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GPU-accelerated computing of three-dimensional solar wind background

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Abstract

High-performance computational models are required to make the real-time or faster than real-time numerical prediction of adverse space weather events and their influence on the geospace environment. The main objective in this article is to explore the application of programmable graphic processing units (GPUs) to the numerical space weather modeling for the study of solar wind background that is a crucial part in the numerical space weather modeling. GPU programming is realized for our Solar-Interplanetary-CESE MHD model (SIP-CESE MHD model) by numerically studying the solar corona/interplanetary solar wind. The global solar wind structures are obtained by the established GPU model with the magnetic field synoptic data as input. Meanwhile, the time-dependent solar surface boundary conditions derived from the method of characteristics and the mass flux limit are incorporated to couple the observation and the three-dimensional (3D) MHD model. The simulated evolution of the global structures for two Carrington rotations 2058 and 2062 is compared with solar observations and solar wind measurements from spacecraft near the Earth. The MHD model is also validated by comparison with the standard potential field source surface (PFSS) model. Comparisons show that the MHD results are in good overall agreement with coronal and interplanetary structures, including the size and distribution of coronal holes, the position and shape of the streamer belts, and the transition of the solar wind speeds and magnetic field polarities.

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  1. SIGMA Weather Group, State Key Laboratory for Space Weather, Center for Space Science and Applied Research, Chinese Academy of Sciences, Beijing, 100190, China

    XueShang Feng, DingKun Zhong, ChangQing Xiang & Yao Zhang

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Feng, X., Zhong, D., Xiang, C. et al. GPU-accelerated computing of three-dimensional solar wind background. Sci. China Earth Sci. 56, 1864–1880 (2013). https://doi.org/10.1007/s11430-013-4661-y

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