Installation

Installation#

Dependencies#

You should install these yourself

  • CUDA Toolkit 10.0 or later

  • A C++ compiler which supports C++17, such as GCC

  • On Windows (good luck): MSVC 2019

These will be installed automatically within the conda environment

  • cmake 4.0.0

  • Python 3.13

  • pybind11 v2.13.6

  • NumPy

  • matplotlib

  • SciPy

  • Sphinx

Linux#

Make sure that the following applications and build tools are installed:

  • C++ compiler which supports c++17, such as GCC

  • CPython (version ≥ 3.8 recommended) and pip

  • CUDA Toolkit (version 10.0 or later)

  • git

  • miniconda or anaconda

Make especially sure that everything CUDA-related (like nvcc) can be found inside your path. 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 might differ if CUDA Toolkit has been installed in a different location. If successful, a command such as nvcc --version should work.

Clone the mumax+ git repository. The --recursive flag is used here 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. You could also skip this step and use your own conda environment instead if preferred.

conda env create -f environment.yml
conda activate mumaxplus

Then build and install mumax+ using pip.

pip install -v .

If changes are made to the code, then pip install -v . can be used to rebuild mumax+. If you want to change the Python code without needing to reinstall, you can use pip install -ve ..

You could also compile the source code 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

Windows#

Warning

These instructions are old and worked at some point (2021), but not today. If you are brave enough to try Windows and you manage to get it working, please let us know!

  1. Install Visual Studio 2019 and the desktop development with C++ workload

  2. Install CUDA Toolkit 10.x

  3. Install cmake

  4. Download the pybind11 submodule with git

    git submodule init
git submodule update

  5. Install Python packages using conda

    conda env create -f environment.yml

  6. Build mumaxplus using setuptools

    activate mumaxplus
python setup.py develop

    or conda

    conda activate mumaxplus
conda develop -b .
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