Containers in HPC

No longer an experimental topic, containers are here to stay in HPC. They offer software portability, improved collaboration, and data reproducibility. A variety of tools (e.g. Docker, Shifter, Singularity, Podman) exist for users who want to incorporate containers into their workflows, but oftentimes they may not know where to start.

This tutorial will cover the basics of creating and using containers in an HPC environment. We will make use of hands-on demonstrations from a range of disciplines to highlight how containers can be used in scientific workflows. These examples will draw from Bioinformatics, Machine Learning, Computational Fluid Dynamics and other areas.

Through this discussion, attendees will learn how to run GPU- and MPI-enabled applications with containers. We will also show how containers can be used to improve performance in Python workflows and I/O-intensive jobs.

Lastly, we will discuss best practices for container management and administration. These practices include how to incorporate good software engineering principles, such as the use of revision control and continuous integration tools.