Branch Prediction DANIEL A. JIM ENEZ Rutgers University and CALVIN LIN The...  Home/Search
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Abstract: This article presents a new and highly accurate method for branch prediction. The key idea is to use one of the simplest possible neural methods, the perceptron, as an alternative to the commonly used two-bit counters. The source of our predictor's accuracy is its ability to use long history lengths, because the hardware resources for our method scale linearly, rather than exponentially, with the history length. We describe two versions of perceptron predictors, and we evaluate these ... (Update)
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BibTeX entry: (Update)
@misc{ daniel-neural,
author = "Branch Prediction Daniel",
title = "Neural Methods for Dynamic",
url = "citeseer.ist.psu.edu/731976.html" }
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