Actual source code: chaco.c
1: #define PETSCMAT_DLL
3: #include src/mat/impls/adj/mpi/mpiadj.h
5: #ifdef PETSC_HAVE_UNISTD_H
6: #include <unistd.h>
7: #endif
9: #ifdef PETSC_HAVE_STDLIB_H
10: #include <stdlib.h>
11: #endif
13: #include "petscfix.h"
16: /* Chaco does not have an include file */
18: float *ewgts, float *x, float *y, float *z, char *outassignname,
19: char *outfilename, short *assignment, int architecture, int ndims_tot,
20: int mesh_dims[3], double *goal, int global_method, int local_method,
21: int rqi_flag, int vmax, int ndims, double eigtol, long seed);
25: /*
26: int nvtxs; number of vertices in full graph
27: int *start; start of edge list for each vertex
28: int *adjacency; edge list data
29: int *vwgts; weights for all vertices
30: float *ewgts; weights for all edges
31: float *x, *y, *z; coordinates for inertial method
32: char *outassignname; name of assignment output file
33: char *outfilename; output file name
34: short *assignment; set number of each vtx (length n)
35: int architecture; 0 => hypercube, d => d-dimensional mesh
36: int ndims_tot; total number of cube dimensions to divide
37: int mesh_dims[3]; dimensions of mesh of processors
38: double *goal; desired set sizes for each set
39: int global_method; global partitioning algorithm
40: int local_method; local partitioning algorithm
41: int rqi_flag; should I use RQI/Symmlq eigensolver?
42: int vmax; how many vertices to coarsen down to?
43: int ndims; number of eigenvectors (2^d sets)
44: double eigtol; tolerance on eigenvectors
45: long seed; for random graph mutations
46: */
50: typedef struct {
51: int architecture;
52: int ndims_tot;
53: int mesh_dims[3];
54: int rqi_flag;
55: int numbereigen;
56: double eigtol;
57: int global_method; /* global method */
58: int local_method; /* local method */
59: int nbvtxcoarsed; /* number of vertices for the coarse graph */
60: char *mesg_log;
61: } MatPartitioning_Chaco;
63: #define SIZE_LOG 10000 /* size of buffer for msg_log */
67: static PetscErrorCode MatPartitioningApply_Chaco(MatPartitioning part, IS *partitioning)
68: {
70: int *parttab, *locals, i, size, rank;
71: Mat mat = part->adj, matMPI, matSeq;
72: int nb_locals;
73: Mat_MPIAdj *adj;
74: MatPartitioning_Chaco *chaco = (MatPartitioning_Chaco *) part->data;
75: PetscTruth flg;
76: #ifdef PETSC_HAVE_UNISTD_H
77: int fd_stdout, fd_pipe[2], count;
78: #endif
82: FREE_GRAPH = 0; /* otherwise Chaco will attempt to free memory for adjacency graph */
83:
84: MPI_Comm_size(mat->comm, &size);
86: PetscTypeCompare((PetscObject) mat, MATMPIADJ, &flg);
88: /* check if the matrix is sequential, use MatGetSubMatrices if necessary */
89: if (size > 1) {
90: int M, N;
91: IS isrow, iscol;
92: Mat *A;
94: if (flg) {
95: SETERRQ(0, "Distributed matrix format MPIAdj is not supported for sequential partitioners");
96: }
97: PetscPrintf(part->comm, "Converting distributed matrix to sequential: this could be a performance loss\n");
99: MatGetSize(mat, &M, &N);
100: ISCreateStride(PETSC_COMM_SELF, M, 0, 1, &isrow);
101: ISCreateStride(PETSC_COMM_SELF, N, 0, 1, &iscol);
102: MatGetSubMatrices(mat, 1, &isrow, &iscol, MAT_INITIAL_MATRIX, &A);
103: ISDestroy(isrow);
104: ISDestroy(iscol);
105: matSeq = *A;
106: PetscFree(A);
107: } else
108: matSeq = mat;
110: /* check for the input format that is supported only for a MPIADJ type
111: and set it to matMPI */
112: if (!flg) {
113: MatConvert(matSeq, MATMPIADJ, MAT_INITIAL_MATRIX, &matMPI);
114: } else
115: matMPI = matSeq;
117: adj = (Mat_MPIAdj *) matMPI->data; /* finaly adj contains adjacency graph */
119: {
120: /* arguments for Chaco library */
121: int nvtxs = mat->rmap.N; /* number of vertices in full graph */
122: int *start = adj->i; /* start of edge list for each vertex */
123: int *adjacency; /* = adj -> j; edge list data */
124: int *vwgts = NULL; /* weights for all vertices */
125: float *ewgts = NULL; /* weights for all edges */
126: float *x = NULL, *y = NULL, *z = NULL; /* coordinates for inertial method */
127: char *outassignname = NULL; /* name of assignment output file */
128: char *outfilename = NULL; /* output file name */
129: short *assignment; /* set number of each vtx (length n) */
130: int architecture = chaco->architecture; /* 0 => hypercube, d => d-dimensional mesh */
131: int ndims_tot = chaco->ndims_tot; /* total number of cube dimensions to divide */
132: int *mesh_dims = chaco->mesh_dims; /* dimensions of mesh of processors */
133: double *goal = NULL; /* desired set sizes for each set */
134: int global_method = chaco->global_method; /* global partitioning algorithm */
135: int local_method = chaco->local_method; /* local partitioning algorithm */
136: int rqi_flag = chaco->rqi_flag; /* should I use RQI/Symmlq eigensolver? */
137: int vmax = chaco->nbvtxcoarsed; /* how many vertices to coarsen down to? */
138: int ndims = chaco->numbereigen; /* number of eigenvectors (2^d sets) */
139: double eigtol = chaco->eigtol; /* tolerance on eigenvectors */
140: long seed = 123636512; /* for random graph mutations */
142: /* return value of Chaco */
143: PetscMalloc((mat->rmap.N) * sizeof(short), &assignment);
144:
145: /* index change for libraries that have fortran implementation */
146: PetscMalloc(sizeof(int) * start[nvtxs], &adjacency);
147: for (i = 0; i < start[nvtxs]; i++)
148: adjacency[i] = (adj->j)[i] + 1;
150: /* redirect output to buffer: chaco -> mesg_log */
151: #ifdef PETSC_HAVE_UNISTD_H
152: fd_stdout = dup(1);
153: pipe(fd_pipe);
154: close(1);
155: dup2(fd_pipe[1], 1);
156: PetscMalloc(SIZE_LOG * sizeof(char), &(chaco->mesg_log));
157: #endif
159: /* library call */
160: interface(nvtxs, start, adjacency, vwgts, ewgts, x, y, z,
161: outassignname, outfilename, assignment, architecture, ndims_tot,
162: mesh_dims, goal, global_method, local_method, rqi_flag, vmax, ndims,
163: eigtol, seed);
165: #ifdef PETSC_HAVE_UNISTD_H
166: fflush(stdout);
167: count = read(fd_pipe[0], chaco->mesg_log, (SIZE_LOG - 1) * sizeof(char));
168: if (count < 0)
169: count = 0;
170: chaco->mesg_log[count] = 0;
171: close(1);
172: dup2(fd_stdout, 1);
173: close(fd_stdout);
174: close(fd_pipe[0]);
175: close(fd_pipe[1]);
176: #endif
178: if (ierr) { SETERRQ(PETSC_ERR_LIB, chaco->mesg_log); }
180: PetscFree(adjacency);
182: PetscMalloc((mat->rmap.N) * sizeof(int), &parttab);
183: for (i = 0; i < nvtxs; i++) {
184: parttab[i] = assignment[i];
185: }
186: PetscFree(assignment);
187: }
189: /* Creation of the index set */
190: MPI_Comm_rank(part->comm, &rank);
191: MPI_Comm_size(part->comm, &size);
192: nb_locals = mat->rmap.N / size;
193: locals = parttab + rank * nb_locals;
194: if (rank < mat->rmap.N % size) {
195: nb_locals++;
196: locals += rank;
197: } else
198: locals += mat->rmap.N % size;
199: ISCreateGeneral(part->comm, nb_locals, locals, partitioning);
201: /* destroy temporary objects */
202: PetscFree(parttab);
203: if (matSeq != mat) {
204: MatDestroy(matSeq);
205: }
206: if (matMPI != mat) {
207: MatDestroy(matMPI);
208: }
209: return(0);
210: }
215: PetscErrorCode MatPartitioningView_Chaco(MatPartitioning part, PetscViewer viewer)
216: {
218: MatPartitioning_Chaco *chaco = (MatPartitioning_Chaco *) part->data;
219: PetscErrorCode ierr;
220: PetscMPIInt rank;
221: PetscTruth iascii;
225: MPI_Comm_rank(part->comm, &rank);
226: PetscTypeCompare((PetscObject) viewer, PETSC_VIEWER_ASCII, &iascii);
227: if (iascii) {
228: if (!rank && chaco->mesg_log) {
229: PetscViewerASCIIPrintf(viewer, "%s\n", chaco->mesg_log);
230: }
231: } else {
232: SETERRQ1(PETSC_ERR_SUP,"Viewer type %s not supported for this Chaco partitioner",((PetscObject) viewer)->type_name);
233: }
235: return(0);
236: }
240: /*@
241: MatPartitioningChacoSetGlobal - Set method for global partitioning.
243: Input Parameter:
244: . part - the partitioning context
245: . method - MP_CHACO_MULTILEVEL_KL, MP_CHACO_SPECTRAL, MP_CHACO_LINEAR,
246: MP_CHACO_RANDOM or MP_CHACO_SCATTERED
248: Level: advanced
250: @*/
251: PetscErrorCode MatPartitioningChacoSetGlobal(MatPartitioning part, MPChacoGlobalType method)
252: {
253: MatPartitioning_Chaco *chaco = (MatPartitioning_Chaco *) part->data;
257: switch (method) {
258: case MP_CHACO_MULTILEVEL_KL:
259: chaco->global_method = 1;
260: break;
261: case MP_CHACO_SPECTRAL:
262: chaco->global_method = 2;
263: break;
264: case MP_CHACO_LINEAR:
265: chaco->global_method = 4;
266: break;
267: case MP_CHACO_RANDOM:
268: chaco->global_method = 5;
269: break;
270: case MP_CHACO_SCATTERED:
271: chaco->global_method = 6;
272: break;
273: default:
274: SETERRQ(PETSC_ERR_SUP, "Chaco: Unknown or unsupported option");
275: }
276: return(0);
277: }
281: /*@
282: MatPartitioningChacoSetLocal - Set method for local partitioning.
284: Input Parameter:
285: . part - the partitioning context
286: . method - MP_CHACO_KERNIGHAN_LIN or MP_CHACO_NONE
288: Level: advanced
290: @*/
291: PetscErrorCode MatPartitioningChacoSetLocal(MatPartitioning part, MPChacoLocalType method)
292: {
293: MatPartitioning_Chaco *chaco = (MatPartitioning_Chaco *) part->data;
297: switch (method) {
298: case MP_CHACO_KERNIGHAN_LIN:
299: chaco->local_method = 1;
300: break;
301: case MP_CHACO_NONE:
302: chaco->local_method = 2;
303: break;
304: default:
305: SETERRQ(PETSC_ERR_ARG_CORRUPT, "Chaco: Unknown or unsupported option");
306: }
308: return(0);
309: }
313: /*@
314: MatPartitioningChacoSetCoarseLevel - Set the coarse level
315:
316: Input Parameter:
317: . part - the partitioning context
318: . level - the coarse level in range [0.0,1.0]
320: Level: advanced
322: @*/
323: PetscErrorCode MatPartitioningChacoSetCoarseLevel(MatPartitioning part, PetscReal level)
324: {
325: MatPartitioning_Chaco *chaco = (MatPartitioning_Chaco *) part->data;
329: if (level < 0 || level > 1.0) {
330: SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,
331: "Chaco: level of coarsening out of range [0.01-1.0]");
332: } else
333: chaco->nbvtxcoarsed = (int)(part->adj->cmap.N * level);
335: if (chaco->nbvtxcoarsed < 20)
336: chaco->nbvtxcoarsed = 20;
338: return(0);
339: }
343: /*@
344: MatPartitioningChacoSetEigenSolver - Set method for eigensolver.
346: Input Parameter:
347: . method - MP_CHACO_LANCZOS or MP_CHACO_RQI_SYMMLQ
349: Level: advanced
351: @*/
352: PetscErrorCode MatPartitioningChacoSetEigenSolver(MatPartitioning part,
353: MPChacoEigenType method)
354: {
355: MatPartitioning_Chaco *chaco = (MatPartitioning_Chaco *) part->data;
359: switch (method) {
360: case MP_CHACO_LANCZOS:
361: chaco->rqi_flag = 0;
362: break;
363: case MP_CHACO_RQI_SYMMLQ:
364: chaco->rqi_flag = 1;
365: break;
366: default:
367: SETERRQ(PETSC_ERR_ARG_CORRUPT, "Chaco: Unknown or unsupported option");
368: }
370: return(0);
371: }
375: /*@
376: MatPartitioningChacoSetEigenTol - Set tolerance for eigensolver.
378: Input Parameter:
379: . tol - Tolerance requested.
381: Level: advanced
383: @*/
384: PetscErrorCode MatPartitioningChacoSetEigenTol(MatPartitioning part, PetscReal tol)
385: {
386: MatPartitioning_Chaco *chaco = (MatPartitioning_Chaco *) part->data;
390: if (tol <= 0.0) {
391: SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,
392: "Chaco: Eigensolver tolerance out of range");
393: } else
394: chaco->eigtol = tol;
396: return(0);
397: }
401: /*@
402: MatPartitioningChacoSetEigenNumber - Set number of eigenvectors for partitioning.
404: Input Parameter:
405: . num - This argument should have a value of 1, 2 or 3 indicating
406: partitioning by bisection, quadrisection, or octosection.
408: Level: advanced
410: @*/
411: PetscErrorCode MatPartitioningChacoSetEigenNumber(MatPartitioning part, int num)
412: {
413: MatPartitioning_Chaco *chaco = (MatPartitioning_Chaco *) part->data;
417: if (num > 3 || num < 1) {
418: SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,
419: "Chaco: number of eigenvectors out of range");
420: } else
421: chaco->numbereigen = num;
423: return(0);
424: }
428: PetscErrorCode MatPartitioningSetFromOptions_Chaco(MatPartitioning part)
429: {
431: int i;
432: PetscReal r;
433: PetscTruth flag;
434: const char *global[] =
435: { "multilevel-kl", "spectral", "linear", "random", "scattered" };
436: const char *local[] = { "kernighan-lin", "none" };
437: const char *eigen[] = { "lanczos", "rqi_symmlq" };
440: PetscOptionsHead("Set Chaco partitioning options");
442: PetscOptionsEList("-mat_partitioning_chaco_global",
443: "Global method to use", "MatPartitioningChacoSetGlobal", global, 5,
444: global[0], &i, &flag);
445: if (flag)
446: MatPartitioningChacoSetGlobal(part, (MPChacoGlobalType)i);
448: PetscOptionsEList("-mat_partitioning_chaco_local",
449: "Local method to use", "MatPartitioningChacoSetLocal", local, 2,
450: local[0], &i, &flag);
451: if (flag)
452: MatPartitioningChacoSetLocal(part, (MPChacoLocalType)i);
454: PetscOptionsReal("-mat_partitioning_chaco_coarse_level",
455: "Coarse level", "MatPartitioningChacoSetCoarseLevel", 0, &r,
456: &flag);
457: if (flag)
458: MatPartitioningChacoSetCoarseLevel(part, r);
460: PetscOptionsEList("-mat_partitioning_chaco_eigen_solver",
461: "Eigensolver to use in spectral method", "MatPartitioningChacoSetEigenSolver",
462: eigen, 2, eigen[0], &i, &flag);
463: if (flag)
464: MatPartitioningChacoSetEigenSolver(part, (MPChacoEigenType)i);
466: PetscOptionsReal("-mat_partitioning_chaco_eigen_tol",
467: "Tolerance for eigensolver", "MatPartitioningChacoSetEigenTol", 0.001,
468: &r, &flag);
469: if (flag)
470: MatPartitioningChacoSetEigenTol(part, r);
472: PetscOptionsInt("-mat_partitioning_chaco_eigen_number",
473: "Number of eigenvectors: 1, 2, or 3 (bi-, quadri-, or octosection)",
474: "MatPartitioningChacoSetEigenNumber", 1, &i, &flag);
475: if (flag)
476: MatPartitioningChacoSetEigenNumber(part, i);
478: PetscOptionsTail();
479: return(0);
480: }
485: PetscErrorCode MatPartitioningDestroy_Chaco(MatPartitioning part)
486: {
487: MatPartitioning_Chaco *chaco = (MatPartitioning_Chaco *) part->data;
488: PetscErrorCode ierr;
491: PetscFree(chaco->mesg_log);
492: PetscFree(chaco);
493: return(0);
494: }
499: /*@C
500: MAT_PARTITIONING_Chaco - Creates a partitioning context via the external package Chaco.
502: Collective on MPI_Comm
504: Input Parameter:
505: . part - the partitioning context
507: Options Database Keys:
508: + -mat_partitioning_chaco_global <multilevel-kl> (one of) multilevel-kl spectral linear random scattered
509: . -mat_partitioning_chaco_local <kernighan-lin> (one of) kernighan-lin none
510: . -mat_partitioning_chaco_coarse_level <0>: Coarse level (MatPartitioningChacoSetCoarseLevel)
511: . -mat_partitioning_chaco_eigen_solver <lanczos> (one of) lanczos rqi_symmlq
512: . -mat_partitioning_chaco_eigen_tol <0.001>: Tolerance for eigensolver (MatPartitioningChacoSetEigenTol)
513: - -mat_partitioning_chaco_eigen_number <1>: Number of eigenvectors: 1, 2, or 3 (bi-, quadri-, or octosection) (MatPartitioningChacoSetEigenNumber)
515: Level: beginner
517: Notes: See http://www.cs.sandia.gov/CRF/chac.html
519: .keywords: Partitioning, create, context
521: .seealso: MatPartitioningSetType(), MatPartitioningType
523: @*/
524: PetscErrorCode MatPartitioningCreate_Chaco(MatPartitioning part)
525: {
527: MatPartitioning_Chaco *chaco;
530: PetscNew(MatPartitioning_Chaco, &chaco);
532: chaco->architecture = 1;
533: chaco->ndims_tot = 0;
534: chaco->mesh_dims[0] = part->n;
535: chaco->global_method = 1;
536: chaco->local_method = 1;
537: chaco->rqi_flag = 0;
538: chaco->nbvtxcoarsed = 200;
539: chaco->numbereigen = 1;
540: chaco->eigtol = 0.001;
541: chaco->mesg_log = NULL;
543: part->ops->apply = MatPartitioningApply_Chaco;
544: part->ops->view = MatPartitioningView_Chaco;
545: part->ops->destroy = MatPartitioningDestroy_Chaco;
546: part->ops->setfromoptions = MatPartitioningSetFromOptions_Chaco;
547: part->data = (void*) chaco;
549: return(0);
550: }