The rapid growth in Internet-of-Things (IoT) and Artificial Intelligence (AI) is creating a huge demand for intelligent electronic devices with very low cost and high energy efficiency. Conventional digital technology is faced with computing bottleneck due to the difficulty of further technology scaling. As a result, new computing methods are urgently needed to meet the demand from the machine learning empowered applications. This project explores a non-conventional time-domain computing technique with promise of bringing fundamental improvement to the energy efficiency of computing. The project can potentially bring significant advancement to the IoT/AI developments by enabling expensive machine learning operations in small IoT devices or sensor nodes. This project will also create significant outreach activities to the society by disseminating the study of energy efficient edge processing to K-12 students and underrepresented groups through a combination of workshops and training programs. New course materials and hand-on experiments will be introduced to undergraduate and graduate students to promote a cross-layer learning strategy from algorithm to hardware design for computer engineering.
This project aims at developing a systematic design approach for the emerging time-domain computing which utilizes time for information processing. The proposed developments cover a range of techniques including circuit design, electronic design automation, implementation of machine learning algorithms and integration for near-sensor computing. Specifically, the project will be dedicated to: (1) developing a thorough design principles of the time-domain computing, (2) developing a design automation methodology that is compatible with modern commercial tools and capable of large-scale implementation of the techniques, (3) exploring its strong benefits in machine learning and other popular computing algorithms, and (4) performing system integration with sensor nodes for intelligent edge processing devices. The project will deliver a highly automated systematic design methodology enabling large-scale integration and enhanced energy-efficiency for new time-domain computing techniques.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
