Simulation Of Large Systems Research Articles

Applicability of O(N)-like density functional study on the structural properties of nitrogen defects in SiC

We investigate the quantitative applicability of a subspace optimization method formulated in terms of localized nonorthogonal orbitals. A Grassmann conjugate gradient algorithm is our subspace optimization method. We usethe substitution of a silicon atom by a nitrogen atom in cubic SiC with two different configurations as our test systems. Modifications of the existing method are made for the inclusion of a half-filled defect level. The approximation of localization for the orbitals gives linear scaling of the dominant parts of the algorithm thus allowing for the simulation of large systems. Numerical tests indicate that quite accurate quantitative results are obtained when using extended orbitals near the defect and a localization regions with radii of 7 Bohr for orbitals away from the defect.

A two-layer spreading code scheme for dual-rate ds-cdma systems

This letter considers multiuser detection in variable-spreading-length multi-rate direct-sequence code-division multiple-access systems. A two-layer spreading (TLS) code scheme is proposed which facilitates the low-complexity adaptive implementation of linear minimum mean-square error multiuser receivers in a dual-rate system. It is demonstrated via large system analysis and simulation that imposing a TLS structure does not incur loss in terms of the output signal-to-interference ratio performance.

Accelerated Stokesian dynamics: Brownian motion

A new Stokesian dynamics (SD) algorithm for Brownian suspensions is presented. The implementation is based on the recently developed accelerated Stokesian dynamics (ASD) simulation method [Sierou and Brady, J. Fluid Mech. 448, 115 (2001)] for non-Brownian particles. As in ASD, the many-body long-range hydrodynamic interactions are computed using fast Fourier transforms, and the resistance matrix is inverted iteratively, in order to keep the computational cost O(N log N). A fast method for computing the Brownian forces acting on the particles is applied by splitting them into near- and far-field contributions to avoid the O(N3) computation of the square root of the full resistance matrix. For the near-field part, representing the forces as a sum of pairwise contributions reduces the cost to O(N); and for the far-field part, a Chebyshev polynomial approximation for the inverse of the square root of the mobility matrix results in an O(N1.25 log N) computational cost. The overall scaling of the method is thus roughly of O(N1.25 log N) and makes possible the simulation of large systems, which are necessary for studying long-time dynamical properties and/or polydispersity effects in colloidal dispersions. In this work the method is applied to study the rheology of concentrated colloidal suspensions, and results are compared with conventional SD. Also, a faster approximate method is presented and its accuracy discussed.

Nonlinear Galerkin methods for the model reduction of nonlinear dynamical systems

Numerical simulations of large nonlinear dynamical systems, especially over long-time intervals, may be computationally very expensive. Model reduction methods have been used in this context for a long time, usually projecting the dynamical system onto a sub-space of its phase space. Nonlinear Galerkin methods try to improve on this by projecting onto a sub-manifold which does not have to be flat. These methods are applied to the finite element model of a wind-turbine, where both the mechanical and the aerodynamical degrees of freedom can be considered for model reduction. For the internal forces (moments, section forces) the nonlinear Galerkin method gives a considerable increase in accuracy for very little computational cost.

Atomic scale computer aided design for novel semiconductor devices

Conventional simulation tools for microelectronic technological processes will be soon obsolete since the scaling-down of semiconductor devices requires atomic scale design. In this context only the concurrent use of different complementary methodologies can satisfy the demands of accurate and efficient modelling. We have applied a series of approaches to a noteworthy case: the B-type doping of Si. The choice of appropriate methodology depends on the peculiar problem we must address. Statics and migration mechanism are studied by quantum mechanical calculation. These calculations validate semiempirical approaches based on atomic particle–particle potential which are applied to the system evolution simulation. These last methodologies are useful when the kinetic evolution occurring during the processes is characterized by rearrangements in different structural identities. Moreover, using these simulations, we can set the parameters ruling the complex dissolution rates in the models which can be applied to the large system simulation.

Ferroelectric Phase Transitions in Nano-Scale Chemically Ordered PbSc 0.5 Nb 0.5 O 3 Using a First-Principles Model Hamiltonian

Effects of chemical order, disorder, short range order, and anti-phase boundaries on phase transitions and dielectric properties of PbSc 1/2 Nb 1/2 O 3 are studied through molecular dynamics simulations of a FP model. Simulations of large systems are required to capture these effects, and we present an efficient reciprocal space method, based on fast Fourier transforms, for calculating long-range interactions and inhomogeneous strain. Calculations for random or partially disordered systems yield significant increases in T = 0 K dielectric response, and broadening of the ferroelectric phase transition. Coupling between random fields caused by chemical disorder and the inhomogeneous strain (acoustic modes) affects the dynamics of soft modes in chemically nano-structured configurations.

An ultra-large-scale simulation framework

Many modern systems involve complex interactions between a large number of diverse entities that constitute these systems. Unfortunately, these large, complex systems frequently defy analysis by conventional analytical methods and their study is generally performed using simulation models. Further aggravating the situation, detailed simulations of large systems will frequently require days, weeks, or even months of computer time and lead to scaled down studies. These scaled down studies may be achieved by the creation of smaller, representative, models and/or by analysis with short duration simulation exercises. Unfortunately, scaled down simulation studies will frequently fail to exhibit behaviors of the full-scale system under study. Consequently, better simulation infrastructure is needed to support the analysis of ultra-large (models containing over 1 million components)-scale models. Simulation support for ultra-large-scale simulation models must be achieved using low-cost commodity computer systems. The expense of custom or high-end parallel systems prevent their widespread use. Consequently, we have developed an Ultra-large-Scale Simulation Framework (USSF). This paper presents the issues involved in the design and development of USSF. Parallel simulation techniques are used to enable optimal time versus resource tradeoffs in USSF. The techniques employed in the framework to reduce and regulate the memory requirements of the simulations are described. The API needed for model development is illustrated. The results obtained from the experiments conducted using various system models with two parallel simulation kernels (comparing a conventional approach with USSF) are also presented.

Determination of the effective dielectric constant from the accurate solution of the Poisson equation.

Constant dielectric (CD) and distance-dependent dielectric (DDD) functions are the most popular and widespread in the Molecular Mechanics simulations of large molecular systems. In this article, we present a simple procedure to derive an effective dielectric constant, epsilon (out,eff), for these two methods based on numerical solutions of the Poisson equation. It was found that because of the very approximate nature of the CD and DDD models there is no universal epsilon (out,eff), which will work equally well for all molecular systems. For example, different MD trajectories of the same molecule can produce different optimal epsilon (out,eff)s. The DDD function was found to yield better agreement with the numerical solutions of the Poisson equation than a CD model does. The reason is that a DDD function gives a better description of the electrostatic interactions at short distances between the atoms. Another interesting finding of this study is that under certain conditions epsilon (out,eff) can take negative values for a system of two atoms at a limited distance range. However, in principle, there is nothing to prevent the epsilon (out,eff) from taking negative values for specific conformations of some molecules.

A large scale molecular dynamics simulation code using the fast multipole algorithm (FMD): performance and application

We present the performance of the fast classical molecular dynamics (MD) code, fast molecular dynamics (FMD), designed for efficient, object-oriented, and scalable large scale simulations, and summarize its application to a liquid crystalline cluster. FMD uses an implementation of the three-dimensional fast multipole method, developed in our group. The fast multipole method offers an efficient way (order O( N)) to handle long range electrostatic interactions, thus, enabling more realistic simulations of large molecular systems. Performance testing was carried out on IBM SP2, SGI Origin 2000, and CRAY T3E massively parallel systems using the MPI massage passing library. The electrostatic forces were tested on models of up to 100,000 randomly placed charges, and on protein and liquid crystalline molecular systems of over 99,000 atoms. Tests on the stability of the method are presented, along with comparisons with direct calculations, the namd2 code, and the physical multipole-based cell-multipole method.

Dynamic Iteration Using Reduced Order Models: A Method for Simulation of Large Scale Modular Systems

We describe a new iterative method, dynamic iteration using reduced order models (DIRM), for simulation of large scale modular systems using reduced order models that preserve the interconnection structure. This method may be compared to the waveform relaxation technique; however, unlike DIRM, waveform relaxation does not take advantage of model reduction techniques. The DIRM method involves simulating in turn each subsystem connected to model reduced versions of the other subsystems. The data from this simulation is then used to update the reduced model for that particular subsystem. We provide analytical results on convergence and accuracy of the DIRM method as well as numerical examples that demonstrate the success of DIRM and verify the analysis.

APPLICATION OF OBSERVER-BASED MONITORING TECHNIQUE IN BELT CONVEYOR SYSTEMS

In this paper an information system is presented, which is developed to meet the requirements on simulation, on-line monitoring, quality management and optimum design of large scale belt conveyor systems. The core of this information system is a mathematical model and an observer. Successful application is also presented to illustrate the proposed approach. Copyright© 2002 IFAC

ReaxFF: A Reactive Force Field for Hydrocarbons

To make practical the molecular dynamics simulation of large scale reactive chemical systems (1000s of atoms), we developed ReaxFF, a force field for reactive systems. ReaxFF uses a general relationship between bond distance and bond order on one hand and between bond order and bond energy on the other hand that leads to proper dissociation of bonds to separated atoms. Other valence terms present in the force field (angle and torsion) are defined in terms of the same bond orders so that all these terms go to zero smoothly as bonds break. In addition, ReaxFF has Coulomb and Morse (van der Waals) potentials to describe nonbond interactions between all atoms (no exclusions). These nonbond interactions are shielded at short range so that the Coulomb and van der Waals interactions become constant as Rij → 0. We report here the ReaxFF for hydrocarbons. The parameters were derived from quantum chemical calculations on bond dissociation and reactions of small molecules plus heat of formation and geometry data for...

An effective pair potential for heavy water

The properties of heavy water are of interest in different disciplines. The simulation of such a substance, particularly in comparison with ordinary water, requires an appropriate interaction potential that allows the simulations of large systems. The potential presented in this work is an efective three-point charge potential type based on the well-known simple point charges/extended model and is named simple point charges/heavy water (SPC/HW). Molecular dynamics simulation done with the SPC/HW potential shows a good agreement with the experimental values for several properties.

Structure and melting of two-dimensional dust crystals

Dust particles in plasmas confined near the boundary between the plasma bulk and the sheath form a two-dimensional system when appropriate conditions are satisfied. To keep dust particles from running away horizontally, the electrostatic potential is usually applied to the electrode surrounding these dusty plasmas and we have finite two-dimensional systems of dust particles. Adopting the Yukawa model for the interaction between dust particles, structures of finite two-dimensional Yukawa systems at low temperatures have been analyzed both by molecular dynamics simulations and variational methods. The effect of the correlation energy between dust particles is shown to play an important role in the formation of the one-body distribution in these systems. Molecular dynamics simulations of large systems typically with 103 to 104 particles have been performed and the behavior of the mean square displacement is obtained for various combinations of characteristic parameters. The results are discussed in relation to the melting transition on the basis of the theoretical analysis on static structures.

Fast simulation for Road Traffic Network

In this paper we present a method to perform fast simulation of large Markovian systems. This method is based on the use of three concepts: Markov chain uniformization, event-driven dynamics, and modularity. An application of urban traffic simulation is presented to illustrate the performance of our approach.

The Development of Conservative Superstep Protocols for Shared Memory Multiprocessor Systems

This paper summarizes our work involving the successive refinements of a conservative superstep protocol. The refined protocols are known as the SST, SLS, and FET protocols. Each of the refinements improves the safetime bound, which in turn reduces the number of supersteps. In general, this helps to reduce the synchronization overhead and thus the execution time. However, a change in the number of supersteps can also introduce load imbalances within supersteps into the simulation. This observation becomes apparent with the FET protocol in particular. The performance of the refined protocols is compared through several semiconductor supply-chain simulation models. The results from the experiments strongly indicate the feasibility of using parallel discrete-event simulation techniques in the simulation of large scale systems such as a supply-chain.

Going through Rough Times: from Non-Equilibrium Surface Growth to Algorithmic Scalability

AbstractEffcient and faithful parallel simulation of large asynchronous systems is a challenging computational problem. It requires using the concept of local simulated times and a synchronization scheme. We study the scalability of massively parallel algorithms for discrete-event simulations which employ conservative synchronization to enforce causality. We do this by looking at the simulated time horizon as a complex evolving system, and we identify its universal characteristics. We find that the time horizon for the conservative parallel discrete-event simulation scheme exhibits Kardar-Parisi-Zhang-like kinetic roughening. This implies that the algorithm is asymptotically scalable in the sense that the average progress rate of the simulation approaches a non-zero constant. It also implies, however, that there are diverging memory requirements associated with such schemes.

Going Through Rough Times: from Non-Equilibrium Surface Growth to Algorithmic Scalability

ABSTRACTEfficient and faithful parallel simulation of large asynchronous systems is a challenging computational problem. It requires using the concept of local simulated times and a synchronization scheme. We study the scalability of massively parallel algorithms for discrete-event simulations which employ conservative synchronization to enforce causality. We do this by looking at the simulated time horizon as a complex evolving system, and we identify its universal characteristics. We find that the time horizon for the conservative parallel discrete-event simulation scheme exhibits Kardar-Parisi-Zhang-like kinetic roughening. This implies that the algorithm is asymptotically scalable in the sense that the average progress rate of the simulation approaches a non-zero constant. It also implies, however, that there are diverging memory requirements associated with such schemes.

A Model-Based Information System for Simulation and Monitoring of Belt Conveyor Systems

In this paper an information system is presented, which is developed to meet the requirements on simulation and on-line monitoring of large scale belt conveyor systems. The core of this information system is a mathematical model and an observer. Successful applications to a number of belt conveyor systems document the efficiency and performance of the information system.

Component Oriented Modelling of Electrical and Mechanical Systems as Required by Component Simulation Software

Mechatronic systems integrate components originating from different technical disciplines. Although most of these engineering domains have capable computer based tools for modelling and simulation there is still no approved conception available adapted for the multi-domain approach. Verifying the common special tools and the used mathematical principles at the present time it seems not to be reasonable to look for an overall formula to solve the problem. With respect to system’s composition it is more favourable to do modelling a component oriented way. This paper presents a module concept that allows to model and simulate even large and complex mechatronic systems. Based on strict modularity and consistent interface definition, components from different disciplines can be combined to form complete systems that can be operated and used for virtual experiments. Both model components and connections are active objects that do essential tasks independently, having more intelligence and autonomy in comparison with conventional simulation tools. On the strength of no concerning other system parts special tools still can be used for modelling single components. This leads to a powerful instrument for fast, efficient and plain modelling and simulation of large mechatronic systems.