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Parallel Minimax Tree Searching on GPU

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Part of the Lecture Notes in Computer Science book series (LNTCS,volume 6067)

Abstract

The paper describes results of minimax tree searching algorithm implemented within CUDA platform. The problem regards move choice strategy in the game of Reversi. The parallelization scheme and performance aspects are discussed, focusing mainly on warp divergence problem and data transfer size. Moreover, a method of minimizing warp divergence and performance degradation is described. The paper contains both the results of test performed on multiple CPUs and GPUs. Additionally, it discusses αβ parallel pruning implementation.

Keywords

  • Root Node
  • Parallelization Scheme
  • Minimax Algorithm
  • Parallel Depth
  • Thread Divergence

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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  • DOI: 10.1007/978-3-642-14390-8_47
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Rocki, K., Suda, R. (2010). Parallel Minimax Tree Searching on GPU. In: Wyrzykowski, R., Dongarra, J., Karczewski, K., Wasniewski, J. (eds) Parallel Processing and Applied Mathematics. PPAM 2009. Lecture Notes in Computer Science, vol 6067. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14390-8_47

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  • DOI: https://doi.org/10.1007/978-3-642-14390-8_47

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-14389-2

  • Online ISBN: 978-3-642-14390-8

  • eBook Packages: Computer ScienceComputer Science (R0)