Making a Better Use of Caches for GCN Accelerators with Feature Slicing and Automatic Tile Morphing. - Mingi Yoo; Jaeyong Song 002; Jounghoo Lee; Namhyung Kim; Youngsok Kim; Jinho Lee 001 (IEEE Comput. Archit. Lett., 2021)

Slice-and-Forge: Making Better Use of Caches for Graph Convolutional Network Accelerators. - Mingi Yoo; Jaeyong Song 002; Hyeyoon Lee; Jounghoo Lee; Namhyung Kim; Youngsok Kim; Jinho Lee 001 (PACT, 2022)

Optimus-CC: Efficient Large NLP Model Training with 3D Parallelism Aware Communication Compression. - Jaeyong Song 002; Jinkyu Yim; Jaewon Jung 001; Hongsun Jang; Hyung-Jin Kim; Youngsok Kim; Jinho Lee 001 (ASPLOS (2), 2023)

Fast Adversarial Training with Dynamic Batch-level Attack Control. - Jaewon Jung 001; Jaeyong Song 002; Hongsun Jang; Hyeyoon Lee; Kanghyun Choi; Noseong Park; Jinho Lee 001 (DAC, 2023)

Pipe-BD: Pipelined Parallel Blockwise Distillation. - Hongsun Jang; Jaewon Jung 001; Jaeyong Song 002; Joonsang Yu; Youngsok Kim; Jinho Lee 001 (DATE, 2023)

SGCN: Exploiting Compressed-Sparse Features in Deep Graph Convolutional Network Accelerators. - Mingi Yoo; Jaeyong Song 002; Jounghoo Lee; Namhyung Kim; Youngsok Kim; Jinho Lee 001 (HPCA, 2023)

GraNNDis: Efficient Unified Distributed Training Framework for Deep GNNs on Large Clusters. - Jaeyong Song 002; Hongsun Jang; Jaewon Jung 001; Youngsok Kim; Jinho Lee 001 (CoRR, 2023)

GraNNDis: Fast Distributed Graph Neural Network Training Framework for Multi-Server Clusters. - Jaeyong Song 002; Hongsun Jang; Hunseong Lim; Jaewon Jung 001; Youngsok Kim; Jinho Lee 001 (PACT, 2024)

PeerAiD: Improving Adversarial Distillation from a Specialized Peer Tutor. - Jaewon Jung 001; Hongsun Jang; Jaeyong Song 002; Jinho Lee 001 (CVPR, 2024)

Pipette: Automatic Fine-Grained Large Language Model Training Configurator for Real-World Clusters. - Jinkyu Yim; Jaeyong Song 002; Yerim Choi; Jaebeen Lee; Jaewon Jung 001; Hongsun Jang; Jinho Lee 001 (DATE, 2024)

Smart-Infinity: Fast Large Language Model Training using Near-Storage Processing on a Real System. - Hongsun Jang; Jaeyong Song 002; Jaewon Jung 001; Jaeyoung Park; Youngsok Kim; Jinho Lee 001 (HPCA, 2024)

AGAThA: Fast and Efficient GPU Acceleration of Guided Sequence Alignment for Long Read Mapping. - Seongyeon Park; Junguk Hong; Jaeyong Song 002; Hajin Kim; Youngsok Kim; Jinho Lee 001 (PPoPP, 2024)

A Case for In-Memory Random Scatter-Gather for Fast Graph Processing. - Changmin Shin 002; Taehee Kwon 002; Jaeyong Song 002; Jae Hyung Ju; Frank Liu 001; YeonKyu Choi; Jinho Lee 001 (IEEE Comput. Archit. Lett., 2024)

AIS-SNU/GraNNDis_Artifact: Artifact Evaluation Submission. - Jaeyong Song 002; Hongsun Jang; Hunseong Lim; Jaewon Jung 001; Youngsok Kim; Jinho Lee 001 (Zenodo, 2024)

Piccolo: Large-Scale Graph Processing with Fine-Grained in-Memory Scatter-Gather. - Changmin Shin 002; Jaeyong Song 002; Hongsun Jang; Dogeun Kim; Jun Sung; Taehee Kwon 002; Jae Hyung Ju; Frank Liu 001; YeonKyu Choi; Jinho Lee 001 (HPCA, 2025)

FALA: Locality-Aware PIM-Host Cooperation for Graph Processing with Fine-Grained Column Access. - Changmin Shin 002; Jaeyong Song 002; Seongmin Na; Jun Sung; Hongsun Jang; Jinho Lee 001 (MICRO, 2025)

INF2: High-Throughput Generative Inference of Large Language Models using Near-Storage Processing. - Hongsun Jang; Si Ung Noh; Changmin Shin 002; Jaewon Jung 001; Jaeyong Song 002; Jinho Lee 001 (CoRR, 2025)

A Cost-Effective Near-Storage Processing Solution for Offline Inference of Long-Context LLMs. - Hongsun Jang; Jaeyong Song 002; Changmin Shin 002; Si Ung Noh; Jaewon Jung 001; Jisung Park 001; Jinho Lee 001 (ASPLOS (2), 2026)

FlexiWalker: Extensible GPU Framework for Efficient Dynamic Random Walks with Runtime Adaptation. - Seongyeon Park; Jaeyong Song 002; Changmin Shin 002; Sukjin Kim; Junguk Hong; Jinho Lee 001 (EuroSys, 2026)

GriNNder: Breaking the Memory Capacity Wall in Full-Graph GNN Training with Storage Offloading. - Jaeyong Song 002; Seongyeon Park; Hongsun Jang; Jaewon Jung 001; Hunseong Lim; Junguk Hong; Jinho Lee 001 (CoRR, 2026)

NAVIS: Concurrent Search and Update with Low Position-Seeking Overhead in On-SSD Graph-Based Vector Search. - Jaeyong Song 002; Hongsun Jang; Changmin Shin 002; Seongyeon Park; Yong Jae Ryoo; Seo Jin Park; Jinho Lee 001 (CoRR, 2026)