基于320亿网格有限元计算的壁面分辨大涡模拟拖曳水池数值试验的实现

C. Kato, Y. Yamade, K. Nagano, Kiyoshi Kumahata, K. Minami, Tatsuo Nishikawa
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引用次数: 6

摘要

为了通过大幅缩短求解时间来实现数值拖曳槽测试,一个名为FrontFlow/blue (FFB)的通用有限元流求解器已经进行了全面优化,以便通过其四个热内核中的三个实现最大可能的持续内存吞吐量。在日本下一代旗舰计算机Fugaku上实现了179.0 GFLOPS的单节点持续性能,相当于峰值性能的5.3%。弱规模基准测试已经证实,FFB在5,505,024个计算核心上以超过85%的并行效率运行,并实现了16.7 PFLOPS的整体持续性能。因此,使用320亿个网格进行大涡模拟所需的时间已从近两天显著减少到仅37分钟,即71倍。这清楚地表明,在几年内,实际上可以建造一个用于船舶流体力学的数值拖曳箱。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Toward Realization of Numerical Towing-Tank Tests by Wall-Resolved Large Eddy Simulation based on 32 Billion Grid Finite-Element Computation
To realize numerical towing-tank tests by substantially shortening the time to the solution, a general-purpose Finite-Element flow solver, named FrontFlow/blue (FFB), has been fully optimized so as to achieve maximum possible sustained memory throughputs with three of its four hot kernels. A single-node sustained performance of 179.0 GFLOPS, which corresponds to 5.3% of the peak performance, has been achieved on Fugaku, the next flagship computer of Japan. A weak-scale benchmark test has confirmed that FFB runs with a parallel efficiency of over 85% up to 5,505,024 compute cores, and an overall sustained performance of16.7 PFLOPS has been achieved. As a result, the time needed for large-eddy simulation using 32 billion grids has been significantly reduced from almost two days to only 37 min., or by a factor of 71. This has clearly indicated that a numerical towing-tank could actually be built for ship hydrodynamics within a few years.
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