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Issue No. 05 - September/October (2017 vol. 19)
ISSN: 1521-9615
pp: 27-37
Hans Johansen , Lawrence Berkeley National Laboratory
Arthur Rodgers , Lawrence Livermore National Laboratory
N. Anders Petersson , Lawrence Livermore National Laboratory
David McCallen , Lawrence Berkeley National Laboratory
Bjorn Sjogreen , Lawrence Livermore National Laboratory
Mamun Miah , Lawrence Berkeley National Laboratory
Modernizing SW4 for massively parallel time-domain simulations of earthquake ground motions in 3D earth models increases resolution and provides ground motion estimates for critical infrastructure risk evaluations. Simulations of ground motions from large (M ≥ 7.0) earthquakes require domains on the order of 100 to500 km and spatial granularity on the order of 1 to5 m resulting in hundreds of billions of grid points. Surface-focused structured mesh refinement (SMR) allows for more constant grid point per wavelength scaling in typical Earth models, where wavespeeds increase with depth. In fact, MR allows for simulations to double the frequency content relative to a fixed grid calculation on a given resource. The authors report improvements to the SW4 algorithm developed while porting the code to the Cori Phase 2 (Intel Xeon Phi) systems at the National Energy Research Scientific Computing Center (NERSC) at Lawrence Berkeley National Laboratory. Investigations of the performance of the innermost loop of the calculations found that reorganizing the order of operations can improve performance for massive problems.
Earthquakes, Solid modeling, Computational modeling, Three-dimensional displays, Geology, Analytical models, Acceleration,computational seismology, structural mechanics, earthquake simulations, exascale computing, scientific computing
Hans Johansen, Arthur Rodgers, N. Anders Petersson, David McCallen, Bjorn Sjogreen, Mamun Miah, "Toward Exascale Earthquake Ground Motion Simulations for Near-Fault Engineering Analysis", Computing in Science & Engineering, vol. 19, no. , pp. 27-37, September/October 2017, doi:10.1109/MCSE.2017.3421558
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