cfg_bmf_max_iteration("bmf/max-iterations",
"Maximum number of steps to be performed while searching for a BMF allocation", 1000);
-simgrid::config::Flag<bool> cfg_bmf_selective_update{
- "bmf/selective-update", "Update the constraint set propagating recursively to others constraints (off by default)",
- false};
+simgrid::config::Flag<double> cfg_bmf_precision{"bmf/precision",
+ "Numerical precision used when computing resource sharing", 1E-12};
namespace simgrid {
namespace kernel {
return std::max(0.0, capacity);
}
-double BmfSolver::get_maxmin_share(int resource) const
+double BmfSolver::get_maxmin_share(int resource, const std::vector<int>& bounded_players) const
{
- auto n_players = (A_.row(resource).array() > 0).count();
- return C_[resource] / n_players;
+ auto n_players = (A_.row(resource).array() > 0).count() - bounded_players.size();
+ double capacity = get_resource_capacity(resource, bounded_players);
+ if (n_players > 0)
+ capacity /= n_players;
+ return capacity;
}
std::vector<int> BmfSolver::alloc_map_to_vector(const allocation_map_t& alloc) const
alloc.clear();
for (int player_idx = 0; player_idx < A_.cols(); player_idx++) {
int selected_resource = NO_RESOURCE;
- double bound = phi_[player_idx];
+
/* the player's maximal rate is the minimum among all resources */
- double min_rate = (bound <= 0 || initial) ? -1 : bound;
+ double min_rate = -1;
for (int cnst_idx = 0; cnst_idx < A_.rows(); cnst_idx++) {
if (A_(cnst_idx, player_idx) <= 0.0)
continue;
+ /* Note: the max_ may artificially increase the rate if priority < 0
+ * The equilibrium sets a rho which respects the C_ though */
double rate = fair_sharing[cnst_idx] / maxA_(cnst_idx, player_idx);
- if (min_rate == -1 || rate < min_rate) {
+ if (min_rate == -1 || double_positive(min_rate - rate, cfg_bmf_precision)) {
selected_resource = cnst_idx;
min_rate = rate;
}
+ double bound = initial ? -1 : phi_[player_idx];
+ /* Given that the priority may artificially increase the rate,
+ * we need to check that the bound given by user respects the resource capacity C_ */
+ if (bound > 0 && bound * A_(cnst_idx, player_idx) < C_[cnst_idx] &&
+ double_positive(min_rate - bound, cfg_bmf_precision)) {
+ selected_resource = NO_RESOURCE;
+ min_rate = bound;
+ }
}
alloc[selected_resource].insert(player_idx);
}
return true;
std::vector<int> alloc_by_player = alloc_map_to_vector(alloc);
- auto ret = allocations_.insert(alloc_by_player);
+ bool inserted = allocations_.insert(alloc_by_player).second;
/* oops, allocation already tried, let's pertube it a bit */
- if (not ret.second) {
+ if (not inserted) {
XBT_DEBUG("Allocation already tried: %s", debug_alloc(alloc).c_str());
return disturb_allocation(alloc, alloc_by_player);
}
void BmfSolver::set_fair_sharing(const allocation_map_t& alloc, const Eigen::VectorXd& rho,
Eigen::VectorXd& fair_sharing) const
{
+ std::vector<int> bounded_players = get_bounded_players(alloc);
+
for (int r = 0; r < fair_sharing.size(); r++) {
auto it = alloc.find(r);
- if (it != alloc.end()) { // resource selected by some player, fair share depends on rho
- int player = *(it->second.begin()); // equilibrium assures that every player receives the same, use one of them to
- // calculate the fair sharing for resource r
- fair_sharing[r] = maxA_(r, player) * rho[player];
+ if (it != alloc.end()) { // resource selected by some player, fair share depends on rho
+ double min_share = std::numeric_limits<double>::max();
+ for (int p : it->second) {
+ double share = A_(r, p) * rho[p];
+ min_share = std::min(min_share, share);
+ }
+ fair_sharing[r] = min_share;
} else { // nobody selects this resource, fair_sharing depends on resource saturation
// resource r is saturated (A[r,*] * rho > C), divide it among players
double consumption_r = A_.row(r) * rho;
- double_update(&consumption_r, C_[r], sg_maxmin_precision);
+ double_update(&consumption_r, C_[r], cfg_bmf_precision);
if (consumption_r > 0.0) {
- fair_sharing[r] = get_maxmin_share(r);
+ fair_sharing[r] = get_maxmin_share(r, bounded_players);
} else {
fair_sharing[r] = C_[r];
}
fprintf(stderr, "Unable to find a BMF allocation for your system.\n"
"You may try to increase the maximum number of iterations performed by BMF solver "
"(\"--cfg=bmf/max-iterations\").\n"
- "Additionally, you could decrease numerical precision (\"--cfg=surf/precision\").\n");
+ "Additionally, you could adjust numerical precision (\"--cfg=bmf/precision\").\n");
fprintf(stderr, "Internal states (after %d iterations):\n", it);
fprintf(stderr, "A:\n%s\n", debug_eigen(A_).c_str());
fprintf(stderr, "maxA:\n%s\n", debug_eigen(maxA_).c_str());
C(cnst_idx) = cnst.bound_;
if (cnst.get_sharing_policy() == Constraint::SharingPolicy::NONLINEAR && cnst.dyn_constraint_cb_) {
C(cnst_idx) = cnst.dyn_constraint_cb_(cnst.bound_, cnst.concurrency_current_);
- if (not warned_nonlinear_) {
- XBT_WARN("You are using dynamic constraint bound with parallel tasks and BMF model."
- " The BMF solver assumes that all flows (and subflows) are always active and executing."
- " This is quite pessimist, specially considering parallel tasks with small subflows."
- " Analyze your results with caution.");
- warned_nonlinear_ = true;
- }
}
cnst2idx_[&cnst] = cnst_idx;
// FATPIPE links aren't really shared
template <class CnstList> void BmfSystem::bmf_solve(const CnstList& cnst_list)
{
- /* initialize players' weight and constraint matrices */
idx2Var_.clear();
cnst2idx_.clear();
Eigen::MatrixXd A;
