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Publication Detail
Improving SSE parallel code with grow and graft genetic programming
  • Publication Type:
  • Authors:
    Langdon WB, Lorenz R
  • Publication date:
  • Pagination:
    1537, 1538
  • Published proceedings:
    GECCO 2017 - Proceedings of the Genetic and Evolutionary Computation Conference Companion
  • ISBN-13:
  • Status:
RNAfold predicts the secondary structure of RNA molecules from their base sequence. We apply a mixture of manual and automated genetic improvements to its C source. GI gives a 1.6% improvement to parallel SSE4.1 code. The automatic programming evolutionary system has access to Intel library code and previous revisions. On 4 666 curated structures from RNA STRAND, GGGP gives a combined speed up of 31.9%, with no loss of accuracy (GI code run 1:4 1011 times).
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