12 citations · 17 across the 9 of their papers we have counts for
14 papers
A High-Throughput Hardware Accelerator for Lempel-Ziv 4 Compression Algorithm
Tao Chen, Suwen Song, Zhongfeng Wang
This paper delves into recent hardware implementations of the Lempel-Ziv 4 (LZ4) algorithm, highlighting two key factors that limit the throughput of single-kernel compressors. Fir…
NASH: Neural Architecture and Accelerator Search for Multiplication-Reduced Hybrid Models
Yang Xu, Huihong Shi, Zhongfeng Wang
The significant computational cost of multiplications hinders the deployment of deep neural networks (DNNs) on edge devices. While multiplication-free models offer enhanced hardwar…
Fast and Accurate FSA System Using ELBERT: An Efficient and Lightweight BERT
Siyuan Lu, Chenchen Zhou, Keli Xie +2
With the development of deep learning and Transformer-based pre-trained models like BERT, the accuracy of many NLP tasks has been dramatically improved. However, the large number o…
ViTALiTy: Unifying Low-rank and Sparse Approximation for Vision Transformer Acceleration with a Linear Taylor Attention
Jyotikrishna Dass, Shang Wu, Huihong Shi +4
Vision Transformer (ViT) has emerged as a competitive alternative to convolutional neural networks for various computer vision applications. Specifically, ViT multi-head attention…
An Efficient FPGA-based Accelerator for Deep Forest
Mingyu Zhu, Jiapeng Luo, Wendong Mao +1
Deep Forest is a prominent machine learning algorithm known for its high accuracy in forecasting. Compared with deep neural networks, Deep Forest has almost no multiplication opera…
Accelerate Three-Dimensional Generative Adversarial Networks Using Fast Algorithm
Ziqi Su, Wendong Mao, Zhongfeng Wang +3
Three-dimensional generative adversarial networks (3D-GAN) have attracted widespread attention in three-dimension (3D) visual tasks. 3D deconvolution (DeConv), as an important comp…