* under the terms of the license (GNU LGPL) which comes with this package. */
#include "src/kernel/lmm/bmf.hpp"
-#include <eigen3/Eigen/LU>
+#include "xbt/config.hpp"
+
+#include <Eigen/LU>
#include <iostream>
+#include <numeric>
#include <sstream>
XBT_LOG_NEW_DEFAULT_SUBCATEGORY(ker_bmf, kernel, "Kernel BMF solver");
-void simgrid::kernel::lmm::BmfSystem::set_matrix_A()
-{
- A_.resize(active_constraint_set.size(), variable_set.size());
- A_.setZero();
- maxA_.resize(active_constraint_set.size(), variable_set.size());
+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);
- int var_idx = 0;
- for (Variable& var : variable_set) {
- if (var.sharing_penalty_ <= 0)
- continue;
- bool active = false;
- var.value_ = 1; // assign something by default for tasks with 0 consumption
- for (const Element& elem : var.cnsts_) {
- double consumption = elem.consumption_weight;
- if (consumption > 0) {
- int cnst_idx = cnst2idx_[elem.constraint];
- A_(cnst_idx, var_idx) = consumption;
- maxA_(cnst_idx, var_idx) = elem.max_consumption_weight;
- active = true;
+simgrid::config::Flag<double> cfg_bmf_precision{"bmf/precision",
+ "Numerical precision used when computing resource sharing", 1E-12};
+
+namespace simgrid {
+namespace kernel {
+namespace lmm {
+
+AllocationGenerator::AllocationGenerator(Eigen::MatrixXd A) : A_(std::move(A)), alloc_(A_.cols(), 0)
+{
+ // got a first valid allocation
+ for (size_t p = 0; p < alloc_.size(); p++) {
+ for (int r = 0; r < A_.rows(); r++) {
+ if (A_(r, p) > 0) {
+ alloc_[p] = r;
+ break;
}
}
- if (active) {
- idx2Var_[var_idx] = &var;
- var_idx++;
- }
}
- // resize matrix to active variables only
- A_.conservativeResize(Eigen::NoChange_t::NoChange, var_idx);
- maxA_.conservativeResize(Eigen::NoChange_t::NoChange, var_idx);
}
-void simgrid::kernel::lmm::BmfSystem::set_vector_C()
+bool AllocationGenerator::next(std::vector<int>& next_alloc)
{
- C_.resize(active_constraint_set.size());
- cnst2idx_.clear();
- int cnst_idx = 0;
- for (const Constraint& cnst : active_constraint_set) {
- C_(cnst_idx) = cnst.bound_;
- cnst2idx_[&cnst] = cnst_idx;
- cnst_idx++;
+ if (first_) {
+ next_alloc = alloc_;
+ first_ = false;
+ return true;
}
-}
-std::unordered_map<int, std::vector<int>>
-simgrid::kernel::lmm::BmfSystem::get_alloc(const Eigen::VectorXd& fair_sharing) const
-{
- std::unordered_map<int, std::vector<int>> alloc;
- for (int player_idx = 0; player_idx < A_.cols(); player_idx++) {
- int selected_resource = -1;
- double min_share = 0;
- 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 (selected_resource == -1 || double_positive(min_share - share, sg_maxmin_precision)) {
- selected_resource = cnst_idx;
- min_share = share;
- }
+ auto n_resources = A_.rows();
+ size_t idx = 0;
+ while (idx < alloc_.size()) {
+ alloc_[idx] = (alloc_[idx] + 1) % n_resources;
+ if (alloc_[idx] == 0) {
+ idx++;
+ continue;
+ } else {
+ idx = 0;
+ }
+ if (A_(alloc_[idx], idx) > 0) {
+ next_alloc = alloc_;
+ return true;
}
- alloc[selected_resource].push_back(player_idx);
}
- return alloc;
+ return false;
}
-void simgrid::kernel::lmm::BmfSystem::set_fair_sharing(const std::unordered_map<int, std::vector<int>>& alloc,
- const Eigen::VectorXd& rho, Eigen::VectorXd& fair_sharing) const
+/*****************************************************************************/
+
+BmfSolver::BmfSolver(Eigen::MatrixXd A, Eigen::MatrixXd maxA, Eigen::VectorXd C, std::vector<bool> shared,
+ Eigen::VectorXd phi)
+ : A_(std::move(A))
+ , maxA_(std::move(maxA))
+ , C_(std::move(C))
+ , C_shared_(std::move(shared))
+ , phi_(std::move(phi))
+ , gen_(A_)
+ , max_iteration_(cfg_bmf_max_iteration)
+
{
- 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[0]; // 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];
- } 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 = std::count_if(A_.row(r).data(), A_.row(r).data() + A_.row(r).size(),
- [](double v) { return double_positive(v, sg_maxmin_precision); });
- fair_sharing[r] = C_[r] / n_players;
- } else {
- fair_sharing[r] = C_[r];
- }
- }
- }
+ xbt_assert(max_iteration_ > 0,
+ "Invalid number of iterations for BMF solver. Please check your \"bmf/max-iterations\" configuration.");
+ xbt_assert(A_.cols() == maxA_.cols(), "Invalid number of cols in matrix A (%td) or maxA (%td)", A_.cols(),
+ maxA_.cols());
+ xbt_assert(A_.cols() == phi_.size(), "Invalid size of phi vector (%td)", phi_.size());
+ xbt_assert(static_cast<long>(C_shared_.size()) == C_.size(), "Invalid size param shared (%zu)", C_shared_.size());
}
-template <typename T> std::string simgrid::kernel::lmm::BmfSystem::debug_eigen(const T& obj) const
+template <typename T> std::string BmfSolver::debug_eigen(const T& obj) const
{
std::stringstream debug;
debug << obj;
return debug.str();
}
-template <typename T> std::string simgrid::kernel::lmm::BmfSystem::debug_vector(const std::vector<T>& vector) const
+template <typename C> std::string BmfSolver::debug_vector(const C& container) const
{
std::stringstream debug;
- std::copy(vector.begin(), vector.end(), std::ostream_iterator<T>(debug, " "));
+ std::copy(container.begin(), container.end(),
+ std::ostream_iterator<typename std::remove_reference<decltype(container)>::type::value_type>(debug, " "));
return debug.str();
}
-std::string simgrid::kernel::lmm::BmfSystem::debug_alloc(const std::unordered_map<int, std::vector<int>>& alloc) const
+std::string BmfSolver::debug_alloc(const allocation_map_t& alloc) const
{
std::stringstream debug;
for (const auto& e : alloc) {
return debug.str();
}
-Eigen::VectorXd
-simgrid::kernel::lmm::BmfSystem::equilibrium(const std::unordered_map<int, std::vector<int>>& alloc) const
+double BmfSolver::get_resource_capacity(int resource, const std::vector<int>& bounded_players) const
{
- int n_players = A_.cols();
+ double capacity = C_[resource];
+ if (not C_shared_[resource])
+ return capacity;
+
+ for (int p : bounded_players) {
+ capacity -= A_(resource, p) * phi_[p];
+ }
+ return std::max(0.0, capacity);
+}
+
+double BmfSolver::get_maxmin_share(int resource, const std::vector<int>& bounded_players) const
+{
+ 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
+{
+ std::vector<int> alloc_by_player(A_.cols(), -1);
+ for (const auto& it : alloc) {
+ for (auto p : it.second) {
+ alloc_by_player[p] = it.first;
+ }
+ }
+ return alloc_by_player;
+}
+
+std::vector<int> BmfSolver::get_bounded_players(const allocation_map_t& alloc) const
+{
+ std::vector<int> bounded_players;
+ for (const auto& e : alloc) {
+ if (e.first == NO_RESOURCE) {
+ bounded_players.insert(bounded_players.end(), e.second.begin(), e.second.end());
+ }
+ }
+ return bounded_players;
+}
+
+Eigen::VectorXd BmfSolver::equilibrium(const allocation_map_t& alloc) const
+{
+ 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);
- // iterate over alloc to verify if 2 players have chosen the same resource
- // if so, they must have a fair sharing of this resource, adjust A_p and C_p accordingly
- int last_row = n_players - 1;
- int first_row = 0;
+ int row = 0;
+ auto bounded_players = get_bounded_players(alloc);
for (const auto& e : alloc) {
// add one row for the resource with A[r,]
- int cur_resource = e.first;
- A_p.row(first_row) = A_.row(cur_resource);
- C_p[first_row] = C_[cur_resource];
- first_row++;
+ int cur_resource = e.first;
+ /* bounded players, nothing to do */
+ if (cur_resource == NO_RESOURCE)
+ continue;
+ /* 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) {
- int i = e.second[0]; // first player
- for (size_t idx = 1; idx < e.second.size(); idx++) { // for each other player sharing this resource
+ // 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 = e.second[idx];
- C_p[last_row] = 0;
- A_p(last_row, i) = maxA_(cur_resource, i);
- A_p(last_row, k) = -maxA_(cur_resource, k);
- last_row--;
+ 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 */
+ for (int p : bounded_players) {
+ A_p.col(p).setZero();
+ }
XBT_DEBUG("A':\n%s", debug_eigen(A_p).c_str());
XBT_DEBUG("C':\n%s", debug_eigen(C_p).c_str());
- return 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];
+ }
+ return rho;
+}
+
+bool BmfSolver::disturb_allocation(allocation_map_t& alloc, std::vector<int>& alloc_by_player)
+{
+ while (gen_.next(alloc_by_player)) {
+ if (allocations_.find(alloc_by_player) == allocations_.end()) {
+ allocations_.clear();
+ allocations_.insert(alloc_by_player);
+ alloc.clear();
+ for (size_t p = 0; p < alloc_by_player.size(); p++) {
+ alloc[alloc_by_player[p]].insert(p);
+ }
+ return false;
+ }
+ }
+ return true;
}
-bool simgrid::kernel::lmm::BmfSystem::is_bmf(const Eigen::VectorXd& rho) const
+bool BmfSolver::get_alloc(const Eigen::VectorXd& fair_sharing, const allocation_map_t& last_alloc,
+ allocation_map_t& alloc, bool initial)
+{
+ alloc.clear();
+ for (int player_idx = 0; player_idx < A_.cols(); player_idx++) {
+ int selected_resource = NO_RESOURCE;
+
+ /* the player's maximal rate is the minimum among all resources */
+ 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 || 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);
+ }
+ bool is_stable = (alloc == last_alloc);
+ if (is_stable)
+ return true;
+
+ std::vector<int> alloc_by_player = alloc_map_to_vector(alloc);
+ bool inserted = allocations_.insert(alloc_by_player).second;
+ /* oops, allocation already tried, let's pertube it a bit */
+ if (not inserted) {
+ XBT_DEBUG("Allocation already tried: %s", debug_alloc(alloc).c_str());
+ return disturb_allocation(alloc, alloc_by_player);
+ }
+ return false;
+}
+
+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
+ 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], cfg_bmf_precision);
+ if (consumption_r > 0.0) {
+ fair_sharing[r] = get_maxmin_share(r, bounded_players);
+ } else {
+ fair_sharing[r] = C_[r];
+ }
+ }
+ }
+}
+
+bool BmfSolver::is_bmf(const Eigen::VectorXd& rho) const
{
bool bmf = true;
// 1) the capacity of all resources is respected
+ Eigen::VectorXd shared(C_shared_.size());
+ for (int j = 0; j < shared.size(); j++)
+ shared[j] = C_shared_[j] ? 1.0 : 0.0;
+
Eigen::VectorXd remaining = (A_ * rho) - C_;
+ remaining = remaining.array() * shared.array(); // ignore non shared resources
bmf = bmf && (not std::any_of(remaining.data(), remaining.data() + remaining.size(),
[](double v) { return double_positive(v, sg_maxmin_precision); }));
- // 2) at least 1 resource is saturated
- bmf = bmf && (std::any_of(remaining.data(), remaining.data() + remaining.size(),
- [](double v) { return double_equals(v, 0.0, sg_maxmin_precision); }));
// 3) every player receives maximum share in at least 1 saturated resource
// due to subflows, compare with the maximum consumption and not the A matrix
Eigen::MatrixXd usage =
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();
+ // just check if it has received at least it's bound
+ for (int p = 0; p < rho.size(); p++) {
+ if (double_equals(rho[p], phi_[p], sg_maxmin_precision)) {
+ player_max_share(0, p) = 1; // it doesn't really matter, just to say that it's a bmf
+ saturated[0] = 1;
+ }
+ }
+
+ // 2) at least 1 resource is saturated
+ bmf = bmf && (saturated.array() == 1).any();
+
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;
}
-void simgrid::kernel::lmm::BmfSystem::bottleneck_solve()
+Eigen::VectorXd BmfSolver::solve()
{
- if (not modified_)
- return;
+ XBT_DEBUG("Starting BMF solver");
- /* initialize players' weight and constraint matrices */
- set_vector_C();
- set_matrix_A();
XBT_DEBUG("A:\n%s", debug_eigen(A_).c_str());
+ XBT_DEBUG("maxA:\n%s", debug_eigen(maxA_).c_str());
XBT_DEBUG("C:\n%s", debug_eigen(C_).c_str());
+ XBT_DEBUG("phi:\n%s", debug_eigen(phi_).c_str());
/* no flows to share, just returns */
if (A_.cols() == 0)
- return;
+ return {};
int it = 0;
auto fair_sharing = C_;
/* BMF allocation for each player (current and last one) stop when are equal */
- std::unordered_map<int, std::vector<int>> last_alloc;
- auto cur_alloc = get_alloc(fair_sharing);
+ allocation_map_t last_alloc;
+ allocation_map_t cur_alloc;
Eigen::VectorXd rho;
- while (it < max_iteration_ && last_alloc != cur_alloc) {
+
+ while (it < max_iteration_ && not get_alloc(fair_sharing, last_alloc, cur_alloc, it == 0)) {
last_alloc = cur_alloc;
XBT_DEBUG("BMF: iteration %d", it);
XBT_DEBUG("B (current allocation): %s", debug_alloc(cur_alloc).c_str());
XBT_DEBUG("Fair sharing vector (per resource):\n%s", debug_eigen(fair_sharing).c_str());
// get new allocation for players
- cur_alloc = get_alloc(fair_sharing);
- XBT_DEBUG("B (new allocation): %s", debug_alloc(cur_alloc).c_str());
it++;
}
- xbt_assert(is_bmf(rho), "Not a BMF allocation");
+ /* Not mandatory but a safe check to assure we have a proper solution */
+ if (not is_bmf(rho)) {
+ 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 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());
+ fprintf(stderr, "C:\n%s\n", debug_eigen(C_).c_str());
+ fprintf(stderr, "C_shared:\n%s\n", debug_vector(C_shared_).c_str());
+ fprintf(stderr, "phi:\n%s\n", debug_eigen(phi_).c_str());
+ fprintf(stderr, "rho:\n%s\n", debug_eigen(rho).c_str());
+ xbt_abort();
+ }
+
+ XBT_DEBUG("BMF done after %d iterations", it);
+ return rho;
+}
+
+/*****************************************************************************/
+
+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();
+ maxA.resize(number_cnsts, variable_set.size());
+ maxA.setZero();
+ phi.resize(variable_set.size());
+
+ int var_idx = 0;
+ for (Variable& var : variable_set) {
+ if (var.sharing_penalty_ <= 0)
+ continue;
+ bool active = false;
+ bool linked = false; // variable is linked to some constraint (specially for selective_update)
+ for (const Element& elem : var.cnsts_) {
+ 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 */
+ linked = true;
+ double consumption = elem.consumption_weight;
+ if (consumption > 0) {
+ int cnst_idx = cnst2idx_[elem.constraint];
+ A(cnst_idx, var_idx) += consumption;
+ // a variable with double penalty must receive half share, so it max weight is greater
+ maxA(cnst_idx, var_idx) = std::max(maxA(cnst_idx, var_idx), elem.max_consumption_weight * var.sharing_penalty_);
+ active = true;
+ }
+ }
+ /* skip variables not linked to any modified or active constraint */
+ if (not linked)
+ continue;
+ if (active) {
+ phi[var_idx] = var.get_bound();
+ idx2Var_[var_idx] = &var;
+ var_idx++;
+ } else {
+ var.value_ = 1; // assign something by default for tasks with 0 consumption
+ }
+ }
+ // resize matrix to active variables only
+ A.conservativeResize(Eigen::NoChange_t::NoChange, var_idx);
+ maxA.conservativeResize(Eigen::NoChange_t::NoChange, var_idx);
+ phi.conservativeResize(var_idx);
+}
+
+template <class CnstList>
+void BmfSystem::get_constraint_data(const CnstList& cnst_list, Eigen::VectorXd& C, std::vector<bool>& shared)
+{
+ C.resize(cnst_list.size());
+ shared.resize(cnst_list.size());
+ cnst2idx_.clear();
+ int cnst_idx = 0;
+ for (const Constraint& cnst : cnst_list) {
+ 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_);
+ }
+ cnst2idx_[&cnst] = cnst_idx;
+ // FATPIPE links aren't really shared
+ shared[cnst_idx] = (cnst.sharing_policy_ != Constraint::SharingPolicy::FATPIPE);
+ cnst_idx++;
+ }
+}
+
+void BmfSystem::do_solve()
+{
+ 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)
+{
+ idx2Var_.clear();
+ cnst2idx_.clear();
+ 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);
+
+ auto solver = BmfSolver(std::move(A), std::move(maxA), std::move(C), std::move(shared), std::move(bounds));
+ auto rho = solver.solve();
+
+ if (rho.size() == 0)
+ return;
/* setting rhos */
for (int i = 0; i < rho.size(); i++) {
idx2Var_[i]->value_ = rho[i];
}
-
- XBT_DEBUG("BMF done after %d iterations", it);
- print();
}
+
+} // namespace lmm
+} // namespace kernel
+} // namespace simgrid
