Evolving gzip matches Kernel from an nVidia CUDA Template

W. B. Langdon and M. Harman
CREST centre, Department of Computer Science, King’s College, London, WC2R 2LS, UK
Technical report TR-10-02, 5 Feb 2010, Department of Computer Science, King’s College, London


   title={Evolving gzip matches kernel from an nVidia CUDA template},

   author={Langdon, WB and Harman, M.},




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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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