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Design of a Hierarchical Clos-Benes Optical Network-on-Chip Architecture

机译:分层Clos-Benes片上光网络架构的设计

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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.
机译:随着芯片多处理器能力的不断提高,片上通信效率对于整体性能至关重要。然而,基于电子开关的片上网络遭受过大的功耗和有限的性能。为了利用光互连在芯片多处理器中进行大规模片上通信的优势,我们提出了一种具有优化控制和路由方案的分层Clos-Benes片上光网络(NoC)设计。所提出的控制和路由方案包括针对Clos网络的基于优先级的循环虚拟输出队列选择和基于Q学习的启发式路由算法,以及针对交换机内Benes网络的基于流量的自适应路由。通过考虑网络负载和运行时路径分配,建议的基于Q学习的启发式路由可以最终以最佳的路径分配成功率预测所有可能的可用路径中的最佳替代路径。在均匀流量下对256核芯片多处理器进行的案例研究表明,与网格,胖树和基线Clos-Benes光学NoC相比,网络吞吐量分别增加了400%,60%和16%。与一组网格,胖树和基线Clos-Benes网络相比,平均一组实际应用程序的应用程序ETE延迟分别减少了48%,29%和20%。

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