Solid State Circuits Society

Winter 2017 Chapter Activities Report

See the original article from IEEE Solid State Circuits Magazine, Vol. 9, Issue 1 here.

Recent Silicon Valley SSCS Chapter Activities: Seminars, Webinars, and Distinguished Lecturer Talks

by Mojtaba Sharifzadeh, Chapter Vice Chair, Silicon Valley SSCS Chapter

The IEEE Solid-State Circuits Society (SSCS) Santa Clara Valley Chapter held a number of seminars, webinars, and Distinguished Lecturer (DL) talks in the summer and fall of 2016. This article is just a highlight of recent events held by the Chapter. Please feel free to contact the SSCS Silicon Valley Chapter if you are interested in presenting at our meetings, would like to attend the Chapter events, or would like to volunteer for the Chapter.

18 August 2016: DL Seminar “Enabling and Exploiting Machine Learning in Ultra-Low-Power Devices” by Prof. Naveen Verma, Princeton University

Speakers at Silicon Valley SSCS Chapter consist of experts from academia and industry. Intelligent systems are of high interest today in the valley, and the Chapter decided to hold a seminar on this topic in the summer of 2016 to present the state of the art in academia from a hardware perspective. Prof. Naveen Verma, SSCS DL from Princeton University, held the seminar “Enabling and Exploiting Machine Learning in Ultra-Low-Power Devices,” in which he explained his research work on low-power digital circuits and systems. He showed the results of his research by applying it to a classical and real-life machine learning problem of recognizing hand-written numbers. The results were very exciting, showing significant improvement in accuracy and speed of recognition by improving the hardware. This seminar attracted many professionals from academia and industry in Silicon Valley, and it was sold out weeks before the seminar date with approximately 200 attendees in the venue and many more watching the live broadcast online. This event was also cosponsored by the IEEE Signal Processing Society, IEEE Circuits and Systems Society, and IEEE Computer Society Chapters and will be available to SSCS members later this year on the Society website as a webinar.

Abstract

Increasingly, sensing devices are required that are not only capable of acquiring complex embedded signals but also capable of performing highvalue analyses on the signals they acquire. Machine-learning algorithms play an important role because they enable modeling and inference over signals that may otherwise be too complex to model through analytical methods. This talk looked at such algorithms first from the perspective of enabling them within severely resource-constrained devices and then from the perspective of exploiting them toward more resource-efficient implementations of systems. Through several systems based on custom IC prototypes, this talk explores many avenues that machinelearning algorithms give rise to for addressing system bottlenecks. The focus on resource-efficient implementations directs us to use the algorithms in new ways, then leads to unconventional circuit architectures.

22 September 2016: “Trends in Broadband Converters and the Quest for the Software-Defined System” by David Robertson, Analog Devices

Data converters are one of the most interesting components in classical analog/mixed-signal design. The SSCS Silicon Valley Chapter invited Dave Robertson, one of the experts and long-time veterans in this field and the product and technology director for the high-speed converter group at Analog Devices. The seminar covered a comprehensive background of data converters to date with focus on broadband data converters targeting softwaredefined systems. Approximately 100 circuit and system design professionals in Silicon Valley attended this talk and became engaged with the speaker on recent advancements in softwaredefined systems with some Maxim employees watching the live broadcast online. The Chapter acknowledges the generous sponsorship of Maxim Inc. for providing the venue and audio/visual support for recording the event. There will be a webinar for this seminar on the SSCS website available to Society members.

Abstract

The concept of a software-defined radio, software-defined instrument, or any software-defined system is to move all the signal processing functions into the digital/software domain, thereby making the system highly reconfigurable. The principle is simple enough, but actually realizing workable systems is challenging since the performance demands on the data converters can be daunting, not only in bandwidth but in dynamic range. This talk will explore some of the progress that has been made over the last 15 years, with perspectives on both the driving applications and how converter technology has advanced in an effort to meet the applications challenges.

20 October 2016: DL Seminar “Demystifying Linear Time-Varying Circuits” by Shanthi Pavan, Indian Institute of Technology-Madras

Time-varying linear circuit components and systems have always been a challenging dilemma for most circuit and system designers. In this seminar, Prof. Shanthi Pavan, Indian Institute of Technology (IIT)-Madras, tried to answer many of these challenges in a technical forum with professionals in industry. More than 100 circuit design professionals from various companies in Silicon Valley attended the talk, and some Maxim employees watched the live broadcast online. The speaker arranged the seminar as a comprehensive and interactive short course format, with the attendees engaged in learning. He covered many aspects of time-varying linear systems from toplevel intuition to detailed mathematical equations as well as many interesting real-life design examples. This seminar will also be available as an SSCS webinar in the spring of 2017. Please feel free to attend the webinar and ask your long-time design questions live online from Prof. Pavan after the webinar in the dedicated Q&A session.

Abstract

An analog/mixed-signal designer en – counters time-varying circuits everywhere—sample-and-holds, chopper stabilized amplifiers, mixers, switchedcapacitor amplifiers and filters, discrete and continuous-time delta-sigma modulators, and N-path filters. The analysis of signals and noise in these circuits is often associated with messy mathematics and algebra. This talk aims to demystify linear (periodically) time-varying circuits. Starting from first principles, intuition behind various aspects of timevarying circuits and systems will be given. This intuition is illustrated with case studies of practical circuits and systems, like chopper-stabilized amplifiers and continuous-time deltasigma modulators.

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