Travis CI:
With the code in this repository, you can build a Docker container that provides
the OpenMPI runtime and tools along with various supporting libaries,
including the MPI4Py Python bindings. The container also runs an OpenSSH server
so that multiple containers can be linked together and used via mpirun.
While containers can in principle be started manually via docker run, we suggest that your use
Docker Compose, a simple command-line tool
to define and run multi-container applications. We provide a sample docker-compose.yml file in the repository:
mpi_head:
image: openmpi
ports:
- "22"
links:
- mpi_node
mpi_node:
image: openmpi
(Note: the above is docker-compose API version 1)
The file defines an mpi_head and an mpi_node. Both containers run the same openmpi image.
The only difference is, that the mpi_head container exposes its SSH server to
the host system, so you can log into it to start your MPI applications.
The following command, run from the repository's directory, will start one mpi_head container and three mpi_node containers:
$> docker-compose scale mpi_head=1 mpi_node=3
Once all containers are running, you can login into the mpi_head node and start MPI jobs with mpirun. Alternatively, you can execute a one-shot command on that container with the docker-compose exec syntax, as follows:
docker-compose exec --user mpirun --privileged mpi_head mpirun -n 2 python /home/mpirun/mpi4py_benchmarks/all_tests.py
----------------------------------------- ----------- --------------------------------------------------
1. 2. 3.
Breaking the above command down:
- Execute command on node
mpi-head - run on 2 MPI ranks
- Command to run (NB: the Python script needs to import MPI bindings)
You can spin up a docker-compose cluster, run a battery of MPI4py tests and remove the cluster using a recipe provided in the included Makefile (handy for development):
make main
This repository draws from work on https://github.com/dispel4py/ by O. Weidner and R. Filgueira