Probabilistic data flow analysis: a linear equational approach

Alessandra Di Pierro
(University of Verona)
Herbert Wiklicky
(Imperial College London)

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.

In Gabriele Puppis and Tiziano Villa: Proceedings Fourth International Symposium on Games, Automata, Logics and Formal Verification (GandALF 2013), Borca di Cadore, Dolomites, Italy, 29-31th August 2013, Electronic Proceedings in Theoretical Computer Science 119, pp. 150–165.
Published: 16th July 2013.

ArXived at: https://dx.doi.org/10.4204/EPTCS.119.14 bibtex PDF
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