Applications of multi-GPU computing in large-scale fully kinetic particle-in-cell simulations of space plasma

The rapid development of an emerging computing device, the graphical processing unit (GPU), has significantly enhanced our ability to conduct full kinetic particle-in-cell (PIC) simulations in space physics. In this paper, we propose an approach that leverages multiple GPUs to facilitate large-scale PIC simulations. This method can effectively reduce data transmission frequency and latency during the computing process. The data communication between GPU devices is optimized through a combination of Message Passing Interface (MPI)-NVIDIA Collective Communications Library (NCCL) running pattern. Our implementation surpasses the expected linear acceleration, achieving superior computing performance and operational efficiency. The instances of large-scale PIC simulations are presented based on physical models of magnetic reconnection, plasma turbulence, and quasi-perpendicular shock. The importance of large-scale simulations is demonstrated in terms of grid resolution, macroparticles used per cell, and the mass ratio between ions and electrons. The multi-GPU enabled fully kinetic PIC simulation demonstrates its capability to efficiently handle large-scale PIC simulations as a crucial requirement for the study of space plasma physics.

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Publication Details

Journal
AIP Advances
Published
2025-02-01
DOI
https://doi.org/10.1063/5.0251687
Citations
1
Primary Topic
Ionosphere and magnetosphere dynamics
Type
article
Field-Weighted Citation Impact
1.15

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article

Applications of multi-GPU computing in large-scale fully kinetic particle-in-cell simulations of space plasma

Q. Y. Xiong, Honghong Wu, Bharatkumar Sharma, K. Jiang et al.
1 citations
AIP Advances
Ionosphere and magnetosphere dynamics
1.15
article

Applications of multi-GPU computing in large-scale fully kinetic particle-in-cell simulations of space plasma

Q. Y. Xiong, Honghong Wu, Bharatkumar Sharma, K. Jiang, S. Y. Huang, Zhuoning Yuan, Lin Yu, Lvlin Kuang
article en
1 citations

Abstract

The rapid development of an emerging computing device, the graphical processing unit (GPU), has significantly enhanced our ability to conduct full kinetic particle-in-cell (PIC) simulations in space physics. In this paper, we propose an approach that leverages multiple GPUs to facilitate large-scale PIC simulations. This method can effectively reduce data transmission frequency and latency during the computing process. The data communication between GPU devices is optimized through a combination of Message Passing Interface (MPI)-NVIDIA Collective Communications Library (NCCL) running pattern. Our implementation surpasses the expected linear acceleration, achieving superior computing performance and operational efficiency. The instances of large-scale PIC simulations are presented based on physical models of magnetic reconnection, plasma turbulence, and quasi-perpendicular shock. The importance of large-scale simulations is demonstrated in terms of grid resolution, macroparticles used per cell, and the mass ratio between ions and electrons. The multi-GPU enabled fully kinetic PIC simulation demonstrates its capability to efficiently handle large-scale PIC simulations as a crucial requirement for the study of space plasma physics.

AIP AdvancesVol. 15(2)
Nvidia (United Kingdom) (GB), Wuhan University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 22%
Ionosphere and magnetosphere dynamics
1.15
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