001052213 001__ 1052213
001052213 005__ 20260122203307.0
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001052213 0247_ $$2datacite_doi$$a10.34734/FZJ-2026-00840
001052213 037__ $$aFZJ-2026-00840
001052213 1001_ $$00000-0001-5229-3739$$aTsai, Yu-Hsiang$$b0
001052213 1112_ $$aSCA/HPCAsia 2026: Supercomputing Asia and International Conference on High Performance Computing in Asia Pacific Region$$cOsaka$$d2026-01-26 - 2026-01-29$$wJapan
001052213 245__ $$aWhat Will the Grace Hopper-Powered Jupiter Supercomputer Bring for Sparse Linear Algebra?
001052213 260__ $$aNew York, NY, USA$$bACM New York, NY, USA$$c2026
001052213 300__ $$a228 - 235
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001052213 520__ $$aThe first exascale supercomputer in Europe, JUPITER, is currently being built using the NVIDIA Grace Hopper superchips as main building blocks. JUPITER is designed to provide computing power for both data-driven (AI) workloads and numerics-based simulation workloads. For both workload types, and particularly for PDE-based simulations, high-performance sparse linear algebra operations are crucial. In this paper, we analyze the performance levels that sparse linear algebra operations can achieve on the JUPITER supercomputer and identify algorithmic modifications that can improve performance by acknowledging the Grace Hopper architecture.
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001052213 536__ $$0G:(EU-Grant)101118139$$aInno4Scale - Innovative Algorithms for Applications on European Exascale Supercomputers (101118139)$$c101118139$$fHORIZON-EUROHPC-JU-2022-ALG-02$$x1
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001052213 7001_ $$0P:(DE-Juel1)192255$$aBode, Mathis$$b1$$ufzj
001052213 7001_ $$00000-0003-2177-952X$$aAnzt, Hartwig$$b2
001052213 770__ $$z9798400720673
001052213 773__ $$a10.1145/3773656.3773691
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001052213 9141_ $$y2026
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