Roberts, Stephen, Wright, Steven orcid.org/0000-0001-7133-8533, Lecomber, David et al. (4 more authors) (2016) POSE:A mathematical and visual modelling tool to guide energy aware code optimisation. In: 2015 6th International Green and Sustainable Computing Conference. 6th International Green and Sustainable Computing Conference, IGSC 2015, 14-16 Dec 2015 IEEE , USA
Abstract
Performance engineers are beginning to explore software-level optimisation as a means to reduce the energy consumed when running their codes. This paper presents POSE, a mathematical and visual modelling tool which highlights the relationship between runtime and power consumption. POSE allows developers to assess whether power optimisation is worth pursuing for their codes. We demonstrate POSE by studying the power optimisation characteristics of applications from the Mantevo and Rodinia benchmark suites. We show that LavaMD has the most scope for CPU power optimisation, with improvements in Energy Delay Squared Product (ED2P) of up to 30.59%. Conversely, MiniMD offers the least scope, with improvements to the same metric limited to 7.60%. We also show that no power optimised version of MiniMD operating below 2.3 GHz can match the ED2P performance of the original code running at 3.2 GHz. For LavaMD this limit is marginally less restrictive at 2.2 GHz.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © Copyright 2016 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions. This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy. Further copying may not be permitted; contact the publisher for details. |
Dates: |
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Institution: | The University of York |
Academic Units: | The University of York > Faculty of Sciences (York) > Computer Science (York) |
Depositing User: | Pure (York) |
Date Deposited: | 06 Sep 2018 09:10 |
Last Modified: | 17 Dec 2024 00:33 |
Published Version: | https://doi.org/10.1109/IGCC.2015.7393705 |
Status: | Published |
Publisher: | IEEE |
Identification Number: | 10.1109/IGCC.2015.7393705 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:135343 |