• Journal of Broadcast Engineering
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• v.18 no.2
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• pp.204-214
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• 2013

Recently various research have been conducted relating to the implementation of signal processing or communication system by software using the massively parallel processing capability of the GPU. In this work, we focus on reducing software simulation time of 2K/8K FFT in DVB-T by using GPU. we estimate the processing time of the DVB-T system, which is one of the standards for DTV transmission, by CPU. Then we implement the FFT processing by the software using the NVIDIA's massively parallel GPU processor. In this paper we apply stream process method to reduce the overhead for data transfer between CPU and GPU, coalescing method to reduce the global memory access time and data structure design method to maximize the shared memory usage. The results show that our proposed method is approximately 20~30 times as fast as the CPU based FFT processor, and approximately 1.8 times as fast as the CUFFT library (version 2.1) which is provided by the NVIDIA when applied to the DVB-T 2K/8K mode FFT.

• Spatial Information Research
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• v.23 no.2
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• pp.1-9
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• 2015

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.