Use of graphics processing units for automatic synthesis of programs
Created by W.Langdon from
gp-bibliography.bib Revision:1.8081
- @Article{daSilva:2015:CEE,
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author = "Cleomar Pereira {da Silva} and Douglas {Mota Dias} and
Cristiana Bentes and Marco Aurelio Cavalcanti Pacheco",
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title = "Use of graphics processing units for automatic
synthesis of programs",
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journal = "Computer \& Electrical Engineering",
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volume = "46",
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pages = "112--122",
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year = "2015",
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ISSN = "0045-7906",
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DOI = "doi:10.1016/j.compeleceng.2015.04.006",
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URL = "http://www.sciencedirect.com/science/article/pii/S0045790615001342",
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abstract = "Genetic programming (GP) is an evolutionary method
that allows computers to solve problems automatically.
However, the computational power required for the
evaluation of billions of programs imposes a serious
limitation on the problem size. This work focuses on
accelerating GP to support the synthesis of large
problems. This is done by completely exploiting the
highly parallel environment of graphics processing
units (GPUs). Here, we propose a new quantum-inspired
linear GP approach that implements all the GP steps in
the GPU and provides the following: (1) significant
performance improvements in the GP steps, (2)
elimination of the overhead of copying the fitness
results from the GPU to the CPU, and (3) incorporation
of a new selection mechanism to recognize the programs
with the best evaluations. The proposed approach
outperforms the previous approach for large-scale
synthetic and real-world problems. Further, it provides
a remarkable speedup over the CPU execution.",
-
keywords = "genetic algorithms, genetic programming, GPU
acceleration, Machine code, Quantum-inspired
algorithms, Massive parallelism",
- }
Genetic Programming entries for
Cleomar Pereira da Silva
Douglas Mota Dias
Cristiana Bentes
Marco Aurelio Cavalcanti Pacheco
Citations