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首页> 外文期刊>International Journal of Modern Physics: Conference Series >GPU IMPLEMENTATION OF A VISCOUS FLOW SOLVER ON UNSTRUCTURED GRIDS
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GPU IMPLEMENTATION OF A VISCOUS FLOW SOLVER ON UNSTRUCTURED GRIDS

机译:非结构化网格上粘性流求解器的GPU实现

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Graphics processing units have gained popularities in scientific computing over past several years due to their outstanding parallel computing capability. Computational fluid dynamics applications involve large amounts of calculations, therefore a latest GPU card is preferable of which the peak computing performance and memory bandwidth are much better than a contemporary high-end CPU. We herein focus on the detailed implementation of our GPU targeting Reynolds-averaged Navier-Stokes equations solver based on finite-volume method. The solver employs a vertex-centered scheme on unstructured grids for the sake of being capable of handling complex topologies. Multiple optimizations are carried out to improve the memory accessing performance and kernel utilization. Both steady and unsteady flow simulation cases are carried out using explicit Runge-Kutta scheme. The solver with GPU acceleration in this paper is demonstrated to have competitive advantages over the CPU targeting one.
机译:图形处理单元由于其出色的并行计算能力,在过去的几年中已在科学计算中获得普及。计算流体动力学应用程序涉及大量计算,因此,最好使用最新的GPU卡,其峰值计算性能和内存带宽要比现代高端CPU好得多。本文中,我们重点介绍基于有限体积方法针对GPU的雷诺平均Navier-Stokes方程求解器的GPU的详细实现。为了能够处理复杂的拓扑,求解器在非结构化网格上采用了以顶点为中心的方案。进行了多次优化以提高内存访问性能和内核利用率。稳态和非稳态流动模拟情况均使用显式Runge-Kutta方案进行。本文证明了具有GPU加速功能的求解器比以CPU为目标的求解器具有竞争优势。

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