Improving CUDA DNA Analysis Software with Genetic Programming

@article{Langdon2015ImprovingCD,
  title={Improving CUDA DNA Analysis Software with Genetic Programming},
  author={William B. Langdon and Brian Yee Hong Lam and Justyna Petke and Mark Harman},
  journal={Proceedings of the 2015 Annual Conference on Genetic and Evolutionary Computation},
  year={2015}
}
  • W. Langdon, B. Lam, +1 author M. Harman
  • Published 11 July 2015
  • Computer Science
  • Proceedings of the 2015 Annual Conference on Genetic and Evolutionary Computation
We genetically improve BarraCUDA using a BNF grammar incorporating C scoping rules with GP. Barracuda maps next generation DNA sequences to the human genome using the Burrows-Wheeler algorithm (BWA) on nVidia Tesla parallel graphics hardware (GPUs). GI using phenotypic tabu search with manually grown code can graft new features giving more than 100 fold speed up on a performance critical kernel without loss of accuracy. 
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