40 citations · 47 across the 6 of their papers we have counts for
Showing 2020Show all
3 papers · 1 filter
cs.NE2020★ 40 cited
Fusion-Catalyzed Pruning for Optimizing Deep Learning on Intelligent Edge Devices
Guangli Li, Xiu Ma, Xueying Wang +3
The increasing computational cost of deep neural network models limits the applicability of intelligent applications on resource-constrained edge devices. While a number of neural…
cs.DC2020
Accelerating Deep Learning Inference with Cross-Layer Data Reuse on GPUs
Xueying Wang, Guangli Li, Xiao Dong +3
Accelerating the deep learning inference is very important for real-time applications. In this paper, we propose a novel method to fuse the layers of convolutional neural networks…
cs.CV2020★ 1 cited
LANCE: Efficient Low-Precision Quantized Winograd Convolution for Neural Networks Based on Graphics Processing Units
Guangli Li, Lei Liu, Xueying Wang +2
Accelerating deep convolutional neural networks has become an active topic and sparked an interest in academia and industry. In this paper, we propose an efficient low-precision qu…