Probabilistic data flow analysis: a linear equational approach
Programming Languages
2013-07-18 v1
Abstract
Speculative optimisation relies on the estimation of the probabilities that certain properties of the control flow are fulfilled. Concrete or estimated branch probabilities can be used for searching and constructing advantageous speculative and bookkeeping transformations. We present a probabilistic extension of the classical equational approach to data-flow analysis that can be used to this purpose. More precisely, we show how the probabilistic information introduced in a control flow graph by branch prediction can be used to extract a system of linear equations from a program and present a method for calculating correct (numerical) solutions.
Cite
@article{arxiv.1307.4474,
title = {Probabilistic data flow analysis: a linear equational approach},
author = {Alessandra Di Pierro and Herbert Wiklicky},
journal= {arXiv preprint arXiv:1307.4474},
year = {2013}
}
Comments
In Proceedings GandALF 2013, arXiv:1307.4162