L. Cucu-Grosjean, L. Santinelli, Michael Houston, Code Lo, T. Vardanega, Leonidas Kosmidis, J. Abella, E. Mezzetti, E. Quiñones, F. Cazorla
{"title":"基于测量的多路径程序概率时序分析","authors":"L. Cucu-Grosjean, L. Santinelli, Michael Houston, Code Lo, T. Vardanega, Leonidas Kosmidis, J. Abella, E. Mezzetti, E. Quiñones, F. Cazorla","doi":"10.1109/ECRTS.2012.31","DOIUrl":null,"url":null,"abstract":"The rigorous application of static timing analysis requires a large and costly amount of detail knowledge on the hardware and software components of the system. Probabilistic Timing Analysis has potential for reducing the weight of that demand. In this paper, we present a sound measurement-based probabilistic timing analysis technique based on Extreme Value Theory. In all the experiments made as part of this work, the timing bounds determined by our technique were less than 15% pessimistic in comparison with the tightest possible bounds obtainable with any probabilistic timing analysis technique. As a point of interest to industrial users, our technique also requires a comparatively low number of measurement runs of the program under analysis, less than 650 runs were needed for the benchmarks presented in this paper.","PeriodicalId":425794,"journal":{"name":"2012 24th Euromicro Conference on Real-Time Systems","volume":"5 2","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"260","resultStr":"{\"title\":\"Measurement-Based Probabilistic Timing Analysis for Multi-path Programs\",\"authors\":\"L. Cucu-Grosjean, L. Santinelli, Michael Houston, Code Lo, T. Vardanega, Leonidas Kosmidis, J. Abella, E. Mezzetti, E. Quiñones, F. Cazorla\",\"doi\":\"10.1109/ECRTS.2012.31\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The rigorous application of static timing analysis requires a large and costly amount of detail knowledge on the hardware and software components of the system. Probabilistic Timing Analysis has potential for reducing the weight of that demand. In this paper, we present a sound measurement-based probabilistic timing analysis technique based on Extreme Value Theory. In all the experiments made as part of this work, the timing bounds determined by our technique were less than 15% pessimistic in comparison with the tightest possible bounds obtainable with any probabilistic timing analysis technique. As a point of interest to industrial users, our technique also requires a comparatively low number of measurement runs of the program under analysis, less than 650 runs were needed for the benchmarks presented in this paper.\",\"PeriodicalId\":425794,\"journal\":{\"name\":\"2012 24th Euromicro Conference on Real-Time Systems\",\"volume\":\"5 2\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-07-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"260\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 24th Euromicro Conference on Real-Time Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ECRTS.2012.31\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 24th Euromicro Conference on Real-Time Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ECRTS.2012.31","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Measurement-Based Probabilistic Timing Analysis for Multi-path Programs
The rigorous application of static timing analysis requires a large and costly amount of detail knowledge on the hardware and software components of the system. Probabilistic Timing Analysis has potential for reducing the weight of that demand. In this paper, we present a sound measurement-based probabilistic timing analysis technique based on Extreme Value Theory. In all the experiments made as part of this work, the timing bounds determined by our technique were less than 15% pessimistic in comparison with the tightest possible bounds obtainable with any probabilistic timing analysis technique. As a point of interest to industrial users, our technique also requires a comparatively low number of measurement runs of the program under analysis, less than 650 runs were needed for the benchmarks presented in this paper.