Utilizing Containers for HPC and Deep Learning Workloads

In application-development circles, containers have gotten a lot of attention in recent years -- for many good reasons. To name a few advantages, containers simplify and accelerate the process of building and isolating applications. They are lightweight and come with low overhead. And they enable easier application sharing and reproducibility, because the container image includes both the application and its development environment. Especially when it comes to deep learning (DL) frameworks, containerization is now rising in importance.