The VOLNA-OP2 Tsunami Code (Version 1.0)

Handle URI:
http://hdl.handle.net/10754/627392
Title:
The VOLNA-OP2 Tsunami Code (Version 1.0)
Authors:
Reguly, Istvan Z. ( 0000-0002-4385-4204 ) ; Gopinathan, Devaraj ( 0000-0002-0490-3229 ) ; Beck, Joakim H.; Giles, Michael B. ( 0000-0002-5445-3721 ) ; Guillas, Serge; Dias, Frederic ( 0000-0002-5123-4929 )
Abstract:
In 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.
KAUST Department:
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Citation:
Reguly 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.
Publisher:
Copernicus GmbH
Journal:
Geoscientific Model Development Discussions
Issue Date:
8-Mar-2018
DOI:
10.5194/gmd-2018-18
Type:
Article
ISSN:
1991-962X
Sponsors:
We 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).
Additional Links:
https://www.geosci-model-dev-discuss.net/gmd-2018-18/
Appears in Collections:
Articles; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

Full metadata record

DC FieldValue Language
dc.contributor.authorReguly, Istvan Z.en
dc.contributor.authorGopinathan, Devarajen
dc.contributor.authorBeck, Joakim H.en
dc.contributor.authorGiles, Michael B.en
dc.contributor.authorGuillas, Sergeen
dc.contributor.authorDias, Fredericen
dc.date.accessioned2018-04-01T08:20:28Z-
dc.date.available2018-04-01T08:20:28Z-
dc.date.issued2018-03-08en
dc.identifier.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.en
dc.identifier.issn1991-962Xen
dc.identifier.doi10.5194/gmd-2018-18en
dc.identifier.urihttp://hdl.handle.net/10754/627392-
dc.description.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.en
dc.description.sponsorshipWe 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).en
dc.publisherCopernicus GmbHen
dc.relation.urlhttps://www.geosci-model-dev-discuss.net/gmd-2018-18/en
dc.rightsThis work is distributed under the Creative Commons Attribution 4.0 License.en
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en
dc.titleThe VOLNA-OP2 Tsunami Code (Version 1.0)en
dc.typeArticleen
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
dc.identifier.journalGeoscientific Model Development Discussionsen
dc.eprint.versionPublisher's Version/PDFen
dc.contributor.institutionPázmány Péter Catholic University, Faculty of Information Technology and Bionics, Prater u 50/a, 1088 Budapest, Hungaryen
dc.contributor.institutionDepartment of Statistical Science, University College London, London, UKen
dc.contributor.institutionMath Institute, University of Oxford, Oxford, UKen
dc.contributor.institutionSchool of Mathematics and Statistics, University College Dublin, Dublin, Irelanden
kaust.authorBeck, Joakim H.en
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