MD-Bench: A performance-focused prototyping harness for state-of-the-art short-range molecular dynamics algorithms

RRL Machado and J Eitzinger and J Laukemann and G Hager and H Koestler and G Wellein, FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 149, 25-38 (2023).

DOI: 10.1016/j.future.2023.06.023

Molecular dynamics (MD) simulations provide considerable benefits for the investigation and exper-imentation of systems at atomic level. Their usage is widespread into several research fields, but their system size and timescale are crucially limited by the available computing power. Performance engineering of MD kernels is therefore critical to understand their bottlenecks and investigate possible improvements. For that reason, we developed MD-Bench, a performance-focused prototyping harness for short-range MD kernels that implements state-of-the-art algorithms from multiple production applications such as LAMMPS and GROMACS. The MD-Bench source code is simple, understandable, and extensible, and therefore well suited for benchmarking, teaching, and researching MD algorithms. In this paper we introduce MD-Bench, describe its design, structure, and implemented algorithms. Finally, we show five use-cases of MD-Bench and describe how these are useful to gain a deeper understanding of the performance of MD kernels.& COPY; 2023 Elsevier B.V. All rights reserved.

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