Parallel optimization of the Crystal-KMC on Tianhe-2

Abstract

The Kinetic Monte Carlo (KMC) is one of the commonly used methods for simulating radiation damage of materials. Our team develops a parallel KMC software named Crystal-KMC, which supports the Embedded Atom Method (EAM) potential energy and utilizes the Message Passing Interface (MPI) technology to simulate the vacancy transition of the Copper (Cu) element under neutron radiation. To make better use of the computing power of modern supercomputers, we develop the parallel efficiency optimization model for the Crystal-KMC on Tianhe-2, to achieve a larger simulation of the damage process of materials under irradiation environment. Firstly, we analyze the performance bottleneck of the Crystal-KMC software and use the MIC offload statement to implement the operation of key modules of the software on the MIC coprocessor. We use OpenMP to develop parallel optimization for the Crystal-KMC, combined with existing MPI inter-process communication optimization, finally achieving hybrid parallel optimization. The experimental results show that in the single-node CPU and MIC collaborative parallel mode, the speedup of the calculation hotspot reaches 30.1, and the speedup of the overall software reaches 7.43.