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Parallel Minimax Tree Searching on GPU

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Parallel Processing and Applied Mathematics (PPAM 2009)

Part of the book series: Lecture Notes in Computer Science ((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.

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References

  1. Knuth, D.E., Moore, R.W.: An analysis of alpha-beta pruning. Artificial Intelligence 6, 293–326 (1975)

    Article  MATH  MathSciNet  Google Scholar 

  2. Manohararajah, V.: Parallel Alpha-Beta Search on Shared Memory Multiprocessors, Master Thesis, Graduate Department of Electrical and Computer Engineering, University of Toronto (2001)

    Google Scholar 

  3. Warren, H.S.: Hacker’s Delight. Addison-Wesley, Reading (2002)

    Google Scholar 

  4. Schaeffer, J.: Improved Parallel Alpha Beta Search. In: Proceedings of 1986 ACM Fall Joint Computer Conference (1986)

    Google Scholar 

  5. Borovska, P., Lazarova, M.: Efficiency of Parallel Minimax Algorithm for Game Tree Search. In: Proceedings of the International Conference on Computer Systems and Technologies (2007)

    Google Scholar 

  6. Schaeffer, J., Brockington, M.G.: The APHID Parallel αβ algorithm. In: Proceedings of the 8th IEEE Symposium on Parallel and Distributed Processing, p. 428 (1996)

    Google Scholar 

  7. Hewett, R., Ganesan, K.: Consistent Linear speedup in Parallel Alpha-beta Search. In: Proceedings of the ICCI 1992, Fourth International Conference on Computing and Information, pp. 237–240 (1992)

    Google Scholar 

  8. Hopp, H., Sanders, P.: Parallel Game Tree Search on SIMD Machines. In: Ferreira, A., Rolim, J.D.P. (eds.) IRREGULAR 1995. LNCS, vol. 980, pp. 349–361. Springer, Heidelberg (1995)

    Google Scholar 

  9. Sanders, P.: Efficient Emulation of MIMD behavior on SIMD Machines. In: Proceedings of the International Conference on Massively Parallel Processing Applications and Development, pp. 313–321 (1995)

    Google Scholar 

  10. Russell, S., Norvig, P.: Artificial Intelligence: A Modern Approach, pp. 163–171. Prentice Hall, Englewood Cliffs (2003)

    Google Scholar 

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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)

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