TOPICAL DISCUSS
Wu Jianbang, Qiu Tian, Zhang Xin, Wu Peiwen, Lin Xiaoyan, Fu Xiao, Li Muyun, Ning Honglong
Integrated Circuits and Embedded Systems.
2023, 23(2):
7-11.
In the paper,the definition,advantages and current problems of tiny machine learning are introduced.From exclusive or general tiny machine learning deployment methods,microprocessor design based on ARM Cortex-M or RISC-V,and deployment algorithms based on neural architecture search,the existing problems are discussed and the research status is introduced.Looking forward to the future development of tiny machine learning,it is believed that a full-featured tiny machine learning deployment framework is needed in the future,and hardware research is more based on RISC-V and hardware neural network acceleration units to form microprocessors,and how to improve search efficiency and reduce neural architecture search time.Finally,on the basis of the above,some thoughts are put forward on how to improve and develop the tiny machine learning ecology.