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Publication Detail
Evolving gzip matches Kernel from an nVidia CUDA Template
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Publication Type:Report
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Authors:Langdon WB, Harman M
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publication date:05/02/2010
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Place of publication:London, WC2R 2LS, UK
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Report number:TR-10-02
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Notes:keywords: genetic algorithms, genetic programming, GIP, automatic coding, GPU, gpgpu, Genetic Interface Programming, SIR, gawk, strongly typed genetic programming, BNF grammar size: 15 pages
Abstract
Rather than attempting to evolve a complete program from scratch we demonstrate genetic interface programming by automatically generating a parallel CUDA kernel with identical functionality to existing highly optimised ancient sequential C code. Generic GPGPU nVidia kernel C++ code is converted into a BNF grammar. Strongly typed genetic programming uses the BNF to generate compilable and executable graphics card kernels. Their fitness is given by running the population on a GPU with randomised subsets of training data itself given by running the original code’s test suite.
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