Implementation of random linear network coding using NVIDIA'S CUDA toolkit
Research output: Contribution to book/Conference proceedings/Anthology/Report › Conference contribution › Contributed › peer-review
Contributors
Abstract
In this paper we describe an efficient GPU-based implementation of random linear network coding using NVIDIA's CUDA toolkit. The implementation takes advantage of the highly parallel nature of modern GPUs. The paper reports speed ups of 500% for encoding and 90% for decoding in comparison with a standard CPU-based implementation.
Details
Original language | English |
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Title of host publication | Networks for Grid Applications |
Editors | Anastasios Doulamis, Joe Mambretti, Ioannis Tomkos, Theodora Varvarigou |
Pages | 131-138 |
Number of pages | 8 |
ISBN (electronic) | 978-3-642-11733-6 |
Publication status | Published - 2010 |
Peer-reviewed | Yes |
Externally published | Yes |
Publication series
Series | Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering |
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Volume | 25 LNICST |
ISSN | 1867-8211 |
Conference
Title | 3rd International ICST Conference on Networks for Grid Applications, GridNets 2009 |
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Duration | 8 - 9 September 2009 |
City | Athens |
Country | Greece |
External IDs
ORCID | /0000-0001-8469-9573/work/162348324 |
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Keywords
ASJC Scopus subject areas
Keywords
- Cuda, Gpgpu, Parallelization, Random linear network coding