Articles | Volume 8, issue 9
https://doi.org/10.5194/gmd-8-2815-2015
https://doi.org/10.5194/gmd-8-2815-2015
Development and technical paper
 | Highlight paper
 | 
09 Sep 2015
Development and technical paper | Highlight paper |  | 09 Sep 2015

POM.gpu-v1.0: a GPU-based Princeton Ocean Model

S. Xu, X. Huang, L.-Y. Oey, F. Xu, H. Fu, Y. Zhang, and G. Yang

Related authors

Reconstructed global monthly burned area maps from 1901 to 2020
Zhixuan Guo, Wei Li, Philippe Ciais, Stephen Sitch, Guido R. van der Werf, Simon P. K. Bowring, Ana Bastos, Florent Mouillot, Jiaying He, Minxuan Sun, Lei Zhu, Xiaomeng Du, Nan Wang, and Xiaomeng Huang
Earth Syst. Sci. Data, 17, 3599–3618, https://doi.org/10.5194/essd-17-3599-2025,https://doi.org/10.5194/essd-17-3599-2025, 2025
Short summary
Precipitation Nowcasting Based on Convolutional LSTM with Spatio-Temporal Information Transformation Using Multi-Meteorological Factors
Dufu Liu, Feihu Huang, Peng Zheng, Xiaomeng Huang, Xi Wu, Xia Yuan, Jiafeng Zheng, Xiaojie Li, and Jing Hu
EGUsphere, https://doi.org/10.5194/egusphere-2025-2714,https://doi.org/10.5194/egusphere-2025-2714, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
Optimizing output operations in high-resolution climate models through dynamic scheduling
Dong Wang and Xiaomeng Huang
EGUsphere, https://doi.org/10.5194/egusphere-2024-3533,https://doi.org/10.5194/egusphere-2024-3533, 2025
Short summary
LB-SCAM: a learning-based method for efficient large-scale sensitivity analysis and tuning of the Single Column Atmosphere Model (SCAM)
Jiaxu Guo, Juepeng Zheng, Yidan Xu, Haohuan Fu, Wei Xue, Lanning Wang, Lin Gan, Ping Gao, Wubing Wan, Xianwei Wu, Zhitao Zhang, Liang Hu, Gaochao Xu, and Xilong Che
Geosci. Model Dev., 17, 3975–3992, https://doi.org/10.5194/gmd-17-3975-2024,https://doi.org/10.5194/gmd-17-3975-2024, 2024
Short summary
A Deep Learning-Based Consistency Test Approach for Earth System Models on Heterogeneous Many-Core Systems
Yangyang Yu, Shaoqing Zhang, Haohuan Fu, Dexun Chen, Yang Gao, Xiaopei Lin, Zhao Liu, and Xiaojing Lv
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-10,https://doi.org/10.5194/gmd-2024-10, 2024
Preprint withdrawn
Short summary

Related subject area

Climate and Earth system modeling
SASIEv.1: a framework for seasonal and multi-centennial Arctic sea ice emulation
Sian Megan Chilcott, Malte Meinshausen, and Dirk Notz
Geosci. Model Dev., 18, 4965–4982, https://doi.org/10.5194/gmd-18-4965-2025,https://doi.org/10.5194/gmd-18-4965-2025, 2025
Short summary
COSP-RTTOV-1.0: flexible radiation diagnostics to enable new science applications in model evaluation, climate change detection, and satellite mission design
Jonah K. Shaw, Dustin J. Swales, Sergio DeSouza-Machado, David D. Turner, Jennifer E. Kay, and David P. Schneider
Geosci. Model Dev., 18, 4935–4950, https://doi.org/10.5194/gmd-18-4935-2025,https://doi.org/10.5194/gmd-18-4935-2025, 2025
Short summary
Assessing modifications to the Abdul-Razzak and Ghan aerosol activation parameterization (version ARG2000) to improve simulated aerosol–cloud radiative effects in the UK Met Office Unified Model (UM version 13.0)
Pratapaditya Ghosh, Katherine J. Evans, Daniel P. Grosvenor, Hyun-Gyu Kang, Salil Mahajan, Min Xu, Wei Zhang, and Hamish Gordon
Geosci. Model Dev., 18, 4899–4913, https://doi.org/10.5194/gmd-18-4899-2025,https://doi.org/10.5194/gmd-18-4899-2025, 2025
Short summary
Correction of sea surface biases in the NEMO ocean general circulation model using neural networks
Andrea Storto, Sergey Frolov, Laura Slivinski, and Chunxue Yang
Geosci. Model Dev., 18, 4789–4804, https://doi.org/10.5194/gmd-18-4789-2025,https://doi.org/10.5194/gmd-18-4789-2025, 2025
Short summary
Representing lateral groundwater flow from land to river in Earth system models
Chang Liao, L. Ruby Leung, Yilin Fang, Teklu Tesfa, and Robinson Negron-Juarez
Geosci. Model Dev., 18, 4601–4624, https://doi.org/10.5194/gmd-18-4601-2025,https://doi.org/10.5194/gmd-18-4601-2025, 2025
Short summary

Cited articles

Allen, J. S. and Newberger, P. A.: Downwelling Circulation on the Oregon Continental Shelf. Part I: Response to Idealized Forcing, J. Phys. Oceanogr., 26, 2011–2035, https://doi.org/10.1175/1520-0485(1996)026<2011:DCOTOC>2.0.CO;2, 1996.
Berntsen, J. and Oey, L.-Y.: Estimation of the internal pressure gradient in σ-coordinate ocean models: comparison of second-, fourth-, and sixth-order schemes, Ocean Dynam., 60, 317–330, 2010.
Blumberg, A. F. and Mellor, G. L.: Diagnostic and prognostic numerical circulation studies of the South Atlantic Bight, J. Geophys. Res.-Oceans, (1978–2012), 88, 4579–4592, 1983.
Blumberg, A. F. and Mellor, G. L.: A description of a three-dimensional coastal ocean circulation model, Coast. Est. Sci., 4, 1–16, 1987.
Browne, S., Dongarra, J., Garner, N., Ho, G., and Mucci, P.: A portable programming interface for performance evaluation on modern processors, Int. J. High Perf. Comp. Appl., 14, 189–204, 2000.
Download
Short summary
In this paper, we redesign the mpiPOM with GPUs. Specifically, we first convert the model from its original Fortran form to a new CUDA-C version, POM.gpu-v1.0. Then we optimize the code on each of the GPUs, the communications between the GPUs, and the I/O between the GPUs and the CPUs. We show that the performance of the new model on a workstation containing 4 GPUs is comparable to that on a powerful cluster with 408 standard CPU cores, and it reduces the energy consumption by a factor of 6.8.
Share