GPU acceleration for general conservation equations and its application to several engineering problems

Kuo, Fang-An; Smith, Matthew R.; Hsieh, Chih‐Wei; Chou, Chau Yi; Wu, Jingwei

doi:10.1016/j.compfluid.2010.10.007

Cited by 28 publications

(13 citation statements)

References 3 publications

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“…There are numerous work on applying GPU computing for computational fluid dynamics. Here, we only listed some work related to shallow flow models . Kuo et al presented application of the split HLL scheme for both the Euler and shallow water equations to Tesla C1060 GPU (first generation general purpose GPU) using CUDA and reported over 67 times speedup over an Intel Xeon X5472 CPU core (3.0 GHz).…”

Section: Introductionmentioning

confidence: 99%

Solving the Savage–Hutter equations for granular avalanche flows with a second‐order Godunov type method on GPU

Zhai

Liu

et al. 2014

Numerical Methods in Fluids

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SUMMARYIn this article, we apply Davis's second-order predictor-corrector Godunov type method to numerical solution of the Savage-Hutter equations for modeling granular avalanche flows. The method uses monotone upstream-centered schemes for conservation laws (MUSCL) reconstruction for conservative variables and Harten-Lax-van Leer contact (HLLC) scheme for numerical fluxes. Static resistance conditions and stopping criteria are incorporated into the algorithm. The computation is implemented on graphics processing unit (GPU) by using compute unified device architecture programming model. A practice of allocating memory for two-dimensional array in GPU is given and computational efficiency of two-dimensional memory allocation is compared with one-dimensional memory allocation. The effectiveness of the present simulation model is verified through several typical numerical examples. Numerical tests show that significant speedups of the GPU program over the CPU serial version can be obtained, and Davis's method in conjunction with MUSCL and HLLC schemes is accurate and robust for simulating granular avalanche flows with shock waves. As an application example, a case with a teardrop-shaped hydraulic jump in Johnson and Gray's granular jet experiment is reproduced by using specific friction coefficients given in the literature.

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Section: Introductionmentioning

confidence: 99%

Solving the Savage–Hutter equations for granular avalanche flows with a second‐order Godunov type method on GPU

Zhai

Liu

et al. 2014

Numerical Methods in Fluids

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“…computational fluid dynamics (CFD), This is an author-formatted preprint of an article accepted for publication in the International Journal of Offshore and Polar Engineering. The version of record will be available at http://www.isope.org/publications/journallist.htm magneto-hydrodynamics, and gas dynamics (Wang et al, 2010;Kuo et al, 2011;Rossinelli et al, 2011;Schive et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

Computationally Efficient Tsunami Modelling on Graphics Processing Units (GPU)

Amouzgar¹,

Liang²,

Clarke³

et al. 2017

Preprint

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Tsunamis generated by earthquakes commonly propagate as long waves in the deep ocean and develop into sharp-fronted surges moving rapidly towards the coast in shallow water, which may be effectively simulated by hydrodynamic models solving the nonlinear shallow water equations (SWEs). However, most of the existing tsunami models suffer from long simulation time for large-scale real-world applications. In this work, a graphics processing unit (GPU) accelerated finite volume shock-capturing hydrodynamic model is presented for computationally efficient tsunami simulations. The improved performance of the GPU-accelerated tsunami model is demonstrated through a laboratory benchmark test and a field-scale simulation.

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“…Parallelization based on GPUs is attracting a lot of attention (over conventional multi-cpu parallelization) because of its favourable cost to performance ratio. There are many CFD applications both in compressible and incompressible flows, which makes use of GPU computing [22][23][24][25][26]. It must be noted that [26] is a 2D solver.…”

Section: Introductionmentioning

confidence: 99%

“…There are many CFD applications both in compressible and incompressible flows, which makes use of GPU computing [22][23][24][25][26]. It must be noted that [26] is a 2D solver. [27], Kelly [28] have applied GPU computing in their own style to study multiphase flows.…”

Section: Introductionmentioning

confidence: 99%