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DTSTART:19700308T020000
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DTSTAMP:20190719T085744Z
LOCATION:HG D 3.2
DTSTART;TZID=Europe/Stockholm:20190613T164500
DTEND;TZID=Europe/Stockholm:20190613T171500
UID:submissions.pasc-conference.org_PASC19_sess152_msa115@linklings.com
SUMMARY:Acceleration of Prediction of Chemical Shift of Protein Structures
  using OpenACC
DESCRIPTION:Minisymposium\nComputer Science and Applied Mathematics, Emerg
 ing Application Domains, Climate and Weather, Life Sciences\n\nAcceleratio
 n of Prediction of Chemical Shift of Protein Structures using OpenACC\n\nC
 handrasekaran, Perilla\n\nExperimental chemical shifts from solution and s
 olid-state magic-angle-spinning nuclear magnetic resonance spectra provide
  atomic level data for each amino acid within a protein or complex. Howeve
 r, the structure determination of large complexes and assemblies based on 
 NMR data alone remains challenging due to the complexity of the calculatio
 ns. This talk will describe key computational challenges starting from a s
 equential chemical shift codebase, present a hardware accelerated strategy
  based on OpenACC that will expedite the prediction of estimation of NMR c
 hemical-shifts of large macromolecular complexes by manyfold. Results will
  show the scalability and feasibility of our approach in systems of increa
 sing complexity ranging from 2,000 to 11,000,000 atoms while demonstrating
  how the computation time was reduced from several hours to a few seconds.
  A performance yet portable solution demonstrated on both the multicore sy
 stems and GPUs will be presented.
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