Shift-BNN: Highly-Efficient Probabilistic Bayesian Neural Network Training via Memory-Friendly Pattern Retrieving
This paper was presented in 54th IEEE/ACM International Symposium on Microarchitecture(MICRO-2021).
Who am I?
I am a first-year PhD student at University of Sydney (USYD), Australia. My supervisor is Shuaiwen Leon Song. My research interests include Software-Hardware Co-Design, Computer Architecture and Machine Learning System. I obtained both Bachelor's degree (2018) and Master's degree (2021) in Computer Science from University of Science and Technology of China (USTC), Hefei, China. I was successfully selected for the Talent Program of the School of Computer Science, USTC, as an undergraduate. Besides, I was selected as an outstanding graduate of USTC. In addition to being a PhD student at USYD, I am also a research intern in Alibaba Cloud under the supervision of Shuaiwen Leon Song at USYD and Zhen Zheng at Alibaba Cloud.
Recent Work
η-LSTM: Co-Designing Highly-Efficient Large LSTM Training via Exploiting Memory-Saving and Architectural Design Opportunities
This paper has been presented in ACM/IEEE 48th Annual International Symposium on Computer Architecture (ISCA-2021).
(Thesis) The design and implementation of a lightweight automata processor.
This thesis is the Dissertation of my Master's Degree, which is extended from my DATE-2021 paper(LAP).
LAP: A Lightweight Automata Processor for Pattern-Matching Tasks
This paper has been presented in Design, Automation and Test in Europe Conference(DATE 2021).
Get In Touch
Feel free to contact me through email.