GPUMD 4.0: A high-performance molecular dynamics package for versatile materials simulations with machine-learned potentials
Review article, 2025
This paper provides a comprehensive overview of the latest stable release of the graphics processing units molecular dynamics (GPUMD) package, GPUMD 4.0. We begin with a brief review of its development history, starting from the initial version. We then discuss the theoretical foundations for the development of the GPUMD package, including the formulations of the interatomic force, virial and heat current for many-body potentials, the development of the highly efficient and flexible neuroevolution potential (NEP) method, the supported integrators and related operations, the various physical properties that can be calculated on the fly, and the GPUMD ecosystem. After presenting these functionalities, we review a range of applications enabled by GPUMD, particularly in combination with the NEP approach. Finally, we outline possible future development directions for GPUMD.
GPUMD
molecular dynamics
materials simulation
interatomic potential
machine-learned potential
Author
Ke Xu
Bohai University
Hekai Bu
Wuhan University
Shuning Pan
Nanjing University
Eric Lindgren
Chalmers, Physics, Condensed Matter and Materials Theory
Yongchao Wu
Beijing Institute of Technology
Yong Wang
Princeton Univ, Dept Chem
Nanjing University
Jiahui Liu
Beijing University of Technology
Keke Song
Beijing University of Technology
Bin Xu
Chinese Academy of Sciences
Yifan Li
Princeton Univ, Dept Chem
Tobias Hainer
Chalmers, Physics, Condensed Matter and Materials Theory
Lucas Svensson
Chalmers, Physics, Condensed Matter and Materials Theory
Julia Wiktor
Chalmers, Physics, Condensed Matter and Materials Theory
Rui Zhao
Xinyu University
Hongfu Huang
Beihang University
Shuo Zhang
Jiangnan University
Zezhu Zeng
The University of Hong Kong
Bohan Zhang
Bohai University
Benrui Tang
Bohai University
Yang Xiao
Bohai University
Zihan Yan
Westlake Univ
Jiuyang Shi
Nanjing University
Zhixin Liang
Nanjing University
Junjie Wang
Nanjing University
Ting Liang
Chinese University of Hong Kong
Shuo Cao
Beijing University of Technology
Yanzhou Wang
Aalto University
Penghua Ying
Tel Aviv University
Nan Xu
Zhejiang University
Chengbing Chen
Guilin University of Electronic Technology
Yuwen Zhang
Eastern Inst Technol
Zherui Chen
Shenzhen University
Xin Wu
University of Tokyo
Wenwu Jiang
Wuhan University
Esmée Berger
Chalmers, Physics, Condensed Matter and Materials Theory
Yanlong Li
Shandong Acad Sci
Shunda Chen
George Washington University
Alexander J. Gabourie
DeepSim Inc
Haikuan Dong
Bohai University
Shiyun Xiong
Guangdong University of Technology
Ning Wei
Jiangnan University
Yue Chen
The University of Hong Kong
Jianbin Xu
Chinese University of Hong Kong
Zhimei Sun
Beihang University
Tapio Ala-Nissila
Loughborough University
Aalto University
Ari Harju
Siemens Healthineers Co
Jincheng Zheng
Xiamen Univ Malaysia
Xiamen University
Pengfei Guan
Chinese Academy of Sciences
Paul Erhart
Chalmers, Physics, Condensed Matter and Materials Theory
Jian Sun
Nanjing University
Wengen Ouyang
Wuhan University
Yanjing Su
Beijing University of Technology
Zheyong Fan
Bohai University
MATERIALS GENOME ENGINEERING ADVANCES
2940-9489 (ISSN) 2940-9497 (eISSN)
Vol. 3 3 e70028Harnessing Localized Charges for Advancing Polar Materials Engineering (POLARISE)
European Commission (EC) (EC/HE/101162195), 2025-01-01 -- 2029-12-31.
SwedNESS
Swedish Foundation for Strategic Research (SSF) (GSn15-0008), 2016-07-01 -- 2021-06-30.
Swedish Foundation for Strategic Research (SSF) (GSn15-0008), 2017-01-01 -- 2020-12-31.
Subject Categories (SSIF 2025)
Condensed Matter Physics
DOI
10.1002/mgea.70028