RLScheduler: Learn to Schedule HPC Batch Jobs Using Deep Reinforcement Learning. - Di Zhang 015; Dong Dai 001; Youbiao He; Forrest Sheng Bao (CoRR, 2019)

RLScheduler: an automated HPC batch job scheduler using reinforcement learning. - Di Zhang 015; Dong Dai 001; Youbiao He; Forrest Sheng Bao; Bing Xie (SC, 2020)

SentiLog: Anomaly Detecting on Parallel File Systems via Log-based Sentiment Analysis. - Di Zhang 015; Dong Dai 001; Runzhou Han; Mai Zheng (HotStorage, 2021)

ClusterLog: Clustering Logs for Effeftxsctive Log-based Anomaly Detection. - Chris Egersdoerfer; Di Zhang 015; Dong Dai 001 (FTXS@SC, 2022)

SchedInspector: A Batch Job Scheduling Inspector Using Reinforcement Learning. - Di Zhang 015; Dong Dai 001; Bing Xie (HPDC, 2022)

A Study of Failure Recovery and Logging of High-Performance Parallel File Systems. - Runzhou Han; Om Rameshwar Gatla; Mai Zheng; Jinrui Cao; Di Zhang 015; Dong Dai 001; Yong Chen 001; Jonathan E. Cook 001 (ACM Trans. Storage, 2022)

Early Exploration of Using ChatGPT for Log-based Anomaly Detection on Parallel File Systems Logs. - Chris Egersdoerfer; Di Zhang 015; Dong Dai 001 (HPDC, 2023)

Drill: Log-based Anomaly Detection for Large-scale Storage Systems Using Source Code Analysis. - Di Zhang 015; Chris Egersdoerfer; Tabassum Mahmud; Mai Zheng; Dong Dai 001 (IPDPS, 2023)

A Reinforcement Learning Based Backfilling Strategy for HPC Batch Jobs. - Elliot Kolker-Hicks; Di Zhang 015; Dong Dai 001 (SC Workshops, 2023)

ClusterLog: Clustering Logs for Effective Log-based Anomaly Detection. - Chris Egersdoerfer; Dong Dai 001; Di Zhang 015 (CoRR, 2023)

Cross-System Analysis of Job Characterization and Scheduling in Large-Scale Computing Clusters. - Di Zhang 015; Monish Soundar Raj; Bing Xie; Sheng Di; Dong Dai 001 (IPDPS, 2024)

An Empirical Study of Machine Learning-Based Synthetic Job Trace Generation Methods. - Monish Soundar Raj; Thomas MacDougall; Di Zhang 015; Dong Dai 001 (JSSPP, 2024)