* under the terms of the license (GNU LGPL) which comes with this package. */
#include "src/kernel/lmm/bmf.hpp"
+#include "xbt/config.hpp"
+
#include <Eigen/LU>
#include <iostream>
#include <numeric>
XBT_LOG_NEW_DEFAULT_SUBCATEGORY(ker_bmf, kernel, "Kernel BMF solver");
-int sg_bmf_max_iterations = 1000; /* Change this with --cfg=bmf/max-iterations:VALUE */
+simgrid::config::Flag<int>
+ 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};
namespace simgrid {
namespace kernel {
return true;
}
- int n_resources = A_.rows();
+ auto n_resources = A_.rows();
size_t idx = 0;
while (idx < alloc_.size()) {
- alloc_[idx] = (++alloc_[idx]) % n_resources;
+ alloc_[idx] = (alloc_[idx] + 1) % n_resources;
if (alloc_[idx] == 0) {
idx++;
continue;
, C_shared_(std::move(shared))
, phi_(std::move(phi))
, gen_(A_)
+ , max_iteration_(cfg_bmf_max_iteration)
+
{
xbt_assert(max_iteration_ > 0,
"Invalid number of iterations for BMF solver. Please check your \"bmf/max-iterations\" configuration.");
return std::max(0.0, capacity);
}
+double BmfSolver::get_maxmin_share(int resource) const
+{
+ auto n_players = (A_.row(resource).array() > 0).count();
+ return C_[resource] / n_players;
+}
+
std::vector<int> BmfSolver::alloc_map_to_vector(const allocation_map_t& alloc) const
{
std::vector<int> alloc_by_player(A_.cols(), -1);
- for (auto it : alloc) {
+ for (const auto& it : alloc) {
for (auto p : it.second) {
alloc_by_player[p] = it.first;
}
Eigen::VectorXd BmfSolver::equilibrium(const allocation_map_t& alloc) const
{
- int n_players = A_.cols();
+ auto n_players = A_.cols();
Eigen::MatrixXd A_p = Eigen::MatrixXd::Zero(n_players, n_players); // square matrix with number of players
Eigen::VectorXd C_p = Eigen::VectorXd::Zero(n_players);
for (const auto& e : alloc) {
// add one row for the resource with A[r,]
int cur_resource = e.first;
+ /* bounded players, nothing to do */
if (cur_resource == NO_RESOURCE)
continue;
-
- if (C_shared_[cur_resource]) {
- /* shared resource: fairly share it between players */
- A_p.row(row) = A_.row(cur_resource);
- C_p[row] = get_resource_capacity(cur_resource, bounded_players);
- row++;
- if (e.second.size() > 1) {
- // if 2 players have chosen the same resource
- // they must have a fair sharing of this resource, adjust A_p and C_p accordingly
- auto it = e.second.begin();
- int i = *it; // first player
- /* for each other player sharing this resource */
- for (++it; it != e.second.end(); ++it) {
- /* player i and k on this resource j: so maxA_ji*rho_i - maxA_jk*rho_k = 0 */
- int k = *it;
- C_p[row] = 0;
- A_p(row, i) = maxA_(cur_resource, i);
- A_p(row, k) = -maxA_(cur_resource, k);
- row++;
- }
- }
- } else {
- /* not shared resource, each player can receive the full capacity of the resource */
+ /* not shared resource, each player can receive the full capacity of the resource */
+ if (not C_shared_[cur_resource]) {
for (int i : e.second) {
C_p[row] = get_resource_capacity(cur_resource, bounded_players);
A_p(row, i) = A_(cur_resource, i);
row++;
}
+ continue;
+ }
+
+ /* shared resource: fairly share it between players */
+ A_p.row(row) = A_.row(cur_resource);
+ C_p[row] = get_resource_capacity(cur_resource, bounded_players);
+ row++;
+ if (e.second.size() > 1) {
+ // if 2 players have chosen the same resource
+ // they must have a fair sharing of this resource, adjust A_p and C_p accordingly
+ auto it = e.second.begin();
+ int i = *it; // first player
+ /* for each other player sharing this resource */
+ for (++it; it != e.second.end(); ++it) {
+ /* player i and k on this resource j: so maxA_ji*rho_i - maxA_jk*rho_k = 0 */
+ int k = *it;
+ C_p[row] = 0;
+ A_p(row, i) = maxA_(cur_resource, i);
+ A_p(row, k) = -maxA_(cur_resource, k);
+ row++;
+ }
}
}
/* clear players which are externally bounded */
XBT_DEBUG("A':\n%s", debug_eigen(A_p).c_str());
XBT_DEBUG("C':\n%s", debug_eigen(C_p).c_str());
- /* Being optimist, PartialPivLU is much faster than FullPivLU but requires that the matrix is invertible
- * FullPivLU however assures that it finds come solution even if the matrix is singular */
- Eigen::VectorXd rho = Eigen::PartialPivLU<Eigen::MatrixXd>(A_p).solve(C_p);
- if (rho.array().isNaN().any()) {
- XBT_DEBUG("rho with nan values, falling back to FullPivLU, rho:\n%s", debug_eigen(rho).c_str());
- rho = Eigen::FullPivLU<Eigen::MatrixXd>(A_p).solve(C_p);
- }
-
+ /* PartialPivLU is much faster than FullPivLU but requires that the matrix is invertible
+ * FullPivLU however assures that it finds come solution even if the matrix is singular
+ * Ideally we would like to be optimist and try Partial and in case of error, go back
+ * to FullPivLU.
+ * However, this with isNaN doesn't work if compiler uses -Ofastmath. In our case,
+ * the icc compiler raises an error when compiling the code (comparison with NaN always evaluates to false in fast
+ * floating point modes).
+ * Eigen::VectorXd rho = Eigen::PartialPivLU<Eigen::MatrixXd>(A_p).solve(C_p);
+ * if (rho.array().isNaN().any()) {
+ * XBT_DEBUG("rho with nan values, falling back to FullPivLU, rho:\n%s", debug_eigen(rho).c_str());
+ * rho = Eigen::FullPivLU<Eigen::MatrixXd>(A_p).solve(C_p);
+ * }
+ */
+
+ Eigen::VectorXd rho = Eigen::FullPivLU<Eigen::MatrixXd>(A_p).solve(C_p);
for (int p : bounded_players) {
rho[p] = phi_[p];
}
for (int player_idx = 0; player_idx < A_.cols(); player_idx++) {
int selected_resource = NO_RESOURCE;
double bound = phi_[player_idx];
- double min_share = (bound <= 0 || initial) ? -1 : bound;
+ /* the player's maximal rate is the minimum among all resources */
+ double min_rate = (bound <= 0 || initial) ? -1 : bound;
for (int cnst_idx = 0; cnst_idx < A_.rows(); cnst_idx++) {
if (A_(cnst_idx, player_idx) <= 0.0)
continue;
- double share = fair_sharing[cnst_idx] / A_(cnst_idx, player_idx);
- if (min_share == -1 || share < min_share) {
-
+ double rate = fair_sharing[cnst_idx] / maxA_(cnst_idx, player_idx);
+ if (min_rate == -1 || rate < min_rate) {
selected_resource = cnst_idx;
- min_share = share;
+ min_rate = rate;
}
}
alloc[selected_resource].insert(player_idx);
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] = A_(r, player) * rho[player];
+ if (rho[player] < 0) { // negative rho doesn't make sense, consider the resource is saturated in this case
+ fair_sharing[r] = get_maxmin_share(r);
+ } else {
+ fair_sharing[r] = maxA_(r, player) * rho[player];
+ }
} 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);
if (consumption_r > 0.0) {
- int n_players = (A_.row(r).array() > 0).count();
- fair_sharing[r] = C_[r] / n_players;
+ fair_sharing[r] = get_maxmin_share(r);
} else {
fair_sharing[r] = get_resource_capacity(r, bounded_players);
}
Eigen::MatrixXi player_max_share =
((usage.array().colwise() - max_share.array()).abs() <= sg_maxmin_precision).cast<int>();
// but only saturated resources must be considered
- Eigen::VectorXi saturated = ((remaining.array().abs() <= sg_maxmin_precision)).cast<int>();
+ Eigen::VectorXi saturated = (remaining.array().abs() <= sg_maxmin_precision).cast<int>();
XBT_DEBUG("Saturated_j resources:\n%s", debug_eigen(saturated).c_str());
player_max_share.array().colwise() *= saturated.array();
XBT_DEBUG("Player_ji usage of saturated resources:\n%s", debug_eigen(player_max_share).c_str());
// for all columns(players) it has to be the max at least in 1
- bmf = bmf && (player_max_share.colwise().sum().all() >= 1);
+ bmf = bmf && (player_max_share.colwise().sum().array() >= 1).all();
return bmf;
}
auto fair_sharing = C_;
/* BMF allocation for each player (current and last one) stop when are equal */
- allocation_map_t last_alloc, cur_alloc;
+ allocation_map_t last_alloc;
+ allocation_map_t cur_alloc;
Eigen::VectorXd rho;
while (it < max_iteration_ && not get_alloc(fair_sharing, last_alloc, cur_alloc, it == 0)) {
/*****************************************************************************/
-void BmfSystem::get_flows_data(int number_cnsts, Eigen::MatrixXd& A, Eigen::MatrixXd& maxA, Eigen::VectorXd& phi)
+void BmfSystem::get_flows_data(Eigen::Index number_cnsts, Eigen::MatrixXd& A, Eigen::MatrixXd& maxA,
+ Eigen::VectorXd& phi)
{
A.resize(number_cnsts, variable_set.size());
A.setZero();
bool active = false;
bool linked = false; // variable is linked to some constraint (specially for selective_update)
for (const Element& elem : var.cnsts_) {
- boost::intrusive::list_member_hook<>& cnst_hook = selective_update_active
- ? elem.constraint->modified_constraint_set_hook_
- : elem.constraint->active_constraint_set_hook_;
+ const boost::intrusive::list_member_hook<>& cnst_hook = selective_update_active
+ ? elem.constraint->modified_constraint_set_hook_
+ : elem.constraint->active_constraint_set_hook_;
if (not cnst_hook.is_linked())
continue;
/* active and linked variable, lets check its consumption */
}
}
-void BmfSystem::solve()
+void BmfSystem::do_solve()
{
- if (modified_) {
- if (selective_update_active)
- bmf_solve(modified_constraint_set);
- else
- bmf_solve(active_constraint_set);
- }
+ if (selective_update_active)
+ bmf_solve(modified_constraint_set);
+ else
+ bmf_solve(active_constraint_set);
}
template <class CnstList> void BmfSystem::bmf_solve(const CnstList& cnst_list)
/* initialize players' weight and constraint matrices */
idx2Var_.clear();
cnst2idx_.clear();
- Eigen::MatrixXd A, maxA;
- Eigen::VectorXd C, bounds;
+ Eigen::MatrixXd A;
+ Eigen::MatrixXd maxA;
+ Eigen::VectorXd C;
+ Eigen::VectorXd bounds;
std::vector<bool> shared;
get_constraint_data(cnst_list, C, shared);
get_flows_data(C.size(), A, maxA, bounds);
for (int i = 0; i < rho.size(); i++) {
idx2Var_[i]->value_ = rho[i];
}
-
- print();
}
} // namespace lmm
