{"title":"An efficient probability framework for error propagation and correlation estimation","authors":"Liang Chen, M. Tahoori","doi":"10.1109/IOLTS.2012.6313867","DOIUrl":null,"url":null,"abstract":"Soft error is becoming one of the major reliability concerns with continuously shrinking transistor size. Low level transient events may result in multiple correlated bit flips at high level. Considering this correlation effect is essential for accurate error rate estimation and efficient error mitigation. This paper proposes a novel framework to address this correlation issue at logic level. Based on the concept of error propagation function, graph transformation techniques are utilized to convert the error probability and correlation problem into the computation of signal probability and correlation. The experimental results show that compared with Monte-Carlo simulation, our approach is 72× faster, while the average inaccuracy of error probability estimation is below 0.006.","PeriodicalId":246222,"journal":{"name":"2012 IEEE 18th International On-Line Testing Symposium (IOLTS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"17","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 IEEE 18th International On-Line Testing Symposium (IOLTS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IOLTS.2012.6313867","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 17
Abstract
Soft error is becoming one of the major reliability concerns with continuously shrinking transistor size. Low level transient events may result in multiple correlated bit flips at high level. Considering this correlation effect is essential for accurate error rate estimation and efficient error mitigation. This paper proposes a novel framework to address this correlation issue at logic level. Based on the concept of error propagation function, graph transformation techniques are utilized to convert the error probability and correlation problem into the computation of signal probability and correlation. The experimental results show that compared with Monte-Carlo simulation, our approach is 72× faster, while the average inaccuracy of error probability estimation is below 0.006.