X-Git-Url: http://bilbo.iut-bm.univ-fcomte.fr/pub/gitweb/simgrid.git/blobdiff_plain/6d64c296b8f063bec38fb27e00ad60469080228a..5843ccab4e336d47ca34f54e68760ac78d242f36:/src/kernel/lmm/bmf.cpp diff --git a/src/kernel/lmm/bmf.cpp b/src/kernel/lmm/bmf.cpp index 7dfa0e06d6..d6950bf3b8 100644 --- a/src/kernel/lmm/bmf.cpp +++ b/src/kernel/lmm/bmf.cpp @@ -1,21 +1,19 @@ -/* Copyright (c) 2007-2022. The SimGrid Team. All rights reserved. */ +/* Copyright (c) 2007-2023. The SimGrid Team. All rights reserved. */ /* This program is free software; you can redistribute it and/or modify it * under the terms of the license (GNU LGPL) which comes with this package. */ #include "src/kernel/lmm/bmf.hpp" -#include +#include "src/simgrid/math_utils.h" + +#include #include #include #include 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 */ - -namespace simgrid { -namespace kernel { -namespace lmm { +namespace simgrid::kernel::lmm { AllocationGenerator::AllocationGenerator(Eigen::MatrixXd A) : A_(std::move(A)), alloc_(A_.cols(), 0) { @@ -38,10 +36,10 @@ bool AllocationGenerator::next(std::vector& next_alloc) 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; @@ -58,11 +56,22 @@ bool AllocationGenerator::next(std::vector& next_alloc) /*****************************************************************************/ -BmfSolver::BmfSolver(Eigen::MatrixXd A, Eigen::MatrixXd maxA, Eigen::VectorXd C, Eigen::VectorXd phi) - : A_(std::move(A)), maxA_(std::move(maxA)), C_(std::move(C)), phi_(std::move(phi)), gen_(A_) +BmfSolver::BmfSolver(Eigen::MatrixXd A, Eigen::MatrixXd maxA, Eigen::VectorXd C, std::vector 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_) + { 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(C_shared_.size()) == C_.size(), "Invalid size param shared (%zu)", C_shared_.size()); } template std::string BmfSolver::debug_eigen(const T& obj) const @@ -76,15 +85,15 @@ template std::string BmfSolver::debug_vector(const C& container) co { std::stringstream debug; std::copy(container.begin(), container.end(), - std::ostream_iterator::type::value_type>(debug, " ")); + std::ostream_iterator::value_type>(debug, " ")); return debug.str(); } std::string BmfSolver::debug_alloc(const allocation_map_t& alloc) const { std::stringstream debug; - for (const auto& e : alloc) { - debug << "{" + std::to_string(e.first) + ": [" + debug_vector(e.second) + "]}, "; + for (const auto& [resource, players] : alloc) { + debug << "{" + std::to_string(resource) + ": [" + debug_vector(players) + "]}, "; } return debug.str(); } @@ -92,55 +101,86 @@ std::string BmfSolver::debug_alloc(const allocation_map_t& alloc) const double BmfSolver::get_resource_capacity(int resource, const std::vector& bounded_players) const { 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& 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 BmfSolver::alloc_map_to_vector(const allocation_map_t& alloc) const { std::vector alloc_by_player(A_.cols(), -1); - for (auto it : alloc) { - for (auto p : it.second) { - alloc_by_player[p] = it.first; + for (const auto& [resource, players] : alloc) { + for (auto p : players) { + alloc_by_player[p] = resource; } } return alloc_by_player; } +std::vector BmfSolver::get_bounded_players(const allocation_map_t& alloc) const +{ + std::vector bounded_players; + for (const auto& [resource, players] : alloc) { + if (resource == NO_RESOURCE) { + bounded_players.insert(bounded_players.end(), players.begin(), players.end()); + } + } + return bounded_players; +} + 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); - // 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; - std::vector bounded_players; - for (const auto& e : alloc) { + int row = 0; + auto bounded_players = get_bounded_players(alloc); + for (const auto& [resource, players] : alloc) { // add one row for the resource with A[r,] - int cur_resource = e.first; - if (cur_resource == NO_RESOURCE) { - bounded_players.insert(bounded_players.end(), e.second.begin(), e.second.end()); + /* bounded players, nothing to do */ + if (resource == NO_RESOURCE) + continue; + /* not shared resource, each player can receive the full capacity of the resource */ + if (not C_shared_[resource]) { + for (int i : players) { + C_p[row] = get_resource_capacity(resource, bounded_players); + A_p(row, i) = A_(resource, i); + row++; + } continue; } - A_p.row(first_row) = A_.row(cur_resource); - C_p[first_row] = get_resource_capacity(cur_resource, bounded_players); - first_row++; - if (e.second.size() > 1) { - auto it = e.second.begin(); + + /* shared resource: fairly share it between players */ + A_p.row(row) = A_.row(resource); + C_p[row] = get_resource_capacity(resource, bounded_players); + row++; + if (players.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 = players.begin(); int i = *it; // first player /* for each other player sharing this resource */ - for (++it; it != e.second.end(); ++it) { + for (++it; it != players.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[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_(resource, i); + A_p(row, k) = -maxA_(resource, k); + row++; } } } @@ -152,6 +192,20 @@ Eigen::VectorXd BmfSolver::equilibrium(const allocation_map_t& alloc) const XBT_DEBUG("A':\n%s", debug_eigen(A_p).c_str()); XBT_DEBUG("C':\n%s", debug_eigen(C_p).c_str()); + /* 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(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(A_p).solve(C_p); + * } + */ + Eigen::VectorXd rho = Eigen::FullPivLU(A_p).solve(C_p); for (int p : bounded_players) { rho[p] = phi_[p]; @@ -181,49 +235,36 @@ bool BmfSolver::get_alloc(const Eigen::VectorXd& fair_sharing, const allocation_ alloc.clear(); 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 = -1; 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 || double_positive(min_share - share, sg_maxmin_precision)) { + /* Note: the max_ may artificially increase the rate if priority < 0 + * The equilibrium sets a rho which respects the C_ though */ + if (double rate = fair_sharing[cnst_idx] / maxA_(cnst_idx, player_idx); + min_rate == -1 || double_positive(min_rate - rate, cfg_bmf_precision)) { selected_resource = cnst_idx; - min_share = share; + min_rate = rate; + } + /* 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 (double bound = initial ? -1 : phi_[player_idx]; 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) + if (alloc == last_alloc) // considered stable return true; - std::vector alloc_by_player = alloc_map_to_vector(alloc); -#if 0 - std::vector last_alloc_by_player = alloc_map_to_vector(last_alloc); - if (not initial) { - std::for_each(allocations_age_.begin(), allocations_age_.end(), [](int& n) { n++; }); - std::vector age_idx(allocations_age_.size()); - std::iota(age_idx.begin(), age_idx.end(), 0); - std::stable_sort(age_idx.begin(), age_idx.end(), - [this](auto a, auto b) { return this->allocations_age_[a] > this->allocations_age_[b]; }); - for (int p : age_idx) { - if (alloc_by_player[p] != last_alloc_by_player[p]) { - alloc = last_alloc; - alloc[last_alloc_by_player[p]].erase(p); - if (alloc[last_alloc_by_player[p]].empty()) - alloc.erase(last_alloc_by_player[p]); - alloc[alloc_by_player[p]].insert(p); - allocations_age_[p] = 0; - } - } - alloc_by_player = alloc_map_to_vector(alloc); - } -#endif - auto ret = allocations_.insert(alloc_by_player); - /* oops, allocation already tried, let's pertube it a bit */ - if (not ret.second) { + if (auto alloc_by_player = alloc_map_to_vector(alloc); not allocations_.insert(alloc_by_player).second) { + /* oops, allocation already tried, let's pertube it a bit */ XBT_DEBUG("Allocation already tried: %s", debug_alloc(alloc).c_str()); return disturb_allocation(alloc, alloc_by_player); } @@ -233,20 +274,23 @@ bool BmfSolver::get_alloc(const Eigen::VectorXd& fair_sharing, const allocation_ void BmfSolver::set_fair_sharing(const allocation_map_t& alloc, const Eigen::VectorXd& rho, Eigen::VectorXd& fair_sharing) const { + std::vector 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] = A_(r, player) * rho[player]; + if (it != alloc.end()) { // resource selected by some player, fair share depends on rho + double min_share = std::numeric_limits::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) { - 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; + fair_sharing[r] = get_maxmin_share(r, bounded_players); } else { fair_sharing[r] = C_[r]; } @@ -259,9 +303,14 @@ 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); })); + [](double v) { return double_positive(v, sg_precision_workamount); })); // 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 @@ -273,15 +322,15 @@ bool BmfSolver::is_bmf(const Eigen::VectorXd& rho) const // matrix_ji: boolean indicating player p has the maximum share at resource j Eigen::MatrixXi player_max_share = - ((usage.array().colwise() - max_share.array()).abs() <= sg_maxmin_precision).cast(); + ((usage.array().colwise() - max_share.array()).abs() <= sg_precision_workamount).cast(); // but only saturated resources must be considered - Eigen::VectorXi saturated = ((remaining.array().abs() <= sg_maxmin_precision)).cast(); + Eigen::VectorXi saturated = (remaining.array().abs() <= sg_precision_workamount).cast(); 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)) { + if (double_equals(rho[p], phi_[p], sg_precision_workamount)) { player_max_share(0, p) = 1; // it doesn't really matter, just to say that it's a bmf saturated[0] = 1; } @@ -292,7 +341,7 @@ bool BmfSolver::is_bmf(const Eigen::VectorXd& rho) const 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; } @@ -303,6 +352,7 @@ Eigen::VectorXd BmfSolver::solve() 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) @@ -312,7 +362,8 @@ Eigen::VectorXd BmfSolver::solve() 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)) { @@ -337,11 +388,13 @@ Eigen::VectorXd BmfSolver::solve() 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()); 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(); } @@ -352,7 +405,8 @@ Eigen::VectorXd BmfSolver::solve() /*****************************************************************************/ -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(); @@ -367,18 +421,18 @@ void BmfSystem::get_flows_data(int number_cnsts, Eigen::MatrixXd& A, Eigen::Matr 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_; - if (not cnst_hook.is_linked()) + if (const auto& cnst_hook = selective_update_active ? elem.constraint->modified_constraint_set_hook_ + : elem.constraint->active_constraint_set_hook_; + 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; - maxA(cnst_idx, var_idx) = elem.max_consumption_weight; + 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; } } @@ -399,39 +453,46 @@ void BmfSystem::get_flows_data(int number_cnsts, Eigen::MatrixXd& A, Eigen::Matr phi.conservativeResize(var_idx); } -template void BmfSystem::get_constraint_data(const CnstList& cnst_list, Eigen::VectorXd& C) +template +void BmfSystem::get_constraint_data(const CnstList& cnst_list, Eigen::VectorXd& C, std::vector& 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::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 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; - get_constraint_data(cnst_list, C); + Eigen::MatrixXd A; + Eigen::MatrixXd maxA; + Eigen::VectorXd C; + Eigen::VectorXd bounds; + std::vector shared; + get_constraint_data(cnst_list, C, shared); get_flows_data(C.size(), A, maxA, bounds); - auto solver = BmfSolver(A, maxA, C, 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) @@ -441,10 +502,6 @@ template void BmfSystem::bmf_solve(const CnstList& cnst_list) for (int i = 0; i < rho.size(); i++) { idx2Var_[i]->value_ = rho[i]; } - - print(); } -} // namespace lmm -} // namespace kernel -} // namespace simgrid \ No newline at end of file +} // namespace simgrid::kernel::lmm