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.

PDHG parameters

name	type	default
l_inf_ruiz_iterations	Int	10
has_pock_chambolle_alpha	Bool	true
pock_chambolle_alpha	Float64	1.0
bound_objective_rescaling	Bool	true
verbose	Bool	false
termination_evaluation_frequency	Int	200
sv_max_iter	Int	5000
sv_tol	Float64	1e-4
reflection_coefficient	Float64	1.0
feasibility_polishing	Bool	false
presolve	Bool	true
artificial_restart_threshold	Float64	0.36
sufficient_reduction_for_restart	Float64	0.2
necessary_reduction_for_restart	Float64	0.5
k_p	Float64	0.99
k_i	Float64	0.01
k_d	Float64	0.0
i_smooth	Float64	0.3

Termination criteria

name	type	default
eps_optimal_relative	Float64	1e-4
eps_feasible_relative	Float64	1e-4
eps_feas_polish_relative	Float64	1e-6
eps_infeasible	Float64	1e-10
time_sec_limit	Float64	3600.0
iteration_limit	Int	INT32_MAX