Parallel Discrete Event Simulation of Molecular Dynamics Through Event-Based Decomposition

Herbordt, Martin C.; Khan, Md. Ashfaquzzaman; Dean, Tony

doi:10.1109/asap.2009.39

Cited by 9 publications

(8 citation statements)

References 13 publications

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“…4a). The parallel implementation of ECMC, for short-range interactions, is conceptually much simpler than that of event-driven molecular dynamics [29,14,20], and it may well extend to long-range interacting system.…”

Section: Parallelizationmentioning

confidence: 99%

JeLLyFysh-Version1.0 — a Python application for all-atom event-chain Monte Carlo

Hoellmer

Qin

Faulkner

et al. 2020

Computer Physics Communications

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We present JeLLyFysh-Version1.0, an open-source Python application for eventchain Monte Carlo (ECMC), an event-driven irreversible Markov-chain Monte Carlo algorithm for classical N -body simulations in statistical mechanics, biophysics and electrochemistry. The application's architecture closely mirrors the mathematical formulation of ECMC. Local potentials, long-ranged Coulomb interactions and multi-body bending potentials are covered, as well as bounding potentials and cell systems including the cell-veto algorithm. Configuration files illustrate a number of specific implementations for interacting atoms, dipoles, and water molecules.

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Section: Parallelizationmentioning

confidence: 99%

JeLLyFysh-Version1.0 — a Python application for all-atom event-chain Monte Carlo

Hoellmer

Qin

Faulkner

et al. 2020

Computer Physics Communications

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“…In the past, DMD simulations were often associated with coarse-grained molecular systems. With the recent development of a high-resolution DMD force field as well as advances in DMD efficiency, DMD simulations have been applied to study the dynamics of [47,48], in the future the DMD engine will be extended to sample the dynamics of ever larger molecules and molecular complexes with even longer time scales. With its ability to efficiently sample the conformational dynamics of complicated systems, DMD simulations will play an important role in our understanding of biology and the effort to combat human diseases.…”

Section: Resultsmentioning

confidence: 99%

Discrete Molecular Dynamics Simulation of Biomolecules

Ding

Dokholyan

2012

Computational Modeling of Biological Systems

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“…Software packages such as DynamO [7] implement all of these methods, but are currently limited to systems with friction coefficient γ = 0. Finally, methods to efficiently parallelise EDPD algorithms have also been constructed [26].…”

Section: Parametrisation Of G (2) ( )mentioning

confidence: 99%

“…The moments eqs. (26)and 27 can be constructed analytically by using standard results for moments of Gaussians with mean μ and variance ς:…”

Section: Appendix a Moments Of The Collision Operatormentioning

confidence: 99%

Modelling inelastic Granular Media Using Dynamical Density Functional Theory

2021

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We construct a new mesoscopic model for granular media using Dynamical Density Functional Theory (DDFT). The model includes both a collision operator to incorporate inelasticity and the Helmholtz free energy functional to account for external potentials, interparticle interactions and volume exclusion. We use statistical data from event-driven microscopic simulations to determine the parameters not given analytically by the closure relations used to derive the DDFT. We numerically demonstrate the crucial effects of each term and approximations in the DDFT, and the importance of including an accurately parametrised pair correlation function.

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Parallel Discrete Event Simulation of Molecular Dynamics Through Event-Based Decomposition

Cited by 9 publications

References 13 publications

JeLLyFysh-Version1.0 — a Python application for all-atom event-chain Monte Carlo

JeLLyFysh-Version1.0 — a Python application for all-atom event-chain Monte Carlo

Discrete Molecular Dynamics Simulation of Biomolecules

Modelling inelastic Granular Media Using Dynamical Density Functional Theory

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