A 20ns-write 45ns-read and 1014-cycle endurance memory module composed of 60nm crystalline oxide semiconductor transistors

Shuhei Maeda, S. Ohshita, K. Furutani, Y. Yakubo, T. Ishizu, T. Atsumi, Y. Ando, D. Matsubayashi, K. Kato, T. Okuda, M. Fujita, S. Yamazaki
{"title":"A 20ns-write 45ns-read and 1014-cycle endurance memory module composed of 60nm crystalline oxide semiconductor transistors","authors":"Shuhei Maeda, S. Ohshita, K. Furutani, Y. Yakubo, T. Ishizu, T. Atsumi, Y. Ando, D. Matsubayashi, K. Kato, T. Okuda, M. Fujita, S. Yamazaki","doi":"10.1109/ISSCC.2018.8310395","DOIUrl":null,"url":null,"abstract":"Development of LSI targeting artificial intelligence (AI) has accelerated, some chips have been used and are commercially available in a number of applications. LSI capable of performing arithmetic operation for deep learning, etc., at low power and high speed is crucial for achieving more sophisticated AI. Power consumption is increasing significantly owing particularly to the practical use of AI, and power reduction techniques are urgently necessary.","PeriodicalId":6617,"journal":{"name":"2018 IEEE International Solid - State Circuits Conference - (ISSCC)","volume":"9 1","pages":"484-486"},"PeriodicalIF":0.0000,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE International Solid - State Circuits Conference - (ISSCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISSCC.2018.8310395","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5

Abstract

Development of LSI targeting artificial intelligence (AI) has accelerated, some chips have been used and are commercially available in a number of applications. LSI capable of performing arithmetic operation for deep learning, etc., at low power and high speed is crucial for achieving more sophisticated AI. Power consumption is increasing significantly owing particularly to the practical use of AI, and power reduction techniques are urgently necessary.
一种由60nm晶体氧化物半导体晶体管组成的20ns写入45ns读取1014周期持久存储器模块
针对人工智能(AI)的大规模集成电路的发展已经加速,一些芯片已经在许多应用中使用并商业化。能够以低功耗和高速度进行深度学习等算术运算的LSI对于实现更复杂的人工智能至关重要。由于人工智能的实际应用,功耗正在显著增加,因此迫切需要降低功耗的技术。
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