An Alternative TAGE-like Conditional Branch Predictor-Reference-Cited by-同舟云学术

An Alternative TAGE-like Conditional Branch Predictor

Published:2018-10-08 Issue:3 Volume:15 Page:1-23
ISSN:1544-3566
Container-title:ACM Transactions on Architecture and Code Optimization
language:en
Short-container-title:ACM Trans. Archit. Code Optim.

Author:

Michaud Pierre¹

Affiliation:

1. Inria, University of Rennes, CNRS, IRISA, France

Abstract

TAGE is one of the most accurate conditional branch predictors known today. However, TAGE does not exploit its input information perfectly, as it is possible to obtain significant prediction accuracy improvements by complementing TAGE with a statistical corrector using the same input information. This article proposes an alternative TAGE-like predictor making statistical correction practically superfluous.

Publisher

Association for Computing Machinery (ACM)

Subject

Hardware and Architecture,Information Systems,Software

Link

https://dl.acm.org/doi/pdf/10.1145/3226098

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