Tuning of Vectorization Parameters for Molecular Dynamics Simulations in AutoPas
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arXiv
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| Auteurs principaux: | , , , , , |
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| Format: | Preprint |
| Publié: |
2025
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| _version_ | 1866917121791885312 |
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| author | Gall, Luis Newcome, Samuel James Gratl, Fabio Alexander Mühlhäußer, Markus Mishra, Manish Kumar Bungartz, Hans-Joachim |
| author_facet | Gall, Luis Newcome, Samuel James Gratl, Fabio Alexander Mühlhäußer, Markus Mishra, Manish Kumar Bungartz, Hans-Joachim |
| contents | Molecular Dynamics simulations can help scientists to gather valuable insights for physical processes on an atomic scale. This work explores various techniques for SIMD vectorization to improve the pairwise force calculation between molecules in the scope of the particle simulation library AutoPas. The focus lies on the order in which particle values are loaded into vector registers to achieve the most optimal performance regarding execution time or energy consumption.
As previous work indicates that the optimal MD algorithm can change during runtime, this paper investigates simulation-specific parameters like particle density and the impact of the neighbor identification algorithms, which distinguishes this work from related projects. Furthermore, AutoPas' dynamic tuning mechanism is extended to choose the optimal vectorization order during runtime.
The benchmarks show that considering different particle interaction orders during runtime can lead to a considerable performance improvement for the force calculation compared to AutoPas' previous approach. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2512_03565 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Tuning of Vectorization Parameters for Molecular Dynamics Simulations in AutoPas Gall, Luis Newcome, Samuel James Gratl, Fabio Alexander Mühlhäußer, Markus Mishra, Manish Kumar Bungartz, Hans-Joachim Distributed, Parallel, and Cluster Computing Computational Engineering, Finance, and Science Performance Molecular Dynamics simulations can help scientists to gather valuable insights for physical processes on an atomic scale. This work explores various techniques for SIMD vectorization to improve the pairwise force calculation between molecules in the scope of the particle simulation library AutoPas. The focus lies on the order in which particle values are loaded into vector registers to achieve the most optimal performance regarding execution time or energy consumption. As previous work indicates that the optimal MD algorithm can change during runtime, this paper investigates simulation-specific parameters like particle density and the impact of the neighbor identification algorithms, which distinguishes this work from related projects. Furthermore, AutoPas' dynamic tuning mechanism is extended to choose the optimal vectorization order during runtime. The benchmarks show that considering different particle interaction orders during runtime can lead to a considerable performance improvement for the force calculation compared to AutoPas' previous approach. |
| title | Tuning of Vectorization Parameters for Molecular Dynamics Simulations in AutoPas |
| topic | Distributed, Parallel, and Cluster Computing Computational Engineering, Finance, and Science Performance |
| url | https://arxiv.org/abs/2512.03565 |