Accelerating neuro-evolution by compilation to native machine code

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@InProceedings{Siebel:2010:ijcnn,

• author = "Nils T Siebel and Andreas Jordt and Gerald Sommer",
• title = "Accelerating neuro-evolution by compilation to native machine code",
• booktitle = "International Joint Conference on Neural Networks (IJCNN 2010)",
• year = "2010",
• address = "Barcelona, Spain",
• month = "18-23 " # jul,
• publisher = "IEEE Press",
• keywords = "genetic algorithms, genetic programming",
• isbn13 = "978-1-4244-6917-8",
• abstract = "Any neuro-evolutionary algorithm that solves complex problems needs to deal with the issue of computational complexity. We show how a neural network (feed-forward, recurrent or RBF) can be transformed and then compiled in order to achieve fast execution speeds without requiring dedicated hardware like FPGAs. The compiled network uses a simple external data structure #x2014;a vector #x2014;for its parameters. This allows the weights of the neural network to be optimised by the evolutionary process without the need to re-compile the structure. In an experimental comparison our method effects a speedup of factor 5 #x2013;10 compared to the standard method of evaluation (i.e., traversing a data structure with optimised C++ code)",
• DOI = "doi:10.1109/IJCNN.2010.5596296",
• notes = "WCCI 2010. Also known as \cite{5596296}",

}

Genetic Programming entries for Nils T Siebel Andreas Jordt Gerald Sommer

Citations