Abstract
There is a tradition at our university for teaching and research in High Performance Computing (HPC) systems engineering. With exascale computing on the horizon and a shortage of HPC talent, there is a need for new specialists to secure the future of research computing. Whilst many institutions provide research computing training for users within their particular domain, few offer HPC engineering and infrastructure-related courses, making it difficult for students to acquire these skills. This paper outlines how and why we are training students in HPC systems engineering, including the technologies used in delivering this goal. We demonstrate the potential for a multi-tenant HPC system for education and research, using novel container and cloud-based architecture. This work is supported by our previously published work that uses the latest open-source technologies to create sustainable, fast and flexible turn-key HPC environments with secure access via an HPC portal. The proposed multi-tenant HPC resources can be deployed on a “bare metal” infrastructure or in the cloud. An evaluation of our activities over the last five years is given in terms of recruitment metrics, skills audit feedback from students, and research outputs enabled by the multi-tenant usage of the resource.
Highlights
Fast computing is essential to modern science
The Parallel Computer Architecture (PCA) module is offered in two options for Computing and Engineering students with an intermediate level of programming experience, one of which is for undergraduate students that are being taught over two terms with a 1.5 h lab and 2 h lecture weekly
We have presented the results of research in provisioning flexible and scalable resources for the delivery of undergraduate and postgraduate courses in High Performance Computing (HPC)
Summary
Fast computing is essential to modern science. It has become a fundamental tool underpinning research and innovation in an ever-increasing array of domains, including the modelling of physical phenomena, fluid dynamics, molecular interactions, astronomy, genomics, game design, social media and even music technology. We find that students have a high level of engagement with this approach and demonstrate a more acute understanding of exploiting the performance and efficiency gains from a computer cluster that they designed and built themselves. This provides an environment that stimulates discussion between peers and sparks new research projects in HPC infrastructures. We describe the current iteration of the systems, as presented at SC2018, and the technology used to provide it in a way, which is sustainable, cost-effective and offers a low administrative burden by considering the teaching aspects in the context of other computational research requirements
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