ICCM2016: The Implementation of Two-Dimensional Multi-Block Lattice Boltzmann Method on GPU

Ya Zhang; Guang Pan; Qiaogao Huang

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ICCM2016: The Implementation of Two-Dimensional Multi-Block Lattice Boltzmann Method on GPU

机译：ICCM2016：在GPU上实现二维多块格子Boltzmann方法

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A straightforward implementation of the Multi-Block Lattice Boltzmann Method (MB-LBM) on a Graphics Processing Unit (GPU) is presented to accelerate the simulation of fluid flows in two-dimensional geometries. The algorithm is measured in terms of both accuracy and efficiency with the benchmark cases of the lid-driven cavity flow and the flow past a circular cylinder, and satisfactory results are obtained. The results show that the performance on GPU becomes even better with the amount of data increasing. Moreover, the arrangement of the computational domain has a significant effect on the efficiency. These results demonstrate the great potential of GPU on the MB-LBM, especially when dealing with massive data.

机译：提出了在图形处理单元（GPU）上的多块格子Boltzmann方法（MB-LBM）的直接实现以加速二维几何形状中的流体流的模拟。根据精度和效率来测量算法，利用盖子驱动腔流量的基准情况和圆柱体的流动，获得令人满意的结果。结果表明，通过增加的数据量，GPU的性能变得更好。此外，计算结构域的布置对效率具有显着影响。这些结果表明了GPU对MB-LBM的巨大潜力，特别是在处理大规模数据时。

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来源
《International journal of computational methods》 |2019年第5期|共16页
作者
Ya Zhang; Guang Pan; Qiaogao Huang;
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作者单位

1School of Marine Science and Technology Northwestern Polytechnical University Xi’an 710072 China;

1School of Marine Science and Technology Northwestern Polytechnical University Xi’an 710072 China;

1School of Marine Science and Technology Northwestern Polytechnical University Xi’an 710072 China;

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原文格式 PDF
正文语种 eng
中图分类数学;
关键词
Multi-block lattice Boltzmann method; graphics processing unit; ratio of acceleration;

机译：多块格子Boltzmann方法;图形处理单元;加速度的比例;

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专利

1. ICCM2016: The Implementation of Two-Dimensional Multi-Block Lattice Boltzmann Method on GPU [J] . Ya Zhang, Guang Pan, Qiaogao Huang International journal of computational methods . 2019,第5期

机译：ICCM2016：在GPU上实现二维多块格子Boltzmann方法
2. Multi-thread implementations of the lattice Boltzmann method on non-uniform grids for CPUs and GPUs [J] . M. Schdnherr, K. Kucher, M. Geier, Computers & mathematics with applications . 2011,第12期

机译：针对CPU和GPU的非均匀网格上的格子Boltzmann方法的多线程实现
3. FULL GPU Implementation of Lattice-Boltzmann Methods with Immersed Boundary Conditions for Fast Fluid Simulations [J] . G Boroni, J Dottori, P Rinaldi The international journal of multiphysics . 2017,第1期

机译：具有浸入式边界条件的Lattice-Boltzmann方法的全GPU实现，用于快速流体模拟
4. Implementation of a Lattice Boltzmann Method for Large Eddy Simulation on Multiple GPUs [C] . Li Qinjian, Zhong Chengwen, Li Kai, The 14th IEEE International Conference on High Performance Computing and Communication ; The 9th IEEE International Conference on Embedded Software and Systems. . 2012

机译：用于多个GPU的大涡模拟的莱迪思Boltzmann方法的实现
5. GPU accelerated study of heat transfer and fluid flow by lattice Boltzmann method on CUDA. [D] . Ren, Qinlong. 2016

机译：GPU在CUDA上通过格子Boltzmann方法加速了传热和流体流动的研究。
6. Efficient methods for implementation of multi-level nonrigid mass-preserving image registration on GPUs and multi-threaded CPUs [O] . Nathan D. Ellingwood, Youbing Yin, Matthew Smith, -1

机译：在GPU和多线程CPU上实现多级非刚性批量保存图像注册的有效方法
7. Multi-thread implementations of the lattice Boltzmann method on non-uniform grids for CPUs and GPUs [O] . Schönherr M., Kucher K., Geier M., 2011

机译：针对CPU和GPU的非均匀网格上的格子Boltzmann方法的多线程实现

ICCM2016: The Implementation of Two-Dimensional Multi-Block Lattice Boltzmann Method on GPU

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