Efficient Parallel Algorithm for Statistical Ion Track Simulations in Crystalline Materials

TL;DR

This paper introduces a highly efficient parallel algorithm for statistical Molecular Dynamics simulations of ion tracks in crystalline materials, utilizing a host-client polling scheme to improve scalability and real-time feedback for rare event sampling.

Contribution

The paper develops a novel parallelization strategy for the REED-MD algorithm, enabling scalable and efficient simulations of ion tracks in solids with real-time feedback mechanisms.

Findings

Achieved high parallel efficiency in multiple processor setups.

Demonstrated the algorithm on radiation effects in nuclear oxide fuel.

Validated the method's effectiveness for rare event sampling.

Abstract

We present an efficient parallel algorithm for statistical Molecular Dynamics simulations of ion tracks in solids. The method is based on the Rare Event Enhanced Domain following Molecular Dynamics (REED-MD) algorithm, which has been successfully applied to studies of, e.g., ion implantation into crystalline semiconductor wafers. We discuss the strategies for parallelizing the method, and we settle on a host-client type polling scheme in which a multiple of asynchronous processors are continuously fed to the host, which, in turn, distributes the resulting feed-back information to the clients. This real-time feed-back consists of, e.g., cumulative damage information or statistics updates necessary for the cloning in the rare event algorithm. We finally demonstrate the algorithm for radiation effects in a nuclear oxide fuel, and we show the balanced parallel approach with high parallel efficiency in multiple processor configurations.