模拟大规模尖峰神经网络模型的AER通信方案的同步数字实现

J. Moreno, J. Madrenas, L. Kotynia
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引用次数: 7

摘要

在本文中,我们将介绍一种完全同步的地址事件表示(AER)通信方案的数字实现,该方案已在PERPLEXUS芯片中使用,以便允许模拟大规模生物激发的尖峰神经网络模型。通过在AER协议中引入特定的命令,可以将AER总线分布在大量芯片中,在这些芯片中模拟尖峰神经元的功能。使用紧凑内容可寻址存储器(CAMs)的AER编码器模块的精心设计允许大规模模型的可行实现。
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Synchronous Digital Implementation of the AER Communication Scheme for Emulating Large-Scale Spiking Neural Networks Models
In this paper we shall present a fully synchronous digital implementation of the Address Event Representation (AER) communication scheme that has been used in the PERPLEXUS chip in order to permit the emulation of large-scale biologically inspired spiking neural networks models. By introducing specific commands in the AER protocol it is possible to distribute the AER bus among a large number of chips where the functionality of the spiking neurons is being emulated. A careful design of the AER encoder module using compact Content Addressable Memories (CAMs) allows for a feasible realization of large-scale models.
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