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Original Articles

Accelerating parallel particle swarm optimization via GPU

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Pages 33-51 | Received 18 Nov 2009, Accepted 14 Jul 2010, Published online: 25 Aug 2010

References

  • Banks , A. , Vincent , J. and Anyakoha , C. 2007 . A review of particle swarm optimization. Part I: Background and development . Nat. Comput. , 6 ( 4 ) : 467 – 484 .
  • Banks , A. , Vincent , J. and Anyakoha , C. 2008 . A review of particle swarm optimization. Part II: Hybridisation, combinatorial, multicriteria and constrained optimization, and indicative applications . Nat. Comput. , 7 ( 1 ) : 109 – 124 .
  • Blum , C. and Merkle , D. 2008 . Swarm Intelligence: Introduction and Applications , New York : Springer-Verlag New York Inc .
  • Bratton , D. and Kennedy , J. Defining a Standard for Particle Swarm Optimization . IEEE Swarm Intelligence Symposium . 2007 , Piscataway , NJ . pp. 120 – 127 . IEEE . SIS 2007
  • Chang , J.-F. , Chu , S.-C. and Pan , J.-S. 2005 . A parallel particle swarm optimization algorithm with communication strategies . J. Inf. Sci. Eng. , 21 ( 4 ) : 809 – 818 .
  • Chapman , B. , Jost , G. , Van der Pas , R. and Kuck , D. J. 2007 . Using OpenMP: Portable Shared Memory Parallel Programming , Cambridge , MA : The MIT Press .
  • Chatterjee , A. and Siarry , P. 2006 . Nonlinear inertia weight variation for dynamic adaptation in particle swarm optimization . Comput. Oper. Res. , 33 ( 3 ) : 859 – 871 .
  • Clerc , M. 2006 . Particle Swarm Optimization , Newport Beach , CA : ISTE Publishing Company .
  • Clerc , M. and Kennedy , J. 2002 . The particle swarm-explosion, stability, and convergence in a multidimensional complex space . IEEE Trans. Evol. Comput. , 6 ( 1 ) : 58 – 73 .
  • Dean , J. and Ghemawat , S. MapReduce: Simplified Data Processing on Large Clusters . OSDI04: Sixth Symposium on Operating System Design and Implementation . Available at http://labs.google.com/papers/mapreduce-osdi04.pdf
  • Dorigo , M. and Stützle , T. 2004 . Ant Colony Optimization , Cambridge , MA : The MIT Press .
  • Elble , J. M. , Sahinidis , N. V. and Vouzis , P. 2009 . GPU computing with Kaczmarz's and other iterative algorithms for linear systems . Parallel Comput. , 36 ( 5–6 ) : 215 – 231 .
  • Engelbrecht , A. P. 2006 . Fundamentals of Computational Swarm Intelligence , Hoboken , NJ : John Wiley & Sons .
  • Fan , S. K.S. and Chang , J. M. A Modified Particle Swarm Optimizer Using an Adaptive Dynamic Weight Scheme . Proceedings of the 1st International Conference on Digital Human Modeling . pp. 56 – 65 . Springer-Verlag .
  • Gies , D. and Rahmat-Samii , Y. 2003 . Particle swarm optimization for reconfigurable phase-differentiated array design . Microw. Opt. Technol. Lett. , 38 ( 3 ) : 168 – 175 .
  • Glover , F. and Laguna , M. 1997 . Tabu Search , Boston , MA : Kluwer Academic Publishers .
  • Goldberg , D. E. 1989 . Genetic Algorithms in Search, Optimization and Machine Learning , Boston , MA : Addison-Wesley Longman Publishing Co., Inc .
  • Harris , M. 2007 . High Performance Computing with CUDA (Slides for Tutorial Section s05 in sc07.) . Available at http://gpgpu.org/static/sc2007/SC07CUDA5OptimizationHarris.pdf
  • Ho , S.-Y. , Shu , L.-S. and Chen , J.-H. 2004 . Intelligent evolutionary algorithms for large parameter optimization problems . IEEE Trans. Evol. Comput. , 8 ( 6 ) : 522 – 541 .
  • Ho , S. Y. , Lin , H. S. , Liauh , W. H. and Ho , S. J. 2008 . OPSO: Orthogonal particle swarm optimization and its application to task assignment problems . IEEE Trans. Syst. Man Cybernet. A , 38 ( 2 ) : 288 – 298 .
  • Ide , A. and Yasuda , K. 2005 . A basic study of adaptive particle swarm optimization . Electr. Eng. Jpn , 151 ( 3 ) : 41 – 49 .
  • Kalivarapu , V. and Winer , E. Implementation of Digital Pheromones in PSO Accelerated by Commodity Graphics Hardware . 12th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, 2008. Available at http://pdf.aiaa.org/preview/CDReadyMMAOC081876/PV20086021.pdf
  • Kennedy , J. The Behavior of Particles . Proceedings of the 7th International Conference on Evolutionary Programming VII . pp. 581 – 589 . London : Springer-Verlag .
  • Kennedy , J. Eberhart , R. C. t 1995 . “ Particle Swarm Optimization ” . In Proceedings of IEEE International Conference on Neural Networks , Vol. 4 , t , 1942 – 1948 . Piscataway , NJ : IEEE .
  • Kirkpatrick , S. , Gelatt , C. D. and Vecchi , M. P. 1983 . Optimization by simulated annealing . Science , 220 ( 4598 ) : 671 – 680 .
  • Koh , B. I. , George , A. D. , Haftka , R. T. and Fregly , B. J. 2006 . Parallel asynchronous particle swarm optimization . Int. J. Numer. Methods Eng. , 67 : 578 – 595 .
  • Krishnakumar , K. , Narayanaswamy , S. and Garg , S. 1996 . “ Solving large parameter optimization problems using a genetic algorithm with stochastic coding, in Genetic Algorithms in Engineering and Computer Science ” . Edited by: Winter , G. , Periaux , J. , Galan , M. and Cuesta , P. New York , NY : John Wiley & Sons, Inc .
  • Li , J. M. , Wan , D. L. , Chi , Z. X. and Hu , X. 2006 . A parallel particle swarm optimization algorithm based on fine-grained model with GPU-accelerating . J. Harbin Inst. Technol. , 38 ( 12 ) : 2162 – 2166 .
  • McNabb , A. W. , Monson , C. K. and Seppi , K. D. Parallel PSO using MapReduce . IEEE Congress on Evolutionary Computation . pp. 7 – 14 . CEC 2007, 2007, pp. doi:10.1109/CEC.2007.4424448
  • Mendes , R. , Kennedy , J. and Neves , J. 2004 . The fully informed particle swarm: Simpler, maybe better . IEEE Trans. Evol. Comput. , 8 ( 3 ) : 204 – 210 .
  • Mussi , L. and Cagnoni , S. 2009 . Particle swarm optimization within the CUDA architecture . Available at http://www.gpgpgpu.com/gecco2009/1.pdf
  • NVIDIA Corporation, NVIDIA CUDA CUBLAS Library 2008
  • NVIDIA Corporation . 2009 . NVIDIA CUDA Programming Guide . Version 2.3.1
  • Oster , B. 2008 . Advanced CUDA Training (NVISION 08 Tutorials) .
  • Poli , R. , Kennedy , J. and Blackwell , T. 2007 . Particle swarm optimization . Swarm Intell. , 1 ( 1 ) : 33 – 57 .
  • Poli , R. , Kennedy , J. , Blackwell , T. and Freitas , A. 2008 . “ Particle Swarms: The Second Decade ” . Hindawi Publishing Corporation .
  • Schutte , J. F. , Reinbolt , J. A. , Fregly , B. J. , Haftka , R. T. and George , A. D. 2004 . Parallel global optimization with the particle swarm algorithm . Int. J. Numer. Methods Eng. , 61 ( 13 ) : 2296 – 2315 .
  • Shi , Y. and Eberhart , R. A Modified Particle Swarm Optimizer . The 1998 IEEE International Conference on Evolutionary Computation, ICEC’98 . pp. 69 – 73 .
  • Shi , Y. and Eberhart , R. C. 1998 . Parameter Selection in Particle Swarm Optimization . Lecture Notes in Computer Science , : 591 – 600 .
  • Tomov , S. , Nath , R. , Ltaief , H. and Dongarr , J. A Scalable High Performance Cholesky Factorization for Multicore with GPU Accelerators . Proceedings of IPDPS 2010: 24th IEEE International Parallel and Distributed Processing Symposium . Available at http://icl.cs.utk.edu/newspub/submissions/tilemagmaconf.pdf
  • Venter , G. and Sobieszczanki-Sobieksi , J. 2006 . A parallel particle swarm optimization algorithm accelerated by asynchronous evaluations . J. Aerosp. Comput. Inf. Commun. , 3 : 123 – 137 .
  • Wang , D. , Wu , C.-H. , Ip , A. , Wang , D. and Yan , Y. Parallel multi-population Particle Swarm Optimization Algorithm for the Uncapacitated Facility Location problem using OpenMP . IEEE Congress on Evolutionary Computation . pp. 1214 – 1218 .
  • Zhang , Y. , Gallipoli , D. and Augarde , C. E. 2009 . Simulation-based calibration of geotechnical parameters using parallel hybrid moving boundary particle swarm optimization . Comput. Geotech. , 36 : 604 – 615 .
  • Zhou , Y. and Tan , Y. 2009 . GPU-based Parallel Particle Swarm Optimization . IEEE Congress on Evolutionary Computation , : 1493 – 1500 .
  • Zhu , W. and Curry , J. Particle Swarm with Graphics Hardware Acceleration and Local Pattern Search on Bound Constrained Problems . IEEE Swarm Intelligence Symposium (SIS ’09) . pp. 1 – 8 .

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