AI on the Edge: Rethinking AI-based IoT Applications Using Specialized Edge Architectures

Understand

Edge computing has emerged as a popular paradigm for supporting mobile and IoT applications with low latency or high bandwidth needs.

• The attractiveness of edge computing has been further enhanced due to the recent availability of special-purpose hardware to accelerate specific compute tasks, such as deep learning inference, on edge nodes.
• In this paper, we experimentally compare the benefits and limitations of using specialized edge systems, built using edge accelerators, to more traditional forms of edge and cloud computing.
• Our experimental study using edge-based AI workloads shows that today's edge accelerators can provide comparable, and in many cases better, performance, when normalized for power or cost, than traditional edge and cloud servers.