All seminars will take place via Zoom on Fridays at 11 a.m.
October 30, 2020
11:00am - 12:00pm
Brain-Inspired Hyperdimensional System for Efficient and Robust Cognitive Learning
Modern computing systems are plagued with significant issues in efficiently performing learning tasks. In this talk, I will present a new brain-inspired computing system that supports various learning and cognitive tasks while offering significantly high computation efficiency and robustness than existing platforms. Our platform utilizes HyperDimensional (HD) computing, an alternative method of computation that implements principles of the brain functionality: (i) fast learning, (ii) robustness to noise/error, and (iii) intertwined memory and logic. These features make HD computing a promising solution for today’s embedded devices with limited resources as well as future computing systems in deep nanoscaled technology that have issues of high noise and variability. To leverage the memory-centric nature of HD computing, I exploit emerging technologies to enable processing in-memory which is capable of highly-parallel computation and data movement reduction. I will also show how this architecture can accelerate a wide range of big data applications such as deep learning.
Mohsen Imani is an Assistant Professor in the Department of Computer Science at UC Irvine. He is also a director of Bio-Inspired Architecture and Systems (BIASLab). He is working on a wide range of practical problems in the area of brain-inspired computing, machine learning, computer architecture, and embedded systems. His research goal is to design real-time, robust, and programmable computing platforms that can natively support a wide range of learning and cognitive tasks on edge devices. Dr. Imani received his Ph.D. from the Department of Computer Science and Engineering at the UC San Diego. He has a stellar record of publication with over 90 papers in top conferences/journals. His contribution has led to a new direction on brain-inspired hyperdimensional computing that enables ultra-efficient and real-time learning and cognitive support. His research was also the main initiative in opening up multiple industrial and governmental research programs. Dr. Imani research has been recognized with several awards, including the Bernard and Sophia Gordon Engineering Leadership Award, the Outstanding Researcher Award, and the Powell Fellowship Award. He also received the Best Doctorate Research from UCSD and several best paper nomination awards at multiple top conferences including Design Automation Conference (DAC) in 2019 and 2020, Design Automation and Test in Europe (DATE) in 2020, and International Conference on Computer-Aided Design (ICCAD) in 2020.