4 papers
FedBit: Accelerating Privacy-Preserving Federated Learning via Bit-Interleaved Packing and Cross-Layer Co-Design
Xiangchen Meng, Yangdi Lyu
Federated learning (FL) with fully homomorphic encryption (FHE) effectively safeguards data privacy during model aggregation by encrypting local model updates before transmission,…
AutoVeriFix: Automatically Correcting Errors and Enhancing Functional Correctness in LLM-Generated Verilog Code
Yan Tan, Xiangchen Meng, Zijun Jiang +1
Large language models (LLMs) have demonstrated impressive capabilities in generating software code for high-level programming languages such as Python and C++. However, their appli…
MiCo: End-to-End Mixed Precision Neural Network Co-Exploration Framework for Edge AI
Zijun Jiang, Yangdi Lyu
Quantized Neural Networks (QNN) with extremely low-bitwidth data have proven promising in efficient storage and computation on edge devices. To further reduce the accuracy drop whi…
HF-NTT: Hazard-Free Dataflow Accelerator for Number Theoretic Transform
Xiangchen Meng, Zijun Jiang, Yangdi Lyu
Polynomial multiplication is one of the fundamental operations in many applications, such as fully homomorphic encryption (FHE). However, the computational inefficiency stemming fr…