Parallel Nonbinary LDPC Decoding on GPU

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dc.citation.conferenceDate2012en_US
dc.citation.conferenceName2012 IEEE Asilomar Conference on Signals, Systems, and Computersen_US
dc.citation.locationPacific Grove, GAen_US
dc.contributor.authorWang, Guohuien_US
dc.contributor.authorShen, Haoen_US
dc.contributor.authorYin, Beien_US
dc.contributor.authorWu, Michaelen_US
dc.contributor.authorSun, Yangen_US
dc.contributor.authorCavallaro, Joseph R.en_US
dc.date.accessioned2012-12-05T16:04:28Zen_US
dc.date.available2012-12-05T16:04:28Zen_US
dc.date.issued2012-12-01en_US
dc.description.abstractNonbinary Low-Density Parity-Check (LDPC) codes are a class of error-correcting codes constructed over the Galois field GF(q) for q > 2. As extensions of binary LDPC codes, nonbinary LDPC codes can provide better error-correcting performance when the code length is short or moderate, but at a cost of higher decoding complexity. This paper proposes a massively parallel implementation of a nonbinary LDPC decoding accelerator based on a graphics processing unit (GPU) to achieve both great flexibility and scalability. The implementation maps the Min-Max decoding algorithm to GPU’s massively parallel architecture. We highlight the methodology to partition the decoding task to a heterogeneous platform consisting of the CPU and GPU. The experimental results show that our GPUbased implementation can achieve high throughput while still providing great flexibility and scalability.en_US
dc.description.sponsorshipNational Science Foundation (NSF)en_US
dc.identifier.citationG. Wang, H. Shen, B. Yin, M. Wu, Y. Sun and J. R. Cavallaro, "Parallel Nonbinary LDPC Decoding on GPU," 2012.en_US
dc.identifier.doihttp://dx.doi.org/10.1109/ACSSC.2012.6489229en_US
dc.identifier.urihttps://hdl.handle.net/1911/68437en_US
dc.language.isoengen_US
dc.publisherIEEEen_US
dc.subjectGPUen_US
dc.subjectOpenCLen_US
dc.subjectnonbinaryen_US
dc.subjectLDPCen_US
dc.subjecterror correcting codesen_US
dc.subjectparallel architectureen_US
dc.titleParallel Nonbinary LDPC Decoding on GPUen_US
dc.typeConference paperen_US
dc.type.dcmiTexten_US
dc.type.dcmiTexten_US
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