采用嵌入式假开关和中节点预充电方案的混合模式 SNN 横杆阵列

IF 1.3 4区 计算机科学 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC ETRI Journal Pub Date : 2024-10-12 DOI:10.4218/etrij.2024-0120
Kwang-Il Oh, Hyuk Kim, Taewook Kang, Sung-Eun Kim, Jae-Jin Lee, Byung-Do Yang
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引用次数: 0

摘要

本文介绍了一种膜计算误差最小化混合模式尖峰神经网络(SNN)横杆阵列。我们的方法包括实施嵌入式假开关方案和中节点预充电方案,以构建高精度电流模式突触。我们有效地抑制了膜电容之间的电荷共享以及导致膜计算误差的突触寄生电容。我们采用 28 纳米 FDSOI CMOS 工艺制造了 400 × 20 SNN 横条原型芯片,并成功识别了 20 个尺寸缩小为 20 × 20 像素的 MNIST 图案,功耗仅为 411 μW。此外,从 21 个已制造的 SNN 原型芯片测得的归一化输出尖峰计数的峰峰值偏差与理想值的偏差在 16.5% 以内,其中包括样本随机变量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Mixed-mode SNN crossbar array with embedded dummy switch and mid-node pre-charge scheme

This paper presents a membrane computation error-minimized mixed-mode spiking neural network (SNN) crossbar array. Our approach involves implementing an embedded dummy switch scheme and a mid-node pre-charge scheme to construct a high-precision current-mode synapse. We effectively suppressed charge sharing between membrane capacitors and the parasitic capacitance of synapses that results in membrane computation error. A 400 × 20 SNN crossbar prototype chip is fabricated via a 28-nm FDSOI CMOS process, and 20 MNIST patterns with their sizes reduced to 20 × 20 pixels are successfully recognized under 411 μW of power consumed. Moreover, the peak-to-peak deviation of the normalized output spike count measured from the 21 fabricated SNN prototype chips is within 16.5% from the ideal value, including sample-wise random variations.

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来源期刊
ETRI Journal
ETRI Journal 工程技术-电信学
CiteScore
4.00
自引率
7.10%
发文量
98
审稿时长
6.9 months
期刊介绍: ETRI Journal is an international, peer-reviewed multidisciplinary journal published bimonthly in English. The main focus of the journal is to provide an open forum to exchange innovative ideas and technology in the fields of information, telecommunications, and electronics. Key topics of interest include high-performance computing, big data analytics, cloud computing, multimedia technology, communication networks and services, wireless communications and mobile computing, material and component technology, as well as security. With an international editorial committee and experts from around the world as reviewers, ETRI Journal publishes high-quality research papers on the latest and best developments from the global community.
期刊最新文献
Issue Information Free-space quantum key distribution transmitter system using WDM filter for channel integration Metaheuristic optimization scheme for quantum kernel classifiers using entanglement-directed graphs SNN eXpress: Streamlining Low-Power AI-SoC Development With Unsigned Weight Accumulation Spiking Neural Network NEST-C: A deep learning compiler framework for heterogeneous computing systems with artificial intelligence accelerators
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