Brain-Inspired Computing: The Extraordinary Voyages in Known and Unknown Worlds
Human brain is the most sophisticated organ that nature ever builds. Building a machine that can function like a human brain, indubitably, is the ultimate dream of a computer architect. Although we have not yet fully understood the working mechanism of human brains, the part that we have learned in past seventy years already guided us to many remarkable successes in computing applications, e.g., artificial neural network and machine learning. The recently emerged research on "neuromorphic computing", which stands for hardware acceleration of brain-inspired computing, has become one of the most active areas in computer engineering. Our presentation starts with a background introduction of neuromorphic computing, followed by two examples of hardware acceleration schemes of learning and neural network algorithms on IBM TrueNorth Chip and memristor-based computing engine, respectively. At the end, we will share our prospects on the future technology challenges and advances of neuromorphic computing.
Dr. Yiran Chen received B.S and M.S. (both with honor) from Tsinghua University and Ph.D. from Purdue University in 2005. After five years in industry, he joined University of Pittsburgh in 2010 as Assistant Professor and then promoted to Associate Professor in 2014. He is now holding Bicentennial Alumni Faculty Fellow and co-directing Evolutionary Intelligence Lab (www.ei-lab.org) at Electrical and Computer Engineering Department, focusing on the research of nonvolatile memory and storage systems, neuromorphic computing, and mobile applications. Dr. Chen has published one book, a dozen of book chapters, and more than 250 journal and conference papers. He has been granted with 90 US and international patents with other 13 pending applications. He is the associate editor of IEEE TCAD, IEEE D&T, IEEE ESL, ACM JETC, ACM SIGDA E-newsletter and served on the technical and organization committees of around 40 international conferences. He received 3 best paper awards from ISQED'08, ISLPED'10 and GLSVLS'13 and other a dozen nominations from DAC, DATE, ASPDAC, ISLPED, CODES+ISSS, etc. He also received NSF CAREER award in 2013, ACM SIGDA outstanding new faculty award in 2014, and was the invitee of 2013 U.S. Frontiers of Engineering Symposium of National Academy of Engineering