• Journal of Institute of Control, Robotics and Systems
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• v.20 no.1
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• pp.37-41
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• 2014

FFT (Fast Fourier Transform) has been widely used in various fields such as image processing, voice processing, physics, astronomy, applied mathematics and so forth. Much research has been conducted due to the importance of the FFT and recently new FFT algorithms using a GPU (Graphics Processing Unit) have been developed for the purpose of much faster processing. In this paper, the new optimal FFT algorithm using the Pease FFT algorithm has been proposed reflecting the hardware configuration of a GPGPU (General Purpose computing of GPU). According to the experiments, the proposed algorithm outperformed by between 3% to 43% compared to the CUFFT algorithm.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.05a
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• pp.131-134
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• 2013

영상처리, 음성처리, 물리학, 천문학, 응용 수학등 다양한 분야에 FFT가 널리 사용되고 있다. FFT의 중요성 때문에 많은 연구가 이루어졌고, 최근 고속처리를 위하여 GPU를 활용한 FFT 알고리즘들이 개발되고 있다. 본 논문은 FFT알고리즘의 변형중 하나인 Pease FFT알고리즘을 GPGPU의 하드웨어 구성을 반영하여 최적화시킨 FFT 가속알고리즘을 제안한다. 실험결과 제안된 알고리즘은 CUFFT에 비하여 3% ~ 43%까지 우수한 성능을 보였다.

• 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.