Two Ports of a Full Evolutionary Algorithm onto GPGPU

  • Ogier Maitre
  • Nicolas Lachiche
  • Pierre Collet
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7401)


This paper presents two parallelizations of a standard evolutionary algorithm on an NVIDIA GPGPU card, thanks to a parallel replacement operator.

These algorithms tackle new problems where previously presented approaches do not obtain satisfactory speedup. If programming is more complicated and fewer options are allowed, the whole algorithm is executed in parallel, thereby fully exploiting the intrinsic parallelism of EAs and the many available GPGPU cores.

Finally, the method is validated using two benchmarks.


Evolutionary Algorithm Shared Memory Global Memory Single Instruction Multiple Data Evaluation Step 
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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Amdahl, G.: Validity of the single processor approach to achieving large scale computing capabilities. In: Proceedings of the Spring Joint Computer Conference, April 18-20, pp. 483–485. ACM, New York (1967)Google Scholar
  2. 2.
    Fok, K.L., Wong, T.T., Wong, M.L.: Evolutionary computing on consumer graphics hardware. IEEE Intelligent Systems 22(2), 69–78 (2007)CrossRefGoogle Scholar
  3. 3.
    Langdon, W.B.: A Many Threaded CUDA Interpreter for Genetic Programming. In: Esparcia-Alcázar, A.I., Ekárt, A., Silva, S., Dignum, S., Uyar, A.Ş. (eds.) EuroGP 2010. LNCS, vol. 6021, pp. 146–158. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  4. 4.
    Li, J.M., Wang, X.J., He, R.S., Chi, Z.X.: An efficient fine-grained parallel genetic algorithm based on GPU-accelerated. In: IFIP International Conference on Network and Parallel Computing Workshops, pp. 855–862 (2007)Google Scholar
  5. 5.
    Maitre, O., Lachiche, N., Clauss, P., Baumes, L., Corma, A., Collet, P.: Efficient Parallel Implementation of Evolutionary Algorithms on GPGPU Cards. In: Sips, H., Epema, D., Lin, H.-X. (eds.) Euro-Par 2009. LNCS, vol. 5704, pp. 974–985. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  6. 6.
    Maitre, O., Baumes, L.A., Lachiche, N., Corma, A., Collet, P.: Coarse grain parallelization of evolutionary algorithms on GPGPU cards with EASEA. In: GECCO 2009: Proceedings of the 11th Annual Conference on Genetic and Evolutionary Computation, pp. 1403–1410. ACM, New York (2009)CrossRefGoogle Scholar
  7. 7.
    Maitre, O., Krüger, F., Querry, S., Lachiche, N., Collet, P.: EASEA: Specification and execution of evolutionary algorithms on GPGPU. Soft Computing - A Fusion of Foundations, Methodologies and Applications, Special Issue on Evolutionary Computation on General Purpose Graphics Processing Units, 1Google Scholar
  8. 8.
    Maitre, O., Querry, S., Lachiche, N., Collet, P.: EASEA parallelization of tree-based genetic programming. In: Fogel, et al. (eds.) IEEE CEC 2010, pp. 1–8. IEEE (2010)Google Scholar
  9. 9.
    Maitre, O., Sharma, D., Lachiche, N., Collet, P.: DISPAR-Tournament: A Parallel Population Reduction Operator That Behaves Like a Tournament. In: Di Chio, C., Cagnoni, S., Cotta, C., Ebner, M., Ekárt, A., Esparcia-Alcázar, A.I., Merelo, J.J., Neri, F., Preuss, M., Richter, H., Togelius, J., Yannakakis, G.N. (eds.) EvoApplications 2011, Part I. LNCS, vol. 6624, pp. 284–293. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  10. 10.
    Pospichal, P., Jaros, J., Schwarz, J.: Parallel Genetic Algorithm on the CUDA Architecture. In: Di Chio, C., Cagnoni, S., Cotta, C., Ebner, M., Ekárt, A., Esparcia-Alcazar, A.I., Goh, C.-K., Merelo, J.J., Neri, F., Preuß, M., Togelius, J., Yannakakis, G.N. (eds.) EvoApplicatons 2010, Part I. LNCS, vol. 6024, pp. 442–451. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  11. 11.
    Robilliard, D., Marion-Poty, V., Fonlupt, C.: Genetic programming on graphics processing units. Genetic Programming and Evolvable Machines 10(4), 447–471 (2009)CrossRefGoogle Scholar
  12. 12.
    Schwefel, H.P.: Numerical Optimization of Computer Models. Wiley, Chichester (1981)zbMATHGoogle Scholar
  13. 13.
    Yu, Q., Chen, C., Pan, Z.: Parallel Genetic Algorithms on Programmable Graphics Hardware. In: Wang, L., Chen, K., S. Ong, Y. (eds.) ICNC 2005, Part III. LNCS, vol. 3612, pp. 1051–1059. Springer, Heidelberg (2005)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Ogier Maitre
    • 1
  • Nicolas Lachiche
    • 1
  • Pierre Collet
    • 1
  1. 1.LSIITUniversity of StrasbourgIllkirchFrance

Personalised recommendations