Neuromorphic Computing
11/29/2022
In this talk Anup shows his recent work on hardware-software interface for such systems. He discusses a compiler tool chain that his team has developed to translate a user’s machine learning program to low-level languages that can be interpreted by neuromorphic systems. He also presented interesting resource optimization strategies to improve program performance, energy, reliability, and security. Finally, he presented an Operating System like framework that we have developed to allow programmers to easily deploy their machine learning programs on neuromorphic computers as well as to perform full-stack co-design of neuromorphic systems.
Anup Das
Dr. Anup Das is an Associate Professor at Drexel University. He received a Ph.D. in Embedded Systems from National University of Singapore in 2014. Following his Ph.D., he was a postdoctoral fellow at the University of Southampton, UK and a researcher at IMEC in Belgium/Netherlands. He is the recipient of NSF/DARPA RTML award in 2019, NSF Early Faculty CAREER award in 2020, and DOE CAREER award in 2021. His work led to several best paper nominations. His research focuses on neuromorphic computing and architectural exploration. He is a senior member of the IEEE.