5 papers
RRAM-DP: Device-Calibrated Differential Privacy for In-Memory Edge Learning
Kwunhang Wong, Jichang Yang, Karl M. H. Lai +7
Edge Artificial Intelligence of Things (AIoT) systems often collect sensitive data in situ, raising serious privacy concerns. Resistive-switching random-access memory (RRAM) is an…
FusionCIM: Accelerating LLM Inference with Fusion-Driven Computing-in-Memory Architecture
Zihao Xuan, Jia Chen, Yewen Li +4
In this paper, we propose FusionCIM, an operator-fusion-driven compute-in-memory (CIM) accelerator architecture for efficient and scalable LLM inference, with three key innovations…
Continuous-Time Digital Twin with Analogue Memristive Neural Ordinary Differential Equation Solver
Hegan Chen, Jichang Yang, Jia Chen +20
Digital twins, the cornerstone of Industry 4.0, replicate real-world entities through computer models, revolutionising fields such as manufacturing management and industrial automa…
Resistive Memory-based Neural Differential Equation Solver for Score-based Diffusion Model
Jichang Yang, Hegan Chen, Jia Chen +19
Human brains image complicated scenes when reading a novel. Replicating this imagination is one of the ultimate goals of AI-Generated Content (AIGC). However, current AIGC methods,…
Random resistive memory-based deep extreme point learning machine for unified visual processing
Shaocong Wang, Yizhao Gao, Yi Li +21
Visual sensors, including 3D LiDAR, neuromorphic DVS sensors, and conventional frame cameras, are increasingly integrated into edge-side intelligent machines. Realizing intensive m…