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(346aw) GPU Optimized Monte Carlo Version 2.50

Potoff, J. J. - Presenter, Wayne State University
Nejahi, Y., Wayne State University
Soroush Barhaghi, M., Wayne State University
Schwing, G., Wayne State University
Schwiebert, L., Wayne State University
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.