DCOM-based Parallel Distributed Implementation of GP

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@Article{tanev:2000:pdiGP,
  author =       "Ivan T. Tanev and Takashi Uozumi and Koichi Ono",
  title =        "DCOM-based Parallel Distributed Implementation of GP",
  journal =      "Parallel and Distributed Computing Practices",
  year =         "2000",
  volume =       "3",
  number =       "1",
  month =        mar,
  keywords =     "genetic algorithms, genetic programming",
  ISSN =         "1097-2803",
  URL =          "http://www.scpe.org/index.php/scpe/article/view/181",
  abstract =     "We present an approach for parallel distributed
                 implementation of genetic programming, which is devoted
                 to improve the computational performance of genetic
                 programming by exploiting parallelism at the level of
                 evaluation of the individuals. The approach is based on
                 DCOM client-server model. Using the DCOM-paradigm
                 offers the advantages of parallel distributed
                 implementation of genetic programming, such as binary
                 standardization, platform-, machine- and
                 protocol-neutrality, and seamless integration with
                 different Internet protocols. The developed
                 implementation of genetic programming runs in LAN
                 and/or Internet environments.

                 The double-queued multi-threaded architecture of the
                 DCOM-server, aimed to extend the functionality of the
                 DCOM with features, such as asynchronous communications
                 still implementing blocking-mode calls, and reduced
                 communication overhead of the evaluation of simple
                 GP-individuals, is developed. The implementation of
                 batching, directed towards the alleviation of
                 communication overhead during the evaluation of simple
                 GP-individuals, is proposed. Analytically estimated and
                 experimentally obtained performance evaluation results
                 are discussed. The results show that clear super linear
                 speedup can be achieved upon code growth in genetic
                 programming.",
  notes =        "parallel and distributed computing Journal renamed
                 'Scalable Computing: Practice and Experience'",
}

Genetic Programming entries for Ivan T Tanev Takashi Uozumi Koichi Ono

Citations