A Parallel Method of Surface Flow Dynamics Simulation based on CUDA

Qianjiao WU; Yumin CHEN

doi:10.12082/dqxxkx.2020.190500

Journals >Journal of Geo-information Science >Volume 22 >Issue 3 >Page 505 > Article

Journal of Geo-information Science
Vol. 22, Issue 3, 505 (2020)

A Parallel Method of Surface Flow Dynamics Simulation based on CUDA

Qianjiao WU and Yumin CHEN^*

Author Affiliations

School of Resource and Environment Science, Wuhan University, Wuhan 430079, China

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DOI: 10.12082/dqxxkx.2020.190500 Cite this Article

Qianjiao WU, Yumin CHEN. A Parallel Method of Surface Flow Dynamics Simulation based on CUDA[J]. Journal of Geo-information Science, 2020, 22(3): 505 Copy Citation Text

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Fig. 1. Model of the threads by the CUDA

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Fig. 2. Transmission mode of data during the parallelization process based on CUDA

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Fig. 3. Partition model of thread during the parallelization process based on CUDA

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Fig. 4. Test DEM of the BBW

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Fig. 5. TINs on the sub-region under different thresholds

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Fig. 6. Flow pathnetworks on the sub-region under different scales of the rainfall points （threshold is 0.5m）

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Fig. 7. Comparison of the simulated results at the BBW's outlet

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Fig. 8. Speed ratio under different scales of the rainfall points

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Fig. 9. Nash coefficient distribution map of simulation results

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Fig. 10. Correlation coefficient distribution map of simulation results

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Fig. 11. Balance coefficient distribution map of simulation results

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阈值/m	0.5	1.0	1.5	2.0	2.5
特征点数量/个	10 859	4295	2149	1268	822
TIN表面三角面的数量/个	23 348	11 079	6854	5139	4285
RMSE/m	0.17	0.31	0.45	0.58	0.73

Table 1. The accuracy of TIN under different thresholds on the BBW

阈值/m	算法	模型	降雨源点尺度/m
阈值/m	算法	模型	10	15	20	25	30
0.5	基于TIN的地表水动态模拟算法	N	0.77	0.77	0.77	0.77	0.77
		R	0.91	0.91	0.91	0.91	0.91
		B	1.30	1.31	1.31	1.30	1.30
	基于CUDA的地表水动态模拟并行方法	N	0.77	0.77	0.77	0.77	0.77
		R	0.91	0.91	0.91	0.91	0.91
		B	1.30	1.31	1.31	1.30	1.30
1.0	基于TIN的地表水动态模拟算法	N	0.77	0.77	0.77	0.77	0.77
		R	0.91	0.91	0.91	0.91	0.91
		B	1.31	1.31	1.31	1.31	1.31
	基于CUDA的地表水动态模拟并行方法	N	0.77	0.77	0.77	0.77	0.77
		R	0.91	0.91	0.91	0.91	0.91
		B	1.31	1.31	1.31	1.31	1.31
1.5	基于TIN的地表水动态模拟算法	N	0.77	0.77	0.77	0.77	0.77
		R	0.91	0.91	0.91	0.91	0.91
		B	1.31	1.31	1.32	1.32	1.31
	基于CUDA的地表水动态模拟并行方法	N	0.77	0.77	0.77	0.77	0.77
		R	0.91	0.91	0.91	0.91	0.91
		B	1.31	1.31	1.32	1.32	1.31
2.0	基于TIN的地表水动态模拟算法	N	0.77	0.77	0.77	0.77	0.77
		R	0.91	0.91	0.91	0.91	0.91
		B	1.31	1.32	1.31	1.32	1.31
	基于CUDA的地表水动态模拟并行方法	N	0.77	0.77	0.77	0.77	0.77
		R	0.91	0.91	0.91	0.91	0.91
		B	1.31	1.32	1.31	1.32	1.31
2.5	基于TIN的地表水动态模拟算法	N	0.77	0.77	0.77	0.77	0.77
		R	0.91	0.91	0.91	0.91	0.91
		B	1.31	1.31	1.32	1.32	1.32
	基于CUDA的地表水动态模拟并行方法	N	0.77	0.77	0.77	0.77	0.77
		R	0.91	0.91	0.91	0.91	0.91
		B	1.31	1.31	1.32	1.32	1.32

Table 2. Accuracy comparison of simulating the flow discharge at the outlet of the BBW

	评价参数
	N	R	B
SWAT	0.41	0.87	0.96

Table 3. Statistical factors utilized to assess the precision of SWAT model （scale of DEM is 30 m）

阈值/m	算法	降雨源点尺度/m
阈值/m	算法	10	15	20	25	30
0.5	基于TIN的地表水动态模拟算法	953.82	425.37	278.18	213.77	169.77
0.5	基于CUDA的地表水动态模拟并行方法	93.16	43.49	28.34	22.72	19.00
1.0	基于TIN的地表水动态模拟算法	912.16	407.40	278.21	203.25	159.87
1.0	基于CUDA的地表水动态模拟并行方法	86.32	42.75	27.72	21.23	18.47
1.5	基于TIN的地表水动态模拟算法	899.07	395.99	267.96	196.33	159.60
1.5	基于CUDA的地表水动态模拟并行方法	80.51	41.88	27.23	20.74	17.88
2.0	基于TIN的地表水动态模拟算法	893.92	396.22	270.80	198.07	159.21
2.0	基于CUDA的地表水动态模拟并行方法	86.14	43.86	28.01	21.39	17.95
2.5	基于TIN的地表水动态模拟算法	892.59	400.38	260.40	199.60	164.56
2.5	基于CUDA的地表水动态模拟并行方法	85.61	43.60	27.77	20.80	17.29

Table 4. Computation performance of simulating the flow discharge at the outlet of the BBW (s)

Qianjiao WU, Yumin CHEN. A Parallel Method of Surface Flow Dynamics Simulation based on CUDA[J]. Journal of Geo-information Science, 2020, 22(3): 505

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