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Source-to-source compilation targeting OpenMP-based automatic parallelization of C applications

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Abstract

Directive-driven programming models, such as OpenMP, are one solution for exploring the potential parallelism when targeting multicore architectures. Although these approaches significantly help developers, code parallelization is still a non-trivial and time-consuming process, requiring parallel programming skills. Thus, many efforts have been made toward automatic parallelization of the existing sequential code. This article presents AutoPar-Clava, an OpenMP-based automatic parallelization compiler which: (1) statically detects parallelizable loops in C applications; (2) classifies variables used inside the target loop based on their access pattern; (3) supports reduction clauses on scalar and array variables whenever it is applicable; and (4) generates a C OpenMP parallel code from the input sequential version. The effectiveness of AutoPar-Clava is evaluated by using the NAS and Polyhedral Benchmark suites and targeting a x86-based computing platform. The achieved results are very promising and compare favorably with closely related auto-parallelization compilers, such as Intel C/C++ Compiler (icc), ROSE, TRACO and CETUS.

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Notes

  1. http://www.openmp.org/wp-content/uploads/openmp-4.5.pdf#page=210.

  2. http://www.cs.umd.edu/projects/omega/.

  3. https://sourceforge.net/projects/polybench/.

  4. https://www.nas.nasa.gov/publications/npb.html.

  5. https://sourceforge.net/projects/traco.

  6. https://engineering.purdue.edu/Cetus.

  7. https://software.intel.com/en-us/articles/step-by-step-optimizing-with-intel-c-compiler.

  8. https://software.intel.com/en-us/forums/intel-c-compiler/topic/755677.

  9. https://software.intel.com/en-us/node/522957.

  10. https://github.com/specs-feup/specs-lara/tree/master/Publications/2019-SC.

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Acknowledgements

This work was partially funded by the ANTAREX project through the EU H2020 FET-HPC program under Grant No. 671623. João Bispo acknowledges the support provided by Fundação para a Ciência e a Tecnologia, Portugal, under Post-Doctoral Grant SFRH/BPD/118211/2016.

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Authors and Affiliations

  1. INESC TEC and Faculdade de Engenharia, Universidade do Porto, Porto, Portugal

    Hamid Arabnejad, João Bispo & João M. P. Cardoso

  2. LIACC and Faculdade de Engenharia, Universidade do Porto, Porto, Portugal

    Jorge G. Barbosa

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  1. Hamid Arabnejad
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  2. João Bispo
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  3. João M. P. Cardoso
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  4. Jorge G. Barbosa
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Correspondence to Jorge G. Barbosa.

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Arabnejad, H., Bispo, J., Cardoso, J.M.P. et al. Source-to-source compilation targeting OpenMP-based automatic parallelization of C applications. J Supercomput 76, 6753–6785 (2020). https://doi.org/10.1007/s11227-019-03109-9

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