A practical automatic polyhedral parallelizer and locality optimizer

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A practical automatic polyhedral parallelizer and locality optimizer (2008)

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by Uday Bondhugula , Albert Hartono , J. Ramanujam

Venue:	In PLDI ’08: Proceedings of the ACM SIGPLAN 2008 conference on Programming language design and implementation
Citations:	120 - 8 self

BibTeX

@INPROCEEDINGS{Bondhugula08apractical,
    author = {Uday Bondhugula and Albert Hartono and J. Ramanujam},
    title = {A practical automatic polyhedral parallelizer and locality optimizer},
    booktitle = {In PLDI ’08: Proceedings of the ACM SIGPLAN 2008 conference on Programming language design and implementation},
    year = {2008}
}

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Abstract

We present the design and implementation of an automatic polyhedral source-to-source transformation framework that can optimize regular programs (sequences of possibly imperfectly nested loops) for parallelism and locality simultaneously. Through this work, we show the practicality of analytical model-driven automatic transformation in the polyhedral model.Unlike previous polyhedral frameworks, our approach is an end-to-end fully automatic one driven by an integer linear optimization framework that takes an explicit view of finding good ways of tiling for parallelism and locality using affine transformations. The framework has been implemented into a tool to automatically generate OpenMP parallel code from C program sections. Experimental results from the tool show very high performance for local and parallel execution on multi-cores, when compared with state-of-the-art compiler frameworks from the research community as well as the best native production compilers. The system also enables the easy use of powerful empirical/iterative optimization for general arbitrarily nested loop sequences.

Keyphrases

locality optimizer practical automatic polyhedral parallelizer automatic polyhedral source-to-source transformation framework powerful empirical iterative optimization program section explicit view affine transformation tool show polyhedral model integer linear optimization framework regular program high performance loop sequence parallel execution easy use state-of-the-art compiler framework previous polyhedral framework experimental result native production compiler analytical model-driven automatic transformation research community openmp parallel code good way

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