GPU based IP forwarding

Abstract: This thesis was about investigating if it is feasible to implement an IP-forwarding data plane on a GPU. A GPU is energy efficient compared to other more powerful processors on the market today and should in theory be efficient to use for routing purposes. An IP-forwarding data plane consist of several things where we focused on some of the concepts. We have implemented IP-forwarding lookup operations, packet header changes, prioritization between different packets and a traffic shaper to restrict the packet throughput. To test these concepts we implemented a prototype, on a Tegra platform, in CUDA and evaluated its performance. We are able to forward 28 Mpackets/second with a best case latency of 27 µS given local simulated packets. The conclusions we can draw of this thesis work is that using a GPU for IP-forwarding purposes seems like an energy efficient solution compared to other routers on the market today. In the thesis we also tried the concept of only launching the GPU kernel once and let it be infinite which shows promising results for future work.