Accelerated parallel genetic programming tree evaluation with OpenCL
Created by W.Langdon from
gp-bibliography.bib Revision:1.8098
- @Article{Augusto2012,
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author = "Douglas A. Augusto and Helio J. C. Barbosa",
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title = "Accelerated parallel genetic programming tree
evaluation with {OpenCL}",
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journal = "Journal of Parallel and Distributed Computing",
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volume = "73",
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number = "1",
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pages = "86--100",
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year = "2013",
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note = "Metaheuristics on GPUs",
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ISSN = "0743-7315",
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DOI = "doi:10.1016/j.jpdc.2012.01.012",
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URL = "http://www.sciencedirect.com/science/article/pii/S074373151200024X",
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keywords = "genetic algorithms, genetic programming, GPU, OpenCL,
GP-GPU, Accelerated tree evaluation",
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abstract = "Inspired by the process of natural selection, genetic
programming (GP) aims at automatically building
arbitrarily complex computer programs. Being classified
as an embarrassingly parallel technique, GP can
theoretically scale up to tackle very diverse problems
by increasingly adding computational power to its
arsenal. With today's availability of many powerful
parallel architectures, a challenge is to take
advantage of all those heterogeneous compute devices in
a portable and uniform way. This work proposes both (i)
a transcription of existing GP parallelisation
strategies into the OpenCL programming platform; and
(ii) a freely available implementation to evaluate its
suitability for GP, by assessing the performance of
parallel strategies on the CPU and GPU processors from
different vendors. Benchmarks on the symbolic
regression and data classification domains were
performed. On the GPU we could achieve 13 billion node
evaluations per second, delivering almost 10 times the
throughput of a twelve-core CPU.",
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notes = "Genetic Programming in OpenCL Source",
- }
Genetic Programming entries for
Douglas A Augusto
Helio J C Barbosa
Citations