Sciweavers

Share
APCSAC
2006
IEEE

Understanding Prediction Limits Through Unbiased Branches

9 years 4 months ago
Understanding Prediction Limits Through Unbiased Branches
The majority of currently available branch predictors base their prediction accuracy on the previous k branch outcomes. Such predictors sustain high prediction accuracy but they do not consider the impact of unbiased branches which are difficult-to-predict. In this paper, we quantify and evaluate the impact of unbiased branches and show that any gain in prediction accuracy is proportional to the frequency of unbiased branches. By using the SPECcpu2000 integer benchmarks we show that there are a significant proportion of unbiased branches which severely impact on prediction accuracy (averaging between 6% and 24% depending on the prediction context used).
Lucian N. Vintan, Arpad Gellert, Adrian Florea, Ma
Added 10 Jun 2010
Updated 10 Jun 2010
Type Conference
Year 2006
Where APCSAC
Authors Lucian N. Vintan, Arpad Gellert, Adrian Florea, Marius Oancea, Colin Egan
Comments (0)
books