Advertisement

A Twofold Distributed Game-Tree Search Approach Using Interconnected Clusters

  • Kai Himstedt
  • Ulf Lorenz
  • Dietmar P. F. Möller
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5168)

Abstract

Even sophisticated classical approaches to parallelize game-tree search are restricted to using one single cluster at most. One further idea to speed up the game-tree search is to extend the cluster on the lowest level with specialized hardware components. Two well-known examples for this idea are the FPGA based Hydra system and IBM’s Deep Blue. Taking computer chess as an example in this paper a contrasting idea is introduced: A parallelized chess program running on a cluster forms a base component. With a second parallel approach on top several clusters can be used to achieve a further speedup. Results based on benchmarks and on the participation in the latest World Computer-Chess Championship will be presented.

Keywords

Hash Table Distribute Hash Table Good Move Search Depth History Table 
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.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Feldmann, R.: Game Tree Search on Massively Parallel Systems. PhD Thesis, University of Paderborn, Paderborn (1993)Google Scholar
  2. 2.
    Feldmann, R., Mysliwietz, M., Monien, B.: Studying Overheads in Massively Parallel Min/Max-Tree Evaluation. In: 6th ACM Annual symposium on parallel algorithms and architectures (SPAA 1994), New York, pp. 94–104 (1994)Google Scholar
  3. 3.
    Donninger, C., Kure, A., Lorenz, U.: Parallel Brutus: The First Distributed, FPGA Accelerated Chess Program. In: Proceedings of the 18th International Parallel and Distributed Processing Symposium (IPDPS 2004), CD-ROM. Santa Fe, p. 44 (2004)Google Scholar
  4. 4.
    Donninger, C., Lorenz, U.: The Chess Monster Hydra. In: Becker, J., Platzner, M., Vernalde, S. (eds.) FPL 2004. LNCS, vol. 3203, pp. 927–932. Springer, Heidelberg (2004)Google Scholar
  5. 5.
    Himstedt, K.: An Optimistic Pondering Approach for Asynchronous Distributed Game-Tree Search. ICGA Journal 28(2), 77–90 (2005)Google Scholar
  6. 6.
    Knuth, D.E., Moore, R.W.: An Analysis of Alpha-Beta Pruning. Artificial Intelligence 6, 293–326 (1975)zbMATHCrossRefMathSciNetGoogle Scholar
  7. 7.
    de Bruin, A., Plaat, A., Schaeffer, J., Pijls, W.: A minimax Algorithm better than SSS*. Artificial Intelligence 87, 255–293 (1999)Google Scholar
  8. 8.
    Reinefeld, A.: Spielbaum-Suchverfahren. Springer, Berlin (1989)zbMATHGoogle Scholar
  9. 9.
    Anantharaman, T.S.: Extension heuristics. ICCA Journal 14(2), 47–63 (1991)MathSciNetGoogle Scholar
  10. 10.
    Beal, D.F.: Experiments with the Null Move. In: Beal, D.F. (ed.) Advances in Computer Chess 5, pp. 65–79. Elsevier Science Publishers B.V., Amsterdam (1989)Google Scholar
  11. 11.
    Donninger, C.: Null Move and Deep Search: Selective-search Heuristics for Obtuse Chess Programs. ICCA Journal 16(3), 137–143 (1993)Google Scholar
  12. 12.
    Björnsson, Y., Marsland, T.A.: Multi-cut αβ-pruning in game-tree search. Theoretical Computer Science 252(1-2), 177–196 (2001)zbMATHCrossRefMathSciNetGoogle Scholar
  13. 13.
    Schaeffer, J.: The History Heuristic and Alpha-Beta Search Enhancements in Practice. IEEE Transactions on Pattern Analysis and Machine Intelligence 11(11), 1203–1212 (1989)CrossRefGoogle Scholar
  14. 14.
    Shannon, C.E.: Programming a computer for playing chess. Philosophical Magazine 41, 256–275 (1950)zbMATHMathSciNetGoogle Scholar
  15. 15.
    Slate, D.J., Atkin, L.R.: CHESS 4.5 – The Northwestern University chess program. In: Frey, P.W. (ed.) Chess Skill in Man and Machine, pp. 82–118. Springer, Heidelberg (1977)Google Scholar
  16. 16.
    Condon, J.H., Thompson, K.: Belle Chess Hardware. In: Clarke, M.R.B. (ed.) Advances in Computer Chess 3, pp. 45–54. Pergamon Press, Oxford (1982)Google Scholar
  17. 17.
    Berliner, H.: Hitech Chess: From Master to Senior Master with no Hardware Change. In: International Workshop on Industrial Applications of Machine Intelligence and Vision (MIV 1989), Tokyo, pp. 12–21 (1989)Google Scholar
  18. 18.
    Hyatt, R.M., Gower, A.E., Nelson, H.L.: Cray Blitz. In: Beal, D.F. (ed.) Advances in Computer Chess 4, pp. 8–18. Pergamon Press, Oxford (1986)Google Scholar
  19. 19.
    Hsu, F.-H.: IBM’s Deep Blue Chess grandmaster chips. IEEE Micro 19(2), 70–81 (1999)CrossRefGoogle Scholar
  20. 20.
    Hsu, F.-H.: Behind Deep Blue: Building the Computer that Defeated the World Chess Champion. Princeton University Press, Princeton (2002)zbMATHGoogle Scholar
  21. 21.
    Hsu, F.-H., Anantharaman, T.S., Campbell, M.S., Nowatzyk, A.: Deep Thought. In: Marsland, T.A., Schaeffer, J. (eds.) Computers, Chess, and Cognition, pp. 55–78. Springer, Heidelberg (1990)Google Scholar
  22. 22.
    Foster, I., Kesselman, C., Tuecke, S.: The Anatomy of the Grid: Enabling Scalable Virtual Organizations. International Journal of High Performance Computing Applications 15(3), 200–222 (2001)CrossRefGoogle Scholar
  23. 23.
    Zobrist, A.L.: A Hashing Method with Applications for Game Playing. Technical Report 88. University of Wisconsin, Computer Sciences Department, Madison (1970)Google Scholar
  24. 24.
    Lim, Y.J.: On Forward Pruning in Game-Tree Search. PhD Thesis, National University of Singapore, Singapore (2007)Google Scholar
  25. 25.
    Hyatt, R.M.: Using Time Wisely. ICCA Journal 7(1), 4–9 (1984)Google Scholar
  26. 26.
    Althöfer, I., Donninger, C., Lorenz, U., Rottmann, V.: On Timing, Permanent Brain and Human Intervention. In: van den Herik, H.J., Herschberg, I.S., Uiterwijk, J.W.H.M. (eds.) Advances in Computer Chess 7, pp. 285–296. University of Limburg, Maastricht (1994)Google Scholar
  27. 27.
    Fleming, P.J., Wallace, J.J.: How not to lie with statistics: the correct way to summarize benchmark results. CACM 29(3), 218–221 (1986)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Kai Himstedt
    • 1
  • Ulf Lorenz
    • 2
  • Dietmar P. F. Möller
    • 1
  1. 1.Department of InformaticsUniversity of HamburgHamburgGermany
  2. 2.Department of MathematicsTechnical University DarmstadtDarmstadtGermany

Personalised recommendations