2 citations · 5 across the 4 of their papers we have counts for
4 papers
SysOM-AI: Continuous Cross-Layer Performance Diagnosis for Production AI Training
Yusheng Zheng, Wenan Mao, Shuyi Cheng +8
Performance diagnosis in production-scale AI training is challenging because subtle OS-level issues can trigger cascading GPU delays and network slowdowns, degrading training effic…
PDiT: Interleaving Perception and Decision-making Transformers for Deep Reinforcement Learning
Hangyu Mao, Rui Zhao, Ziyue Li +7
Designing better deep networks and better reinforcement learning (RL) algorithms are both important for deep RL. This work studies the former. Specifically, the Perception and Deci…
Comprehensive Deadlock Prevention for GPU Collective Communication
Lichen Pan, Juncheng Liu, Yongquan Fu +4
Distributed deep neural network training necessitates efficient GPU collective communications, which are inherently susceptible to deadlocks. GPU collective deadlocks arise easily…
Transformer in Transformer as Backbone for Deep Reinforcement Learning
Hangyu Mao, Rui Zhao, Hao Chen +5
Designing better deep networks and better reinforcement learning (RL) algorithms are both important for deep RL. This work focuses on the former. Previous methods build the network…