Best Paper Award at PPAM 2022 for MD-Bench
We are pleased to announce that the paper “MD-Bench: A generic proxy-app toolbox for state-of-the-art molecular dynamics algorithms” by Rafael Ravedutti Lucio Machado, Jan Eitzinger, Harald Köstler, and Gerhard Wellein just received the best paper award at PPAM 2022, the 14th International Conference on Parallel Processing and Applied Mathematics, in Gdansk, Poland.
In this paper, Rafael presented MD-Bench (https://github.com/RRZE-HPC/MD-Bench), a proxy-app for short-range molecular dynamics (MD) algorithms. In contrast to other proxy-apps in this domain, MD-Bench includes algorithms from multiple major MD community codes and focuses on a simple and transparent implementation, which makes it well suited for research, teaching, and of course for benchmarking.
The paper described features and benefits of MD-Bench and illustrates its use-cases on three examples: an assembly analysis showing how the compiler-generated code can be improved, an investigation of memory latency contributions in a classical material science MD test case, and a systematic compiler code quality study based on hardware performance counter measurements.
PhD Student Rafael Ravedutti Lucio Machado is a liaison scientist at NHR@FAU and works on performance engineering for classical MD applications.
A preprint of the paper is available at arXiv:2207.13094.