Report Number: CSL-TR-92-553
Institution: Stanford University, Computer Systems Laboratory
Title: Branch predication using large self history
Author: Johnson, John D.
Date: December 1992
Abstract: Branch prediction is the main method of providing speculative opportunities for new high performance processors, therefore the accuracy of branch prediction is becoming very important. Motivated by this desire to achieve high levels of branch prediction, this study examines methods of using up to 24 bits branch direction history to determine the probable outcome of the next execution of a conditional branch. Using profiling to train a prediction logic function achieves an average branch prediction accuracy of up to 96.9% for the six benchmarks used in this study.