13 citations · 31 across the 11 of their papers we have counts for
12 papers
HE^2: A Communication-Light Heterogeneous Architecture for Efficient Fully Homomorphic Encryption
Shangyi Shi, Husheng Han, Zhaoxuan Kan +8
CKKS, an emerging fully homomorphic encryption (FHE) scheme, has been promising in privacy-preserving applications by enabling SIMD fixed-point computations on ciphertexts. Despite…
AutoPPA: Automated Circuit PPA Optimization via Contrastive Code-based Rule Library Learning
Chongxiao Li, Pengwei Jin, Di Huang +14
Performance, power, and area (PPA) optimization is a fundamental task in RTL design, requiring a precise understanding of circuit functionality and the relationship between circuit…
Think with Self-Decoupling and Self-Verification: Automated RTL Design with Backtrack-ToT
Zhiteng Chao, Yonghao Wang, Xinyu Zhang +9
Large language models (LLMs) hold promise for automating integrated circuit (IC) engineering using register transfer level (RTL) hardware description languages (HDLs) like Verilog.…
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)…
AGON: Automated Design Framework for Customizing Processors from ISA Documents
Chongxiao Li, Di Huang, Pengwei Jin +12
Customized processors are attractive solutions for vast domain-specific applications due to their high energy efficiency. However, designing a processor in traditional flows is tim…
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…
TensorTEE: Unifying Heterogeneous TEE Granularity for Efficient Secure Collaborative Tensor Computing
Husheng Han, Xinyao Zheng, Yuanbo Wen +11
Heterogeneous collaborative computing with NPU and CPU has received widespread attention due to its substantial performance benefits. To ensure data confidentiality and integrity d…
Pushing the Limits of Machine Design: Automated CPU Design with AI
Shuyao Cheng, Pengwei Jin, Qi Guo +16
Design activity -- constructing an artifact description satisfying given goals and constraints -- distinguishes humanity from other animals and traditional machines, and endowing m…
Unlearnable Examples Give a False Sense of Data Privacy: Understanding and Relearning
Pucheng Dang, Xing Hu, Kaidi Xu +5
Unlearnable examples are proposed to prevent third parties from exploiting unauthorized data, which generates unlearnable examples by adding imperceptible perturbations to public p…
Real-Time Robust Video Object Detection System Against Physical-World Adversarial Attacks
Husheng Han, Xing Hu, Kaidi Xu +7
DNN-based video object detection (VOD) powers autonomous driving and video surveillance industries with rising importance and promising opportunities. However, adversarial patch at…
ScaleCert: Scalable Certified Defense against Adversarial Patches with Sparse Superficial Layers
Husheng Han, Kaidi Xu, Xing Hu +6
Adversarial patch attacks that craft the pixels in a confined region of the input images show their powerful attack effectiveness in physical environments even with noises or defor…