4 citations · 5 across the 3 of their papers we have counts for
3 papers
cs.DC2023
Mirage: Towards Low-interruption Services on Batch GPU Clusters with Reinforcement Learning
Qiyang Ding, Pengfei Zheng, Shreyas Kudari +2
Accommodating long-running deep learning (DL) training and inference jobs is challenging on GPU clusters that use traditional batch schedulers, such as Slurm. Given fixed wall cloc…
cs.DC2022★ 4 cited
Shockwave: Fair and Efficient Cluster Scheduling for Dynamic Adaptation in Machine Learning
Pengfei Zheng, Rui Pan, Tarannum Khan +2
Dynamic adaptation has become an essential technique in accelerating distributed machine learning (ML) training. Recent studies have shown that dynamically adjusting model structur…
cs.LG2022★ 1 cited
Finding Dynamics Preserving Adversarial Winning Tickets
Xupeng Shi, Pengfei Zheng, A. Adam Ding +2
Modern deep neural networks (DNNs) are vulnerable to adversarial attacks and adversarial training has been shown to be a promising method for improving the adversarial robustness o…