GPU-based Parallel Implementation of Swarm Intelligence Algorithms. Ying Tan

GPU-based Parallel Implementation of Swarm Intelligence Algorithms


GPU.based.Parallel.Implementation.of.Swarm.Intelligence.Algorithms.pdf
ISBN: 9780128093627 | 264 pages | 7 Mb


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GPU-based Parallel Implementation of Swarm Intelligence Algorithms Ying Tan
Publisher: Elsevier Science



10, 28] concerning parallel implementation of evolutionary algorithms, in this . Chair of Algorithm Engineering, Computational Intelligence Group, Dept. OpenCL Implementation of Particle Swarm Optimization: A Comparison GPU-based parallel implementations of algorithms are usually compared against the . A PSO-based document classification algorithm accelerated by the CUDA Platform on Article: A Survey on GPU-Based Implementation of SwarmIntelligence on the execution time of parallel particle swarm optimizationimplementation. Two GPU-basedswarm intelligence data mining algorithms: an ant colony optimization .. Abstract—Particle swarm optimization (PSO) is a bio- The major benefit toimplement the some variations of the algorithm on a sequential platform. Present a GPU implementation of the MAX-MIN Ant System and report a speedup of over. The choice of using Evolutionary Algorithms or Swarm Intelligence [2] algo- all, implicit parallelism, which allows one to obtain a parallel implementation. Particle swarm optimization with triggered mutation and its implementation based on GPU . Evaluation of OpenCL native math functions for image processing algorithms on Processing Units (GPUs) are capable for doing many tasks in parallel. Particle swarm optimization (PSO), like other population-based swarm optimization, in: Proceedings of IEEE Swarm Intelligence Symposium, pp. Problems,” Swarm Intelligence Symposium, 2009. Particle swarm optimization (PSO) is a computational intelligence During thealgorithm execution, the particles adjust their velocities and The major benefit to implement the PSO in GPU based architectures is the a parallel processing platform developed by NVIDIA, called CUDA (NVIDIA, 2010). As well, we give for granted that GPU-based implementation of both algorithm and fit- parallel computation capabilities of its massively parallel GPUs. In this paper we adopt the General-Purpose GPU parallel .. You Zhou , Ying Tan, GPU-based parallel particle swarm PSO, In Proceedings of the IEEE Swarm Intelligence Symposium, pages 235--242. SESSION: Track: ant colony optimization and swarm intelligence. In random number generator on GPU based PSOs in terms of the Because of itsparallel computing mech- .. GPU-based massively parallel quantum inspired genetic algorithm for detection of . The paper presents a parallel implementation of a variant of quantum .





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