Parallel Genetic Algorithm on the CUDA Architecture

1. Pharr, M., Fernando, R.: GPU Gems 2: Programming Techniques for High-Performance Graphics and General-Purpose Computation. Addison-Wesley Professional, Reading (2005)

   Google Scholar 

2. Nguyen, H.: GPU gems 3. Addison-Wesley Professional, Reading (2007)

   Google Scholar 

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

   Google Scholar 

4. Jiang, C., Snir, M.: Automatic Tuning Matrix Multiplication Performance on Graphics Hardware. In: Proceedings of the 14th International Conference on Parallel Architectures and Compilation Techniques, pp. 185–196 (2005)

   Google Scholar 

5. Galoppo, N., Govindaraju, N.K., Henson, M., Manocha, D.: LU-GPU: Efficient Algorithms for Solving Dense Linear Systems on Graphics Hardware. In: Proceedings of the ACM/IEEE SC 2005 Conference, vol. 3 (2005)

   Google Scholar 

6. Cant-Paz, E.: Efficient and Accurate Parallel Genetic Algorithms. Kluwer Academic Publishers, Dordrecht (2000)

   Google Scholar 

7. NVIDIA, C.: Compute Unified Device Architecture Programming Guide. NVIDIA: Santa Clara, CA (2007)

   Google Scholar 

8. Munshi, A.: The OpenCL specification version 1.0. Khronos OpenCL Working Group (2009)

   Google Scholar 

9. Harris, M., Luebke, D.: GPGPU: General-purpose computation on graphics hardware. In: Proceedings of the International Conference on Computer Graphics and Interactive Techniques: ACM SIGGRAPH 2005 Courses, Los Angeles, California (2005)

   Google Scholar 

10. Yu, Q., Chen, C., Pan, Z.: Parallel genetic algorithms on programmable graphics hardware. In: Wang, L., Chen, K., S. Ong, Y. (eds.) ICNC 2005. LNCS, vol. 3612, pp. 1051–1059. Springer, Heidelberg (2005)

    Google Scholar 

11. 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, NPC Workshops, pp. 855–862 (2007)

    Google Scholar 

12. Maitre, Q., Baumes, L.A., Lachiche, N., Corma, A., Collet, P.: Coarse grain parallelization of evolutionary algorithms on GPGPU cards with EASEA. In: Proceedings of the 11th Annual conference on Genetic and evolutionary computation table of contents, Montreal, Qubec, Canada, pp. 1403–1410 (2009) ISBN 978-1-60558-325-9

    Google Scholar 

13. Wong, M.L., Wong, T.T.: Implementation of Parallel Genetic Algorithms on Graphics Processing Units. In: Intelligent and Evolutionary Systems, vol. 187, pp. 197–216. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

14. Matthew, W.: GAlib: A C++ Library of Genetic Algorithm Components. Massachusetts Institute of Technology (1996)

    Google Scholar 

15. Pelikan, M., Sastry, K., Cantú-Paz, E.: Scalable Optimization via Probabilistic Modeling: From Algorithms to Applications. Studies in Computational Intelligence. Springer, Heidelberg (2006)

    Book  MATH  Google Scholar 

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