Oct 6 (Thu) @ 7:00pm: "Towards High-Performance, Efficient, and Reliable Quantum Computing System," Gushu Li, ECE PhD Defense
https://ucsb.zoom.us/j/7736663712
Abstract
As the new "race to the moon", quantum computing can possibly trigger a computation revolution due to its strong potential in several important domains, e.g., cryptography, chemistry simulation, optimization, and machine learning. However, as an emerging research area, grand challenges remain ahead since state-of-the-art quantum computing, from software to hardware, is still highly immature. In this talk we will explore high-performance, efficient, and reliable quantum computing systems, and strike a synergy among different technology stacks, including application, programming language, compiler optimization, hardware architecture design, simulation. This talk will first focus on the software side. We will summarize the challenges in designing quantum software systems as the sizes of quantum computer systems continue to grow. Then we will show how we can overcome this grand scalability challenge by leveraging the power of high-level operators in various important tasks, including quantum compiler optimization, quantum program testing, and so on. In the end, we will briefly introduce our work on quantum software-hardware co-design and conclude this defense with future research opportunities.
Bio
Mr. Gushu Li is a Ph.D. candidate at the University of California, Santa Barbara, advised by Prof. Yuan Xie and Prof. Yufei Ding. He is an incoming Assistant Professor at the University of Pennsylvania. His research features the emerging quantum computer system and spans mainly across the quantum programming language, quantum compiler, and quantum computer architecture. His research has been recognized by the ACM SIGPLAN Distinguished Paper Award at OOPSLA 2020 and an NSF Quantum Information Science and Engineering Network Fellow Grant Award. His research outputs have been adopted by several industry/academia quantum software frameworks, including IBM’s Qiskit, Amazon’s Braket, Cambridge Quantum Computing’s TKET, and Oak Ridge National Lab’s qcor.
Hosted by: Professor Yufei Ding
Submitted by: Gushu Li <gushuli@ece.ucsb.edu>