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Fixed latency on-chip interconnect for hardware spiking neural network architectures

机译:固定延迟的片上互连,用于硬件尖峰神经网络架构

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摘要

Information in a Spiking Neural Network (SNN) is encoded as the relative timing between spikes. Distortion in spike timings can impact the accuracy of SNN operation by modifying the precise firing time of neurons within the SNN. Maintaining the integrity of spike timings is crucial for reliable operation of SNN applications. A packet switched Network on Chip (NoC) infrastructure offers scalable connectivity for spike communication in hardware SNN architectures. However, shared resources in NoC architectures can result in unwanted variation in spike packet transfer latency. This packet latency jitter distorts the timing information conveyed on the synaptic connections in the SNN, resulting in unreliable application behaviour. This paper presents a SystemC simulation based analysis of the synaptic information distortion in NoC based hardware SNNs. The paper proposes a fixed spike transfer latency ring topology interconnect for spike communication between neural tiles, using a novel timestamped spike broadcast flow control scheme. The proposed architectural technique is evaluated using spike rates employed in previously reported mesh topology NoC based hardware SNN applications, which exhibited spike latency jitter over NoC paths. Results indicate that the proposed interconnect offers fixed spike transfer latency and eliminates the associated information distortion. The paper presents the micro-architecture of the proposed ring router. The FPGA validated ring interconnect architecture has been synthesised using 65nm low-power CMOS technology. Silicon area comparisons for various ring sizes are presented. Scalability of the proposed architecture has been addressed by employing a hierarchical NoC architecture.
机译:尖峰神经网络(SNN)中的信息被编码为尖峰之间的相对时间。尖峰时序的失真会通过修改SNN中神经元的精确触发时间来影响SNN操作的准确性。维持尖峰时序的完整性对于SNN应用程序的可靠运行至关重要。分组交换片上网络(NoC)基础结构为硬件SNN架构中的尖峰通信提供了可扩展的连接性。但是,NoC架构中的共享资源可能会导致尖峰包传输延迟的不希望有的变化。数据包延迟抖动会使SNN中的突触连接上传达的时序信息失真,从而导致应用程序行为不可靠。本文提出了基于SystemC仿真的基于NoC的硬件SNN中突触信息失真的分析。本文提出了一种固定的尖峰传输等待时间环拓扑互连,用于使用新的带时间戳的尖峰广播流控制方案来实现神经图块之间的尖峰通信。使用先前报告的基于网状拓扑NoC的硬件SNN应用程序中使用的尖峰速率对提出的体系结构技术进行了评估,该尖峰速率在NoC路径上表现出尖峰等待时间抖动。结果表明,提出的互连提供了固定的尖峰传输延迟,并消除了相关的信息失真。本文介绍了所提出的环形路由器的微体系结构。经过FPGA验证的环形互连架构已使用65nm低功耗CMOS技术进行了综合。给出了各种环尺寸的硅面积比较。所提出的体系结构的可扩展性已经通过采用分级NoC体系结构解决。

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