Accurate indirect jump prediction is critical for the performance and energy efficiency of modern high-performance processors.This paper proposes the Hybrid Value Correlation (HVC) based indirect jump prediction

which combines various types of correlated information to reduce indirect jump mispredictions.First of all

our mechanism relies on the compiler to identify the correlated data values based on high-level dataflow information.Second

our mechanism maintains two kinds of correlated information:the single data value and the value history.Our mechanism makes use of a low-cost hardware structure

which dynamically chooses the best correlated information for indirect jump prediction according to different processor states.Experimental results show that HVC prediction can significantly reduce the misprediction rate over the baseline-BTB prediction and the state-of-the-art VBBI prediction.The low misprediction rate of HVC prediction leads to better performance and lower power consumption over previous predictors.