Dec 05, 2023




Our research has focused on system optimizations for interesting applications in modern eras, which include deep learning frameworks and big data analysis platforms. Our current interests include:

  • Compiler Optimization for GPU/FPGA Computing
  • Platform Optimization for Big Data/Machine Learning Frameworks
  • System Software Design for Non-Volatile Memories
  • Static/Dynamic Program Analysis for Performance and Security

Current Grants

  • Loop analysis based optimizations for deep learning compilers, Samsung Advanced Institute of Technology (SAIT), 2023.03-2024.02
    • Investigate loop analysis for general fusion/fission methods integrated with schedulers for multiple devices.
  • Analysis of applications for zns-ssd storage systems and application, Samsung Electronics, 2022.06-2024.05
    • Investigate application characteristics for specialized-SDDs and explore design space.
  • Improving FPGA Programmability for Big Data Analytics, National Research Foundation (NRF), 2021.03-2025.02
    • Investigate techniques for accelerator programmability on big data analytics frameworks.
  • Research on Edge-Native Operating Systems for Edge Micro-Data-Centers, Institute of Information & Communications Technology Planning & Evaluation (IITP), 2021.04-2024.12
    • Develop abstraction techniques in compilers for HW-accelerators in EMDC operating systems.

[ Past Grants ]



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