Abstract
The fundamental particle theory called Quantum Chromodynamics (QCD) dictates everything about protons and neutrons, from their intrinsic properties to interactions that bind them into atomic nuclei. Quantities that cannot be fully resolved through experiment, such as the neutron lifetime (whose precise value is important for the existence of light-atomic elements that make the sun shine and life possible), may be understood through numerical solutions to QCD. We directly solve QCD using Lattice Gauge Theory and calculate nuclear observables such as neutron lifetime. We have developed an improved algorithm that expoentially decreases the time-to-solution and applied it on the new CORAL supercomputers, Sierra and Summit. We use run-time autotuning to distribute GPU resources, achieving 20% performance at low node count. We also developed optimal application mapping through a job manager, which allows CPU and GPU jobs to be interleaved, yielding 15% of peak performance when deployed across large fractions of CORAL.
Original language | English |
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Title of host publication | Proceedings - International Conference for High Performance Computing, Networking, Storage, and Analysis, SC 2018 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 697-705 |
Number of pages | 9 |
ISBN (Electronic) | 9781538683842 |
DOIs | |
State | Published - Jul 2 2018 |
Event | 2018 International Conference for High Performance Computing, Networking, Storage, and Analysis, SC 2018 - Dallas, United States Duration: Nov 11 2018 → Nov 16 2018 |
Publication series
Name | Proceedings - International Conference for High Performance Computing, Networking, Storage, and Analysis, SC 2018 |
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Conference
Conference | 2018 International Conference for High Performance Computing, Networking, Storage, and Analysis, SC 2018 |
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Country/Territory | United States |
City | Dallas |
Period | 11/11/18 → 11/16/18 |
Funding
An award of computer time was provided by the Innovative and Novel Computational Impact on Theory and Experiment (INCITE) program to CalLat (2016) as well as the Lawrence Livermore National Laboratory (LLNL) Multiprogrammatic and Institutional Computing program through a Tier 1 Grand Challenge award. This research used the NVIDIA GPU-accelerated Titan, Summit-Dev, and Summit supercomputers at the Oak Ridge Leadership Computing Facility at the Oak Ridge National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC05-00OR22725, and the NVIDIA GPU-accelerated Surface, Ray, and Sierra supercomputers LLNL. This work was performed under the auspices of the U.S. Department of Energy by LLNL under Contract No. DE-AC52-07NA27344 and under contract DE-AC02-05CH11231, which the Regents of the University of California manage and operate Lawrence Berkeley National Laboratory and the National Energy Research Scientific Computing Center