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
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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

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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.
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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.
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