Molecular dynamics simulations with many-body potentials on multiple GPUs - the implementation, package and performance
Qing Hou, Min Li, Yulu Zhou, Jiechao Cui, Zhenguo Cui, Jun Wang

TL;DR
This paper presents a multi-GPU implementation of molecular dynamics simulations that significantly increases system size capacity and achieves substantial speedups over CPU versions, enabling efficient large-scale materials science modeling.
Contribution
The paper introduces a one-host-process-multiple-GPU (OHPMG) scheme for MD simulations with many-body potentials, overcoming memory limitations of traditional single-GPU approaches.
Findings
Achieved 28.9x to 86.0x speedup over CPU implementations.
Enabled simulation of systems with millions of atoms.
Improved efficiency for multiple small-box simulations.
Abstract
Molecular dynamics (MD) is an important research tool extensively applied in materials science. Running MD on a graphics processing unit (GPU) is an attractive new approach for accelerating MD simulations. Currently, GPU implementations of MD usually run in a one-host-process-one-GPU (OHPOG) scheme. This scheme may pose a limitation on the system size that an implementation can handle due to the small device memory relative to the host memory. In this paper, we present a one-host-process-multiple-GPU (OHPMG) implementation of MD with embedded-atom-model or semi-empirical tight-binding many-body potentials. Because more device memory is available in an OHPMG process, the system size that can be handled is increased to a few million or more atoms. In comparison with the CPU implementation, in which Newton's third law is applied to improve the computational efficiency, our OHPMG…
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