Applications of multi-GPU computing in large-scale fully kinetic particle-in-cell simulations of space plasma
Source abstract
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.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Ionosphere and magnetosphere dynamics · Solar and Space Plasma Dynamics · Plasma Diagnostics and Applications
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Earth and Space Science Technology, Hubei Luojia Laboratory, Wuhan University 1 , Wuhan 430072,
NVIDIA 2 , Beijing 100020,
NVIDIA Graphics Pvt. Ltd. 3 , Bangalore 560048,
Funding
National Natural Science Foundation of China
References (44)
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