Abstract
Molecular simulations and molecular dynamics in particular are among the most performance-demanding computational methods. As the scale of simulations increases, the task of processing the simulation results becomes a computationally-hungry problem as well. The usual approach to build easy-to-use post-processing tools is based on providing an interface to a high-performance library called from a scripting language such as Python. We overview the advantages of using Julia programming language for building such tools, due to its easy surface syntax close to that of scripting languages and JIT compilation enabling high runtime performance. Then, we overview the package MDProcessing.jl written in Julia, regarding its customizability, abstractions for common processing workflows and performance characteristics.
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The article was prepared within the framework of the HSE University Basic Research Program. The research was supported in part through computational resources of HPC facilities at HSE University
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Pisarev, V., Panov, M. (2023). MDProcessing.jl: Julia Programming Language Application for Molecular Dynamics Trajectory Processing. In: Voevodin, V., Sobolev, S., Yakobovskiy, M., Shagaliev, R. (eds) Supercomputing. RuSCDays 2023. Lecture Notes in Computer Science, vol 14389. Springer, Cham. https://doi.org/10.1007/978-3-031-49435-2_15
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