基于片上电流传感器和邻域比较逻辑的sram阻性开口缺陷检测技术

F. Lavratti, L. Bolzani, A. Calimera, F. Vargas, E. Macii
{"title":"基于片上电流传感器和邻域比较逻辑的sram阻性开口缺陷检测技术","authors":"F. Lavratti, L. Bolzani, A. Calimera, F. Vargas, E. Macii","doi":"10.1109/LATW.2013.6562688","DOIUrl":null,"url":null,"abstract":"Technology scaling has made possible the integration of millions of transistors into a small area. The consequent increase of memory's density generated new types of defects during the manufacturing process that have become important concerns for the testing of Nano-Scale Static Random Access Memories (SRAMs). The rapidly increasing need to store more information results in the fact that the memory elements occupy great part of the Systemon-Chip's (SoC) silicon area. In this context, a technique based on On-Chip Current Sensors (OCCS) and Neighbourhood Comparison Logic (NCL) to detect resistive-open defects in SRAMs is proposed. The main idea behind the hardware-based technique is to explore the evaluation throughout an analysis of the current of neighbouring SRAM cells in order to identify the presence of manufacturing defects. Experimental results obtained throughout simulations demonstrate the technique's efficiency. Finally, an analysis of the overheads makes possible the comparison with today's standard techniques.","PeriodicalId":186736,"journal":{"name":"2013 14th Latin American Test Workshop - LATW","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Technique based on On-Chip Current Sensors and Neighbourhood Comparison Logic to detect resistive-open defects in SRAMs\",\"authors\":\"F. Lavratti, L. Bolzani, A. Calimera, F. Vargas, E. Macii\",\"doi\":\"10.1109/LATW.2013.6562688\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Technology scaling has made possible the integration of millions of transistors into a small area. The consequent increase of memory's density generated new types of defects during the manufacturing process that have become important concerns for the testing of Nano-Scale Static Random Access Memories (SRAMs). The rapidly increasing need to store more information results in the fact that the memory elements occupy great part of the Systemon-Chip's (SoC) silicon area. In this context, a technique based on On-Chip Current Sensors (OCCS) and Neighbourhood Comparison Logic (NCL) to detect resistive-open defects in SRAMs is proposed. The main idea behind the hardware-based technique is to explore the evaluation throughout an analysis of the current of neighbouring SRAM cells in order to identify the presence of manufacturing defects. Experimental results obtained throughout simulations demonstrate the technique's efficiency. Finally, an analysis of the overheads makes possible the comparison with today's standard techniques.\",\"PeriodicalId\":186736,\"journal\":{\"name\":\"2013 14th Latin American Test Workshop - LATW\",\"volume\":\"8 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-04-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 14th Latin American Test Workshop - LATW\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/LATW.2013.6562688\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 14th Latin American Test Workshop - LATW","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/LATW.2013.6562688","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7

摘要

缩放技术使数百万个晶体管集成到一个小区域成为可能。随着存储器密度的增加,在制造过程中产生了新的缺陷类型,这些缺陷已成为纳米尺度静态随机存取存储器(sram)测试的重要问题。存储更多信息的需求迅速增长,导致存储元件占据了系统芯片(SoC)硅面积的很大一部分。在此背景下,提出了一种基于片上电流传感器(OCCS)和邻域比较逻辑(NCL)的sram阻性开放缺陷检测技术。基于硬件的技术背后的主要思想是通过分析邻近SRAM单元的电流来探索评估,以识别制造缺陷的存在。仿真实验结果证明了该方法的有效性。最后,对开销的分析使与当今标准技术的比较成为可能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Technique based on On-Chip Current Sensors and Neighbourhood Comparison Logic to detect resistive-open defects in SRAMs
Technology scaling has made possible the integration of millions of transistors into a small area. The consequent increase of memory's density generated new types of defects during the manufacturing process that have become important concerns for the testing of Nano-Scale Static Random Access Memories (SRAMs). The rapidly increasing need to store more information results in the fact that the memory elements occupy great part of the Systemon-Chip's (SoC) silicon area. In this context, a technique based on On-Chip Current Sensors (OCCS) and Neighbourhood Comparison Logic (NCL) to detect resistive-open defects in SRAMs is proposed. The main idea behind the hardware-based technique is to explore the evaluation throughout an analysis of the current of neighbouring SRAM cells in order to identify the presence of manufacturing defects. Experimental results obtained throughout simulations demonstrate the technique's efficiency. Finally, an analysis of the overheads makes possible the comparison with today's standard techniques.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Fast fault injection techniques using FPGAs Assessment of diagnostic test for automated bug localization Local data fusion algorithm for fire detection through mobile robot Vertically-stacked silicon nanowire transistors with controllable polarity: A robustness study Improving error detection with selective redundancy in software-based techniques
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1