Identifying Latent Reduced Models to Precondition Lossy Compression. - Huizhang Luo; Dan Huang 001; Qing Liu 002; Zhenbo Qiao; Hong Jiang 001; Jing Bi 001; Haitao Yuan 001; Mengchu Zhou; Jinzhen Wang; Zhenlu Qin (IPDPS, 2019)

A Comprehensive Study of In-Memory Computing on Large HPC Systems. - Dan Huang 001; Zhenlu Qin; Qing Liu 002; Norbert Podhorszki; Scott Klasky (ICDCS, 2020)

Identifying challenges and opportunities of in-memory computing on large HPC systems. - Dan Huang 001; Zhenlu Qin; Qing Liu 002; Norbert Podhorszki; Scott Klasky (J. Parallel Distributed Comput., 2022)

A Data-driven Approach to Harvesting Latent Reduced Models to Precondition Lossy Compression for Scientific Data. - Huizhang Luo; Junqi Wang 002; Zhenlu Qin; Dan Huang 001; Qing Liu 002; Mengchu Zhou; Hong Jiang 001 (IEEE Trans. Big Data, 2023)

A Generic Performance Metric for Scientific Data Compression. - Zhenlu Qin; Jessie Gu; Maggie Liu; Jinzhen Wang; Hongjian Zhu (e-Science, 2024)

Tango: A Cross-layer Approach to Managing I/O Interference over Local Ephemeral Storage. - Zhenbo Qiao; Qirui Tian; Zhenlu Qin; Jinzhen Wang; Qing Liu 002; Norbert Podhorszki; Scott Klasky; Hongjian Zhu (SC, 2024)