基于GPU的内存约束流体仿真的自适应网格结构

IF 1.4 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING
Wouter Raateland, Torsten Hädrich, Jorge Alejandro Amador Herrera, D. Banuti, Wojciech Palubicki, S. Pirk, K. Hildebrandt, D. Michels
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引用次数: 3

摘要

本文介绍了动态约束网格(DCGrid),一种用于流体模拟的分层自适应网格结构,并结合了一种有效管理网格自适应的方案。DCGrid被设计为在GPU上实现并用于高性能模拟。具体来说,它允许我们有效地改变和调整整个空间域的网格分辨率,并在GPU实现中快速评估局部模板和单个单元。DCGrid的一个特别之处在于网格自适应的控制被建模为在最大可用内存约束下的优化,这解决了基于gpu的仿真中的内存限制问题。为了进一步推进DCGrid在高性能模拟中的应用,我们在DCGrid的基础上补充了一种有效的方案,用于模拟不同分辨率的细胞上流体和静态固体之间的碰撞。我们展示了DCGrid在烟雾流和复杂云模拟中的有效性,其中地形-大气相互作用需要与不同分辨率和快速变化条件的单元一起工作。最后,我们比较了DCGrid与其他自适应网格结构的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
DCGrid: An Adaptive Grid Structure for Memory-Constrained Fluid Simulation on the GPU
We introduce Dynamic Constrained Grid (DCGrid), a hierarchical and adaptive grid structure for fluid simulation combined with a scheme for effectively managing the grid adaptations. DCGrid is designed to be implemented on the GPU and used in high-performance simulations. Specifically, it allows us to efficiently vary and adjust the grid resolution across the spatial domain and to rapidly evaluate local stencils and individual cells in a GPU implementation. A special feature of DCGrid is that the control of the grid adaption is modeled as an optimization under a constraint on the maximum available memory, which addresses the memory limitations in GPU-based simulation. To further advance the use of DCGrid in high-performance simulations, we complement DCGrid with an efficient scheme for approximating collisions between fluids and static solids on cells with different resolutions. We demonstrate the effectiveness of DCGrid for smoke flows and complex cloud simulations in which terrain-atmosphere interaction requires working with cells of varying resolution and rapidly changing conditions. Finally, we compare the performance of DCGrid to that of alternative adaptive grid structures.
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CiteScore
2.90
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