Skip to main content
SpringerLink
Log in

Parallel Differential Evolution in the PGAS Programming Model Implemented with PCJ Java Library

  • Conference paper
  • First Online:
Parallel Processing and Applied Mathematics (PPAM 2015)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9573))

Abstract

New ways to exploit parallelism of large scientific codes are still researched on. In this paper we present parallelization of the differential evolution algorithm. The simulations are implemented in Java programming language using PGAS programing paradigm enabled by the PCJ library. The developed solution has been used to test differential evolution on a number of mathematical function as well as to fine-tune the parameters of nematode’s C. Elegans connectome model. The results have shown that a good scalability and performance was achieved with relatively simple and easy to develop code.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Sutter, H.: The free lunch is over. a fundamental turn toward concurrency in software. Dr. Dobbs J. 30(3), 202–210 (2005)

    Google Scholar 

  2. Tasoulis, D.K., Pavlidis, N.G., Plagianakos, V.P., Vrahatis, M.N.: Parallel differential evolution. In: IEEE Congress on Evolutionary Computation (CEC) (2004)

    Google Scholar 

  3. Parallel Computing in Java. Homepage: http://pcj.icm.edu.pl/. Accessed 6 November 2015

  4. Berkeley UPC. Homepage: http://upc.lbl.gov/. Accessed 6 November 2015

  5. Information technology - Programming languages - Fortran. ISO, Language standard ISO/IEC: 1539–1 (2010)

    Google Scholar 

  6. Rice University: Coarray Fortran 2.0. Homepage: http://caf.rice.edu/. Accessed 6 November 2015

  7. Chapel Programming Language. Homepage: http://chapel.cray.com/. Accessed 6 November 2015

  8. X10 Programming Language. http://x10-lang.org/. Accessed 6 November 2015

  9. Das, S., Suganthan, P.N.: Differential evolution: a survey of the state-of-the-art. IEEE Trans. Evol. Comput. 15(1), 4–32 (2010)

    Article  Google Scholar 

  10. Fogel, L.J., Owens, A.J., Walsh, M.J.: Artificial Intelligence through Simulated Evolution. Wiley, New York (1966)

    MATH  Google Scholar 

  11. Rechenberg, I.: Evolutionsstrategie - optimierung technischer systeme nach prinzipien der biologischen evolution, Ph.D. thesis (1971)

    Google Scholar 

  12. Schwafel, H.-P.: Numerische optimierung von computer-modellen. Ph.D. thesis (1974)

    Google Scholar 

  13. Holland, J.H.: Adaptation in Natural and Artificial Systems. University of Michigan Press, Ann Arbor (1975)

    Google Scholar 

  14. Storn, R., Price, K.V.: Differential evolution. a simple and eficient adaptive scheme for global optimization over continuous spaces: ICSI, TR-95-012 (1995). http://icsi.berkeley.edu/storn/litera.html. Accessed 6 November 2015

  15. Kromer, P., Platos, J., Snasel, V.: Parallel differential evolution in unified parallel C. In: IEEE Congress on Evolutionary Computation (CEC), pp. 642–649. Cancun (2013)

    Google Scholar 

  16. Ungar, D.: Everything you know (about parallel programming) is wrong!. IBM Research Technical report, A Wild Screed About the Future (2011)

    Google Scholar 

  17. Feoktisov, V.: Differential Evolution. In Search of Solutions. Springer, New York (2007)

    Google Scholar 

  18. Apache Commons. homepage: https://commons.apache.org/. Accessed 2 November 2015

  19. Tušar, T., Filipič, B.: Differential evolution versus genetic algorithms in multiobjective optimization. In: Obayashi, S., Deb, K., Poloni, C., Hiroyasu, T., Murata, T. (eds.) EMO 2007. LNCS, vol. 4403, pp. 257–271. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  20. Zhou, C.: Fast parallelization of differential evolution algorithm using mapreduce. In: Proceedings of the 12th Annual Conference on Genetic and Evolutionary Computation, Portland, Oregon, USA, pp. 1113–1114 (2010)

    Google Scholar 

Download references

Acknowledgement

This work has been performed using the PL-Grid infrastructure. Partial support from CHIST-ERA consortium is acknowledged.

Author information

Authors and Affiliations

  1. Faculty of Mathematics and Computer Science, Nicolaus Copernicus University, Toruń, Poland

    Łukasz Górski

  2. Interdisciplinary Centre for Mathematical and Computational Modelling, University of Warsaw, Warsaw, Poland

    Franciszek Rakowski & Piotr Bała

Authors
  1. Łukasz Górski
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Franciszek Rakowski
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Piotr Bała
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to Łukasz Górski or Piotr Bała .

Editor information

Editors and Affiliations

  1. Czestochowa University of Technolog, Czestochowa, Poland

    Roman Wyrzykowski

  2. Department of Computer Science, University of Southern California, Marina Del Rey, California, USA

    Ewa Deelman

  3. Electrical Engineering & Comput. Science, University of Tennessee, Knoxville, Tennessee, USA

    Jack Dongarra

  4. Czestochowa University of Technology, Institute of Computer & Information Sci., Czestochowa, Poland

    Konrad Karczewski

  5. Department of Computer Science, AGH University of Science and Technology, Krakow, Poland

    Jacek Kitowski

  6. Systèmes d’informations, Big Data et Rec, AGH University of Science and Technology, Krakow, Poland

    Kazimierz Wiatr

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing Switzerland

About this paper

Cite this paper

Górski, Ł., Rakowski, F., Bała, P. (2016). Parallel Differential Evolution in the PGAS Programming Model Implemented with PCJ Java Library. In: Wyrzykowski, R., Deelman, E., Dongarra, J., Karczewski, K., Kitowski, J., Wiatr, K. (eds) Parallel Processing and Applied Mathematics. PPAM 2015. Lecture Notes in Computer Science(), vol 9573. Springer, Cham. https://doi.org/10.1007/978-3-319-32149-3_42

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-32149-3_42

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-32148-6

  • Online ISBN: 978-3-319-32149-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation