mirror of
https://github.com/mozilla/gecko-dev.git
synced 2024-11-14 15:37:55 +00:00
766 lines
20 KiB
C++
766 lines
20 KiB
C++
/* This Source Code Form is subject to the terms of the Mozilla Public
|
|
* License, v. 2.0. If a copy of the MPL was not distributed with this
|
|
* file, You can obtain one at http://mozilla.org/MPL/2.0/. */
|
|
|
|
/*
|
|
|
|
A program that attempts to find an optimal function ordering for an
|
|
executable using a genetic algorithm whose fitness function is
|
|
computed using runtime profile information.
|
|
|
|
The fitness function was inspired by Nat Friedman's <nat@nat.org>
|
|
work on `grope':
|
|
|
|
_GNU Rope - A Subroutine Position Optimizer_
|
|
<http://www.hungry.com/~shaver/grope/grope.ps>
|
|
|
|
Brendan Eich <brendan@mozilla.org> told me tales about Scott Furman
|
|
doing something like this, which sort of made me want to try it.
|
|
|
|
As far as I can tell, it would take a lot of computers a lot of time
|
|
to actually find something useful on a non-trivial program using
|
|
this.
|
|
|
|
*/
|
|
|
|
#include <assert.h>
|
|
#include <fstream>
|
|
#include <hash_map>
|
|
#include <vector>
|
|
#include <limits.h>
|
|
#include <unistd.h>
|
|
#include <stdio.h>
|
|
#include <fcntl.h>
|
|
|
|
#include "elf_symbol_table.h"
|
|
|
|
#define _GNU_SOURCE
|
|
#include <getopt.h>
|
|
|
|
#define PAGE_SIZE 4096
|
|
#define SYMBOL_ALIGN 4
|
|
|
|
//----------------------------------------------------------------------
|
|
|
|
class call_pair
|
|
{
|
|
public:
|
|
const Elf32_Sym *m_lo;
|
|
const Elf32_Sym *m_hi;
|
|
|
|
call_pair(const Elf32_Sym *site1, const Elf32_Sym *site2)
|
|
{
|
|
if (site1 < site2) {
|
|
m_lo = site1;
|
|
m_hi = site2;
|
|
}
|
|
else {
|
|
m_hi = site1;
|
|
m_lo = site2;
|
|
}
|
|
}
|
|
|
|
friend bool
|
|
operator==(const call_pair &lhs, const call_pair &rhs)
|
|
{
|
|
return (lhs.m_lo == rhs.m_lo) && (lhs.m_hi == rhs.m_hi);
|
|
}
|
|
};
|
|
|
|
// Straight outta plhash.c!
|
|
#define GOLDEN_RATIO 0x9E3779B9U
|
|
|
|
template<>
|
|
struct hash<call_pair>
|
|
{
|
|
size_t operator()(const call_pair &pair) const
|
|
{
|
|
size_t h = (reinterpret_cast<size_t>(pair.m_hi) >> 4);
|
|
h += (reinterpret_cast<size_t>(pair.m_lo) >> 4);
|
|
h *= GOLDEN_RATIO;
|
|
return h;
|
|
}
|
|
};
|
|
|
|
//----------------------------------------------------------------------
|
|
|
|
struct hash<const Elf32_Sym *>
|
|
{
|
|
size_t operator()(const Elf32_Sym *sym) const
|
|
{
|
|
return (reinterpret_cast<size_t>(sym) >> 4) * GOLDEN_RATIO;
|
|
}
|
|
};
|
|
|
|
//----------------------------------------------------------------------
|
|
|
|
typedef hash_map<call_pair, unsigned int> call_graph_t;
|
|
call_graph_t call_graph;
|
|
|
|
typedef hash_map<const Elf32_Sym *, unsigned int> histogram_t;
|
|
histogram_t histogram;
|
|
long long total_calls = 0;
|
|
|
|
elf_symbol_table symtab;
|
|
|
|
bool opt_debug = false;
|
|
int opt_generations = 10;
|
|
int opt_mutate = 0;
|
|
const char *opt_out = "order.out";
|
|
int opt_population_size = 100;
|
|
int opt_tick = 0;
|
|
bool opt_verbose = false;
|
|
int opt_window = 0;
|
|
|
|
static struct option long_options[] = {
|
|
{ "debug", no_argument, 0, 'd' },
|
|
{ "exe", required_argument, 0, 'e' },
|
|
{ "generations", required_argument, 0, 'g' },
|
|
{ "help", no_argument, 0, '?' },
|
|
{ "mutate", required_argument, 0, 'm' },
|
|
{ "out", required_argument, 0, 'o' },
|
|
{ "population", required_argument, 0, 'p' },
|
|
{ "seed", required_argument, 0, 's' },
|
|
{ "tick", optional_argument, 0, 't' },
|
|
{ "verbose", no_argument, 0, 'v' },
|
|
{ "window", required_argument, 0, 'w' },
|
|
{ 0, 0, 0, 0 }
|
|
};
|
|
|
|
//----------------------------------------------------------------------
|
|
|
|
static long long
|
|
llrand()
|
|
{
|
|
long long result;
|
|
result = (long long) rand();
|
|
result *= (long long) (unsigned int) (RAND_MAX + 1);
|
|
result += (long long) rand();
|
|
return result;
|
|
}
|
|
|
|
//----------------------------------------------------------------------
|
|
|
|
class symbol_order {
|
|
public:
|
|
typedef vector<const Elf32_Sym *> vector_t;
|
|
typedef long long score_t;
|
|
|
|
static const score_t max_score;
|
|
|
|
/**
|
|
* A vector of symbols that is this ordering.
|
|
*/
|
|
vector_t m_ordering;
|
|
|
|
/**
|
|
* The symbol ordering's score.
|
|
*/
|
|
score_t m_score;
|
|
|
|
symbol_order() : m_score(0) {}
|
|
|
|
/**
|
|
* ``Shuffle'' a symbol ordering, randomizing it.
|
|
*/
|
|
void shuffle();
|
|
|
|
/**
|
|
* Initialize this symbol ordering by performing a crossover from
|
|
* two ``parent'' symbol orderings.
|
|
*/
|
|
void crossover_from(const symbol_order *father, const symbol_order *mother);
|
|
|
|
/**
|
|
* Randomly mutate this symbol ordering.
|
|
*/
|
|
void mutate();
|
|
|
|
/**
|
|
* Score a symbol ordering based on paginated locality.
|
|
*/
|
|
score_t compute_score_page();
|
|
|
|
/**
|
|
* Score a symbol ordering based on a sliding window.
|
|
*/
|
|
score_t compute_score_window(int window_size);
|
|
|
|
static score_t compute_score(symbol_order &order);
|
|
|
|
/**
|
|
* Use the symbol table to dump the ordered symbolic constants.
|
|
*/
|
|
void dump_symbols() const;
|
|
|
|
friend ostream &
|
|
operator<<(ostream &out, const symbol_order &order);
|
|
};
|
|
|
|
const symbol_order::score_t
|
|
symbol_order::max_score = ~((symbol_order::score_t)1 << ((sizeof(symbol_order::score_t) * 8) - 1));
|
|
|
|
symbol_order::score_t
|
|
symbol_order::compute_score_page()
|
|
{
|
|
m_score = 0;
|
|
|
|
unsigned int off = 0; // XXX in reality, probably not page-aligned to start
|
|
|
|
vector_t::const_iterator end = m_ordering.end(),
|
|
last = end,
|
|
sym = m_ordering.begin();
|
|
|
|
while (sym != end) {
|
|
vector_t page;
|
|
|
|
// If we had a symbol that spilled over from the last page,
|
|
// then include it here.
|
|
if (last != end)
|
|
page.push_back(*last);
|
|
|
|
// Pack symbols into the page
|
|
do {
|
|
page.push_back(*sym);
|
|
|
|
int size = (*sym)->st_size;
|
|
size += SYMBOL_ALIGN - 1;
|
|
size &= ~(SYMBOL_ALIGN - 1);
|
|
|
|
off += size;
|
|
} while (++sym != end && off < PAGE_SIZE);
|
|
|
|
// Remember if there was spill-over.
|
|
off %= PAGE_SIZE;
|
|
last = (off != 0) ? sym : end;
|
|
|
|
// Now score the page as the count of all calls to symbols on
|
|
// the page, less calls between the symbols on the page.
|
|
vector_t::const_iterator page_end = page.end();
|
|
for (vector_t::const_iterator i = page.begin(); i != page_end; ++i) {
|
|
histogram_t::const_iterator func = histogram.find(*i);
|
|
if (func == histogram.end())
|
|
continue;
|
|
|
|
m_score += func->second;
|
|
|
|
vector_t::const_iterator j = i;
|
|
for (++j; j != page_end; ++j) {
|
|
call_graph_t::const_iterator call =
|
|
call_graph.find(call_pair(*i, *j));
|
|
|
|
if (call != call_graph.end())
|
|
m_score -= call->second;
|
|
}
|
|
}
|
|
}
|
|
|
|
assert(m_score >= 0);
|
|
|
|
// Integer reciprocal so we minimize instead of maximize.
|
|
if (m_score == 0)
|
|
m_score = 1;
|
|
|
|
m_score = (total_calls / m_score) + 1;
|
|
|
|
return m_score;
|
|
}
|
|
|
|
symbol_order::score_t
|
|
symbol_order::compute_score_window(int window_size)
|
|
{
|
|
m_score = 0;
|
|
|
|
vector_t::const_iterator *window = new vector_t::const_iterator[window_size];
|
|
int window_fill = 0;
|
|
|
|
vector_t::const_iterator end = m_ordering.end(),
|
|
sym = m_ordering.begin();
|
|
|
|
for (; sym != end; ++sym) {
|
|
histogram_t::const_iterator func = histogram.find(*sym);
|
|
if (func != histogram.end()) {
|
|
long long scale = ((long long) 1) << window_size;
|
|
|
|
m_score += func->second * scale * 2;
|
|
|
|
vector_t::const_iterator *limit = window + window_fill;
|
|
vector_t::const_iterator *iter;
|
|
for (iter = window ; iter < limit; ++iter) {
|
|
call_graph_t::const_iterator call =
|
|
call_graph.find(call_pair(*sym, **iter));
|
|
|
|
if (call != call_graph.end())
|
|
m_score -= (call->second * scale);
|
|
|
|
scale >>= 1;
|
|
}
|
|
}
|
|
|
|
// Slide the window.
|
|
vector_t::const_iterator *begin = window;
|
|
vector_t::const_iterator *iter;
|
|
for (iter = window + (window_size - 1); iter > begin; --iter)
|
|
*iter = *(iter - 1);
|
|
|
|
if (window_fill < window_size)
|
|
++window_fill;
|
|
|
|
*window = sym;
|
|
}
|
|
|
|
delete[] window;
|
|
|
|
assert(m_score >= 0);
|
|
|
|
// Integer reciprocal so we minimize instead of maximize.
|
|
if (m_score == 0)
|
|
m_score = 1;
|
|
|
|
m_score = (total_calls / m_score) + 1;
|
|
|
|
return m_score;
|
|
}
|
|
|
|
symbol_order::score_t
|
|
symbol_order::compute_score(symbol_order &order)
|
|
{
|
|
if (opt_window)
|
|
return order.compute_score_window(opt_window);
|
|
|
|
return order.compute_score_page();
|
|
}
|
|
|
|
void
|
|
symbol_order::shuffle()
|
|
{
|
|
vector_t::iterator sym = m_ordering.begin();
|
|
vector_t::iterator end = m_ordering.end();
|
|
for (; sym != end; ++sym) {
|
|
int i = rand() % m_ordering.size();
|
|
const Elf32_Sym *temp = *sym;
|
|
*sym = m_ordering[i];
|
|
m_ordering[i] = temp;
|
|
}
|
|
}
|
|
|
|
void
|
|
symbol_order::crossover_from(const symbol_order *father, const symbol_order *mother)
|
|
{
|
|
histogram_t used;
|
|
|
|
m_ordering = vector_t(father->m_ordering.size(), 0);
|
|
|
|
vector_t::const_iterator parent_sym = father->m_ordering.begin();
|
|
vector_t::iterator sym = m_ordering.begin();
|
|
vector_t::iterator end = m_ordering.end();
|
|
|
|
for (; sym != end; ++sym, ++parent_sym) {
|
|
if (rand() % 2) {
|
|
*sym = *parent_sym;
|
|
used[*parent_sym] = 1;
|
|
}
|
|
}
|
|
|
|
parent_sym = mother->m_ordering.begin();
|
|
sym = m_ordering.begin();
|
|
|
|
for (; sym != end; ++sym) {
|
|
if (! *sym) {
|
|
while (used[*parent_sym])
|
|
++parent_sym;
|
|
|
|
*sym = *parent_sym++;
|
|
}
|
|
}
|
|
}
|
|
|
|
void
|
|
symbol_order::mutate()
|
|
{
|
|
int i, j;
|
|
i = rand() % m_ordering.size();
|
|
j = rand() % m_ordering.size();
|
|
|
|
const Elf32_Sym *temp = m_ordering[i];
|
|
m_ordering[i] = m_ordering[j];
|
|
m_ordering[j] = temp;
|
|
}
|
|
|
|
void
|
|
symbol_order::dump_symbols() const
|
|
{
|
|
ofstream out(opt_out);
|
|
|
|
vector_t::const_iterator sym = m_ordering.begin();
|
|
vector_t::const_iterator end = m_ordering.end();
|
|
for (; sym != end; ++sym)
|
|
out << symtab.get_symbol_name(*sym) << endl;
|
|
|
|
out.close();
|
|
}
|
|
|
|
ostream &
|
|
operator<<(ostream &out, const symbol_order &order)
|
|
{
|
|
out << "symbol_order(" << order.m_score << ") ";
|
|
|
|
symbol_order::vector_t::const_iterator sym = order.m_ordering.begin();
|
|
symbol_order::vector_t::const_iterator end = order.m_ordering.end();
|
|
for (; sym != end; ++sym)
|
|
out.form("%08x ", *sym);
|
|
|
|
out << endl;
|
|
|
|
return out;
|
|
}
|
|
|
|
//----------------------------------------------------------------------
|
|
|
|
static void
|
|
usage(const char *name)
|
|
{
|
|
cerr << "usage: " << name << " [options] [<file> ...]" << endl;
|
|
cerr << " Options:" << endl;
|
|
cerr << " --debug, -d" << endl;
|
|
cerr << " Print lots of verbose debugging cruft." << endl;
|
|
cerr << " --exe=<image>, -e <image> (required)" << endl;
|
|
cerr << " Specify the executable image from which to read symbol information." << endl;
|
|
cerr << " --generations=<num>, -g <num>" << endl;
|
|
cerr << " Specify the number of generations to run the GA (default is 10)." << endl;
|
|
cerr << " --help, -?" << endl;
|
|
cerr << " Print this message and exit." << endl;
|
|
cerr << " --mutate=<num>, -m <num>" << endl;
|
|
cerr << " Mutate every <num>th individual, or zero for no mutation (default)." << endl;
|
|
cerr << " --out=<file>, -o <file>" << endl;
|
|
cerr << " Specify the output file to which to dump the symbol ordering of the" << endl;
|
|
cerr << " best individual (default is `order.out')." << endl;
|
|
cerr << " --population=<num>, -p <num>" << endl;
|
|
cerr << " Set the population size to <num> individuals (default is 100)." << endl;
|
|
cerr << " --seed=<num>, -s <num>" << endl;
|
|
cerr << " Specify a seed to srand()." << endl;
|
|
cerr << " --tick[=<num>], -t [<num>]" << endl;
|
|
cerr << " When reading address data, print a dot to stderr every <num>th" << endl;
|
|
cerr << " address processed from the call trace. If specified with no argument," << endl;
|
|
cerr << " a dot will be printed for every million addresses processed." << endl;
|
|
cerr << " --verbose, -v" << endl;
|
|
cerr << " Issue progress messages to stderr." << endl;
|
|
cerr << " --window=<num>, -w <num>" << endl;
|
|
cerr << " Use a sliding window instead of pagination to score orderings." << endl;
|
|
cerr << endl;
|
|
cerr << "This program uses a genetic algorithm to produce an `optimal' ordering for" << endl;
|
|
cerr << "an executable based on call patterns." << endl;
|
|
cerr << endl;
|
|
cerr << "Addresses from a call trace are read as binary data from the files" << endl;
|
|
cerr << "specified, or from stdin if no files are specified. These addresses" << endl;
|
|
cerr << "are used with the symbolic information from the executable to create" << endl;
|
|
cerr << "a call graph. This call graph is used to `score' arbitrary symbol" << endl;
|
|
cerr << "orderings, and provides the fitness function for the GA." << endl;
|
|
cerr << endl;
|
|
}
|
|
|
|
/**
|
|
* Using the symbol table, map a stream of address references into a
|
|
* callgraph and a histogram.
|
|
*/
|
|
static void
|
|
map_addrs(int fd)
|
|
{
|
|
const Elf32_Sym *last = 0;
|
|
unsigned int buf[128];
|
|
ssize_t cb;
|
|
|
|
unsigned int count = 0;
|
|
while ((cb = read(fd, buf, sizeof buf)) > 0) {
|
|
if (cb % sizeof buf[0])
|
|
fprintf(stderr, "unaligned read\n");
|
|
|
|
unsigned int *addr = buf;
|
|
unsigned int *limit = buf + (cb / 4);
|
|
|
|
for (; addr < limit; ++addr) {
|
|
const Elf32_Sym *sym = symtab.lookup(*addr);
|
|
|
|
if (last && sym && last != sym) {
|
|
++total_calls;
|
|
++histogram[sym];
|
|
++call_graph[call_pair(last, sym)];
|
|
|
|
if (opt_tick && (++count % opt_tick == 0)) {
|
|
cerr << ".";
|
|
flush(cerr);
|
|
}
|
|
}
|
|
|
|
last = sym;
|
|
}
|
|
}
|
|
|
|
if (opt_tick)
|
|
cerr << endl;
|
|
|
|
cerr << "Total calls: " << total_calls << endl;
|
|
total_calls *= 1024;
|
|
|
|
if (opt_window)
|
|
total_calls <<= (opt_window + 1);
|
|
}
|
|
|
|
static symbol_order *
|
|
pick_parent(symbol_order *ordering, int max, int index)
|
|
{
|
|
while (1) {
|
|
index -= ordering->m_score;
|
|
if (index < 0)
|
|
break;
|
|
|
|
++ordering;
|
|
}
|
|
|
|
return ordering;
|
|
}
|
|
|
|
/**
|
|
* The main program
|
|
*/
|
|
int
|
|
main(int argc, char *argv[])
|
|
{
|
|
const char *opt_exe = 0;
|
|
|
|
int c;
|
|
while (1) {
|
|
int option_index = 0;
|
|
c = getopt_long(argc, argv, "?de:g:m:o:p:s:t:vw:", long_options, &option_index);
|
|
|
|
if (c < 0)
|
|
break;
|
|
|
|
switch (c) {
|
|
case '?':
|
|
usage(argv[0]);
|
|
return 0;
|
|
|
|
case 'd':
|
|
opt_debug = true;
|
|
break;
|
|
|
|
case 'e':
|
|
opt_exe = optarg;
|
|
break;
|
|
|
|
case 'g':
|
|
opt_generations = atoi(optarg);
|
|
break;
|
|
|
|
case 'm':
|
|
opt_mutate = atoi(optarg);
|
|
break;
|
|
|
|
case 'o':
|
|
opt_out = optarg;
|
|
break;
|
|
|
|
case 'p':
|
|
opt_population_size = atoi(optarg);
|
|
break;
|
|
|
|
case 's':
|
|
srand(atoi(optarg));
|
|
break;
|
|
|
|
case 't':
|
|
opt_tick = optarg ? atoi(optarg) : 1000000;
|
|
break;
|
|
|
|
case 'v':
|
|
opt_verbose = true;
|
|
break;
|
|
|
|
case 'w':
|
|
opt_window = atoi(optarg);
|
|
if (opt_window < 0 || opt_window > 8) {
|
|
cerr << "invalid window size: " << opt_window << endl;
|
|
return 1;
|
|
}
|
|
|
|
break;
|
|
|
|
default:
|
|
usage(argv[0]);
|
|
return 1;
|
|
}
|
|
}
|
|
|
|
// Make sure an image was specified
|
|
if (! opt_exe) {
|
|
usage(argv[0]);
|
|
return 1;
|
|
}
|
|
|
|
// Read the sym table.
|
|
symtab.init(opt_exe);
|
|
|
|
// Process addresses to construct the call graph.
|
|
if (optind >= argc) {
|
|
map_addrs(STDIN_FILENO);
|
|
}
|
|
else {
|
|
do {
|
|
int fd = open(argv[optind], O_RDONLY);
|
|
if (fd < 0) {
|
|
perror(argv[optind]);
|
|
return 1;
|
|
}
|
|
|
|
map_addrs(fd);
|
|
close(fd);
|
|
} while (++optind < argc);
|
|
}
|
|
|
|
if (opt_debug) {
|
|
cerr << "Call graph:" << endl;
|
|
|
|
call_graph_t::const_iterator limit = call_graph.end();
|
|
call_graph_t::const_iterator i;
|
|
for (i = call_graph.begin(); i != limit; ++i) {
|
|
const call_pair& pair = i->first;
|
|
cerr.form("%08x %08x %10d\n",
|
|
pair.m_lo->st_value,
|
|
pair.m_hi->st_value,
|
|
i->second);
|
|
}
|
|
}
|
|
|
|
// Collect the symbols into a vector
|
|
symbol_order::vector_t ordering;
|
|
elf_symbol_table::const_iterator end = symtab.end();
|
|
for (elf_symbol_table::const_iterator sym = symtab.begin(); sym != end; ++sym) {
|
|
if (symtab.is_function(sym))
|
|
ordering.push_back(sym);
|
|
}
|
|
|
|
if (opt_verbose) {
|
|
symbol_order initial;
|
|
initial.m_ordering = ordering;
|
|
cerr << "created initial ordering, score=" << symbol_order::compute_score(initial) << endl;
|
|
|
|
if (opt_debug)
|
|
cerr << initial;
|
|
}
|
|
|
|
// Create a population.
|
|
if (opt_verbose)
|
|
cerr << "creating population" << endl;
|
|
|
|
symbol_order *population = new symbol_order[opt_population_size];
|
|
|
|
symbol_order::score_t total = 0, min = symbol_order::max_score, max = 0;
|
|
|
|
// Score it.
|
|
symbol_order *order = population;
|
|
symbol_order *limit = population + opt_population_size;
|
|
for (; order < limit; ++order) {
|
|
order->m_ordering = ordering;
|
|
order->shuffle();
|
|
|
|
symbol_order::score_t score = symbol_order::compute_score(*order);
|
|
|
|
if (opt_debug)
|
|
cerr << *order;
|
|
|
|
if (min > score)
|
|
min = score;
|
|
if (max < score)
|
|
max = score;
|
|
|
|
total += score;
|
|
}
|
|
|
|
if (opt_verbose) {
|
|
cerr << "Initial population";
|
|
cerr << ": min=" << min;
|
|
cerr << ", max=" << max;
|
|
cerr << " mean=" << (total / opt_population_size);
|
|
cerr << endl;
|
|
}
|
|
|
|
|
|
// Run the GA.
|
|
if (opt_verbose)
|
|
cerr << "begininng ga" << endl;
|
|
|
|
symbol_order::score_t best = 0;
|
|
|
|
for (int generation = 1; generation <= opt_generations; ++generation) {
|
|
// Create a new population.
|
|
symbol_order *offspring = new symbol_order[opt_population_size];
|
|
|
|
symbol_order *kid = offspring;
|
|
symbol_order *offspring_limit = offspring + opt_population_size;
|
|
for (; kid < offspring_limit; ++kid) {
|
|
// Pick parents.
|
|
symbol_order *father, *mother;
|
|
father = pick_parent(population, max, llrand() % total);
|
|
mother = pick_parent(population, max, llrand() % total);
|
|
|
|
// Create a kid.
|
|
kid->crossover_from(father, mother);
|
|
|
|
// Mutate, possibly.
|
|
if (opt_mutate) {
|
|
if (rand() % opt_mutate == 0)
|
|
kid->mutate();
|
|
}
|
|
}
|
|
|
|
delete[] population;
|
|
population = offspring;
|
|
|
|
// Score the new population.
|
|
total = 0;
|
|
min = symbol_order::max_score;
|
|
max = 0;
|
|
|
|
symbol_order *fittest = 0;
|
|
|
|
limit = offspring_limit;
|
|
for (order = population; order < limit; ++order) {
|
|
symbol_order::score_t score = symbol_order::compute_score(*order);
|
|
|
|
if (opt_debug)
|
|
cerr << *order;
|
|
|
|
if (min > score)
|
|
min = score;
|
|
|
|
if (max < score)
|
|
max = score;
|
|
|
|
if (best < score) {
|
|
best = score;
|
|
fittest = order;
|
|
}
|
|
|
|
total += score;
|
|
}
|
|
|
|
if (opt_verbose) {
|
|
cerr << "Generation " << generation;
|
|
cerr << ": min=" << min;
|
|
cerr << ", max=" << max;
|
|
if (fittest)
|
|
cerr << "*";
|
|
cerr << " mean=" << (total / opt_population_size);
|
|
cerr << endl;
|
|
}
|
|
|
|
// If we've found a new ``best'' individual, dump it.
|
|
if (fittest)
|
|
fittest->dump_symbols();
|
|
}
|
|
|
|
delete[] population;
|
|
return 0;
|
|
}
|