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. To build HiPO, you need to have BLAS installed on your machine. Please follow the instructions below.

BLAS

On Linux, libblas and libopenblas are supported. We recomment 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

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

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

vcpkg install openblas[threads]

Note, that [threads] is required for HiPO.

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.

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.

HiPO

To install HiPO, on Linux and MacOS, run

cmake -S. -B build -DHIPO=ON

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.

-DCMAKE_TOOLCHAIN_FILE="C:/vcpkg/scripts/buildsystems/vcpkg.cmake"

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

These binaries are provided by the Julia community and are not officially supported by the HiGHS development team. If you have trouble using these libraries, please open a GitHub issue and tag @odow in your question.

Precompiled static executables are available for a variety of platforms at

• https://github.com/JuliaBinaryWrappers/HiGHSstatic_jll.jl/releases

Multiple versions are available. Each version has the form vX.Y.Z. In general, you should choose the most recent version.

To install a precompiled binary, download the appropriate HiGHSstatic.vX.Y.Z.[platform-string].tar.gz file and extract the executable located at /bin/highs.

Do not download the file starting with HiGHSstatic-logs. These files contain information from the automated compilation system. Click "Show all N assets" to see more files.

Platform strings

The GitHub releases contain precompiled binaries for a number of different platforms. These are indicated by the platform-specific string in each filename.

• For Windows users: choose the file ending in x86_64-w64-mingw32-cxx11.tar.gz
• For M1 macOS users: choose the file ending in aarch64-apple-darwin.tar.gz
• For Intel macOS users: choose the file ending in x86_64-apple-darwin.tar.gz

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