Merging Path and GShare Indexing in Perception Branch Prediction

Report
Authors:Tarjan, David, Department of Computer ScienceUniversity of Virginia Skadron, Kevin, Department of Computer ScienceUniversity of Virginia
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%.

Rights:
All rights reserved (no additional license for public reuse)
Language:
English
Source Citation:

Tarjan, David, and Kevin Skadron. "Merging Path and GShare Indexing in Perception Branch Prediction." University of Virginia Dept. of Computer Science Tech Report (2004).

Publisher:
University of Virginia, Department of Computer Science
Published Date:
2004