TensorMD: Molecular Dynamics Simulation with Ab Initio Accuracy of 50 Billion Atoms

Molecular dynamics simulation emerges as an important area that HPC+AI helps to investigate the physical properties, with machine-learning interatomic potentials (MLIPs) being used. General-purpose machine-learning (ML) tools have been leveraged in MLIPs, but they are not perfectly matched with each other, since many optimization opportunities in MLIPs have been missed by ML tools. This inefficiency arises from the fact that HPC+AI applications work with far more computational complexity compared with pure AI scenarios. This paper has developed an MLIP, named TensorMD, independently from any ML tool. TensorMD has been evaluated on two supercomputers and scaled to 51.8 billion atoms, i.e., ~ 3× compared with state-of-the-art.

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Published
2025-02-28
DOI
https://doi.org/10.1145/3710848.3710882
Citations
1
Primary Topic
Machine Learning in Materials Science
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article
Field-Weighted Citation Impact
0.52
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article

TensorMD: Molecular Dynamics Simulation with Ab Initio Accuracy of 50 Billion Atoms

Honghui Shang, Jiahao Shan, Zhenchuan Chen, Haifeng Song et al.
1 citations
Machine Learning in Materials Science
0.52
article

TensorMD: Molecular Dynamics Simulation with Ab Initio Accuracy of 50 Billion Atoms

Honghui Shang, Jiahao Shan, Zhenchuan Chen, Haifeng Song, Xingyu Gao, Yucheng Ouyang, Xiaobing Feng, Xin Chen, Ying Liu, Huimin Cui, Rongfen Lin, Lifang Wang, Xin Chen, Fang Li
article en
1 citations

Abstract

Molecular dynamics simulation emerges as an important area that HPC+AI helps to investigate the physical properties, with machine-learning interatomic potentials (MLIPs) being used. General-purpose machine-learning (ML) tools have been leveraged in MLIPs, but they are not perfectly matched with each other, since many optimization opportunities in MLIPs have been missed by ML tools. This inefficiency arises from the fact that HPC+AI applications work with far more computational complexity compared with pure AI scenarios. This paper has developed an MLIP, named TensorMD, independently from any ML tool. TensorMD has been evaluated on two supercomputers and scaled to 51.8 billion atoms, i.e., ~ 3× compared with state-of-the-art.

Chinese Academy of Sciences (CN), Institute of Computing Technology (CN), Institute of Applied Physics and Computational Mathematics (CN)
Openalex Percentile: Top 41%
Machine Learning in Materials Science
0.52
DOIOpen Access PDFOpenAlex
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TensorMD: Molecular Dynamics Simulation with Ab Initio Accuracy of 50 Billion Atoms — Honghui Shang, Jiahao Shan, et al. · (2025) | TGRS Research Map | TGRS