Corpus-Based Static Branch Prediction

Correctly predicting the direction that branches will take is increasingly important in today’s wide-issue computer architectures. The name program-based branch prediction is given to static branch prediction techniques that base their prediction on a program’s structure. In this paper, we investigate a new approach to program-based branch prediction that uses a body of existing programs to predict the branch behavior in a new program. We call this approach to program-based branch prediction, evidence-based static prediction, or ESP. The main idea of ESP is that the behavior of a corpus of programs can be used to infer the behavior of new programs. In this paper, we use a neural network to map static features associated with each branch to the probabilty that the branch will be taken. ESP shows significant advantages over other prediction mechanisms. Specifically, it is a program-based technique, it is effective across a range of programming languages and programming styles, and...

• Type: Conference
• Year: 1995
• Where: PLDI
• Authors: Brad Calder, Dirk Grunwald, Donald C. Lindsay, James H. Martin, Michael Mozer, Benjamin G. Zorn
• Keywords: Branch Prediction, PLDI 1995, Program-based Branch Prediction, Programming Languages, Static Branch Prediction