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Benchmarking Genetically Improved BarraCUDA on Epigenetic Methylation NGS datasets and nVidia GPUs

Published:20 July 2016Publication History

ABSTRACT

BarraCUDA uses CUDA graphics cards to map DNA reads to the human genome. Previously its software source code was genetically improved for short paired end next generation sequences. On longer noisy epigenetics strings using nVidia Titan and twin Tesla K40 the same GI-ed code is more than 3 times faster than bwa-meth on an 8 core CPU.

References

  1. P. Klus et al. BarraCUDA. BMC Res Nts, 5(27), 2012.Google ScholarGoogle Scholar
  2. W. B. Langdon. Genetically improved software. Handbook GP Applications, pp181--220. Springer, 2015.Google ScholarGoogle ScholarCross RefCross Ref
  3. W. B. Langdon, Brian Y. H. Lam, J. Petke, and M. Harman. Improving CUDA DNA analysis software with genetic programming. In GECCO 2015, pp1063--70 Google ScholarGoogle ScholarDigital LibraryDigital Library

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  1. Benchmarking Genetically Improved BarraCUDA on Epigenetic Methylation NGS datasets and nVidia GPUs

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    • Published in

      cover image ACM Conferences
      GECCO '16 Companion: Proceedings of the 2016 on Genetic and Evolutionary Computation Conference Companion
      July 2016
      1510 pages
      ISBN:9781450343237
      DOI:10.1145/2908961

      Copyright © 2016 ACM

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 20 July 2016

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      GECCO '16 Companion Paper Acceptance Rate137of381submissions,36%Overall Acceptance Rate1,669of4,410submissions,38%

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