MARM-GA: Mapping Applications to Reconfigurable Mesh using Genetic Algorithm

P. Kullu, S. Tosun
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引用次数: 5

Abstract

Rapidly decreasing size of the CMOS transistors allowed us to place more components on a single chip than ever before. In order to meet the performance demands of these dense designs, designers introduced an efficient communication paradigm, Network-on-Chip (NoC), instead of traditional wiring-based methods. Although mesh topology is most commonly used topology for NoC design, it has several problems such as network congestion and energy consumption. Reconfigurable mesh topology is a good alternative to traditional mesh since it gives more mapping and routing options for reducing network congestion. However, design automation tools still lack efficient mapping and routing algorithms for reconfigurable meshes. In this study, we propose a genetic algorithm (GA) based method that simultaneously maps the application nodes on 2D reconfigurable mesh structure and determines the routing paths between communicating pairs with the objective of energy minimization. We have applied our method on four benchmarks and compared our results against two heuristic strategies. Simulation results show the superiority of our proposed method over the existing ones in terms of energy consumption.
MARM-GA:基于遗传算法的可重构网格映射应用
快速减小的CMOS晶体管尺寸使我们能够在单个芯片上放置比以往更多的组件。为了满足这些密集设计的性能要求,设计人员引入了一种高效的通信范式,即片上网络(NoC),取代了传统的基于布线的方法。虽然网状拓扑是NoC设计中最常用的拓扑结构,但它存在网络拥塞和能耗等问题。可重构网格拓扑是传统网格的一个很好的替代方案,因为它为减少网络拥塞提供了更多的映射和路由选择。然而,设计自动化工具仍然缺乏有效的映射和路由算法的可重构网格。在本研究中,我们提出了一种基于遗传算法(GA)的方法,以能量最小化为目标,同时将应用节点映射到二维可重构网格结构上,并确定通信对之间的路由路径。我们在四个基准上应用了我们的方法,并将我们的结果与两种启发式策略进行了比较。仿真结果表明,该方法在能量消耗方面优于现有方法。
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