From Quantity To Quality: Massive Molecular Dynamics Simulation of Nanostructures under Plastic Ddeformation in Desktop and Service Grid Distributed Computing Infrastructure

Abstract

The distributed computing infrastructure (DCI) on the basis of BOINC and EDGeS-bridge technologies for high-performance distributed computing is used for porting the sequential molecular dynamics (MD) application to its parallel version for DCI with Desktop Grids (DGs) and Service Grids (SGs). The actual metrics of the working DG-SG DCI were measured, and the normal distribution of host performances, and signs of log-normal distributions of other characteristics (CPUs, RAM, and HDD per host) were found. The practical feasibility and high efficiency of the MD simulations on the basis of DG-SG DCI were demonstrated during the experiment with the massive MD simulations for the large quantity of aluminum nanocrystals (∼ 10 2 -10 3 ). Statistical analysis (Kolmogorov-Smirnov test, moment analysis, and bootstrapping analysis) of the defect density distribution over the ensemble of nanocrystals had shown that change of plastic deformation mode is followed by the qualitative change of defect density distribution type over ensemble of nanocrystals. Some limitations (fluctuating performance, unpredictable availability of resources, etc.) of the typical DG-SG DCI were outlined, and some advantages (high efficiency, high speedup, and low cost) were demonstrated. Deploying on DG DCI allows to get new scientific quality from the simulated quantity of numerous configurations by harnessing sufficient computational power to undertake MD simulations in a wider range of physical parameters (configurations) in a much shorter timeframe.

Change of scaling and appearance of scale-free size distribution in aggregation kinetics by additive rules

“…One of the examples of such scaling analysis applied for CDFs was demonstrated for statistical analysis of features observed on surfaces of plastically deformed Al single crystals under real-time video monitoring and processing [42], Another example of such scaling and statistical analysis (Kolmogorov-Smirnov test of fitting, moment analysis, and bootstrapping analysis) was proposed for the defect density distribution over the ensemble of nanocrystals. And it had shown that change of plastic deformation mode is followed by the qualitative change of defect density distribution type over ensemble of nanocrystals [43].…”

IMP Science Gateway: from the Portal to the Hub of Virtual Experimental Labs in e‐Science and Multiscale Courses in e‐Learning

“…The complex workflow (Figure ) for this application contains several independent components (LAMMPS package, Pizza.py Toolkit, AtomEye package, debyer, R‐package, and FFMPEG), which can be combined by the modular approach in various sets for the purposes of end users . End users can check the intermediate results after MD simulation by LAMMPS package (tables in the red rectangles in the center of Figure d) and the results converted by Pizza.py Toolkit script package for post‐processing (table in the red rectangle in the bottom of Figure d).…”

IMP Science Gateway: From the Portal to the Hub of Virtual Experimental Labs in Materials Science

“…The complex workflow ( Fig. 2) for this application contains several independent components (LAMMPS package, Pizza.py Toolkit, AtomEye package, debyer, R-package, FFMPEG), which can be combined in various sets for the purposes of the end users [11], [12]. The endusers can check the intermediate results: after MD simulation by LAMMPS package (tables in the red rectangles in the center of Fig.…”