mpi4py provides MPI bindings to the Python programming language. This document provides instructions for using mpi4py on the FAS cluster at Harvard University.
We recommend the Mambaforge Python distribution. The latest version is available with the python/3.10.9-fasrc01
software module. Since mpi4py
is not available with the default module you need to install it in your user environment.
The most straightforward way to install mpi4py
in your user space is to create a new conda environment with the mpi4py
package. For instance, you can do something like the below:
module load python/3.10.12-fasrc01
mamba create -n python3_env1 python numpy pip wheel mpi4py
source activate python3_env1
This will create a conda
environment named python3_env1
with the mpi4py
package and activate it. It will also install a MPI library required by mpi4py
. By default, the above commands will install MPICH.
For most of the cases the above installation procedure should work well. However, if your workflow requires a specific flavor and/or version of MPI, you could use pip
to install mpi4py
in your custom conda environment as detailed below:
- Load compiler and MPI software modules:
module load gcc/12.2.0-fasrc01
module load openmpi/4.1.5-fasrc03
This will load OpenMPI in your user environment. You can also look at our user documentation to learn more about software modules on the FAS cluster.
- Load a Python module:
module load python/3.10.12-fasrc01
- Create a conda environment:
mamba create -n python3_env2 python numpy pip wheel
- Install
mpi4py
withpip
:
pip install mpi4py
- Activate the new environment:
source activate python3_env2
Now that you have successfully installed mpi4py
in your environment you can try some examples!