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Date: August 14, 2018
Location: Hsinchu, Taiwan
The Cadence User Conference, CDNLive Taiwan, on August 14, 2018, was a popular and successful event with over 1000 attendees. In addition, the Academic Network had their first ever Academic Track, from 1:30pm-5:00pm, moderated by Jess Yang from DSG. There were a total of 4 academic speakers that filled the conference room for the entire time, covering a variety of topics along the theme of AI Research and the Academic Network.
The day started with Dr. Tian-Sheuan Chang, the Deputy Director of the National Chip Implementation Center and Professor of Electronics Engineering at the National Chiao Tung University, talking about AI Trends and CNN research & CIC collaboration with Cadence. He shared his experiences on a variety of efficient CNN hardware accelerator designs with resource constraints.
The next speaker for the Academic Track was Dr. Jing-Jia Liou, Professor and Chair of Department of Electrical Engineering from National Tsing Hua University, who spoke about Optimizing Farneback Optical Flow Accelerators with HLS Flow. He shared how using Stratus High-Level Synthesis for teaching and fundamental research can make it convenient to evaluate architectures, both at module level and system level, and more efficient at RTL implementation for DSP algorithms.
Dr. Yean-Ru Chen, former Cadence Application Engineer for JasperGold, now Assistant Professor in the Department of Electronics Engineering at National Cheng Kung University, hosted the third Academic Track session. She spoke about Formal Verification in the Academic Field, discussing her academic research, the advancements in formal verification technology, both theoretical concepts and application training, and the next steps in the coming years.
The last session of the day was hosted by Weibin Ding, a Cadence Software Engineering Group Director of the Digital Implementation Group. He asked the question, “Can Deep Reinforcement Learning Produce Better Results on Digital Routing? and addressed the Challenges of Physical Implementation and Machine Learning Opportunities for Advanced Technology.
Thank you to the many participants and attendees who made the event first Academic Track at CDNLive Taiwan a success. The Academic Network looks forward to many more years of participating in CDNLive, which brings together users, developers, and experts for networking and sharing of knowledge and best practices in the Electronic Design Automation industry.