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A High Performance Load Balance Strategy for Real-Time Multicore Systems
Finding ways to distribute workloads to each processor core and efficiently reduce power consumption is of vital importance, especially for real-time systems. In this paper, a novel scheduling algorithm is proposed for real-time multicore systems to balance the computation loads and save power. The...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4009124/ https://www.ncbi.nlm.nih.gov/pubmed/24955382 http://dx.doi.org/10.1155/2014/101529 |
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author | Cho, Keng-Mao Tsai, Chun-Wei Chiu, Yi-Shiuan Yang, Chu-Sing |
author_facet | Cho, Keng-Mao Tsai, Chun-Wei Chiu, Yi-Shiuan Yang, Chu-Sing |
author_sort | Cho, Keng-Mao |
collection | PubMed |
description | Finding ways to distribute workloads to each processor core and efficiently reduce power consumption is of vital importance, especially for real-time systems. In this paper, a novel scheduling algorithm is proposed for real-time multicore systems to balance the computation loads and save power. The developed algorithm simultaneously considers multiple criteria, a novel factor, and task deadline, and is called power and deadline-aware multicore scheduling (PDAMS). Experiment results show that the proposed algorithm can greatly reduce energy consumption by up to 54.2% and the deadline times missed, as compared to the other scheduling algorithms outlined in this paper. |
format | Online Article Text |
id | pubmed-4009124 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
spelling | pubmed-40091242014-06-22 A High Performance Load Balance Strategy for Real-Time Multicore Systems Cho, Keng-Mao Tsai, Chun-Wei Chiu, Yi-Shiuan Yang, Chu-Sing ScientificWorldJournal Research Article Finding ways to distribute workloads to each processor core and efficiently reduce power consumption is of vital importance, especially for real-time systems. In this paper, a novel scheduling algorithm is proposed for real-time multicore systems to balance the computation loads and save power. The developed algorithm simultaneously considers multiple criteria, a novel factor, and task deadline, and is called power and deadline-aware multicore scheduling (PDAMS). Experiment results show that the proposed algorithm can greatly reduce energy consumption by up to 54.2% and the deadline times missed, as compared to the other scheduling algorithms outlined in this paper. Hindawi Publishing Corporation 2014 2014-04-14 /pmc/articles/PMC4009124/ /pubmed/24955382 http://dx.doi.org/10.1155/2014/101529 Text en Copyright © 2014 Keng-Mao Cho et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Cho, Keng-Mao Tsai, Chun-Wei Chiu, Yi-Shiuan Yang, Chu-Sing A High Performance Load Balance Strategy for Real-Time Multicore Systems |
title | A High Performance Load Balance Strategy for Real-Time Multicore Systems |
title_full | A High Performance Load Balance Strategy for Real-Time Multicore Systems |
title_fullStr | A High Performance Load Balance Strategy for Real-Time Multicore Systems |
title_full_unstemmed | A High Performance Load Balance Strategy for Real-Time Multicore Systems |
title_short | A High Performance Load Balance Strategy for Real-Time Multicore Systems |
title_sort | high performance load balance strategy for real-time multicore systems |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4009124/ https://www.ncbi.nlm.nih.gov/pubmed/24955382 http://dx.doi.org/10.1155/2014/101529 |
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