What a difference a year can make; after a couple consecutive years of pandemic-related uncertainties, the world has finally turned the page. And as we kick off 2023, the team at Sylabs couldn’t be prouder of all the progress we made with everything from new offerings...
TL;DR: Singularity is used routinely with containers provided via the NVIDIA GPU Cloud (NGC). In this SUG talk, best practices and lessons learned are shared for the benefit of all users of containers that target execution on one or more GPUs.
SUG Series Introduction
The inaugural meeting of the Singularity User Group (SUG) was held March 12-13, 2019, at the San Diego Supercomputer Center (SDSC). The event attracted diverse representation from the international advanced computing community as conveyed through the post-event press release issued jointly by SDSC and Sylabs.
Over the course of the two-day event, over 20 talks were presented by members of the Singularity user, developer, and provider community. Because SUG generated a significant amount of interest, even from those who were unable to attend, we are sharing online each of the talks presented.
SUG Talk Introduction
Self identifying as an outspoken advocate of both Open Source and Open Science (OSOS), Bob Killen displays both of these predilections by framing Kubernetes as a platform for academic research in his talk from SUG. As a Research Cloud Administrator with the Advanced Research Computing Technology Services (ARC-TS) group at the University of Michigan, and a Cloud Native Computing Foundation Ambassador, Bob is uniquely qualified in representing the potential of this OSOS pairing. The abstract for Bob’s contributed SUG talk Kubernetes the next research program is as follows:
The abstract for Adam’s contributed SUG talk NVIDIA HPC Container Efforts: An Overview is as follows:
Kubernetes has become the defacto standard as a platform for container orchestration. Its ease of extending and many integrations has paved the way for a wide variety of data science and research tooling to be built on top of it.
From all encompassing tools like Kubeflow that make it easy for researchers to build end-to-end Machine Learning pipelines to specific orchestration of analytics engines such as Spark; Kubernetes has made the deployment and management of these things easy. This presentation will showcase some of the larger research tools in the ecosystem and go into how Kubernetes has enabled this easy form of application management.
Bob’s talk from SUG can be found below and here. Enjoy!
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