Improving performance of a semi-analytical model for nonlinear water waves

Paprota, Maciej; Sulisz, Wojciech

doi:10.1016/j.jher.2019.01.002

Cited by 4 publications

(1 citation statement)

References 62 publications

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“…In contrast, our trial of GPU speedup for the HOS method in this study only requires NVIDIA GPUs with moderate or high performance, making it a more cost-effective solution for parallel processing. The impressive performance of the GPU speedup in our study was also confirmed by a recent study on nonlinear wave simulations [69]. Furthermore, the relaxation module in our solver consumed less than 5% of the total CPU time in NWS-B and less than 1% of the total CPU time in NWS-CU.…”

Section: Discussionsupporting

confidence: 85%

A Graphic Processing Unit–High-Order Spectral (GPU-HOS) Numerical Wave Tank for the Simulation of Directional Wave Field Evolution over a Long Time

Zhou,

Zhang

2023

JMSE

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Existing numerical models for direct simulations of stochastically directional waves are limited by their computational burden, and only a few of them can be applied to modeling directional waves on account of nonlinear evolutions on large time scales. In response to these drawbacks, this paper proposes a modified rectangular numerical wave tank based on the high-order spectral (HOS) method. Three main arrangements are responsible for the model improvement. Firstly, the relaxation technique is applied on the four sides of the tank for generating and attenuating waves, with an enhancement in the total computational efforts required of less than 5% being achieved. Secondly, for this paper, the HOS method for solving the nonlinear evolution of waves was modified to a GPU-speedup version for the first time, and the speedup increases dramatically (up to 16-fold) when the grid number is O(106). Thirdly, the higher-order Runge–Kutta method with order 8 is adopted for the purpose of suppressing cumulative temporal errors. Furthermore, several numerical results are presented for the validation of the model. With our modified numerical wave tank, the nonlinear evolutions of random directional waves can be efficiently studied over a large time and space scale.

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Section: Discussionsupporting

confidence: 85%