18 citations · 21 across the 21 of their papers we have counts for
6 papers · 1 filter
Breaking the Layer Barrier: Remodeling Private Transformer Inference with Hybrid CKKS and MPC
Tianshi Xu, Wen-jie Lu, Jiangrui Yu +4
This paper presents an efficient framework for private Transformer inference that combines Homomorphic Encryption (HE) and Secure Multi-party Computation (MPC) to protect data priv…
No Redundancy, No Stall: Lightweight Streaming 3D Gaussian Splatting for Real-time Rendering
Linye Wei, Jiajun Tang, Fan Fei +3
3D Gaussian Splatting (3DGS) enables high-quality rendering of 3D scenes and is getting increasing adoption in domains like autonomous driving and embodied intelligence. However, 3…
SpecASR: Accelerating LLM-based Automatic Speech Recognition via Speculative Decoding
Linye Wei, Shuzhang Zhong, Songqiang Xu +3
Large language model (LLM)-based automatic speech recognition (ASR) has recently attracted a lot of attention due to its high recognition accuracy and enhanced multi-dialect suppor…
HybriMoE: Hybrid CPU-GPU Scheduling and Cache Management for Efficient MoE Inference
Shuzhang Zhong, Yanfan Sun, Ling Liang +3
The Mixture of Experts (MoE) architecture has demonstrated significant advantages as it enables to increase the model capacity without a proportional increase in computation. Howev…
ReaLM: Reliable and Efficient Large Language Model Inference with Statistical Algorithm-Based Fault Tolerance
Tong Xie, Jiawang Zhao, Zishen Wan +5
The demand for efficient large language model (LLM) inference has propelled the development of dedicated accelerators. As accelerators are vulnerable to hardware faults due to agin…
LightMamba: Efficient Mamba Acceleration on FPGA with Quantization and Hardware Co-design
Renjie Wei, Songqiang Xu, Linfeng Zhong +5
State space models (SSMs) like Mamba have recently attracted much attention. Compared to Transformer-based large language models (LLMs), Mamba achieves linear computation complexit…