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學術報告預告:面向圖像識別與機器學習的低功耗超大規模集成電路設計

發布時間:2019-05-2053棋牌172

報告題目:Energy-efficient VLSI design for image recognition and machine learning algorithms 面向圖像識別與機器學習的低功耗超大規模集成電路設計

報告人:安豐偉博士 (南方科技大學)

時間地點:2019521日上午1000-1130 工科E927

報告摘要:Nowadays, many computer-vision and machine-learning applications in portable devices such as robotics, smartphones, and autonomous vehicles are constrained by their real-time performance requirements. Meanwhile, the power consumption is also a critical factor for battery-powered systems. The VLSI design for image recognition and machine learning must take account of the processing speed and energy-efficiency simultaneously. In particular, embedded SRAM (static random-access memory) macros are important power-dissipation sources in image processing algorithms due to the high-capacitance buses and frequent accesses. To avoid the inductive bounce noise on the power supply and ground caused by large in rush/discharge currents in mode transitions of power-gating approach, in this research, a hardware-friendly algorithm with optimized SRAM utilization is developed to image recognition and machine learning algorithms. The prototype chips with energy-efficient VLSI architecture have been silicon-proved in 28/65/180nm CMOS technology with high integration density and memory-utilization efficiency for demonstrating the applicability in portable devices.

報告人簡曆:FENGWEI AN received the Ph.D. from Hiroshima University, Japan in 2013. He worked with the Graduate School of Engineering, Hiroshima University as an Assistant Professor from 2013 and as an Associate Professor from 2017. From April 2018 to March 2019, he worked with Panasonic Semiconductor Solutions Co., Ltd for DSP design of CIS and Time-of-Flight Cameras. Now, he is an Associate Professor in Southern University of Science and Technology. His research interests include reconfigurable computing, ultra-low power digital circuits, and systems, and embedded system architecture for image recognition and machine learning algorithms.

研究方向:安豐偉博士的主要研究领域是基于计算机视觉的低功耗边缘人工智能芯片设计,具体包括图像处理、图像识别、机器学习的超大规模数字集成电路设计和系统集成,并有在工业界的研究开发经验。

教育經曆

20133月獲日本廣島大學博士學位

20103月獲日本廣島大學碩士學位

20067月獲青島科技大學學士學位

工作經曆

2018.04~2019.03  日本京都松下半導體解決方案有限公司工程師

2017.04~2018.03  日本廣島大學副教授(特約)

2013.12~2017.03  日本廣島大學助理教授(特別任命)

2013.04~2017.11  日本廣島大學研究員