Value Based BTB Indexing for indirect jump prediction

Abstract

History-based branch direction predictors for conditional branches are shown to be highly accurate. Indirect branches however, are hard to predict as they may have multiple targets corresponding to a single indirect branch instruction. We propose the Value Based BTB Indexing (VBBI), a correlation-based target address prediction scheme for indirect jump instructions. For each static hard-to-predict indirect jump instruction, the compiler identifies a ‘hint instruction’, whose output value strongly correlates with the target address of the indirect jump instruction. At run time, multiple target addresses of the indirect jump instruction are stored and subsequently accessed from the BTB at different indices computed using the jump instruction PC and the hint instruction output values. In case the hint instruction has not finished its execution when the jump instruction is fetched, a second and more accurate target address prediction is made when the hint instruction output is available, thus reducing the jump misprediction penalty. We compare our design to the regular BTB design and the best previously proposed indirect jump predictor, the tagged target cache (TTC). Our evaluation shows that the VBBI scheme improves the indirect jump target prediction accuracy by 48% and 18%, compared with the baseline BTB and TTC designs, respectively. This results in average performance improvement of 16.4% over the baseline BTB scheme, and 13% improvement over the TTC predictor. Out of this performance improvement 2% is contributed by target prediction overriding which is accurate 96% of the time.