- author = "Gopinath Chennupati and Jeannie Fitzgerald and Conor Ryan",
- title = "On The Efficiency of Multi-core Grammatical Evolution (MCGE) Evolving Multi-Core Parallel Programs",
- booktitle = "Sixth World Congress on Nature and Biologically Inspired Computing",
- year = "2014",
- editor = "Ana Maria Madureira and Ajith Abraham and Emilio Corchado and Leonilde Varela and Azah Kamilah Muda and Choo yun Huoy",
- pages = "238--243",
- address = "Porto, Portugal",
- month = "30 " # jul # " - 1 " # jul,
- publisher = "IEEE",
- keywords = "genetic algorithms, genetic programming, Grammatical Evolution, OpenMP, Parallel programming, GPU",
- isbn13 = "978-1-4799-5937-2/14",
-
DOI = "
doi:10.1109/NaBIC.2014.6921885",
- size = "6 pages",
-
abstract = "In this paper we investigate a novel technique that
optimises the execution time of Grammatical Evolution
through the usage of on-chip multiple processors. This
technique, Multi-core Grammatical Evolution (MCGE)
evolves natively parallel programs with the help of
OpenMP primitives through the grammars, such that not
only can we exploit parallelism while evolving
individuals, but the final individuals produced can
also be executed on parallel architectures even outside
the evolutionary system.
We test MCGE on two difficult benchmark GP problems and show its efficiency in exploiting the power of the multi-core architectures. We further discuss that, on these problems, the system evolves longer individuals while they are evaluated quicker than their serial implementation.",
- notes = "cites \cite{williams98} NaBIC 2014 http://www.mirlabs.net/nabic14/",
