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Loosen presolve tolerance and update timers to report cumulative presolve/solve time #381

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Merged
rapids-bot merged 3 commits into from
Sep 15, 2025
Merged

Loosen presolve tolerance and update timers to report cumulative presolve/solve time #381

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2823464
Increase presolve tolerance and update timers to include cumulative p…
hlinsen Sep 8, 2025
3943b5f
Address review comments
hlinsen Sep 10, 2025
8c11ad3
Merge branch 'branch-25.10' of github.com:NVIDIA/cuopt into lp-settings
hlinsen Sep 10, 2025
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67 changes: 25 additions & 42 deletions cpp/src/linear_programming/pdlp.cu
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Original file line number Diff line number Diff line change
Expand Up @@ -253,22 +253,14 @@ void pdlp_solver_t<i_t, f_t>::set_initial_dual_solution(
initial_dual_.data(), initial_dual_solution.data(), initial_dual_solution.size(), stream_view_);
}

static bool time_limit_reached(const std::chrono::high_resolution_clock::time_point& start_time,
double seconds)
{
auto current_time = std::chrono::high_resolution_clock::now();
auto elapsed =
std::chrono::duration_cast<std::chrono::milliseconds>(current_time - start_time).count();

return elapsed >= (seconds * 1000.0);
}
static bool time_limit_reached(const timer_t& timer) { return timer.check_time_limit(); }

template <typename i_t, typename f_t>
std::optional<optimization_problem_solution_t<i_t, f_t>> pdlp_solver_t<i_t, f_t>::check_limits(
const std::chrono::high_resolution_clock::time_point& start_time)
const timer_t& timer)
{
// Check for time limit
if (time_limit_reached(start_time, settings_.time_limit)) {
if (time_limit_reached(timer)) {
if (settings_.save_best_primal_so_far) {
#ifdef PDLP_VERBOSE_MODE
RAFT_CUDA_TRY(cudaDeviceSynchronize());
Expand Down Expand Up @@ -491,14 +483,10 @@ pdlp_warm_start_data_t<i_t, f_t> pdlp_solver_t<i_t, f_t>::get_filled_warmed_star
}

template <typename i_t, typename f_t>
void pdlp_solver_t<i_t, f_t>::print_termination_criteria(
const std::chrono::high_resolution_clock::time_point& start_time, bool is_average)
void pdlp_solver_t<i_t, f_t>::print_termination_criteria(const timer_t& timer, bool is_average)
{
if (!inside_mip_) {
const auto current_time = std::chrono::high_resolution_clock::now();
const f_t elapsed =
std::chrono::duration_cast<std::chrono::milliseconds>(current_time - start_time).count() /
1000.0;
auto elapsed = timer.elapsed_time();
if (is_average) {
average_termination_strategy_.print_termination_criteria(total_pdlp_iterations_, elapsed);
} else {
Expand All @@ -509,13 +497,13 @@ void pdlp_solver_t<i_t, f_t>::print_termination_criteria(

template <typename i_t, typename f_t>
void pdlp_solver_t<i_t, f_t>::print_final_termination_criteria(
const std::chrono::high_resolution_clock::time_point& start_time,
const timer_t& timer,
const convergence_information_t<i_t, f_t>& convergence_information,
const pdlp_termination_status_t& termination_status,
bool is_average)
{
if (!inside_mip_) {
print_termination_criteria(start_time, is_average);
print_termination_criteria(timer, is_average);
CUOPT_LOG_INFO(
"LP Solver status: %s",
optimization_problem_solution_t<i_t, f_t>::get_termination_status_string(termination_status)
Expand All @@ -538,7 +526,7 @@ void pdlp_solver_t<i_t, f_t>::print_final_termination_criteria(

template <typename i_t, typename f_t>
std::optional<optimization_problem_solution_t<i_t, f_t>> pdlp_solver_t<i_t, f_t>::check_termination(
const std::chrono::high_resolution_clock::time_point& start_time)
const timer_t& timer)
{
raft::common::nvtx::range fun_scope("Check termination");

Expand Down Expand Up @@ -580,8 +568,8 @@ std::optional<optimization_problem_solution_t<i_t, f_t>> pdlp_solver_t<i_t, f_t>
// enough) We still need to check iteration and time limit prior without breaking the logic below
// of first checking termination before the limit
if (total_pdlp_iterations_ <= 1) {
print_termination_criteria(start_time);
return check_limits(start_time);
print_termination_criteria(timer);
return check_limits(timer);
}

// First check for pdlp_termination_reason_t::Optimality and handle the first primal feasible case
Expand Down Expand Up @@ -654,9 +642,8 @@ std::optional<optimization_problem_solution_t<i_t, f_t>> pdlp_solver_t<i_t, f_t>
std::cout << "Optimal. End total number of iteration current=" << internal_solver_iterations_
<< std::endl;
#endif
print_final_termination_criteria(start_time,
current_termination_strategy_.get_convergence_information(),
termination_current);
print_final_termination_criteria(
timer, current_termination_strategy_.get_convergence_information(), termination_current);
return current_termination_strategy_.fill_return_problem_solution(
internal_solver_iterations_,
pdhg_solver_,
Expand All @@ -669,7 +656,7 @@ std::optional<optimization_problem_solution_t<i_t, f_t>> pdlp_solver_t<i_t, f_t>
std::cout << "Optimal. End total number of iteration average=" << internal_solver_iterations_
<< std::endl;
#endif
print_final_termination_criteria(start_time,
print_final_termination_criteria(timer,
average_termination_strategy_.get_convergence_information(),
termination_average,
true);
Expand All @@ -689,7 +676,7 @@ std::optional<optimization_problem_solution_t<i_t, f_t>> pdlp_solver_t<i_t, f_t>
std::cout << "Optimal. End total number of iteration average=" << internal_solver_iterations_
<< std::endl;
#endif
print_final_termination_criteria(start_time,
print_final_termination_criteria(timer,
average_termination_strategy_.get_convergence_information(),
termination_average,
true);
Expand All @@ -707,7 +694,7 @@ std::optional<optimization_problem_solution_t<i_t, f_t>> pdlp_solver_t<i_t, f_t>
<< std::endl;
#endif
print_final_termination_criteria(
start_time, current_termination_strategy_.get_convergence_information(), termination_current);
timer, current_termination_strategy_.get_convergence_information(), termination_current);
return current_termination_strategy_.fill_return_problem_solution(
internal_solver_iterations_,
pdhg_solver_,
Expand All @@ -729,9 +716,8 @@ std::optional<optimization_problem_solution_t<i_t, f_t>> pdlp_solver_t<i_t, f_t>
std::cout << "Current Infeasible. End total number of iteration current="
<< internal_solver_iterations_ << std::endl;
#endif
print_final_termination_criteria(start_time,
current_termination_strategy_.get_convergence_information(),
termination_current);
print_final_termination_criteria(
timer, current_termination_strategy_.get_convergence_information(), termination_current);
return current_termination_strategy_.fill_return_problem_solution(
internal_solver_iterations_,
pdhg_solver_,
Expand All @@ -745,7 +731,7 @@ std::optional<optimization_problem_solution_t<i_t, f_t>> pdlp_solver_t<i_t, f_t>
std::cout << "Average Infeasible. End total number of iteration current="
<< internal_solver_iterations_ << std::endl;
#endif
print_final_termination_criteria(start_time,
print_final_termination_criteria(timer,
average_termination_strategy_.get_convergence_information(),
termination_average,
true);
Expand All @@ -765,9 +751,8 @@ std::optional<optimization_problem_solution_t<i_t, f_t>> pdlp_solver_t<i_t, f_t>
std::cout << "Infeasible. End total number of iteration current="
<< internal_solver_iterations_ << std::endl;
#endif
print_final_termination_criteria(start_time,
current_termination_strategy_.get_convergence_information(),
termination_current);
print_final_termination_criteria(
timer, current_termination_strategy_.get_convergence_information(), termination_current);
return current_termination_strategy_.fill_return_problem_solution(
internal_solver_iterations_,
pdhg_solver_,
Expand All @@ -785,7 +770,7 @@ std::optional<optimization_problem_solution_t<i_t, f_t>> pdlp_solver_t<i_t, f_t>
<< internal_solver_iterations_ << std::endl;
#endif
print_final_termination_criteria(
start_time, current_termination_strategy_.get_convergence_information(), termination_current);
timer, current_termination_strategy_.get_convergence_information(), termination_current);
return optimization_problem_solution_t<i_t, f_t>{pdlp_termination_status_t::NumericalError,
stream_view_};
}
Expand All @@ -797,10 +782,10 @@ std::optional<optimization_problem_solution_t<i_t, f_t>> pdlp_solver_t<i_t, f_t>
average_termination_strategy_,
termination_current,
termination_average);
if (total_pdlp_iterations_ % 1000 == 0) { print_termination_criteria(start_time); }
if (total_pdlp_iterations_ % 1000 == 0) { print_termination_criteria(timer); }

// No reason to terminate
return check_limits(start_time);
return check_limits(timer);
}

template <typename f_t>
Expand Down Expand Up @@ -983,8 +968,7 @@ void pdlp_solver_t<i_t, f_t>::update_primal_dual_solutions(
}

template <typename i_t, typename f_t>
optimization_problem_solution_t<i_t, f_t> pdlp_solver_t<i_t, f_t>::run_solver(
const std::chrono::high_resolution_clock::time_point& start_time)
optimization_problem_solution_t<i_t, f_t> pdlp_solver_t<i_t, f_t>::run_solver(const timer_t& timer)
{
bool verbose;
#ifdef PDLP_VERBOSE_MODE
Expand Down Expand Up @@ -1139,8 +1123,7 @@ optimization_problem_solution_t<i_t, f_t> pdlp_solver_t<i_t, f_t>::run_solver(
pdhg_solver_.get_dual_solution());

// Check for termination
std::optional<optimization_problem_solution_t<i_t, f_t>> solution =
check_termination(start_time);
std::optional<optimization_problem_solution_t<i_t, f_t>> solution = check_termination(timer);

if (solution.has_value()) { return std::move(solution.value()); }

Expand Down
17 changes: 7 additions & 10 deletions cpp/src/linear_programming/pdlp.cuh
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Original file line number Diff line number Diff line change
Expand Up @@ -29,6 +29,8 @@

#include <mip/problem/problem.cuh>

#include <utilities/timer.hpp>

#include <raft/core/handle.hpp>

#include <rmm/device_scalar.hpp>
Expand Down Expand Up @@ -68,8 +70,7 @@ class pdlp_solver_t {
pdlp_solver_settings_t<i_t, f_t> const& settings = pdlp_solver_settings_t<i_t, f_t>{},
bool is_batch_mode = false);

optimization_problem_solution_t<i_t, f_t> run_solver(
const std::chrono::high_resolution_clock::time_point& start_time);
optimization_problem_solution_t<i_t, f_t> run_solver(const timer_t& timer);

f_t get_primal_weight_h() const;
f_t get_step_size_h() const;
Expand Down Expand Up @@ -99,19 +100,16 @@ class pdlp_solver_t {
void set_inside_mip(bool inside_mip);

private:
void print_termination_criteria(const std::chrono::high_resolution_clock::time_point& start_time,
bool is_average = false);
void print_termination_criteria(const timer_t& timer, bool is_average = false);
void print_final_termination_criteria(
const std::chrono::high_resolution_clock::time_point& start_time,
const timer_t& timer,
const convergence_information_t<i_t, f_t>& convergence_information,
const pdlp_termination_status_t& termination_status,
bool is_average = false);
void compute_initial_step_size();
void compute_initial_primal_weight();
std::optional<optimization_problem_solution_t<i_t, f_t>> check_termination(
const std::chrono::high_resolution_clock::time_point& start_time);
std::optional<optimization_problem_solution_t<i_t, f_t>> check_limits(
const std::chrono::high_resolution_clock::time_point& start_time);
std::optional<optimization_problem_solution_t<i_t, f_t>> check_termination(const timer_t& timer);
std::optional<optimization_problem_solution_t<i_t, f_t>> check_limits(const timer_t& timer);
void record_best_primal_so_far(const detail::pdlp_termination_strategy_t<i_t, f_t>& current,
const detail::pdlp_termination_strategy_t<i_t, f_t>& average,
const pdlp_termination_status_t& termination_current,
Expand Down Expand Up @@ -212,7 +210,6 @@ class pdlp_solver_t {
// Only used if save_best_primal_so_far is toggeled
optimization_problem_solution_t<i_t, f_t> best_primal_solution_so_far;
primal_quality_adapter_t best_primal_quality_so_far_;

// Flag to indicate if solver is being called from MIP. No logging is done in this case.
bool inside_mip_{false};
};
Expand Down
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