Isla Vista Remembrance Tribute Exhibit at the 2015 All Gaucho Reunion

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Special exhibit representing the compassion of Gauchos and community coming together

  • Thursday, April 23 8 a.m. – 5 p.m.
  • Friday, April 24 8 a.m. – 5 p.m.
  • Saturday, April 25 9 a.m. – 3 p.m.
  • Sunday, April 26 10 a.m. – noon

IV Remembrance Tribute

“Isla Vista Memorial Project Underway” (article)

UCSB Gradpost Interview with the curator, Melissa Barthelemy, UCSB History graduate student

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Professor Shuji Nakamura named a 2015 Global Energy Prize Laureate

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Nakamura receives the prestigious Russian prize for invention, commercialization and development of energy efficient white LED lightning technology

“I am so pleased that the Global Energy Prize committee has recognized my breakthrough work on InGaN LEDs, which has led to energy-efficient white LED lighting,” said Nakamura, who was one of three 2014 Nobel Prize winners in physics for the invention of the bright blue LED. This was an innovation that would lead to the creation of the white LED and the ability to save energy, reduce carbon emissions and provide a low energy, durable and sustainable light source for those with little or no access to electricity.

“We are so proud to congratulate our colleague Shuji Nakamura on this prestigious recognition as a Global Energy Prize Laureate,” said UC Santa Barbara Chancellor Henry T. Yang. “The applications and consequences of his pioneering work in solid-state lighting continue to grow, with far-reaching impact on fields ranging from information and communication, to energy and the environment, to health care and life sciences. By making it possible to bring affordable, energy-efficient lighting to developing countries, Professor Nakamura has made a tremendous humanitarian contribution to our world.”

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ECE Assistant Professor Dmitry Strukov interviewed by MIT Technology Review about the memristor and HP’s “The Machine”


In 2008 HP’s Dr. Stanley Williams’ research group created a tiny electronic device called the memristor, inventing a promising new form of data storage. He says the memristor will offer an unrivaled combination of speed, density, and energy efficiency.

CTO Martin Fink has put most of HP’s researchers to work on a new design for computers based on memristor memory and HP Enterprise is working on this risky research project in hopes of driving a remarkable comeback. Nearly three-quarters of the people in HP’s research division are now dedicated to a single project: a powerful new kind of computer known as “The Machine.” It would fundamentally redesign the way computers function, making them simpler and more powerful. If it works, the project could dramatically upgrade everything from servers to smartphones—and save HP itself.

Strukov, one of Williams’s former collaborators at HP, says memristors have yet to pass a key test. Strukov, an assistant professor at the University of California, Santa Barbara, and lead author on the 2008 paper announcing the memristor, says that while technical publications released by HP and SK Hynix have shown that individual memristors can be switched trillions of times without failing, it’s not yet clear that large arrays perform the same way. “That’s nontrivial,” he says.

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Exploration of Register and Cache-Level Nonvolatile Processor Design for Energy Harvesting Sensing System

Energy harvesting has been widely investigated as a promising method of providing power for ultra-low-power applications. Such energy sources include solar energy, radio- frequency (RF) radiation, piezoelectricity, thermal gradients, etc. However, the power supplied by these sources is highly unreliable and dependent upon ambient environment factors. Hence, it is necessary to develop specialized systems that are tolerant to this power variation, and also capable of making forward progress on the computation tasks.

With the emerging memory technologies, nonvolatile processors are manufactured with nonvolatile registers and can work reliably under the environments with frequency power interrupts, such as energy harvesting and wireless powered applications. What’s more, it also has the following advantages: I) zero-standby power; II) instant on and off; III) high resilience to power failures; IV) fine-grained power management support.

This talk will first present a fabricated nonvolatile processor based on the ferroelectric flip-flops to demonstrate the conceptual design. Measured results show that it can operate continuously even under power failures occurring at 20KHz with 3us restore time, which achieves 2-4 magnitudes improvement on the wakeup time and energy compared with the state-of-the-art processors. Furthermore, different architectures of nonvolatile processors are explored under different power traces and power management strategies for maximizing forward progress. Third, a nonvolatile sensing platform is developed and several interesting applications based on the unique nonvolatile processor are discussed. Finally, some research opportunities and challenges associated with the nonvolatile processors will be given out for collaborations.

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Rethinking Software for Non-volatile Processors on Energy Harvesting Embedded Systems

Energy harvesting is a favorable alternative to power future wearable devices, with its advantages in terms of size, weight and convenience. However, harvested energy is naturally unstable and thus introduces frequent program execution interruptions. To enable accumulative program execution, non-volatile processors demonstrate promising results. With the need of efficient backup and resumptions, non-volatile processor is different from traditional processors and necessitates new designs in both hardware and software. While a few works have been done in hardware level, little effort has been seen at the software level. In this talk, we explore software re-designs for non-volatile processors. First, two stack-oriented optimizations are presented to reduce the content to back up prior to power failure. As a result, backup and resumption can be done faster with smaller required size of non-volatile memory. Then, based on the observation that the backup procedure may induce errors, a consistency-aware check-pointing scheme is proposed to locate and eliminate the potential errors. We believe that this is the beginning of a series of software re-designs, which are necessary for non-volatile processors, to enable its wide-spread application in future energy harvesting powered embedded systems.

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Professor Kaustav Banerjee selected by National Academy of Engineering (NAE) for Frontiers of Engineering Symposium

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Banerjee one of only 60 engineers selected by the National Academy of Engineering to attend its prestigious German-American Frontiers of Engineering (GAFOE) Symposium in Potsdam, Germany, from April 16-18

The Frontiers of Engineering (FOE) program brings together through 2-1/2 day meetings a select group of emerging engineering leaders from industry, academia, and government labs to discuss pioneering technical work and leading edge research in various engineering fields and industry sectors. Participation in the FOE symposia is by invitation only following a competitive nomination and selection process.

The GAFOE program was started in 1998. Since then, GAFOE symposia have been held every year in locations alternating between Germany and the United States. The GAFOE program is carried out in cooperation with the Alexander von Humboldt Foundation.

Professor Banerjee who directs the Nanoelectronics Research Lab, is internationally recognized as a visionary and a leading innovator in the field of nanoelectronics.

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ECE Professor Jerry Gibson interviewed for Scientific American article on cell phone call quality

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To understand problems with call quality and how they are being addressed, Scientific American interviewed Jerry Gibson, professor of electrical and computer engineering at the University of California, Santa Barbara

Interview with UCSB ECE Prof. Jerry Gibson
(edited transcript)

Why is cell phone call quality so bad?
It is primarily the service providers. A key point to note is that the base station/base station controller, now called eNodeB [for Evolved Node B] in LTE, is all-powerful. That is, eNodeB makes all of the decisions about how much bandwidth each handset gets no matter how good a channel connection a handset may have. Also, base station behaviors are not standardized—that is, no one really knows how they are making these decisions. They take into account how loaded the cell site is and how loaded adjacent cell sites are, plus other network data and other things when allocating bandwidth. A couple of rules providers appear to follow are: Don’t drop a call in progress, and don’t block any new calls if at all possible. This means that the base station allocates bandwidth conservatively, and thus the voice codec in the handset may operate at a lower than desirable rate.

What is the big focus for service providers?
One—video is king these days, so video sucks up lots of bandwidth. For video, the service providers do not want you to have to wait for buffering, particularly after you have started to view a video. Second, cell sites/base stations cost money, so deployments of new cells are not done lightly. The latter leads to poor RF [radio frequency] connectivity in different areas for different providers.

What’s at stake if we continue to have terrible call quality?
I don’t think the service providers feel voice quality is their main problem today. They want traffic, and video is big traffic compared to voice. Video is expected to dominate mobile data in the future so it is important to their business. The current question of service providers is how to collect money per bit of data. What they say is: “How do we monetize video?”

What are some of the more promising projects aimed at improving call quality?
For the latest generation of cellular, LTE, a new voice codec is being developed. It is designated enhanced voice services [EVS]. It will cover variable [wider] bandwidths so it will be better for music and mixed voice and music content. It has many new codec rates, plus better VoIP [voice over Internet protocol] factors such as packet loss concealment [used to used to mask the disruptive effects of lost or discarded data packets] and jitter buffer management. [“Jitter” refers to variations in the length of time to deliver data packets.] But the standard will take awhile to get into deployments everywhere by service providers.

When fully deployed, LTE with EVS will be a big improvement—if video traffic does not take all of the bandwidth wherever you are, causing eNodeB to only allocate your voice call a low rate. In some ways the approach of service providers is understandable. No one wants a call dropped and no one wants their calls to be blocked [unable to get through]. Plus, video is something everyone appears to want on their mobile device.

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Nanoelectronics Research Lab (NRL) researchers release compact model for atomically-thin transistors

image from NEEDS
Researchers from ECE’s Nanoelectronics Research Lab (NRL) have recently released the first physics-based SPICE compatible compact model for 2D material based transistors in collaboration with NEEDS deployed on

Two-dimensional (2D) and layered semiconductors belonging to the family of transition metal dichalcogenides (TMD) have emerged as promising channel materials for future unprecedented electronic, optoelectronic and sensor applications. 2D semiconducting TMDs offer several key advantages over bulk semiconductors (or 1D materials such as nanotubes and nanowires) with variable but uniform band gaps.

Besides, these atomically-thin TMDs have inherent flexibility and transparency, rendering them attractive to display electronics. These materials additionally have pristine surfaces that can boost device performance, especially in nanoscale transistors.

Compact models are essential for building circuits and systems. Recently, ECE researchers from the Nanoelectronics Research Lab, led by Professor Kaustav Banerjee have built the first detailed compact model specifically designed for such atomically-thin channel field-effect transistors (FETs). Their physics based and SPICE compatible compact model can be employed for efficient exploration of circuits based on 2D TMD FETs as well as for performance evaluation and optimization of such transistors. The UCSB 2D FET compact model provides a crucial platform for building future nanomodular systems based on emerging 2D layered materials.

The compact model has been released on the NEEDS (Nano-Engineered Electronic Device Simulation Node) website hosted by Purdue University’s nanoHub, by ECE PhD student and NRL member Wei Cao.

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2014 Nobel laureate Shuji Nakamura to lecture on April 28th on the development of the bright blue LED

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UCSB Materials / ECE professor and inventor of the bright blue LED, Shuji Nakamura to talk about the “Invention of Blue LED, Laser and Solid State Lighting.” The lecture will be at UCSB’s Campbell Hall on Tuesday, April 28 at 7:30 p.m. The lecture is free and open to the public.

LEDs (light-emitting diodes) have become ubiquitous, and are favored for their energy savings capability. In addition, their versatility makes them the lighting of choice for electronic devices, smart buildings, vehicles, displays, public areas and industrial and commercial settings. Their durability has led also to their use in inhospitable and off-the grid environments where artificial light is both scarce and highly necessary.

Yet it wasn’t until recently that LEDs gained widespread use. Since their invention in the 1960s, LEDs, which were initially available in red, then green, orange and yellow, gained popularity as manufacturing methods improved. However the lack of a complete spectrum of colors limited their application, and it became clear that blue, a primary color necessary for white lighting, needed to be developed.

It also became clear that the blue LED was much more difficult to invent than its predecessors. So difficult, in fact, that in some circles it was deemed impossible.

In this public lecture, Nakamura will outline not only the technical challenges that accompanied his quest to create the blue LED but also the obstacles he faced to accomplish what many around him said couldn’t be done. It’s a journey that begins with Nakamura as a recent graduate, working at a young Japanese manufacturing company in the late 1970s and leads him all the way to Stockholm in 2014 as a Nobel Prize winner in physics. Along the way he has received numerous accolades and is recognized worldwide for his innovations that ultimately paved the way for the white LED light.

Nakamura’s talk will feature live demonstrations onstage and an opportunity for audience members to ask questions.

Pre-signed copies of “Brilliant,” a book by technology writer Bob Johnstone that chronicles Nakamura’s endeavor to invent the blue LED, will be available for purchase at the event.

For more info, call UCSB Arts & Lectures at (805) 893-3535 or visit

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Efficient Implementation of Neuromorphic Systems with Emerging Device Technologies

Nowadays with unbounded expansion of digital world, powerful information processing systems governed by deep learning algorithms are becoming more and more popular. In this situation, usage of fast, powerful, intelligent and trainable deep learning methods seems critical and unavoidable. However, despite of their inherent structural and conceptual differences, all of these intelligent methods and systems share one common property i.e. having enormous number of trainable parameters. However, from a hardware point of view, the size of a practical computing system is always determined based on available resources. In this dissertation, we study these deep learning methods from a hardware point of view and investigate the possibility of their hardware implementation based on two new emerging technologies i.e. resistive switching and floating gate (flash) devices. For this purpose, memristive devices are fabricated with high density in crossbar structure to create a network which then trained with modified RPROB rule to successfully classify images. In addition, biologically plausible spike-timing dependent plasticity rule and its dependence to initial state is demonstrated experimentally on these nano-scale devices. Similar procedure is followed for the other technology, i.e. flash devices. We modified and fabricated the conventional design of digital flash memories which provide us with the ability of individual programming of floating-gate transistors. Having large-scale neural networks in mind, an efficient and high speed tuning method is developed based on acquired dynamic and static models which are then tested experimentally on commercial devices. We have also experimentally investigated the possibility of implementing vector-to-matrix multiplier using these devices which is the main building block of most deep learning methods. Finally, a multi-layer neural network is designed and fabricated using this technology to classify handwritten digits.

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