610591 GPU Optimized Monte Carlo Version 2.50

Wednesday, November 18, 2020
Computational Molecular Science and Engineering Forum (21) (Poster Gallery)
Younes Nejahi1, Mohammad Soroush Barhaghi2, Gregory Schwing3, Loren Schwiebert1 and Jeffrey J. Potoff4, (1)Computer Science, Wayne State University, Detroit, MI, (2)Chemical Engineering and Materials Science, Wayne State University, Detroit, MI, (3)Wayne State University, Detroit, MI, (4)Chemcial Engineering and Materials Science, Wayne State University, Detroit, MI

GOMC is a general-purpose Monte Carlo simulation engine for the simulation of molecular systems with molecular mechanics force fields based on the 12-6 Lennard-Jones, or Mie potentials[1]. It has support for simulations in all common ensembles, including the Gibbs ensemble Monte Carlo algorithm. GOMC was designed with a focus on high performance, and has support for simulations on multi-core CPUs and graphics processing units (GPUs). This poster highlights a number of recent enhancements to GOMC, including new Monte Carlo moves to enhance the sampling of phase space, such as Molecular Exchange Monte Carlo (MEMC)[2,3], configurational-bias for molecules that contain rings, the crankshaft move, parallel tempering, force/torque-biased multi-particle move as well as a multi-particle move using Brownian dynamics[4]. Support for force fields governed by exp-6 potentials, and free energy calculations using thermodynamic integration or free energy perturbation has been added.

[1] Nejahi, Y, Barhaghi, MS, Mick, J, Jackman, B, Rushaidat, K, Li, YZ, et al. GOMC: GPU Optimized Monte Carlo for the simulation of phase equilibria and physical properties of complex fluids. Softwarex, 2019; 9: 20-7.

[2] Barhaghi, MS, Torabi, K, Nejahi, Y, Schwiebert, L,Potoff, JJ. Molecular exchange Monte Carlo: A generalized method for identity exchanges in grand canonical Monte Carlo simulations. J. Chem. Phys., 2018; 149(7): 072318.

[3] Barhaghi, MS,Potoff, JJ. Prediction of phase equilibria and Gibbs free energies of transfer using molecular exchange Monte Carlo in the Gibbs ensemble. Fluid Phase Equilib., 2019; 486: 106-18.

[4] Moucka, F, Rouha, M,Nezbeda, I. Efficient multiparticle sampling in Monte Carlo simulations on fluids: Application to polarizable models. J. Chem. Phys., 2007; 126(22): 224106.


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