Abstract
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.
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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)
Fok, K.L., Wong, T.T., Wong, M.L.: Evolutionary computing on consumer graphics hardware. IEEE Intelligent Systems 22(2), 69–78 (2007)
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)
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)
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)
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)
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, 1
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)
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)
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)
Robilliard, D., Marion-Poty, V., Fonlupt, C.: Genetic programming on graphics processing units. Genetic Programming and Evolvable Machines 10(4), 447–471 (2009)
Schwefel, H.P.: Numerical Optimization of Computer Models. Wiley, Chichester (1981)
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)
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Maitre, O., Lachiche, N., Collet, P. (2012). Two Ports of a Full Evolutionary Algorithm onto GPGPU. In: Hao, JK., Legrand, P., Collet, P., Monmarché, N., Lutton, E., Schoenauer, M. (eds) Artificial Evolution. EA 2011. Lecture Notes in Computer Science, vol 7401. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35533-2_9
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DOI: https://doi.org/10.1007/978-3-642-35533-2_9
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