Print ISSN: 1681-6900

Online ISSN: 2412-0758

Keywords : Advanced Processor Architecture


A Hybrid Neural Based Dynamic Branch Prediction Unit

Gheni A. Ali

Engineering and Technology Journal, 2012, Volume 30, Issue 6, Pages 1066-1081

Modern high performance processor architectures have come to depend upon
highly pipelined operation in order to achieve improvements in operating speed. As a result, the cost associated with flushing the pipeline and refilling it when a branch instruction is mis-predicted can significantly impact processor performance. Many schemes, from the extremely simple to the highly complex, have been proposed to
improve branch prediction accuracy. Conventional two-level branch predictors predict the outcome of a branch either based on the( local branch history) information, comprising the previous outcomes of a single branch (intra-branch correlation), or based on the (global branch history) information, comprising the previous outcomes of all branches (inter-branch correlation). The misprediction
rates for these predictors are very high when they predict branch instructions with hybrid correlations. In this paper we suggest a hybrid perceptron based predictor which employs up to 31-bits of both local and global branch history information to minimize the misprediction rates. The software written for simulation and testing
shows that the suggested hybrid predictor achieves a high accuracy. Our results shows that the best response of the predictor is obtained on history length of 16- bits.