Self-organizing Migration Algorithm on GPU with CUDA

A modification of Self-organizing migration algorithm for general-purpose computing on graphics processing units is proposed in this paper. The algorithm is implemented in C++ with its core parts in c-CUDA. Its implementation details and performance are evaluated and compared to previous, pure C++ version of algorithm. 6 commonly used artificial test functions are used to test the performance. The test results clearly show significant speed gains without a compromise in convergence quality.

[1]  Guohua Zhou,et al.  A parallel Ant Colony Optimization algorithm with GPU-acceleration based on All-In-Roulette selection , 2010, Third International Workshop on Advanced Computational Intelligence.

[2]  Francisco Fernndez de Vega,et al.  Parallel and Distributed Computational Intelligence , 2010, Parallel and Distributed Computational Intelligence.

[3]  Jack J. Purdum,et al.  C programming guide , 1983 .

[4]  William B. Langdon,et al.  Large-Scale Bioinformatics Data Mining with Parallel Genetic Programming on Graphics Processing Units , 2013, Massively Parallel Evolutionary Computation on GPGPUs.

[5]  Renato A. Krohling,et al.  Swarm's flight: Accelerating the particles using C-CUDA , 2009, 2009 IEEE Congress on Evolutionary Computation.

[6]  Tien-Tsin Wong,et al.  Evolutionary Computing on Consumer Graphics Hardware , 2007, IEEE Intelligent Systems.

[7]  Ying Tan,et al.  GPU-based parallel particle swarm optimization , 2009, 2009 IEEE Congress on Evolutionary Computation.

[8]  Tien-Tsin Wong,et al.  Parallel evolutionary algorithms on graphics processing unit , 2005, 2005 IEEE Congress on Evolutionary Computation.

[9]  Roman Senkerik,et al.  Comparison of Differential Evolution and SOMA in the task of chaos control optimization - Extended study: Complex target CF , 2009, 2009 IEEE Congress on Evolutionary Computation.

[10]  Renato A. Krohling,et al.  Differential evolution algorithm on the GPU with C-CUDA , 2010, IEEE Congress on Evolutionary Computation.

[11]  Godfrey C. Onwubolu,et al.  New optimization techniques in engineering , 2004, Studies in Fuzziness and Soft Computing.

[12]  Jirí Jaros,et al.  Parallel Genetic Algorithm on the CUDA Architecture , 2010, EvoApplications.

[13]  Sifa Zhang,et al.  Implementation of Parallel Genetic Algorithm Based on CUDA , 2009, ISICA.

[14]  Ivan Zelinka,et al.  Evolutionary Algorithms in Aircraft Trim Optimization , 2008, 2008 19th International Workshop on Database and Expert Systems Applications.