Private AI

Helios: Melting Kernel Boundaries for GPU-Accelerated HE via Graph Rewriting and Microarchitecture-Aware Mapping

Yi Chen, Ziyu Tang, Chao Yang, Guang Fan, Mingzhe Zhang, Meng Li

OptiPrime: Optimizing Private Inference through protocol-hardware codesign

Jiangrui Yu, Ye Yu, Si Chen, Chenqi Lin, Wenxuan Zeng, Junfeng Fan, Mingyu Gao, Meng Li

CryptoMoE: Privacy-Preserving and Scalable Mixture of Experts Inference via Balanced Expert Routing

Yifan Zhou, Tianshi Xu, Jue Hong, Ye Wu, Meng Li

MPCache: MPC-Friendly KV Cache Eviction for Efficient Private LLM Inference

Wenxuan Zeng, Ye Dong, Jinjin Zhou, Jin Tan, Lei Wang, Tao Wei, Runsheng Wang, Meng Li

FENIX: Flexible and Efficient Hybrid HE/MPC Acceleration with Near-Memory Processing

Tengyu Zhang, Chenqi Lin, Jiangrui Yu, Shuwen Deng, Meng Li

Ironman: Accelerating Oblivious Transfer Extension for Privacy-Preserving AI with Near-Memory Processing

A near-memory architecture that accelerates oblivious-transfer extension, a key bottleneck in privacy-preserving AI.

Chenqi Lin, Kang Yang, Tianshi Xu, Ling Liang, Yufei Wang, Zhaohui Chen, Runsheng Wang, Mingyu Gao, Meng Li

Breaking the Layer Barrier: Remodeling Private Transformer Inference with Hybrid CKKS and MPC

A hybrid CKKS/MPC framework that remodels private Transformer inference through fine-grained operator fusion.

Tianshi Xu, Wenjie Lu, Jiangrui Yu, Chenqi Lin, Yi Chen, Runsheng Wang, Meng Li

FLASH: An Efficient Hardware Accelerator Leveraging Approximate and Sparse FFT for Homomorphic Encryption

Tengyu Zhang, Yufei Xue, Ling Liang, Zhen Gu, Yuan Wang, Runsheng Wang, Ru Huang, Meng Li

PrivCirNet: Efficient Private Inference via Block Circulant Transformation

Tianshi Xu, Lemeng Wu, Runsheng Wang, Meng Li

FlexHE: A flexible Kernel Generation Framework for Homomorphic Encryption-Based Private Inference

Jiangrui Yu, Wenxuan Zeng, Tianshi Xu, Renze Chen, Yun (Eric) Liang, Runsheng Wang, Ru Huang, Meng Li