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Publication

• Fast Adversarial Training with Dynamic Batch-level Attack Control
  • Jaewon Jung, Jaeyong Song, Hongsun Jang, Hyeyoon Lee, Kanghyun Choi, Noseong Park, and Jinho Lee
    DAC (Accepted), 2023


• Pipe-BD: Pipelined Parallel Blockwise Distillation
  • Hongsun Jang, Jaewon Jung, Jaeyong Song, Joonsang Yu, Youngsok Kim, Jinho Lee
    DATE (Accepted), 2023


• Optimus-CC: Efficient Large NLP Model Training with 3D Parallelism Aware Communication Compression
  • Jaeyong Song¹, Jinkyu Yim¹, Jaewon Jung, Hongsun Jang, Hyung-Jin Kim, Youngsok Kim, and Jinho Lee
    ASPLOS, 2023, Paper, GitHub
    


• SGCN: Exploiting Compressed-Sparse Features in Deep Graph Convolutional Network Accelerators
  • Mingi Yoo¹, Jaeyong Song¹, Jounghoo Lee, Namhyung Kim, Youngsok Kim, and Jinho Lee
    HPCA, 2023
    


• Slice-and-Forge: Making Better Use of Caches for Graph Convolutional Network Accelerators
  • Mingi Yoo¹, Jaeyong Song¹, Hyeyoon Lee, Jounghoo Lee, Namhyung Kim, Youngsok Kim, and Jinho Lee
    PACT (Best Paper Award), 2022, Paper
    


• Making a Better Use of Caches for GCN Accelerators with Feature Slicing and Automatic Tile Morphing
  • Mingi Yoo¹, Jaeyong Song¹, Jounghoo Lee, Namhyung Kim, Youngsok Kim, and Jinho Lee
    IEEE CAL, 2021, Paper
    

¹ indicates co-first authors