OpenDust: A fast GPU-accelerated code for the calculation of forces acting on microparticles in a plasma flow

We present the first open-source, GPU-based code for complex plasmas. The code, OpenDust, pursues to provide researchers, both experimenters and theorists, a user-friendly and high-performance tool for self-consistent calculation forces, acting on microparticles, and microparticles' charges in...

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Veröffentlicht in:Computer physics communications 2023-07, Vol.288, p.108746, Article 108746
Hauptverfasser: Kolotinskii, D., Timofeev, A.
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Sprache:eng
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Zusammenfassung:We present the first open-source, GPU-based code for complex plasmas. The code, OpenDust, pursues to provide researchers, both experimenters and theorists, a user-friendly and high-performance tool for self-consistent calculation forces, acting on microparticles, and microparticles' charges in a plasma flow. OpenDust performance originates from a highly-optimized Cuda back-end and performs self-consistent calculations of plasma flow around microparticles in seconds. This code outperforms all available codes for self-consistent complex plasma simulation. Moreover, OpenDust can also be used for the simulation of larger systems of dust microparticles, which was previously unavailable. OpenDust interface is written in Python, which provides ease-of-use and simple installation from the Conda repository. Program Title: OpenDust CPC Library link to program files:https://doi.org/10.17632/bs7rthk29w.1 Developer's repository link:https://github.com/kolotinsky1998/opendust Code Ocean capsule:https://codeocean.com/capsule/2557151 Licensing provisions: MIT Programming language: Python Nature of problem: GPU cards can significantly speedup self-consistent calculations of forces, acting on microparticles in a plasma flow. However, the available codes are CPU-based, or not provided as a package that can also be easily used. Therefore, researchers need to spend much time writing their own codes or use less effective ones. Solution method: Development of a highly-optimized GPU-accelerated library for self-consistent simulations of streaming plasma around microparticles. The functionality of the library is available through a Python interface, which makes it easy to use.
ISSN:0010-4655
1879-2944
DOI:10.1016/j.cpc.2023.108746