Enabling Design Methodologies and Future Trends for Edge AI: Specialization and Codesign
Cong Hao, Jordan Dotzel, Jinjun Xiong, Luca Benini, Zhiru Zhang, Deming Chen
Abstract
This work is an introduction and a survey for the Special Issue on Machine Intelligence at the Edge. The authors argue that workloads that were formerly performed in the cloud are increasingly moving to resource-limited edge computing systems, which raises a new set of challenges for machine learning as well as new opportunities. The topic is introduced by means of building blocks ranging from edge fundamentals to edge AI enabling methodologies as well as future trends and challenges.
Topics & Concepts
Enhanced Data Rates for GSM EvolutionComputer scienceCloud computingData scienceSet (abstract data type)Edge computingRangingResource (disambiguation)Artificial intelligenceSoftware engineeringTelecommunicationsOperating systemComputer networkProgramming languageIoT and Edge/Fog ComputingAdvanced Neural Network ApplicationsData Stream Mining Techniques