7 citations · 23 across the 9 of their papers we have counts for
Showing cs.ARShow all
3 papers · 1 filter
cs.AR2023
MEGA: A Memory-Efficient GNN Accelerator Exploiting Degree-Aware Mixed-Precision Quantization
Zeyu Zhu, Fanrong Li, Gang Li +5
Graph Neural Networks (GNNs) are becoming a promising technique in various domains due to their excellent capabilities in modeling non-Euclidean data. Although a spectrum of accele…
cs.AR2021★ 4 cited
Block Convolution: Towards Memory-Efficient Inference of Large-Scale CNNs on FPGA
Gang Li, Zejian Liu, Fanrong Li +1
Deep convolutional neural networks have achieved remarkable progress in recent years. However, the large volume of intermediate results generated during inference poses a significa…
cs.AR2021★ 5 cited
Hardware Acceleration of Fully Quantized BERT for Efficient Natural Language Processing
Zejian Liu, Gang Li, Jian Cheng
BERT is the most recent Transformer-based model that achieves state-of-the-art performance in various NLP tasks. In this paper, we investigate the hardware acceleration of BERT on…