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DeePMD-kit v2: A software package for deep potential models

文献类型：期刊论文

作者Zeng, Jinzhe2,3; Zhang, Duo4,5,6; Lu, Denghui7; Mo, Pinghui8; Li, Zeyu9; Chen, Yixiao10; Rynik, Marian11; Huang, Li'ang1; Li, Ziyao5,12; Shi, Shaochen13
刊名JOURNAL OF CHEMICAL PHYSICS
出版日期2023-08-07
卷号159期号:5页码:24
ISSN号0021-9606
DOI10.1063/5.0155600
英文摘要DeePMD-kit is a powerful open-source software package that facilitates molecular dynamics simulations using machine learning potentials known as Deep Potential (DP) models. This package, which was released in 2017, has been widely used in the fields of physics, chemistry, biology, and material science for studying atomistic systems. The current version of DeePMD-kit offers numerous advanced features, such as DeepPot-SE, attention-based and hybrid descriptors, the ability to fit tensile properties, type embedding, model deviation, DP-range correction, DP long range, graphics processing unit support for customized operators, model compression, non-von Neumann molecular dynamics, and improved usability, including documentation, compiled binary packages, graphical user interfaces, and application programming interfaces. This article presents an overview of the current major version of the DeePMD-kit package, highlighting its features and technical details. Additionally, this article presents a comprehensive procedure for conducting molecular dynamics as a representative application, benchmarks the accuracy and efficiency of different models, and discusses ongoing developments.
资助项目National Institutes of Health[GM107485] ; National Science Foundation[2138259] ; National Science Foundation[2138286] ; National Science Foundation[2138307] ; National Science Foundation[2137603] ; National Science Foundation[2138296] ; National Science Foundation[CHE190067] ; Van Dyke Award from the Department of Chemistry and Chemical Biology, Rutgers ; VEGA[APVV-19-0371] ; Slovak Research and Development Agency[2021RC4026] ; Science and Technology Innovation Program of Hunan Province[262695] ; Research Council of Norway through the Centre of Excellence Hylleraas Centre for Quantum Molecular Sciences[DE-SC0019759] ; United States Department of Energy (DOE)[2022YFA1004300] ; National Key Ramp;D Program of China[12122103] ; National Natural Science Foundation of China[CHE20002] ; State University of New Jersey ; Advanced Cyberinfrastructure Coordination Ecosystem: Services amp; Support (ACCESS) program ; Chemistry in Solution and at Interfaces (CSI) Center - United States Department of Energy ; Texas Advanced Computing Center (TACC) at the University of Texas at Austin[DE-SC0019394] ; Princeton Research Computing resources at Princeton University ; AMD Cloud Platform at AMD, Inc ; [1/0640/20]
WOS研究方向Chemistry ; Physics
语种英语
WOS记录号WOS:001041174500011
出版者AIP Publishing
源URL[http://119.78.100.204/handle/2XEOYT63/21343]  
专题中国科学院计算技术研究所期刊论文_英文
通讯作者Wang, Han
作者单位1.Tsinghua Univ, Inst Interdisciplinary Informat Sci, Ctr Quantum Informat, Beijing 100084, Peoples R China
2.Rutgers State Univ, Inst Quantitat Biomed, Lab Biomol Simulat Res, Piscataway, NJ 08854 USA
3.Rutgers State Univ, Dept Chem & Chem Biol, Piscataway, NJ 08854 USA
4.AI Sci Inst, Beijing 100080, Peoples R China
5.DP Technol, Beijing 100080, Peoples R China
6.Peking Univ, Acad Adv Interdisciplinary Studies, Beijing 100871, Peoples R China
7.Peking Univ, Coll Engn, HEDPS, CAPT, Beijing 100871, Peoples R China
8.Hunan Univ, Coll Elect & Informat Engn, Changsha, Peoples R China
9.Peking Univ, Yuanpei Coll, Beijing 100871, Peoples R China
10.Princeton Univ, Program Appl & Computat Math, Princeton, NJ 08540 USA
推荐引用方式
GB/T 7714		 Zeng, Jinzhe,Zhang, Duo,Lu, Denghui,et al. DeePMD-kit v2: A software package for deep potential models[J]. JOURNAL OF CHEMICAL PHYSICS,2023,159(5):24.
APA Zeng, Jinzhe.,Zhang, Duo.,Lu, Denghui.,Mo, Pinghui.,Li, Zeyu.,...&Wang, Han.(2023).DeePMD-kit v2: A software package for deep potential models.JOURNAL OF CHEMICAL PHYSICS,159(5),24.
MLA Zeng, Jinzhe,et al."DeePMD-kit v2: A software package for deep potential models".JOURNAL OF CHEMICAL PHYSICS 159.5(2023):24.

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来源：计算技术研究所

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