Installation

Installation#

Dependencies#

You should install the following tools yourself. Open the dropdowns for more details.

CUDA Toolkit (version 10.0 or later)

Important

Make especially sure that everything CUDA-related (like nvcc) can be found inside your PATH. On Linux, for instance, this can be done by editing your ~/.bashrc file and adding the following lines:

# add CUDA
export PATH="/usr/local/cuda/bin:$PATH"
export LD_LIBRARY_PATH="/usr/local/cuda/> lib64:$LD_LIBRARY_PATH"

The paths may differ if the CUDA Toolkit was installed in a different location.

👉 Check CUDA installation with: nvcc --version

A C++ compiler which supports C++17
  • Linux: sudo apt-get install gcc

    • ⚠️ each CUDA version has a maximum supported gcc version. This StackOverflow answer lists the maximum supported gcc version for each CUDA version. If necessary, use sudo apt-get install gcc-<min_version> instead, with the appropriate <min_version>.

  • Windows:

    • CUDA does not support the gcc compiler on Windows, so download and install Microsoft Visual Studio with the “Desktop development with C++” workload. After installing, check if the path to cl.exe was added to your PATH environment variable (i.e., check whether where cl.exe returns an appropriate path like C:\Program Files\Microsoft Visual Studio\2022\Community\VC\Tools\MSVC\14.29.30133\bin\HostX64\x64). If not, add it manually.

👉 Check C installation with: gcc --version on Linux and where.exe cl.exe on Windows.

Git

  • Windows: Download and install.

  • Linux: sudo apt install git

👉 Check Git installation with: git --version

CPython (version ≥ 3.8 recommended), pip and miniconda/anaconda

All these Python-related tools should be included in a standard installation of Anaconda or Miniconda.

👉 Check installation with python --version, pip --version and conda --version.

Building mumax⁺#

First, clone the mumax⁺ Git repository. The --recursive flag is used in the following command to get the pybind11 submodule, which is needed to build mumax⁺.

git clone --recursive https://github.com/mumax/plus.git mumaxplus
cd mumaxplus

We recommend to install mumax⁺ in a clean conda environment as follows. You could also skip this step and use your own conda environment instead if preferred.

Tools automatically installed in the conda environment

  • cmake 4.0.0

  • Python 3.13

  • pybind11 v2.13.6

  • NumPy

  • matplotlib

  • SciPy

  • Sphinx

conda env create -f environment.yml
conda activate mumaxplus

Finally, build and install mumax⁺ using pip.

pip install .

Tip

If changes are made to the code, then pip install -v . can be used to rebuild mumax⁺, with the -v flag enabling verbose debug information.

If you want to change only the Python code, without needing to reinstall after each change, pip install -ve . can also be used.

Tip

The source code can also be compiled with double precision, by changing FP_PRECISION in CMakeLists.txt from SINGLE to DOUBLE before rebuilding.

add_definitions(-DFP_PRECISION=DOUBLE) # FP_PRECISION > should be SINGLE or DOUBLE
Troubleshooting

  • (Windows) If you encounter the error No CUDA toolset found, try copying the files in NVIDIA GPU Computing Toolkit/CUDA/<version>/extras/visual_studio_integration/MSBuildExtensions to Microsoft Visual Studio/<year>/<edition>/MSBuild/Microsoft/VC/<version>/BuildCustomizations. See these instructions for more details.

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