The focus of the GREEN lab is to create scientific understanding and engineering techniques to design future generation computers. We seek to develop the smart machines that are intelligent to generate usable information from data, secure to ensure privacy and prevent malicious attacks, and finally, energy-effiienct to operate under tight resource constraints. We are breaking the traditional boundaries of design abstractions and creating a holistic understanding and methodology for integrated system design.
The GREEN lab is led by Prof. Saibal Mukhopadhyay. Our research interests include artificial intelligence, energy-efficient design, and secure hardware. We explore cross-layer innovations spanning algorithm, architecture, and mixed-signal circuit design.
Congratulations!! Taesik Na has successfully defended their PhD thesis in June 2018.
We will present a paper on Ferroelectric Field Effect Transistor (FeFET) based deep learning accelerator at IEEE/ACM ICCAD 2018.
Paper on an accelerator for training deep learning network will be presented in ESWEEK 2018 and will be published in IEEE TCAD special issue. The paper is nominated for the Best Paper Award at CASES 2018.
We will present two papers on smart sensors at IEEE S3S 2018. One paper will present an SoC for self-powered image sensor, and second paper will show the impact of 3D integration of mixed-signal neural network accelerator with digital pixel image sensors.