iSwitch Computing

Dr. Jian Huang and collaborators from the University of Illinois have developed iSwitch, a technology to reduce latency bottlenecks in data center network communication. The technology is particularly relevant to AI applications such as reinforcement learning (RL)-based training, where frequent gradient aggregation typically requires a large number of network hops. By shifting aggregation to programmable switches, iSwitch results in a system-level speedup of more than 3.5x for both synchronous and asynchronous RL distributed training and also improves scalability.

Application

Networking datacenters

Benefits

iSwitch results in a system-level speedup of more than 3.5x for both synchronous and asynchronous RL distributed training and also improves scalability.