Enhancing branch predictors using genetic algorithm

Md Sarwar M. Haque; Md Rafiul Hassan; Muhammad Sulaiman; Salami Onoruoiza; Joarder Kamruzzaman; Md Arifuzzaman

doi:10.1109/ICMSAO.2019.8880435

Enhancing branch predictors using genetic algorithm

Md Sarwar M. Haque
, Md Rafiul Hassan
, Muhammad Sulaiman
, Salami Onoruoiza
, Joarder Kamruzzaman
, Md Arifuzzaman

Preparatory Year Program

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

9 Scopus citations

Abstract

Dynamic branch prediction is a hardware technique used to speculate the direction of control branches. Inaccurate prediction will make all speculative works useless while accurate prediction will significantly improve microprocessors performance. In this work, we have shown that Genetic Algorithm (GA) can be used to select (near) optimal parameters for branch predictors in most cases. The GA-enhanced predictors take time to find suitable parameters, but once the values of these parameters are determined, the GA-enhanced predictors take the same time to execute as the basic predictors with increased accuracy.

Original language	English
Title of host publication	2019 8th International Conference on Modeling Simulation and Applied Optimization, ICMSAO 2019
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781538676844
DOIs	https://doi.org/10.1109/ICMSAO.2019.8880435
State	Published - Apr 2019

Publication series

Name	2019 8th International Conference on Modeling Simulation and Applied Optimization, ICMSAO 2019

Bibliographical note

Publisher Copyright:
© 2019 IEEE.

Keywords

Branch prediction
Genetic algorithm
Neural network

ASJC Scopus subject areas

Signal Processing
Industrial and Manufacturing Engineering
Safety, Risk, Reliability and Quality
Control and Optimization
Modeling and Simulation
Health Informatics

Access to Document

10.1109/ICMSAO.2019.8880435

Cite this

Haque, M. S. M., Hassan, M. R., Sulaiman, M., Onoruoiza, S., Kamruzzaman, J., & Arifuzzaman, M. (2019). Enhancing branch predictors using genetic algorithm. In 2019 8th International Conference on Modeling Simulation and Applied Optimization, ICMSAO 2019 Article 8880435 (2019 8th International Conference on Modeling Simulation and Applied Optimization, ICMSAO 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICMSAO.2019.8880435

Haque, Md Sarwar M. ; Hassan, Md Rafiul ; Sulaiman, Muhammad et al. / Enhancing branch predictors using genetic algorithm. 2019 8th International Conference on Modeling Simulation and Applied Optimization, ICMSAO 2019. Institute of Electrical and Electronics Engineers Inc., 2019. (2019 8th International Conference on Modeling Simulation and Applied Optimization, ICMSAO 2019).

@inproceedings{4810faf6b7cc428b89f8335834983c8f,

title = "Enhancing branch predictors using genetic algorithm",

abstract = "Dynamic branch prediction is a hardware technique used to speculate the direction of control branches. Inaccurate prediction will make all speculative works useless while accurate prediction will significantly improve microprocessors performance. In this work, we have shown that Genetic Algorithm (GA) can be used to select (near) optimal parameters for branch predictors in most cases. The GA-enhanced predictors take time to find suitable parameters, but once the values of these parameters are determined, the GA-enhanced predictors take the same time to execute as the basic predictors with increased accuracy.",

keywords = "Branch prediction, Genetic algorithm, Neural network",

author = "Haque, \{Md Sarwar M.\} and Hassan, \{Md Rafiul\} and Muhammad Sulaiman and Salami Onoruoiza and Joarder Kamruzzaman and Md Arifuzzaman",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.",

year = "2019",

month = apr,

doi = "10.1109/ICMSAO.2019.8880435",

language = "English",

series = "2019 8th International Conference on Modeling Simulation and Applied Optimization, ICMSAO 2019",

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Haque, MSM, Hassan, MR, Sulaiman, M, Onoruoiza, S, Kamruzzaman, J & Arifuzzaman, M 2019, Enhancing branch predictors using genetic algorithm. in 2019 8th International Conference on Modeling Simulation and Applied Optimization, ICMSAO 2019., 8880435, 2019 8th International Conference on Modeling Simulation and Applied Optimization, ICMSAO 2019, Institute of Electrical and Electronics Engineers Inc. https://doi.org/10.1109/ICMSAO.2019.8880435

Enhancing branch predictors using genetic algorithm. / Haque, Md Sarwar M.; Hassan, Md Rafiul; Sulaiman, Muhammad et al.
2019 8th International Conference on Modeling Simulation and Applied Optimization, ICMSAO 2019. Institute of Electrical and Electronics Engineers Inc., 2019. 8880435 (2019 8th International Conference on Modeling Simulation and Applied Optimization, ICMSAO 2019).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

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AU - Haque, Md Sarwar M.

AU - Hassan, Md Rafiul

AU - Sulaiman, Muhammad

AU - Onoruoiza, Salami

AU - Kamruzzaman, Joarder

AU - Arifuzzaman, Md

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AB - Dynamic branch prediction is a hardware technique used to speculate the direction of control branches. Inaccurate prediction will make all speculative works useless while accurate prediction will significantly improve microprocessors performance. In this work, we have shown that Genetic Algorithm (GA) can be used to select (near) optimal parameters for branch predictors in most cases. The GA-enhanced predictors take time to find suitable parameters, but once the values of these parameters are determined, the GA-enhanced predictors take the same time to execute as the basic predictors with increased accuracy.

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KW - Neural network

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M3 - Conference contribution

AN - SCOPUS:85074991606

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BT - 2019 8th International Conference on Modeling Simulation and Applied Optimization, ICMSAO 2019

PB - Institute of Electrical and Electronics Engineers Inc.

ER -

Haque MSM, Hassan MR, Sulaiman M, Onoruoiza S, Kamruzzaman J, Arifuzzaman M. Enhancing branch predictors using genetic algorithm. In 2019 8th International Conference on Modeling Simulation and Applied Optimization, ICMSAO 2019. Institute of Electrical and Electronics Engineers Inc. 2019. 8880435. (2019 8th International Conference on Modeling Simulation and Applied Optimization, ICMSAO 2019). doi: 10.1109/ICMSAO.2019.8880435

Enhancing branch predictors using genetic algorithm

Abstract

Publication series

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this