Systematic Hardware Error Identification and Calibration for Massive Multisite Testing

Praise O. Farayola, Isaac Bruce, Shravan K. Chaganti, Abdullah O. Obaidi, Abalhassan Sheikh, S. Ravi, Degang Chen
{"title":"Systematic Hardware Error Identification and Calibration for Massive Multisite Testing","authors":"Praise O. Farayola, Isaac Bruce, Shravan K. Chaganti, Abdullah O. Obaidi, Abalhassan Sheikh, S. Ravi, Degang Chen","doi":"10.1109/ITC50571.2021.00042","DOIUrl":null,"url":null,"abstract":"Multisite testing significantly increases throughput by testing multiple chips simultaneously. When implemented on a large scale (massive multisite), the complex signal routing involved, interference, and coupling on the test hardware (amongst other issues) often affect test sites differently, introducing variations in site measurements. We hypothesize in this paper that each test site’s measurement can be modeled as a weak nonlinear function of the true chip measurement with systematic errors. We propose an algorithm to detect these systematic errors and calibrate them. This approach provides a practical black box technique to mitigate test hardware variations while investigating the fundamental root causes. The proposed method is verified with simulation and real test data.","PeriodicalId":147006,"journal":{"name":"2021 IEEE International Test Conference (ITC)","volume":"198 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE International Test Conference (ITC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ITC50571.2021.00042","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6

Abstract

Multisite testing significantly increases throughput by testing multiple chips simultaneously. When implemented on a large scale (massive multisite), the complex signal routing involved, interference, and coupling on the test hardware (amongst other issues) often affect test sites differently, introducing variations in site measurements. We hypothesize in this paper that each test site’s measurement can be modeled as a weak nonlinear function of the true chip measurement with systematic errors. We propose an algorithm to detect these systematic errors and calibrate them. This approach provides a practical black box technique to mitigate test hardware variations while investigating the fundamental root causes. The proposed method is verified with simulation and real test data.
大规模多站点测试的系统硬件误差识别与校准
多站点测试通过同时测试多个芯片显著提高了吞吐量。当在大规模(大规模多站点)上实现时,涉及的复杂信号路由、干扰和测试硬件上的耦合(以及其他问题)通常会对测试站点产生不同的影响,从而在站点测量中引入变化。我们假设每个测试点的测量可以被建模为具有系统误差的真实芯片测量的弱非线性函数。我们提出了一种算法来检测这些系统误差并校准它们。这种方法提供了一种实用的黑盒技术,可以在调查根本原因的同时减少测试硬件的变化。仿真和实测数据验证了该方法的有效性。
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