Embedded Accelerators for Scientific High-Performance Computing: An Energy Study of OpenCL Gaussian Elimination Workloads

Beau Johnston, Brian Lee, Luke Angove, Alistair Rendell

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Energy efficient High-Performance Computing (HPC) is becoming increasingly important. Recent ventures into this space have introduced an unlikely candidate to achieve exascale scientific computing hardware with a small energy footprint. ARM processors and embedded GPU accelerators originally developed for energy efficiency in mobile devices, where battery life is critical, are being repurposed and deployed in the next generation of supercomputers. Unfortunately, the performance of executing scientific workloads on many of these devices is largely unknown, yet the bulk of computation required in high-performance supercomputers is scientific. We present an analysis of one such scientific code, in the form of Gaussian Elimination, and evaluate both execution time and energy used on a range of embedded accelerator SoCs. These include three ARM CPUs and two mobile GPUs. Understanding how these low power devices perform on scientific workloads will be critical in the selection of appropriate hardware for these supercomputers, for how can we estimate the performance of tens of thousands of these chips if the performance of one is largely unknown?

Original languageEnglish
Title of host publicationProceedings
Subtitle of host publication46th International Conference on Parallel Processing Workshops ICPPW 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages59-68
Number of pages10
ISBN (Electronic)9781538610442
DOIs
Publication statusPublished - 5 Sep 2017
Externally publishedYes
Event46th International Conference on Parallel Processing Workshops, ICPPW 2017 - Bristol, United Kingdom
Duration: 14 Aug 2017 → …

Publication series

NameProceedings of the International Conference on Parallel Processing Workshops
ISSN (Print)1530-2016

Conference

Conference46th International Conference on Parallel Processing Workshops, ICPPW 2017
CountryUnited Kingdom
CityBristol
Period14/08/17 → …

Keywords

  • Accelerators
  • Energy Efficiency
  • HPC
  • exascale
  • scientific computing

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    Johnston, B., Lee, B., Angove, L., & Rendell, A. (2017). Embedded Accelerators for Scientific High-Performance Computing: An Energy Study of OpenCL Gaussian Elimination Workloads. In Proceedings: 46th International Conference on Parallel Processing Workshops ICPPW 2017 (pp. 59-68). [8026070] (Proceedings of the International Conference on Parallel Processing Workshops). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICPPW.2017.22