gpu.md
In Uno: R Interface to the 'Uno' Nonlinear Optimization Solver

GPU acceleration

From HiGHS v1.10.0, its first order primal-dual LP (PDLP) solver cuPDLP-C can be run on an NVIDIA GPU under Linux and Windows. However, to achieve this, CUDA utilities must be installed and HiGHS must be built locally using CMake, as described below.

First order solvers for LP are still very much "work in progress". Although impressive results have been reported, these are often to lower accuracy than is achieved by simplex and interior point solvers, have been obtained using top-of-the-range GPUs, and not achieved for all problem classes. Note that, due to PDLP using relative termination conditions, a solution deemed optimal by PDLP may not be accepted as optimal by HiGHS. The user should consider the infeasibility data returned by HighsInfo to decide whether the solution is acceptable to them.

Termination criteria

Although the PDLP solver may report that it has terminated with an optimal solution, HiGHS may identify that the solution returned by PDLP is not optimal. As discussed in HiGHS feasibility and optimality tolerances, this is due to PDLP using relative termination criteria and (unlike interior point solvers) not satisfying feasibility to high accuracy.

If you use the HiGHS PDLP solver, in the first instance it is recommended that you increase the feasibility and optimality tolerances to 1e-4, since this will result in the algorithm terminating much sooner. There are multiple feasibility and optimality tolerances, but all will be set to the value of the kkt_tolerance option (if it differs from its default value of 1e-4) so this is recommended in the first instance.

CUDA Toolkit and CMake.

A CUDA Toolkit installation is required, along with the matching NVIDIA driver. Please install both following the instructions on NVIDIA's website.

HiGHS must be build locally with CMake.

Make sure the CUDA compiler nvcc is installed by running