Global context-based value prediction

Various methods for value prediction have been proposed to overcome the limits imposed by data dependencies within programs. Using a value prediction scheme, an instruction's computed value is predicted during the fetch stage and forwarded to all dependent instructions to speed up execution. Value prediction schemes have been based on a local context by predicting values using the values generated by the same instruction. This paper presents techniques that predict values of an instruction based on a global context where the behavior of other instructions is used in prediction. The global context includes the path along which an instruction is executed and the values computed by other previously completed instructions. We present techniques that augment conventional last value and stride predictors with global context information. Experiments performed using path-based techniques with realistic table sizes resulted in an increase in prediction of 6.4-8.4% over the current prediction schemes. Prediction using values computed by other instructions resulted in a further improvement of 7.2% prediction accuracy over the best path-based predictor.