Title: Solving combinatorial optimization using oscillator-based dynamical systems
Abstract: Modern information processing relies largely on digital computers. However, a large class of combinatorial optimization problems, with extensive practical applications, are still considered intractable to solve on a traditional digital platform. Solving such problems typically entails exponentially increasing computing resources (time, memory etc.) as the problem sizes increase, and practical problems become unmanageable without the use of enormous, energy-guzzling computing resources. Consequently, overcoming this limitation has motivated the quest to find efficient beyond-digital computing fabrics. In this talk, I will describe one such potentially promising paradigm based on analog dynamical systems of electronic oscillators.
Speaker Bio: Nikhil Shukla is currently an assistant
professor at the University of Virginia with a joint appointment in the department of Electrical & Computer Engineering, and the department of Materials Science and Engineering. He received his PhD from the University of Notre Dame in 2017. Nikhil’s research
interests lie in co-designing new devices, circuits, and computational models to make computing more efficient. He has authored/co-authored over 50 journal and conference papers and has received the best paper award from IEEE TMSCS in 2017. He has also served
on the technical program committee for Design Automation Conference (DAC) in 2020 and 2021.