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Events for April 03, 2014
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EE Seminar: Robust System Design
Thu, Apr 03, 2014 @ 10:30 AM - 12:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Yanjing Li, Research Scientist, Intel Labs
Talk Title: Robust System Design
Abstract: Malfunctions in electronic systems can have major consequences ranging from loss of data and services, to financial
and productivity losses, or even loss of human life. Such impacts continue to increase as systems become more
complex, interconnected, and pervasive. Hardware failures are especially a growing concern because:
1. Existing test and validation methods barely cope with today’s complexity. New techniques will be essential to
minimize the effects of defects and design flaws.
2. For coming generations of silicon technologies, several failure mechanisms that were largely benign in the
past are now becoming visible at the system level. A large class of future systems will require tolerance of hardware
errors during their operation.
Robust system design is required to ensure that future electronic systems, from supercomputers all the way to
embedded systems, perform correctly despite rising levels of complexity and disturbances. Traditional fault‐tolerant
computing techniques are generally very expensive, and often inadequate, for this purpose. I will present two
techniques that are essential for robust system design:
1. A new online self‐test and diagnostics technique, called CASP, which enables a system to test itself thoroughly
during normal operation to quickly detect and localize hardware failures. CASP is very thorough with respect to a
wide variety of test coverage metrics (96‐99.5%) while incurring only 1% area and power costs, and 3% performance
cost. In contrast, existing techniques suffer from low coverage (e.g., 70%), high area costs (e.g., 20%), or significant
performance penalties (e.g., 30%) including possible system unresponsiveness.
2. A new self‐repair technique to keep the system functioning correctly even in the presence of hardware failures.
Unlike naïve redundancy with very high (20%) area costs, this technique enables thorough self‐repair with only 7.5%
area impact, 3% power impact, and 0‐5% performance impact.
A key aspect of the approach to these techniques is the orchestration across multiple abstraction layers: physical
design, architecture, and system software. I will demonstrate the effectiveness and practicality of these techniques
using results from the industrial OpenSPARC T2 multi‐core design and the Intel Core i7 hardware platform. I will also
share recent experiences in implementing these techniques in the latest Intel designs.
Biography: Yanjing Li is a research scientist at Intel Labs and a visiting scholar at Stanford University. She received her Ph.D. in
Electrical Engineering from Stanford University. Her research interests include robust system design, energy‐efficient
systems, system validation and test, computer architecture, and system software. Dr. Li received the European Design
and Automation Association Outstanding Dissertation Award, the IEEE International Test Conference Best Student
Paper Award, and the IEEE VLSI Test Symposium Best Paper Award for novel research on robust system design, and
two Intel Divisional Recognition Awards for mobile processor designs that are being adopted by product groups at
Intel.
Host: Professor Murali Annavaram
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Janice Thompson
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EE-EP Seminar - Sam Emaminejad
Thu, Apr 03, 2014 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Sam Emaminejad, Stanford University
Talk Title: Detection and Actuation at Micro- and Nanoscales: Emerging Biomarker Sensors for Personalized Medicine
Abstract: Personalized medicine is transforming the field of clinical diagnosis. Unlike traditional diagnostic methods that have been reactive and dependent on patient’s apparent symptoms, personalized medicine relies on biomarkers to provide predictive and preemptive care with customized and more effective drug and therapy selection. Informative biomarkers include genes, proteins, and cells whose abundance in human samples are indicative of patient health. Detection of such micro- and nanoscale biomarkers requires biosensors that are equipped with actuation and sensing capabilities at length scales comparable to the size of these bioparticles. To this end, we exploit advanced micro- and nanofabrication techniques and combine high throughput microfluidic and electronic technologies to develop low-cost integrated biosensors geared toward point-of-care diagnostic applications.
In this talk, I will discuss parameters such as multiplexing, sensitivity, and specificity that govern the performance of biosensors. In relation to these parameters, I will present three platforms in which we have demonstrated actuation and sensing of bioparticles on both the micro- and nanoscales, using novel electronic solutions that enable point-of-care diagnosis. The first platform is a multiplexed protein detection system that is realized through enhancing dielectrophoresis force by two orders of magnitude to overcome protein-protein interactions. Next, we will demonstrate a novel contactless impedance sensing scheme to perform low-cost cytometry in whole blood. In the third platform, we will present a sample preparation system for delivery of proteins, with controlled orientation, purified from a complex biological sample to the surface of a quantum tunneling-based biosensor. I will conclude my talk with a discussion of future research directions which prelude my long term vision of developing wearable diagnostic devices for real-time biomarker monitoring.
Biography: Sam Emaminejad received his BASc (2009) and MS (2011) degrees in Electrical Engineering from the University of Waterloo and Stanford University, respectively. He is currently pursuing his PhD in Electrical Engineering at Stanford University, where he is working toward his thesis at the Stanford Genome Technology Center and Stanford School of Medicine. His research is focused on exploiting micro- and nanotechnologies to develop low-cost and integrated biosensing and bioeletronics platforms for personalized medicine applications. Sam has previously worked as an ASIC and Analog Designer in semiconductor companies such as STMicroelectronics and Analog Devices. Sam was awarded Natural Sciences and Engineering Research Council (NSERC) scholarship and was the recipient of Best Paper Award at the IEEE Sensors conference in 2013.
Host: EE-Electrophysics
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
