Gyeongseo Park

Research Interests

  • Energy-Efficient Computing
  • Systems for Network
  • Virtualization
  • Systems for Machine Learning

Education

  • Ph.D. in Electrical Engineering and Computer Science, DGIST, Daegu, Mar, 2017 – 2024
  • B.S. in Electrical and Computer Engineering (Magna Cum Laude), Ajou University, Suwon, Feb, 2016

Experience

Research Assistant, March 2017 to August 2024

  • ML for Systems & Systems for ML
    • Participating in industry-university cooperation to develop PIM (Processing In Memory) for distributed computing (e.g., Spark, Hadoop) [2019 – 2020]
    • Participating in industry-university cooperation to develop PIM for DLRM (Deep Learning Recommendation Model) [2020 – 2021]
    • Participating in industry-university cooperation to develop distributed computing framework providing tiered-memory management (e.g., CXL Memory, Persistent Memory, etc.) [2022 – 2024]
    • Developing reinforcement learning-based dynamic core allocation for latency-critical services [Work in Progress]
  • Energy-Efficient Systems for Latency-Critical Services
    • Developing network load-aware power management for latency-critical services (CAL ’20, MICRO ’21)
    • Developing network interrupt rate management for improving the energy efficiency of latency-critical services (ICCD ’20, IEEE Access ‘20)
    • Developing latency-critical container-aware power management (ISET ’18)
    • Developing dynamic core allocation in virtualization (i.e., KVM) for improving the performance and energy efficiency of latency-critical services [Work in Progress]

Skiils and Techniques

  • Machine Learning Algorithms: DLRM, DQN, PPO, etc.
  • Programing Language: C, Python, C++
  • Frameworks/Packages: Pytorch, Pandas, eBPF