Reliability Aspects of Memristive Devices for Computation-in-Memory Applications

S. Menzel, C. Bengel, J. Mohr, D. Wouters, S. Wiefels, F. Cüppers, S. Hoffmann‐Eifert
{"title":"Reliability Aspects of Memristive Devices for Computation-in-Memory Applications","authors":"S. Menzel, C. Bengel, J. Mohr, D. Wouters, S. Wiefels, F. Cüppers, S. Hoffmann‐Eifert","doi":"10.1109/CNNA49188.2021.9610760","DOIUrl":null,"url":null,"abstract":"Due to the high amount of data being processed in modern computing systems, the conventional physical separation of data processing and data storage limits the computing performance. Thus, new computing paradigms such as computation-in-memory are investigated to alleviate the limitations of the conventional computing scheme. Memristive devices based on the valence change mechanism offer multilevel programming capability in the CMOS compatible voltage range at reasonable speed. These properties are exploited for different computation-in-memory approaches such as Boolean logic, vector-matrix multiplications or arithmetic operations. One obstacle is the reliability of these devices. They typically show switching variability from device-to-device and cycle-to-cycle as well as read instability in the high resistive state. Here, we discuss the basic reliability issues of valence change memory cells and show a variability-aware compact model. Further, the influence of these reliability aspects on vector-matrix multiplications is discussed.","PeriodicalId":325231,"journal":{"name":"2021 17th International Workshop on Cellular Nanoscale Networks and their Applications (CNNA)","volume":"108 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 17th International Workshop on Cellular Nanoscale Networks and their Applications (CNNA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CNNA49188.2021.9610760","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Due to the high amount of data being processed in modern computing systems, the conventional physical separation of data processing and data storage limits the computing performance. Thus, new computing paradigms such as computation-in-memory are investigated to alleviate the limitations of the conventional computing scheme. Memristive devices based on the valence change mechanism offer multilevel programming capability in the CMOS compatible voltage range at reasonable speed. These properties are exploited for different computation-in-memory approaches such as Boolean logic, vector-matrix multiplications or arithmetic operations. One obstacle is the reliability of these devices. They typically show switching variability from device-to-device and cycle-to-cycle as well as read instability in the high resistive state. Here, we discuss the basic reliability issues of valence change memory cells and show a variability-aware compact model. Further, the influence of these reliability aspects on vector-matrix multiplications is discussed.
内存计算应用中记忆器件的可靠性问题
由于现代计算系统处理的数据量很大,传统的数据处理和数据存储的物理分离限制了计算性能。因此,人们开始研究新的计算范式,如内存计算,以减轻传统计算方案的局限性。基于价变机制的忆阻器件在CMOS兼容电压范围内以合理的速度提供多电平编程能力。这些属性可用于不同的内存计算方法,如布尔逻辑、向量矩阵乘法或算术运算。其中一个障碍是这些设备的可靠性。它们通常表现出从器件到器件和周期到周期的开关可变性以及高阻状态下的读取不稳定性。本文讨论了价变记忆单元的基本可靠性问题,并给出了一个变量感知的紧凑模型。进一步,讨论了这些可靠性方面对向量-矩阵乘法的影响。
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:604180095
Book学术官方微信