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通信论坛:Energy-Efficient Data Converter Design & On the Power of Preprocessing and Reconfigurable Networks
文:信息与通信工程学院 来源:信通学院 时间:2018-12-14 3473

  由信息与通信工程学院主办的“通信论坛”将邀请美国得克萨斯大学奥斯丁分校唐希源博士、奥地利维也纳大学Klaus-Tycho Foerster博士来校交流,欢迎广大师生参加!

  讲座一:

  主 题:Energy-Efficient Data Converter Design

  主讲人:唐希源 博士(University of Texas at Austin)

  时 间:2018年12月19日(周三)16:00

  地 点:清水河校区科研楼B302

  报告内容:

  Analog-to-Digital Converters (ADCs) are critical components as interfaces between the analog world and digital processor in modern system-on-chips (SoCs). Successive approximation register (SAR) ADC becomes popular as it is low power and digital scaling friendly. Three interesting techniques to further improve SAR ADC efficiency will be discussed in this talk.

  The specifications of the SAR ADCs are driven by different applications. For energy constraint applications, such as wireless sensors and biomedical implants, low-speed and moderate-resolution ADCs are required. A statistical noise estimation technique will be discussed. We will take advantage of thermal noise and achieve a Signal-to-Noise Ratio (SNR) enhancement.

  High-speed ADCs are widely used in measurement instruments, serial link transceivers, and wireless communication systems. A novel calibration free architecture is proposed to perform A/D conversion at a high speed while maintaining the power efficiency.

  The energy-efficient converter design expertise is leveraged to the sensor readout system. An ADC assisted Capacitance-to-Digital Converter (CDC) will be discussed at the end. By performing Time-Domain ΔΣM with a zoomed-SAR operation, this capacitance converter achieves > 2x energy efficient improvement compared to all prior works.

  主讲人简介:

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  Xiyuan Tang received the B.Sc. degree (Hons.) from the School of Microelectronics, Shanghai Jiao Tong University, Shanghai, China, in 2012, and the M.S. degree in electrical engineering from The University of Texas at Austin, Austin, TX, USA, where he is currently pursuing the Ph.D. degree. He was a Design Engineer with Silicon Laboratories, Austin, from 2014 to 2017, where he was involved in receiver design. His research interests include digitally assisted data converters, low-power mixed-signal circuits, and analog data processing.

  Mr. Tang received the National Scholarship in China in 2011. He serves as a reviewer for the IEEE TCAS-I, IEEE TVLSI, and IEEE Sensor Journal.

  讲座二:

  主 题:On the Power of Preprocessing and Reconfigurable Networks

  主讲人:Klaus-Tycho Foerster(Postdoctoral researcher,University of Vienna, Austria)

  时 间:2018年12月20日(周四)9:30

  地 点:清水河校区科研楼B302

  报告内容:

  In this talk, Klaus-Tycho Foerster will present some of his recent works on (1) preprocessing for decentralized network optimization (INFOCOM'19) and (2) for optimizing reconfigurable networks (SIGCOMM/ANCS'18), along with a short overview on some other current research, such as efficiently handling network failures.

  Regarding preprocessing, as communication networks are growing at a fast pace, the need for more scalable approaches to operate such networks is pressing. Decentralization and locality are key concepts to provide scalability. Existing models for which local algorithms are designed fail to model an important aspect of many modern communication networks such as software-defined networks: the possibility to precompute distributed network state. We take this as an opportunity to study the fundamental question of how and to what extent local algorithms can benefit from preprocessing.

  Regarding reconfigurable networks, we explore two directions, data centers and wide area networks. While prior work has shown the practical benefits of reconfigurable data center topologies, the underlying algorithmic complexity is not yet well understood. In particular, most reconfigurable topologies are hybrid, where parts of the network are reconfigurable (consisting of optical or wireless devices) while other parts are static (consisting of electrical switches). Current proposals enforce a routing policy that routes flows on either part “exclusively” by labeling flows as mice or elephant. We show that such artificial segregation in routing policy results in non-optimal paths and argue for algorithms that route packets across the network seamlessly.

  For wide area networks, we propose the idea of adapting the capacity of fiber optic links based on their signal-to-noise ratio. We investigate this idea by analyzing the SNR of over 8,000 links in an optical backbone for a period of three years. We show that the capacity of 64% of 100 Gbps IP links can be augmented by at least 75 Gbps, leading to an overall capacity gain of over 134 Tbps. Moreover, adapting link capacity to a lower rate can prevent up to 25% of link failures. Our analysis shows that using the same links, we get higher capacity, better availability, and 32% lower cost per gigabit per second. We also propose a corresponding traffic engineering system which in data-driven simulations improves the overall network throughput by 40% while also improving the average link availability.

  主讲人简介:

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  As of 2018, Klaus-Tycho Foerster is a postdoctoral researcher at the University of Vienna, Austria, working with Stefan Schmid. In 2017 he was a postdoc at Aalborg University, Denmark and a visiting researcher at Microsoft Research, Redmond, USA, working with Ratul Mahajan for Fall 2016. He received his PhD degree from ETH Zurich, Switzerland, in September 2016, supervised by Roger Wattenhofer in the Distributed Computing Group. His research focus evolves around algorithms and complexity in the areas of networking and distributed computing. He co-authored over 45 papers, at venues such as ACM SIGCOMM, IEEE INFOCOM, IEE/ACM Transactions on Networking, and IEEE Communications Surveys and Tutorials.


                  信息与通信工程学院

                   2018年12月14日 



编辑:杨棋凌  / 审核:林坤  / 发布:陈伟

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