Implementing Molecular Dynamics on Hybrid High Performance Computers – Particle-Particle Particle-Mesh

W. Michael Brown, Axel Kohlmeyer, Steven J. Plimpton, Arnold N. Tharrington
National Center for Computational Sciences, Oak Ridge National Laboratory, Oak Ridge, Tennessee, USA
Computer Physics Communications, Volume 183, Issue 3, Pages 449-459, 2012


   title={Implementing molecular dynamics on hybrid high performance computers–Particle-particle particle-mesh},

   author={Brown, W.M. and Kohlmeyer, A. and Plimpton, S.J. and Tharrington, A.N.},

   journal={Computer Physics Communications},




Download Download (PDF)   View View   Source Source   Source codes Source codes




The use of accelerators such as graphics processing units (GPUs) has become popular in scientific computing applications due to their low cost, impressive floating-point capabilities, high memory bandwidth, and low electrical power requirements. Hybrid high-performance computers, machines with nodes containing more than one type of floating-point processor (e.g. CPU and GPU), are now becoming more prevalent due to these advantages. In this paper, we present a continuation of previous work implementing algorithms for using accelerators into the LAMMPS molecular dynamics software for distributed memory parallel hybrid machines. In our previous work, we focused on acceleration for short-range models with an approach intended to harness the processing power of both the accelerator and (multi-core) CPUs. To augment the existing implementations, we present an efficient implementation of long-range electrostatic force calculation for molecular dynamics. Specifically, we present an implementation of the particle-particle particle-mesh method based on the work by Harvey and De Fabritiis. We present benchmark results on the Keeneland InfiniBand GPU cluster. We provide a performance comparison of the same kernels compiled with both CUDA and OpenCL. We discuss limitations to parallel efficiency and future directions for improving performance on hybrid or heterogeneous computers.
No votes yet.
Please wait...

* * *

* * *

HGPU group © 2010-2021 hgpu.org

All rights belong to the respective authors

Contact us: