Probabilistic modeling of data cache behavior

V. Puranik, T. Mitra, Y. Srikant
{"title":"Probabilistic modeling of data cache behavior","authors":"V. Puranik, T. Mitra, Y. Srikant","doi":"10.1145/1629335.1629370","DOIUrl":null,"url":null,"abstract":"In this paper, we propose a formal analysis approach to estimate the expected (average) data cache access time of an application across all possible program inputs. Towards this goal, we introduce the notion of probabilistic access history that intuitively summarizes the history of data memory accesses along different program paths (to reach a particular program point) and their associated probabilities. An efficient static program analysis technique has been developed to compute the access history at all program points. We estimate the cache hit/miss probabilities and hence the expected access time of each data memory reference from the access history. Our experimental evaluation confirms the accuracy and viability of the probabilistic data cache modeling approach.","PeriodicalId":143573,"journal":{"name":"International Conference on Embedded Software","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Embedded Software","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/1629335.1629370","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7

Abstract

In this paper, we propose a formal analysis approach to estimate the expected (average) data cache access time of an application across all possible program inputs. Towards this goal, we introduce the notion of probabilistic access history that intuitively summarizes the history of data memory accesses along different program paths (to reach a particular program point) and their associated probabilities. An efficient static program analysis technique has been developed to compute the access history at all program points. We estimate the cache hit/miss probabilities and hence the expected access time of each data memory reference from the access history. Our experimental evaluation confirms the accuracy and viability of the probabilistic data cache modeling approach.
数据缓存行为的概率建模
在本文中,我们提出了一种形式化的分析方法来估计应用程序在所有可能的程序输入中的预期(平均)数据缓存访问时间。为了实现这一目标,我们引入了概率访问历史的概念,它直观地总结了沿着不同程序路径(到达特定程序点)访问数据内存的历史及其相关概率。开发了一种有效的静态程序分析技术来计算所有程序点的访问历史。我们估计缓存命中/未命中概率,从而从访问历史中估计每个数据内存引用的预期访问时间。我们的实验评估证实了概率数据缓存建模方法的准确性和可行性。
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