Parallelism of Evolutionary Design of Image Filters for Evolvable Hardware Using GPU

Created by W.Langdon from gp-bibliography.bib Revision:1.4524

  author =       "Chih-Hung Wu and Chin-Yuan Chiang and Yi-Han Chen",
  booktitle =    "14th ACIS International Conference on Software
                 Engineering, Artificial Intelligence, Networking and
                 Parallel/Distributed Computing (SNPD)",
  title =        "Parallelism of Evolutionary Design of Image Filters
                 for Evolvable Hardware Using GPU",
  year =         "2013",
  pages =        "592--597",
  month =        jul,
  keywords =     "genetic algorithms, genetic programming, Cartesian
                 genetic programming, EHW, GPU, Parallelism,
                 evolutionary design; evolvable hardware, image filter",
  DOI =          "doi:10.1109/SNPD.2013.79",
  abstract =     "Evolvable Hardware (EHW) is a combination of
                 evolutionary algorithm and reconfigurable hardware
                 devices. Due to its flexible and adaptive ability,
                 EHW-based solutions receive a lot of attention in
                 industrial applications. One of the obstacles to
                 realize an EHW-based method is its very long training
                 time. This study deals with the parallelism of
                 EHW-based design of image filters using graphic
                 processing units (GPUs). The design process is analysed
                 and decomposed into some smaller processes that can run
                 in parallel. Pixel-based data for training and
                 verifying EHW solutions are partitioned according to
                 the architecture of GPU. Several strategies for
                 deploying parallel processes are developed and
                 implemented. With the proposed method, significant
                 improvements on the efficiency of training EHW models
                 are gained. Using a GPU with 240 cores, a speedup of 64
                 times is obtained. This paper evaluates and compares
                 the performance of the proposed method with other
  notes =        "Dept. of Electr. Eng., Nat. Univ. of Kaohsiung,
                 Kaohsiung, Taiwan

                 Also known as \cite{6598525}",

Genetic Programming entries for Chih-Hung Wu Chin-Yuan Chiang Yi-Han Chen