Browse > Article
http://dx.doi.org/10.5909/JBE.2013.18.2.204

Implementation of FFT on Massively Parallel GPU for DVB-T Receiver  

Lee, Kyu Hyung (Department of Electronic, information & Communication Engineering, Hongik University)
Heo, Seo Weon (Department of Electronic, information & Communication Engineering, Hongik University)
Publication Information
Journal of Broadcast Engineering / v.18, no.2, 2013 , pp. 204-214 More about this Journal
Abstract
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.
Keywords
FFT; GPU; CUDA; DVB-T; NVIDIA; SDR;
Citations & Related Records
연도 인용수 순위
  • Reference
1 R. deBeer and D. van Ormondt, "Accelerating batched 1D-FFT with a CUDA-capable computer," Proc. IEEE Int. Conf. on Imaging System and Techniques (IST), pp. 446-451, July 2010.
2 Y. Chen, X. Cui, and H. Mei, "Large-scale FFT on GPU clusters," Proc. ACM/IEEE Int. Conf. on Supercomputing, pp. 315-324, June 2010.
3 Z. Lili, Z. Shengbing, Z. Meng and Z. Yi, "Streaming FFT asynchronously on graphics processor units," Proc. IEEE Int. Forum. on Information Technology and Applications (IFITA), pp. 308-312, July 2010.
4 N. Hinitt and T. Kocak, "GPU-based FFT computation for multi-gigabit wireless HD baseband processing," EURASIP Jounal on wireless communications and Networking, vol. 2010, no. 30, June 2010.
5 G. Wang, M. Wu, Y. Sun and J. R. Cavallaro, "A massively parallel implementation of QC-LDPC decoder on GPU," IEEE 9th Symposium on Application Specific Processors (SASP), pp.82-85, June 2011.
6 M. Wu, Y. Sun, S. Gupta, and J. Cavallaro, "Implementation of a high throughput soft MIMO detector on GPU," Journal of Signal Processing Systems, vol. 64, no. 1, pp. 123-136, Sept. 2010.
7 N. K. Govindaraju, B. Lloyd, Y. Dotsenko, B. Smith and J. Manferdelli, "High performance discrete fourier transforms on graphics processors," Proc. ACM/IEEE Int. Conf. on Supercomputing, pp. 1-12, Nov. 2008.
8 L. Vangelista, N. Benvenuto, S. Tomasin, C. Nokes, J. Stott, A. Filippi, M. Vlot, V. Mignone, and A. Morello, "Key technologies for next-generation terrestrial digital television standard DVB-T2," IEEE Communization Magazine, vol. 47, no. 10, pp. 146-153, Oct. 2009.   DOI   ScienceOn
9 J. H. Suck, D. W. Kim, T. W. Kwon, S. K. Hyung and J. R. Choi, "A 8192 complex point FFT/IFFT for COFDM modulation scheme in DVB-T system," Proc. IEEE Int. Conf. on System on Chip (ICSOC), pp. 131-134, Sept. 2003.
10 NVIDIA corp., NVIDIA CUDA C Best Practices Guide 5, Oct. 2012.
11 NVIDIA corp., NVIDIA CUDA C Programming Guide 5, Oct. 2012.
12 NVIDIA corp., NVIDIA CUDA CUFFT Library, Oct. 2011.