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symrcm.cc
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25 
26 /*
27 An implementation of the Reverse Cuthill-McKee algorithm (symrcm)
28 
29 The implementation of this algorithm is based in the descriptions found in
30 
31 @INPROCEEDINGS{,
32  author = {E. Cuthill and J. McKee},
33  title = {Reducing the Bandwidth of Sparse Symmetric Matrices},
34  booktitle = {Proceedings of the 24th ACM National Conference},
35  publisher = {Brandon Press},
36  pages = {157 -- 172},
37  location = {New Jersey},
38  year = {1969}
39 }
40 
41 @BOOK{,
42  author = {Alan George and Joseph W. H. Liu},
43  title = {Computer Solution of Large Sparse Positive Definite Systems},
44  publisher = {Prentice Hall Series in Computational Mathematics},
45  ISBN = {0-13-165274-5},
46  year = {1981}
47 }
48 
49 The algorithm represents a heuristic approach to the NP-complete minimum
50 bandwidth problem.
51 
52 Written by Michael Weitzel <michael.weitzel@@uni-siegen.de>
53  <weitzel@@ldknet.org>
54 */
55 
56 #if defined (HAVE_CONFIG_H)
57 # include "config.h"
58 #endif
59 
60 #include <algorithm>
61 
62 #include "CSparse.h"
63 #include "boolNDArray.h"
64 #include "dNDArray.h"
65 #include "dSparse.h"
66 #include "oct-locbuf.h"
67 #include "oct-sparse.h"
68 #include "quit.h"
69 
70 #include "defun.h"
71 #include "errwarn.h"
72 #include "ov.h"
73 #include "ovl.h"
74 
76 
77 // A node struct for the Cuthill-McKee algorithm
78 struct CMK_Node
79 {
80  // the node's id (matrix row index)
81  octave_idx_type id;
82  // the node's degree
83  octave_idx_type deg;
84  // minimal distance to the root of the spanning tree
85  octave_idx_type dist;
86 };
87 
88 // A simple queue.
89 // Queues Q have a fixed maximum size N (rows,cols of the matrix) and are
90 // stored in an array. qh and qt point to queue head and tail.
91 
92 // Enqueue operation (adds a node "o" at the tail)
93 
94 inline static void
95 Q_enq (CMK_Node *Q, octave_idx_type N, octave_idx_type& qt, const CMK_Node& o)
96 {
97  Q[qt] = o;
98  qt = (qt + 1) % (N + 1);
99 }
100 
101 // Dequeue operation (removes a node from the head)
102 
103 inline static CMK_Node
104 Q_deq (CMK_Node *Q, octave_idx_type N, octave_idx_type& qh)
105 {
106  CMK_Node r = Q[qh];
107  qh = (qh + 1) % (N + 1);
108  return r;
109 }
110 
111 // Predicate (queue empty)
112 #define Q_empty(Q, N, qh, qt) ((qh) == (qt))
113 
114 // A simple, array-based binary heap (used as a priority queue for nodes)
115 
116 // the left descendant of entry i
117 #define LEFT(i) (((i) << 1) + 1) // = (2*(i)+1)
118  // the right descendant of entry i
119 #define RIGHT(i) (((i) << 1) + 2) // = (2*(i)+2)
120  // the parent of entry i
121 #define PARENT(i) (((i) - 1) >> 1) // = floor(((i)-1)/2)
122 
123 // Builds a min-heap (the root contains the smallest element). A is an array
124 // with the graph's nodes, i is a starting position, size is the length of A.
125 
126 static void
127 H_heapify_min (CMK_Node *A, octave_idx_type i, octave_idx_type size)
128 {
129  octave_idx_type j = i;
130  for (;;)
131  {
132  octave_idx_type l = LEFT(j);
133  octave_idx_type r = RIGHT(j);
134 
135  octave_idx_type smallest;
136  if (l < size && A[l].deg < A[j].deg)
137  smallest = l;
138  else
139  smallest = j;
140 
141  if (r < size && A[r].deg < A[smallest].deg)
142  smallest = r;
143 
144  if (smallest != j)
145  {
146  std::swap (A[j], A[smallest]);
147  j = smallest;
148  }
149  else
150  break;
151  }
152 }
153 
154 // Heap operation insert. Running time is O(log(n))
155 
156 static void
157 H_insert (CMK_Node *H, octave_idx_type& h, const CMK_Node& o)
158 {
159  octave_idx_type i = h++;
160 
161  H[i] = o;
162 
163  if (i == 0)
164  return;
165  do
166  {
167  octave_idx_type p = PARENT(i);
168  if (H[i].deg < H[p].deg)
169  {
170  std::swap (H[i], H[p]);
171 
172  i = p;
173  }
174  else
175  break;
176  }
177  while (i > 0);
178 }
179 
180 // Heap operation remove-min. Removes the smallest element in O(1) and
181 // reorganizes the heap optionally in O(log(n))
182 
183 inline static CMK_Node
184 H_remove_min (CMK_Node *H, octave_idx_type& h, int reorg/*=1*/)
185 {
186  CMK_Node r = H[0];
187  H[0] = H[--h];
188  if (reorg)
189  H_heapify_min (H, 0, h);
190  return r;
191 }
192 
193 // Predicate (heap empty)
194 #define H_empty(H, h) ((h) == 0)
195 
196 // Helper function for the Cuthill-McKee algorithm. Tries to determine a
197 // pseudo-peripheral node of the graph as starting node.
198 
199 static octave_idx_type
200 find_starting_node (octave_idx_type N, const octave_idx_type *ridx,
201  const octave_idx_type *cidx, const octave_idx_type *ridx2,
202  const octave_idx_type *cidx2, octave_idx_type *D,
203  octave_idx_type start)
204 {
205  CMK_Node w;
206 
207  OCTAVE_LOCAL_BUFFER (CMK_Node, Q, N+1);
208  boolNDArray btmp (dim_vector (1, N), false);
209  bool *visit = btmp.fortran_vec ();
210 
211  octave_idx_type qh = 0;
212  octave_idx_type qt = 0;
213  CMK_Node x;
214  x.id = start;
215  x.deg = D[start];
216  x.dist = 0;
217  Q_enq (Q, N, qt, x);
218  visit[start] = true;
219 
220  // distance level
221  octave_idx_type level = 0;
222  // current largest "eccentricity"
223  octave_idx_type max_dist = 0;
224 
225  for (;;)
226  {
227  while (! Q_empty (Q, N, qh, qt))
228  {
229  CMK_Node v = Q_deq (Q, N, qh);
230 
231  if (v.dist > x.dist || (v.id != x.id && v.deg > x.deg))
232  x = v;
233 
234  octave_idx_type i = v.id;
235 
236  // add all unvisited neighbors to the queue
237  octave_idx_type j1 = cidx[i];
238  octave_idx_type j2 = cidx2[i];
239  while (j1 < cidx[i+1] || j2 < cidx2[i+1])
240  {
241  if (j1 == cidx[i+1])
242  {
243  octave_idx_type r2 = ridx2[j2++];
244  if (! visit[r2])
245  {
246  // the distance of node j is dist(i)+1
247  w.id = r2;
248  w.deg = D[r2];
249  w.dist = v.dist+1;
250  Q_enq (Q, N, qt, w);
251  visit[r2] = true;
252 
253  if (w.dist > level)
254  level = w.dist;
255  }
256  }
257  else if (j2 == cidx2[i+1])
258  {
259  octave_idx_type r1 = ridx[j1++];
260  if (! visit[r1])
261  {
262  // the distance of node j is dist(i)+1
263  w.id = r1;
264  w.deg = D[r1];
265  w.dist = v.dist+1;
266  Q_enq (Q, N, qt, w);
267  visit[r1] = true;
268 
269  if (w.dist > level)
270  level = w.dist;
271  }
272  }
273  else
274  {
275  octave_idx_type r1 = ridx[j1];
276  octave_idx_type r2 = ridx2[j2];
277  if (r1 <= r2)
278  {
279  if (! visit[r1])
280  {
281  w.id = r1;
282  w.deg = D[r1];
283  w.dist = v.dist+1;
284  Q_enq (Q, N, qt, w);
285  visit[r1] = true;
286 
287  if (w.dist > level)
288  level = w.dist;
289  }
290  j1++;
291  if (r1 == r2)
292  j2++;
293  }
294  else
295  {
296  if (! visit[r2])
297  {
298  w.id = r2;
299  w.deg = D[r2];
300  w.dist = v.dist+1;
301  Q_enq (Q, N, qt, w);
302  visit[r2] = true;
303 
304  if (w.dist > level)
305  level = w.dist;
306  }
307  j2++;
308  }
309  }
310  }
311  } // finish of BFS
312 
313  if (max_dist < x.dist)
314  {
315  max_dist = x.dist;
316 
317  for (octave_idx_type i = 0; i < N; i++)
318  visit[i] = false;
319 
320  visit[x.id] = true;
321  x.dist = 0;
322  qt = qh = 0;
323  Q_enq (Q, N, qt, x);
324  }
325  else
326  break;
327  }
328  return x.id;
329 }
330 
331 // Calculates the node's degrees. This means counting the nonzero elements
332 // in the symmetric matrix' rows. This works for non-symmetric matrices
333 // as well.
334 
335 static octave_idx_type
336 calc_degrees (octave_idx_type N, octave_idx_type *cidx, octave_idx_type *ridx,
338 {
339  octave_idx_type max_deg = 0;
340  for (octave_idx_type i = 0; i < N; i++)
341  D[i] = 0;
342 
343  for (octave_idx_type j = 0; j < N; j++)
344  for (octave_idx_type i = cidx[j]; i < cidx[j+1]; i++)
345  D[ridx[i]]++;
346 
347  for (octave_idx_type j = 0; j < N; j++)
348  for (octave_idx_type i = cidx2[j]; i < cidx2[j+1]; i++)
349  D[ridx2[i]]++;
350 
351  for (octave_idx_type i = 0; i < N; i++)
352  if (D[i] > max_deg)
353  max_deg = D[i];
354 
355  return max_deg;
356 }
357 
358 // Transpose of the structure of a square sparse matrix
359 
360 static void
361 transpose (octave_idx_type N, const octave_idx_type *ridx,
362  const octave_idx_type *cidx, octave_idx_type *ridx2,
363  octave_idx_type *cidx2)
364 {
365  octave_idx_type nz = cidx[N];
366 
368  for (octave_idx_type i = 0; i < N; i++)
369  w[i] = 0;
370  for (octave_idx_type i = 0; i < nz; i++)
371  w[ridx[i]]++;
372  nz = 0;
373  for (octave_idx_type i = 0; i < N; i++)
374  {
375  cidx2[i] = nz;
376  nz += w[i];
377  w[i] = cidx2[i];
378  }
379  cidx2[N] = nz;
380  w[N] = nz;
381 
382  for (octave_idx_type j = 0; j < N; j++)
383  for (octave_idx_type k = cidx[j]; k < cidx[j + 1]; k++)
384  {
385  octave_idx_type q = w[ridx[k]]++;
386  ridx2[q] = j;
387  }
388 }
389 
390 // An implementation of the Cuthill-McKee algorithm.
391 DEFUN (symrcm, args, ,
392  doc: /* -*- texinfo -*-
393 @deftypefn {} {@var{p} =} symrcm (@var{S})
394 Return the symmetric reverse @nospell{Cuthill-McKee} permutation of @var{S}.
395 
396 @var{p} is a permutation vector such that
397 @code{@var{S}(@var{p}, @var{p})} tends to have its diagonal elements closer
398 to the diagonal than @var{S}. This is a good preordering for LU or
399 Cholesky@tie{}factorization of matrices that come from ``long, skinny''
400 problems. It works for both symmetric and asymmetric @var{S}.
401 
402 The algorithm represents a heuristic approach to the NP-complete bandwidth
403 minimization problem. The implementation is based in the descriptions found
404 in
405 
406 @nospell{E. Cuthill, J. McKee}.
407 @cite{Reducing the Bandwidth of Sparse Symmetric Matrices}.
408 Proceedings of the 24th @nospell{ACM} National Conference,
409 157--172 1969, Brandon Press, New Jersey.
410 
411 @nospell{A. George, J.W.H. Liu}. @cite{Computer Solution of Large Sparse
412 Positive Definite Systems}, Prentice Hall Series in Computational
413 Mathematics, ISBN 0-13-165274-5, 1981.
414 
415 @seealso{colperm, colamd, symamd}
416 @end deftypefn */)
417 {
418  if (args.length () != 1)
419  print_usage ();
420 
421  octave_value arg = args(0);
422 
423  octave_idx_type nr = arg.rows ();
424  octave_idx_type nc = arg.columns ();
425 
426  if (nr != nc)
427  err_square_matrix_required ("symrcm", "S");
428 
429  if (nr == 0 && nc == 0)
430  return ovl (NDArray (dim_vector (1, 0)));
431 
432  // dimension of the matrix
433  octave_idx_type N = nr;
434 
435  // the parameter of the matrix is converted into a sparse matrix
436  //(if necessary)
437  SparseMatrix Ar;
438 
439  octave_quit ();
440 
441  if (arg.isreal ())
442  {
443  Ar = arg.sparse_matrix_value ();
444  }
445  else
446  {
448  Ar = max (max (real (Ac), -real (Ac)), max (imag (Ac), -imag (Ac)));
449  }
450 
451  octave_quit ();
452 
453  // Note cidx/ridx are const, so use xridx and xcidx...
454  octave_idx_type *cidx = Ar.xcidx ();
455  octave_idx_type *ridx = Ar.xridx ();
456 
457  // transpose
458  OCTAVE_LOCAL_BUFFER (octave_idx_type, cidx2, N + 1);
459  OCTAVE_LOCAL_BUFFER (octave_idx_type, ridx2, cidx[N]);
460  transpose (N, ridx, cidx, ridx2, cidx2);
461 
462  octave_quit ();
463 
464  // vertex degrees
466  octave_idx_type max_deg = calc_degrees (N, cidx, ridx, cidx2, ridx2, D);
467 
468  octave_quit ();
469 
470  // the permutation vector
471  NDArray P (dim_vector (1, N));
472 
473  // if none of the nodes has a degree > 0 (a matrix of zeros)
474  // the return value corresponds to the identity permutation
475  if (max_deg == 0)
476  {
477  for (octave_idx_type i = 0; i < N; i++)
478  P(i) = i+1; // +1 to convert from base-0 to base-1
479 
480  return ovl (P);
481  }
482 
483  // At this point, all early returns have completed.
484  // Proceed to BFS.
485 
486  // sizes of the heaps
487  octave_idx_type s = 0;
488 
489  // head- and tail-indices for the queue
490  octave_idx_type qt = 0;
491  octave_idx_type qh = 0;
492  CMK_Node v, w;
493 
494  // a heap for the a node's neighbors. The number of neighbors is
495  // limited by the maximum degree max_deg:
496  OCTAVE_LOCAL_BUFFER (CMK_Node, S, max_deg);
497 
498  // a queue for the BFS. The array is always one element larger than
499  // the number of entries that are stored.
500  OCTAVE_LOCAL_BUFFER (CMK_Node, Q, N+1);
501 
502  // a counter (for building the permutation)
503  octave_idx_type c = -1;
504 
505  // upper bound for the bandwidth (=quality of solution)
506  // initialize the bandwidth of the graph with 0. B contains the
507  // the maximum of the theoretical lower limits of the subgraphs
508  // bandwidths.
509  octave_idx_type B = 0;
510 
511  // mark all nodes as unvisited; with the exception of the nodes
512  // that have degree==0 and build a CC of the graph.
513 
514  boolNDArray btmp (dim_vector (1, N), false);
515  bool *visit = btmp.fortran_vec ();
516 
517  octave_quit ();
518 
519  do
520  {
521  // locate an unvisited starting node of the graph
522  octave_idx_type i;
523  for (i = 0; i < N; i++)
524  if (! visit[i])
525  break;
526 
527  // locate a probably better starting node
528  v.id = find_starting_node (N, ridx, cidx, ridx2, cidx2, D, i);
529 
530  // mark the node as visited and enqueue it (a starting node
531  // for the BFS). Since the node will be a root of a spanning
532  // tree, its dist is 0.
533  v.deg = D[v.id];
534  v.dist = 0;
535  visit[v.id] = true;
536  Q_enq (Q, N, qt, v);
537 
538  // lower bound for the bandwidth of a subgraph
539  // keep a "level" in the spanning tree (= min. distance to the
540  // root) for determining the bandwidth of the computed
541  // permutation P
542  octave_idx_type Bsub = 0;
543  // min. dist. to the root is 0
544  octave_idx_type level = 0;
545  // the root is the first/only node on level 0
546  octave_idx_type level_N = 1;
547 
548  while (! Q_empty (Q, N, qh, qt))
549  {
550  v = Q_deq (Q, N, qh);
551  i = v.id;
552 
553  c++;
554 
555  // for computing the inverse permutation P where
556  // A(inv(P),inv(P)) or P'*A*P is banded
557  // P(i) = c;
558 
559  // for computing permutation P where
560  // A(P(i),P(j)) or P*A*P' is banded
561  P(c) = i;
562 
563  // put all unvisited neighbors j of node i on the heap
564  s = 0;
565  octave_idx_type j1 = cidx[i];
566  octave_idx_type j2 = cidx2[i];
567 
568  while (j1 < cidx[i+1] || j2 < cidx2[i+1])
569  {
570  if (j1 == cidx[i+1])
571  {
572  octave_idx_type r2 = ridx2[j2++];
573  if (! visit[r2])
574  {
575  // the distance of node j is dist(i)+1
576  w.id = r2;
577  w.deg = D[r2];
578  w.dist = v.dist+1;
579  H_insert (S, s, w);
580  visit[r2] = true;
581  }
582  }
583  else if (j2 == cidx2[i+1])
584  {
585  octave_idx_type r1 = ridx[j1++];
586  if (! visit[r1])
587  {
588  w.id = r1;
589  w.deg = D[r1];
590  w.dist = v.dist+1;
591  H_insert (S, s, w);
592  visit[r1] = true;
593  }
594  }
595  else
596  {
597  octave_idx_type r1 = ridx[j1];
598  octave_idx_type r2 = ridx2[j2];
599  if (r1 <= r2)
600  {
601  if (! visit[r1])
602  {
603  w.id = r1;
604  w.deg = D[r1];
605  w.dist = v.dist+1;
606  H_insert (S, s, w);
607  visit[r1] = true;
608  }
609  j1++;
610  if (r1 == r2)
611  j2++;
612  }
613  else
614  {
615  if (! visit[r2])
616  {
617  w.id = r2;
618  w.deg = D[r2];
619  w.dist = v.dist+1;
620  H_insert (S, s, w);
621  visit[r2] = true;
622  }
623  j2++;
624  }
625  }
626  }
627 
628  // add the neighbors to the queue (sorted by node degree)
629  while (! H_empty (S, s))
630  {
631  // locate a neighbor of i with minimal degree in O(log(N))
632  v = H_remove_min (S, s, 1);
633 
634  // entered the BFS a new level?
635  if (v.dist > level)
636  {
637  // adjustment of bandwidth:
638  // "[...] the minimum bandwidth that
639  // can be obtained [...] is the
640  // maximum number of nodes per level"
641  if (Bsub < level_N)
642  Bsub = level_N;
643 
644  level = v.dist;
645  // v is the first node on the new level
646  level_N = 1;
647  }
648  else
649  {
650  // there is no new level but another node on
651  // this level:
652  level_N++;
653  }
654 
655  // enqueue v in O(1)
656  Q_enq (Q, N, qt, v);
657  }
658 
659  // synchronize the bandwidth with level_N once again:
660  if (Bsub < level_N)
661  Bsub = level_N;
662  }
663  // finish of BFS. If there are still unvisited nodes in the graph
664  // then it is split into CCs. The computed bandwidth is the maximum
665  // of all subgraphs. Update:
666  if (Bsub > B)
667  B = Bsub;
668  }
669  // are there any nodes left?
670  while (c+1 < N);
671 
672  // compute the reverse-ordering
673  s = N / 2 - 1;
674  for (octave_idx_type i = 0, j = N - 1; i <= s; i++, j--)
675  std::swap (P.elem (i), P.elem (j));
676 
677  // increment all indices, since Octave is not C
678  return ovl (P+1);
679 }
680 
681 /*
682 
683  basic functionality test, with icosahedron:
684 %!test <*64718>
685 %! adj = [ 0 1 1 1 1 1 0 0 0 0 0 0;
686 %! 1 0 1 0 0 1 1 0 0 0 1 0;
687 %! 1 1 0 1 0 0 1 1 0 0 0 0;
688 %! 1 0 1 0 1 0 0 1 1 0 0 0;
689 %! 1 0 0 1 0 1 0 0 1 1 0 0;
690 %! 1 1 0 0 1 0 0 0 0 1 1 0;
691 %! 0 1 1 0 0 0 0 1 0 0 1 1;
692 %! 0 0 1 1 0 0 1 0 1 0 0 1;
693 %! 0 0 0 1 1 0 0 1 0 1 0 1;
694 %! 0 0 0 0 1 1 0 0 1 0 1 1;
695 %! 0 1 0 0 0 1 1 0 0 1 0 1;
696 %! 0 0 0 0 0 0 1 1 1 1 1 0 ];
697 %! p = symrcm (adj);
698 %! assert (p, [12 8 9 10 11 7 3 4 5 6 2 1]);
699 %! assert (bandwidth (adj), 9);
700 %! assert (bandwidth (adj(p, p)), 6);
701 
702  handle zero-matrix properly:
703 %!test <*64718>
704 %! adj = false (5);
705 %! p = symrcm (adj);
706 %! assert (p, 1:5);
707 
708 */
709 
710 OCTAVE_END_NAMESPACE(octave)
charNDArray max(char d, const charNDArray &m)
Definition: chNDArray.cc:230
T & elem(octave_idx_type n)
Size of the specified dimension.
Definition: Array.h:562
T * fortran_vec()
Size of the specified dimension.
Definition: Array-base.cc:1764
octave_idx_type * xcidx()
Definition: Sparse.h:602
octave_idx_type * xridx()
Definition: Sparse.h:589
Vector representing the dimensions (size) of an Array.
Definition: dim-vector.h:94
SparseMatrix sparse_matrix_value(bool frc_str_conv=false) const
Definition: ov.h:900
octave_idx_type rows() const
Definition: ov.h:545
bool isreal() const
Definition: ov.h:738
octave_idx_type columns() const
Definition: ov.h:547
SparseComplexMatrix sparse_complex_matrix_value(bool frc_str_conv=false) const
Definition: ov.h:904
ColumnVector real(const ComplexColumnVector &a)
Definition: dColVector.cc:137
ColumnVector imag(const ComplexColumnVector &a)
Definition: dColVector.cc:143
OCTAVE_BEGIN_NAMESPACE(octave) static octave_value daspk_fcn
void print_usage(void)
Definition: defun-int.h:72
#define DEFUN(name, args_name, nargout_name, doc)
Macro to define a builtin function.
Definition: defun.h:56
void err_square_matrix_required(const char *fcn, const char *name)
Definition: errwarn.cc:122
F77_RET_T const F77_INT F77_CMPLX const F77_INT F77_CMPLX * B
F77_RET_T const F77_INT const F77_INT const F77_INT F77_DBLE const F77_INT F77_DBLE const F77_INT F77_DBLE * Q
F77_RET_T const F77_INT F77_CMPLX * A
F77_RET_T const F77_INT & N
F77_RET_T const F77_DBLE * x
T * r
Definition: mx-inlines.cc:781
std::complex< double > w(std::complex< double > z, double relerr=0)
#define OCTAVE_LOCAL_BUFFER(T, buf, size)
Definition: oct-locbuf.h:44
octave_value_list ovl(const OV_Args &... args)
Construct an octave_value_list with less typing.
Definition: ovl.h:219
#define RIGHT(i)
Definition: symrcm.cc:119
#define LEFT(i)
Definition: symrcm.cc:117
#define H_empty(H, h)
Definition: symrcm.cc:194
#define PARENT(i)
Definition: symrcm.cc:121
#define Q_empty(Q, N, qh, qt)
Definition: symrcm.cc:112