Date and Time:
Location: Large Seminar room OMZ (U014, INF 350, floor -1)
As part of the ZITI Colloquium, we are pleased to welcome Prof. Jie Han from the University of Alberta, who will present his talk:
Approximate and Stochastic Ising Machines
The Ising model is useful in searching for (sub-)optimal solutions to combinatorial optimization problems. CMOS implementations of Ising model-based solvers, commonly referred to as Ising machines, provide reliable and accurate solutions with flexible and dense connectivity. However, they incur significant hardware overhead.
Approximate computing, as a low-power technique, offers a way to reduce hardware complexity, while stochastic computing is efficient in simulating the dynamics of the Ising model. The approximations introduced by these techniques may also be beneficial in helping the system escape from local minima.
In this talk, Prof. Jie Han will discuss the potential of using approximate and stochastic computing to improve the performance of Ising machines.
CV
Jie Han received his B.Sc. degree in Electronic Engineering from Tsinghua University, Beijing, China, and his Ph.D. degree from Delft University of Technology, the Netherlands. He is currently a Professor in the Department of Electrical and Computer Engineering at the University of Alberta, Edmonton, Canada.
Prof. Han has received numerous scientific awards and recognitions, including Best Paper Awards at DATE 2023 and NANOARCH 2015, as well as several Best Paper Nominations. His work on fault-tolerant nanocircuits was also recognized in the 125th anniversary issue of Science Magazine.
He serves or has served as an Associate Editor for several IEEE and international journals and has held leading roles at numerous international conferences, including IEEE NANO, NANOARCH, GLSVLSI, and DFT.
We look forward to welcoming everyone to this exciting ZITI Colloquium.