Cluster algorithm to perform parallel Monte Carlo simulation of atomistic systems

We propose an efficient algorithm to perform Monte Carlo simulations of dense systems using multiple particle moves. The method is intended to be used in the atomistic simulation of complex systems, where the computing requirements for a single simulation run make advisable the use of parallel computing. The algorithm is based on the use of steps in which all the particle positions of the system are perturbed simultaneously. A division of the system in clusters of particles is performed, using a bonding criterion which makes feasible that the acceptance or rejection of the new particle coordinates can be carried out independently for each cluster.     

Implementation of a data parallel,logical domain decomposition method for interparticle interactions in molecular dynamics of structured molecular fluids

In this article, we describe a domain decomposition method for the efficient parallel computation of nonbonded forces and energies in condensed-phase molecular systems. This decomposition is based upon the monotonic logical grid (MLG) approach of Boris [J. Boris, J. Comp. Phys., 66 , 1 (1986)] and yields an efficient, scalable algorithm for interparticle interaction computation on private-memory, single-instruction multiple-data (SIMD) parallel computers. We illustrate the application of this technique in a molecular dynamics kernel for rigid molecular solvents by simulating the structural and thermodynamic properties of water and methanol. The performance of this algorithm on the Thinking Machines' CM-2, private-memory SIMD computer, is demonstrated to be good compared to conventional vector/parallel supercomputers. However, as the fluid becomes less structured performance slightly degrades. © 1994 by John Wiley & Sons, Inc.     

Long-timescale simulations of diffusion in molecular solids

Kinetic processes play a crucial role in the formation and evolution of molecular layers. In this perspective we argue that adaptive kinetic Monte Carlo is a powerful simulation technique for determining key kinetic processes in molecular solids. The applicability of the method is demonstrated by simulating the diffusion of a CO admolecule on a water ice surface, which is an important process for the formation of organic compounds on interstellar dust grains. CO diffusion is found to follow Arrhenius behavior and the corresponding effective activation energy for diffusion is determined to be 50 ± 1 meV. A coarse graining algorithm is applied which greatly enhances the efficiency of the simulations at low temperatures, down to 10 K, without altering the underlying physical processes. Eventually, we argue that a combination of both on- and off-lattice kinetic Monte Carlo techniques is a good way for simulating large-scale processes in molecular solids over long time spans.     

Rapid subgraph search using parallelism

A new parallel processing algorithm is reported for subgraph matching. Parallelism is achieved for the first time within the process of node-by-node matching of two individual graphs. A SIMULA program is described for simulating this parallel subgraph search algorithm. Simulation results from a series of chemical substructure search problems show an average utilization of 84% on a 25-processor machine and up to a 24-fold speed enhancement over a single processor. Potential applications include starting material selections for synthesis as well as general substructure search problems.     

Hybrid particle‐field molecular dynamics simulations: Parallelization and benchmarks

The parallel implementation of a recently developed hybrid scheme for molecular dynamics (MD) simulations (Milano and Kawakatsu, J Chem Phys 2009, 130, 214106) where self‐consistent field theory (SCF) and particle models are combined is described. Because of the peculiar formulation of the hybrid method, considering single particles interacting with density fields, the most computationally expensive part of the hybrid particle‐field MD simulation can be efficiently parallelized using a straightforward particle decomposition algorithm. Benchmarks of simulations, including comparisons of serial MD and MD‐SCF program profiles, serial MD‐SCF and parallel MD‐SCF program profiles, and parallel benchmarks compared with efficient MD program GROMACS 4.5.4 are tested and reported. The results of benchmarks indicate that the proposed parallelization scheme is very efficient and opens the way to molecular simulations of large scale systems with reasonable computational costs. © 2012 Wiley Periodicals, Inc.     

Improvement of energy dissipative particle dynamics method to increase accuracy

In this article, dissipative particle dynamics with energy conservation eDPD is used for simulating hydrodynamic behavior and heat transfer of DPD particles in a two-dimensional channel with parallel planes. To this end, a Fortran programming code is developed and the results are presented as dimensionless velocity and temperature profiles on the cross section perpendicular to the flow direction inside the channel. For the indented geometry, thermal and dynamic boundary conditions have been considered. The dynamic boundary condition of solution domain in the flow’s direction is periodic, and for modeling the walls, freezing layers of DPD particles with Bounce-Back reflection has been used. For the thermal boundary condition, it is assumed that the wall temperature is constant and the temperature of each DPD particle in contact with the wall is the same as the wall temperature. In this article, for the first time, for modeling the walls four frozen layers with Bounce-Back reflection are used and the effect of particle exit on two and three-layers configurations is investigated. Furthermore, for the first time, modified velocity Verlet integration algorithm is improved by adding heat transfer equations. And considering λ?=?0.65 in the algorithm; the indented geometry is well simulated. In order to validate the results, first, the effect of regular and random initial distribution is compared. Furthermore, the results of wall alignment are compared with those obtained from CFD approach. In this paper, in addition to studying the effect of wall alignment and initial particle arrangement, the influence of the size of cells for averaging and the time steps in the output results are investigated.

     

Acceleration of Monte Carlo simulations through spatial updating in the grand canonical ensemble

A new grand canonical Monte Carlo algorithm for continuum fluid models is proposed. The method is based on a generalization of sequential Monte Carlo algorithms for lattice gas systems. The elementary moves, particle insertions and removals, are constructed by analogy with those of a lattice gas. The updating is implemented by selecting points in space (spatial updating) either at random or in a definitive order (sequential). The type of move, insertion or removal, is deduced based on the local environment of the selected points. Results on two-dimensional square-well fluids indicate that the sequential version of the proposed algorithm converges faster than standard grand canonical algorithms for continuum fluids. Due to the nature of the updating, additional reduction of simulation time may be achieved by parallel implementation through domain decomposition.     

Biologically driven neural platform invoking parallel electrophoretic separation and urinary metabolite screening

This work reveals a computational framework for parallel electrophoretic separation of complex biological macromolecules and model urinary metabolites. More specifically, the implementation of a particle swarm optimization (PSO) algorithm on a neural network platform for multiparameter optimization of multiplexed 24-capillary electrophoresis technology with UV detection is highlighted. Two experimental systems were examined: (1) separation of purified rabbit metallothioneins and (2) separation of model toluene urinary metabolites and selected organic acids. Results proved superior to the use of neural networks employing standard back propagation when examining training error, fitting response, and predictive abilities. Simulation runs were obtained as a result of metaheuristic examination of the global search space with experimental responses in good agreement with predicted values. Full separation of selected analytes was realized after employing optimal model conditions. This framework provides guidance for the application of metaheuristic computational tools to aid in future studies involving parallel chemical separation and screening. Adaptable pseudo-code is provided to enable users of varied software packages and modeling framework to implement the PSO algorithm for their desired use.     

Parallelization and improvements of the generalized born model with a simple sWitching function for modern graphics processors

Two fundamental challenges of simulating biologically relevant systems are the rapid calculation of the energy of solvation and the trajectory length of a given simulation. The Generalized Born model with a Simple sWitching function (GBSW) addresses these issues by using an efficient approximation of Poisson–Boltzmann (PB) theory to calculate each solute atom's free energy of solvation, the gradient of this potential, and the subsequent forces of solvation without the need for explicit solvent molecules. This study presents a parallel refactoring of the original GBSW algorithm and its implementation on newly available, low cost graphics chips with thousands of processing cores. Depending on the system size and nonbonded force cutoffs, the new GBSW algorithm offers speed increases of between one and two orders of magnitude over previous implementations while maintaining similar levels of accuracy. We find that much of the algorithm scales linearly with an increase of system size, which makes this water model cost effective for solvating large systems. Additionally, we utilize our GPU‐accelerated GBSW model to fold the model system chignolin, and in doing so we demonstrate that these speed enhancements now make accessible folding studies of peptides and potentially small proteins. © 2016 Wiley Periodicals, Inc.     

A new extension of classical molecular dynamics: An electron transfer algorithm

The molecular dynamics is one of the most widely used methods for the simulation of the properties corresponding to ionic motion. Unfortunately, classical molecular dynamics cannot be applied for electron transfer simulation. Suggested modification of the molecular dynamics allows performing the electron transfer from one particle to another during simulation runtime. All additional data structure and the corresponding algorithms are presented in this article. The method can be applied to the systems with pair Van der Waals and Coulomb interactions. Moreover, it may be extended for many‐bodied interatomic interactions. In addition, an algorithm of transference numbers calculation has been designed. This extension is not an independent method but it can be useful for simulating the systems with high concentration of electron donors and acceptors. © 2017 Wiley Periodicals, Inc.     

ORAC: A Molecular dynamics program to simulate complex molecular systems with realistic electrostatic interactions

In this study, we present a new molecular dynamics program for simulation of complex molecular systems. The program, named ORAC, combines state-of-the-art molecular dynamics (MD) algorithms with flexibility in handling different types and sizes of molecules. ORAC is intended for simulations of molecular systems and is specifically designed to treat biomolecules efficiently and effectively in solution or in a crystalline environment. Among its unique features are: (i) implementation of reversible and symplectic multiple time step algorithms (or r-RESPA, reversible reference system propagation algorithm) specifically designed and tuned for biological systems with periodic boundary conditions; (ii) availability for simulations with multiple or single time steps of standard Ewald or smooth particle mesh Ewald (SPME) for computation of electrostatic interactions; and (iii) possibility of simulating molecular systems in a variety of thermodynamic ensembles. We believe that the combination of these algorithms makes ORAC more advanced than other MD programs using standard simulation algorithms. © 1997 John Wiley & Sons, Inc. J Comput Chem 18 : 1848–1862, 1997     

Surface diffusion an—Exercise in D = 2 + 1 dynamics

The diffusion of particles on surfaces of solids play important role in understanding variety of phenomena, which are of considerable theoretical and applied interest. For example surface diffusion may alter the mode of the morphological structure via which crystal growth progresses. Study of surface diffusion, and more generally dynamics of many particle systems on solid surfaces may also offer an insight into the more fundamental problems, for example how many particle dynamics is affected by change of the spatial dimensionality.     

Optimized parallel tempering simulations of proteins

We apply a recently developed adaptive algorithm that systematically improves the efficiency of parallel tempering or replica exchange methods in the numerical simulation of small proteins. Feedback iterations allow us to identify an optimal set of temperatures/replicas which are found to concentrate at the bottlenecks of the simulations. A measure of convergence for the equilibration of the parallel tempering algorithm is discussed. We test our algorithm by simulating the 36-residue villin headpiece subdomain HP-36 where we find a lowest-energy configuration with a root-mean-square deviation of less than 4 A to the experimentally determined structure.     

A new parallel method for molecular dynamics simulation of macromolecular systems

Short-range molecular dynamics simulations of molecular systems are commonly parallelized by replicated-data methods, in which each processor stores a copy of all atom positions. This enables computation of bonded 2-, 3-, and 4-body forces within the molecular topology to be partitioned among processors straightforwardly. A drawback to such methods is that the interprocessor communication scales as N (the number of atoms) independent of P (the number of processors). Thus, their parallel efficiency falls off rapidly when large numbers of processors are used. In this article a new parallel method for simulating macromolecular or small-molecule systems is presented, called force-decomposition. Its memory and communication costs scale as N/√P, allowing larger problems to be run faster on greater numbers of processors. Like replicated-data techniques, and in contrast to spatial-decomposition approaches, the new method can be simply load balanced and performs well even for irregular simulation geometries. The implementation of the algorithm in a prototypical macromolecular simulation code ParBond is also discussed. On a 1024-processor Intel Paragon, ParBond runs a standard benchmark simulation of solvated myoglobin with a parallel efficiency of 61% and at 40 times the speed of a vectorized version of CHARMM running on a single Cray Y-MP processor. © 1996 by John Wiley & Sons, Inc.     

Rheology of Dilute Acid Hydrolyzed Corn Stover at High Solids Concentration

The rheological properties of acid hydrolyzed corn stover at high solids concentration (20–35 wt.%) were investigated using torque rheometry. These materials are yield stress fluids whose rheological properties can be well represented by the Bingham model. Yield stresses increase with increasing solids concentration and decrease with increasing hydrolysis reaction temperature, acid concentration, and rheometer temperature. Plastic viscosities increase with increasing solids concentration and tend to decrease with increasing reaction temperature and acid concentration. The solids concentration dependence of the yield stress is consistent with that reported for other fibrous systems. The changes in yield stress with reaction conditions are consistent with observed changes in particle size. This study illustrates that torque rheometry can be used effectively to measure rheological properties of concentrated biomass.     

Boundary conditions in local electrostatics algorithms

We study the simulation of charged systems in the presence of general boundary conditions in a local Monte Carlo algorithm based on a constrained electric field. We first show how to implement constant-potential, Dirichlet boundary conditions by introducing extra Monte Carlo moves to the algorithm. Second, we show the interest of the algorithm for studying systems which require anisotropic electrostatic boundary conditions for simulating planar geometries such as membranes.     

Kinetic theory derivation of the transport coefficients of stochastic rotation dynamics

We use a kinetic theory approach to derive the continuum Navier-Stokes and heat conduction equations for stochastic rotation dynamics, a particle based algorithm for simulating a fluid. Hence we obtain expressions for the viscosity and thermal conductivity in two and three dimensions. The predictions are tested numerically and good agreement is found.     

Efficient Stochastic Simulation Algorithm for Chemically Reacting Systems Based on Support Vector Regression

The stochastic simulation algorithm （SSA） accurately depicts spatially homogeneous wellstirred chemically reacting systems with small populations of chemical species and properly represents noise, but it is often abandoned when modeling larger systems because of its computational complexity. In this work, a twin support vector regression based stochastic simulations algorithm （TS^3A） is proposed by combining the twin support vector regression and SSA, the former is a well-known robust regression method in machine learning. Numerical results indicate that this proposed algorithm can be applied to a wide range of chemically reacting systems and obtain significant improvements on efficiency and accuracy with fewer simulating runs over the existing methods.     

Emulsifier-free emulsion polymerization with cationic comonomer

An earlier article¹ described the emulsion polymerization of styrene and various anionic comonomers, together with an anionic initiator, to give uniform latices at ca. 35% solids content. This article extends the work to cationic systems. Cationic comonomers 1,2-dimethyl 5-vinylpyridinium methylsulfate and 1-ethyl 2-methyl 5-vinylpyridinium bromide were synthesized and used with azobis(isobutyramidine hydrocholoride) initiator in the emulsifier- free emulsion polymerization of styrene. Recipes and results were generally comparable to those of the anionic systems, excepts for the dependence of particle diameter on comonomers concentration. Here the initial decrease was followed by an increase in particle diameter at higher comonomer content. The surface charge increased sharply with comonomer content.     

Novel On-Line Sedimentation Analyzer

The design and development of a novel vibrating reed technique for on-line measurement of the sedimentation kinetics of two-phase dispersions is described. The feasibility of operation of the analyzer has been successfully verified in conjunction with a variety of model and industrially relevant systems. The former include mono- and polydisperse glass ballotini/water mixtures with solids particle sizes and concentration ranges of 55-200 μm and 1.75-2.81% (v/v), respectively. Measured settling velocities are in good accord with those obtained from direct visual observation of suspension-clear liquid interfaces. The industrially relevant systems include agglomerated kaolin/water suspensions with solids concentrations as high as 20% (v/v) and oil/water emulsions with light phase concentrations in the range 30-50% (v/v). Copyright 2000 Academic Press.