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Implicit Low-Order Unstructured Finite-Element Multiple Simulation Enhanced by Dense Computation Using OpenACC

  • Takuma Yamaguchi
  • Kohei Fujita
  • Tsuyoshi Ichimura
  • Muneo Hori
  • Maddegedara Lalith
  • Kengo Nakajima
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10732)

Abstract

In this paper, we develop a low-order three-dimensional finite-element solver for fast multiple-case crust deformation computation on GPU-based systems. Based on a high-performance solver designed for massively parallel CPU-based systems, we modify the algorithm to reduce random data access, and then insert OpenACC directives. By developing algorithm appropriate for each computer architecture, we enable to exhibit higher performance. The developed solver on ten Reedbush-H nodes (20 P100 GPUs) attained speedup of 14.2 times from the original solver on 20 K computer nodes. On the newest Volta generation V100 GPUs, the solver attained a further 2.52 times speedup with respect to P100 GPUs. As a demonstrative example, we computed 368 cases of crustal deformation analyses of northeast Japan with 400 million degrees of freedom. The total procedure of algorithm modification and porting implementation took only two weeks; we can see that high performance improvement was achieved with low development cost. With the developed solver, we can expect improvement in reliability of crust-deformation analyses by many-case analyses on a wide range of GPU-based systems.

Notes

Acknowledgments

We thank Mr. Craig Toepfer (NVIDIA) and Mr. Yukihiko Hirano (NVIDIA) for the generous support and performance analyses concerning the use of NVIDIA DGX-1 (Volta V100 GPU) and NVIDIA DGX-1 (Pascal P100 GPU) environment. Part of the results were obtained using the K computer at the RIKEN Advanced Institute for Computational Science (Proposal numbers: hp160221, hp160160, 160157, and hp170249). This work was supported by Post K computer project (priority issue 3: Development of Integrated Simulation Systems for Hazard and Disaster Induced by Earthquake and Tsunami), Japan Society for the Promotion of Science (KAKENHI Grant Numbers 15K18110, 26249066, 25220908, and 17K14719) and FOCUS Establishing Supercomputing Center of Excellence.

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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  1. 1.Department of Civil Engineering, Earthquake Research InstituteThe University of TokyoTokyoJapan
  2. 2.Advanced Institute for Computational Science, RIKENKobeJapan
  3. 3.Information Technology CenterThe University of TokyoTokyoJapan

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