Elastic GPU processing for streaming video data

We study using multiple GPU devices to accelerate processing of streaming data. The amount of traffic on the Internet is rapidly rising. Much of this rise is due to media streams that need to be processed. However, the global growth rate of processing capacity is lagging behind. We see Fog computing, i.e., processing capacity attached directly to the nodes of the network, as one possibility to address this problem. In this paper, we present our approach to attach scalable processing capacity to network nodes. We use multiple generic purpose accelerators. To show the viability of our approach, we present our simulations and measurements related to a setup where multiple GPUs are attached to an NPU to accelerate processing of video streams. We show that GPU virtualization and communication batching can be used to get scalable processing.