학술논문
Analysis of the O-GEometric history length branch predictor
Document Type
Conference
Author
Source
32nd International Symposium on Computer Architecture (ISCA'05) Computer architecture Computer Architecture, 2005. ISCA '05. Proceedings. 32nd International Symposium on. :394-405 2005
Subject
Language
ISSN
1063-6897
Abstract
In this paper, we introduce and analyze the Optimized GEometric History Length (O-GEHL) branch Predictor that efficiently exploits very long global histories in the 100-200 bits range. The GEHL predictor features several predictor tables T(i) (e.g. 8) indexed through independent functions of the global branch history and branch address. The set of used global history lengths forms a geometric series, i.e., L(j) = /spl alpha//sup j-1/L(1). This allows the GEHL predictor to efficiently capture correlation on recent branch outcomes as well as on very old branches. As on perceptron predictors, the prediction is computed through the addition of the predictions read on the predictor tables. The O-GEHL predictor further improves the ability of the GEHL predictor to exploit very long histories through the addition of dynamic history fitting and dynamic threshold fitting. The O-GEHL predictor can be ahead pipelined to provide in time predictions on every cycle.