Singh, Amit Kumar, Dziurzanski, Piotr and Indrusiak, Leandro Soares orcid.org/0000-0002-9938-2920 (2016) Value and energy optimizing dynamic resource allocation in many-core HPC systems. In: 2015 IEEE 7th International Conference on Cloud Computing Technology and Science (CloudCom). 7th IEEE International Conference on Cloud Computing Technology and Science, CloudCom 2015, 30 Nov - 03 Dec 2015 IEEE , CAN , pp. 180-185.
Abstract
The conventional approaches to reduce the energy consumption of high performance computing (HPC) data centers focus on consolidation and dynamic voltage and frequency scaling (DVFS). Most of these approaches consider independent tasks (or jobs) and do not jointly optimize for energy and value. In this paper, we propose DVFS-aware profiling and non-profiling based approaches that use design-time profiling results and perform all the computations at run-time, respectively. The profiling based approach is suitable for the scenarios when the jobs or their structure is known at design-time, otherwise, the non-profiling based approach is more suitable. Both the approaches consider jobs containing dependent tasks and exploit efficient allocation combined with identification of voltage/frequency levels of used system cores to jointly optimize value and energy. Experiments show that the proposed approaches reduce energy consumption by 15% when compared to existing approaches while achieving significant amount of value and reducing percentage of rejected jobs leading to zero value.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © IEEE, 2016. 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 |
Keywords: | Energy consumption,High Performance Computing,Many-core,Resource allocation,Value,Value curves |
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: | 03 Aug 2016 09:03 |
Last Modified: | 06 Feb 2025 00:03 |
Published Version: | https://doi.org/10.1109/CloudCom.2015.22 |
Status: | Published |
Publisher: | IEEE |
Identification Number: | 10.1109/CloudCom.2015.22 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:103295 |