PySAGES:flexible,advanced sampling methods accelerated with GPUs  

作　　者：Pablo F.Zubieta Rico Ludwig Schneider Gustavo R.Pérez-Lemus Riccardo Alessandri Siva Dasetty Trung D.Nguyen Cintia A.Menéndez Yiheng Wu Yezhi Jin Yinan Xu Samuel Varner John A.Parker Andrew L.Ferguson Jonathan K.Whitmer Juan Jde Pablo 

机构地区：[1]Pritzker School of Molecular Engineering,The University of Chicago,Chicago,IL 60637,USA [2]Research Computing Center,The University of Chicago,Chicago,IL 60637,USA [3]Division of Chemistry and Chemical Engineering,California Institute of Technology,Pasadena,CA 91125,USA [4]Department of Chemical and Biomolecular Engineering,University of Notre Dame,Notre Dame,IN 46556,USA

出　　处：《npj Computational Materials》2024年第1期2877-2888,共12页计算材料学(英文)

基　　金：supported by the Department of Energy,Basic Energy Sciences,Materials Science and Engineering Division,through the Midwest Integrated Center for Computational Materials(MICCoM);supported by the Dutch Research Council(NWO Rubicon 019.202EN.028);supported by the U.S.Department of Energy,Office of Science,Office of Advanced Scientific Computing Research,Department of Energy Computational Science Graduate Fellowship under Award Number DE-SC0022158.

摘　　要：Molecular simulations are an important tool for research in physics,chemistry,and biology.The capabilities of simulations can be greatly expanded by providing access to advanced sampling methods and techniques that permit calculation of the relevant underlying free energy landscapes.In this sense,software that can be seamlessly adapted to a broad range of complex systems is essential.Building on past efforts to provide open-source community-supported software for advanced sampling,we introduce PySAGES,a Python implementation of the Software Suite for Advanced General Ensemble Simulations(SSAGES)that provides full GPU support for massively parallel applications of enhanced sampling methods such as adaptive biasing forces,harmonic bias,or forward flux sampling in the context of molecular dynamics simulations.By providing an intuitive interface that facilitates the management of a system’s configuration,the inclusion of new collective variables,and the implementation of sophisticated free energy-based sampling methods,the PySAGES library serves as a general platform for the development and implementation of emerging simulation techniques.The capabilities,core features,and computational performance of this tool are demonstrated with clear and concise examples pertaining to different classes of molecular systems.We anticipate that PySAGES will provide the scientific community with a robust and easily accessible platform to accelerate simulations,improve sampling,and enable facile estimation of free energies for a wide range of materials and processes.

关 键 词：PYTHON SAGE COLLECTIVE 

分 类 号：TP3[自动化与计算机技术—计算机科学与技术]