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首页> 外文期刊>Journal of Computational Physics >GPU accelerated simulations of bluff body flows using vortex particle methods
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GPU accelerated simulations of bluff body flows using vortex particle methods

机译：使用涡旋粒子方法进行钝体流的GPU加速仿真

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摘要

We present a GPU accelerated solver for simulations of bluff body flows in 2D using a remeshed vortex particle method and the vorticity formulation of the Brinkman penalization technique to enforce boundary conditions. The efficiency of the method relies on fast and accurate particle-grid interpolations on GPUs for the remeshing of the particles and the computation of the field operators. The GPU implementation uses OpenGL so as to perform efficient particle-grid operations and a CUFFT-based solver for the Poisson equation with unbounded boundary conditions. The accuracy and performance of the GPU simulations and their relative advantages/drawbacks over CPU based computations are reported in simulations of flows past an impulsively started circular cylinder from Reynolds numbers between 40 and 9500. The results indicate up to two orders of magnitude speed up of the GPU implementation over the respective CPU implementations. The accuracy of the GPU computations depends on the Re number of the flow. For Re up to 1000 there is little difference between GPU and CPU calculations but this agreement deteriorates (albeit remaining to within 5% in drag calculations) for higher Re numbers as the single precision of the GPU adversely affects the accuracy of the simulations.
机译：我们提出了一种GPU加速求解器，用于使用修正的涡旋粒子方法和Brinkman罚分技术的涡度公式来强制执行边界条件，从而在2D中模拟钝体流。该方法的效率依赖于GPU上快速，准确的粒子网格插值，以重新划分粒子并计算场算符。 GPU实现使用OpenGL来执行有效的粒子网格操作，并针对具有无限边界条件的泊松方程执行基于CUFFT的求解器。 GPU模拟的准确性和性能，以及相对于基于CPU的计算的相对优势/缺点，是通过40到9500之间的雷诺数通过冲激启动的圆柱流进行的模拟中报告的。该结果表明，速度提高了两个数量级。 GPU实现超过相应的CPU实现。 GPU计算的准确性取决于流的Re数。对于Re高达1000，GPU和CPU计算之间的差异很小，但是对于较高的Re数值，此协议会恶化（尽管在拖动计算中保持在5％以内），因为GPU的单精度会影响模拟的准确性。

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