Abuassal, Ali Mohamed Ahmed, Tempesti, Gianluca orcid.org/0000-0001-8110-8950 and Trefzer, Martin Albrecht orcid.org/0000-0002-6196-6832 (2018) Artificial bee colony-inspired run-time task management for many-core systems. In: 2018 IEEE Symposium Series on Computational Intelligence (SSCI). 2018 SYMPOSIUM SERIES ON COMPUTATIONAL INTELLIGENCE, 18-21 Nov 2018 IEEE , IND , pp. 1084-1091.
Abstract
Efficient resource and application management is one of the most complex and challenging tasks in high performance computing. Large-scale computing systems that contain hundreds, thousands or even millions of cores demand solutions that can operate in a distributed, robust, and scalable fashion. However, while hardware parallelism is relatively straight forward to achieve, this is not generally the case for software. This leads to under-utilization of the hardware parallelism as well as imbalanced load distribution causing inefficiency and hotspots. In response to this challenge, this paper introduces a novel distributed and decentralized run-time management algorithm. The proposed method is guided by an optimization model inspired by artificial bee colonies (ABC). While ABC have proven useful for optimizing large sets of numerical test functions, this is the first time they are applied in the context of many-core system management. The initial result shows that, the ABC model is promising in context of run-time management for many-core systems. It is also anticipated that the algorithms bio-inspired foundations will inherently enable scalability, reliability, and adaptation. We are showing initial experiments, where the initial results indicate the capability of our model to improve the thermal distribution across the system.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © IEEE, 2018. 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: | Many-core system,Bio-inspired Hardware,bee colony,run-time management |
Dates: |
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Institution: | The University of York |
Academic Units: | The University of York > Faculty of Sciences (York) > Electronic Engineering (York) |
Depositing User: | Pure (York) |
Date Deposited: | 26 Sep 2019 09:20 |
Last Modified: | 13 Feb 2025 05:21 |
Published Version: | https://doi.org/10.1109/SSCI.2018.8628713 |
Status: | Published |
Publisher: | IEEE |
Identification Number: | 10.1109/SSCI.2018.8628713 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:151386 |