Neuro-inspired computing: From resistive memory to optics
- Charles Mackin
- Pritish Narayanan
- et al.
- 2019
- CLEO/Europe-EQEC 2019
HsinYu (Sidney) Tsai received her Ph.D. from the Electrical Engineering and Computer Science department at Massachusetts Institute of Technology in 2011. After graduation, Sidney joined the Nanofabrication and Electron Beam Lithography group at the IBM T.J. Watson Research Center as Research Staff Member and developed directed self-assembly (DSA) lithography for finFETs. From 2015-2016, Sidney served as the manager of the Advanced Lithography group in the Microelectronics Research Laboratory (MRL), managing operations of a 200mm research prototyping line.
Sidney currently works in the Almaden Research Center in San Jose, CA, as a Principal Research Staff Member and manager of the Analog AI group. Analog AI based on Phase Change Memory (PCM) devices utilizes emerging non-volatile memory for compute vector-matrix multiplication at the location of the data, potentially achieving high power performance for deep learning workloads in the Cloud and on the edge. The group demonstrates software compatible accuracies for both training and inference of Deep Neural Networks (DNNs). The team published two papers in Nature in 2018 and 2023, one on training and one on inference. The two inference chips with PCM devices fabricated on top of 14nm CMOS transistors was highlighted at VLSI in 2021.