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.
@article{arxiv.2508.13523,
title = {LAMMPS-KOKKOS: Performance Portable Molecular Dynamics Across Exascale Architectures},
author = {Anders Johansson and Evan Weinberg and Christian R. Trott and Megan J. McCarthy and Stan G. Moore},
journal= {arXiv preprint arXiv:2508.13523},
year = {2025}
}