A Multiscale Formulation for Reducing Computation Time in Atomistic Simulations

2018 ◽  
Vol 13 (5) ◽  
Author(s):  
Ashley Guy ◽  
Alan Bowling
Keyword(s):  
Computation Time ◽  
Atomistic Simulations ◽  
Integration Time ◽  
Temperature Constraint ◽  
High Frequency Vibrations ◽  
Multiscale Problem ◽  
Dynamics Simulations ◽  
Time Required ◽  
Computational Resources ◽  
The Continuum

Molecular dynamics simulations require significant computational resources to generate modest time evolutions. Large active forces lead to large accelerations, requiring subfemtosecond integration time steps to capture the resultant high-frequency vibrations. It is often necessary to combine these fast dynamics with larger scale phenomena, creating a multiscale problem. A multiscale method has been previously shown to greatly reduce the time required to simulate systems in the continuum regime. A new multiscale formulation is proposed to extend the continuum formulation to the atomistic scale. A canonical ensemble model is defined using a modified Nóse–Hoover thermostat to maintain the constant temperature constraint. Results show a significant reduction in computation time mediated by larger allowable integration time steps.

An Adaptive Multiscaling Approach for Reducing Computation Time in Simulations of Articulated Biopolymers

2019 ◽  
Vol 14 (5) ◽  
Author(s):  
Ashley Guy ◽  
Alan Bowling
Keyword(s):  
Computational Cost ◽  
Time History ◽  
Computation Time ◽  
Coarse Graining ◽  
Integration Time ◽  
Dynamic Simulations ◽  
Equivalent Time ◽  
Time Histories ◽  
Time Required ◽  
Computational Resources

Microscale dynamic simulations can require significant computational resources to generate desired time evolutions. Microscale phenomena are often driven by even smaller scale dynamics, requiring multiscale system definitions to combine these effects. At the smallest scale, large active forces lead to large resultant accelerations, requiring small integration time steps to fully capture the motion and dictating the integration time for the entire model. Multiscale modeling techniques aim to reduce this computational cost, often by separating the system into subsystems or coarse graining to simplify calculations. A multiscale method has been previously shown to greatly reduce the time required to simulate systems in the continuum regime while generating equivalent time histories. This method identifies a portion of the active and dissipative forces that cancel and contribute little to the overall motion. The forces are then scaled to eliminate these noncontributing portions. This work extends that method to include an adaptive scaling method for forces that have large changes in magnitude across the time history. Results show that the adaptive formulation generates time histories similar to those of the unscaled truth model. Computation time reduction is consistent with the existing method.

scholarly journals Control of Discrete Event Systems by Means of Discrete Optimization and Disjunctive Colored PNs: Application to Manufacturing Facilities

2014 ◽  
Vol 2014 ◽  
pp. 1-16 ◽  
Author(s):  
Juan-Ignacio Latorre-Biel ◽  
Emilio Jiménez-Macías ◽  
Mercedes Pérez de la Parte ◽  
Julio Blanco-Fernández ◽  
Eduardo Martínez-Cámara
Keyword(s):  
Discrete Event ◽  
Optimal Solution ◽  
Solution Space ◽  
Discrete Systems ◽  
Discrete Control ◽  
Classic Approach ◽  
Event Dynamic ◽  
Time Required ◽  
Computational Resources ◽  
Control Methodology

Artificial intelligence methodologies, as the core of discrete control and decision support systems, have been extensively applied in the industrial production sector. The resulting tools produce excellent results in certain cases; however, the NP-hard nature of many discrete control or decision making problems in the manufacturing area may require unaffordable computational resources, constrained by the limited available time required to obtain a solution. With the purpose of improving the efficiency of a control methodology for discrete systems, based on a simulation-based optimization and the Petri net (PN) model of the real discrete event dynamic system (DEDS), this paper presents a strategy, where a transformation applied to the model allows removing the redundant information to obtain a smaller model containing the same useful information. As a result, faster discrete optimizations can be implemented. This methodology is based on the use of a formalism belonging to the paradigm of the PN for describing DEDS, the disjunctive colored PN. Furthermore, the metaheuristic of genetic algorithms is applied to the search of the best solutions in the solution space. As an illustration of the methodology proposal, its performance is compared with the classic approach on a case study, obtaining faster the optimal solution.

Dislocation Generation and Crack Propagation in Metals Examined in Molecular Dynamics Simulations

1992 ◽  
Vol 278 ◽  
Author(s):  
J. A. Rifkin ◽  
C. S. Becquart ◽  
D. Kim ◽  
P. C. Clapp
Keyword(s):  
Crack Propagation ◽  
Atomistic Simulations ◽  
Many Body ◽  
Dislocation Generation ◽  
Embedded Atom ◽  
Stress Levels ◽  
Different Temperatures ◽  
The Many ◽  
Dynamics Simulations ◽  
Many Body Interactions

AbstractWe have carried out a series of atomistic simulations on arrays of about 10,000 atoms containing an atomically sharp crack and subjected to increasing stress levels. The ordered stoichiometric alloys B2 NiAl, B2 RuAl and A15 Nb3AI have been studied at different temperatures and stress levels, as well as the elements Al, Ni, Nb and Ru. The many body interactions used in the simulations were derived semi-empirically, using techniques related to the Embedded Atom Method. Trends in dislocation generation rates and crack propagation modes will be discussed and compared to experimental indications where possible, and some of the simulations will be demonstrated in the form of computer movies.

scholarly journals Data (Video) Encryption in Mobile devices

2017 ◽  
Vol 2 (3) ◽  
pp. 32-39
Author(s):  
Aya Khalid Naji ◽  
Saad Najim Alsaad
Keyword(s):  
Elliptic Curve ◽  
Mobile Devices ◽  
Mobile Device ◽  
Elliptic Curve Cryptography ◽  
Computation Time ◽  
Video Encryption ◽  
Android Platform ◽  
Time Required ◽  
New Generation

In the development of 3G devices, all elements of multimedia (text, image, audio, and video) are becoming crucial choice for communication. The secured system in 3G devices has become an issue of importance, on which lot of research is going on. The traditional cryptosystem like DES, AES, and RSA do not able to meet with the properties of the new generation of digital mobile devices. This paper presents an implementation of video protection of fully encrypted using Elliptic Curve   Cryptography (ECC) on a mobile device. The Android platform is used for this purpose.  The results refer that the two important criteria of video mobile encryption: the short computation time required and high confidentially are provided.

Molecular Dynamics Simulations of Interfacial Heat and Mass Transfer at Nanostructured Surface

2007 ◽  
Author(s):  
Gyoko Nagayama ◽  
Masako Kawagoe ◽  
Takaharu Tsuruta
Keyword(s):  
Heat Transfer ◽  
Molecular Dynamics ◽  
Boundary Condition ◽  
Thermal Resistance ◽  
Hydrodynamic Resistance ◽  
Hydrophilic Surface ◽  
Dynamics Simulations ◽  
Solid Liquid Interface ◽  
Solid Liquid ◽  
The Continuum

The nanoscale heat and mass transport phenomena play important roles on the applications of nanotechnologies with great attention to its differences from the continuum mechanics. In this paper, the breakdown of the continuum assumption for nanoscale flows has been verified based on the molecular dynamics simulations and the heat transfer mechanism at the nanostructured solid-liquid interface in the nanochannels is studied from the microscopic point of view. Simple Lennard-Jones (LJ) fluids are simulated for thermal energy transfer in a nanochannel using nonequilibrium molecular dynamics techniques. Multi-layers of platinum atoms are utilized to simulate the solid walls with arranged nanostructures and argon atoms are employed as the LJ fluid. The results show that the interface structure (i.e. the solid-like structure formed by the adsorption layers of liquid molecules) between solid and liquid are affected by the nanostructures. It is found that the hydrodynamic resistance and thermal resistance dependents on the surface wettability and for the nanoscale heat and fluid flows, the interface resistance cannot be neglected but can be reduced by the nanostructures. For the hydrodynamic boundary condition at the solid-liquid interface, the no-slip boundary condition holds good at the super-hydrophilic surface with large hydrodynamic resistance. However, apparent slip is observed at the low hydrodynamic resistance surface when the driving force overcomes the interfacial resistance. For the thermal boundary condition, it is found that the thermal resistance at the interface depends on the interface wettability and the hydrophilic surface has lower thermal resistance than that of the hydrophobic surfaces. The interface thermal resistance decreases at the nanostructed surface and significant heat transfer enhancement has been achieved at the hydrophilic nanostructured surfaces. Although the surface with nanostrutures has larger surface area than the flat surface, the rate of heat flux increase caused by the nanostructures is remarkable.

Dynamic Collision Detection Using Space Partitioning

1990 ◽  
Author(s):  
M. A. Ganter ◽  
B. P. Isarankura
Keyword(s):  
Collision Detection ◽  
Computation Time ◽  
Local Region ◽  
Detection Time ◽  
Space Partitioning ◽  
Worst Case ◽  
Simulated Environment ◽  
Time Required ◽  
Six Degree Of Freedom ◽  
Partitioning Technique

Abstract A technique termed space partitioning is employed which dramatically reduces the computation time required to detect dynamic collision during computer simulation. The simulated environment is composed of two nonconvex polyhedra traversing two general six degree of freedom trajectories. This space partitioning technique reduces collision detection time by subdividing the space containing a given object into a set of linear partitions. Using these partitions, all testing can be confined to the local region of overlap between the two objects. Further, all entities contained in the partitions inside the region of overlap are ordered based on their respective minimums and maximums to further reduce testing. Experimental results indicate a worst-case collision detection time for two one thousand faced objects is approximately three seconds per trajectory step.

Damage-fragmentation transition: Size effect and scaling behavior for impact fragmentation of slender projectiles

2016 ◽  
Vol 27 (2) ◽  
pp. 201-217 ◽  
Author(s):  
Sreten Mastilovic
Keyword(s):  
Size Effect ◽  
Finite Size ◽  
Rigid Wall ◽  
Atomistic Simulations ◽  
Generic Model ◽  
Scaling Analysis ◽  
Impact Fragmentation ◽  
Indispensable Tool ◽  
Dynamics Simulations ◽  
Different Diameters

The focus of the present article is on the size effect of a transition region from the damaged to the fragmented phase in impact-induced breakup of a slender projectile. Molecular dynamics simulations of the classic ballistic Taylor test are performed with a simple generic model to explore an extended low-energy range. In the simulation setup, flat-ended, monocrystalline, nanoscale projectiles, with a fixed aspect ratio but 10 different diameters, collide perpendicularly with a rough rigid wall. With gradually increasing impact energy, a non-negligible projectile disintegration eventually takes place and is identified with the damage-fragmentation phase transition. These atomistic simulations offer an indispensable tool to gain an insight into damage evolution in the neighborhood of the damage-fragmentation transition resulting in the occurrence of fragmentation at the critical point. A finite size scaling analysis of the average fragment mass is carried out to determine critical exponents and dependence of the critical striking velocity upon the slender projectile’s diameter.

A simplified approach for thermal elastohydrodynamic lubrication analysis of circular contacts using realistic lubricant properties

2018 ◽  
Vol 232 (12) ◽  
pp. 1618-1632
Author(s):  
Puneet Katyal ◽  
Punit Kumar
Keyword(s):  
Mathematical Models ◽  
Point Contact ◽  
Elastohydrodynamic Lubrication ◽  
Computation Time ◽  
Fluid Temperature ◽  
Simplified Approach ◽  
Lubrication Film ◽  
Isothermal Case ◽  
Lubrication Characteristics ◽  
Time Required

Thermal effect in elastohydrodynamic lubrication has been the subject of extensive research for several decades. The focus of this study was primarily on the development of an efficient numerical scheme to deal with the computational challenges involved in the solution of thermal elastohydrodynamic lubrication model; however, some important aspects related to the accurate description of lubricant properties such as viscosity, rheology, and thermal conductivity in elastohydrodynamic lubrication point contact analysis remain largely neglected. A few studies available in this regard are based upon highly complex mathematical models difficult to formulate and execute. The end-users may not have the specialized skill, knowledge, and time required for the development of computational codes pertaining to these models. Therefore, this paper offers a very simple approach to determine the distribution of mean fluid temperature within an elastohydrodynamic lubrication film. While it is an approximate method, it yields reasonably accurate results with only a little increase in computation time with respect to the isothermal case. Moreover, it can be added as a small module to any existing isothermal algorithm. Using this simplified thermal elastohydrodynamic lubrication model for point contacts, this work sheds some light on the importance of accurate characterization of the lubricant properties and demonstrates that the computed thermal elastohydrodynamic lubrication characteristics are highly sensitive to lubricant properties. It also emphasizes the use of appropriate mathematical models with experimentally determined parameters to account for the correct lubricant behavior.

scholarly journals SparkRA: Enabling Big Data Scalability for the GATK RNA-seq Pipeline with Apache Spark

Genes ◽  
2020 ◽  
Vol 11 (1) ◽  
pp. 53
Author(s):  
Zaid Al-Ars ◽  
Saiyi Wang ◽  
Hamid Mushtaq
Keyword(s):  
Low Cost ◽  
Computing Time ◽  
Scale Up ◽  
Variant Calling ◽  
Computation Time ◽  
Apache Spark ◽  
Rna Seq ◽  
Single Node ◽  
Practical Applications ◽  
Computational Resources

The rapid proliferation of low-cost RNA-seq data has resulted in a growing interest in RNA analysis techniques for various applications, ranging from identifying genotype–phenotype relationships to validating discoveries of other analysis results. However, many practical applications in this field are limited by the available computational resources and associated long computing time needed to perform the analysis. GATK has a popular best practices pipeline specifically designed for variant calling RNA-seq analysis. Some tools in this pipeline are not optimized to scale the analysis to multiple processors or compute nodes efficiently, thereby limiting their ability to process large datasets. In this paper, we present SparkRA, an Apache Spark based pipeline to efficiently scale up the GATK RNA-seq variant calling pipeline on multiple cores in one node or in a large cluster. On a single node with 20 hyper-threaded cores, the original pipeline runs for more than 5 h to process a dataset of 32 GB. In contrast, SparkRA is able to reduce the overall computation time of the pipeline on the same single node by about 4×, reducing the computation time down to 1.3 h. On a cluster with 16 nodes (each with eight single-threaded cores), SparkRA is able to further reduce this computation time by 7.7× compared to a single node. Compared to other scalable state-of-the-art solutions, SparkRA is 1.2× faster while achieving the same accuracy of the results.

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