• DocumentCode
    174351
  • Title

    Clustering using artificial bee colony on CUDA

  • Author

    Janousek, Jan ; Platos, Jan ; Snasel, Vaclav

  • Author_Institution
    Dept. of Comput. Sci., VSB - Tech. Univ. of Ostrava, Poruba, Czech Republic
  • fYear
    2014
  • fDate
    5-8 Oct. 2014
  • Firstpage
    3803
  • Lastpage
    3807
  • Abstract
    Artificial bee colony is a meta-heuristic optimization algorithm based on the behavior of honey bee swarm. These bees work largely independently of other bees, making the algorithm suitable for parallel implementation. Within this paper, we introduce the algorithm itself and its subsequent parallelization utilizing the CUDA platform. The runtime speedup is demonstrated on several commonly used test functions for optimization. The algorithm is subsequently applied to the problem of clustering real data.
  • Keywords
    ant colony optimisation; parallel architectures; pattern clustering; CUDA platform; artificial bee colony; honey bee swarm behavior; metaheuristic optimization algorithm; parallel implementation; real data clustering; test functions; Algorithm design and analysis; Clustering algorithms; Educational institutions; Electroencephalography; Graphics processing units; Optimization; Runtime; CUDA; artificial bee colony; clustering; parallel algorithm;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man and Cybernetics (SMC), 2014 IEEE International Conference on
  • Conference_Location
    San Diego, CA
  • Type

    conf

  • DOI
    10.1109/SMC.2014.6974523
  • Filename
    6974523