Abstract
Developing multiphysics finite element methods (FEM) and scalable HPC implementations can be very challenging in terms of software complexity and performance, even more so with the addition of goal-oriented adaptive mesh refinement. To manage the complexity we in this work present general adaptive stabilized methods with automated implementation in the FEniCS-HPC automated open source software framework. This allows taking the weak form of a partial differential equation (PDE) as input in near-mathematical notation and automatically generating the low-level implementation source code and auxiliary equations and quantities necessary for the adaptivity. We demonstrate new optimal strong scaling results for the whole adaptive framework applied to turbulent flow on massively parallel architectures down to 25000 vertices per core with ca. 5000 cores with the MPI-based PETSc backend and for assembly down to 500 vertices per core with ca. 20000 cores with the PGAS-based JANPACK backend. As a demonstration of the power of the combination of the scalability together with the adaptive methodology allowing prediction of gross quantities in turbulent flow we present an application in aerodynamics of a full DLR-F11 aircraft in connection with the HiLift-PW2 benchmarking workshop with good match to experiments.
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Acknowledgments
This research has been supported by EU-FET grant EUNISON 308874, the European Research Council, the Swedish Foundation for Strategic Research, the Swedish Research Council, the Basque Excellence Research Center (BERC 2014-2017) program by the Basque Government, the Spanish Ministry of Economy and Competitiveness MINECO: BCAM Severo Ochoa accreditation SEV-2013-0323 and the Project of the Spanish MINECO: MTM2013-40824.
We acknowledge PRACE for awarding us access to the supercomputer resources Hermit, Hornet and SuperMUC based in Germany at The High Performance Computing Center Stuttgart (HLRS) and Leibniz Supercomputing Center (LRZ), from the Swedish National Infrastructure for Computing (SNIC) at PDC – Center for High-Performance Computing and on resources provided by the “Red Española de Supercomputación” and the “Barcelona Supercomputing Center - Centro Nacional de Supercomputación”.
We would also like to acknowledge the FEniCS and FEniCS-HPC developers globally.
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Hoffman, J., Jansson, J., Jansson, N. (2016). FEniCS-HPC: Automated Predictive High-Performance Finite Element Computing with Applications in Aerodynamics. In: Wyrzykowski, R., Deelman, E., Dongarra, J., Karczewski, K., Kitowski, J., Wiatr, K. (eds) Parallel Processing and Applied Mathematics. PPAM 2015. Lecture Notes in Computer Science(), vol 9573. Springer, Cham. https://doi.org/10.1007/978-3-319-32149-3_34
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DOI: https://doi.org/10.1007/978-3-319-32149-3_34
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