Task Assignment for Heterogeneous Multiprocessors Using Re-Excited Particle Swarm Optimization

Mohamed B. Abdelhalim
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引用次数: 20

Abstract

The problem of determining whether a set of periodic tasks can be assigned to a set of heterogeneous processors in such a way that all timing constraints are met has been shown, in general, to be NP-hard. This paper presents a modified algorithm based on the Particle Swarm Optimization (PSO) heuristic for solving this problem. The modified version is called Re-Excited PSO. Experimental results show that our approach outperform the major existing methods. In addition to being able to search for a feasible assignment solution, our PSO approach can further optimize the solution to reduce its energy consumption as well as to obtain good tradeoff between minimizing the design makespan as well as energy consumption.
基于重激励粒子群优化的异构多处理器任务分配
一般来说,确定一组周期性任务能否以满足所有时间约束的方式分配给一组异构处理器的问题已被证明是np困难的。本文提出了一种基于粒子群优化(PSO)启发式的改进算法来解决这一问题。修改后的版本称为重激PSO。实验结果表明,该方法优于现有的主要方法。除了能够寻找可行的分配方案外,我们的PSO方法还可以进一步优化解决方案,以减少其能耗,并在最小化设计完工时间和能耗之间取得良好的权衡。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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