docker-mpi

MPI cluster on Docker Swarm.

Another (more complete solution) is available here https://github.com/NLKNguyen/alpine-mpich

Do you have two or more physical machines and want to try your personal MPI cluster for your calculations? This toy project might be useful for you! Setup your Docker Swarm cluster, deploy mpistack image, attach to the master container and simply run your MPI program on multiple hosts.

Prerequisites

Those things you need to do only once.

Setup Docker Sworm network (details: TBD)

Set up registry container (this is the approach to distribute image among nodes):

docker service create --name registry --publish published=5000,target=5000 registry:2

Now we are ready to push your image there.

Launching MPI cluster

Build and push stackmpi image to the registry:

docker-compose build
docker-compose push

stackmpi is besed on Ubuntu 20.04 with MPICH installed. If you need any additianal software available on each node, modify Dockerfile appropriately and build+push image again. REMARK: If you restart your machine, from some reason the image needs to be pushed to the repository again.

There are a few helper scripts available: start-stack and stop-stack starts or stops all nodes (docker stack) specified in docker-compose.yml. By default there is one master node started on manager node (assume this is current one) and 2 worker nodes. If you want more workers, go to docker-compose.yml file and modify replicas attribute in worker section.

attach-stack attaches to the master container. The another approach is to SSH to the container with ssh-stack but by default SSH port is not exposed. You can do this by modification docker-compose.yml (uncomment port section in master section).

Inside master node, there are a few aditional commands available: node-master displays IP of master node, node-workers displays list of IPs of worker nodes, machines get list of IPs of all nodes (master and workers) and put it into the file /root/machines (yep, not perfect), sync replicates directory /root/project/ to all nodes at the same location (synchronization of nodes using rsync). Directory docker-mpi/project/ (docker-mpi repository) is mount as a volume to /root/project/ and acts as a directory for your project. You should put here binaries of your program and any necessary resources.

Executing MPI program

Attach to the master container with attach-stack command and fill the file /root/machines with the list of IPs of all nodes with machines command. Now you are ready to run simplest MPI program:

mpiexec -f machinefile -n 3 hostname

The output might look like this

root@32c03a788550:~# mpiexec -f machinefile -n 3 hostname
32c03a788550
399a9293ebdb
7688c165e99f

Now lets try something closer to the reality. Go to /root/project/ and build sample program with make, and synchronized project directory with all nodes (sync command). Exacute the program with:

mpiexec -f machinefile -n 3 project/test-mpi

The output might look like this

root@32c03a788550:~# mpiexec -f machinefile -n 3 project/test-mpi
Processor 399a9293ebdb, rank 2 out of 3 processors. CPUs: 2   CPUs available: 2
Processor 32c03a788550, rank 0 out of 3 processors. CPUs: 8   CPUs available: 8
Processor 7688c165e99f, rank 1 out of 3 processors. CPUs: 4   CPUs available: 4