Complex Branch Profiling for Dynamic Conditional Execution

Branch predictors are widely used as an alternative to deal with conditional branches. Despite the high accuracy rates, misprediction penalties are still large in any superscalar pipeline. DCE, or Dynamic Conditional Execution, is a alternative to reduce the number of predicted branches by executing both paths of certain branches thus reducing the number of predictions and therefore the misprediction occurrence. The goal of this work is to analyze the complexity of branch structures and determine the number of branches that can be predicated in DCE and the distribution of mispredictions according to the classification proposed. The complex branch classification proposed extends the classification presented by Klauser [KLA98]. As result, it is showed that an average of 35% of all branches can be predicated in DCE and around 32% of mispredictions fall into these branches. Keywords— Superscalar architectures, Multipath execution, Branch prediction, Dynamic predication