一种分层闭合光网络片上结构的设计

Renjie Yao, Yaoyao Ye, Weichen Liu
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引用次数: 1

摘要

随着芯片多处理器性能的不断提高,片内通信效率对芯片的整体性能至关重要。然而,基于电子交换机的片上网络存在功耗过大、性能受限的问题。为了充分利用光互连技术在芯片多处理器中实现大规模片上通信,提出了一种具有优化控制和路由方案的层次化Clos-Benes片上光网络(NoC)设计。提出的控制和路由方案包括Clos网络的基于优先级的轮询虚拟输出队列选择和基于q学习的启发式路由算法,以及交换机内Benes网络的流量感知自适应路由。通过考虑网络负载和运行时路径分配,所提出的基于q学习的启发式路由最终能够在所有可能的可用路径中预测出最佳备选路径,并且路径分配成功率大大提高。通过对256核芯片多处理器在均匀流量下的实例研究表明,网络吞吐量比mesh、attree和基线Clos-Benes光NoC分别提高400%、60%和16%。在一组实际应用中,应用程序的ETE延迟平均比mesh、fatree和基线Clos-Benes网络分别减少48%、29%和20%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Design of a Hierarchical Clos-Benes Optical Network-on-Chip Architecture
As chip multiprocessors keep growing in capability, on-chip communication efficiency is crucial to the overall performance. However, on-chip networks based on electronic switches suffer from excessive power consumption and limited performance. In order to take advantages of optical interconnect for large-scale on-chip communication in chip multiprocessors, we propose a design of hierarchical Clos-Benes optical network-on-chip (NoC) with an optimized control and routing scheme. The proposed control and routing scheme includes a priority based round-robin virtual output queue selection and a Q-learning based heuristic routing algorithm for the Clos network, and a traffic-aware adaptive routing for the intra-switch Benes network. By taking network load and runtime path allocation into account, the proposed Q-learning based heuristic routing can finally predict the best alternative path among all possible available paths with a much better path allocation success rate. A case study on a 256-core chip multiprocessor under uniform traffic shows that the network throughput is increased by 400%, 60%, and 16% respectively than the mesh, fattree and the baseline Clos-Benes optical NoC. On average of a set of real applications, the application ETE delay is reduced by 48%, 29%, and 20% respectively than the mesh, fattree and the baseline Clos-Benes network.
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