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讲师
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讲座时间
讲者简介
Yao Chen is a Postdoc researcher at Advanced Digital Sciences Center (ADSC), Singapore, which is a research center of University of Illinois at Urbana-Champaign (UIUC) based in Singapore. He got his Bachelor and PhD at Nankai University from 2006 to 2016, respectively. His current research Interests including FPGA enabled High Performance Computing, High Level Synthesis, Distributed Systems and Wireless Sensor Networks. Some of his work also related to Internet of Things, Bioinformatics and High Precision/Accuracy Analog ASIC Design. For the details, please refer to https://microideax.github.io/.
摘要
The efficacy and effectiveness of Convolutional Neural Networks(CNNs) have been proven in a wide range of machine learning applications. However, the high computational complexity of CNNs presents a critical challenge towards their broader adoption in real-time and power-efficient scenarios. FPGAs are poised to take a significant role for high-performance and energy-efficient computation of CNNs for both mobile (e.g., UAVs, self-driving cars, and IoT devices) and cloud computing domains.
However, implementing an effective CNN system onto FPGAs efficiently remains problematic. The current cloud-based FPGAs with unique design constraints and architectural characteristics remain challenging. The Internet of Thing (IoT) devices, with strict constraints on hardware resources, power budgets, response latency, and manufacturing cost also further increases the difficulties.
To address these challenges, we have several different approaches, which are named as Cloud-DNN, T-DLA and uL2Q. The details will be presented in the talk.
主办单位
计算机与控制工程学院
承办单位
工业机器人应用福建省高校工程研究中心
协办单位
福建省信息处理与智能控制重点实验室
数字福建智能化生产物联网实验室
电子信息与控制工程研究中心
福州市机器人技术应用联合实验室
闽江学院互联网创新研究中心
闽江学院汇川科技物联网联合研究院
闽江学院计算机与控制技术研究所
闽江学院2011协同创新培育点“物联网技术与智能系统”