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Garrett Mills 2 years ago
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# Computing in the Kubernetes Framework
This repository contains some resources for getting started with OpenMPI and high-performance computing on Kubernetes. This accompanies a presentation given by Garrett Mills at the KU CRMDA on Docker, Kubernetes, and high-performance computing.
## Get up and running.
If you want to follow along or try OpenMPI on Kubernetes out for yourself, you can get started by creating a virtual cluster on your machine with Minikube. Here's how to get set up:
1. Install VirtualBox. Our test Kubernetes cluster will run on a collection of VMs, so we'll install VirtualBox to make that possible. [Here's the download.](
2. Install `kubectl`. This is the Kubernetes CLI tool. It's how you interface with Kubernetes. [Grab it here.](
3. Install Minikube. Minikube is a software tool that creates a Kubernetes cluster with VMs on your local machine. This is an excellent tool for testing deployments. [Get it here.](
4. Install Helm. Helm is a Kubernetes package manager used by the cluster framework. [Here's the link.](
5. Clone this repository to your computer using Git: `git clone`
That's it! You're ready to start using the Kubernetes cluster on your computer.
## Basic use.
From within the cloned repository's folder, run the `./` command. This will clone the `kube-openmpi` repository and generate the SSH key used by OpenMPI.
Now, we can start the cluster by running the `./` script. This will create the Kubernetes resources and start the cluster. If you have the `watch` command line tool installed, it will open up the cluster status page so you can see when it's done initializing.
At this point, we have a fully-functional OpenMPI cluster. By default, the definitions provided in this repo will create 5 worker nodes. You can run commands on the cluster using the `./` script. For example:
$ ./ mpiexec --allow-run-as-root --hostfile /kube-openmpi/generated/hostfile -n 5 echo "Hello, world!"
Hello, world!
Hello, world!
Hello, world!
Hello, world!
Hello, world!
When you're finished with the cluster, stop it using the `./` command. → View File