The research activities of Li’s group span several themes: integrated circuits and systems, parallel computing, computational biology/neuroscience:
In the past several decades, CMOS technology scaling has enabled the proliferation of a wide spectrum of electronic systems, ranging from microprocessors, DSP processors, system-on-a-chips, consumer electronics and sensors, literally into every aspect of human life. Technology scaling not only offers increasing system performance at lower cost, but also, as an unavoidable side effect, introduces significant challenges as we strive for the next-level of high performance and high reliability in power-efficient circuits and systems. The ability in analyzing, designing and verifying increasingly complex designs plays a critical role in capitalizing nanometer manufacturing technology. On the other hand, new system architectures and design strategies, notably multi-core microarchietures, self-test & self-adapting designs, and bio-inspired circuits, have emerged for achieving optimal performance, power and reliability tradeoffs in lieu of technology scaling. This calls for new design techniques as well as CAD methodologies for such systems.
Current research topics are:
- Parallel algorithms and tools for integrated system design on multi-/many-core, GPU and distributed platforms
- Design of power distribution networks, voltage regulation/conversion circuits for energy-efficient IC power delivery
- Design verification, built-in test and tuning of analog/RF circuits
- Silicon-based machine learning
- Biophysically based simulation and modeling of brain networks
- Bio-inspired architectures and circuits
Our research has been funded by the National Science Foundation (NSF), Texas Analog of Excellence (TxAcE), Semiconductor Research Corporation (SRC), and the US semiconductor industry with collaboration with major semiconductor and EDA companies (IBM, Intel, Freescale Semiconductors, Texas Instruments, AMD, Mentor Graphics etc) and other interdisciplinary research teams.