Accelerating molecular dynamics simulations with population annealing

TL;DR

This paper adapts population annealing, a Monte Carlo method, to molecular dynamics, demonstrating significant acceleration and scalability on supercomputers for peptide folding simulations.

Contribution

It introduces population annealing to molecular dynamics, enabling nearly unlimited parallelization and efficient use of supercomputing resources.

Findings

Comparable performance to parallel tempering

Scales efficiently to many processors

Enables large-scale, accelerated molecular simulations

Abstract

Population annealing is a powerful tool for large-scale Monte Carlo simulations. We adapt this method to molecular dynamics simulations and demonstrate its excellent accelerating effect by simulating the folding of a short peptide commonly used to gauge the performance of algorithms. The method is compared to the well established parallel tempering approach and is found to yield similar performance for the same computational resources. In contrast to other methods, however, population annealing scales to a nearly arbitrary number of parallel processors and it is thus a unique tool that enables molecular dynamics to tap into the massively parallel computing power available in supercomputers that is so much needed for a range of difficult computational problems.