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Parametric GPU Code Generation for Affine Loop Programs

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Languages and Compilers for Parallel Computing (LCPC 2013)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8664))

Abstract

Partitioning a parallel computation into finite-sized chunks for effective mapping onto a parallel machine is a critical concern for source-to-source compilation. In the context of OpenCL and CUDA, this translates to the definition of a uniform hyper-rectangular partitioning of the parallel execution space where each partition is subject to a fine-grained distribution of resources that has a direct yet hard to estimate impact on performance. This paper develops the first compilation scheme for generating parametrically tiled codes for affine loop programs on GPUs, which facilitates run-time exploration of partitioning parameters as a fast and portable way of finding the ones that yield maximum performance. Our approach is based on a parametric tiling scheme for producing wavefronts of parallel rectangular partitions of parametric size and a novel runtime system that manages wavefront execution and local memory usage dynamically through an inspector-executor mechanism. An experimental evaluation demonstrates the effectiveness of our approach for wavefront as well as rectangularly-parallel partitionings.

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Notes

  1. 1.

    In order to facilitate the generality of the definitions presented and used in the rest of the paper, the OpenCL terminology will be primarily adopted.

  2. 2.

    A floor operator returns the largest integer that is not greater than the actual result of the fraction.

  3. 3.

    Currently supporting CUDA targets.

  4. 4.

    http://www.doc.ic.ac.uk/~phjk/LCPC13

  5. 5.

    We used tile sizes ranging from 8 to 32 with a stride of 4 while on Jacobi-1d we searched up to time tile sizes of 256.

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Acknowledgments

This work was supported in part by the U.S. National Science Foundation through awards 0811457, 0904549, 1059417 and 1205682. The authors would also like to thank Codeplay Software and EPSRC for their support as well as Louis-Noël Pouchet and Sanket Tavarageri for their valuable contributions.

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Authors and Affiliations

  1. Imperial College London, London, UK

    Athanasios Konstantinidis & Paul H. J. Kelly

  2. Louisiana State University, Baton Rouge, USA

    J. Ramanujam

  3. The Ohio State University, Columbus, USA

    P. Sadayappan

Authors
  1. Athanasios Konstantinidis
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  2. Paul H. J. Kelly
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  3. J. Ramanujam
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  4. P. Sadayappan
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Corresponding author

Correspondence to Athanasios Konstantinidis .

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Editors and Affiliations

  1. Silicon Valley, Qualcomm Research, San Jose, California, USA

    Călin Cașcaval

  2. Silicon Valley, Qualcomm Research, San Jose, California, USA

    Pablo Montesinos

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Konstantinidis, A., Kelly, P.H.J., Ramanujam, J., Sadayappan, P. (2014). Parametric GPU Code Generation for Affine Loop Programs. In: Cașcaval, C., Montesinos, P. (eds) Languages and Compilers for Parallel Computing. LCPC 2013. Lecture Notes in Computer Science(), vol 8664. Springer, Cham. https://doi.org/10.1007/978-3-319-09967-5_8

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  • DOI: https://doi.org/10.1007/978-3-319-09967-5_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-09966-8

  • Online ISBN: 978-3-319-09967-5

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