您的位置 : 题目: Towards Architectures for the Next Decade: Modeling and Design of Hardware Accelerators
时间: 2017年09月14日上午 11:00-12:00
地点: 玉泉校区信电楼215会议室
报告人: Yakun SHAO 研究员
Abstract:
Traditional performance and energy scaling benefits based on technology improvements have slowed greatly. At the same time, the demand for computing capability is unsatisfied with new killer applications emerging in the domains of robotics, automotive, and machine intelligence. Lack of progress in technology scaling will necessarily place more demands on the computer architecture and software layers to deliver higher capability.
To overcome these challenges, hardware acceleration in the form of data path and control circuitry customized to particular algorithms or applications has surfaced as a promising approach, as it delivers orders of magnitude performance and energy benefits compared to general-purpose solutions. The importance of accelerators is already evident in today's energy-efficient mobile SoCs and network processors. These accelerator-centric architectures require quite different tools and design methodologies from general-purpose designs. In this talk, I will discuss some of my PhD work on developing new methodologies for workload characterization, rapid accelerator design, pre-RTL simulation, and system integration of accelerator-centric systems.
Biography:
Yakun SHAO is a Research Scientist at NVIDIA. She received her Ph.D. degree in Computer Science from Harvard University in 2016, working with Professor David Brooks and Professor Gu-Yeon Wei. Her primary research interests lie in the general area of computer architecture, with a particular focus on modeling and design for heterogeneous architectures. She received her B.S. degree in Electrical Engineering from Zhejiang University, China and her S.M. degree in Computer Science from Harvard University. Her previous experience includes internships at Intel Labs and IBM T.J Watson Research Center. Her paper was selected as one of the Top Picks in Computer Architecture in 2015. She is a Siebel Scholar and a recipient of the IBM Ph.D. Fellowship.
