Energy Efficient VLSI Circuits for Machine Learning On-chip

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• Hao Yu (Southern University of Science and Technology, China)
• Monday 30 September 2019, 16:00-17:00
• Level 9 Seminar Room, EEE Dept..

If you have a question about this talk, please contact George A Constantinides.

The machine-learning based data analytics to support a cloud intelligence (such as Google’s αGo) has already gone beyond the scalability of the present computing technology and architecture. The current deep learning based method is not efficient and requires huge consumption of data and power, which has a long latency running on data servers. With the emergence of autonomous vehicles, unmanned aerial vehicles and robotics, there is a huge demand to only analyze a necessary sensed data with small latency and low power at terminal devices. In this talk, we will discuss efficient machine-learning algorithms such as fast least-squares method, binary and tensory convolutional neural network method, with according prototyping accelerator developed in FPGA and CMOS -ASIC chips, which has potential to outperform traditional GPU devices. The mapping on future RRAM device will be also briefly addressed.

Speaker Bio: Dr. Yu obtained his B.S. degree from Fudan University (Shanghai China), and obtained M.S/Ph. D degrees both from electrical engineering department at UCLA , with major of integrated circuit and embedded computing. He was a senior research staff at Berkeley Design Automation (BDA) at Silicon Valley, and then with Nanyang Technological University (NTU) at Singapore. He has joined Southern University of Science and Technology (SUSTech) at China in 2017 for founding School of Microelectronics.

Dr. Yu has ~240 peer-reviewed and referred publications [conference (163) and journal (80)], 7 books, 1 best paper award in ACM Transactions on Design Automation of Electronic Systems (TODAES), 1 best paper in IEEE Biomedical circuits and systems, 3 best paper award nominations (DAC’06, ICCAD ’06, ASP DAC’12), 3 student paper competition finalists (SiRF’13, RFIC ’13, IMS ’15), 2 keynote talks, 1 inventor award from semiconductor research cooperation (SRC). He is Distinguished Lecturer of IEEE Circuit and System (2017), Associate Editor of Elsevier Integration, the VLSI Journal (2016-), Elsevier Microelectronics Journal (2016-), Nature Scientific Reports (2016-), ACM Trans. on Embedded Computing Systems (2017-) and IEEE Trans. on Biomedical Circuits and Systems (2017-), and Technical Program Committee member of several conferences (CICC’17-, DAC ’15-, DATE ’15-, ICCAD ’17-, ISLPED ’17-, A-SSCC’13-, BioCAS’16- etc.). His main research interest is about smart energy-efficient data analytics, links and sensors with multi-million government and industry funding. He is a senior member of IEEE and member of ACM .

This talk is part of the CAS Talks series.

This talk is included in these lists:

• Andrea Picciau's list
• CAS Talks
• Circuits and Systems Group: Internal Seminars
• Level 9 Seminar Room, EEE Dept.

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