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Hierarchical parallelization of divide‐and‐conquer density functional tight‐binding molecular dynamics and metadynamics simulations
Author(s) -
Nishimura Yoshifumi,
Nakai Hiromi
Publication year - 2020
Publication title -
journal of computational chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.907
H-Index - 188
eISSN - 1096-987X
pISSN - 0192-8651
DOI - 10.1002/jcc.26217
Subject(s) - metadynamics , molecular dynamics , divide and conquer algorithms , replica , tight binding , massively parallel , computer science , statistical physics , parallel tempering , computational chemistry , computational science , chemical physics , physics , parallel computing , chemistry , electronic structure , algorithm , artificial intelligence , art , bayesian probability , markov chain monte carlo , monte carlo molecular modeling , visual arts
Abstract Massively parallel divide‐and‐conquer density functional tight‐binding (DC‐DFTB) molecular dynamics and metadynamics simulations are efficient approaches for describing various chemical reactions and dynamic processes of large complex systems via quantum mechanics. In this study, DC‐DFTB simulations were combined with multi‐replica techniques. Specifically, multiple walkers metadynamics, replica exchange molecular dynamics, and parallel tempering metadynamics methods were implemented hierarchically into the in‐house D cdftbmd program. Test simulations in an aqueous phase of the internal rotation of formamide and conformational changes of dialanine showed that the newly developed extensions increase the sampling efficiency and the exploration capabilities in DC‐DFTB configuration space.