Student cluster competition 2017, team NTHU: Reproducing vectorization of the tersoff multi-body potential on the Intel Skylake and Nvidia P100 architecture

Abstract

Abstract Markus Hohnerbach et al. recently published a work to optimize the performance of Tersoff potential, which is a computing scheme used in the LAMMPS molecular dynamics (MD) code. The optimization solver was implemented with three different computation precisions, namely single, mixed, and double. As a special activity of the Student Cluster Competition at SC17 conference, we aimed to reproduce their experimental studies of the optimization solvers in terms of accuracy, performance and scalability. We conducted our experiments on a cluster with Intel Xeon Gold 6130 CPUs and Nvidia Tesla P100 GPUs, while the original work was on a cluster with Intel Xeon E5-2650 CPUs and K40 GPUs. Desite of the differences in computing systems, we demonstrate the claims from the original work can be successfully reproduced by showing the solvers with less precision implementation can still achieve high accuracy results, and exhibit good performance speedup and scalability.