Trends in Demand, Growth, and Breadth in Scientific Computing Training Delivered by a High-Performance Computing Center
| Autor: | van Zon, Ramses, Ponce, Marcelo, Spence, Erik, Gruner, Daniel |
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| Rok vydání: | 2019 |
| Předmět: | |
| Zdroj: | Journal of Computational Science Education Volume 10, Issue 1, pp. 53-60 (2019) |
| Druh dokumentu: | Working Paper |
| DOI: | 10.22369/issn.2153-4136/10/1/9 |
| Popis: | We analyze the changes in the training and educational efforts of the SciNet HPC Consortium, a Canadian academic High Performance Computing center, in the areas of Scientific Computing and High-Performance Computing, over the last six years. Initially, SciNet offered isolated training events on how to use HPC systems and write parallel code, but the training program now consists of a broad range of workshops and courses that users can take toward certificates in scientific computing, data science, or high-performance computing. Using data on enrollment, attendence, and certificate numbers from SciNet's education website, used by almost 1800 users so far, we extract trends on the growth, demand, and breadth of SciNet's training program. Among the results are a steady overall growth, a sharp and steady increase in the demand for data science training, and a wider participation of 'non-traditional' computing disciplines, which has motivated an increasingly broad spectrum of training offerings. Of interest is also that many of the training initiatives have evolved into courses that can be taken as part of the graduate curriculum at the University of Toronto. Comment: Presented at the Fifth Workshop on Best Practices for Enhancing HPC Training and Education (BPHTE18) @ SC18 |
| Databáze: | arXiv |
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