorCode MatPartitioningChacoSetCoarseLevel_Chaco(MatPartitioning part, PetscReal level)
376: {
377: MatPartitioning_Chaco *chaco = (MatPartitioning_Chaco *)part->data;
379: PetscFunctionBegin;
380: PetscCheck(level >= 0.0 && level < 1.0, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Chaco: level of coarsening out of range [0.0-1.0]");
381: chaco->nbvtxcoarsed = (PetscInt)(part->adj->cmap->N * level);
382: if (chaco->nbvtxcoarsed < 20) chaco->nbvtxcoarsed = 20;
383: PetscFunctionReturn(PETSC_SUCCESS);
384: }
386: /*@
387: MatPartitioningChacoSetEigenSolver - Set the eigensolver method for Chaco partitioner.
389: Collective
391: Input Parameters:
392: + part - the partitioning context
393: - method - one of `MP_CHACO_LANCZOS` or `MP_CHACO_RQI`
395: Options Database Key:
396: . -mat_partitioning_chaco_eigen_solver method - the eigensolver
398: Level: advanced
400: Note:
401: The default is to use a Lanczos method. See Chaco documentation for details.
403: .seealso: `MatPartitioningType`, `MatPartitioning`, `MATPARTITIONINGCHACO`, `MatPartitioningChacoSetEigenTol()`, `MatPartitioningChacoSetEigenNumber()`,
404: `MatPartitioningChacoGetEigenSolver()`
405: @*/
406: PetscErrorCode MatPartitioningChacoSetEigenSolver(MatPartitioning part, MPChacoEigenType method)
407: {
408: PetscFunctionBegin;
411: PetscTryMethod(part, "MatPartitioningChacoSetEigenSolver_C", (MatPartitioning, MPChacoEigenType), (part, method));
412: PetscFunctionReturn(PETSC_SUCCESS);
413: }
415: static PetscErrorCode MatPartitioningChacoSetEigenSolver_Chaco(MatPartitioning part, MPChacoEigenType method)
416: {
417: MatPartitioning_Chaco *chaco = (MatPartitioning_Chaco *)part->data;
419: PetscFunctionBegin;
420: switch (method) {
421: case MP_CHACO_LANCZOS:
422: case MP_CHACO_RQI:
423: chaco->eigen_method = method;
424: break;
425: default:
426: SETERRQ(PETSC_COMM_SELF, PETSC_ERR_ARG_WRONG, "Chaco: Unknown or unsupported option");
427: }
428: PetscFunctionReturn(PETSC_SUCCESS);
429: }
431: /*@
432: MatPartitioningChacoGetEigenSolver - Get the eigensolver used by the Chaco partitioner.
434: Not Collective
436: Input Parameter:
437: . part - the partitioning context
439: Output Parameter:
440: . method - the method
442: Level: advanced
444: .seealso: `MatPartitioningType`, `MatPartitioning`, `MATPARTITIONINGCHACO`, `MatPartitioningChacoSetEigenSolver()`
445: @*/
446: PetscErrorCode MatPartitioningChacoGetEigenSolver(MatPartitioning part, MPChacoEigenType *method)
447: {
448: PetscFunctionBegin;
450: PetscAssertPointer(method, 2);
451: PetscUseMethod(part, "MatPartitioningChacoGetEigenSolver_C", (MatPartitioning, MPChacoEigenType *), (part, method));
452: PetscFunctionReturn(PETSC_SUCCESS);
453: }
455: static PetscErrorCode MatPartitioningChacoGetEigenSolver_Chaco(MatPartitioning part, MPChacoEigenType *method)
456: {
457: MatPartitioning_Chaco *chaco = (MatPartitioning_Chaco *)part->data;
459: PetscFunctionBegin;
460: *method = chaco->eigen_method;
461: PetscFunctionReturn(PETSC_SUCCESS);
462: }
464: /*@
465: MatPartitioningChacoSetEigenTol - Sets the tolerance for the eigensolver used by Chaco
467: Collective
469: Input Parameters:
470: + part - the partitioning context
471: - tol - the tolerance
473: Options Database Key:
474: . -mat_partitioning_chaco_eigen_tol tol - Tolerance for eigensolver
476: Note:
477: Must be positive. The default value is 0.001.
479: Level: advanced
481: .seealso: `MatPartitioningType`, `MatPartitioning`, `MATPARTITIONINGCHACO`, `MatPartitioningChacoSetEigenSolver()`, `MatPartitioningChacoGetEigenTol()`
482: @*/
483: PetscErrorCode MatPartitioningChacoSetEigenTol(MatPartitioning part, PetscReal tol)
484: {
485: PetscFunctionBegin;
488: PetscTryMethod(part, "MatPartitioningChacoSetEigenTol_C", (MatPartitioning, PetscReal), (part, tol));
489: PetscFunctionReturn(PETSC_SUCCESS);
490: }
492: static PetscErrorCode MatPartitioningChacoSetEigenTol_Chaco(MatPartitioning part, PetscReal tol)
493: {
494: MatPartitioning_Chaco *chaco = (MatPartitioning_Chaco *)part->data;
496: PetscFunctionBegin;
497: if (tol == PETSC_DEFAULT) chaco->eigtol = 0.001;
498: else {
499: PetscCheck(tol > 0.0, PetscObjectComm((PetscObject)part), PETSC_ERR_ARG_OUTOFRANGE, "Tolerance must be positive");
500: chaco->eigtol = tol;
501: }
502: PetscFunctionReturn(PETSC_SUCCESS);
503: }
505: /*@
506: MatPartitioningChacoGetEigenTol - Gets the eigensolver tolerance used by Chaco
508: Not Collective
510: Input Parameter:
511: . part - the partitioning context
513: Output Parameter:
514: . tol - the tolerance
516: Level: advanced
518: .seealso: `MatPartitioningType`, `MatPartitioning`, `MATPARTITIONINGCHACO`, `MatPartitioningChacoSetEigenTol()`
519: @*/
520: PetscErrorCode MatPartitioningChacoGetEigenTol(MatPartitioning part, PetscReal *tol)
521: {
522: PetscFunctionBegin;
524: PetscAssertPointer(tol, 2);
525: PetscUseMethod(part, "MatPartitioningChacoGetEigenTol_C", (MatPartitioning, PetscReal *), (part, tol));
526: PetscFunctionReturn(PETSC_SUCCESS);
527: }
529: static PetscErrorCode MatPartitioningChacoGetEigenTol_Chaco(MatPartitioning part, PetscReal *tol)
530: {
531: MatPartitioning_Chaco *chaco = (MatPartitioning_Chaco *)part->data;
533: PetscFunctionBegin;
534: *tol = chaco->eigtol;
535: PetscFunctionReturn(PETSC_SUCCESS);
536: }
538: /*@
539: MatPartitioningChacoSetEigenNumber - Sets the number of eigenvectors to compute by Chaco during partitioning
540: during partitioning.
542: Collective
544: Input Parameters:
545: + part - the partitioning context
546: - num - the number of eigenvectors
548: Options Database Key:
549: . -mat_partitioning_chaco_eigen_number n - Number of eigenvectors
551: Note:
552: Accepted values are 1, 2 or 3, indicating partitioning by bisection,
553: quadrisection, or octosection.
555: Level: advanced
557: .seealso: `MatPartitioningType`, `MatPartitioning`, `MATPARTITIONINGCHACO`, `MatPartitioningChacoSetEigenSolver()`, `MatPartitioningChacoGetEigenTol()`
558: @*/
559: PetscErrorCode MatPartitioningChacoSetEigenNumber(MatPartitioning part, PetscInt num)
560: {
561: PetscFunctionBegin;
564: PetscTryMethod(part, "MatPartitioningChacoSetEigenNumber_C", (MatPartitioning, PetscInt), (part, num));
565: PetscFunctionReturn(PETSC_SUCCESS);
566: }
568: static PetscErrorCode MatPartitioningChacoSetEigenNumber_Chaco(MatPartitioning part, PetscInt num)
569: {
570: MatPartitioning_Chaco *chaco = (MatPartitioning_Chaco *)part->data;
572: PetscFunctionBegin;
573: if (num == PETSC_DEFAULT) chaco->eignum = 1;
574: else {
575: PetscCheck(num >= 1 && num <= 3, PetscObjectComm((PetscObject)part), PETSC_ERR_ARG_OUTOFRANGE, "Can only specify 1, 2 or 3 eigenvectors");
576: chaco->eignum = num;
577: }
578: PetscFunctionReturn(PETSC_SUCCESS);
579: }
581: /*@
582: MatPartitioningChacoGetEigenNumber - Gets the number of eigenvectors used by Chaco.
584: Not Collective
586: Input Parameter:
587: . part - the partitioning context
589: Output Parameter:
590: . num - number of eigenvectors
592: Level: advanced
594: .seealso: `MatPartitioningType`, `MatPartitioning`, `MATPARTITIONINGCHACO`, `MatPartitioningChacoSetEigenNumber()`
595: @*/
596: PetscErrorCode MatPartitioningChacoGetEigenNumber(MatPartitioning part, PetscInt *num)
597: {
598: PetscFunctionBegin;
600: PetscAssertPointer(num, 2);
601: PetscUseMethod(part, "MatPartitioningChacoGetEigenNumber_C", (MatPartitioning, PetscInt *), (part, num));
602: PetscFunctionReturn(PETSC_SUCCESS);
603: }
605: static PetscErrorCode MatPartitioningChacoGetEigenNumber_Chaco(MatPartitioning part, PetscInt *num)
606: {
607: MatPartitioning_Chaco *chaco = (MatPartitioning_Chaco *)part->data;
609: PetscFunctionBegin;
610: *num = chaco->eignum;
611: PetscFunctionReturn(PETSC_SUCCESS);
612: }
614: static PetscErrorCode MatPartitioningSetFromOptions_Chaco(MatPartitioning part, PetscOptionItems PetscOptionsObject)
615: {
616: PetscInt i;
617: PetscReal r;
618: PetscBool flag;
619: MatPartitioning_Chaco *chaco = (MatPartitioning_Chaco *)part->data;
620: MPChacoGlobalType global;
621: MPChacoLocalType local;
622: MPChacoEigenType eigen;
624: PetscFunctionBegin;
625: PetscOptionsHeadBegin(PetscOptionsObject, "Chaco partitioning options");
626: PetscCall(PetscOptionsEnum("-mat_partitioning_chaco_global", "Global method", "MatPartitioningChacoSetGlobal", MPChacoGlobalTypes, (PetscEnum)chaco->global_method, (PetscEnum *)&global, &flag));
627: if (flag) PetscCall(MatPartitioningChacoSetGlobal(part, global));
628: PetscCall(PetscOptionsEnum("-mat_partitioning_chaco_local", "Local method", "MatPartitioningChacoSetLocal", MPChacoLocalTypes, (PetscEnum)chaco->local_method, (PetscEnum *)&local, &flag));
629: if (flag) PetscCall(MatPartitioningChacoSetLocal(part, local));
630: PetscCall(PetscOptionsReal("-mat_partitioning_chaco_coarse", "Coarse level", "MatPartitioningChacoSetCoarseLevel", 0.0, &r, &flag));
631: if (flag) PetscCall(MatPartitioningChacoSetCoarseLevel(part, r));
632: PetscCall(PetscOptionsEnum("-mat_partitioning_chaco_eigen_solver", "Eigensolver method", "MatPartitioningChacoSetEigenSolver", MPChacoEigenTypes, (PetscEnum)chaco->eigen_method, (PetscEnum *)&eigen, &flag));
633: if (flag) PetscCall(MatPartitioningChacoSetEigenSolver(part, eigen));
634: PetscCall(PetscOptionsReal("-mat_partitioning_chaco_eigen_tol", "Eigensolver tolerance", "MatPartitioningChacoSetEigenTol", chaco->eigtol, &r, &flag));
635: if (flag) PetscCall(MatPartitioningChacoSetEigenTol(part, r));
636: PetscCall(PetscOptionsInt("-mat_partitioning_chaco_eigen_number", "Number of eigenvectors: 1, 2, or 3 (bi-, quadri-, or octosection)", "MatPartitioningChacoSetEigenNumber", chaco->eignum, &i, &flag));
637: if (flag) PetscCall(MatPartitioningChacoSetEigenNumber(part, i));
638: PetscCall(PetscOptionsBool("-mat_partitioning_chaco_verbose", "Show library output", "", chaco->verbose, &chaco->verbose, NULL));
639: PetscOptionsHeadEnd();
640: PetscFunctionReturn(PETSC_SUCCESS);
641: }
643: static PetscErrorCode MatPartitioningDestroy_Chaco(MatPartitioning part)
644: {
645: MatPartitioning_Chaco *chaco = (MatPartitioning_Chaco *)part->data;
647: PetscFunctionBegin;
648: PetscCall(PetscFree(chaco));
649: /* clear composed functions */
650: PetscCall(PetscObjectComposeFunction((PetscObject)part, "MatPartitioningChacoSetGlobal_C", NULL));
651: PetscCall(PetscObjectComposeFunction((PetscObject)part, "MatPartitioningChacoGetGlobal_C", NULL));
652: PetscCall(PetscObjectComposeFunction((PetscObject)part, "MatPartitioningChacoSetLocal_C", NULL));
653: PetscCall(PetscObjectComposeFunction((PetscObject)part, "MatPartitioningChacoGetLocal_C", NULL));
654: PetscCall(PetscObjectComposeFunction((PetscObject)part, "MatPartitioningChacoSetCoarseLevel_C", NULL));
655: PetscCall(PetscObjectComposeFunction((PetscObject)part, "MatPartitioningChacoSetEigenSolver_C", NULL));
656: PetscCall(PetscObjectComposeFunction((PetscObject)part, "MatPartitioningChacoGetEigenSolver_C", NULL));
657: PetscCall(PetscObjectComposeFunction((PetscObject)part, "MatPartitioningChacoSetEigenTol_C", NULL));
658: PetscCall(PetscObjectComposeFunction((PetscObject)part, "MatPartitioningChacoGetEigenTol_C", NULL));
659: PetscCall(PetscObjectComposeFunction((PetscObject)part, "MatPartitioningChacoSetEigenNumber_C", NULL));
660: PetscCall(PetscObjectComposeFunction((PetscObject)part, "MatPartitioningChacoGetEigenNumber_C", NULL));
661: PetscFunctionReturn(PETSC_SUCCESS);
662: }
664: /*MC
665: MATPARTITIONINGCHACO - Creates a partitioning context that uses the external package Chaco {cite}`chaco95`
667: Level: beginner
669: Note:
670: Does not use the `MatPartitioningSetUseEdgeWeights()` option
672: .seealso: `MatPartitioning`, `MatPartitioningSetType()`, `MatPartitioningType`
673: M*/
675: PETSC_EXTERN PetscErrorCode MatPartitioningCreate_Chaco(MatPartitioning part)
676: {
677: MatPartitioning_Chaco *chaco;
679: PetscFunctionBegin;
680: PetscCall(PetscNew(&chaco));
681: part->data = (void *)chaco;
683: chaco->global_method = MP_CHACO_MULTILEVEL;
684: chaco->local_method = MP_CHACO_KERNIGHAN;
685: chaco->eigen_method = MP_CHACO_LANCZOS;
686: chaco->nbvtxcoarsed = 200;
687: chaco->eignum = 1;
688: chaco->eigtol = 0.001;
689: chaco->verbose = PETSC_FALSE;
691: part->ops->apply = MatPartitioningApply_Chaco;
692: part->ops->view = MatPartitioningView_Chaco;
693: part->ops->destroy = MatPartitioningDestroy_Chaco;
694: part->ops->setfromoptions = MatPartitioningSetFromOptions_Chaco;
696: PetscCall(PetscObjectComposeFunction((PetscObject)part, "MatPartitioningChacoSetGlobal_C", MatPartitioningChacoSetGlobal_Chaco));
697: PetscCall(PetscObjectComposeFunction((PetscObject)part, "MatPartitioningChacoGetGlobal_C", MatPartitioningChacoGetGlobal_Chaco));
698: PetscCall(PetscObjectComposeFunction((PetscObject)part, "MatPartitioningChacoSetLocal_C", MatPartitioningChacoSetLocal_Chaco));
699: PetscCall(PetscObjectComposeFunction((PetscObject)part, "MatPartitioningChacoGetLocal_C", MatPartitioningChacoGetLocal_Chaco));
700: PetscCall(PetscObjectComposeFunction((PetscObject)part, "MatPartitioningChacoSetCoarseLevel_C", MatPartitioningChacoSetCoarseLevel_Chaco));
701: PetscCall(PetscObjectComposeFunction((PetscObject)part, "MatPartitioningChacoSetEigenSolver_C", MatPartitioningChacoSetEigenSolver_Chaco));
702: PetscCall(PetscObjectComposeFunction((PetscObject)part, "MatPartitioningChacoGetEigenSolver_C", MatPartitioningChacoGetEigenSolver_Chaco));
703: PetscCall(PetscObjectComposeFunction((PetscObject)part, "MatPartitioningChacoSetEigenTol_C", MatPartitioningChacoSetEigenTol_Chaco));
704: PetscCall(PetscObjectComposeFunction((PetscObject)part, "MatPartitioningChacoGetEigenTol_C", MatPartitioningChacoGetEigenTol_Chaco));
705: PetscCall(PetscObjectComposeFunction((PetscObject)part, "MatPartitioningChacoSetEigenNumber_C", MatPartitioningChacoSetEigenNumber_Chaco));
706: PetscCall(PetscObjectComposeFunction((PetscObject)part, "MatPartitioningChacoGetEigenNumber_C", MatPartitioningChacoGetEigenNumber_Chaco));
707: PetscFunctionReturn(PETSC_SUCCESS);
708: }