GPU-accelerated Tersoff potentials for massively parallel Molecular Dynamics simulations

Trung Dac Nguyen*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

18 Scopus citations

Abstract

The Tersoff potential is one of the empirical many-body potentials that has been widely used in simulation studies at atomic scales. Unlike pair-wise potentials, the Tersoff potential involves three-body terms, which require much more arithmetic operations and data dependency. In this contribution, we have implemented the GPU-accelerated version of several variants of the Tersoff potential for LAMMPS, an open-source massively parallel Molecular Dynamics code. Compared to the existing MPI implementation in LAMMPS, the GPU implementation exhibits a better scalability and offers a speedup of 2.2X when run on 1000 compute nodes on the Titan supercomputer. On a single node, the speedup ranges from 2.0 to 8.0 times, depending on the number of atoms per GPU and hardware configurations. The most notable features of our GPU-accelerated version include its design for MPI/accelerator heterogeneous parallelism, its compatibility with other functionalities in LAMMPS, its ability to give deterministic results and to support both NVIDIA CUDA- and OpenCL-enabled accelerators. Our implementation is now part of the GPU package in LAMMPS and accessible for public use.

Original languageEnglish (US)
Pages (from-to)113-122
Number of pages10
JournalComputer Physics Communications
Volume212
DOIs
StatePublished - Mar 1 2017

Keywords

  • GPU acceleration
  • High-performance computing
  • Hybrid MPI/GPU
  • LAMMPS
  • Tersoff

ASJC Scopus subject areas

  • Hardware and Architecture
  • Physics and Astronomy(all)

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