LAMMPS-KOKKOS: Performance Portable Molecular Dynamics Across Exascale Architectures
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arXiv
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| Autori principali: | , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866912602198638592 |
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| author | Johansson, Anders Weinberg, Evan Trott, Christian R. McCarthy, Megan J. Moore, Stan G. |
| author_facet | Johansson, Anders Weinberg, Evan Trott, Christian R. McCarthy, Megan J. Moore, Stan G. |
| contents | Since its inception in 1995, LAMMPS has grown to be a world-class molecular dynamics code, with thousands of users, over one million lines of code, and multi-scale simulation capabilities. We discuss how LAMMPS has adapted to the modern heterogeneous computing landscape by integrating the Kokkos performance portability library into the existing C++ code. We investigate performance portability of simple pairwise, many-body reactive, and machine-learned force-field interatomic potentials. We present results on GPUs across different vendors and generations, and analyze performance trends, probing FLOPS throughput, memory bandwidths, cache capabilities, and thread-atomic operation performance. Finally, we demonstrate strong scaling on three exascale machines -- OLCF Frontier, ALCF Aurora, and NNSA El Capitan -- as well as on the CSCS Alps supercomputer, for the three potentials. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2508_13523 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | LAMMPS-KOKKOS: Performance Portable Molecular Dynamics Across Exascale Architectures Johansson, Anders Weinberg, Evan Trott, Christian R. McCarthy, Megan J. Moore, Stan G. Distributed, Parallel, and Cluster Computing Performance Computational Physics C.1.4; C.2.4; C.4; D.1.3; D.3.4; E.1; I.6; I.6.8; J.2 Since its inception in 1995, LAMMPS has grown to be a world-class molecular dynamics code, with thousands of users, over one million lines of code, and multi-scale simulation capabilities. We discuss how LAMMPS has adapted to the modern heterogeneous computing landscape by integrating the Kokkos performance portability library into the existing C++ code. We investigate performance portability of simple pairwise, many-body reactive, and machine-learned force-field interatomic potentials. We present results on GPUs across different vendors and generations, and analyze performance trends, probing FLOPS throughput, memory bandwidths, cache capabilities, and thread-atomic operation performance. Finally, we demonstrate strong scaling on three exascale machines -- OLCF Frontier, ALCF Aurora, and NNSA El Capitan -- as well as on the CSCS Alps supercomputer, for the three potentials. |
| title | LAMMPS-KOKKOS: Performance Portable Molecular Dynamics Across Exascale Architectures |
| topic | Distributed, Parallel, and Cluster Computing Performance Computational Physics C.1.4; C.2.4; C.4; D.1.3; D.3.4; E.1; I.6; I.6.8; J.2 |
| url | https://arxiv.org/abs/2508.13523 |