The new iPhone processor can perform more than 1 billion floating point operations per second (or 1 giga FLOPS), consuming approximately 1 Watt. The human brain is estimated to be capable of performing an astounding 20,000,000 giga FLOPS, but consumes a mere 20 Watts! Clearly, nature’s methods and engines for information processing are far superior to the best man-made systems today.
The goal of neuromorphic engineering is to understand the key architectural principles of the brain and to build new computational hardware mimicking these algorithms without compromising on size or power efficiency. In this talk, he will discuss some of the fundamental principles of computation employed by the brain, and the opportunities and challenges in building truly intelligent as well as power efficient information processing systems using novel nanoscale materials and devices.
Dr. Bipin Rajendran is an Assistant Professor in the Department of Electrical Engineering at Indian Institute of Technology, Bombay. He was a Master Inventor and Research Sta? Member at IBM T. J. Watson Research Center in New York during 2006-2012, engaged in exploratory research on non-volatile memory and neuromorphic computation. He has co-authored a book on phase change memory, published more than 30 papers in peer reviewed journals and conferences and has been issued 30 US patents. In Spring 2012, he was an Adjunct Associate Professor in the Engineering school at Columbia University, during which he taught a graduate course on Neuromorphic Engineering. He received a B.Tech. (2000) from Indian Institute of Technology, Kharagpur and M.S. (2003) and Ph.D. (2006) in Electrical Engineering from Stanford University.