Scientific Computing, High-Performance Computing and Data Science in Higher Education

Volume 10, Issue 1 (January 2019), pp. 24–31

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@article{jocse-10-1-5,
  author={Marcelo Ponce and Erik Spence and Ramses van Zon and Daniel Gruner},
  title={Scientific Computing, High-Performance Computing and Data Science in Higher Education},
  journal={The Journal of Computational Science Education},
  year=2019,
  month=jan,
  volume=10,
  issue=1,
  pages={24--31},
  doi={https://doi.org/10.22369/issn.2153-4136/10/1/5}
}

We present an overview of current academic curricula for Scientific Computing, High-Performance Computing and Data Science. After a survey of current academic and non-academic programs across the globe, we focus on Canadian programs and specifically on the education program of the SciNet HPC Consortium, using its detailed enrollment and course statistics for the past six to seven years. Not only do these data display a steady and rapid increase in the demand for research-computing instruction, they also show a clear shift from traditional (high performance) computing to data- oriented methods. It is argued that this growing demand warrants specialized research computing degrees.