GPU accelerated computation and real-time rendering of cellular automata model for spatial simulation

被引：0

作者：

Zhao, Yuan ^{[1
,2
,3
]}

Zhang, Xinchang ^{[4
]}

Zhang, Zhen ^{[1
]}

Wang, Lu ^{[1
,2
,3
]}

Hu, Yueming ^{[1
,2
,3
]}

机构：

[1] College of Informatics, South China Agricultural University, Guangzhou

[2] Guangdong Province Key Laboratory of Land Use and Consolidation, Guangzhou

[3] Key Laboratory of the Ministry of Land and Resources for Construction Land Transformation, Guangzhou

[4] School of Geography and Planning, Sun Yat-Sen University, Guangzhou

来源：

Journal of Information and Computational Science | 2014年 / 11卷 / 12期

关键词：

Cellular automata; GPU-accelerated computation; Real-time rendering;

D O I：

10.12733/jics20104445

中图分类号：

学科分类号：

摘要：

Because Cellular Automata (CA) is a dynamic system with inherent parallelism, many studies are focused on mapping CA to the parallel system in order to obtain high performance computing capability, such as using clusters, supercomputers and networks of computers. But the application of these systems are too expensive and difficult to use on the occasions which need convenient computing. Recent developments in the General Purpose GPU can meet the desktop computing challenge, which have high performance at low cost. This paper presents a general-purpose approach to accelerate the CA in geographical domain in case of spatial simulation. A series of experiments are launched to test the performance of proposed method. Finally, the experimental results indicate the approach in this paper can obtain high performance and computational performance data using GPU based accelerating method are fifty to sixty times faster than the identical algorithms using CPU in test environment. It is worthy of (1) reducing the communication cost between GPU and CPU is crucial when visualization and processing are equally important in real time simulation and (2) improving the parallel capability in the CA functions is essential using GPU Programming. © 2014 Binary Information Press

引用

页码：4453 / 4465

页数：12

共 21 条

[1]

Gobron S., Coltekin A., Bonafos H., Et al., GPGPU computation and visualization of three-dimensional cellular automata , The Visual Computer, 27, 1, pp. 67-81, (2011)

[2]

White R., Engelen G., Cellular automata and fractal urban form: A cellular modelling approach to the evolution of urban land-use patterns , Environment and Planning A, 25, (1993)

[3]

Batty M., Xie Y., From cells to cities , Environment and Planning B, 21, (1994)

[4]

Li X., Yeh A.G.O., Modelling sustainable urban development by the integration of constrained cellular automata and GIS , International Journal of Geographical Information Science, 14, 2, pp. 131-152, (2000)

[5]

Geertman S., Stillwell J., Planning support systems: An inventory of current practice , Computers, Environment and Urban Systems, 28, 4, pp. 291-310, (2004)

[6]

Barredo J.I., Kasanko M., McCormick N., Et al., Modelling dynamic spatial processes: Simulation of urban future scenarios through cellular automata , Landscape and Urban Planning, 64, 3, pp. 145-160, (2003)

[7]

Yu J., Chen Y., Wu J., Et al., Cellular automata-based spatial multi-criteria land suitability simulation for irrigated agriculture , International Journal of Geographical Information Science, 25, 1, pp. 131-148, (2011)

[8]

Malczewski J., GIS-based land-use suitability analysis: A critical overview , Progress in Planning, 62, 1, pp. 3-65, (2004)

[9]

Clarke K.C., Geocomputation's future at the extremes: High performance computing and nanoclients , Parallel Computing, 10, 29, pp. 1281-1295, (2003)

[10]

Clarke K.C., Gaydos L.J., Loose-coupling a cellular automaton model and GIS: Long-term urban growth prediction for San Francisco and Washington/Baltimore , International Journal of Geographical Information Science, 12, 7, pp. 699-714, (1998)

← 1 2 3 →