Accelerated molecular dynamics force evaluation on graphics processing units for thermal conductivity calculations

TL;DR

This paper presents a GPU-accelerated molecular dynamics code optimized for thermal conductivity calculations, comparing two force evaluation schemes and validating results with solid argon and lead telluride.

Contribution

It introduces a novel block-scheme for force evaluation on GPUs, improving performance for small systems and larger cutoff radii, and applies it to thermal conductivity calculations.

Findings

Block-scheme outperforms thread-scheme for small systems

Performance gain increases with larger cutoff radius

Validated thermal conductivity results for argon and lead telluride

Abstract

In this paper, we develop a highly efficient molecular dynamics code fully implemented on graphics processing units for thermal conductivity calculations using the Green-Kubo formula. We compare two different schemes for force evaluation, a previously used thread-scheme where a single thread is used for one particle and each thread calculates the total force for the corresponding particle, and a new block-scheme where a whole block is used for one particle and each thread in the block calculates one or several pair forces between the particle associated with the given block and its neighbor particle(s) associated with the given thread. For both schemes, two different classical potentials, namely, the Lennard-Jones potential and the rigid-ion potential are implemented. While the thread-scheme performs a little better for relatively large systems, the block-scheme performs much better for relatively small systems. The relative performance of the block-scheme over the thread-scheme also increases with the increasing of the cutoff radius. We validate the implementation by calculating lattice thermal conductivities of solid argon and lead telluride.