Improving Branch Prediction Performance with a Generalized Design for Dynamic Branch Predictors

this paper. This predictor is a general case of most of the predictors used nowadays, including One-Level Predictor, Two-level predictor, Gshare, and all their close and distant variations. Exact pros and cons of different predictors are clearly analyzed under the same general format. The concept in the traditional Gshare predictor is then extended to form a more flexible predictor under the same construct. By following this generalized design scheme, we are able to fine-tune various composing parameters to reach an optimal predictor and even allow the predictor to adjust according to various types of applications. From our simulation results, it is evident that significant improvement over traditional predictors is achieved without incurring any additional hardwar