PuReMD-GPU: A reactive molecular dynamics simulation package for GPUs

Kylasa, Sudhir B.; Aktulga, Hasan Metin; Grama, Ananth

doi:10.1016/j.jcp.2014.04.035

Cited by 53 publications

(28 citation statements)

References 20 publications

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“…The 2005 functional form developed for RDX is the current version of ReaxFF distributed by the van Duin group (commonly referred to as 'standalone ReaxFF'), as well as integrated in the open-source LAMMPS code, 9 supported through Nanohub, (http://www.nanohub.org) and available through the PuReMD (Purdue Reactive Molecular Dynamics) code. [10][11][12] Apart from these open-source distributions, the ReaxFF method is also integrated in ADF 13 …”

Section: Development Of the Reaxff Methods History Of Reaxff Developmentmentioning

confidence: 99%

“…An optimised binning-based neighbour generation method, elimination of the bond-order derivatives list in bonded interactions, lookup tables to accelerate non-bonded interaction computations, and preconditioned fast iterative solvers for the charge equilibration problem are the major algorithmic innovations in PuReMD. 10,12,15 The dynamic nature of the bond, three-body and four-body interactions in a reactive molecular system presents challenges in terms of memory management and data structures for efficiently computing bonded interactions. PuReMD introduces novel data structures to store three-body and four-body interactions in a compact form.…”

Section: Future Developments and Outlookmentioning

confidence: 99%

“…Recently, Kylasa et al have developed a publically available GPU version of the PuReMD code, called PuReMD-GPU 10 , which uses CUDA along with an extensive set of optimisations to deliver significant speedups on single GPU systems. For a variety of benchmarks, this code shows up to a 16-fold speedup on an Nvidia C2075 GPU, compared with a single core of an Intel Xeon processor.…”

Section: Future Developments and Outlookmentioning

confidence: 99%

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The ReaxFF reactive force-field: development, applications and future directions

et al. 2016

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The reactive force-field (ReaxFF) interatomic potential is a powerful computational tool for exploring, developing and optimizing material properties. Methods based on the principles of quantum mechanics (QM), while offering valuable theoretical guidance at the electronic level, are often too computationally intense for simulations that consider the full dynamic evolution of a system. Alternatively, empirical interatomic potentials that are based on classical principles require significantly fewer computational resources, which enables simulations to better describe dynamic processes over longer timeframes and on larger scales. Such methods, however, typically require a predefined connectivity between atoms, precluding simulations that involve reactive events. The ReaxFF method was developed to help bridge this gap. Approaching the gap from the classical side, ReaxFF casts the empirical interatomic potential within a bond-order formalism, thus implicitly describing chemical bonding without expensive QM calculations. This article provides an overview of the development, application, and future directions of the ReaxFF method. INTRODUCTIONAtomistic-scale computational techniques provide a powerful means for exploring, developing and optimizing promising properties of novel materials. Simulation methods based on quantum mechanics (QM) have grown in popularity over recent decades due to the development of user-friendly software packages making QM level calculations widely accessible. Such availability has proved particularly relevant to material design, where QM frequently serves as a theoretical guide and screening tool. Unfortunately, the computational cost inherent to QM level calculations severely limits simulation scales. This limitation often excludes QM methods from considering the dynamic evolution of a system, thus hampering our theoretical understanding of key factors affecting the overall behaviour of a material. To alleviate this issue, QM structure and energy data are used to train empirical force fields that require significantly fewer computational resources, thereby enabling simulations to better describe dynamic processes. Such empirical methods, including reactive force-field (ReaxFF), 1 trade accuracy for lower computational expense, making it possible to reach simulation scales that are orders of magnitude beyond what is tractable for QM.Atomistic force-field methods utilise empirically determined interatomic potentials to calculate system energy as a function of atomic positions. Classical approximations are well suited for nonreactive interactions, such as angle-strain represented by harmonic potentials, dispersion represented by van der Waals potentials and Coulombic interactions represented by various polarisation schemes. However, such descriptions are inadequate for modelling changes in atom connectivity (i.e., for modelling chemical reactions as bonds break and form). This motivates the

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Section: Development Of the Reaxff Methods History Of Reaxff Developmentmentioning

confidence: 99%

Section: Future Developments and Outlookmentioning

confidence: 99%

Section: Future Developments and Outlookmentioning

confidence: 99%

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The ReaxFF reactive force-field: development, applications and future directions

et al. 2016

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“…PuReMD and User‐ReaxC have been used by researchers around the world to study phenomena ranging from water‐silica surface interactions to oxidative stress in lipid molecules . Recently, Kylasa et al have developed the GPU accelerated version of the PuReMD codebase (Kylasa et al, in preparation) . The entire PuReMD codebase is freely available with GNU Public Licence on the web…”

Section: Methods and Techniquesmentioning

confidence: 99%

Efficient global optimization of reactive force‐field parameters

et al. 2015

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Reactive force fields make low-cost simulations of chemical reactions possible. However, optimizing them for a given chemical system is difficult and time-consuming. We present a high-performance implementation of global force-field parameter optimization, which delivers parameter sets of the same quality with much less effort and in far less time than before, and also offers excellent parallel scaling. We demonstrate these features with example applications targeting the ReaxFF force field. © 2015 Wiley Periodicals, Inc.

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“…The parallel XRMD code has achieved unprecedented scalability and orders-of-magnitude improvement of the time-to-solution over the previous state-of-the-art based on hybrid message passing + multithreading implementation and various code transformations. Here, it should be noted that the extended Lagrangian method is used in tandem with highly efficient preconditioned conjugate-gradient (PCG) methods [17,18] to achieve a high level of convergence.…”

Section: Introductionmentioning

confidence: 99%

Scalable Reactive Molecular Dynamics Simulations for Computational Synthesis

et al. 2019

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Reactive molecular-dynamics (MD) simulation is a powerful research tool for describing chemical reactions. We eliminate the speed-limiting charge iteration in MD with a novel extended-Lagrangian scheme. The extended-Lagrangian reactive MD (XRMD) code drastically improves energy conservation while substantially reducing time-to-solution. Furthermore, we introduce a new polarizable charge equilibration (PQEq) model to accurately predict atomic charges and polarization. The XRMD code based on hybrid message passing+multithreading achieves a weak-scaling parallel efficiency of 0.977 on 786,432 IBM Blue Gene/Q cores for a 67.6 billion-atom system. The performance is portable to the 2 nd generation Intel Xeon Phi, Knights Landing. Blue Gene/Q simulations for the computational synthesis of materials via novel exfoliation mechanisms for synthesizing atomically thin transition metal dichalcogenide layers, which will dominate nanomaterials science in this century. KEYWORDS

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PuReMD-GPU: A reactive molecular dynamics simulation package for GPUs

Cited by 53 publications

References 20 publications

The ReaxFF reactive force-field: development, applications and future directions

The ReaxFF reactive force-field: development, applications and future directions

Efficient global optimization of reactive force‐field parameters

Scalable Reactive Molecular Dynamics Simulations for Computational Synthesis

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