一个2.56mm2 718GOPS可配置的40nm CMOS尖峰卷积稀疏编码处理器

Chester Liu, Sung-gun Cho, Zhengya Zhang
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引用次数: 1

摘要

一个可配置的神经启发推理处理器被设计成一个神经元阵列,每个神经元在一个独立的时钟域内工作。处理器实现了一个循环网络,前馈操作使用高效的稀疏卷积,零补丁跳变,反馈操作使用稀疏尖峰驱动重构。全局异步本地同步结构使可扩展设计和负载平衡实现22%的功耗降低。这款2.56平方毫米的推理处理器采用40nm CMOS制造,集成了48个神经元、一个集线器和一个OpenRISC处理器。该芯片在380MHz下达到718GOPS,并演示了在图像特征提取和立体图像深度提取方面的应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A 2.56mm2 718GOPS configurable spiking convolutional sparse coding processor in 40nm CMOS
A configurable neuro-inspired inference processor is designed as an array of neurons each operating in an independent clock domain. The processor implements a recurrent network using efficient sparse convolutions with zero-patch skipping for feedforward operations, and sparse spike-driven reconstruction for feedback operations. A globally asynchronous locally synchronous structure enables scalable design and load balancing to achieve 22% reduction in power. Fabricated in 40nm CMOS, the 2.56mm2 inference processor integrates 48 neurons, a hub and an OpenRISC processor. The chip achieves 718GOPS at 380MHz, and demonstrates applications in feature extraction from images and depth extraction from stereo images.
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