Containerizing Visualization Software: Experiences and Best Practices

Abstract

The standard process for software development has changed dramatically in the past decade. What was once a large effort of installing the same software across different systems has become much more streamlined with the rapid emergence and wide-scale adoption of Docker as the de facto container management ecosystem. Coincidentally, this has had an impact in the HPC and scientific computing community, allowing system maintainers to maintain and install packages with easier effort[12]. This can be seen through the adoption of containers on many large scale systems, including those supported by the Texas Advanced Computing Center (TACC), DOE, XSEDE, and the wider NSF community[23] [34] [15]. An extra layer of work is necessary when developing containers that require visualization technologies. This includes applications that require a windowing system such as X[9] to render GUIs. It can be further difficult when wanting to expose NVIDIA or GPU related capabilities to containers[32]. While the ability to containerize applications is widely available, there is no central resource for creating those with visualization requirements. Our work aims to consolidate common issues for visualization containers, including both similar and unique solutions. We give detail to the various ways we have worked at TACC to make visualization containers more available to researchers using HPC systems, made development easier, and the promise to being applied in lab research spaces. Our hope is to share similar challenges that other researchers may face, and providing possible solutions, so that further adoption of containers can be more easily developed.