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

Autor:	Ponce, Marcelo, Spence, Erik, Gruner, Daniel, van Zon, Ramses
Rok vydání:	2016
Předmět:	Computer Science - Computers and Society Computer Science - Distributed Parallel and Cluster Computing
Zdroj:	Journal of Computational Science Education vol 10 (2019)
Druh dokumentu:	Working Paper
DOI:	10.22369/issn.2153-4136/10/1/5
Popis:	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 four to five 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. The possible curricula of such degrees are described next, taking existing programs as an example, and adding SciNet's experiences of student desires as well as trends in advanced research computing. Comment: Updated discussion and title
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1604.05676 Zobrazit plný text záznamu View this record from Arxiv