Deployment of parallel linear genetic programming using GPUs on PC and video game console platforms

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

  author =       "Garnett Wilson and Wolfgang Banzhaf",
  title =        "Deployment of parallel linear genetic programming
                 using GPUs on PC and video game console platforms",
  journal =      "Genetic Programming and Evolvable Machines",
  year =         "2010",
  volume =       "11",
  number =       "2",
  pages =        "147--184",
  month =        jun,
  keywords =     "genetic algorithms, genetic programming, Parallel
                 processing, SIMD, Graphics processing unit, GPU, GPGPU,
                 Xbox 360, Heterogeneous devices",
  ISSN =         "1389-2576",
  DOI =          "doi:10.1007/s10710-010-9102-5",
  size =         "38 pages",
  abstract =     "We present a general method for deploying parallel
                 linear genetic programming (LGP) to the PC and Xbox 360
                 video game console by using a publicly available common
                 framework for the devices called XNA (for XNA's Not
                 Acronymed). By constructing the LGP within this
                 framework, we effectively produce an LGP 'game' for PC
                 and XBox 360 that displays results as they evolve. We
                 use the GPU of each device to parallelize fitness
                 evaluation and the mutation operator of the LGP
                 algorithm, thus providing a general LGP implementation
                 suitable for parallel computation on heterogeneous
                 devices. While parallel GP implementations on PCs are
                 now common, both the implementation of GP on a video
                 game console using GPU and the construction of a GP
                 around a framework for heterogeneous devices are novel
                 contributions. The objective of this work is to
                 describe how to implement the parallel execution of LGP
                 in order to use the underlying hardware (especially
                 GPU) on the different platforms while still maintaining
                 loyalty to the general methodology of the LGP algorithm
                 built for the common framework. We discuss the
                 implementation of texture-based data structures and the
                 sequential and parallel algorithms built for their use
                 on both CPU and GPU. Following the description of the
                 general algorithm, the particular tailoring of the
                 implementations for each hardware platform is
                 described. Sequential (CPU) and parallel (GPU-based)
                 algorithm performance is compared on both PC and video
                 game platforms using the metrics of GP operations per
                 second, actual time elapsed, speedup of parallel over
                 sequential implementation, and percentage of execution
                 time used by the GPU versus CPU.",
  notes =        "This work is based on an earlier work: Deployment of
                 CPU and GPU-based Genetic Programming on Heterogeneous
                 Devices, in Proceedings of the 2009 Genetic and
                 Evolutionary Computation Conference, ACM, 2009.

Genetic Programming entries for Garnett Carl Wilson Wolfgang Banzhaf