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Automatic Streamization of Image Processing Applications

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Languages and Compilers for Parallel Computing (LCPC 2014)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8967))

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Abstract

New many-core architectures such as the Kalray MPPA-256 provide energy-efficiency and high performance for embedded systems. However, to take advantage of these opportunities, careful manual optimizations are required. We investigate the automatic streamization of image processing applications, implemented in C on top of a dedicated API, onto this target accessed through the \(\varSigma \mathrm{C}\) dataflow language. We discuss compiler and runtime design choices and their impact on performance. Our compilation techniques are implemented as source-to-source transformations in the PIPS open-source compilation framework. Experiments show lowest energy consumption on the Kalray MPPA target compared to other hardware targets for a range of 8 test applications.

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Aknowledgements

Thanks to Danielle Bolan and Pierre Jouvelot for proof-reading, Antoniu Pop for his advises and bibliography pointers, Kalray engineers Frédéric Blanc, Jérôme Bussery and Stéphane Gailhard for their support and to anonymous reviewers whose comments greatly helped to improve this paper.

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Authors and Affiliations

  1. MINES ParisTech, PSL Research University, Paris, France

    Pierre Guillou, Fabien Coelho & François Irigoin

Authors
  1. Pierre Guillou
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  2. Fabien Coelho
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  3. François Irigoin
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Corresponding author

Correspondence to Pierre Guillou .

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Editors and Affiliations

  1. Intel Corporation, Santa Clara, California, USA

    James Brodman

  2. Intel Corporation, Santa Clara, California, USA

    Peng Tu

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Guillou, P., Coelho, F., Irigoin, F. (2015). Automatic Streamization of Image Processing Applications. In: Brodman, J., Tu, P. (eds) Languages and Compilers for Parallel Computing. LCPC 2014. Lecture Notes in Computer Science(), vol 8967. Springer, Cham. https://doi.org/10.1007/978-3-319-17473-0_15

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  • DOI: https://doi.org/10.1007/978-3-319-17473-0_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-17472-3

  • Online ISBN: 978-3-319-17473-0

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