The impact of branch direction history combined with global branch history in branch prediction
Most branch predictors use the PC information of the branch instruction and its dynamic Global Branch History (GBH). In this letter, we suggest a Branch Direction History (BDH) as the third component of the branch prediction and analyze its impact upon the prediction accuracy. Additionally, we propose a new branch predictor, direction-gshare predictor, which utilizes the BDH combined with the GBH. At first, we model a neural network with (PC, GBH, and BDH) and analyze their actual impact upon the branch prediction accuracy, and then we simulate our new predictor, the direction-gshare predictor. The simulation results show that the aliasing in Pattern History Table (PHT) is significantly reduced by the additional use of BDH information. The direction-g share predictor outperforms bimodal predictor, two-level adaptive predictor and gshare predictor up to 15.32%, 5.41% and 5.74% respectively, without additional hardware costs.
branch direction history global branch history branch prediction direction-gshare predictor gshare predictor