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2010
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Evolving a CUDA kernel from an nVidia template

8 years 7 months ago
Evolving a CUDA kernel from an nVidia template
Rather than attempting to evolve a complete program from scratch we demonstrate genetic interface programming (GIP) by automatically generating a parallel CUDA kernel with identical functionality to existing highly optimised ancient sequential C code (gzip). 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 derived from gzip's SIR test suite. Backto-back validation uses the original code as a test oracle.
William B. Langdon, Mark Harman
Added 08 Nov 2010
Updated 08 Nov 2010
Type Conference
Year 2010
Where CEC
Authors William B. Langdon, Mark Harman
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