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DTSTAMP:20260522T150115Z
LOCATION:A2 Ballroom
DTSTART;TZID=America/Chicago:20181115T103000
DTEND;TZID=America/Chicago:20181115T110000
UID:submissions.supercomputing.org_SC18_sess467_gb101@linklings.com
SUMMARY:Simulating the Weak Death of the Neutron in a Femtoscale Universe 
 with Near-Exascale Computing
DESCRIPTION:Evan Berkowitz (Forschungszentrum Juelich); M.A. Clark (Nvidia
  Corporation); Arjun Gambhir (Lawrence Livermore National Laboratory, Lawr
 ence Berkeley National Laboratory); Ken McElvain (University of California
 , Berkeley; Lawrence Berkeley National Laboratory); Amy Nicholson (Univers
 ity of North Carolina); Enrico Rinaldi (RIKEN BNL Research Center, Lawrenc
 e Berkeley National Laboratory); Pavlos Vranas (Lawrence Livermore Nationa
 l Laboratory, Lawrence Berkeley National Laboratory); André Walker-Loud (L
 awrence Berkeley National Laboratory, Lawrence Livermore National Laborato
 ry); Chia Cheng Chang (Lawrence Berkeley National Laboratory, RIKEN); Báli
 nt Joó (Thomas Jefferson National Accelerator Facility); Thorsten Kurth (L
 awrence Berkeley National Laboratory); and Kostas Orginos (College of Will
 iam & Mary, Thomas Jefferson National Accelerator Facility)\n\nThe fundame
 ntal particle theory called Quantum Chromodynamics (QCD) dictates everythi
 ng about protons and neutrons, from their intrinsic properties to interact
 ions that bind them into atomic nuclei.  Quantities that cannot be fully r
 esolved through experiment, such as the neutron lifetime (whose precise va
 lue is important for the existence of light-atomic elements that make the 
 sun shine and life possible), may be understood through numerical solution
 s to QCD.  We directly solve QCD using Lattice Gauge Theory and calculate 
 nuclear observables such as neutron lifetime.  We have developed an improv
 ed algorithm that exponentially decreases the time-to-solution and applied
  it on the new CORAL supercomputers, Sierra and Summit.  We use run-time a
 utotuning to distribute GPU resources, achieving 20% performance at low no
 de count.  We also developed optimal application mapping through a job man
 ager, which allows CPU and GPU jobs to be interleaved, yielding 15% of pea
 k performance when deployed across large fractions of CORAL.\n\n
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