  GPU remoting is a promising technique for supporting AI applications.
Networking plays a key role in enabling remoting. However, for efficient
remoting, the network requirements in terms of latency and bandwidth are
unknown. In this paper, we take a GPU-centric approach to derive the minimum
latency and bandwidth requirements for GPU remoting, while ensuring no (or
little) performance degradation for AI applications. Our study including
theoretical model demonstrates that, with careful remoting design, unmodified
AI applications can run on the remoting setup using commodity networking
hardware without any overhead or even with better performance, with low network
demands.
