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Numerical Solutions of Heat and Mass Transfer with the Second Kind Boundary and Initial Conditions in Capillary Porous Media Using Programmable Graphics Hardware

机译:使用可编程图形硬件在毛细管多孔介质中第二种边界和初始条件下传热和传质的数值解

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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 with the second boundary and initial conditions 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 10 times. Therefore, the GPU implementation is a promising approach to acceleration of the heat and mass transfer simulation.
机译:如今,热量和传质模拟在各种工程和工业领域起着重要作用。为了分析热环境的物理行为,我们必须模拟热量和传质现象。然而,为了获得热量和传质方程的数值溶液是多耗时的。因此,在本文中,在利用图形处理单元(GPU)的图形社区中开发的加速技术之一应用于热量和质量传递方程的数值解。在GPU上实现模拟使得GPU计算能力可用于模拟和计算的最耗时的部分。 NVIDIA CUDA编程模型提供了一种描述固有并行计算的简单方法。本文提高了在GPU上数值运行的第二边界和初始条件的求解热量和质量传递方程的计算性能。我们在NVIDIA Quadro FX 4800上的新型CUDA平台实现了热量和传质的仿真,并将其性能与高端英特尔Xeon CPU的优化CPU实现进行了比较。实验结果清楚地表明,GPU可以精确地进行热量和传质模拟,并显着加速数值计算,最大观察到的加速10次。因此,GPU实施是一种有希望加速热和传质模拟的方法。

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