AuthorsReguly, Istvan Z.
Giles, Michael B.
Permanent link to this recordhttp://hdl.handle.net/10754/627392
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AbstractIn this paper, we present the VOLNA-OP2 tsunami model and implementation; a finite volume non-linear shallow water equations (NSWE) solver built on the OP2 domain specific language for unstructured mesh computations. VOLNA-OP2 is unique among tsunami solvers in its support for several high performance computing platforms: CPUs, the Intel Xeon Phi, and GPUs. This is achieved in a way that the scientific code is kept separate from various parallel implementations, enabling easy maintainability. It has already been used in production for several years, here we discuss how it can be integrated into various workflows, such as a statistical emulator. The scalability of the code is demonstrated on three supercomputers, built with classical Xeon CPUs, the Intel Xeon Phi, and NVIDIA P100 GPUs. VOLNA-OP2 shows an ability to deliver productivity to its users, as well as performance and portability on a number of platforms.
CitationReguly IZ, Gopinathan D, Beck JH, Giles MB, Guillas S, et al. (2018) The VOLNA-OP2 Tsunami Code (Version 1.0). Geoscientific Model Development Discussions: 1–18. Available: http://dx.doi.org/10.5194/gmd-2018-18.
SponsorsWe would like to thank Endre Lszló, formerly of PPCU ITK, who worked in the initial port of Volna to OP2. István Reguly was supported by the János Bólyai Research Scholarship of the Hungarian Academy of Sciences. The authors would like to ac- knowledge the use of the University of Oxford Advanced Research Computing (ARC) facility in carrying out this work http://dx.doi.org/10. 20 5281/zenodo.22558. SG gratefully acknowledges support through the NERC grants PURE (Probability, Uncertainty and Risk in the Natural Environment) NE/J017434/1, and “A demonstration tsunami catastrophe risk model for the insurance industry” NE/L002752/1. SG and DG acknowledge support from the NERC project (NE/P016367/1) under the Global Challenges Research Fund: Building Resilience programme. DG acknowledges support from the Royal Society, UK and Science and Engineering Research Board (SERB), India for the Royal Society-SERB Newton International Fellowship (NF151483).
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