A Feedback Based Neural Branch Predictor for Branch Prediction

Abstract

Branch predictors are very important in modern superscalar processor setups. They are responsible for determining the branch instructions that will run smoothly.This paper proposes a feedback neural branch predictor that is implemented in a neural network to improve processor performance. It is based on the concept of the perceptron branch predictor.This paper presents a feedback neural branch predictor that combines the multi-layer and single-layer branch predictor techniques.The proposed model is based on the feedback neural branch predictor method, which combines the multi-layer and single-layer techniques.In this paper, the multi-layer neural network has been studied to develop a neural branch predictor that can predict a misprediction event. When a prediction is made, the developed predictor can update the values of its neurons and weights.The proposed neural branch predictor can predict the weights and neurons of a given branch based on the observed misprediction. It can also update the weights and neurons when there's a misprediction. Thus by using the concept of the neural network in feedback neural branch predictor, the accuracy rate has increased to 97.10%.