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Evaluation of Autoparallelization Toolkits for Commodity GPUs

  • David WilliamsEmail author
  • Valeriu Codreanu
  • Po Yang
  • Baoquan Liu
  • Feng Dong
  • Burhan Yasar
  • Babak Mahdian
  • Alessandro Chiarini
  • Xia Zhao
  • Jos B. T. M. Roerdink
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8384)

Abstract

In this paper we evaluate the performance of the OpenACC and Mint toolkits against C and CUDA implementations of the standard PolyBench test suite. Our analysis reveals that performance is similar in many cases, but that a certain set of code constructs impede the ability of Mint to generate optimal code. We then present some small improvements which we integrate into our own GPSME toolkit (which is derived from Mint) and show that our toolkit now out-performs OpenACC in the majority of tests.

Keywords

GPU computing Autoparallelization Evaluation 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • David Williams
    • 1
    Email author
  • Valeriu Codreanu
    • 1
  • Po Yang
    • 2
  • Baoquan Liu
    • 2
  • Feng Dong
    • 2
  • Burhan Yasar
    • 3
  • Babak Mahdian
    • 4
  • Alessandro Chiarini
    • 5
  • Xia Zhao
    • 6
  • Jos B. T. M. Roerdink
    • 1
  1. 1.University of GroningenGroningenThe Netherlands
  2. 2.University of BedfordshireLutonUK
  3. 3.RotaSoft LtdAnkaraTurkey
  4. 4.ImageMetryPragueCzech Republic
  5. 5.Super Computing SolutionsBolognaItaly
  6. 6.AnSmartWembleyUK

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