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An Efficient Acceleration of Solving Heat and Mass Transfer Equations with the Second Kind Boundary Conditions in Capillary Porous Radially Composite Cylinder Using Programmable Graphics Hardware

机译:使用可编程图形硬件高效求解带第二种边界条件的毛细管多孔径向复合圆柱体中的传热和传质方程

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摘要

With the recent developments in computing technology, increased efforts have gone into the simulation of various scientific methods and phenomenon in engineering fields. One such case is the simulation of heat and mass transfer equations which is becoming more and more important in analyzing various scenarios in engineering applications. Analysing the heat and mass transfer phenomenon under various environmental conditions require us to simulate it. However, this process of numerical solution of heat and mass transfer equations is very time consuming. Therefore, this paper aims at utilizing one of the acceleration techniques developed in the graphics community that exploits a graphics processing unit (GPU) which is applied to the numerical solutions of heat and mass transfer equations. The nVidia Compute Unified Device Architecture (CUDA) programming model can be a good method of applying parallel computing to program the graphical processing unit. This paper shows a good improvement in the performance, while solving the heat and mass transfer equations for a capillary porous radially composite cylinder with the second kind of boundary conditions, numerically running on GPU. This heat and mass transfer simulation is implemented using CUDA platform on nVidia Quadro FX 4800 graphics card. Our experimental results depict the drastic performance improvement when GPU is used to perform heat and mass transfer simulation. GPU can significantly accelerate the performance with a maximum observed speedup of more than 8 fold times. Therefore, the GPU is a good approach to accelerate the heat and mass transfer simulation.
机译:随着计算机技术的最新发展,在工程领域中对各种科学方法和现象的仿真已经投入了更多的精力。一种这样的情况是对传热和传质方程的仿真,这在分析工程应用中的各种情况时变得越来越重要。分析各种环境条件下的传热和传质现象需要我们对其进行模拟。但是,这种传热和传质方程数值解的过程非常耗时。因此,本文旨在利用在图形社区中开发的一种加速技术,该技术利用了图形处理单元(GPU),该图形处理单元被应用于传热和传质方程的数值解。 nVidia计算统一设备架构(CUDA)编程模型可以是应用并行计算对图形处理单元进行编程的一种好方法。本文显示了性能的良好改进,同时解决了在第二种边界条件下数值运行在GPU上的毛细管多孔径向复合圆柱体的传热和传质方程。此传热传质仿真是使用nVidia Quadro FX 4800显卡上的CUDA平台实现的。我们的实验结果表明,使用GPU进行传热和传质仿真时,性能得到了显着改善。 GPU可以显着提高性能,最大观察到的加速超过8倍。因此,GPU是加速传热和传质仿真的好方法。

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