[6] FAST 2023: "SHADE: Enable Fundamental Cacheability for Distributed Deep Learning Training" Redwan Ibne Seraj Khan (VT), Ahmad Hossein Yazdani (VT), Yuqi Fu (UVA), Arnab K. Paul (BITS Pilani), Bo Ji (VT), Xun Jian
, Yue Cheng (UVA), and Ali R. Butt (VT) (Acceptance rate: 28/123=23%)
[5] ISCA 2021: "Quantifying Server Memory Frequency Margin and Using it to Improve Performance in HPC Systems" Da Zhang, Gagandeep Panwar, Jagadish Kotra (AMD), Nathan DeBardeleben (LANL), Sean Blanchard (LANL), Xun Jian (Acceptance rate: 76/406=19%)
[4] ASPLOS 2020: "Forget Failure: Exploiting SRAM Data Remanence for Low-overhead Intermittent Computation" Harrison Williams (VT), Xun Jian, Matthew Hicks (VT) (Acceptance rate: 86/479=18%)
[3] MICRO 2019: "Quantifying Memory Underutilization in HPC Systems and Using it to Improve Performance via Architecture Support" Gagandeep Panwar, Da Zhang, Yihan Pang (VT), Mai Dahshan (VT), Nathan Debardeleben (LANL), Binoy Ravindran (VT), Xun Jian (Acceptance rate: 79/344=22.9%)
[9] MICRO 2018: "Exploring and Optimizing Chipkill-correct for Persistent Memory Based on High-density NVRAMs" Da Zhang, Vilas Sridharan (AMD), and Xun Jian. (Acceptance rate: 74/351=21.1%)
[1] CAL (Best of the Year) 2012: "High Performance, Energy Efficient Chipkill Correct Memory with Multidimensional Parity" Xun Jian, Henry Duwe (UIUC), John Sartori (UIUC), Rakesh Kumar.