Intellectual Merit: This BRIGE project aims at achieving robust ultra-low power computation by exploiting the stochastic switching behavior observed within a CMOS digital circuit that is driven by an ultra-low supply voltage approaching the digital switching limit. This objective is motivated by two observations. First, probabilistic inference and stochastic learning are fundamental in sensor data processing. Second, emerging devices will exhibit sophisticated physical property that may natively compute probabilistic algorithms. This proposed effort will first model and analyze the stochastic switching behavior in minimum-energy CMOS transistors under ultra-low VDD (¡Ö 50mV) both analytically and experimentally. Subsequently, it will develop a field-theoretic methodology to optimize a large-scale logic circuit built with such stochastic switching devices in order to improve its robustness. Finally, it will exploit the stochastic switching behavior natively to design and implement AnaLogic circuits (between analog and logic circuits) that emulate a robust self-motion algorithm inspired by fly eye based on optical flow extraction.
Broader Impacts: Leveraging the physics of field-effect devices to perform computational tasks, this proposed research could potentially inspire a totally unconventional design paradigm for emerging nanoscale device technology with severe device variability and switching uncertainty. Furthermore, the proposed field-theoretic approach offers a rich mathematical structure, therefore can broaden the current digital circuit design theory. Finally, the proposed methodology can enable more accurate understanding of existing logic circuit design methods, especially on their limitations when directly applied to future device technologies driven by ultra-low VDD. Besides disseminating its research findings through new curricula and hardware-based stochastic logic circuit emulations, this project will approach the challenge of broadening the engineering participation from underrepresented minority groups in both bottom-up (public STEM education) and top-down (PhD students recruiting) directions. The PI will create mentoring and outreach programs specifically designed to attract female, African-American, Latino, and first-generation college students to join his group, thus preparing a new diverse work force for the computing industry. Additionally, the Orlando Science Center will be used as the main platform to stimulate public interests in STEM education of computing. The success of this educational effort, through innovative exhibits and engaging mini-lectures, will be judged by the PhD enrollment of computer engineering from underrepresented groups at UCF and the size of public audience to its collaborative exhibit efforts with the Orlando Science Center.
