Serving DNN Models with Multi-Instance GPUs: A Case of the Reconfigurable Machine Scheduling Problem. - Cheng Tan 005; Zhichao Li; Jian Zhang; Yu Cao; Sikai Qi; Zherui Liu; Yibo Zhu; Chuanxiong Guo (CoRR, 2021)

Prediction of GPU Failures Under Deep Learning Workloads. - Heting Liu; Zhichao Li; Cheng Tan 005; Rongqiu Yang; Guohong Cao; Zherui Liu; Chuanxiong Guo (CoRR, 2022)

Aryl: An Elastic Cluster Scheduler for Deep Learning. - Jiamin Li 002; Hong Xu 001; Yibo Zhu; Zherui Liu; Chuanxiong Guo; Cong Wang 001 (CoRR, 2022)

Lyra: Elastic Scheduling for Deep Learning Clusters. - Jiamin Li 002; Hong Xu 001; Yibo Zhu; Zherui Liu; Chuanxiong Guo; Cong Wang 001 (EuroSys, 2023)

Predicting GPU Failures With High Precision Under Deep Learning Workloads. - Heting Liu; Zhichao Li; Cheng Tan 005; Rongqiu Yang; Guohong Cao; Zherui Liu; Chuanxiong Guo (SYSTOR, 2023)

MegaScale: Scaling Large Language Model Training to More Than 10, 000 GPUs. - Ziheng Jiang; Haibin Lin; Yinmin Zhong; Qi Huang; Yangrui Chen; Zhi Zhang; Yanghua Peng; Xiang Li 067; Cong Xie; Shibiao Nong; Yulu Jia; Sun He; et al. (NSDI, 2024)

Understanding Stragglers in Large Model Training Using What-if Analysis. - Jinkun Lin; Ziheng Jiang; Zuquan Song; Sida Zhao; Menghan Yu; Zhanghan Wang; Chenyuan Wang; Zuocheng Shi; Xiang Shi; Wei Jia; Zherui Liu; Shuguang Wang; et al. (OSDI, 2025)