Using genetic algorithms to map hard real-time on NoC-based systems

Adrian Racu, L. Indrusiak
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引用次数: 42

Abstract

This paper investigates the effectiveness of genetic algorithms (GAs) for static task scheduling in wormhole Network-on-Chip-based systems. The overall objective was to get the application model mapped onto the architecture so that all tasks and communication meet their deadlines. Inter-task communication is accounted for by using analytical methods. The GA explores both the mapping of tasks as well as the priority ordering of the task set. A novel fitness function was developed and found to perform better than existing functions.
利用遗传算法在基于noc的系统上进行硬实时映射
研究了遗传算法在虫洞片上网络静态任务调度中的有效性。总体目标是将应用程序模型映射到体系结构上,以便所有任务和通信都能满足它们的最后期限。使用分析方法来解释任务间的通信。GA探索任务的映射以及任务集的优先级排序。开发了一种新的适应度函数,并发现其性能优于现有的适应度函数。
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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