Defect Aggregation in Materials Science

Kinetics of Defect Aggregation in Materials Science Simulated in Desktop Grid Computing Environment Installed in Ordinary Material Science Lab


Aggregation processes are investigated in many branches of science: defect aggregation in materials science, population dynamics in biology, city growth and evolution in sociology. The typical simulation of crystal defect aggregation by our application SLinCA (Scaling Laws in Cluster Aggregation) takes several days and weeks on a single modern CPU, depending on the number of Monte Carlo steps (MCS). However, thousands of scenarios have to be simulated with different initial configurations to get statistically reliable results. Porting to distributed computing infrastructure (DCI) and parallel execution can reduce waiting time and scale up simulated systems to the desirable realistic values.Deploying this application on a Grid computing infrastructure, utilising hundreds of machines at the same time, allows harnessing sufficient computational power to undertake the simulations on a larger scale and in a much shorter timeframe. Running the simulations and analysing the results on the Grid provides the excessive computational power required

Yuri Gordienko, Institut de Physique du Metal – Kiev – Ukraine