.. _install-dependencies: Dependencies ============ WarpX depends on the following popular third party software. Please see installation instructions below. - a mature `C++17 `__ compiler, e.g., GCC 8, Clang 7, NVCC 11.0, MSVC 19.15 or newer - `CMake 3.20.0+ `__ - `Git 2.18+ `__ - `AMReX `__: we automatically download and compile a copy of AMReX - `PICSAR `__: we automatically download and compile a copy of PICSAR Optional dependencies include: - `MPI 3.0+ `__: for multi-node and/or multi-GPU execution - `CUDA Toolkit 11.0+ `__: for Nvidia GPU support (see `matching host-compilers `_) - `OpenMP 3.1+ `__: for threaded CPU execution (currently not fully accelerated) - `FFTW3 `_: for spectral solver (PSATD) support - also needs the ``pkg-config`` tool on Unix - `BLAS++ `_ and `LAPACK++ `_: for spectral solver (PSATD) support in RZ geometry - `Boost 1.66.0+ `__: for QED lookup tables generation support - `openPMD-api 0.15.1+ `__: we automatically download and compile a copy of openPMD-api for openPMD I/O support - see `optional I/O backends `__ - `Ascent 0.8.0+ `__: for in situ 3D visualization - `SENSEI 4.0.0+ `__: for in situ analysis and visualization - `CCache `__: to speed up rebuilds (For CUDA support, needs version 3.7.9+ and 4.2+ is recommended) - `Ninja `__: for faster parallel compiles - `Python 3.7+ `__ - `mpi4py `__ - `numpy `__ - `periodictable `__ - `picmistandard `__ - see our ``requirements.txt`` file for compatible versions Install ------- Pick *one* of the installation methods below to install all dependencies for WarpX development in a consistent manner. Conda (Linux/macOS/Windows) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ .. tip:: We recommend to configure your conda to use the faster `libmamba` `dependency solver `__. .. code-block:: bash conda update -n base conda conda install -n base conda-libmamba-solver conda config --set solver libmamba With MPI (only Linux/macOS): .. code-block:: bash conda create -n warpx-dev -c conda-forge blaspp ccache cmake compilers git lapackpp "openpmd-api=*=mpi_mpich*" python numpy pandas scipy yt "fftw=*=mpi_mpich*" pkg-config matplotlib mamba ninja mpich pip virtualenv source activate warpx-dev Without MPI: .. code-block:: bash conda create -n warpx-dev -c conda-forge blaspp ccache cmake compilers git lapackpp openpmd-api python numpy pandas scipy yt fftw pkg-config matplotlib mamba ninja pip virtualenv source activate warpx-dev # compile WarpX with -DWarpX_MPI=OFF For legacy ``GNUmake`` builds, after each ``source activate warpx-dev``, you also need to set: .. code-block:: bash export FFTW_HOME=${CONDA_PREFIX} export BLASPP_HOME=${CONDA_PREFIX} export LAPACKPP_HOME=${CONDA_PREFIX} .. tip:: A general option to deactivate that conda self-activates its base environment. This `avoids interference with the system and other package managers `__. .. code-block:: bash conda config --set auto_activate_base false Spack (macOS/Linux) ^^^^^^^^^^^^^^^^^^^ First, download a `WarpX Spack desktop development environment `__ of your choice. For most desktop developments, pick the OpenMP environment for CPUs unless you have a supported GPU. * **Debian/Ubuntu** Linux: * OpenMP: ``system=ubuntu; compute=openmp`` (CPUs) * CUDA: ``system=ubuntu; compute=cuda`` (Nvidia GPUs) * ROCm: ``system=ubuntu; compute=rocm`` (AMD GPUs) * SYCL: *todo* (Intel GPUs) * **macOS**: first, prepare with ``brew install gpg2; brew install gcc`` * OpenMP: ``system=macos; compute=openmp`` If you already `installed Spack `__, we recommend to activate its `binary caches `__ for faster builds: .. code-block:: bash spack mirror add rolling https://binaries.spack.io/develop spack buildcache keys --install --trust Now install the WarpX dependencies in a new WarpX development environment: .. code-block:: bash # download environment file curl -sLO https://raw.githubusercontent.com/ECP-WarpX/WarpX/development/Tools/machines/desktop/spack-${system}-${compute}.yaml # create new development environment spack env create warpx-${compute}-dev spack-${system}-${compute}.yaml spack env activate warpx-${compute}-dev # installation spack install python3 -m pip install jupyter matplotlib numpy openpmd-api openpmd-viewer pandas scipy virtualenv yt In new terminal sessions, re-activate the environment with .. code-block:: bash spack env activate warpx-openmp-dev again. Replace ``openmp`` with the equivalent you chose. For legacy ``GNUmake`` builds, after each ``source activate warpx-openmp-dev``, you also need to set: .. code-block:: bash export FFTW_HOME=${SPACK_ENV}/.spack-env/view export BLASPP_HOME=${SPACK_ENV}/.spack-env/view export LAPACKPP_HOME=${SPACK_ENV}/.spack-env/view Brew (macOS/Linux) ^^^^^^^^^^^^^^^^^^ .. code-block:: bash brew update brew tap openpmd/openpmd brew install adios2 # for openPMD brew install ccache brew install cmake brew install fftw # for PSATD brew install git brew install hdf5-mpi # for openPMD brew install libomp brew unlink gcc brew link --force libomp brew install pkg-config # for fftw brew install open-mpi brew install openblas # for PSATD in RZ brew install openpmd-api # for openPMD If you also want to compile with PSATD in RZ, you need to manually install BLAS++ and LAPACK++: .. code-block:: bash sudo mkdir -p /usr/local/bin/ sudo curl -L -o /usr/local/bin/cmake-easyinstall https://raw.githubusercontent.com/ax3l/cmake-easyinstall/main/cmake-easyinstall sudo chmod a+x /usr/local/bin/cmake-easyinstall cmake-easyinstall --prefix=/usr/local git+https://github.com/icl-utk-edu/blaspp.git \ -Duse_openmp=OFF -Dbuild_tests=OFF -DCMAKE_VERBOSE_MAKEFILE=ON cmake-easyinstall --prefix=/usr/local git+https://github.com/icl-utk-edu/lapackpp.git \ -Duse_cmake_find_lapack=ON -Dbuild_tests=OFF -DCMAKE_VERBOSE_MAKEFILE=ON Apt (Debian/Ubuntu) ^^^^^^^^^^^^^^^^^^^ .. code-block:: bash sudo apt update sudo apt install build-essential ccache cmake g++ git libfftw3-mpi-dev libfftw3-dev libhdf5-openmpi-dev libopenmpi-dev pkg-config python3 python3-matplotlib python3-numpy python3-pandas python3-pip python3-scipy python3-venv # optional: # for CUDA, either install # https://developer.nvidia.com/cuda-downloads (preferred) # or, if your Debian/Ubuntu is new enough, use the packages # sudo apt install nvidia-cuda-dev libcub-dev