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Numerical Solutions of Heat and Mass Transfer in Capillary Porous Media Using Programmable Graphics Hardware

机译:可编程图形硬件在毛细管多孔介质中传热传质的数值解

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Nowadays, a heat and mass transfer simulation plays an important role in various engineering and industrial fields. To analyze physical behaviors of a thermal environment, we have to simulate heat and mass transfer phenomena. However to obtain numerical solutions to heat and mass transfer equations is much time-consuming. In this paper, therefore, one of acceleration techniques developed in the graphics community that exploits a graphics processing unit (GPU) is applied to the numerical solutions of heat and mass transfer equations. Implementation of the simulation on GPU makes GPU computing power available for the most time-consuming part of the simulation and calculation. The nVidia CUDA programming model provides a straightforward means of describing inherently parallel computations. This paper improves the computational performance of solving heat and mass transfer equations numerically running on GPU. We implemented simulation of heat and mass transfer using the novel CUDA platform on nVidia Quadro FX 4800 and compared its performance with an optimized CPU implementation on a high-end Intel Xeon CPU. The experimental results clearly show that GPU can perform heat and mass transfer simulation accurately and significantly accelerate the numerical calculation with the maximum observed speedups 20 times. Therefore, the GPU implementation is a promising approach to acceleration of the heat and mass transfer simulation.
机译:如今,传热和传质模拟在各种工程和工业领域中都发挥着重要作用。要分析热环境的物理行为,我们必须模拟传热和传质现象。但是,要获得传热和传质方程的数值解很费时。因此,在本文中,在图形社区中开发的一种利用图形处理单元(GPU)的加速技术被应用于传热和传质方程的数值解。在GPU上执行仿真使GPU的计算能力可用于仿真和计算中最耗时的部分。 nVidia CUDA编程模型提供了一种描述固有并行计算的简单方法。本文提高了求解在GPU上数值运行的传热和传质方程的计算性能。我们在nVidia Quadro FX 4800上使用新颖的CUDA平台实施了传热和传质的仿真,并将其性能与高端Intel Xeon CPU上的优化CPU实施进行了比较。实验结果清楚地表明,GPU可以准确地进行传热和传质仿真,并以最大的观察到的加速比显着加速数值计算。因此,GPU实施是加速传热和传质仿真的一种有前途的方法。

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