片上网络系统中基于aco的死锁感知全自适应路由

Kuan-Yu Su, Hsien-Kai Hsin, En-Jui Chang, A. Wu
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引用次数: 6

摘要

蚁群优化(蚁群优化)是一种受现实世界蚁群行为启发的问题解决技术。在片上网络(Network-on-Chip, NoC)中,性能主要由流量分配和路由决定,基于aco的路由在均衡流量负载方面也有很大的潜力。由于蚁群算法中的信息素同时提供了网络的时空信息,我们发现基于蚁群算法的路由可以降低死锁的概率及其惩罚。仿真结果表明,受蚂蚁行为的启发,这三种方案被命名为基于蚁群的死锁感知路由(ACO-DAR),可以大大抑制死锁的发生,从而提高网络性能。此外,ACO-DAR利用原有基于aco的路由的现有硬件,因此面积开销较小,因此ACO-DAR具有成本效益。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
ACO-Based Deadlock-Aware Fully-Adaptive Routing in Network-on-Chip Systems
Ant Colony Optimization (ACO) is a problem-solving technique inspired by the behavior of real-world ant colony. ACO-based routing also has high potential on balancing the traffic load in the domain of Network-on-Chip (NoC), where the performance is generally dominated by traffic distribution and routing. Since the pheromone in ACO provides both spatial and temporal network information, we find ACO-based routing suitable for reducing the probability of deadlock and its penalty. With the three schemes inspired by the behavior of ants and named as ACO-based Deadlock-Aware Routing (ACO-DAR), our simulation shows that the occurrence of deadlock can be greatly suppressed and the network performance also improves as a consequence. Moreover, ACO-DAR makes use of the existing hardware of the original ACO-based routing, so the area overhead is minor and ACO-DAR is thus cost-effective.
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