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020 _ _ |a 978-3-031-85702-7 (print)
020 _ _ |a 978-3-031-85703-4 (electronic)
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024 7 _ |2 ISSN
|a 0302-9743
024 7 _ |2 ISSN
|a 1611-3349
024 7 _ |2 datacite_doi
|a 10.34734/FZJ-2025-02673
024 7 _ |2 WOS
|a WOS:001529693400004
037 _ _ |a FZJ-2025-02673
041 _ _ |a English
100 1 _ |0 P:(DE-Juel1)186723
|a Caviedes Voullieme, Daniel
|b 0
|u fzj
111 2 _ |a International Conference on Parallel Processing and Applied Mathematics
|c Ostrava
|d 2024-09-08 - 2024-09-11
|g PPAM 2024
|w Czech Republic
245 _ _ |a Portability of Multiphysics Applications on Heterogeneous Modular Supercomputers
260 _ _ |a Cham
|b Springer Nature Switzerland
|c 2025
295 1 0 |a Parallel Processing and Applied Mathematics
300 _ _ |a 47 - 62
336 7 _ |2 ORCID
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490 0 _ |a Lecture Notes in Computer Science
|v 15581
500 _ _ |a ISSN: 0302-9743=1611-3349 ; ISBN: 978-3-031-85702-7=978-3-031-85703-4
520 _ _ |a The Modular Supercomputer Architecture (MSA) integrates various processing units, with compute modules tailored for specific algorithms, forming a unified heterogeneous system. Modules operate as parallel clustered systems, interconnected via a common or federated network. Optimized resource management allows flexible node selection, aiming for better performance. Hardware heterogeneity poses challenges for developers, who must port and optimize codes for various configurations. This study evaluated the performance of two applications-TSMP (regional Earth-system simulation) and mAIA (fluid dynamics)-across two MSA platforms (DEEP, Wisteria/BDEC-01), considering both hardware and software configurations.
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700 1 _ |0 P:(DE-Juel1)176474
|a Koh, Seong-Ryong
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700 1 _ |0 P:(DE-Juel1)165588
|a Poll, Stefan
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700 1 _ |0 P:(DE-Juel1)142361
|a Suarez, Estela
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700 1 _ |0 P:(DE-HGF)0
|a Arakawa, Takashi
|b 4
700 1 _ |0 P:(DE-HGF)0
|a Nakajima, Kengo
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700 1 _ |0 P:(DE-HGF)0
|a Sumimoto, Shinji
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773 _ _ |a 10.1007/978-3-031-85703-4_4
856 4 _ |u https://link.springer.com/chapter/10.1007/978-3-031-85703-4_4
856 4 _ |u https://juser.fz-juelich.de/record/1042839/files/Caviedes_et_al_PPAM2025_Modular_Supercomputing.pdf
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