@inbook{17435d9176a5420e88363d8df1757ac0,
title = "Evolving a CUDA Kernel from an nVidia Template",
abstract = "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. Back-to-back validation uses the original code as a test oracle.",
author = "Langdon, {W. B.} and M. Harman",
year = "2010",
language = "English",
isbn = "978-1-4244-8126-2",
series = "2010 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC)",
publisher = "IEEE",
booktitle = "Unknown",
note = "2010 IEEE World Congress on Computational Intelligence ; Conference date: 18-07-2010 Through 23-07-2010",
}