Deployment of parallel linear genetic programming using GPUs on PC and video game console platforms
Created by W.Langdon from
gp-bibliography.bib Revision:1.8098
- @Article{Wilson:2010:GPEM,
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author = "Garnett Wilson and Wolfgang Banzhaf",
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title = "Deployment of parallel linear genetic programming
using GPUs on PC and video game console platforms",
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journal = "Genetic Programming and Evolvable Machines",
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year = "2010",
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volume = "11",
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number = "2",
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pages = "147--184",
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month = jun,
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keywords = "genetic algorithms, genetic programming, Parallel
processing, SIMD, Graphics processing unit, GPU, GPGPU,
Xbox 360, Heterogeneous devices",
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ISSN = "1389-2576",
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DOI = "doi:10.1007/s10710-010-9102-5",
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size = "38 pages",
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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.",
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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.
\cite{DBLP:conf/gecco/WilsonB09a},
http://doi.acm.org/10.1145/1570256.1570356",
- }
Genetic Programming entries for
Garnett Carl Wilson
Wolfgang Banzhaf
Citations