Introduction to the lecture
The implementation of artificial intelligence (AI) algorithm needs strong computing power support, especially the large-scale application of deep learning algorithm, which requires higher computing power and energy efficiency. In recent years, academic and industrial circles at home and abroad have invested a lot of R & D resources in the field of AI chip design, and various AI chip architectures for different application scenarios have emerged. This lecture will mainly introduce many key technologies behind the design of AI chips, the technical characteristics of typical AI chips, and the new application fields of AI chips. Finally, the development of AI chip architecture is prospected.
Guest profile
Dr. Lin Jun (IEEE sensor member) graduated from the Department of physics, Nanjing University in 2010, and from the high university in 2015. He has obtained the doctor's degree in electronic engineering. At present, his main research directions are: low-power and high-performance artificial intelligence chip and system architecture, high-speed communication baseband signal processing algorithm and hardware architecture, agile chip design, etc. in IEEE Nearly 100 papers were published in mainstream magazines and top conferences in the field of integrated circuit design such as tvlsi / TCAS, among which nearly 40 papers were published in IEEE magazine, and more than 20 invention patents were applied for. Dr. Lin has won IEEE appcas08 Excellent Student Thesis Award, 2019 IEEE Computer Society annual symbol on VLSI (isvlsi) best Thesis Award, 2019 IEEE International signal processing systems (SIPS) best Thesis Award.
Lecture time
19:30 PM, April 24, 2020
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