1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539 540 541 542 543 544 545 546 547 548 549 550 551 552 553 554 555 556 557 558 559 560 561 562 563 564 565 566 567 568 569 570 571 572 573 574 575 576 577 578 579 580 581 582 583 584 585 586 587 588 589 590 591 592 593 594 595 596 597 598 599 600 601 602 603 604 605 606 607 608 609 610 611 612 613 614 615 616 617 618 619 620 621 622 623 624 625 626 627 628 629 630 631 632 633 634 635 636 637 638 639 640 641 642 643 644 645 646 647 648 649 650 651 652 653 654 655 656 657 658 659 660 661 662 663 664 665 666 667 668 669 670 671 672 673 674 675 676 677 678 679 680 681 682 683 684 685 686 687 688 689 690 691 692 693 694 695 696 697 698 699 700 701 702 703 704 705 706 707 708 709 710 711 712 713 714 715 716 717 718 719 720 721 722 723 724 725 726 727 728 729 730 731 732 733 734 735 736 737 738 739 740 741 742 743 744 745 746 747 748 749 750 751 752 753 754 755 756 757 758 759 760 761 762 763 764 765 766 767 768 769 770 771 772 773 774 775 776 777 778 779 780 781 782 783 784 785 786 787 788 789 790 791 792 793 794 795 796 797 798 799 800 801 802 803 804 805 806 807 808 809 810 811 812 813 814 815 816 817 818 819 820 821 822 823 824 825 826 827 828 829 830 831 832 833 834 835 836 837 838 839 840 841 842 843 844 845 846 847 848 849 850 851 852 853 854 855 856 857 858 859 860 861 862 863 864 865 866 867 868 869 870 871 872 873 874 875 876 877 878 879 880 881 882 883 884 885 886 887 888 889 890 891 892 893 894 895 896 897 898 899 900 901 902 903 904 905 906 907 908 909 910 911 912 913 914 915 916 917 918 919 920 921 922 923 924
|
/*
* Copyright (c) 2014-2022 Cisco Systems, Inc. All rights reserved
* Copyright (c) 2017-2019 Amazon.com, Inc. or its affiliates. All Rights
* reserved.
* $COPYRIGHT$
*
* Additional copyrights may follow
*
* $HEADER$
*/
#include "opal_config.h"
#include <stddef.h>
#include <stdlib.h>
#include "opal/class/opal_list.h"
#include "opal/class/opal_pointer_array.h"
#include "opal/constants.h"
#include "opal/util/error.h"
#include "opal/util/misc.h"
#include "opal/util/output.h"
#include "opal_stdint.h"
#include "opal/util/bipartite_graph.h"
#include "opal/util/bipartite_graph_internal.h"
#define GRAPH_DEBUG 0
#if GRAPH_DEBUG
# define GRAPH_DEBUG_OUT(args) printf(args)
#else
# define GRAPH_DEBUG_OUT(args) \
do { \
} while (0)
#endif
#define MAX_COST INT64_MAX
#ifndef MAX
# define MAX(a, b) ((a) > (b) ? (a) : (b))
#endif
#ifndef MIN
# define MIN(a, b) ((a) < (b) ? (a) : (b))
#endif
#define f(i, j) flow[n * i + j]
/* ensure that (a+b<=max) */
static inline void check_add64_overflow(int64_t a, int64_t b)
{
assert(!((b > 0) && (a > (INT64_MAX - b))) && !((b < 0) && (a < (INT64_MIN - b))));
}
static void edge_constructor(opal_bp_graph_edge_t *e)
{
OBJ_CONSTRUCT(&e->outbound_li, opal_list_item_t);
OBJ_CONSTRUCT(&e->inbound_li, opal_list_item_t);
}
static void edge_destructor(opal_bp_graph_edge_t *e)
{
OBJ_DESTRUCT(&e->outbound_li);
OBJ_DESTRUCT(&e->inbound_li);
}
OBJ_CLASS_DECLARATION(opal_bp_graph_edge_t);
OBJ_CLASS_INSTANCE(opal_bp_graph_edge_t, opal_object_t, edge_constructor, edge_destructor);
static void dump_vec(const char *name, int *vec, int n) __opal_attribute_unused__;
static void dump_vec(const char *name, int *vec, int n)
{
int i;
fprintf(stderr, "%s={", name);
for (i = 0; i < n; ++i) {
fprintf(stderr, "[%d]=%2d, ", i, vec[i]);
}
fprintf(stderr, "}\n");
}
static void dump_vec64(const char *name, int64_t *vec, int n) __opal_attribute_unused__;
static void dump_vec64(const char *name, int64_t *vec, int n)
{
int i;
fprintf(stderr, "%s={", name);
for (i = 0; i < n; ++i) {
fprintf(stderr, "[%d]=%2" PRIi64 ", ", i, vec[i]);
}
fprintf(stderr, "}\n");
}
static void dump_flow(int *flow, int n) __opal_attribute_unused__;
static void dump_flow(int *flow, int n)
{
int u, v;
fprintf(stderr, "flow={\n");
for (u = 0; u < n; ++u) {
fprintf(stderr, "u=%d| ", u);
for (v = 0; v < n; ++v) {
fprintf(stderr, "%2d,", f(u, v));
}
fprintf(stderr, "\n");
}
fprintf(stderr, "}\n");
}
static int get_capacity(opal_bp_graph_t *g, int source, int target)
{
opal_bp_graph_edge_t *e;
CHECK_VERTEX_RANGE(g, source);
CHECK_VERTEX_RANGE(g, target);
FOREACH_OUT_EDGE(g, source, e)
{
assert(e->source == source);
if (e->target == target) {
return e->capacity;
}
}
return 0;
}
static int set_capacity(opal_bp_graph_t *g, int source, int target, int cap)
{
opal_bp_graph_edge_t *e;
CHECK_VERTEX_RANGE(g, source);
CHECK_VERTEX_RANGE(g, target);
FOREACH_OUT_EDGE(g, source, e)
{
assert(e->source == source);
if (e->target == target) {
e->capacity = cap;
return OPAL_SUCCESS;
}
}
return OPAL_ERR_NOT_FOUND;
}
static void free_vertex(opal_bp_graph_t *g, opal_bp_graph_vertex_t *v)
{
if (NULL != v) {
if (NULL != g->v_data_cleanup_fn && NULL != v->v_data) {
g->v_data_cleanup_fn(v->v_data);
}
free(v);
}
}
int opal_bp_graph_create(opal_bp_graph_cleanup_fn_t v_data_cleanup_fn,
opal_bp_graph_cleanup_fn_t e_data_cleanup_fn, opal_bp_graph_t **g_out)
{
int err;
opal_bp_graph_t *g = NULL;
if (NULL == g_out) {
return OPAL_ERR_BAD_PARAM;
}
*g_out = NULL;
g = calloc(1, sizeof(*g));
if (NULL == g) {
OPAL_ERROR_LOG(OPAL_ERR_OUT_OF_RESOURCE);
err = OPAL_ERR_OUT_OF_RESOURCE;
goto out_free_g;
}
g->source_idx = -1;
g->sink_idx = -1;
g->v_data_cleanup_fn = v_data_cleanup_fn;
g->e_data_cleanup_fn = e_data_cleanup_fn;
/* now that we essentially have an empty graph, add vertices to it */
OBJ_CONSTRUCT(&g->vertices, opal_pointer_array_t);
err = opal_pointer_array_init(&g->vertices, 0, INT_MAX, 32);
if (OPAL_SUCCESS != err) {
goto out_free_g;
}
*g_out = g;
return OPAL_SUCCESS;
out_free_g:
free(g);
return err;
}
int opal_bp_graph_free(opal_bp_graph_t *g)
{
int i;
opal_bp_graph_edge_t *e, *next;
opal_bp_graph_vertex_t *v;
/* remove all edges from all out_edges lists */
for (i = 0; i < NUM_VERTICES(g); ++i) {
v = V_ID_TO_PTR(g, i);
LIST_FOREACH_SAFE_CONTAINED(e, next, &v->out_edges, opal_bp_graph_edge_t, outbound_li)
{
opal_list_remove_item(&v->out_edges, &e->outbound_li);
OBJ_RELEASE(e);
}
}
/* now remove from all in_edges lists and free the edge */
for (i = 0; i < NUM_VERTICES(g); ++i) {
v = V_ID_TO_PTR(g, i);
LIST_FOREACH_SAFE_CONTAINED(e, next, &v->in_edges, opal_bp_graph_edge_t, inbound_li)
{
opal_list_remove_item(&v->in_edges, &e->inbound_li);
if (NULL != g->e_data_cleanup_fn && NULL != e->e_data) {
g->e_data_cleanup_fn(e->e_data);
}
OBJ_RELEASE(e);
}
free_vertex(g, V_ID_TO_PTR(g, i));
opal_pointer_array_set_item(&g->vertices, i, NULL);
}
g->num_vertices = 0;
OBJ_DESTRUCT(&g->vertices);
free(g);
return OPAL_SUCCESS;
}
int opal_bp_graph_clone(const opal_bp_graph_t *g, bool copy_user_data,
opal_bp_graph_t **g_clone_out)
{
int err;
int i;
int index;
opal_bp_graph_t *gx;
opal_bp_graph_edge_t *e;
if (NULL == g_clone_out) {
return OPAL_ERR_BAD_PARAM;
}
*g_clone_out = NULL;
if (copy_user_data) {
opal_output(0, "[%s:%d:%s] user data copy requested but not yet supported", __FILE__,
__LINE__, __func__);
abort();
return OPAL_ERR_FATAL;
}
gx = NULL;
err = opal_bp_graph_create(NULL, NULL, &gx);
if (OPAL_SUCCESS != err) {
return err;
}
assert(NULL != gx);
/* reconstruct all vertices */
for (i = 0; i < NUM_VERTICES(g); ++i) {
err = opal_bp_graph_add_vertex(gx, NULL, &index);
if (OPAL_SUCCESS != err) {
goto out_free_gx;
}
assert(index == i);
}
/* now reconstruct all the edges (iterate by source vertex only to avoid
* double-adding) */
for (i = 0; i < NUM_VERTICES(g); ++i) {
FOREACH_OUT_EDGE(g, i, e)
{
assert(i == e->source);
err = opal_bp_graph_add_edge(gx, e->source, e->target, e->cost, e->capacity, NULL);
if (OPAL_SUCCESS != err) {
goto out_free_gx;
}
}
}
*g_clone_out = gx;
return OPAL_SUCCESS;
out_free_gx:
/* we don't reach in and manipulate gx's state directly, so it should be
* safe to use the standard free function */
opal_bp_graph_free(gx);
return err;
}
int opal_bp_graph_indegree(const opal_bp_graph_t *g, int vertex)
{
opal_bp_graph_vertex_t *v;
v = V_ID_TO_PTR(g, vertex);
return opal_list_get_size(&v->in_edges);
}
int opal_bp_graph_outdegree(const opal_bp_graph_t *g, int vertex)
{
opal_bp_graph_vertex_t *v;
v = V_ID_TO_PTR(g, vertex);
return opal_list_get_size(&v->out_edges);
}
int opal_bp_graph_add_edge(opal_bp_graph_t *g, int from, int to, int64_t cost, int capacity,
void *e_data)
{
opal_bp_graph_edge_t *e;
opal_bp_graph_vertex_t *v_from, *v_to;
if (from < 0 || from >= NUM_VERTICES(g)) {
return OPAL_ERR_BAD_PARAM;
}
if (to < 0 || to >= NUM_VERTICES(g)) {
return OPAL_ERR_BAD_PARAM;
}
if (cost == MAX_COST) {
return OPAL_ERR_BAD_PARAM;
}
if (capacity < 0) {
/* negative cost is fine, but negative capacity is not currently
* handled appropriately */
return OPAL_ERR_BAD_PARAM;
}
FOREACH_OUT_EDGE(g, from, e)
{
assert(e->source == from);
if (e->target == to) {
return OPAL_EXISTS;
}
}
/* this reference is owned by the out_edges list */
e = OBJ_NEW(opal_bp_graph_edge_t);
if (NULL == e) {
OPAL_ERROR_LOG(OPAL_ERR_OUT_OF_RESOURCE);
return OPAL_ERR_OUT_OF_RESOURCE;
}
e->source = from;
e->target = to;
e->cost = cost;
e->capacity = capacity;
e->e_data = e_data;
v_from = V_ID_TO_PTR(g, from);
opal_list_append(&v_from->out_edges, &e->outbound_li);
OBJ_RETAIN(e); /* ref owned by in_edges list */
v_to = V_ID_TO_PTR(g, to);
opal_list_append(&v_to->in_edges, &e->inbound_li);
return OPAL_SUCCESS;
}
int opal_bp_graph_add_vertex(opal_bp_graph_t *g, void *v_data, int *index_out)
{
opal_bp_graph_vertex_t *v;
v = calloc(1, sizeof(*v));
if (NULL == v) {
OPAL_ERROR_LOG(OPAL_ERR_OUT_OF_RESOURCE);
return OPAL_ERR_OUT_OF_RESOURCE;
}
/* add to the ptr array early to simplify cleanup in the incredibly rare
* chance that adding fails */
v->v_index = opal_pointer_array_add(&g->vertices, v);
if (-1 == v->v_index) {
free(v);
OPAL_ERROR_LOG(OPAL_ERR_OUT_OF_RESOURCE);
return OPAL_ERR_OUT_OF_RESOURCE;
}
assert(v->v_index == g->num_vertices);
++g->num_vertices;
v->v_data = v_data;
OBJ_CONSTRUCT(&v->out_edges, opal_list_t);
OBJ_CONSTRUCT(&v->in_edges, opal_list_t);
if (NULL != index_out) {
*index_out = v->v_index;
}
return OPAL_SUCCESS;
}
int opal_bp_graph_get_vertex_data(opal_bp_graph_t *g, int v_index, void **v_data_out)
{
opal_bp_graph_vertex_t *v;
v = V_ID_TO_PTR(g, v_index);
if (NULL == v) {
return OPAL_ERR_BAD_PARAM;
}
*v_data_out = v->v_data;
return OPAL_SUCCESS;
}
int opal_bp_graph_order(const opal_bp_graph_t *g)
{
return NUM_VERTICES(g);
}
/**
* shrink a flow matrix for old_n vertices to one works for new_n
*
* Takes a matrix stored in a one-dimensional array of size (old_n*old_n) and
* "truncates" it into a dense array of size (new_n*new_n) that only contain
* the flow values for the first new_n vertices. E.g., it turns this array
* (old_n=5, new_n=3):
*
* 1 2 3 4 5
* 6 7 8 9 10
* 11 12 13 14 15
* 16 17 18 19 20
* 21 22 23 24 25
*
* into this array;
*
* 1 2 3
* 6 7 8
* 11 12 13
*/
static void shrink_flow_matrix(int *flow, int old_n, int new_n)
{
int u, v;
assert(old_n > new_n);
for (u = 0; u < new_n; ++u) {
for (v = 0; v < new_n; ++v) {
flow[new_n * u + v] = flow[old_n * u + v];
}
}
}
/**
* Compute the so-called "bottleneck" capacity value for a path "pred" through
* graph "gx".
*/
static int bottleneck_path(opal_bp_graph_t *gx, int n, int *pred)
{
int u, v;
int min;
min = INT_MAX;
FOREACH_UV_ON_PATH(pred, gx->source_idx, gx->sink_idx, u, v)
{
int cap_f_uv = get_capacity(gx, u, v);
min = MIN(min, cap_f_uv);
}
return min;
}
/**
* This routine implements the Bellman-Ford shortest paths algorithm, slightly
* specialized for our forumlation of flow networks:
* https://en.wikipedia.org/wiki/Bellman%E2%80%93Ford_algorithm
*
* Specifically, it attempts to find the shortest path from "source" to
* "target". It returns true if such a path was found, false otherwise. Any
* found path is returned in "pred" as a predecessor chain (i.e., pred[sink]
* is the start of the path and pred[pred[sink]] is its predecessor, etc.).
*
* The contents of "pred" are only valid if this routine returns true.
*/
bool opal_bp_graph_bellman_ford(opal_bp_graph_t *gx, int source, int target, int *pred)
{
int64_t *dist;
int i;
int n;
int u, v;
bool found_target = false;
if (NULL == gx) {
OPAL_ERROR_LOG(OPAL_ERR_BAD_PARAM);
return false;
}
if (NULL == pred) {
OPAL_ERROR_LOG(OPAL_ERR_BAD_PARAM);
return false;
}
if (source < 0 || source >= NUM_VERTICES(gx)) {
return OPAL_ERR_BAD_PARAM;
}
if (target < 0 || target >= NUM_VERTICES(gx)) {
return OPAL_ERR_BAD_PARAM;
}
/* initialize */
n = opal_bp_graph_order(gx);
dist = malloc(n * sizeof(*dist));
if (NULL == dist) {
OPAL_ERROR_LOG(OPAL_ERR_OUT_OF_RESOURCE);
goto out;
}
for (i = 0; i < n; ++i) {
dist[i] = MAX_COST;
pred[i] = -1;
}
dist[source] = 0;
/* relax repeatedly */
for (i = 1; i < NUM_VERTICES(gx); ++i) {
bool relaxed = false;
#if GRAPH_DEBUG
dump_vec("pred", pred, NUM_VERTICES(gx));
dump_vec64("dist", dist, NUM_VERTICES(gx));
#endif
for (u = 0; u < NUM_VERTICES(gx); ++u) {
opal_bp_graph_edge_t *e_ptr;
FOREACH_OUT_EDGE(gx, u, e_ptr)
{
v = e_ptr->target;
/* make sure to only construct paths from edges that actually have
* non-zero capacity */
if (e_ptr->capacity > 0
&& dist[u] != MAX_COST) { /* avoid signed overflow for "infinity" */
check_add64_overflow(dist[u], e_ptr->cost);
if ((dist[u] + e_ptr->cost) < dist[v]) {
dist[v] = dist[u] + e_ptr->cost;
pred[v] = u;
relaxed = true;
}
}
}
}
/* optimization: stop if an outer iteration did not succeed in
* changing any dist/pred values (already at optimum) */
if (!relaxed) {
GRAPH_DEBUG_OUT(("relaxed==false, breaking out"));
break;
}
}
/* check for negative-cost cycles */
for (u = 0; u < NUM_VERTICES(gx); ++u) {
opal_bp_graph_edge_t *e_ptr;
FOREACH_OUT_EDGE(gx, u, e_ptr)
{
v = e_ptr->target;
if (e_ptr->capacity > 0 && dist[u] != MAX_COST && /* avoid signed overflow */
(dist[u] + e_ptr->cost) < dist[v]) {
opal_output(0, "[%s:%d:%s] negative-weight cycle detected", __FILE__, __LINE__,
__func__);
abort();
goto out;
}
}
}
if (dist[target] != MAX_COST) {
found_target = true;
}
out:
#if GRAPH_DEBUG
dump_vec("pred", pred, NUM_VERTICES(gx));
#endif
assert(pred[source] == -1);
free(dist);
GRAPH_DEBUG_OUT(("bellman_ford: found_target=%s", found_target ? "true" : "false"));
return found_target;
}
/**
* Transform the given connected, bipartite, acyclic digraph into a flow
* network (i.e., add a source and a sink, with the source connected to vertex
* set V1 and the sink connected to vertex set V2). This also creates
* residual edges suitable for augmenting-path algorithms. All "source" nodes
* in the original graph are considered to have an output of 1 and "sink"
* nodes can take an input of 1. The result is that "forward" edges are all
* created with capacity=1, "backward" (residual) edges are created with
* capacity=0.
*
* After this routine, all capacities are "residual capacities" ($c_f$ in the
* literature).
*
* Initial flow throughout the network is assumed to be 0 at all edges.
*
* The graph will be left in an undefined state if an error occurs (though
* freeing it should still be safe).
*/
int opal_bp_graph_bipartite_to_flow(opal_bp_graph_t *g)
{
int err;
int order;
int u, v;
int num_left, num_right;
/* grab size before adding extra vertices */
order = opal_bp_graph_order(g);
err = opal_bp_graph_add_vertex(g, NULL, &g->source_idx);
if (OPAL_SUCCESS != err) {
return err;
}
err = opal_bp_graph_add_vertex(g, NULL, &g->sink_idx);
if (OPAL_SUCCESS != err) {
return err;
}
/* The networks we are interested in are bipartite and have edges only
* from one partition to the other partition (none vice versa). We
* visualize this conventionally with all of the source vertices on the
* left-hand side of an imaginary rendering of the graph and the target
* vertices on the right-hand side of the rendering. The direction
* "forward" is considered to be moving from left to right.
*/
num_left = 0;
num_right = 0;
for (u = 0; u < order; ++u) {
int inbound = opal_bp_graph_indegree(g, u);
int outbound = opal_bp_graph_outdegree(g, u);
if (inbound > 0 && outbound > 0) {
opal_output(0, "[%s:%d:%s] graph is not (unidirectionally) bipartite", __FILE__,
__LINE__, __func__);
abort();
} else if (inbound > 0) {
/* "right" side of the graph, create edges to the sink */
++num_right;
err = opal_bp_graph_add_edge(g, u, g->sink_idx, 0, /* no cost */
/*capacity=*/1,
/*e_data=*/NULL);
if (OPAL_SUCCESS != err) {
GRAPH_DEBUG_OUT(("add_edge failed"));
return err;
}
} else if (outbound > 0) {
/* "left" side of the graph, create edges to the source */
++num_left;
err = opal_bp_graph_add_edge(g, g->source_idx, u, 0, /* no cost */
/*capacity=*/1,
/*e_data=*/NULL);
if (OPAL_SUCCESS != err) {
GRAPH_DEBUG_OUT(("add_edge failed"));
return err;
}
}
}
/* it doesn't make sense to extend this graph with a source and sink
* unless */
if (num_right == 0 || num_left == 0) {
return OPAL_ERR_BAD_PARAM;
}
/* now run through and create "residual" edges as well (i.e., create edges
* in the reverse direction with 0 initial flow and a residual capacity of
* $c_f(u,v)=c(u,v)-f(u,v)$). Residual edges can exist where no edges
* exist in the original graph.
*/
order = opal_bp_graph_order(g); /* need residuals for newly created
source/sink edges too */
for (u = 0; u < order; ++u) {
opal_bp_graph_edge_t *e_ptr;
FOREACH_OUT_EDGE(g, u, e_ptr)
{
v = e_ptr->target;
/* (u,v) exists, add (v,u) if not already present. Cost is
* negative for these edges because "giving back" flow pays us
* back any cost already incurred. */
err = opal_bp_graph_add_edge(g, v, u, -e_ptr->cost,
/*capacity=*/0,
/*e_data=*/NULL);
if (OPAL_SUCCESS != err && OPAL_EXISTS != err) {
return err;
}
}
}
return OPAL_SUCCESS;
}
/**
* Implements the "Successive Shortest Path" algorithm for computing the
* minimum cost flow problem. This is a generalized version of the
* Ford-Fulkerson algorithm. There are two major changes from F-F:
* 1. In addition to capacities and flows, this algorithm pays attention to
* costs for traversing an edge. This particular function leaves the
* caller's costs alone but sets its own capacities.
* 2. Shortest paths are computed using the cost metric.
*
* The algorithm's sketch looks like:
* 1 Transform network G by adding source and sink, create residual edges
* 2 Initial flow x is zero
* 3 while ( Gx contains a path from s to t ) do
* 4 Find any shortest path P from s to t
* 5 Augment current flow x along P
* 6 update Gx
*
* This function mutates the given graph (adding vertices and edges, changing
* capacties, etc.), so callers may wish to clone the graph before calling
* this routine.
*
* The result is an array of (u,v) vertex pairs, where (u,v) is an edge in the
* original graph which has non-zero flow.
*
* Returns OMPI error codes like OPAL_SUCCESS/OPAL_ERR_OUT_OF_RESOURCE.
*
* This version of the algorithm has a theoretical upper bound on its running
* time of O(|V|^2 * |E| * f), where f is essentially the maximum flow in the
* graph. In our case, f=min(|V1|,|V2|), where V1 and V2 are the two
* constituent sets of the bipartite graph.
*
* This algorithm's performance could probably be improved by modifying it to
* use vertex potentials and Dijkstra's Algorithm instead of Bellman-Ford.
* Normally vertex potentials are needed in order to use Dijkstra's safely,
* but our graphs are constrained enough that this may not be necessary.
* Switching to Dijkstra's implemented with a heap should yield a reduced
* upper bound of O(|V| * |E| * f * log(|V|)). Let's consider this a future
* enhancement for the time being, since it's not obvious at this point that
* the faster running time will be worth the additional implementation
* complexity.
*/
static int min_cost_flow_ssp(opal_bp_graph_t *gx, int **flow_out)
{
int err = OPAL_SUCCESS;
int n;
int *pred = NULL;
int *flow = NULL;
int u, v;
int c;
GRAPH_DEBUG_OUT(("begin min_cost_flow_ssp()"));
if (NULL == flow_out) {
return OPAL_ERR_BAD_PARAM;
}
*flow_out = NULL;
n = opal_bp_graph_order(gx);
pred = malloc(n * sizeof(*pred));
if (NULL == pred) {
OPAL_ERROR_LOG(OPAL_ERR_OUT_OF_RESOURCE);
err = OPAL_ERR_OUT_OF_RESOURCE;
goto out_error;
}
/* "flow" is a 2d matrix of current flow values, all initialized to zero */
flow = calloc(n * n, sizeof(*flow));
if (NULL == flow) {
OPAL_ERROR_LOG(OPAL_ERR_OUT_OF_RESOURCE);
err = OPAL_ERR_OUT_OF_RESOURCE;
goto out_error;
}
/* loop as long as paths exist from source to sink */
while (opal_bp_graph_bellman_ford(gx, gx->source_idx, gx->sink_idx, pred)) {
int cap_f_path;
/* find any shortest path P from s to t (already present in pred) */
GRAPH_DEBUG_OUT(("start outer iteration of SSP algorithm"));
#if GRAPH_DEBUG
dump_vec("pred", pred, NUM_VERTICES(gx));
dump_flow(flow, n);
#endif
cap_f_path = bottleneck_path(gx, n, pred);
/* augment current flow along P */
FOREACH_UV_ON_PATH(pred, gx->source_idx, gx->sink_idx, u, v)
{
assert(u == pred[v]);
f(u, v) = f(u, v) + cap_f_path; /* "forward" edge */
f(v, u) = f(v, u) - cap_f_path; /* residual network edge */
assert(f(u, v) == -f(v, u)); /* skew symmetry invariant */
/* update Gx as we go along: decrease capacity by this new
* augmenting flow */
c = get_capacity(gx, u, v) - cap_f_path;
assert(c >= 0);
err = set_capacity(gx, u, v, c);
if (OPAL_SUCCESS != err) {
opal_output(0, "[%s:%d:%s] unable to set capacity, missing edge?", __FILE__,
__LINE__, __func__);
abort();
}
c = get_capacity(gx, v, u) + cap_f_path;
assert(c >= 0);
err = set_capacity(gx, v, u, c);
if (OPAL_SUCCESS != err) {
opal_output(0, "[%s:%d:%s] unable to set capacity, missing edge?", __FILE__,
__LINE__, __func__);
abort();
}
}
}
out:
*flow_out = flow;
free(pred);
return err;
out_error:
free(*flow_out);
GRAPH_DEBUG_OUT(("returning error %d", err));
goto out;
}
int opal_bp_graph_solve_bipartite_assignment(const opal_bp_graph_t *g, int *num_match_edges_out,
int **match_edges_out)
{
int err;
int i;
int u, v;
int n;
int *flow = NULL;
opal_bp_graph_t *gx = NULL;
if (NULL == match_edges_out || NULL == num_match_edges_out) {
return OPAL_ERR_BAD_PARAM;
}
*num_match_edges_out = 0;
*match_edges_out = NULL;
/* don't perturb the caller's data structure */
err = opal_bp_graph_clone(g, false, &gx);
if (OPAL_SUCCESS != err) {
GRAPH_DEBUG_OUT(("opal_bp_graph_clone failed"));
goto out;
}
/* Transform gx into a residual flow network with capacities, a source, a
* sink, and residual edges. We track the actual flow separately in the
* "flow" matrix. Initial capacity for every forward edge is 1. Initial
* capacity for every backward (residual) edge is 0.
*
* For the remainder of this routine (and the ssp routine) the capacities
* refer to residual capacities ($c_f$) not capacities in the original
* graph. For convenience we adjust all residual capacities as we go
* along rather than recomputing them from the flow and capacities in the
* original graph. This allows many other graph operations to have no
* direct knowledge of the flow matrix.
*/
err = opal_bp_graph_bipartite_to_flow(gx);
if (OPAL_SUCCESS != err) {
GRAPH_DEBUG_OUT(("bipartite_to_flow failed"));
OPAL_ERROR_LOG(err);
return err;
}
/* Use the SSP algorithm to compute the min-cost flow over this network.
* Edges with non-zero flow in the result should be part of the matching.
*
* Note that the flow array returned is sized for gx, not for g. Index
* accordingly later on.
*/
err = min_cost_flow_ssp(gx, &flow);
if (OPAL_SUCCESS != err) {
GRAPH_DEBUG_OUT(("min_cost_flow_ssp failed"));
return err;
}
assert(NULL != flow);
/* don't care about new edges in gx, only old edges in g */
n = opal_bp_graph_order(g);
#if GRAPH_DEBUG
dump_flow(flow, NUM_VERTICES(gx));
#endif
shrink_flow_matrix(flow, opal_bp_graph_order(gx), n);
#if GRAPH_DEBUG
dump_flow(flow, n);
#endif
for (u = 0; u < n; ++u) {
for (v = 0; v < n; ++v) {
if (f(u, v) > 0) {
++(*num_match_edges_out);
}
}
}
if (0 == *num_match_edges_out) {
/* avoid attempting to allocate a zero-byte buffer */
goto out;
}
*match_edges_out = malloc(*num_match_edges_out * 2 * sizeof(int));
if (NULL == *match_edges_out) {
*num_match_edges_out = 0;
OPAL_ERROR_LOG(OPAL_ERR_OUT_OF_RESOURCE);
err = OPAL_ERR_OUT_OF_RESOURCE;
goto out;
}
i = 0;
for (u = 0; u < n; ++u) {
for (v = 0; v < n; ++v) {
/* flow exists on this edge so include this edge in the matching */
if (f(u, v) > 0) {
(*match_edges_out)[i++] = u;
(*match_edges_out)[i++] = v;
}
}
}
out:
free(flow);
opal_bp_graph_free(gx);
return err;
}
|