Random Linear Network Coding on the GPU

The goal of this project is to implement network coding on OpenGL-enabled graphics cards. Network coding is an interesting approach to increase the capacity and robustness in multi-hop networks. The current problem is to implement random linear network coding on mobile devices which are limited in computational power, energy, and memory. Some mobile devices are equipped with a 3D graphics accelerator, which could be used to do most of the RLNC related calculations. Such a cross-over have already been used in computationally demanding research tasks as in physics or medicine. As a first step the project focuses on the implementation of RLNC using the OpenGL library and NVidia's Cg toolkit on desktop PCs and laptops. Several measurement results show that the implementation on the graphics accelerator is outperforming even the fastest CPU by a significant margin.


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