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Improving an autotuning engine for 3D Fast Wavelet Transform on manycore systems

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Abstract

This paper presents an enhanced auto-optimization method to run the 3D-Fast Wavelet Transform on different computing units in a system (GPU, MIC, CPU). The proposed method automatically selects a set of parameter values (block size, number of streams and number of threads) in order to reduce the total execution time, obtaining performances close to the optimal and decreasing the number of evaluations needed.

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Acknowledgments

This work was supported by the Spanish MINECO, as well as by European Commission FEDER funds, under grant TIN2012-38341-C04-03. We are grateful to the reviewers for their valuable comments.

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Authors and Affiliations

  1. University of Murcia, Murcia, Spain

    Gregorio Bernabé, Javier Cuenca & Domingo Giménez

  2. Technical University of Cartagena, Cartagena, Spain

    Luis Pedro García

Authors
  1. Gregorio Bernabé
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  2. Javier Cuenca
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  3. Luis Pedro García
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  4. Domingo Giménez
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Corresponding author

Correspondence to Gregorio Bernabé.

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Bernabé, G., Cuenca, J., García, L.P. et al. Improving an autotuning engine for 3D Fast Wavelet Transform on manycore systems. J Supercomput 70, 830–844 (2014). https://doi.org/10.1007/s11227-014-1302-y

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  • DOI: https://doi.org/10.1007/s11227-014-1302-y

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