Rehashable BTB: An Adaptive Branch Target Buffer to Improve the Target Predictability of Java Code

Java programs are increasing in popularity and prevalence on numerous platforms, including high-performance general-purpose processors. The dynamic characteristics of the Java runtime system present unique performance challenges for several aspects of microarchitecture design. In this work, we focus on the effects of indirect branches on branch target address prediction performance. Runtime bytecode translation, just-in-time compilation, frequent calls to the native interface libraries, and dependence on virtual methods increase the frequency of polymorphic indirect branches. Therefore, accurate target address prediction for indirect branches is very important for Java code. This paper characterizes the indirect branch behavior in Java processing and proposes an adaptive branch target buffer (BTB) design to enhance the predictability of the targets. Our characterization shows that a traditional BTB will frequently mispredict polymorphic indirect branches, significantly deteriorating predictor accuracy in Java processing. Therefore, we propose a Rehashable branch target buffer (R-BTB), which dynamically identifies polymorphic indirect branches and adapts branch target storage to accommodate multiple targets for a branch. The R-BTB improves the target predictability of indirect branches without sacrificing overall target prediction accuracy. Simulations show that the R-BTB eliminates 61% of the indirect branch mispredictions suffered with a traditional BTB for Java programs running in interpreter mode (46% in JIT mode), which leads to a 57% decrease in overall target address misprediction rate (29% in JIT mode). With an equivalent number of entries, the R-BTB also outperforms the previously proposed target cache scheme for a majority of Java programs by adapting to a greater variety of indirect branch behaviors.