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基于GPU带有复杂边界的三维实时流体模拟
引用本文:柳有权,刘学慧,吴恩华.基于GPU带有复杂边界的三维实时流体模拟[J].软件学报,2006,17(3):568-576.
作者姓名:柳有权  刘学慧  吴恩华
作者单位:1. 中国科学院软件研究所计算机科学重点实验室,北京,100080;中国科学院研究生院,北京,100049
2. 中国科学院软件研究所计算机科学重点实验室,北京,100080
3. 澳门大学科学技术学院电脑与资讯科学系,澳门
基金项目:中国科学院资助项目;科技部科研项目;澳门大学校科研和教改项目
摘    要:在GPU(graphics processing unit)上求解了复杂场景中的三维流动问题,充分利用了GPU并行能力以加速计算.与前人的方法不同,该方法对于边界条件的处理更为通用.首先,通过在图像空间生成实心的剖切截面构成整个障碍物信息图,算法使得流体计算与整个几何场景的复杂度无关,通过对各体素进行分类并结合边界条件,根据障碍物形成修正因子来修改对应的值;另外,采用更为紧凑的数据格式,以充分利用硬件的并行性.通过将所有标量的运算压缩到纹元的4个颜色通道并结合平铺三维纹理,减少了三维流场计算所需要的绘制次数.实验结果显示出算法的有效性和高效率.该算法可以实时计算并显示一个采用中等规模离散的复杂场景.

关 键 词:图形硬件  可编程性  纳维-斯托克斯方程组  三维流动模拟  实时
收稿时间:9/2/2004 12:00:00 AM
修稿时间:2005-02-25

Real-Time 3D Fluid Simulation on GPU with Complex Obstacles
LIU You-Quan,LIU Xue-Hui and WU En-Hua.Real-Time 3D Fluid Simulation on GPU with Complex Obstacles[J].Journal of Software,2006,17(3):568-576.
Authors:LIU You-Quan  LIU Xue-Hui and WU En-Hua
Affiliation:1.Laboratory of Computer Science, Institute of Software, The Chinese Academy of Sciences, Beijing 100080, China; 2.Department of Computer and Information Science, Faculty of Science and Technology, University of Macau, Macso, China; 3.Graduate School, The Chinese Academy of Sciences, Beijing 100049, China
Abstract:This paper, solves the 3D fluid dynamics problem in a complex environment by taking advantage of the parallelism and programmability of GPU (graphics processing unit). In difference from other methods, innovation is made in two aspects. Firstly, more general boundary conditions could be processed on GPU in the method. By the method, the boundary from a 3D scene with capped solid clipping is generated, making the computation run on GPU despite of the complexity of the whole geometry scene. Then by grouping the voxels into different types according to their positions relative to the obstacles and locating the voxel that determines the value of the current voxel, the values on the boundaries are modified according to the boundary conditions. Secondly, more compact structure in data packing is designed at the fragment processing level to enhance parallelism and reduce execution passes. The scalar variables including density and temperature are packed into four channels of texels to accelerate the computation of 3D Navier-Stokes Equations. The test results show the efficiency of the method, and as a result, it is feasible to run middle-scale problems of 3D fluid dynamics in an interactive speed for more general environment with complex geometry on PC platform.
Keywords:GPU
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