Towards Practical Superconducting Computing with Technology-Driven Optimizations

Abstract: Semiconductors have dominated every aspect of electronics over the past decades. However, the diminishing gains in performance and power efficiency observed in recent years, coupled with the diversification of target applications, have sparked a search for the next breakthrough. Although it is unlikely for semiconductors to be completely replaced in the foreseeable future, there are signs that a transition to superconductors may benefit many domains from classical high-performance computing and quantum computing to sensing systems. In this talk, I firstly introduce the underlying principles of superconductor electronics and describe how common misconceptions have hampered progress. Secondly, I present a logic-biasing co-optimization that results in a versatile superconducting logic family with truly zero static power dissipation. Thirdly, I describe how to overcome the biggest obstacle in superconducting computing—the lack of a scalable memory solution—by exploiting nearly-lossless passive superconducting delay lines. Finally, I outline a roadmap for practical superconducting computing and discuss how this can be generalized to close the gap between other emerging devices and applications.

Bio: Jennifer Volk is a Ph.D. candidate in Electrical and Computer Engineering at UC Santa Barbara; a researcher at MIT Lincoln Laboratory; and a visiting scholar at the University of Michigan. Her research spans from applied physics to circuit design and computer architecture and has been published in top venues, including Nature Sci. Rep., DAC, ISCA, ASPLOS, and PLDI. Her contributions have been recognized by the respective communities with two IEEE Micro Top Picks distinctions and a Best Student Paper award at the Applied Superconductivity Conference. She was also selected as a 2023 EECS Rising Star.