Molecular Dynamics is an important tool for computational biologists, chemists, and materials scientists, consuming a sizable amount of supercomputing resources. Many of the investigated systems contain charged particles, which can only be simulated accurately using a long-range solver, such as PPPM. We extend the popular LAMMPS molecular dynamics code with an implementation of PPPM particularly suitable for the second generation Intel Xeon Phi. Our main target is the optimization of computational kernels by means of vectorization, and we observe speedups in these kernels of up to 12x. These improvements carry over to LAMMPS users, with overall speedups ranging between 2-3x, without requiring users to retune input parameters. Furthermore, our optimizations make it easier for users to determine optimal input parameters for attaining top performance.
@article{arxiv.1702.04250,
title = {LAMMPS' PPPM Long-Range Solver for the Second Generation Xeon Phi},
author = {William McDoniel and Markus Höhnerbach and Rodrigo Canales and Ahmed E. Ismail and Paolo Bientinesi},
journal= {arXiv preprint arXiv:1702.04250},
year = {2017}
}
Comments
18 pages, 8 figures, submitted to ISC High Performance 2017