When traditional Weakly Compressible Smoothed Particle Hydrodynamics (WCSPH) model is used to simulate free surface flow with large Reynolds number, the instability of numerical calculation due to high random pressure oscillations will be resulted, while accurate pressure field is of vital significance for simulating violent fluid-structure interactions. Riemann-based SPH and Delta-SPH are widely used to solve this problem. In this paper, to enhance computational efficiency, the SPH method is implemented on the General Processing Unit (GPU) platform through Compute Unified Device Architecture (CUDA). The parallelized SPH programs including standard SPH method, Riemann-based SPH and Delta-SPH are verified by a dam break model with large Reynolds number and violent deformation of free surface. The results show that all SPH methods can vividly reflect the whole process of splashing, rolling and backward jet flow; both the Riemann-based SPH and the Delta-SPH are effective in alleviating the problem of inhomogeneous pressure distribution in the simulation process; Riemann-based SPH has better stability even with relatively large particle spacing, and it has higher accuracy in simulating impact pressure. When the number of particles reaches 100,000, compared with the single-thread Central Processing Unit (CPU) implementation, the speedups obtained with NVIDIA Titan V with high computing cores and Quadro K2200 with low computing cores are thousands and hundreds, respectively.
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