CuPDLPx.jl

Julia interface for cuPDLPx.

Installation

CuPDLPx.jl is available from the Julia General registry:

pkg> add CuPDLPx

Use with JuMP

To use CuPDLPx with JuMP, use CuPDLPx.Optimizer:

using JuMP, CuPDLPx
model = Model(CuPDLPx.Optimizer)

Setting solver parameters

CuPDLPx.jl supports setting solver parameters via set_optimizer_attribute.

using JuMP
using CuPDLPx

model = read_from_file("2club200v15p5scn.mps.gz")
undo = relax_integrality(model)

println("Read MPS succeed.")
set_optimizer(model, CuPDLPx.Optimizer)

set_optimizer_attribute(model, "verbose", true)
set_optimizer_attribute(model, "l_inf_ruiz_iterations", 0)
set_optimizer_attribute(model, "iteration_limit", 200)

optimize!(model)
println(solution_summary(model))

Supported parameters

All of the following attributes are supported.

1. Termination criteria

Name	Type	Default	Description
`eps_optimal_relative`	`Float64`	`1e-4`	Relative tolerance for optimality gap.
`eps_feasible_relative`	`Float64`	`1e-4`	Relative tolerance for primal and dual feasibility.
`eps_feas_polish_relative`	`Float64`	`1e-6`	Relative tolerance used during the polishing phase.
`time_sec_limit`	`Float64`	`3600.0`	Maximum runtime allowed in seconds.
`iteration_limit`	`Int32`	`2147483647`	Maximum number of iterations.
`optimality_norm`	`norm_type_t`	`NORM_TYPE_L2`	Norm used to measure residuals: `NORM_TYPE_L2` (0) or `NORM_TYPE_L_INF` (1).
`termination_evaluation_frequency`	`Int`	`200`	Frequency (in iterations) at which to check termination criteria.

2. Algorithm and Preconditioning

Name	Type	Default	Description
`presolve`	`Bool`	`true`	Whether to enable the PSLP presolver.
`l_inf_ruiz_iterations`	`Int`	`10`	Number of Ruiz rescaling iterations.
`has_pock_chambolle_alpha`	`Bool`	`true`	Whether to use Pock-Chambolle rescaling.
`pock_chambolle_alpha`	`Float64`	`1.0`	$\alpha$ used in Pock-Chambolle rescaling.
`bound_objective_rescaling`	`Bool`	`true`	Whether to use objective and bound rescaling.
`reflection_coefficient`	`Float64`	`1.0`	Reflection coefficient (typically in $[0, 1]$).
`feasibility_polishing`	`Bool`	`false`	Wheather to perform post-solve feasibility polishing.
`sv_max_iter`	`Int`	`5000`	Maximum iterations for singular value estimation.
`sv_tol`	`Float64`	`1e-4`	Tolerance for singular value estimation.
`verbose`	`Bool`	`false`	Whether to enable console output and progress logging.

3. Adaptive Restart and Primal Weight

Name	Type	Default	Description
`artificial_restart_threshold`	`Float64`	`0.36`	Threshold for triggering a forced "artificial" restart (based on iterations).
`sufficient_reduction_for_restart`	`Float64`	`0.2`	Threshold for sufficient decay in fixed-point error to trigger a restart.
`necessary_reduction_for_restart`	`Float64`	`0.8`	Threshold for necessary decay in fixed-point error to trigger a restart.
`k_p`	`Float64`	`0.99`	Proportional gain for the primal weight (PID) controller.
`k_i`	`Float64`	`0.01`	Integral gain for the primal weight (PID) controller.
`k_d`	`Float64`	`0.0`	Derivative gain for the primal weight (PID) controller.
`i_smooth`	`Float64`	`0.3`	Smoothing factor for the integral component of the controller.