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Attribute Grammar Genetic Programming Algorithm for Automatic Code Parallelization

  • Daniel Howard
  • Conor Ryan
  • J. J. Collins
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6935)

Abstract

A method is presented for evolving individuals that use an Attribute Grammar (AG) in a generative way. AGs are considerably more flexible and powerful than the closed, context free grammars normally employed by GP. Rather than evolving derivation trees as in most approaches, we employ a two step process that first generates a vector of real numbers using standard GP, before using the vector to produce a parse tree. As the parse tree is being produced, the choices in the grammar depend on the attributes being input to the current node of the parse tree. The motivation is automatic parallelization or the discovery of a re-factoring of a sequential code or equivalent parallel code that satisfies certain performance gains when implemented on a target parallel computing platform such as a multicore processor. An illustrative and a computed example demonstrate this methodology.

Keywords

Context Free Grammar Attribute Grammar Parallel Computing Automatic Parallelization Genetic Programming Grammatical Evolution Evolutionary Computation 

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References

  1. 1.
    Koza, J.R.: Genetic Programming: On the Programming of Computers by Means of Natural Selection. MIT Press, Cambridge (1992)zbMATHGoogle Scholar
  2. 2.
    Howard, D., Roberts, S.C.: Genetic Programming solution of the convection-diffusion equation. In: Spector, L., et al. (eds.) Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2001), pp. 34–41. Morgan Kaufmann, San Francisco (2001)Google Scholar
  3. 3.
    Baber, C., Stanton, N., Howard, D., Houghton, R.J.: Paper 15 - Predicting the Structure of Covert Networks using Genetic Programming, Cognitive Work Analysis and Social Network Analysis. Papers presented at the NATO RTO Modelling and Simulation Group Symposium held in Brussels, Belgium on October 15-16, 2009 (2009) ISBN 978-92-837-0100-2Google Scholar
  4. 4.
    Howard, D.: Bio-inspired simulation tool for PERT. In: Lee, G., et al. (eds.) Proceedings of the 2009 International Conference on Hybrid Information Technology, ICHIT 2009, Daejeon, Korea, August 27-29. ACM International Conference Proceeding Series, vol. 321, pp. 537–540. ACM, New York (2009) ISBN 978-1-60558-662-5CrossRefGoogle Scholar
  5. 5.
    Amdahl, G.: Validity of the Single Processor Approach to Achieving Large-Scale Computing Capabilities. In: AFIPS Conference Proceeding, vol. (30), pp. 483–485 (1967)Google Scholar
  6. 6.
    Ryan, C., Walsh, P.: Automatic conversion of programs from serial to parallel using Genetic Programming - The Paragen System. In: Proceedings of ParCo 1995. North-Holland, Amsterdam (1995)Google Scholar
  7. 7.
    Walsh, P., Ryan, C.: Paragen: A Novel Technique for the Autoparallelisation of Sequential Programs using Genetic Programming. In: Koza, J.R., et al. (eds.) Genetic Programming 1996: Proceedings of the First Annual Conference, pp. 406–409. Stanford University, MIT Press, CA, USA (1996)Google Scholar
  8. 8.
    Ryan, C., Laur, I.: Automatic Parallelization of Arbitrary Programs. In: Langdon, W.B., Fogarty, T.C., Nordin, P., Poli, R. (eds.) EuroGP 1999. LNCS, vol. 1598, pp. 244–254. Springer, Heidelberg (1999)CrossRefGoogle Scholar
  9. 9.
    Ryan, C., Laur, I.: Paragen - The first results. In: Poli, R., Banzhaf, W., Langdon, W.B., Miller, J., Nordin, P., Fogarty, T.C. (eds.) EuroGP 2000. LNCS, vol. 1802, pp. 338–348. Springer, Heidelberg (2000)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Daniel Howard
    • 1
  • Conor Ryan
    • 2
  • J. J. Collins
    • 2
  1. 1.Howard Science LimitedMalvernUnited Kingdom
  2. 2.Department of Computer Science and Information Science (CSIS)University of LimerickIreland

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