Young, CliffGloy, NicolasSmith, Michael2016-01-061995Young, Cliff, Nicolas Gloy, and Michael D. Smith. 1995. A Comparative Analysis of Schemes for Correlated Branch Prediction. Harvard Computer Science Group Technical Report TR-06-95.http://nrs.harvard.edu/urn-3:HUL.InstRepos:24015805Modern 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 increases 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.en-USbranch predictionbranch correlationbranch stream characteristicsA Comparative Analysis of Schemes for Correlated Branch PredictionResearch Paper or Report2016-01-06