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Developing High Performance Computing Resources for Teaching Cluster and Grid Computing courses

Holmes, Violeta and Kureshi, Ibad (2015) Developing High Performance Computing Resources for Teaching Cluster and Grid Computing courses. Procedia Computer Science, 51. pp. 1714-1723. ISSN 1877-0509

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High-Performance Computing (HPC) and the ability to process large amounts of data are of
paramount importance for UK business and economy as outlined by Rt Hon David Willetts
MP at the HPC and Big Data conference in February 2014. However there is a shortage of
skills and available training in HPC to prepare and expand the workforce for the HPC and
Big Data research and development. Currently, HPC skills are acquired mainly by students
and staff taking part in HPC-related research projects, MSc courses, and at the dedicated
training centres such as Edinburgh University’s EPCC. There are few UK universities teaching
the HPC, Clusters and Grid Computing courses at the undergraduate level. To address the
issue of skills shortages in the HPC it is essential to provide teaching and training as part of
both postgraduate and undergraduate courses. The design and development of such courses is
challenging since the technologies and software in the fields of large scale distributed systems
such as Cluster, Cloud and Grid computing are undergoing continuous change. The students
completing the HPC courses should be proficient in these evolving technologies and equipped
with practical and theoretical skills for future jobs in this fast developing area.
In this paper we present our experience in developing the HPC, Cluster and Grid modules
including a review of existing HPC courses offered at the UK universities. The topics covered in
the modules are described, as well as the coursework projects based on practical laboratory work.
We conclude with an evaluation based on our experience over the last ten years in developing
and delivering the HPC modules on the undergraduate courses, with suggestions for future work.

Item Type: Article
Subjects: L Education > L Education (General)
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Schools: School of Computing and Engineering
Related URLs:
Depositing User: Violeta Holmes
Date Deposited: 21 May 2015 12:49
Last Modified: 04 Nov 2015 17:50


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