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A fast method based on GPU for solidification structure simulation of continuous casting billets

delete2021-01-01
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PRE
AI
J
Jing Jing Wang *
H
Hong Ji Meng
阳
阳剑 (Jian Yang)
Z
Zhi Xie
DOI:10.1016/j.jocs.2020.101265delete
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摘要

摘要

En 中文
The present paper develops a fast method to simulate the solidification structure of continuous billets with Cellular Automaton (CA) model. Traditional solution of the CA model on single CPU takes a long time for the massive datasets and complicated calculations, making it unrealistic to optimize the parameters through numerical simulation. In this paper, a parallel method based on Graphics Processing Units (GPU) was proposed to accelerate the calculation, which developed new algorithms for the solute redistribution and neighbor capture to avoid data race in parallel computing. This new method was applied to simulate the solidification structure of Fe0.64C alloy, and the simulating results were in good agreement with the experiment results with the same parameters. The absolute computational time for the fast method implemented on Tesla P100 GPU is 277 s, while the traditional method implemented on Intel(R) Xeon(R) CPU E5-2680 v4 @ 2.40 GHz with single core is 24.57 h. The speedup, ratio between the absolute computational time of GPU-CA and CPU-CA, varies from 300 to 400 with the increase of the grids.
Keyword:
Fast method
Graphics processing units
Cellular automaton
Solidification structure
Parallel algorithms
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Nature Computational Science 封面图
Nature Computational Science
IF:
18.3
论文数:
3.1K
被引数:
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机构

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northeastern university - china
学者数:
3.2W
论文数: 2.7W
被引数: 37
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