基於GPU之LDPC架構的分析應用

近年來在通訊領域裡，由於不同體制的存在，使得越來越多的新系統不斷出現，這讓傳統上的硬體設計漸漸失去其優勢，而為了因應此種問題，一種稱為「軟體無線電」的新概念應運而生；在傳統上，我們以硬體解決了「準確」、「快速」和「大量」這三大問題，然而為了因應最新的通訊發展趨勢，我們重新使用軟體來替換掉硬體，這使得舊有的軟體問題「快速」和「大量」浮現了出來。本論文將實現一種通訊上的編解碼架構LDPC（Low density parity check，低密度奇偶校驗碼）的解碼部分，並將之應用在軟體無線電（Software Defined Radio）上，由於LDPC架構極為適合平行，所以本文利用新的平行技術CUDA（Compute Unified Device Architecture，統一計算架構）進行加速以解決軟體效能低落的問題；在一般上，軟體無線電是以多個CPU來平行加速，但是CP值較低，所以本文提出利用GPU來取代CPU以改善此現象；本研究會對兩種解碼演算法SPA（Sum-Product Algorithm，和積演算法）與MS（Min-Sum Algorithm，最小和演算法）進行測試，並分析在不同GPGPU和不同平行架構下的異同。

關鍵字

GPU ； CUDA ； LDPC

並列摘要

Recently, in communication field, because of the existence of different systems, more and newer systems appear constantly, which makes traditional design lost their advantages gradually. To solve these questions, a new concept "Software Defined Radio" is proposed. Traditionally, we use hardware to solve these issues such as "accuracy", "fast" and "volume". However, for the newest trend of communication development, we reuse the software to replace the hardware, which makes some old software questions appear such as "fast" and "volume". Our thesis will realize structural LDPC (Low density parity check, low density odd-even check-up yard) on a kind of communication decoding, which will been applied to SDR (Software Defined Radio). Because LDPC structure is extremely suitable for paralleling, we will use a new parallel technology "CUDA" (Compute Unified Device Architecture, calculate the structure in unison) to speed up the process of solving low efficiency. Generally, SDR speed up the work by numerous CPUs, but CPI (Cost Performance Index) is low relatively. Our thesis makes use of GPU to replace CPU to improve this phenomenon. We perform and measure for both SPA (Sum-Product Algorithm) and MS(Min-Sum Algorithm), and analyze the similarities and differences under different GPGPUs and parallel structures.

並列關鍵字

GPU ； CUDA ； LDPC

參考文獻

[1] Moon, Todd K., “Error Correction Coding Mathematical Methods”, John Wiley & Sons, 634-379

[2] Falcao G, Yamagiwa S, Silva V et al., “Parallel LDPC decoding on GPUs using a stream-based computing approach,” JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY, 24(5): 913-924 Sept. 2009

[3] R. G. Gallager, “Low Density Parity Check Codes,”. IRE. Trans. Inf. Theory. IT:8:21-28, Jan. 1962

[4] D. J. C. MACKAY, “Near Shannon limit performance of Low Density Parity Check Codes,” Electron. Lett., vol. 33 , pp. 457-458, Mar. 1997

[5] Bormin H, Jarno M, Hyunjong O, H-L A.H., “Development of a GPU-based High-Performance Radiative Transfer Model for the Infrated Atmospheric Sounding Interferometer (IASI)”, Journal of Computational Physics

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基於GPU之LDPC架構的分析應用

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