I’m currently a PhD student in the NCSU Systems Lab department of Computer Science at NC State University advised by Prof. Frank Mueller . Prior to that, I earned my Master degree at Wuhan National Laboratory for Optoelectronics (WNLO) at Huazhong University of Science and Technology (HUST) under the supervise of Prof. Ke Zhou . And I receive my Bacholar degree at Hainan University .

My Research interest mainly focused on the System Architecture, High Performance Computer and Storage techniques (e.g. Persistent Memory and CXL memory).

🌎 Motto

  • 读万卷书 行万里路
  • Gain wisdom through reading and broaden horizons through travel.

🔥 News

  • 2024.10:  🎉🎉 Excited to share that my poster has been accepted for SC 2024! Looking forward to attending the conference in Atlanta.
  • 2023.08:  🎉🎉 Began my PhD journey at NC State University!

📖 Educations

  • 08/2023 – Present, North Carolina State University, Raleigh, NC
    Ph.D. candidate in Computer Science (Advisor: Prof. Frank Mueller)

  • 09/2019 – 06/2023, Huazhong University of Science and Technology, Wuhan, China
    M.Sc. in Computer System Architecture
    • Thesis: Research on Performance Anomaly Detection and Root Cause Analysis for Storage Systems in Data Centers
    • Advisor: Prof. Ke Zhou
    • Focus: Data Center, Storage System, Anomaly Detection, Root Cause Analysis, Machine Learning
  • 09/2015 – 06/2019, Hainan University, Haikou, China
    B.Eng. in Computer Science and Technology

📝 Publications

Poster

  • Guangxing Hu, Awais Khan, Frank Mueller.
    “A Zero-Copy Storage with Metadata-Driven File Management Using Persistent Memory.”
    SC, 2024.

Publications

  1. Yu Liu, Yunchuan Guan, Tianming Jiang, Ke Zhou, Hua Wang, Guangxing Hu, Ji Zhang, Wei Fang, Zhuo Cheng, Ping Huang.
    “SPAE: Lifelong Disk Failure Prediction via End-to-End GAN-based Anomaly Detection with Ensemble Update.”
    Future Generation Computer Systems, 2023.

  2. Yanzhao Xie, Guangxing Hu, Yu Liu, Zhiqiu Lin, Ke Zhou, Yuhong Zhao.
    “How Visual Chirality Affects the Performance of Image Hashing.”
    Neural Computing and Applications, 2022.

  3. Yangtao Wang, Yanzhao Xie, Lisheng Fan, Guangxing Hu.
    “STMG: Swin transformer for multi-label image recognition with graph convolution network.”
    Neural Computing and Applications, 2021.

🎖 Honors and Awards

  • National Grand Prize of Massive Storage Algorithm Competition 2023
  • Academic Scholarship of Huazhong University of Science and Technology 2019–2022
  • Grand Prize, Group Programming Ladder Tournament, China Collegiate Computing Contest 2018
  • The Principal Scholarships of Hainan University (Top 2%) 2018
  • The Most Innovative and Outstanding Student Award of Hainan University 2018
  • The Second Scholarships of Hainan University 2016, 2017

💻 Internships

  • 2024.06 - 2024.08, Oak Ridge National Laboratory (ORNL), Oak Ridge, TN, USA. During my internship at ORNL, I focused on enhancing high-performance computing (HPC) capabilities for large-scale deep learning training. Specifically, I worked on extending the HVAC framework—a caching system originally designed to utilize node-local SSD storage for data-intensive workloads—by integrating Persistent Memory (PM) to reduce I/O overhead through zero-copy access. This involved:
    • Migrating and Debugging Code: I set up and debugged the HVAC runtime environment on both ORNL’s Frontier supercomputer and NC State University’s ARC cluster, resolving MPI dependencies and configuration issues to enable consistent, multi-site functionality.
    • Developing a PM-Backed Caching Layer: By leveraging the byte-addressability of PM, I introduced a new cache tier that further accelerates deep learning training while reducing unnecessary data transfers. A key aspect was using the Direct Access (DAX) mode on PM, which allows for faster read/write speeds compared to SSDs or file systems built on top of PM. The details of this work can be seen at my Github.
    • Preliminary Results and SC Poster: Preliminary benchmarks demonstrated significant improvements in I/O performance, and these findings were consolidated into a poster—A Zero-Copy Storage with Metadata-Driven File Management Using Persistent Memory—accepted at SC 2024.

🔖 Projects (TBA)