Rooted in open-source SingularityCE, the Singularity container platform has become an indispensable tool for users in large computing environments practicing mission-critical data science, artificial intelligence (AI), compute-driven analytics, simulation, and high performance computing (HPC) related tasks.
“HPC, AI/ML, and scientific computing are indispensable technologies, and as such advanced container platforms that can handle these larger workloads are absolutely essential,” said Adam Hughes, CTO of Sylabs. “Singularity allows users to build a container on virtually any system, including their laptop, that can be run on many of the world’s largest HPC clusters, local university or corporate clusters, a single server, the cloud, or a workstation down the hall. With this SingularityCE certification course, Sylabs is providing students and professionals with the skills they need to design and run containers in a variety of efficient and adaptable environments.”
As a container platform, Singularity is unique in that it is tailor-made for the needs of large, multi-tenant computing environments where security and efficient resource utilization are paramount. Singularity ensures that complex workflows can be managed securely and effectively without impacting other users or system stability. Build on your laptop, a hardware specific environment and run anywhere.
Built for the needs of high performance computing (HPC), Singularity has been shaped by the community to complement and enhance the existing container ecosystem. It is designed to be interoperable with Open Container Initiative (OCI)-compliant container platforms, such as Docker, and integrate seamlessly with workflow systems like Nextflow. This approach does not seek to replace these systems but rather to augment them, providing specialized capabilities that address the unique requirements of HPC workflows while benefiting from the widespread adoption and support of established container technologies.
Although the course is as streamlined as possible, potential participants should have a background in computer science with some Linux command-line experience. With the right background, professionals working in the industry and current students can expect to greatly enhance their skills in containerization workflows for large-scale environments.
