- By:
- Diehl, Patrick; Wai li, Ying; Junghans, Christoph; Holmen, John K; Maccarthy, Elijah A; Parete-Koon, Suzanne T; He, Yun (Helen); Hartman-Baker, Rebecca; Lively, Charles; Gott, Kevin; Gupta, Lipi; Streu, Kristina; Ghadar, Yasaman; Kinsley, Paige; Herriman, Jane; Draeger, Erik; Mehringer, Susan; Eijkhout, Victor
- Journal Name:
- Journal of Computational Science Education
- Page Number:
- 19-27
- Volume:
- 17
- Issue Number:
- 1
- Publication Date:
- April 21, 2026
- View DOI Listing:
- https://doi.org/10.22369/issn.2153-4136/17/1/3
Abstract
Workforce training at national laboratories and computing centers is essential and typically falls into two categories: foundational training for newcomers and advanced training for experienced users. Foundational topics—such as version control, build systems, and basic HPC usage—are largely transferable across institutions, while cluster-specific training varies due to differences in hardware, job schedulers, and local workflows. Training on emerging technologies is split between hardware-specific content and broadly applicable programming paradigms. To reduce redundancy and increase impact, national labs, computing centers, and vendors are collaborating through initiatives like the HPC Training Working Group to share best practices, co-develop materials, and broaden outreach. These coordinated efforts aim to make HPC training more accessible, scalable, and consistent across the community.
