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http://dx.doi.org/10.12672/ksis.2015.23.2.001

A Parallel Processing Technique for Large Spatial Data  

Park, Seunghyun (Dept. of Computer Engineering, Kumoh National Institute of Technology)
Oh, Byoung-Woo (Dept. of Computer Engineering, Kumoh National Institute of Technology)
Publication Information
Spatial Information Research / v.23, no.2, 2015 , pp. 1-9 More about this Journal
Abstract
Graphical processing unit (GPU) contains many arithmetic logic units (ALUs). Because many ALUs can be exploited to process parallel processing, GPU provides efficient data processing. The spatial data require many geographic coordinates to represent the shape of them in a map. The coordinates are usually stored as geodetic longitude and latitude. To display a map in 2-dimensional Cartesian coordinate system, the geodetic longitude and latitude should be converted to the Universal Transverse Mercator (UTM) coordinate system. The conversion to the other coordinate system and the rendering process to represent the converted coordinates to screen use complex floating-point computations. In this paper, we propose a parallel processing technique that processes the conversion and the rendering using the GPU to improve the performance. Large spatial data is stored in the disk on files. To process the large amount of spatial data efficiently, we propose a technique that merges the spatial data files to a large file and access the file with the method of memory mapped file. We implement the proposed technique and perform the experiment with the 747,302,971 points of the TIGER/Line spatial data. The result of the experiment is that the conversion time for the coordinate systems with the GPU is 30.16 times faster than the CPU only method and the rendering time is 80.40 times faster than the CPU.
Keywords
GPU; CUDA; Memory Mapped File; Parallel processing; Spatial Data;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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