计算机科学
MNIST数据库
人工神经网络
存水弯(水管)
闪光灯(摄影)
MATLAB语言
突触
非易失性存储器
闪存
计算机硬件
计算机体系结构
工程类
人工智能
物理
操作系统
生物
环境工程
神经科学
光学
作者
Jung Nam Kim,Jaehong Lee,Jo Eun Kim,Suck Won Hong,Minsuk Koo,Yoon Kim
标识
DOI:10.1109/jeds.2022.3208241
摘要
In this work, we proposed a three-dimensional (3-D) channel stacked array architecture based on charge-trap flash (CTF) memory for an artificial neural network accelerator. The proposed synapse array architecture could be a promising solution for implementing efficiently a large-size artificial neural network on a limited-size hardware chip. We designed a full array architecture including a stacked layer selection circuit. In addition, we investigated the synaptic characteristics of CTF device by using technology computer-aided design (TCAD) simulation. We demonstrated the feasibility of the synapse array for neural network accelerators through a system-level MATLAB simulation with the Modified National Institute of Standards and Technology (MNIST) database.
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