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Conference paper

A Time-predictable Branch Predictor

In Proceedings of the Acm Symposium on Applied Computing — 2019, pp. 607-616
From

Department of Applied Mathematics and Computer Science, Technical University of Denmark1

Embedded Systems Engineering, Department of Applied Mathematics and Computer Science, Technical University of Denmark2

Institut national de recherche en informatique et en automatique3

Long pipelines need good branch predictors to keep the pipeline running. Current branch predictors are optimized for the average case, which might not be a good fit for real-time systems and worst-case execution time analysis. This paper presents a time-predictable branch predictor co-designed with the associated worst-case execution time analysis.

The branch predictor uses a fully-associative cache to track branch outcomes and destination addresses. The fully-associative cache avoids any false sharing of entries between branches. Therefore, we can analyze program scopes that contain a number of branches lower than or equal to the number of branches in the prediction table.

Experimental results show that the worst-case execution time bounds of programs using the proposed predictor are lower than using static branch predictors at a moderate hardware cost.

Language: English
Publisher: Association for Computing Machinery
Year: 2019
Pages: 607-616
Proceedings: 34th Annual ACM Symposium on Applied Computing
ISBN: 1450359337 and 9781450359337
Types: Conference paper
DOI: 10.1145/3297280.3297337
ORCIDs: Schoeberl, Martin

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