Djemame, K orcid.org/0000-0001-5811-5263 and Carr, H orcid.org/0000-0001-6739-0283 (2020) Exascale Computing Deployment Challenges. In: Djemame, K, Altmann, J, Bañares, JÁ, Agmon Ben-Yehuda, O, Stankovski, V and Tuffin, B, (eds.) Lecture Notes in Computer Science. GECON2020: 17th International Conference on the Economics of Grids, Clouds, Systems, and Services, 15-17 Sep 2020, Izola, Slovenia. Springer , Cham, Switzerland , pp. 211-216. ISBN 9783030630577
Abstract
As Exascale computing proliferates, we see an accelerating shift towards clusters with thousands of nodes and thousands of cores per node, often on the back of commodity graphics processing units. This paper argues that this drives a once in a generation shift of computation, and that fundamentals of computer science therefore need to be re-examined. Exploiting the full power of Exascale computation will require attention to the fundamentals of programme design and specification, programming language design, systems and software engineering, analytic, performance and cost models, fundamental algorithmic design, and to increasing replacement of human bandwidth by computational analysis. As part of this, we will argue that Exascale computing will require a significant degree of co-design and close attention to the economics underlying the challenges ahead.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © Springer Nature Switzerland AG 2020. This is an author produced version of a conference paper published in Lecture Notes in Computer Science. Uploaded in accordance with the publisher's self-archiving policy. This version of the article has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature’s AM terms of use (https://www.springernature.com/gp/open-research/policies/accepted-manuscript-terms), but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: https://doi.org/10.1007/978-3-030-63058-4_19 . |
Keywords: | Exascale computing; High performance computing; Holistic approach; Economics |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) |
Funding Information: | Funder Grant number US Department of Energy Not Known |
Depositing User: | Symplectic Publications |
Date Deposited: | 10 Aug 2020 12:36 |
Last Modified: | 03 Jun 2023 02:45 |
Published Version: | http://gecon2020.gecon.info/ |
Status: | Published |
Publisher: | Springer |
Identification Number: | 10.1007/978-3-030-63058-4_19 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:164225 |