Private AI

Cachemir: Fully Homomorphic Encrypted Inference of Generative Large Language Model with KV Cache

一种在全同态加密大语言模型推理中高效集成KV缓存以加速自回归解码的框架。

Ye Yu, Yifan Zhou, Yi Chen, Pedro Soto, Wenjie Xiong, 李萌

ROSETTA: Efficient and Accurate Privacy-Preserving LLM Decoding via Hybrid CKKS/TFHE Evaluation

一种采用混合CKKS/TFHE计算的高效、准确隐私保护大语言模型自回归解码框架。

Jiangrui Yu, Baosheng Zhang, Liang Kong, Lin Ding, Yi Chen, Ye Yu, Mingzhe Zhang, 李萌

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, 李萌

OptiPrime: Optimizing Private Inference through protocol-hardware codesign

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

PEFT: A Near-Memory Processing-Enabled Heterogeneous Accelerator for BatchPBS TFHE

一种面向BatchPBS TFHE工作负载、通过近存计算减少数据搬移的异构加速器。

Jiangrui Yu, Yi Chen, 李萌

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

Yifan Zhou, Tianshi Xu, Jue Hong, Ye Wu, 李萌

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, 李萌

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

Tengyu Zhang, Chenqi Lin, Jiangrui Yu, Shuwen Deng, 李萌

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, 李萌

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, 李萌