Massive parallelization technique for random linear network coding
- Authors
- Choi, S.-M.; Park, J.-S.
- Issue Date
- 2014
- Publisher
- IEEE Computer Society
- Keywords
- GPGPU; Network Coding; Parallel algorithm
- Citation
- 2014 International Conference on Big Data and Smart Computing, BIGCOMP 2014, pp.296 - 299
- Journal Title
- 2014 International Conference on Big Data and Smart Computing, BIGCOMP 2014
- Start Page
- 296
- End Page
- 299
- URI
- https://scholarworks.bwise.kr/hongik/handle/2020.sw.hongik/16423
- DOI
- 10.1109/BIGCOMP.2014.6741456
- ISSN
- 0000-0000
- Abstract
- Random linear network coding (RLNC) has gain popularity as a useful performance-enhancing tool for communications networks. In this paper, we propose a RLNC parallel implementation technique for General Purpose Graphical Processing Units (GPGPUs.) Recently, GPGPU technology has paved the way for parallelizing RLNC; however, current state-of-the-art parallelization techniques for RLNC are unable to fully utilize GPGPU technology in many occasions. Addressing this problem, we propose a new RLNC parallelization technique that can fully exploit GPGPU architectures. Our parallel method shows over 4 times higher throughput compared to existing state-of-the-art parallel RLNC decoding schemes for GPGPU and 20 times higher throughput over the state-of-the-art serial RLNC decoders. © 2014 IEEE.
- Files in This Item
- There are no files associated with this item.
- Appears in
Collections - College of Engineering > Computer Engineering > Journal Articles
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.