GPU Acceleration of Hydraulic Transient Simulations of Large-Scale Water Supply Systems

被引:7
|
作者
Meng, Wanwan [1 ]
Cheng, Yongguang [1 ]
Wu, Jiayang [1 ,2 ]
Yang, Zhiyan [1 ]
Zhu, Yunxian [3 ]
Shang, Shuai [4 ]
机构
[1] Wuhan Univ, State Key Lab Water Resources & Hydropower Engn S, Wuhan 430072, Hubei, Peoples R China
[2] Wuhan Univ, Ministerial Key Lab Hydraul Machinery Transients, Minist Educ, Wuhan 430072, Hubei, Peoples R China
[3] Construct Management Co, Chushandian Reservoir Project Henan Prov, Zhengzhou 450000, Henan, Peoples R China
[4] Zhangfeng Water Conservancy Management Co LtD, Qinshui 048000, Peoples R China
来源
APPLIED SCIENCES-BASEL | 2019年 / 9卷 / 01期
基金
中国国家自然科学基金;
关键词
graphics processing unit (GPU); method of characteristics; hydraulic transients; large-scale water supply system; parallel computing; speedup ratio; FLOW;
D O I
10.3390/app9010091
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
Simulating hydraulic transients in ultra-long water (oil, gas) transmission or large-scale distribution systems are time-consuming, and exploring ways to improve the simulation efficiency is an essential research direction. The parallel implementation of the method of characteristics (MOC) on graphics processing unit (GPU) chips is a promising approach for accelerating the simulations, because GPU has a great parallelization ability for massive but simple computations, and the explicit and local features of MOC meet the features of GPU quite well. In this paper, we propose and verify a GPU implementation of MOC on a single chip for more efficient simulations of hydraulic transients. Details of GPU-MOC parallel strategies are introduced, and the accuracy and efficiency of the proposed method are verified by simulating the benchmark single pipe water hammer problem. The transient processes of a large scale water distribution system and a long-distance water transmission system are simulated to investigate the computing capability of the proposed method. The results show that GPU-MOC method can achieve significant performance gains, and the speedup ratios are up to hundreds compared to the traditional method. This preliminary work demonstrates that GPU-MOC parallel computing has great prospects in practical applications with large computing load.
引用
收藏
页数:14
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