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Merging Path and GShare Indexing in Perception Branch Prediction

Tarjan, David; Skadron, Kevin
Format
Report
Author
Tarjan, David
Skadron, Kevin
Abstract
We introduce the hashed perceptron predictor, which merges the concepts behind the gshare, path-based and perceptron branch predictors. This predictor can achieve superior accuracy to a path-based and a global perceptron predictor, previously the most accurate dynamic branch predictors known in the literature. We also show how such a predictor can be ahead pipelined to yield one cycle effective latency. On 11 programs from the SPECint2000 set of benchmarks, the hashed perceptron predictor improves accuracy by up to 22% over a path-based perceptron and improves IPC by up to 6.5%.
Language
English
Date Received
2012-10-29
Published
University of Virginia, Department of Computer Science, 2004
Published Date
2004
Rights
All rights reserved (no additional license for public reuse)
Collection
Libra Open Repository

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