University of WashingtonComputer Science & Engineering

and Electrical Engineering

Computer Engineering and the UW Experimental Computer

Engineering Lab (ExCEL)

Fall 2010

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Computer Engineering at UW

Three years ago, the UW Departments of Computer Science & Engineering and Electrical Engineering created an initiative — the UW Experimental Computer Engineering Lab (ExCEL) — to facilitate broad collaboration between the departments along the computer engineering boundary. Key to this initiative was our intention to make six new joint hires in computer engineering. We are very excited at our progress; here we announce our third joint computer engineering hire: in early 2011, Josh Smith, currently at Intel Research, will join our two departments. Josh, who works in wireless sensing systems and robotics, will complement our previous ExCEL hires Shwetak Patel (whose research includes sensors and ubiquitous computing) and Georg Seelig (whose research focuses on synthetic biology), along with numerous other computer engineers in the two departments. We are intending to continue to grow the program with more hires over the next few years. Areas of interest include nanotechnology, implantable and biologically interfaced devices, synthetic molecular engineering, VLSI, embedded systems, sensor systems, parallel computing, network systems, and technology for the developing world.

We highlight here the work of our new hires as well as some of the ongoing computer engineering research at the University of Washington.

Henry M. Levy Leung TsangChairman and Wissner-Slivka Chair ChairmanComputer Science & Engineering Electrical Engineering

Departments of

Computer Science &

Engineering (CSE) and

Electrical Engineering (EE)

Highlights of Current Computer Engineering Research at the University of Washington

Recent HiresShwetak Patel, Assistant Professor (CSE/EE); Georg Seelig, Assistant Professor (EE/CSE); Joshua R. Smith, Associate Professor (CSE/EE)

Sensing and Energy SustainabilityShwetak Patel, Assistant Professor (CSE/EE)

Battery-Free Micropower SensingBrian Otis, Assistant Professor (EE); Joshua R. Smith, Associate Professor (CSE/EE)

Synthetic BiologyEric Klavins, Associate Professor (EE); Georg Seelig, Assistant Professor (CSE/EE)

Sensorimotor Neural EngineeringYoky Matsuoka, Associate Professor (CSE); Raj Rao, Associate Professor (CSE)

Low Power Analog/RFIC ResearchBrian Otis, Assistant Professor (EE); Chris Rudell, Associate Professor (EE)

Next-Generation Reconfigurable HardwareCarl Ebeling, Professor (CSE); Scott Hauck, Professor (EE)

Engineered Self-AssemblyKarl Bohringer, Professor (EE); Eric Klavins, Associate Professor (EE); Babak Parviz, Associate Professor (EE)

Technology for the Developing WorldRichard Anderson, Professor (CSE); Gaetano Borriello, Professor (CSE)

Security and Privacy for Emerging Technologies Tadayoshi Kohno, Assistant Professor (CSE); Radha Poovendran, Associate Professor (EE)

Deterministic Execution for Multicore SystemsLuis Ceze, Assistant Professor (CSE); Susan Eggers, Professor (CSE); Steve Gribble, Associate Professor (CSE); Dan Grossman, Associate Professor (CSE); Mark Oskin, Professor (CSE)

Recent Hires in Computer Engineering

Shwetak Patel, Assistant Professor, was the first faculty member to join the Experimental Computer Engineering Lab (ExCEL) in 2008. His general research interests are in the areas of human-computer interaction, ubiquitous computing, and user interface software and technology. He is particularly interested in developing easy-to-deploy sensing technologies and approaches for location and activity recognition applications. He is also interested in exploring novel interaction techniques for mobile devices, mobile sensing systems, and low power wireless sensor technologies.

Patel’s most recent research has been in building a new class of low-cost and easy-to-deploy sensing systems for the home, called infrastructure mediated sensing, which leverages existing utility infrastructures in a home to support whole-house sensing. In 2009, Patel was honored by Technology Review as a TR35 recipient. He received his PhD in Computer Science from the Georgia Institute of Technology in 2008 and BS in Computer Science in 2003.

Georg Seelig, Assistant Professor, joined the CSE and EE faculty in Spring 2009, as part of ExCEL. Seelig received his Diploma in Physics from the University of Basel in 1999 and his PhD in Theoretical Physics from the University of Geneva in 2003. Prior to joining UW, he held a postdoc in synthetic biology at Caltech. In 2007, he received a Career Award at the Scientific Interface from the Burroughs Wellcome Fund. Seelig is interested in understanding how biological organisms process information using complex biochemical networks and how such networks can be engineered to program cellular behavior. The focus of his research is the identification of systematic design rules for the de novo construction of biological control circuits with DNA and RNA components. His approach integrates the design of molecular circuitry in the test tube and in the cell with the investigation of existing biological pathways like the microRNA pathway. Such engineered circuits and circuit elements are being applied to problems in disease diagnostics and therapy.

Joshua R. Smith, Associate Professor, joins the CSE and EE departments in February 2011. He has been with nearby Intel Labs Seattle, collaborating with many UW students and faculty, from 2004-2010. He holds PhD and S.M. degrees from MIT, an M.A. in Physics from Cambridge University, and B.A. degrees in Computer Science and Philosophy from Williams College. Smith is interested in all aspects of sensor systems, including creating novel sensor systems, powering them wirelessly, and using them in applications such as robotics, ubiquitous computing, and human-computer

interaction. Previously, he co-invented an electric field sensing system for suppressing unsafe airbag firing that is included in every Honda car. At Intel, he has led research projects in the areas of wireless power and robotics.

Sensing and Energy Sustainability

Shwetak Patel

In an effort to contribute to the nation’s goal of reducing our overall energy use, researchers at UW’s Computer Science & Engineering department are applying their expertise in sensing, embedded systems, and human-computer interaction in creating solutions to help better inform consumers of their energy use and encourage more sustainable activities.

Over the last few years, Dr. Patel and his research lab have been developing the next generation smart grid technology for the home. Reducing the use of energy and water is one way homeowners can do their part to decrease pollution and slow global warming. Monitoring utility demand has not been easy or affordable for the general public or utilities until now. Patel and his team have developed sensor systems that allow on-line monitoring of water, electricity, and gas use by recognizing the unique ‘signature’ given off by every faucet, toilet, appliance and electronic device in the home. Using this system, residents can track their electricity and water consumption, and, for instance, take advantage of off-peak power rates. That data can also be fed back to the consumers to help them better understand their own consumption.

At the heart of the team’s utility monitoring system is a novel pattern recognition technology that, once calibrated, can identify individual components of a home’s

plumbing or electrical system. The beauty of the system is that the homeowner only needs to install one pressure sensor, usually at the outside hose faucet or water heater drain valve. The entire home’s water usage can then be tracked down to the use of each fixture. The signal recognition software is smart enough to distinguish between two or more simultaneous events, such as two different faucets being turned on at the same time.

Similar technology has been developed to monitor electrical systems. As with the water sensor, a single sensor plugged into a conventional wall outlet will detect a variety of electrical events throughout the home, each of which has its own unique electrical noise signal. Machine learning techniques allow the monitoring system to distinguish between each light switch, home appliance or electronic device.

Hydrosense sensor

Battery-Free Micropower Sensing

Brian Otis and

Joshua R. SmithThe power consumption of microelectronic devices has recently crossed a threshold: wireless sensing systems can now power themselves by harvesting energy from ambient sources such as broadcast TV towers or by using RFID readers as wireless power sources. Realizing the promise of this new low-power, battery-free regime requires a combination of low-power circuit design and power harvesting. The collaboration of Professors Otis and Smith brings these two perspectives together to create exciting new capabilities.

Professor Smith and students began exploring RFID-powered sensors with their Wireless Identification and Sensing Platform (WISP). WISP is a platform for sensing and computation that is powered and read by long range UHF RFID readers. They built the first accelerometer sensing system to be wirelessly powered and read by UHF radio waves, which propagate long distances. Beyond sensing applications, security researchers are using WISP to implement cryptographic protocols that cannot be implemented in standard RFID tags. The first workshop on WISP was held in Berkeley, CA in 2009, and in 2011 Springer will publish a collection of WISP-related research from around the world.

Professor Otis and students recently created the SoCWISP (System-on-Chip WISP), a single chip that integrates the RF and digital communication functions of the WISP and connects an integrated low noise analog front-end and analog-to-digital converter to a variety of sensor interfaces. This device is much smaller, lighter, and lower in power than the discrete component WISPs. In fact, this sensing platform is so light that Otis, working with Professor Tom Daniel of UW Biology, was able to wirelessly measure the muscle temperature of untethered Hawk Moths while they are actually in flight. This research will help answer fundamental questions

about the relationship between muscle temperature and mechanical performance in this important model biosystem.

As Moore’s law and advances in circuit design push power requirements down and system performance up, we expect battery-free wireless sensing platforms to transition from surprising novelties, to useful systems, and perhaps eventually to essential infrastructure, embedded in the environment and in our bodies.

A living moth, with the sensor system attached. Note that the system is so small and light that the month can still fly.

Synthetic Biology

Biological organisms process information and control cellular behavior using complex biochemical circuits. The goal of synthetic biology is to learn how to engineer circuits of similar complexity and thus “program” biology. Synthetic biology brings engineering tools and methodologies to the subject of biology, much as electrical engineering brings these tools to physics. The novel biological systems, new life forms really, resulting from this approach will someday afford humanity a new level of control over the processes in our bodies, in our crops, in landfills, compost heaps, and the ocean waters. Instead of the current brute force attempts to control the living world with machines and harsh chemicals, synthetic biology promises control at the level of individual molecules using engineered living cells as tiny chemical processing plants.

Seelig’s work focuses on systematic design rules for the de novo construction of biological control circuits with DNA and RNA components. The approach integrates

the design of molecular circuitry in the test tube and in the cell with the investigation of existing biological pathways like the microRNA pathway. Engineered circuits and circuit elements are being applied to problems in disease diagnostics and therapy. Klavins; work focuses on control and signal processing behaviors, such as linear transfer functions, oscillators, sensors, and switches. These we implement either in vitro using nucleic acids and a few enzymes or in vivo by genetically engineering our favorite organisms: E. coli or yeast. We then gather

data from our systems using fluorescence measurements, microscopy, etc. Finally, we work to characterize the devices we build using analytical tools from controls systems, such as system identification, model reduction, model discrimination and model invalidation.

The applications of synthetic biology are broad: If we can design sensors implemented with molecules and encode them as genes, we might someday engineer genetically enhanced, synthetic immune systems to treat immunodeficiency disorders and cancer. If we can harness the biochemical processes inside soil bacteria, we might someday engineer custom-made bio-remediation bacteria. If we can exploit the process of evolution, we can use directed evolution to tune the activity of enzymes that could be used in manufacturing and health.

Eric Klavins and

Georg Seelig

Sensorimotor Neural Engineering

The Engineering Research Center for Sensorimotor Neural Engineering (ERC/SNE or “Center”) will become a global hub for delivering neural-inspired sensorimotor devices. Using devices that mine the rich data in neural signals available from implantable, wearable, and interactive interfaces, the ERC/SNE will build end-to-end integrated systems. Examples include: implantable neurochips that can activate paralyzed limbs by electrically stimulating muscles or nerve roots; stationary robots that extract neural signals from a user’s touch to provide home-based, post-stroke therapy; neural-controlled adaptive prosthetic limbs that provide sophisticated sensory feedback; and wearable caps that control external exploration devices. The foundation for all systems developed by the ERC/SNE is a robust and adaptive closed-loop interaction between human nervous systems and sensorimotor devices.

The Center’s mission is to develop innovative ways to connect a deep mathematical understanding of how biological systems acquire and process information with the design of effective devices that interact seamlessly with human beings. Our singular approach reverse-engineers the nervous system’s sensorimotor functions to develop engineering models that correct or compensate for neural deficits and augment neural capabilities. Using these mathematical and structural models, it is possible to design neural interfaces integrated with external control devices. These forward engineered devices, in turn, enable further discovery and mathematical modeling of neural computation. This information can then be used to develop hierarchical, non-linear, robust and adaptive algorithms that enable sensorimotor closed-loop control between humans and devices.

Yoky Matsuoka and Raj Rao

Low Power Analog/RFIC Research

Brian Otis andChris Rudell

In roughly 50 years, technology scaling of electronic devices has taken us from consumer electronics containing 10 vacuum tubes to devices containing over 10 billion transistors. This immense computational power, however, does not directly benefit what is one of the most important classes of electronic devices: the analog circuitry that interfaces directly with the real world. Emerging applications demand portable, low power implementations of increasingly complex systems. Fundamental circuit design that pushes the limits of IC technology will define the platforms available to the next generation of computer engineers.

Professor Otis’ group explores the limits of power dissipation on miniaturized wireless sensors. This group has two main research directions. First, they utilize emerging MEMS devices to create new low power radio architectures. Second, the group works extensively with the UW Medical School to develop new research and clinical tools to enable previously impossible collection of data. For example, they have developed a 0.3 gram single-chip wireless biosignal transmitter called the ‘Bumblebee.’ The device is a self-contained and can transmit up to 10 meters to a USB-compatible receiver for continuous EKG monitoring, neural recording, audio transmission, and acceleration sensing.

Professor Rudell’s group explores high-frequency, high-performance analog circuits implement in low-cost silicon technologies. Research taking place in his group focuses on a diverse application space including the use of mm-Wave

CMOS circuits for imaging and communications, to highly programmable cognitive radios. At present, the FAST lab has a research effort to vastly increase the distance a single sensor radio may communication information, from meters to potentially kilometers. The lab seeks to introduce a Wide Area Radio Network for Sensor (WARNS) communication concept that will allow direct communication of sensor devices to any available wireless infrastructure, including cellular and WiFi networks. This will greatly expand the potential coverage for a single sensor device and enable new sensor applications from environmental monitoring to homeland security.

The ‘Bumblebee’ – a wireless biosignal interface that operates continuously for three days from a hearing aid battery.

Next-Generation Reconfigurable Hardware

Carl Ebeling andScott Hauck

FPGAs are devices that can be programmed and reprogrammed to implement complex digital circuits and systems. They merge together the flexibility of microprocessors with the performance of custom hardware, and are used in many systems that require very high performance that can only be achieved via extreme parallelism and custom circuits. These include network interfaces and switches, video and signal processing, cryptography, and bio-informatics.

Research over the last two decades by the University of Washington reconfigurable computing group has ranged from new architectures (Triptych, the first FPGA to merge logic and routing, and RaPiD, one of the first coarse-grained architectures), to CAD tools (Pathfinder, the de facto standard FPGA router, and SPR, a compiler for coarse-grained configurable architectures), to applications (MICES, a high-performance medical imaging system shown in the photo below, a PET scanner developed jointly with with the University of Washington’s Department of Radiology).

The reconfigurable computing group at UW is currently working on several related projects whose goal is to move configurable computing into the mainstream. The first is a project with a local company, Pico Computing, to speedup sequence alignment algorithms for next-generation DNA sequence machines by orders of magnitude over current cluster-computing solutions.

The second is designing a computing model, language and compiler for large-scale configurable computing systems that comprise many processors and FPGA accelerators. The third is the development of energy-efficient configurable platforms using coarse-grained reconfigurable architectures.

Self-Engineered Assembly

The realm of the extremely small is a new frontier of engineering. It is at the nano scale that tiny biological machines construct macro scale tissues, move our limbs, and detect pathogens. Our ability to engineer at the nano scale, however, is restricted to a handful of (relatively) simple techniques: Lithography is limited to flat layers of a few compounds, while manipulation with atomic force microscopes is limited to small numbers of atoms. Nevertheless, nature is filled with sophisticated machines, such as the ribosome or the mechanical motor in the bacterial flagellum, that seem to have been built in bulk somehow spontaneously. At issue is the fundamental question: How does matter become complex? One hypothesis is that simple small components self assemble into more complex ones in systems, in a process “designed” by billions of years of evolution.

We approach engineering self-assembling systems by designing parts that have some control over the binding interactions in which they participate, developing a theory and practice of programmed self-assembly. In a biochemical environment, this control might be mediated by molecular conformation (shape). In meso-scale self-assembly, particles might have control over the wettabilities of their edges and some idea of their local state. At the macro scale in particular, we have implemented programmed robotic self-assembly where robotic parts have microcontrollers, local

sensing and mechanical or magnetic latches. Given a specification from the user, we download programs onto each robotic part so that when they are placed in a suitable environment the parts self assemble into the desired assembly. No global control signal or expensive coordination algorithm is allowed.

Ultimately, we expect to be able to build artificial self-assembled functional devices that allow an unprecedented control over nanoscale systems and that will form a basis of highly functional smart materials, biosensors, and nanoelectronics. For example, self-assembly is a strong candidate technology for building interfaces between macroscale devices and the human body. An engineering discipline and the supporting mathematics for self-assembly will essentially enable macroscale objects with specific nanoscale features to be programmed to grow from simple raw materials. The number and scope of possible applications of such a technology is staggering.

Karl Bohringer, Eric Klavins, and Babak A. Parviz

Self-organizing robots

Technology for the Developing World

Information and Communication Technologies (ICTs) can have a big impact on the development of local economies, health care, and education systems. They can make a particular difference in low-resource environments such as those found in developing countries where the ability to collect, move, and analyze large and varied amounts of data are just starting to become feasible with the penetration of cellular networks.

We work with non-governmental organizations around the world to put our software and hardware into practice. Students explore new design spaces due to the very different constraints encountered in low-resource settings. Issues of intermittent connectivity and power as well as user interfaces tailored to the cultures and capabilities of users are very different from those encountered in the industrialized world. The work in these areas is under the umbrella of the Change group (http://change.washington.edu), a multi-disciplinary group of researchers on our campus interested in ICTs and their application in the real world to improve people’s lives.

One of these is the Open Data Kit (http://opendatakit.org), an open source collection of software modules for building mobile phone-based data collection

systems. The focus of this project has been community health workers, the first line of many public health systems. ODK provides not only the ability to follow-up on patients and collect information about their health status that can be shared with health care facilities, but also decision support so that volunteer personnel can make decisions that conform to established protocols.

Another project, FoneAstra, is a small and inexpensive add-on hardware module

that can turn a low-tier mobile phone into a remote sensing platform using SMS messages for data communication. This is being deployed in cold-chain monitoring for vaccine distribution and storage. FoneAstra devices can track shipments of vaccines as they travel from central warehouses to local dispensaries, monitoring their temperature during transit and once in local cold storage to ensure the vaccines remain effective and are not spoiled.

Richard Anderson and Gaetano Borriello

A community health worker uses ODK to scan a barcode on a patient ID card. (Kenya)

Security and Privacy for Emerging Technologies

Tadayoshi Kohno and

Radha Poovendran

Unexpected security risks can arise with new, emerging computer technologies. We seek to stay one step ahead of the “bad guys” and identify, measure, and learn from their risks before actual threats manifest. We co-led the first experimental study of the computer security properties of wireless implantable medical devices. We found that unauthorized individuals could, from close range, wirelessly affect the state of this medical device, extract private patient information, and cause the device to issue electrical shocks. We also co-led the first experimental computer security analysis of complete modern automobiles. We found that an adversary connected to our cars’ internal computer network could affect critical computerized components within our car, such as forcibly disengaging the brakes and make it impossible for the driver to stop. The computerization of these technologies brings many benefits, and we caution patients and drivers not to be overly alarmed today. However — as with the Web — the risks could increase as these and other devices

evolve and become more sophisticated. Informed by our results, we are developing principled approaches for overcoming the computer security risks with these and other emerging technologies, and we are evaluating our defenses with a broad collection of stakeholders.

We are also studying methods by which devices communicate wirelessly, in addition to the devices themselves.

Our contributions include the development of the science of secure network design, such as introduction of novel metrics for quantifying vulnerability between any two nodes in a given network via circuit theory and development of optimization framework for modeling and mitigation of coordinated jamming attacks. We have developed a privacy preserving protocol with constant time identification of Radio Frequency Identification (RFID) tags. Further, the development of joint performance and resiliency metric functions that are convex is a major new direction of our program. In the last few years, we have also been actively transitioning our research work to be implementable in off-the-shelf hardware as well as in emerging simulation tools such as ns-3.

Inside view of test car

Deterministic Execution for Multicore Systems

Luis Ceze, Susan Eggers, Steve Gribble, Dan Grossman, and Mark Oskin

Today, multicore processors are found in nearly all systems: from cell phones, to network routers, to laptops, to data-center nodes. However, programming these processors is challenging for multiple reasons. Our research addresses fundamental problems in making multicores easier to program, more scalable, and more reliable. We are addressing these challenges by breaking traditional boundaries in systems design and exploring better hardware/software interfaces, better compilers, better operating systems, and better ways to express programs. One of our key projects is on making multicores deterministic. Each time a multicore executes a parallel application, it can produce a different output, even if supplied with the same input. This frustrates debugging efforts and limits the ability to properly test multithreaded code, becoming a major obstacle to widespread adoption of parallel programming. We are demonstrating that it is actually possible to make multicore systems behave deterministically. This is extremely important because it allows programmers to deal with parallel programs the way they deal with sequential programs, making software testing more assuring, allowing more meaningful collection of crash information, and increasing the reliability of multithreaded software deployed in the field.

Software reliability is degrading along with the broad adoption of parallel programming and the general increase of software complexity. We are addressing this problem by developing techniques that can not only find and report bugs very accurately but are also able to automatically avoid bugs in deployed software. Such systems significantly decrease the probability that software bugs will lead to crashes.

On the energy front, we are developing new hardware/software interfaces to decrease the energy consumption of web-enabled mobile devices and exploring how to expose energy considerations at the programming language level, giving programmers explicit energy-accuracy-performance trade-offs. These projects can lead to power savings beyond what can be done in software or hardware in isolation.

Our Approach: Rethink The Whole Stack

Hardware

OS

Runtime

Compiler

PL •New programming constructs that limit the risk of mistakes

•New debugging and testing methods

•Post-deployment continuous monitoring and control for reliability

•Educating students to think parallel

•New general low-complexity architecture support for efficiency

University of WashingtonComputer Science & EngineeringBox 352350Seattle, WA 98195-2350

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http://www.cs.washington.edu http://www.ee.washington.edu