NDLI: Massive parallel LDPC decoding on GPU

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Massive parallel LDPC decoding on GPU

Content Provider	ACM Digital Library
Author	Falcão, Gabriel Sousa, Leonel Silva, Vitor
Abstract	Low-Density Parity-Check (LDPC) codes are powerful error correcting codes (ECC). They have recently been adopted by several data communication standards such as DVB-S2 and WiMax. LDPCs are represented by bipartite graphs, also called Tanner graphs, and their decoding demands very intensive computation. For that reason, VLSI dedicated architectures have been investigated and developed over the last few years. This paper proposes a new approach for LDPC decoding on graphics processing units (GPUs). Efficient data structures and an new algorithm are proposed to represent the Tanner graph and to perform LDPC decoding according to the stream-based computing model. GPUs were programmed to efficiently implement the proposed algorithms by applying data-parallel intensive computing. Experimental results show that GPUs perform LDPC decoding nearly three orders of magnitude faster than modern CPUs. Moreover, they lead to the conclusion that GPUs with their tremendous processing power can be considered as a consistent alternative to state-of-the-art hardware LDPC decoders.
Starting Page	83
Ending Page	90
Page Count	8
File Format	PDF
ISBN	9781595937957
DOI	10.1145/1345206.1345221
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2008-02-20
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Low-density parity-check codes Computer unified device architecture Parallel processing Cuda Graphics processing unit Ldpc
Content Type	Text
Resource Type	Article

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