/**
* 2-sieve
*/
template <class ZT, class F> bool GaussSieve<ZT, F>::run_2sieve()
{
ListPoint<ZT> *current_point;
NumVect<Z_NR<ZT>> vec(nc);
Z_NR<ZT> current_norm;
#ifdef REDUCE_TIMING
struct timeval time, time2;
gettimeofday(&time, 0);
long startt = 1000000 * time.tv_sec + time.tv_usec;
double sec, sec2 = 0.0;
long nred = 0;
#endif
/*
Loop till you find a short enough vector,
or enough collisions. */
while ((best_sqr_norm > goal_sqr_norm) && (collisions < mult * max_list_size + add))
{
/* update stats */
iterations++;
max_list_size = max(max_list_size, long(List.size()));
/* sample new or fetch from queue */
if (Queue.empty())
{
vec = Sampler->sample();
current_point = num_vec_to_list_point(vec, nc);
samples++;
}
else
{
current_point = Queue.front();
Queue.pop();
}
#ifdef REDUCE_TIMING
gettimeofday(&time2, 0);
long startt2 = 1000000 * time2.tv_sec + time2.tv_usec;
nred++;
#endif
/* sieve current_point */
current_norm = update_p_2reduce(current_point);
//print_list(List);
#ifdef REDUCE_TIMING
gettimeofday(&time2, 0);
long endt2 = 1000000 * time2.tv_sec + time2.tv_usec;
sec2 += (endt2 - startt2) / 1000000.0;
#endif
/* record collisions */
if (current_norm == 0)
collisions++;
if (current_norm > 0 && current_norm < best_sqr_norm)
{
best_sqr_norm = current_norm;
}
#if 1
print_curr_info();
/*if (samples+nr-List.size()-Queue.size() != collisions)
exit(1);
*/
#endif
/* tuples of (iters, max_list_size) */
iters_norm.push_back(best_sqr_norm);
iters_ls.push_back(max_list_size);
}
#ifdef REDUCE_TIMING
gettimeofday(&time, 0);
long endt = 1000000 * time.tv_sec + time.tv_usec;
sec = (endt - startt) / 1000000.0;
cout << "# [info] total-reducuction time " << sec2;
cout << ", average-reducuction time " << sec2 / nred << " (" << nred << ")" << endl;
cout << "# [info] total time " << sec << endl;
#endif
/* finished main procedure, output some information */
print_final_info();
#ifdef DEBUG_CHECK_2RED
if (check_2reduce_order_list<ZT>(List))
cout << "# [info] check 2-reduced OK" << endl;
else
cout << "# Error: check 2-reduced not OK" << endl;
#endif
if (best_sqr_norm > goal_sqr_norm)
return false;
return true;
}
/**
* 4-sieve
*/
template <class ZT, class F> bool GaussSieve<ZT, F>::run_4sieve()
{
ListPoint<ZT> *current_point;
NumVect<Z_NR<ZT>> vec(nc);
Z_NR<ZT> current_norm;
/* main iteration */
while ((best_sqr_norm > target_sqr_norm) && (collisions < mult * max_list_size + 200))
{
iterations++;
max_list_size = max(max_list_size, long(List.size()));
if (Queue.empty())
{
vec = Sampler->sample();
current_point = num_vec_to_list_point(vec, nc);
samples++;
}
else
{
current_point = Queue.front();
Queue.pop();
}
current_norm = update_p_4reduce(current_point);
#if 0
if (!check_4reduce_order_list<ZT>(List)) {
cout << "!!! Failed " << endl;
//print_list(List);
exit(1);
}
else {
cout << "[check 4-red] OK " << endl;
//print_list(List);
}
#endif
if (current_norm == 0)
collisions++;
if (current_norm > 0 && current_norm < best_sqr_norm)
{
best_sqr_norm = current_norm;
}
#if 1
print_curr_info();
#endif
/* tuples of (iters, max_list_size) */
iters_norm.push_back(best_sqr_norm);
iters_ls.push_back(max_list_size);
}
/* finished main procedure, output some information */
print_final_info();
#ifdef DEBUG_CHECK_4RED
if (check_4reduce_order_list<ZT>(List))
cout << "# [info] check 4-reduced OK" << endl;
else
cout << "# Error: check 4-reduced not OK" << endl;
#endif
// print_list(List);
if (best_sqr_norm > target_sqr_norm)
return false;
return true;
}
