2 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.PF2021
Pinpointing the Memory Behaviors of DNN Training
Jiansong Li, Xiao Dong, Guangli Li +9
The training of deep neural networks (DNNs) is usually memory-hungry due to the limited device memory capacity of DNN accelerators. Characterizing the memory behaviors of DNN train…
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.PF2019★ 2 cited
The Pitfall of Evaluating Performance on Emerging AI Accelerators
Zihan Jiang, Jiansong Li, Jiangfeng Zhan
In recent years, domain-specific hardware has brought significant performance improvements in deep learning (DL). Both industry and academia only focus on throughput when evaluatin…