Branch Behavior Characterization for Multimedia Applications

Modern embedded processors, like Intel's XScale, employ dynamic branch prediction to reduce performance penalty caused by branch instructions. Existing branch predictor de-
signs are all based on the behavior of applications on a GPP (general purpose processor), such as gcc and gzip. However, for an embedded system, such as smart phone, multimedia and communication applications are two main workloads. I found that a commonly used bimodal branch predictor actually has lower branch prediction accuracy for multimedia/communication workloads than workloads for GPP. In this thesis, I perform detailed analysis on the branch behavior of multimedia/communication applications. I found that the iteration counts of loop branches in these applications are very regular, and most of them are counted loops. I also found that many mispredictions of if-branches occur on sequential comparisons of array elements. Finally, many of the values of control variables in if-branches
have the property of data predictability. The findings of this work are important for branch predictor design for embedded processors.