Gpu-Accelerated Computations For Supersonic Flow Modeling On Hybrid Grids

2020 5TH INTERNATIONAL CONFERENCE ON MECHANICAL, CONTROL AND COMPUTER ENGINEERING (ICMCCE 2020)(2020)

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摘要
With its strong floating-point operation capability and high memory bandwidth in data parallelism, the graphics processing unit (GPU) has been widely used in general-purpose computing. GPU-based computations have been extensively applied in the field of computational fluid dynamics (CFD). This paper aims to design an extremely efficient double-precision GPU-accelerated parallel algorithm for supersonic flow computations on hybrid grids. Compute unified device architecture (CUDA) is used as a general-purpose parallel computing platform and programming model to perform parallel computing codes on GPUs. The cell-centered finite volume method based on unstructured grids is used in the spatial discretization of governing equations, whereas the three-stage explicit Runge-Kutta scheme with second-order accuracy is used for temporal discretization. The turbulence is solved by using the K-omega SST two-equation model. Three test cases are studied to validate the computational accuracy of the proposed algorithm. The numerical results agree well with the experiment data, thereby suggesting that the GPU-accelerated parallel algorithm has good accuracy.
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关键词
graphics processing unit, compute unified device architecture, supersonic flow, hybrid grids, parallel algorithm
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