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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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https://hal.inria.fr/inria-00551509
Contributor : Albert Cohen <>
Submitted on : Tuesday, January 4, 2011 - 12:04:42 AM
Last modification on : Wednesday, September 16, 2020 - 5:06:38 PM
Long-term archiving on: : Monday, November 5, 2012 - 3:15:49 PM

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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. ⟨inria-00551509⟩

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