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OpenMM 7:分子动力学高性能算法的快速开发。

OpenMM 7: Rapid development of high performance algorithms for molecular dynamics.

作者信息

Eastman Peter, Swails Jason, Chodera John D, McGibbon Robert T, Zhao Yutong, Beauchamp Kyle A, Wang Lee-Ping, Simmonett Andrew C, Harrigan Matthew P, Stern Chaya D, Wiewiora Rafal P, Brooks Bernard R, Pande Vijay S

机构信息

Department of Chemistry, Stanford University, Stanford, California, United States of America.

Department of Chemistry and Chemical Biology and BioMaPS Institute, Rutgers University, Piscataway, New Jersey, United States of America.

出版信息

PLoS Comput Biol. 2017 Jul 26;13(7):e1005659. doi: 10.1371/journal.pcbi.1005659. eCollection 2017 Jul.

DOI:10.1371/journal.pcbi.1005659
PMID:28746339
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5549999/
Abstract

OpenMM is a molecular dynamics simulation toolkit with a unique focus on extensibility. It allows users to easily add new features, including forces with novel functional forms, new integration algorithms, and new simulation protocols. Those features automatically work on all supported hardware types (including both CPUs and GPUs) and perform well on all of them. In many cases they require minimal coding, just a mathematical description of the desired function. They also require no modification to OpenMM itself and can be distributed independently of OpenMM. This makes it an ideal tool for researchers developing new simulation methods, and also allows those new methods to be immediately available to the larger community.

摘要

OpenMM是一个分子动力学模拟工具包,特别注重可扩展性。它允许用户轻松添加新功能,包括具有新颖函数形式的力、新的积分算法和新的模拟协议。这些功能可在所有支持的硬件类型(包括CPU和GPU)上自动运行,并且在所有这些硬件上都能良好运行。在许多情况下,它们只需要最少的编码,只需对所需函数进行数学描述。它们也不需要对OpenMM本身进行修改,并且可以独立于OpenMM进行分发。这使其成为研究人员开发新模拟方法的理想工具,也使这些新方法能够立即供更广泛的社区使用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/efb1/5549999/17f3e1e8515a/pcbi.1005659.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/efb1/5549999/17f3e1e8515a/pcbi.1005659.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/efb1/5549999/17f3e1e8515a/pcbi.1005659.g001.jpg

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