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Corpus-based static branch prediction

Authors:

Donald Lindsay,

Michael Mozer, and

Benjamin ZornAuthors Info & Claims

ACM SIGPLAN Notices, Volume 30, Issue 6

Pages 79 - 92

https://doi.org/10.1145/223428.207118

Published: 01 June 1995 Publication History

Abstract

Correctly predicting the direction that branches will take is increasingly important in today's wide-issue computer architectures. The name program-based branch prediction is given to static branch prediction techniques that base their prediction on a program's structure. In this paper, we investigate a new approach to program-based branch prediction that uses a body of existing programs to predict the branch behavior in a new program. We call this approach to program-based branch prediction, evidence-based static prediction, or ESP. The main idea of ESP is that the behavior of a corpus of programs can be used to infer the behavior of new programs. In this paper, we use a neural network to map static features associated with each branch to the probability that the branch will be taken. ESP shows significant advantages over other prediction mechanisms. Specifically, it is a program-based technique, it is effective across a range of programming languages and programming styles, and it does not rely on the use of expert-defined heuristics.

In this paper, we describe the application of ESP to the problem of branch prediction and compare our results to existing program-based branch predictors. We also investigate the applicability of ESP across computer architectures, programming languages, compilers, and run-time systems. Averaging over a body of 43 C and Fortran programs, ESP branch prediction results in a miss rate of 20%, as compared with the 25% miss rate obtained using the best existing program-based heuristics.

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Cited By

Richter EValancius SMcclanahan JMixter JAkoglu A(2018)Balancing the learning ability and memory demand of a perceptron-based dynamically trainable neural networkThe Journal of Supercomputing10.1007/s11227-018-2374-x74:7(3211-3235)Online publication date: 1-Jul-2018
https://dl.acm.org/doi/10.1007/s11227-018-2374-x
Lee WChang J(2004)A garbage collection policy based on empirical behaviorInformation Sciences: an International Journal10.1016/j.ins.2003.05.014167:1-4(129-146)Online publication date: 2-Dec-2004
https://dl.acm.org/doi/10.1016/j.ins.2003.05.014
Vintan LSbera MMihu IFlorea A(2003)An alternative to branch predictionACM SIGARCH Computer Architecture News10.1145/882105.88210931:3(20-29)Online publication date: 1-Jun-2003
https://dl.acm.org/doi/10.1145/882105.882109
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Index Terms

Corpus-based static branch prediction

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Information & Contributors

Information

Published In

cover image ACM SIGPLAN Notices

ACM SIGPLAN Notices Volume 30, Issue 6

June 1995

327 pages

ISSN:0362-1340

EISSN:1558-1160

DOI:10.1145/223428

Editors:
Brent T. Hailpern
IBM T. J. Watson Research Center, Yorktown Heoghts, NY
,
Richard L. Wexelblat
IRS IS:AO, Washington, DC

Issue’s Table of Contents

PLDI '95: Proceedings of the ACM SIGPLAN 1995 conference on Programming language design and implementation
June 1995
335 pages
ISBN:0897916972
DOI:10.1145/207110
Chairman:
David W. Wall
Digital—Western Research Laboratory

Copyright © 1995 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 June 1995

Published in SIGPLAN Volume 30, Issue 6

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Cited By

Richter EValancius SMcclanahan JMixter JAkoglu A(2018)Balancing the learning ability and memory demand of a perceptron-based dynamically trainable neural networkThe Journal of Supercomputing10.1007/s11227-018-2374-x74:7(3211-3235)Online publication date: 1-Jul-2018
https://dl.acm.org/doi/10.1007/s11227-018-2374-x
Lee WChang J(2004)A garbage collection policy based on empirical behaviorInformation Sciences: an International Journal10.1016/j.ins.2003.05.014167:1-4(129-146)Online publication date: 2-Dec-2004
https://dl.acm.org/doi/10.1016/j.ins.2003.05.014
Vintan LSbera MMihu IFlorea A(2003)An alternative to branch predictionACM SIGARCH Computer Architecture News10.1145/882105.88210931:3(20-29)Online publication date: 1-Jun-2003
https://dl.acm.org/doi/10.1145/882105.882109
Egan CSteven GQuick PAnguera RSteven FVintan L(2003)Two-level branch prediction using neural networksJournal of Systems Architecture: the EUROMICRO Journal10.1016/S1383-7621(03)00095-X49:12-15(557-570)Online publication date: 1-Dec-2003
https://dl.acm.org/doi/10.1016/S1383-7621%2803%2900095-X
Avetisyan AGaisaryan SSamovarov O(2002)Possibilities of Optimal Execution of Parallel Programs Containing Simple and Iterated Loops on Heterogeneous Parallel Computational Systems with Distributed MemoryProgramming and Computing Software10.1023/A:101370760064328:1(28-40)Online publication date: 1-Jan-2002
https://dl.acm.org/doi/10.1023/A%3A1013707600643
Lee WChang M(2002)A study of dynamic memory management in C++ programsComputer Languages, Systems and Structures10.1016/S0096-0551(02)00015-228:3(237-272)Online publication date: 1-Oct-2002
https://dl.acm.org/doi/10.1016/S0096-0551%2802%2900015-2
Steven GAnguera REgan CSteven FVintan L(2001)Dynamic branch prediction using neural networksProceedings Euromicro Symposium on Digital Systems Design10.1109/DSD.2001.952279(178-185)Online publication date: 2001
https://doi.org/10.1109/DSD.2001.952279
Chang JLee WSrisa-an W(2001)A study of the allocation behavior of C++ programsJournal of Systems and Software10.1016/S0164-1212(00)00122-957:2(107-118)Online publication date: 22-Jun-2001
https://dl.acm.org/doi/10.1016/S0164-1212%2800%2900122-9
Ramirez ALarriba-Pey JValero M(2001)Branch Prediction Using Profile DataEuro-Par 2001 Parallel Processing10.1007/3-540-44681-8_57(386-394)Online publication date: 17-Aug-2001
https://doi.org/10.1007/3-540-44681-8_57
Farooq MKhubaib John L(2013)Store-Load-Branch (SLB) predictorProceedings of the 2013 IEEE 19th International Symposium on High Performance Computer Architecture (HPCA)10.1109/HPCA.2013.6522307(59-70)Online publication date: 23-Feb-2013
https://dl.acm.org/doi/10.1109/HPCA.2013.6522307
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