5x Reliability Enhanced 40nm TaOx Approximate-ReRAM with Domain-Specific Computing for Real-time Image Recognition of IoT Edge Devices

Y. Yamaga, Yoshiaki Deguchi, S. Fukuyama, K. Takeuchi
{"title":"5x Reliability Enhanced 40nm TaOx Approximate-ReRAM with Domain-Specific Computing for Real-time Image Recognition of IoT Edge Devices","authors":"Y. Yamaga, Yoshiaki Deguchi, S. Fukuyama, K. Takeuchi","doi":"10.1109/VLSIT.2018.8510669","DOIUrl":null,"url":null,"abstract":"Highly reliable Approximate-ReRAM (A-ReRAM) with Pixel-to-Pixel Data Matching (P2P-DM) and Inter-Pixel error-correcting code (IP-ECC) is proposed to recognize the image accurately by deep neural network (DNN). By specializing for the image recognition applications and modulating the image data based on pixel-to-pixel features and ReRAM error characteristics, data-retention time and endurance of ReRAM increases by 5x and 3.3x, respectively.","PeriodicalId":6561,"journal":{"name":"2018 IEEE Symposium on VLSI Technology","volume":"26 1","pages":"109-110"},"PeriodicalIF":0.0000,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE Symposium on VLSI Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/VLSIT.2018.8510669","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

Abstract

Highly reliable Approximate-ReRAM (A-ReRAM) with Pixel-to-Pixel Data Matching (P2P-DM) and Inter-Pixel error-correcting code (IP-ECC) is proposed to recognize the image accurately by deep neural network (DNN). By specializing for the image recognition applications and modulating the image data based on pixel-to-pixel features and ReRAM error characteristics, data-retention time and endurance of ReRAM increases by 5x and 3.3x, respectively.
5x可靠性增强的40nm TaOx Approximate-ReRAM与特定领域计算,用于物联网边缘设备的实时图像识别
提出了基于像素间数据匹配(P2P-DM)和像素间纠错码(IP-ECC)的高可靠近似reram (A-ReRAM)算法,通过深度神经网络(DNN)实现图像的准确识别。通过专为图像识别应用和基于像素间特征和ReRAM误差特征调制图像数据,ReRAM的数据保留时间和耐用性分别提高了5倍和3.3倍。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信