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.