On the Automatic Generation of Efficient Parallel Iterative Sorting Algorithms

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@InProceedings{Chennupati:2015:GECCOcompa,
  author =       "Gopinath Chennupati and R. Muhammad Atif Azad and 
                 Conor Ryan",
  title =        "On the Automatic Generation of Efficient Parallel
                 Iterative Sorting Algorithms",
  booktitle =    "GECCO Companion '15: Proceedings of the Companion
                 Publication of the 2015 Annual Conference on Genetic
                 and Evolutionary Computation",
  year =         "2015",
  editor =       "Sara Silva and Anna I Esparcia-Alcazar and 
                 Manuel Lopez-Ibanez and Sanaz Mostaghim and Jon Timmis and 
                 Christine Zarges and Luis Correia and Terence Soule and 
                 Mario Giacobini and Ryan Urbanowicz and 
                 Youhei Akimoto and Tobias Glasmachers and 
                 Francisco {Fernandez de Vega} and Amy Hoover and Pedro Larranaga and 
                 Marta Soto and Carlos Cotta and Francisco B. Pereira and 
                 Julia Handl and Jan Koutnik and Antonio Gaspar-Cunha and 
                 Heike Trautmann and Jean-Baptiste Mouret and 
                 Sebastian Risi and Ernesto Costa and Oliver Schuetze and 
                 Krzysztof Krawiec and Alberto Moraglio and 
                 Julian F. Miller and Pawel Widera and Stefano Cagnoni and 
                 JJ Merelo and Emma Hart and Leonardo Trujillo and 
                 Marouane Kessentini and Gabriela Ochoa and Francisco Chicano and 
                 Carola Doerr",
  isbn13 =       "978-1-4503-3488-4",
  keywords =     "genetic algorithms, genetic programming, grammatical
                 evolution: Poster",
  pages =        "1369--1370",
  month =        "11-15 " # jul,
  organisation = "SIGEVO",
  address =      "Madrid, Spain",
  URL =          "http://doi.acm.org/10.1145/2739482.2764695",
  DOI =          "doi:10.1145/2739482.2764695",
  publisher =    "ACM",
  publisher_address = "New York, NY, USA",
  abstract =     "Increasing availability of multiple processing
                 elements on the recent desktop and personal computers
                 poses unavoidable challenges in realizing their
                 processing power. The challenges include programming
                 these high processing elements. Parallel programming is
                 an apt solution for such a realization of the
                 computational capacity. However, it has many
                 difficulties in developing the parallel programs.

                 We present Multi-core Grammatical Evolution for
                 Parallel Sorting (MCGE-PS) that automatically produces
                 native parallel sorting programs. These programs are of
                 iterative nature that also exploit the processing power
                 of the multi-core processors efficiently. The
                 performance of the resultant programs is measured in
                 terms of the execution time. The results indicate a
                 significant improvement over the state-of-the-art
                 implementations. Finally, we conduct an empirical
                 analysis on computational complexity of the evolving
                 parallel programs. The results are competitive with
                 that of the state-of-the-art evolutionary attempts.",
  notes =        "Also known as \cite{2764695} Distributed at
                 GECCO-2015.",
}

Genetic Programming entries for Gopinath Chennupati R Muhammad Atif Azad Conor Ryan

Citations