Abstract
Proxy-apps, or mini-apps, are simple self-contained benchmark codes with performance-relevant kernels extracted from real applications. Initially used to facilitate software-hardware co-design, they are a crucial ingredient for serious performance engineering, especially when dealing with large-scale production codes. MD-Bench is a new proxy-app in the area of classical short-range molecular dynamics. In contrast to existing proxy-apps in MD (e.g. miniMD and coMD) it does not resemble a single application code, but implements state-of-the art algorithms from multiple applications (currently LAMMPS and GROMACS). The MD-Bench source code is understandable, extensible and suited for teaching, benchmarking and researching MD algorithms. Primary design goals are transparency and simplicity, a developer is able to tinker with the source code down to the assembly level. This paper introduces MD-Bench, explains its design and structure, covers implemented optimization variants, and illustrates its usage on three examples.
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MD-Bench is open source and available under LGPL3 License.
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Acknowledgements
The authors gratefully acknowledge the scientific support and HPC resources provided by the Erlangen National High Performance Computing Center (NHR@FAU) of the Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU). NHR funding is provided by federal and Bavarian state authorities. NHR@FAU hardware is partially funded by the German Research Foundation (DFG) - 440719683.
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Ravedutti Lucio Machado, R., Eitzinger, J., Köstler, H., Wellein, G. (2023). MD-Bench: A Generic Proxy-App Toolbox for State-of-the-Art Molecular Dynamics Algorithms. In: Wyrzykowski, R., Dongarra, J., Deelman, E., Karczewski, K. (eds) Parallel Processing and Applied Mathematics. PPAM 2022. Lecture Notes in Computer Science, vol 13826. Springer, Cham. https://doi.org/10.1007/978-3-031-30442-2_24
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