Enabling more optimizations in GRAPHITE: ignoring memory-based dependences

Konrad Trifunovic 1 Albert Cohen 1
1 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 : Data-dependences need to be analyzed to guarantee the legality of a loop transformations and parallelization. But many dependences are spurious memory-based dependences: they are induced by storing values in the same memory location. Spurious dependences reduce the degrees of freedom in loop transformations and parallelization. The effective handling of spurious data-dependences in GIMPLE is essential for the effectiveness of polyhedral compilation in GCC. We show that most memory-based-dependences induced by the gimplification can be ignored, rather than scalar/array expanded. Our method relies on an extension of the violated-dependence-analysis technique implemented in GRAPHITE. It has a minimal impact on compilation time and guarantees that we are not loosing any transformation opportunity compared to a source-to-source compilers. We will detail the algorithm, the current state of the implementation and the future plans.
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Communication dans un congrès
Proceedings of the 8th GCC Developper's Summit, Oct 2010, Ottawa, Canada. 2010
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Konrad Trifunovic, Albert Cohen. Enabling more optimizations in GRAPHITE: ignoring memory-based dependences. Proceedings of the 8th GCC Developper's Summit, Oct 2010, Ottawa, Canada. 2010. 〈inria-00551509〉

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