Magic Castle — Enabling Scalable HPC Training through Scalable Supporting Infrastructures

Volume 13, Issue 1 (April 2022), pp. 21–22

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@article{jocse-13-1-3,
  author={F\'{e}lix-Antoine Fortin and Alan \'{O} Cais},
  title={Magic Castle \textemdash Enabling Scalable HPC Training through Scalable Supporting Infrastructures},
  journal={The Journal of Computational Science Education},
  year=2022,
  month=apr,
  volume=13,
  issue=1,
  pages={21--22},
  doi={https://doi.org/10.22369/issn.2153-4136/13/1/3}
}

The potential HPC community grows ever wider as methodologies such as AI and big data analytics push the computational needs of more and more researchers into the HPC space. As a result, requirements for training are exploding as HPC adoption continues to gather pace. However, the number of topics that can be thoroughly addressed without providing access to actual HPC resources is very limited, even at the introductory level. In cases where access to production HPC resources is available, security concerns and the typical overhead of arranging for account provision and training reservations make the scalability of this approach challenging.