Parallelizing discrete dislocation dynamics simulations on multi-core systems

Materials science simulations are among the leading applications for scientific supercomputing. Discrete dislocation dynamics (DDD) is a numerical tool used to model the plastic behavior of crystalline materials using the elastic theory of dislocations. DDD simulations require very long running times to produce meaningful scientific results. This paper presents early experiences and results on improving the running time of Micromegas, an application code for three-dimensional DDD simulations. We used open source profiling and tracing tools to analyze the behavior and performance, as well as to identify the performance bottlenecks of Micromegas. The major performance bottleneck of Micromegas, amounts to ∼68% of the total sequential run time and is parallelized using OpenMP. Evaluation and validation tests conducted on a Nehalem quad-core processor show ∼50% improvement in the simulation time for 3-D DDD over 100,000 time steps. The correctness of the scientific data produced by the parallel Micromegas are successfully validated against those of the serial version