2 citations · 2 across the 4 of their papers we have counts for
4 papers
Faver: Boosting LLM-based RTL Generation with Function Abstracted Verifiable Middleware
Jianan Mu, Mingyu Shi, Yining Wang +5
LLM-based RTL generation is an interesting research direction, as it holds the potential to liberate the least automated stage in the current chip design. However, due to the subst…
FicGCN: Unveiling the Homomorphic Encryption Efficiency from Irregular Graph Convolutional Networks
Zhaoxuan Kan, Husheng Han, Shangyi Shi +5
Graph Convolutional Neural Networks (GCNs) have gained widespread popularity in various fields like personal healthcare and financial systems, due to their remarkable performance.…
FlexMem: High-Parallel Near-Memory Architecture for Flexible Dataflow in Fully Homomorphic Encryption
Shangyi Shi, Husheng Han, Jianan Mu +7
Fully Homomorphic Encryption (FHE) imposes substantial memory bandwidth demands, presenting significant challenges for efficient hardware acceleration. Near-memory Processing (NMP)…
InputSnatch: Stealing Input in LLM Services via Timing Side-Channel Attacks
Xinyao Zheng, Husheng Han, Shangyi Shi +4
Large language models (LLMs) possess extensive knowledge and question-answering capabilities, having been widely deployed in privacy-sensitive domains like finance and medical cons…