An Alternative TAGE-like Conditional Branch Predictor

被引：8
|
作者：
Michaud, Pierre [1 ]
机构：
[1] Univ Rennes, IRISA, CNRS, Inria, Campus Beaulieu, F-35000 Rennes, France
来源：
ACM TRANSACTIONS ON ARCHITECTURE AND CODE OPTIMIZATION | 2018年 / 15卷 / 03期
关键词：
Branch prediction; PPM; TAGE; Bayesian confidence estimation;
D O I：
10.1145/3226098
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
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.
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收藏
页数：23
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