Home > Publications database > Assessing the Performance of Portable Programming Models Across GPU Vendors for the N-Body Problem > print

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005     20250912110141.0
020 _ _ |a 978-3-031-85700-3
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024 7 _ |a 10.1007/978-3-031-85700-3_9
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024 7 _ |a 0302-9743
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024 7 _ |a 1611-3349
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037 _ _ |a FZJ-2025-02193
041 _ _ |a English
100 1 _ |a Bartolomeu, Rodrigo
|0 P:(DE-Juel1)201930
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111 2 _ |a Parallel Processing and Applied Mathematics
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|c Ostrava
|d 2024-09-08 - 2024-09-11
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245 _ _ |a Assessing the Performance of Portable Programming Models Across GPU Vendors for the N-Body Problem
260 _ _ |a Cham
|c 2025
|b Springer Nature Switzerland
295 1 0 |a Parallel Processing and Applied Mathematics
300 _ _ |a 119 - 133
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490 0 _ |a Lecture Notes in Computer Science
|v 15580
520 _ _ |a With the inclusion of Aurora in the TOP500 list in November 2023 three different GPU (Graphics Processing Unit) vendors are represented in the top 10 of the list. Each vendor has its own preferred model for programming GPUs. For this paper we implemented the N-body problem using portable programming frameworks and the vendors’ preferred APIs. We show how the performance of the portable solutions compares to the performance of the native solution on each hardware both in absolute numbers and as fraction of the achievable peak performance.
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700 1 _ |a Halver, Rene
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700 1 _ |a Meinke, Jan
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700 1 _ |a Sutmann, Godehard
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770 _ _ |a Parallel Processing and Applied Mathematics
|z 978-3-031-85700-3
773 _ _ |a 10.1007/978-3-031-85700-3_9
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