6 citations · 19 across the 18 of their papers we have counts for
5 papers · 1 filter
AccLLM: Accelerating Long-Context LLM Inference Via Algorithm-Hardware Co-Design
Yanbiao Liang, Huihong Shi, Haikuo Shao +1
Recently, large language models (LLMs) have achieved huge success in the natural language processing (NLP) field, driving a growing demand to extend their deployment from the cloud…
M-ViT: Accelerating Hybrid Vision Transformers with Two-Level Mixed Quantization
Yanbiao Liang, Huihong Shi, Zhongfeng Wang
Although Vision Transformers (ViTs) have achieved significant success, their intensive computations and substantial memory overheads challenge their deployment on edge devices. To…
An FPGA-Based Reconfigurable Accelerator for Convolution-Transformer Hybrid EfficientViT
Haikuo Shao, Huihong Shi, Wendong Mao +1
Vision Transformers (ViTs) have achieved significant success in computer vision. However, their intensive computations and massive memory footprint challenge ViTs' deployment on em…
Instant-3D: Instant Neural Radiance Field Training Towards On-Device AR/VR 3D Reconstruction
Sixu Li, Chaojian Li, Wenbo Zhu +6
Neural Radiance Field (NeRF) based 3D reconstruction is highly desirable for immersive Augmented and Virtual Reality (AR/VR) applications, but achieving instant (i.e., < 5 seconds)…
NASA: Neural Architecture Search and Acceleration for Hardware Inspired Hybrid Networks
Huihong Shi, Haoran You, Yang Zhao +2
Multiplication is arguably the most cost-dominant operation in modern deep neural networks (DNNs), limiting their achievable efficiency and thus more extensive deployment in resour…