Optimus-CC: Efficient Large NLP Model Training with 3D Parallelism Aware Communication Compression. - Jaeyong Song; Jinkyu Yim; Jaewon Jung 001; Hongsun Jang; Hyung-Jin Kim; Youngsok Kim; Jinho Lee (ASPLOS (2), 2023)

Fast Adversarial Training with Dynamic Batch-level Attack Control. - Jaewon Jung 001; Jaeyong Song; Hongsun Jang; Hyeyoon Lee; Kanghyun Choi; Noseong Park; Jinho Lee (DAC, 2023)

Pipe-BD: Pipelined Parallel Blockwise Distillation. - Hongsun Jang; Jaewon Jung 001; Jaeyong Song; Joonsang Yu; Youngsok Kim; Jinho Lee (DATE, 2023)

GraNNDis: Efficient Unified Distributed Training Framework for Deep GNNs on Large Clusters. - Jaeyong Song; Hongsun Jang; Jaewon Jung 001; Youngsok Kim; Jinho Lee (CoRR, 2023)

GraNNDis: Fast Distributed Graph Neural Network Training Framework for Multi-Server Clusters. - Jaeyong Song; Hongsun Jang; Hunseong Lim; Jaewon Jung 001; Youngsok Kim; Jinho Lee (PACT, 2024)

PeerAiD: Improving Adversarial Distillation from a Specialized Peer Tutor. - Jaewon Jung 001; Hongsun Jang; Jaeyong Song; Jinho Lee (CVPR, 2024)

Pipette: Automatic Fine-Grained Large Language Model Training Configurator for Real-World Clusters. - Jinkyu Yim; Jaeyong Song; Yerim Choi; Jaebeen Lee; Jaewon Jung 001; Hongsun Jang; Jinho Lee (DATE, 2024)

Smart-Infinity: Fast Large Language Model Training using Near-Storage Processing on a Real System. - Hongsun Jang; Jaeyong Song; Jaewon Jung 001; Jaeyoung Park; Youngsok Kim; Jinho Lee (HPCA, 2024)

AIS-SNU/GraNNDis_Artifact: Artifact Evaluation Submission. - Jaeyong Song; Hongsun Jang; Hunseong Lim; Jaewon Jung 001; Youngsok Kim; Jinho Lee (Zenodo, 2024)

INF2: High-Throughput Generative Inference of Large Language Models using Near-Storage Processing. - Hongsun Jang; Si Ung Noh; Changmin Shin; Jaewon Jung 001; Jaeyong Song; Jinho Lee (CoRR, 2025)