Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/69934
Title: Efficient decoding of QC-LDPC codes using GPUs
Authors: Zhao, Y
Chen, X
Sham, CW
Tam, WM
Lau, FCM 
Keywords: Belief propagation
CUDA
Graphics
Processing unit (GPU)
Low-density parity-check codes
LDPC decoder
Issue Date: 2011
Publisher: Springer
Source: Lecture notes in computer science (including subseries Lecture notes in artificial intelligence and lecture notes in bioinformatics), 2011, v. 7016, p. 294-305 How to cite?
Journal: Lecture notes in computer science (including subseries Lecture notes in artificial intelligence and lecture notes in bioinformatics) 
Abstract: In this work, we propose an efficient quasi-cyclic LDPC (QC-LDPC) decoder simulator which runs on graphics processing units (GPUs). We optimize the data structures of the messages used in the decoding process such that both the read and write processes can be performed in a highly parallel manner by the GPUs. We also propose a highly efficient algorithm to convert the data structure of the messages from one form to another with very little latency. Finally, with the use of a large number of cores in the GPU to perform the simple computations simultaneously, our GPU-based LDPC decoder is found to run at around 100 times faster than a CPU-based simulator.
Description: 11th International Conference on Algorithms and Architectures for Parallel Processing (ICA3PP'2011), Melbourne, Australia, 24-26 October 2011
URI: http://hdl.handle.net/10397/69934
ISBN: 978-3-642-24649-4
978-3-642-24650-0
ISSN: 0302-9743
EISSN: 1611-3349
DOI: 10.1007/978-3-642-24650-0_25
Appears in Collections:Conference Paper

Access
View full-text via PolyU eLinks SFX Query
Show full item record

SCOPUSTM   
Citations

3
Last Week
0
Last month
Citations as of Aug 20, 2018

Page view(s)

33
Last Week
3
Last month
Citations as of Aug 21, 2018

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.