001042287 001__ 1042287
001042287 005__ 20250822121437.0
001042287 0247_ $$2datacite_doi$$a10.34734/FZJ-2025-02503
001042287 037__ $$aFZJ-2025-02503
001042287 041__ $$aEnglish
001042287 1001_ $$0P:(DE-HGF)0$$aTsai, Yu-Hsiang M.$$b0
001042287 1112_ $$a35th Parallel CFD International Conference 2024$$cBonn$$d2024-09-02 - 2024-09-04$$gParCFD 2024$$wGermany
001042287 245__ $$aPortable Linear Solvers for High-Order Spectral Element Methods on GPUs
001042287 260__ $$aJülich$$bForschungszentrum Jülich GmbH Zentralbibliothek, Verlag$$c2025
001042287 29510 $$aProceedings of the 35th Parallel CFD International Conference 2024
001042287 300__ $$a253 - 256
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001042287 4900_ $$aSchriften des Forschungszentrums Jülich IAS Series$$v69
001042287 520__ $$aThe diversification in hardware architectures has become a challenge for computational science: software stacks implemented for a specific hardware architecture often fail to port to other systems. To counter this problem, simulation software stacks increasingly rely on portability layers or software stacks that feature backends for different hardware architectures. We present Ginkgo, a math library that takes platform portability as a central design principle and can be used for numerical calculations in the nekRS CFD code. A runtime and scalability analysis for CFD applications demonstrates that Ginkgo enables platform portability at high performance and scalability.
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001042287 536__ $$0G:(EU-Grant)101118139$$aInno4Scale - Innovative Algorithms for Applications on European Exascale Supercomputers (101118139)$$c101118139$$fHORIZON-EUROHPC-JU-2022-ALG-02$$x1
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001042287 7001_ $$0P:(DE-HGF)0$$aOlenik, Gregor$$b1
001042287 7001_ $$0P:(DE-Juel1)145478$$aHerten, Andreas$$b2$$ufzj
001042287 7001_ $$0P:(DE-Juel1)192255$$aBode, Mathis$$b3$$ufzj
001042287 7001_ $$0P:(DE-HGF)0$$aAnzt, Hartwig$$b4$$eCorresponding author
001042287 770__ $$z978-3-95806-819-3
001042287 773__ $$a10.34734/FZJ-2025-02503
001042287 8564_ $$uhttps://juser.fz-juelich.de/record/1042287/files/164.pdf$$yOpenAccess
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