Parallel implementation of a Lagrangian-based model on an adaptive mesh in C++: Application to sea-ice

International audience We present a parallel implementation framework for a new dynamic/thermodynamic seaice model, called neXtSIM, based on the Elasto-Brittle rheology and using an adaptive mesh. The spatial discretisation of the model is done using the finite-element method. The temporal discretis...

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Bibliographic Details
Published in:Journal of Computational Physics
Main Authors: Samaké, Abdoulaye, Rampal, Pierre, Bouillon, Sylvain, Ólason, Einar
Other Authors: Nansen Environmental and Remote Sensing Center Bergen (NERSC)
Format: Article in Journal/Newspaper
Language:English
Published: HAL CCSD 2017
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Online Access:https://hal.univ-grenoble-alpes.fr/hal-03405832
https://hal.univ-grenoble-alpes.fr/hal-03405832/document
https://hal.univ-grenoble-alpes.fr/hal-03405832/file/Samake2017J._Comp._Phys.pdf
https://doi.org/10.1016/j.jcp.2017.08.055
Description
Summary:International audience We present a parallel implementation framework for a new dynamic/thermodynamic seaice model, called neXtSIM, based on the Elasto-Brittle rheology and using an adaptive mesh. The spatial discretisation of the model is done using the finite-element method. The temporal discretisation is semi-implicit and the advection is achieved using either a pure Lagrangian scheme or an Arbitrary Lagrangian Eulerian scheme (ALE). The parallel implementation presented here focuses on the distributed-memory approach using the message-passing library MPI. The efficiency and the scalability of the parallel algorithms are illustrated by the numerical experiments performed using up to 500 processor cores of a cluster computing system. The performance obtained by the proposed parallel implementation of the neXtSIM code is shown being sufficient to perform simulations for state-of-the-art sea ice forecasting and geophysical process studies over geographical domain of several millions squared kilometers like the Arctic region.