Instruction Cache Prediction Using Bayesian Networks

Authors:
Mark Bartlett;Iain Bate;James Cussens
Affiliations:
Department of Computer Science, University of York, UK, email: firstname.lastname@cs.york.ac.uk;Department of Computer Science, University of York, UK, email: firstname.lastname@cs.york.ac.uk;Department of Computer Science, University of York, UK, email: firstname.lastname@cs.york.ac.uk
Venue:
Proceedings of the 2010 conference on ECAI 2010: 19th European Conference on Artificial Intelligence
Year:
2010

Citing 4
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Abstract

Storing instructions in caches has led to dramatic increases in the speed at which programs can execute. However, this has also made it harder to reason about the time needed for execution in those domains where temporal behaviour of code is important. This paper presents a novel approach to predicting which instructions will be found in the cache when required using machine learning. More specifically, we demonstrate a method in which a Bayesian network is inferred from examples of a program running and is then used to predict the presence of instructions in the cache when the same program is run with unknown inputs.