inst/HiGHS/docs/src/installation.md

In Uno: R Interface to the 'Uno' Nonlinear Optimization Solver

Install HiGHS

Compile from source

HiGHS uses CMake as build system, and requires at least version 3.15. Details about building from source using CMake can be found in HiGHS/cmake/README.md.

HiGHS with HiPO

HiGHS does not have any external dependencies, however, the new interior point solver HiPO uses BLAS. At the moment HiPO is optional and can be enabled via CMake.

External ordering heuristics

HiPO also relies on a fill-reducing ordering heuristic. HiGHS includes the source code of Metis, AMD and RCM, three open-source ordering heuristics. Their source code is already part of the HiGHS library, so there is no need to link them. In particular, there is no need to have Metis installed separately, as in previous versions of HiPO. These source codes can be found in extern/metis, extern/amd, extern/rcm, together with the respective license files. Notice that the HiGHS source code is MIT licensed. However, if you build HiGHS with HiPO support, then libhighs and the HiGHS executables are licensed Apache 2.0, due to the presence of Metis and AMD.

BLAS

On MacOS no BLAS installation is required because HiPO uses Apple Accelerate by default.

On Windows and Linux, you can either compile OpenBLAS at configure time using the option -DBUILD_OPENBLAS=ON (OFF by default) or compile BLAS using the instructions below.

MacOS

To build HiPO on MacOS, run

cmake -S. -B build -DHIPO=ON

Linux and Windows: Compile OpenBLAS at configure time

cmake -S. -B build -DHIPO=ON -DBUILD_OPENBLAS=ON

Linux and Windows: Link with BLAS installatied on your machine

On Linux, libblas and libopenblas are supported. We recommend libopenblas for its better performance, and it is found by default if available on the system. Install with

sudo apt update
sudo apt install libopenblas-dev

To build HiPO, run

cmake -S. -B build -DHIPO=ON

On Windows, OpenBLAS is required. It could be installed via vcpkg with

vcpkg install openblas[threads]

Note, that [threads] is required for HiPO.

On Windows, you also need to specify the path to OpenBLAS. If it was installed with vcpkg as suggested above, add the path to vcpkg.cmake to the CMake flags, e.g.

cmake -S. -B build -DHIPO=ON -DCMAKE_TOOLCHAIN_FILE="C:/vcpkg/scripts/buildsystems/vcpkg.cmake"

Path to BLAS

To specify explicitly which BLAS vendor to look for, BLA_VENDOR coud be set in CMake, e.g. -DBLA_VENDOR=Apple or -DBLA_VENDOR=OpenBLAS. Alternatively, to specify which BLAS library to use, set BLAS_LIBRARIES to the full path of the library e.g. -DBLAS_LIBRARIES=/path_to/libopenblas.so.

Bazel build

Alternatively, building with Bazel is supported for Bazel-based projects. To build HiGHS, from the root directory, run

bazel build //...

Install via a package manager

HiGHS can be installed using a package manager in the cases of Julia, Python, CSharp and Rust.

Precompiled Binaries

Precompiled static binaries are available at https://github.com/ERGO-Code/HiGHS/releases.

Additionally, there is one package containing shared libraries for Windows x64.

The *-mit binary packages contain HiGHS and are MIT-licenced. The *-apache binary packages contain HiGHS with HiPO and are Apache-licenced, due to the licensing of the dependencies of HiPO. For more information, see THIRD_PARTY_NOTICES.md.

If you have any questions or requests for more platforms and binaries, please get in touch with us at [e-mail].

To install a precompiled binary, download and extract the archive corresponding to your Operating System and architecture, the executable is located at /bin/highs.

Building HiGHS with NVidia GPU support

HiGHS must be built, from the root directory, with

cmake -S. -Bbuild -DCUPDLP_GPU=ON
cmake --build build --parallel

This uses FindCUDAToolkit to find a CUDA installation locally. For more details on HiGHS with CMake, see HiGHS/cmake/README.md.

Find CUDA

If CUDA is not found automatically, there is an extra option -DCUPDLP_FIND_CUDA=ON, to be used with -DCUPDLP_GPU=ON, which instead uses cuPDLP-C's FindCUDAConf.cmake.

This requires the environment variable CUDA_HOME to be set to the directory with the CUDA installation. Having set this, run

cmake -S. -Bbuild -DCUPDLP_GPU=ON -DCUPDLP_FIND_CUDA=ON
cmake --build build --parallel

to build HiGHS.

Bazel build with Cuda

Alternatively, for Bazel run

bazel build //... --//:cupdlp_gpu

It may be necessary to also specify the architecture, e.g.

bazel build //... --//:cupdlp_gpu --@rules_cuda//cuda:archs=sm_89

Uno documentation built on Aug. 30, 2026, 5:07 p.m.