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Large Scale GPU Accelerated PPMLR-MHD Simulations for Space Weather Forecast
Guo, Xiangyu; Tang, Binbin; Tao, Jian; Huang, Zhaohui; Du, Zhihui; Du, ZH (reprint author), Tsinghua Univ, Dept Comp Sci & Technol, Tsinghua Natl Lab Informat Sci & Technol, Beijing 100084, Peoples R China.
Department空间科学部
Source Publication2016 16TH IEEE/ACM INTERNATIONAL SYMPOSIUM ON CLUSTER, CLOUD AND GRID COMPUTING (CCGRID)
2016
Pages576-581
Language英语
ISSN2376-4414
ISBN978-1-5090-2453-7
AbstractPPMLR-MHD is a new magnetohydrodynamics (MHD) model used to simulate the interactions of the solar wind with the magnetosphere, which has been proved to be the key element of the space weather cause-and-effect chain process from the Sun to Earth. Compared to existing MHD methods, PPMLR-MHD achieves the advantage of high order spatial accuracy and low numerical dissipation. However, the accuracy comes at a cost. On one hand, this method requires more intensive computation. On the other hand, more boundary data is subject to be transferred during the process of simulation. In this work, we present a parallel hybrid solution of the PPMLR-MHD model implemented using the computing capabilities of both CPUs and GPUs. We demonstrate that our optimized implementation alleviates the data transfer overhead by using GPU Direct technology and can scale up to 151 processes and achieve significant performance gains by distributing the workload among the CPUs and GPUs on Titan at Oak Ridge National Laboratory. The performance results show that our implementation is fast enough to carry out highly accurate MHD simulations in real time.
KeywordCuda Space Weather Forecast Ppmlr-mhd Cuda-aware Mpi
Conference Name16th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid)
Conference DateMAY 16-19, 2016
Conference PlaceCartagena, COLOMBIA
Indexed ByEI ; CPCI
Document Type会议论文
Identifierhttp://ir.nssc.ac.cn/handle/122/5577
Collection空间科学部
Corresponding AuthorDu, ZH (reprint author), Tsinghua Univ, Dept Comp Sci & Technol, Tsinghua Natl Lab Informat Sci & Technol, Beijing 100084, Peoples R China.
Recommended Citation
GB/T 7714
Guo, Xiangyu,Tang, Binbin,Tao, Jian,et al. Large Scale GPU Accelerated PPMLR-MHD Simulations for Space Weather Forecast[C]:IEEE,2016:576-581.
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