Efficient Worst-Case Execution Time Analysis of Dynamic Branch Prediction

Wolfgang Puffitsch

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

Dynamic branch prediction is commonly found in modern processors, but notoriously difficult to model for worst-case execution time analysis. This is particularly true for global dynamic branch predictors, where predictions are influenced by the global branch history. Prior research in this area has concluded that modeling of global branch prediction is too costly for practical use. This paper presents an approach to model global branch prediction while keeping the analysis effort reasonably low. The approach separates the branch history analysis from the integer linear programming formulation of the worst-case execution time problem. Consequently, the proposed approach scales to longer branch history lengths than previous approaches.
Original languageEnglish
Title of host publicationProceedings of the 28th Euromicro Conference on Real-Time Systems (ECRTS 2016)
PublisherIEEE
Publication date2016
Pages152-162
ISBN (Print)978-1-5090-2811-5
DOIs
Publication statusPublished - 2016
Event28th Euromicro Conference on Real-Time Systems (ECRTS 2016) - Toulouse, France
Duration: 5 Jul 20168 Jul 2016
Conference number: 28
http://ecrts.eit.uni-kl.de/ecrts16

Conference

Conference28th Euromicro Conference on Real-Time Systems (ECRTS 2016)
Number28
Country/TerritoryFrance
CityToulouse
Period05/07/201608/07/2016
Internet address

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