{"title":"A new methodology for noise sensor placement based on association rule mining","authors":"Yu-Hsiang Hung, Sheng-Hsin Fang, Hung-Ming Chen, Shen-Min Chen, Chang-Tzu Lin, Chia-Hsin Lee","doi":"10.1145/2902961.2902973","DOIUrl":null,"url":null,"abstract":"Due to near-threshold computing nowadays, voltage emergency is threatening our design margins very seriously. Noise sensors are inserted in order to prevent various integrity issues from happening during runtime. In this work, we use a new technique based on association rule mining to plan and place noise sensors. This new methodology can consider the miss rate (the probability of any node occurring voltage emergency without any detection by placed sensors) and simultaneously minimize the number of sensors utilized. The results show that our approach is very effective in converging the miss rate to zero by the least number of sensors. Compared with the state-of-the-art, we can reduce the number of sensors by half in benchmarks while the miss rate is comparable or even smaller than the prior work.","PeriodicalId":407054,"journal":{"name":"2016 International Great Lakes Symposium on VLSI (GLSVLSI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 International Great Lakes Symposium on VLSI (GLSVLSI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2902961.2902973","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 near-threshold computing nowadays, voltage emergency is threatening our design margins very seriously. Noise sensors are inserted in order to prevent various integrity issues from happening during runtime. In this work, we use a new technique based on association rule mining to plan and place noise sensors. This new methodology can consider the miss rate (the probability of any node occurring voltage emergency without any detection by placed sensors) and simultaneously minimize the number of sensors utilized. The results show that our approach is very effective in converging the miss rate to zero by the least number of sensors. Compared with the state-of-the-art, we can reduce the number of sensors by half in benchmarks while the miss rate is comparable or even smaller than the prior work.