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EMBRACE: Emulating Biologically-Inspired Architectures on Hardware

机译:拥抱:在硬件上模拟生物启发架构

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摘要

This paper highlights and discusses the current challenges in the implementation of large scale Spiking Neural Networks (SNNs) in hardware. A mixed-mode approach to realising scalable SNNs on a reconfigurable hardware platform is presented. The approach uses compact low power analogue spiking neuron cells, with a weight storage capability, interconnected using Network on Chip (NoC) routers. Results presented show that this route to hardware implementation is promising.
机译:本文亮点并讨论了在硬件中实施大规模尖峰神经网络(SNNS)的当前挑战。 介绍了在可重构硬件平台上实现可缩放SNN的混合模式方法。 该方法采用紧凑的低功率模拟尖峰神经元细胞,重量存储能力,使用芯片(NOC)路由器上的网络互连。 结果表明,这条途径与硬件实现有前途。

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