1. Design Tools

1.1 Chinook (1992--1998) (no longer active)

I was a contributor to the Chinook hardware/software co-synthesis tool during 1992--1998. The summary can be found at the end of this page.

1.2 IMPACCT (2000--2004)

Since joining UCI, I developed a new tool called IMPACCT, for Integrated Management of Power Aware Computing and Communication Technologies, sponspred by DARPA PAC/C program. During Phase 1 (2000-2002) (J2), IMPACCT focused on constraint-driven (C12) power-aware scheduling (C13) and system-level mode-dependency modeling (C14). For data regular applications, power-aware task motion (C15, J3) applies software pipelining towards satisfaction of timing and power constraints. Communication speed in a multi-speed interface was considered as a knob for power management (C17) with simultaneous functional partitioning among multiple voltage-scalable CPUs (C18, J4) and data compression (C22) more recently. The target applications included NASA/JPL's Sojourner Mars Pathfinder and ATR (automatic target recognition) algorithms.

For phase 2 of the PAC/C program, we work with Rockwell Collins to reduce power in their software-defined radios (SDR). A new tool called ImpacctPro was developed (C30) to enables designers of a software-defined radio (SDR) to explore many options in improving power efficiency. The tool supports high-level modeling of the sytem architecture (C20), tasks, real-time scheduling (C24, C29), power management (C22, C23, C28), co-simulation, and profiling. Innovations include

• (C29) Generalized, multiple power-mode dynamic power management that subsumes the traditional break-even time analysis. We use a novel energy-over-time geometric formulation for optimization on multi-mode transition sequences.
• (C30) ability to control an SDR system in real-time, so that the system can be tested and measured while operating normally.
• (C23, C28) ultra-fast and efficient evolutionary algorithm for slack distribution. It uses very few voltage/frequency steps to accomplish the same level of energy saving as the best published but slow technique, while running hundreds of times faster.

2. System Designs (2002--)

The system design effort is complementary and synergistic with the design tools effort described in Section 1 above. The effort from 2002--present has resulted in three award-winning system designs and a prototype of a medical device.

2.1 B#: Battery Emulator and Power Profiling Instrument (2002--)

B# (pronounced ``B-sharp'') is a system that can perform battery emulation and power profiling, as described in (C21)(J5). The novelty is the combination of the hardware and software: the hardware controls the electrical property, while the software defines the behavior by real-time simulation of the battery chemistry. The most important value of B# is reproducibility: it enables experiments involving embedded systems that track power levels to behave exactly the same way each time. This concept has been extended from lithium-ion batteries to solar panels and fuel cells.

The B# system is available to research groups in academia and industry, and the software is freely downloadable on the Internet for academic research use. We have developed the world's most accurate (1% error) battery models that have been calibrated and validated empirically with B#. This is a unique capability that it is needed by many. The novelty of this work was recognized with the Low Power Design Contest Award at the International Symposium on Low Power Electronics and Design (ISLPED) 2003. It carried a $2,000 cash award and was one of the six winning entries out of 16 submissions worldwide.

2.2 Wireless Sensor Nodes

Wireless sensor nodes received much attention recently due to the rich set of research topics, crosscutting impact, and broad funding opportunities. My contributions have been to build the hardware systems that can actually work under the most extreme of conditions, including power availability, form factor, and precise timing. I have worked with faculty members in other engineering departments at UCI to build up the solid foundation for deploying wireless sensor nodes in many applications.

DuraNode (2003--)

The first sensor node is called DuraNode, a wireless sensor node for monitoring the structural health in civil engineering. Professor Shinozuka, Chair of Civil and Environmental Engineering, has long identified the significance of this approach but found that existing sensor nodes fail to perform in the intended settings. I worked with my students to build this new solar-powered sensor node that overcame many engineering challenges in power management, real-time scheduling, and communication protocols. The result was a durable, robust wireless sensor system that can collect data and transmit the results in real-time over a wireless Internet connection. This sensor node has been demonstrated in April 2004 on the green steel bridge on East Peltason Dr., UCI, and will be deployed throughout the new Cal(IT)2 building. This sensor node design not only provides a brand new technology for civil engineering as articulated in (C25), but it also encompasses many innovations in electrical and computer engineering, including impedance matching with the solar panel by dynamic power management (C27) and reduction of power fragmentation with multiple ambient power sources (C26). These novel aspects were recognized with our second Low Power Design Contest Award ($2,825 in cash prize) at ISLPED in 2004. It was one of the four winners out of 11 submissions.

In November 2004, a new dual-microcontroller DuraNode has been constructed and demonstrated at the Cal(IT)2 open house. Details of this paper will be published in (C32). It supports low-jitter operation, aggressive power management capabilities, and ability to interface with sensors with very different voltage levels.

Eco (2004--)

The second sensor node is called Eco, a world record setter for being the smallest wireless sensor node to date (C33). Only 557mm³ in volume and 1.6 grams in weight, Eco is designed to be worn on the limbs of pre-term infants to monitor their spontaneous movement in response to assisted exercises. Professor Andrei Shkel of Mechanical Engineering, an expert on sensor devices, was working with UCI Medical researchers on this problem, and we designed this ultra-compact sensor node that is only 11% the volume of the smallest of the most popular commercial sensor node, the Mica2DOT from Crossbow. This required overcoming many engineering challenges that are currently still in the publication pipeline, but the novelty was also recognized with our third Low Power Design Contest Award (another $2,825 in cash prize) at ISLPED 2004.

2.3 Medical Instrumentation: Mini-FDM

Mini-FDPM is a noninvasive, optical handheld breast-cancer detector based on the principles of frequency domain photon migration (FDPM), developed by Professor Bruce Tromberg at the Beckman Laser Institute (BLI) at UCI. In addition to shrinking a refrigerator-sized instrument down to a handheld unit, I overcame challenges in broadband and low-power system design. The result is a medical instrument that is higher performance and significantly lower cost than current systems, making it practical for replication and wide distribution. The version from Fall 2004 was published in (C31). I have been invited to participate in the meeting for NTROI -- Network for Translational Research on Optical Imaging, a National Cancer Institute sponsored Network administered through the BLI -- to showcase the Mini-FDPM design to other researchers who would benefit from this technology. This work also lays the foundation for research on a system-on-chip implementation and FDPM-based imaging system.

3. Previous Research: Chinook (1992--1998)

In the first phase (B1, C4), Chinook focused on hardware/software interface synthesis (C1, C5) with the goal of minimizing hardware; and scheduling for multi-mode systems (C2) and for meeting interface-level timing (J1, C3). In the second phase, interface-synthesis was raised to the higher level to IP blocks (C10). Here the "interface" is not so much the detailed signaling, but the higher-level coordination protocol, which is often hardwired in the control-flow constructs and is the primary obstacle to reuse (C8). I propose a way to compose control (C8, C9) and synthesize the distributed protocol controllers (C6, C11). The coordination protocol (CP) view represents a departure from the model-of-computation (MoC) view popularized by Ptolemy: an MoC captures a class of CP's, but MoC's are either over-constraining or over-generalized.