Installation on a local computer¶

Installing FBPIC¶

The installation requires the Anaconda distribution of Python. If Anaconda is not your default Python distribution, download and install it from here.

Installation steps:

Install the dependencies of FBPIC:

conda install -c conda-forge numba scipy h5py mkl mpi4py

Install fbpic
```
pip install fbpic
```
Note

If you want to run FBPIC through the PICMI interface, you can instead use
```
pip install fbpic[picmi]
```
Note

Instead of using a release, you can also install FBPIC from the sources, by cloning the code from Github, and executing python3 -m pip install . from the main directory. A shortcut for this is: python3 -m pip install git+https://github.com/fbpic/fbpic.git.
Optional: In order to be able to run the code on a GPU, install the additional package cupy as well as dependencies needed to enable GPU support in numba.

For CUDA versions below 12, install cupy and cuda-version (which will automatically install cudatoolkit), for example
```
conda install -c conda-forge cupy cuda-version=11.8
```
For CUDA 12+ which no longer provides the cudatoolkit package, explicit installation of cuda-nvcc and cuda-nvrtc is required
```
conda install -c conda-forge cupy cuda-version=12.0 cuda-nvcc cuda-nvrtc
```
Warning

In the above commands, you should choose a CUDA version that is compatible with your GPU driver. You can see the version of your GPU driver by typing the command nvidia-smi. You can then find the compatible CUDA versions using this table.
Optional: In order to run on a CPU which is not an Intel model, you need to install pyfftw, in order to replace the MKL FFT:
```
conda install -c conda-forge pyfftw
```

Potential issues¶

On Mac OSX, the package mpi4py can sometimes cause issues. If you observe that the code crashes with an MPI-related error, try installing mpi4py using MacPorts and pip. To do so, first install MacPorts. Then execute the following commands:

conda uninstall mpi4py
sudo port install openmpi-gcc48
sudo port select --set mpi openmpi-gcc48-fortran
pip install mpi4py

If you are running on an Apple Silicon machine, mkl is not available via conda. You can use brew instead:

brew install onednn

Running simulations¶

See the section How to run the code, for instructions on how to run a simulation.