SunwayLB:基于神威太湖之光的极端尺度晶格玻尔兹曼方法计算流体动力学仿真

Zhao Liu, Xuesen Chu, Xiaojing Lv, Hongsong Meng, Shupeng Shi, Wenji Han, Jingheng Xu, H. Fu, Guangwen Yang
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引用次数: 15

摘要

晶格玻尔兹曼方法(LBM)是一类相对较新的计算流体动力学方法。在本文中,我们报告了我们在SunwayLB上的工作,它使基于LBM的解决方案能够用于工业应用。我们提出了几种技术来提高模拟速度和提高SunwayLB的可扩展性,包括定制的多级域分解和数据共享方案,精心编排的策略来融合具有不同性能约束的内核以实现更平衡的工作负载,以及汇编代码的优化策略,这些策略可以带来高达137倍的加速。基于这些优化方案,我们成功地执行了最大的直接数值模拟,涉及多达5.6万亿晶格单元,实现每秒11,245亿单元更新(GLUPS), 77%的内存带宽利用率和4.7 PFlops的持续性能。我们还演示了一系列的超大规模流体流动的计算实验,作为实际应用的例子,以检查我们工作的有效性和性能。结果表明,SunwayLB能够胜任工业应用的实际解决方案。
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SunwayLB: Enabling Extreme-Scale Lattice Boltzmann Method Based Computing Fluid Dynamics Simulations on Sunway TaihuLight
The Lattice Boltzmann Method (LBM) is a relatively new class of Computational Fluid Dynamics methods. In this paper, we report our work on SunwayLB, which enables LBM based solutions aiming for industrial applications. We propose several techniques to boost the simulation speed and improve the scalability of SunwayLB, including a customized multi-level domain decomposition and data sharing scheme, a carefully orchestrated strategy to fuse kernels with different performance constraints for a more balanced workload, and optimization strategies for assembly code, which bring up to 137x speedup. Based on these optimization schemes, we manage to perform the largest direct numerical simulation which involves up to 5.6 trillion lattice cells, achieving 11,245 billion cell updates per second (GLUPS), 77% memory bandwidth utilization and a sustained performance of 4.7 PFlops. We also demonstrate a series of computational experiments for extreme-large scale fluid flow, as examples of real-world applications, to check the validity and performance of our work. The results show that SunwayLB is competent for a practical solution for industrial applications.
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