Accomplishments of Sandia and Kitware CMake/CTest/CDash Contract for (FY2017-2020)

Bean, Bryon; Galbreath, Zack; Bartlett, Roscoe

doi:10.2172/1784597

Cited by 1 publication

(1 citation statement)

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“…The CMake build system 130 manages all modules, and the pip and scikit-build 131 packages are used to distribute DeePMD-kit as a Python package. The standard Python unit testing framework 132 is used for unit tests on all Python codes, while GoogleTest software 133 is used for tests on all C++ codes.…”

Section: Technical Implementationmentioning

confidence: 99%

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

Zeng,

Zhang,

et al. 2023

The Journal of Chemical Physics

144

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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.

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Section: Technical Implementationmentioning

confidence: 99%