News

ECE Prof. Kaustav Banerjee’s research on 3D integration with 2D materials featured in The UCSB Current

January 6th, 2020

illustration of a city with chips
Banerjee and researchers propose 3D integration with 2D materials
It’s a well-known observation: The number of transistors on a microchip will double roughly every two years. And, thanks to advances in miniaturization and performance, this axiom, known as Moore’s Law, has held true since 1965, when Intel co-founder Gordon Moore first made that statement based on emerging trends in chip manufacturing at Intel.

However, integrated circuits are hitting hard physical limits that are rendering Moore’s Law obsolete — elements on a dense integrated circuit (IC) can get only so small and so tightly packed together before they begin to interfere with each other and otherwise lose their functionality.

“Apart from fundamental physical limits to the scaling of transistor feature sizes below a few nanometers, there are significant challenges in terms of reducing power dissipation, as well as justifying the incurred cost of IC fabrication,” said Kaustav Banerjee, a professor of electrical and computer engineering at UC Santa Barbara. As a result, the very devices that we rely on for their steadily improving performance and versatility — computers, smartphones, internet-enabled gadgets — would also hit a limit, he said.

The UCSB Current – "Saving Moore's Law" (full article)

Banerjee's COE Profile

Banerjee's Nanoelectronics Research Lab (NRL)

In Memoriam: Professor Emeritus Augustine Gray – ECE faculty member from 1964 to 1980

December 20th, 2019

From: UC Santa Barbara – Office of the Chancellor

Dear Members of our Campus Community,

I regret to share the sad news that Professor Emeritus Augustine Gray of our Department of Electrical and Computer Engineering passed away on October 28.

Professor Gray, known affectionately as “Steen,” was a member of our faculty from 1964 to 1980. As one of the first three faculty members in the department, he helped to establish and advance Electrical and Computer Engineering on our campus, providing a strong foundation for its excellence and stature today. We are grateful for his lasting contributions to our campus, department, and the profession.

He received his B.S. and M.S. degrees from MIT, where he participated in the electrical engineering cooperative program with General Electric. During this time, he worked in Menlo Park on the logic design of ERMA (Electronic Recording Machine Accounting), the first major banking computer, built for the Bank of America by the Stanford Research Institute and General Electric. He went on to spend a year as a physics instructor at San Diego State College, teaching electronic circuits, digital design, and digital computers. He then continued his graduate studies at Caltech, where he received his Ph.D. in 1964.

Professor Gray was a dedicated and inspirational teacher and a highly respected colleague who excelled at bringing clarity to complex ideas. Working closely with Professor Glen Culler, among others, Professor Gray made pioneering research contributions to real-time speech communication and processing through digital networks, from local academic networks to the ARPAnet and its successor, the Internet. He also collaborated for many years with UCSB Ph.D. recipient John Markel on the theory and understanding of applications of linear prediction to speech processing. Two of their joint publications won professional awards from the Institute of Electrical and Electronics Engineers (IEEE) Group on Acoustics, Speech, and Signal Processing and its successor, the IEEE Signal Processing Society. In 1976 they coauthored the classic text Linear Prediction of Speech, which played a fundamental role in the early development of digital speech processing, and in 1982 were elected Fellows of the IEEE for “contributions to the theory of linear prediction and its applications to speech processing.” Together they founded Signal Technology, Inc. (STI), along with Larry Pfeiffer. After he retired from UC Santa Barbara, Professor Gray held roles as Senior Scientist, Vice President, and Executive Vice President of STI through 1988. From 1988 through 1993 he held various positions with derivative companies of STI, after which he became an independent computer consultant.

In addition to his research and teaching activities, Professor Gray held an Advanced Extra Class Amateur Radio License (AA6H), and was an avid reader and walker. He and his wife, Averill, were active supporters of the Get Oil Out (GOO) movement and the Santa Barbara Zoo. In 1994, they retired to Florence, Oregon, where they became active volunteers for the Oregon Coast Humane Society.

We extend our sincere condolences to Professor Gray’s family, colleagues, and friends. Our campus flag was lowered in his honor on November 19.

Sincerely,

Henry T. Yang
Chancellor

ECE Prof. Yuan Xie named 2019 Association for Computing Machinery (ACM) Fellow

December 17th, 2019

photo of yuan xie
Xie recognized for his “contributions to technology-driven computer architecture and for developing tools for it its implementation and assessment”

Along with College of Engineering faculty member CS Professor Giovanni Vigna, Xie was among 58 ACM members selected as Fellow for 2019. “Congratulations to Professors Vigna and Xie for being recognized as ACM Fellows,” said Rod Alferness, dean of the UCSB College of Engineering. “This prestigious peer recognition from the most important scholarly societies serves to underscore the important and highly application-enabling work being conducted at the College. We’re extremely grateful to have two such stellar faculty members and groundbreaking researchers as part of the College of Engineering family.”

Yuan Xie leads the Scalable and Energy-efficient Architecture Lab at UCSB. During his career, Xie has made impactful contributions to computer architecture design and design automation that exploit emerging technologies, especially three-dimensional (or “stacked”) integrated circuits (3D ICs) and new nonvolatile memories (NVMs).

3D ICs offer new opportunities to achieve system-level innovation that are not dependent on scaling new technology. Unlike traditional SRAM/DRAM memory, NVMs offer the benefit of nonvolatility, retaining all data even if the device is shut down; higher-density , so that more data can be stored per square millimeter of physical memory; and lower standby power, meaning that if, a computer is left for several minutes and no action is performed, almost no energy will be used.

Xie has developed design automation toolsets — software to enhance designers’ efficiency — for these new technologies and has produced prototype implementations that have inspired commercial follow-ons. He is recognized as a world leader in these two emerging technologies, and as one of the very few researchers who have crossed traditional boundaries separating architecture, design automation, and testing, to embrace all three.

Xie was also recently named a Fellow of the American Association for the Advancement of Science. His road to such dual global recognition could scarcely have been less likely. He was born to peasant-farmer parents in rural southeastern China, miles from the nearest settlement of any size. Life was hard in the village of Da-Ping — its name translates as “big and flat,” but Da-Ping is actually tiny and extremely mountainous, Xie recalls, and getting to school involved a long, rigorous hike.

After his first- and second-grade teacher moved from Xie’s village to a small town about sixty miles away, she volunteered to host Xie, who was first in his class, so that he could attend a better school. That launched him on a fruitful educational journey that led him to earn his BS in electronic engineering at Tsinghua University and, later, his MS and PhD from Princeton.

The UCSB Current – "High Honors for Professors in Computer Hardware and Software" (full article)

Xie's COE Profile

Xie's SEAL Lab

ECE Postdoc Bei Shi receives a Best Paper Award at the Asia Communications and Photonics Conference (ACP)

December 13th, 2019

photo of bei shiShi and co-authors recognized for the development of a MOCVD-based heteroepitaxy approach that offers a practical path toward monolithic integration of InP lasers in silicon photonics

Bei Shi is a member of Professor Jonathan Klamkin’s iPL group and received his PhD degree in 2018 under the supervision of Prof. Kei May Lau from The Hong Kong University of Science and Technology (HKUST) for his work on MOCVD growth III-V quantum dot lasers and III-V/Si heteroepitaxy. Prior to that, he completed his undergraduate studies at Huazhong University of Science and Technology (Wuhan, China), with a BEng in optoelectronics in 2013. His current research interests are mainly focused on monolithic integration of III-V optoelectronic devices on Si, epitaxial growth of quantum dot/dash and III-V nanostructures for integrated photonics circuits.

The ACP Conference was held in Chengdu, China on November 2-5, 2019

Optica, "Continuous-wave Electrically Pumped 1550  nm Lasers Epitaxially Grown on On-axis (001) Silicon

Search for Shi's Publications on Prof. Klamkin's Pub List

Klamkin's Integrated Photonics Laboratory (iPL)

ECE Professor Emeritus Sanjit Mitra elected as a 2019 National Academy of Inventors (NAI) Fellow

December 4th, 2019

photo of Sanjit Mitra
The College of Engineering’s Sanjit Mitra (ECE) and Michael Chabinyc (Materials) are among the 168 prolific academic innovators from around the world to earn fellow status for 2019

The NAI Fellows Program highlights academic inventors who have demonstrated a spirit of innovation in creating or facilitating outstanding inventions that have made a tangible impact on quality of life, economic development and the welfare of society. Election to NAI Fellow is the highest professional distinction accorded solely to academic inventors.

“We offer sincere congratulations to Professor Michael Chabinyc and Professor Sanjit Mitra on their election to the National Academy of Inventors, a well-deserved and prestigious peer recognition of their innovation and important contributions to society with leading-edge research,” said Rod Alferness, dean of the College of Engineering.

Mitra has published more than 700 papers in the areas of analog and digital signal processing, and image processing. He has spent more than 40 years at UC Santa Barbara after joining the faculty in 1977, has authored and co-authored twelve books, and holds six patents.

“I am honored to be elected a fellow of the National Academy of Inventors,” Mitra said. “This recognition by my peers is particularly gratifying as the inventions which had the biggest impact are based on my initial research carried out at UC Santa Barbara in collaboration with visiting researchers from industry.”

Previously, Mitra was elected a fellow by the Institute of Electrical and Electronics Engineers, the American Association for the Advancement of Science, and the International Society for Optical Engineering. He is a member of the U.S. National Academy of Engineering and of several foreign academies.

To date, NAI Fellows hold more than 41,500 issued U.S. patents, which have generated over 11,000 licensed technologies and companies, and created more than 36 million jobs. In addition, over $1.6 trillion in revenue has been generated based on NAI Fellow discoveries.

“Congratulations to the 2019 class of NAI Fellows,” said Laura A. Peter, Deputy Under Secretary of Commerce for Intellectual Property and Deputy Director at the U.S. Patent and Trademark Office. “It is a privilege to welcome these exceptionally qualified individuals to this prestigious organization. I am certain their accomplishments will inspire the next generation of invention pioneers.”

Fellows will be formally inducted during the 2020 NAI Fellows Ceremony on April 10, 2020, in Phoenix, Arizona.

The UCSB Current – "Imagination Plus Expertise" (full article)

Mitra's COE Profile

ECE Professor Yuan Xie named a 2019 American Association for the Advancement of Science (AAAS) Fellow

November 27th, 2019

photo of yuan xieElection as a AAAS Fellow is an honor bestowed upon AAAS members by their peers for their scientifically or socially distinguished efforts to advance science or its applications

“It is with great pride and joy that we congratulate our nine faculty colleagues on their election to the American Association for the Advancement of Science,” said UC Santa Barbara Chancellor Henry T. Yang. “This is a strong testament to their leadership and accomplishments, as recognized by their peers, in advancing scientific research in the interest of humanity. It also is a reflection of the breakthrough research being conducted within their fields as well as across the disciplines at UC Santa Barbara.

ECE Prof. Yuan Xie received the honor for “For distinguished contributions to the field of computer architecture and electronic design automation, particularly three-dimensional integrated circuits and memory architectures.”

Xie researches computer architecture, electronics design automation and embedded systems design in the Department of Electrical and Computer Engineering. His application-driven research projects include novel architectures for artificial intelligence as well as hardware acceleration for emerging applications such as bio-informatics, graphics analytics and robotics.

Each new AAAS Fellow will receive an official certificate and a gold and blue rosette pin at the AAAS Fellows Forum, which will take place during the 2020 AAAS Annual Meeting in February in Seattle, Washington.

The American Association for the Advancement of Science was founded in 1848 and has become the world’s largest general scientific society. The non-profit organization includes more than 250 affiliated societies and academies of science, serving 10 million individuals. The association also publishes many eminent scientific journals including Science.

The UCSB Current – "Distinguished Efforts to Advance Science" (full article)

Xie's COE Profile

Xie's SEAL Lab

ECE Prof. Kaustav Banerjee among scientists named a Clarivate Analytics’ “2019 Highly Cited Researcher”

November 19th, 2019

photo of kaustav banerjee
Clarivate Analytics names 17 UC Santa Barbara scientists and social scientists to its 2019 list of highly cited researchers – Banerjee among five from the College of Engineering

The researchers have been named among the most influential scientists in the world, according to the 2019 list released by Clarivate Analytics (formerly Thomson Reuters).

The annual list recognizes researchers in the sciences and social sciences who produced multiple papers ranking in the top 1% by citations for their field and year of publication, demonstrating significant research influence among their peers. The papers surveyed include those published and cited during the period 2008-2018.

The 2019 list contains 6,216 highly cited researchers in various fields from around the world, and 2,491 highly cited researchers are recognized for their cross-field performance.

The UCSB Current – "Citing Excellence" (full article)

Clarivate Analytics – "Highly Cited Researchers"

Banerjee's COE Profile

ECE Prof. Dan Blumenthal’s FRESCO project featured in the The UCSB Current article “Quiet Light for Future Data Centers”

November 14th, 2019

illustration of a data center
Blumenthal’s project aims to bring the data center into an energy efficient scalable future

The deluge of data we transmit across the globe via the internet-enabled devices and services that come online every day has required us to become much more efficient with the power, bandwidth and physical space needed to maintain the technology of our modern online lives and businesses.

“Much of the world today is interconnected and relies on data centers for everything from business to financial to social interactions,” said Daniel Blumenthal, a professor of electrical and computer engineering at UC Santa Barbara. The amount of data now being processed is growing so fast that the power needed just to get it from one place to another along the so-called information superhighway constitutes a significant portion of the world’s total energy consumption, he said. This is particularly true of interconnects — the part of the internet infrastructure tasked with getting data from one location to another.

“Think of interconnects as the highways and the roads that move data,” Blumenthal said. There are several levels of interconnects, from the local types that move data from one device on a circuit to the next, to versions that are responsible for linkages between data centers. The energy required to power interconnects alone is 10% of the world’s total energy consumption and climbing, thanks to the growing amount of data that these components need to turn from electronic signals to light, and back to electronic signals. The energy needed to keep the data servers cool also adds to total power consumption.

“The amount of worldwide data traffic is driving up the capacity inside data centers to unprecedented levels and today’s engineering solutions break down,” Blumenthal explained. “Using conventional methods as this capacity explodes places a tax on the energy and cost requirements of optical communications between physical equipment, so we need drastically new approaches.”

As the demand for additional infrastructure to maintain the performance of the superhighways increases, the physical space needed for all these components and data centers is becoming a limiting factor, creating bottlenecks of information flow even as data processing chipsets increase their capacity to what could be a whopping 100 terabytes per second for a single chip in the not too far future. This level of expected scaling was unheard of not just a handful of years ago and now it appears that is where the world is headed.

“The challenge we have is to ramp up for when that happens,” said Blumenthal, who also serves as director for UC Santa Barbara’s Terabit Optical Ethernet Center, and represents UC Santa Barbara in Microsoft’s Optics for the Cloud Research Alliance.

This challenge is a now job for Blumenthal’s ARPA-e project called FRESCO: FREquency Stabilized COherent Optical Low-Energy Wavelength Division Multiplexing DC Interconnects. Bringing the speed, high data capacity and low-energy use of light (optics) to advanced internet infrastructure architecture, the FRESCO team aims to solve the data center bottleneck while bringing energy usage and space needs to a sustainable and engineerable level.

The UCSB Current – "Quiet Light for Future Data Centers" (full article)

Blumenthal's COE Profile

Blumenthal's Optical Communications and Photonic Integration Group

ECE Assistant Professor Galan Moody receives Air Force Young Investigator Award for quantum computing

October 21st, 2019

illustration of an all-electric-all-on-chip quantum photonic platformMoody aims to create an optical quantum computing platform in which all of the essential components are integrated onto a single semiconductor chip

Quantum computers use the fundamentals of quantum mechanics to potentially speed up the process of solving complex computations. Suppose you need to perform the task of searching for a specific number in a phone book. A classical computer will search each line of the phone book until it finds a match. A quantum computer could search the entire phone book at the same time by assessing each line simultaneously and return a result much faster.

The difference in speed is due to the computer’s basic unit for processing information. In a classical computer, that basic unit is called a bit, an electrical or optical pulse that represents either 0 or 1. A quantum computer’s basic unit is a qubit, which can represent numerous combinations of values from 0 and 1 at the same time. It is this characteristic that may allow quantum computers to speed up calculations. The downside of qubits is that they exist in a fragile quantum state that is vulnerable to environmental noise, such as changes in temperature. As a result, generating and managing qubits in a controlled environment poses significant challenges for researchers.

Moody, an assistant professor of electrical and computer engineering, has proposed a solution to overcome the poor efficiency and performance of existing quantum computing prototypes that use light to encode and process information. Optical systems are attractive because they naturally link quantum computing and networking in the same physical framework. However, existing technology still requires off-chip optical operations, which dramatically reduce efficiency, performance and scalability. In his project, “Heterogeneous III-V/Silicon Photonics for All-on-Chip: Linear Optical Quantum Computing,” Moody aims to create an optical quantum computing platform in which all of the essential components are integrated onto a single semiconductor chip.

Moody is one of 40 early-career scientists selected for a 2019 Young Investigator Award from the Air Force Office of Scientific Research. Winners receive $450,000 over three years to support their work. The program is intended to foster research by young scientists that supports the Air Force’s mission to control and maximize utilization of air, space and cyberspace, as well as related challenges in science and engineering.

The UCSB Current – "Pushing Quantum Photonics" (full article)

Moody's COE Profile

Moody's Quantum Photonics Lab

ECE Professor Dmitri Strukov and researchers interviewed in Nature Communications article “Building Brain-Inspired-Computing”

October 20th, 2019

photo of Dmitri Strukov
Strukov (an EE, UCSB), Giacomo Indiveri (an EE, U.of Zurich), Julie Grollier (a material physicist, UMPhy) and Stefano Fusi (a neuroscientist, Columbia U) talked to Nature Communications about the opportunities and challenges in developing brain-inspired computing technologies, namely neuromorphic computing, and advocated effective collaborations crossing multidisciplinary research areas to support this emerging community

Please tell us about your research background and how it brought you to work on neuromorphic computing?
Dmitri Strukov (DS): I was trained as an electrical engineer and got interested in developing circuits and architectures using emerging electron devices in my graduate school at Stony Brook University. Afterwards, I moved to Hewlett Packard Laboratories as a postdoctoral researcher and switched my attention to device physics. I spent most of my time developing models for mixed electronic-ionic conductors that could be used to implement resistive switching devices (known as memristors nowadays). This experience naturally led me to choose neuromorphic computing—one of the most promising applications of memristors—as my research area after I joined University of California at Santa Barbara. My major focus now is on the development of practical mixed-signal circuits for artificial neural networks. This is a challenging topic because it spans across a broad range of disciplines, from electron devices to algorithms. In the long term, I hope that our research will lead to practically useful neuromorphic systems that will be used in everyday life.

Why do we need neuromorphic computing?
DS: The answer is quite obvious if one interprets neuromorphic computing as a biologically inspired computing technology facilitated by powerful deep learning algorithms that have already showed profound impact on science, technology, and our society. However, when considering the very original definition of neuromorphic computing coined by Carver Mead at Caltech, which can be loosely put as “analog computing hardware organized similarly to the brains”, the answer becomes less clear to me. This is in part because such definition still leaves some ambiguity in how closely neuromorphic computing hardware should emulate the brains and what functionalities are expected from such systems. One could call neuromorphic computing a hardware that is merely borrowing a few tricks from biology, such as perceptron-like distributed parallel information processing, to perform simple machine learning tasks. Conversely, should it also integrate more advanced functions (e.g. spike-time encoding, various types of plasticity, homeostasis, etc.) and be capable of realizing cognitive functions at higher levels? Nevertheless, the primary motivation is arguably to achieve the extreme energy efficiency of the brains using neuromorphic computing. In fact, this will be the main advantage of analog and mixed-signal implementations of simple perceptron networks as well as of advanced spiking neural networks. Some existing results, albeit they perform simple tasks like image classification, have shown many orders of magnitudes improvement in energy and speed compared to purely digital computing, and some of them can even surpass the performance of the human brain.

What can we learn from our brain for information processing? How to emulate human brain using electronic devices and where are we now?
DS: There is a general consensus on the usefulness of some tricks that are employed by the brains, such as analog and in-memory computing, massively parallel processing, spike coding, task-specific connectivity in neural networks. Many of these ideas have already been implemented in state-of-the-art neuromorphic systems. I do believe, however, that we should not blindly try to mimic all features of the brains—at least not doing so without having a good engineering reason first—and we should consider simpler approaches based on more conventional technologies to achieve the same goal. On the other hand, we should also keep in mind that over millions of years the evolution of biological brains has been constrained to biomaterials optimized for specific tasks, while we have a much wider range of material choices now in the context of neuromorphic engineering. Therefore, there could exist profound differences in designing rules. For example, the brains have to rely on poor conductors offered by biomaterials, which have presumably affected the principles of brain structure and operation in some ways that are not necessarily to be applicable to neuromorphic computing based on high conducting materials.

What are the major hurdles to date towards realizing neuromorphic computing from your perspective?
DS: In my opinion, there are tough challenges at several levels. From a technology perspective, the foremost challenge is various device non-idealities, such as the notorious device-to-device variations in their current-voltage characteristics and poor yields of memory devices—one of the key components of neuromorphic circuits (I will elaborate more on these issues in the answer to question 6). In addition to these technological hurdles, I reckon that there might be other substantial economical and confidence barriers to achieve such highly innovative, yet high-risk technology. Ultimately, to be successful, neuromorphic computing hardware would have to win competition over conventional digital circuits that are supported by presently available infrastructures and enormous investments over years. Fortunately, this barrier does not appear to be as bad as, say, 20 years ago, because of slowing down innovations (mainly about feature size scaling) in conventional CMOS technology, very high development and production cost of sub-10-nm CMOS circuits, and general trend towards more specialized computing hardware. Apart from hardware issues, the progress on the algorithmic front is clearly not sufficient to cope with the explosive increase in the need from neuromorphic computing either, especially for higher cognition tasks. The lack of suitable algorithms, in return, has imposed large uncertainty in designing neuromorphic hardware.

Additional Questions:

  • What is your vision to tackle these major hurdles? Any suggestions?
  • What could be the measure of when the neuromorphic computing is ready to replace the current digital computing?
  • Any suggestion on how researchers, including but not limited to material scientists, device physicists, circuits engineers, computer scientists, neuroscientists or even policy makers, can better work together in this very multidisciplinary field?

Nature Communications – “Building Brain-Inspired-Computing” (full article)

Strukov's COE Profile

Strukov Research Group