2024-01-24T11:48:18+08:002024-01-23|News&Events, Events|

The Distinguished Lecture on “Reconfigurable Compute-In-Memory on Ferroelectric Memory Technology” will take place as follows:

Date: 25 January 2024 (Thursday)

Time: 16:00-16:45

Venue: Research Building N21, G013

The speaker is:

Prof. Liu Xiwen, Assistant Professor, the Hong Kong University of Science and Technology (Guangzhou)


The Lecture is:

Reconfigurable Compute-In-Memory on Ferroelectric Memory Technology



Current computing systems are mainly constructed on the von Neumann architecture, where data needs to be transferred to a processing unit from memory components. The latency associated with accessing data from the memory units is a key performance bottleneck for a range of data-intensive applications in the convergence of big data and AI. Several solutions have been proposed to mitigate and overcome this bottleneck, with a prominent one being placing memory and logic units in close physical proximity. While significant progress has been made along those lines at both technology and architecture levels, a transformative approach would be to perform computing functions precisely where the data are stored using memory devices. This is known as compute-in-memory. In this talk, I will begin by discussing the most recent advancements in the CMOS-compatible ferroelectric memory technologies on aluminum nitride platform. Second, I will present a reconfigurable compute-In-memory system on field-programmable ferroelectric diodes, allowing for on-chip memory, parallel search, and neural network operation. Last, I will discuss the conceptualization and demonstration of a programmable parallel search architecture – analog content-addressable memory (ACAM) on complementary Si-CMOS ferroelectric field-effect-transistor memory. The deployment and acceleration of attention-based deep neural network and kernel method on ACAM will also be presented.



Dr. Liu Xiwen joined the Hong Kong University of Science and Technology (Guangzhou) as an Assistant Professor in 2023. In 2023, he obtained his Ph.D. from the Department of Electrical and Systems Engineering at the University of Pennsylvania in the United States. Dr. Liu’s research interests include micro/nano-electronic devices, novel memory technologies, device-circuit-architecture co-design, and the exploration of non-conventional computing paradigms. To date, he has authored and co-authored over 20 publications in important international journals and conferences, including Nano Letters, Applied Physics Letters, Cell Press Matter, Nature Electronics, and Cell Press Device, among others. His research work in the field of compute-in-memory technology has been recognized by the Bell Labs Prize 2022, and he has received the National Outstanding Self-Financed Students Scholarship for the year 2022.


For more details, kindly find the event poster, abstract and bio.