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FADAlib: an open source C++ library for fuzzy array dataflow analysis

Marouane Belaoucha 1 Denis Barthou 2, 3 Adrien Eliche 1 Sid Touati 1, 4
3 RUNTIME - Efficient runtime systems for parallel architectures
CNRS - Centre National de la Recherche Scientifique : UMR5800, UB - Université de Bordeaux, Inria Bordeaux - Sud-Ouest
4 ALCHEMY - Architectures, Languages and Compilers to Harness the End of Moore Years
LRI - Laboratoire de Recherche en Informatique, UP11 - Université Paris-Sud - Paris 11, Inria Saclay - Ile de France, CNRS - Centre National de la Recherche Scientifique : UMR8623
Abstract : Ubiquitous multicore architectures require that many levels of parallelism have to be found in codes. Dependence analysis is the main approach in compilers for the detection of parallelism. It enables vectorisation and automatic parallelisation, among many other optimising transformations, and is therefore of crucial importance for optimising compilers. This paper presents new open source software, \texttt{FADAlib}, performing an instance-wise dataflow analysis for scalar and array references. The software is a C++ implementation of the Fuzzy Array Dataflow Analysis (FADA) method. This method can be applied on codes with irregular control such as \texttt{while}-loops, \texttt{if-then-else} or non-regular array accesses, and computes exact instance-wise dataflow analysis on regular codes. As far as we know, \texttt{FADAlib} is the first released open source C++ implementation of instance-wise data flow dependence handling larger classes of programs. In addition, the library is technically independent from an existing compiler; It can be plugged in many of them; this article shows an example of a successful integration inside gcc/GRAPHITE. We give details concerning the library implementation and then report some initial results with gcc and possible use for trace scheduling on irregular codes.
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Marouane Belaoucha, Denis Barthou, Adrien Eliche, Sid Touati. FADAlib: an open source C++ library for fuzzy array dataflow analysis. International Conference on Computational Science, May 2010, Amsterdam, Netherlands. p2075-2084. ⟨hal-00551673⟩

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