A comparative analysis of schemes for correlated branch prediction

Cliff Young, Nicolas Gloy, Michael D. Smith
1995 Proceedings of the 22nd annual international symposium on Computer architecture - ISCA '95  
Modern high-performance architectures require extremely accurate branch prediction to overcome the performance limitations of conditional branches. We present a framework that categorizes branch prediction schemes by the way in which they partition dynamic branches and by the kind of predictor that they use. The framework allows us to compare and contrast branch prediction schemes, and to analyze why they work. We use the framework to show how a static correlated branch prediction scheme
more » ... es branch bias and thus improves overall branch prediction accuracy. We also use the framework to identify the fundamental differences between static and dynamic correlated branch prediction schemes. This study shows that there is room to improve the prediction accuracy of existing branch prediction schemes.
doi:10.1145/223982.224438 dblp:conf/isca/YoungGS95 fatcat:h67lwy65pvfcrh4asmfbm3z2ru