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Molecular dynamics (MD) simulations provide considerable benefits for theinvestigation and experimentation of systems at atomic level. Their usage iswidespread into several research fields, but their system size and timescaleare also crucially limited by the computing power they can make use of.Performance engineering of MD kernels is therefore important to understandtheir bottlenecks and point out possible improvements. For that reason, wedeveloped MD-Bench, a proxy-app for short-range MD kernels that implementsstate-of-the-art algorithms from multiple production applications such asLAMMPS and GROMACS. MD-Bench is intended to have simpler, understandable andextensible source code, as well as to be transparent and suitable for teaching,benchmarking and researching MD algorithms. In this paper we introduceMD-Bench, describe its design and structure and implemented algorithms.Finally, we show five usage examples of MD-Bench and describe how these areuseful to have a deeper understanding of MD kernels from a performance point ofview, also exposing some interesting performance insights.

MD-Bench: Engineering the in-core performance of short-range molecular dynamics kernels from state-of-the-art simulation packages