TinyML: Current Progress, Research Challenges, and Future Roadmap

TinyML: tiny in size, BIG in impact!This paper highlights the current progress, challenges and open research opportunities in the domain of tinyML, benchmarking, and emerging applications for Edge-AI.

Saved in:
Bibliographic Details
Published in:2021 58th ACM/IEEE Design Automation Conference (DAC) pp. 1303 - 1306
Main Authors: Shafique, Muhammad, Theocharides, Theocharis, Reddy, Vijay Janapa, Murmann, Boris
Format: Conference Proceeding
Language:English
Published: IEEE 05.12.2021
Subjects:
Benchmark testing
Benchmarking
Deep Learning
Design automation
Edge-AI
Machine Learning
TinyML
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:TinyML: tiny in size, BIG in impact!This paper highlights the current progress, challenges and open research opportunities in the domain of tinyML, benchmarking, and emerging applications for Edge-AI.
DOI:10.1109/DAC18074.2021.9586232