Jaeyong Song

28 papers A* 6A 3B 3Journal 14Unranked 2
YearRankTypeTitle / Venue / Authors
2026 — conf
A Cost-Effective Near-Storage Processing Solution for Offline Inference of Long-Context LLMs.
ASPLOS (2)
Hongsun Jang, Jaeyong Song, Changmin Shin, Si Ung Noh, Jaewon Jung, Jisung Park, Jinho Lee
2026 A conf
FlexiWalker: Extensible GPU Framework for Efficient Dynamic Random Walks with Runtime Adaptation.
EuroSys
Seongyeon Park, Jaeyong Song, Changmin Shin, Sukjin Kim, Junguk Hong, Jinho Lee
2025 A* conf
FALA: Locality-Aware PIM-Host Cooperation for Graph Processing with Fine-Grained Column Access.
MICRO
Changmin Shin, Jaeyong Song, Seongmin Na, Jun Sung, Hongsun Jang, Jinho Lee
2025 J jnl
FlexiWalker: Extensible GPU Framework for Efficient Dynamic Random Walks with Runtime Adaptation.
CoRR
Seongyeon Park, Jaeyong Song, Changmin Shin, Sukjin Kim, Junguk Hong, Jinho Lee
2025 J jnl
INF
CoRR
Hongsun Jang, Si Ung Noh, Changmin Shin, Jaewon Jung, Jaeyong Song, Jinho Lee
2025 J jnl
Piccolo: Large-Scale Graph Processing with Fine-Grained In-Memory Scatter-Gather.
CoRR
Changmin Shin, Jaeyong Song, Hongsun Jang, Dogeun Kim, Jun Sung, Taehee Kwon, Jae Hyung Ju, Frank Liu, YeonKyu Choi, Jinho Lee
2025 A* conf
Piccolo: Large-Scale Graph Processing with Fine-Grained in-Memory Scatter-Gather.
HPCA
Changmin Shin, Jaeyong Song, Hongsun Jang, Dogeun Kim, Jun Sung, Taehee Kwon, Jae Hyung Ju, Frank Liu, YeonKyu Choi, Jinho Lee
2024 J jnl
A Case for In-Memory Random Scatter-Gather for Fast Graph Processing.
IEEE Comput. Archit. Lett.
Changmin Shin, Taehee Kwon, Jaeyong Song, Jae Hyung Ju, Frank Liu, YeonKyu Choi, Jinho Lee
2024 B conf
AGAThA: Fast and Efficient GPU Acceleration of Guided Sequence Alignment for Long Read Mapping.
PPoPP
Seongyeon Park, Junguk Hong, Jaeyong Song, Hajin Kim, Youngsok Kim, Jinho Lee
2024 J jnl
AGAThA: Fast and Efficient GPU Acceleration of Guided Sequence Alignment for Long Read Mapping.
CoRR
Seongyeon Park, Junguk Hong, Jaeyong Song, Hajin Kim, Youngsok Kim, Jinho Lee
2024 B conf
GraNNDis: Fast Distributed Graph Neural Network Training Framework for Multi-Server Clusters.
PACT
Jaeyong Song, Hongsun Jang, Hunseong Lim, Jaewon Jung, Youngsok Kim, Jinho Lee
2024 A* conf
PeerAiD: Improving Adversarial Distillation from a Specialized Peer Tutor.
CVPR
Jaewon Jung, Hongsun Jang, Jaeyong Song, Jinho Lee
2024 J jnl
PeerAiD: Improving Adversarial Distillation from a Specialized Peer Tutor.
CoRR
Jaewon Jung, Hongsun Jang, Jaeyong Song, Jinho Lee
2024 A conf
Pipette: Automatic Fine-Grained Large Language Model Training Configurator for Real-World Clusters.
DATE
Jinkyu Yim, Jaeyong Song, Yerim Choi, Jaebeen Lee, Jaewon Jung, Hongsun Jang, Jinho Lee
2024 J jnl
Pipette: Automatic Fine-grained Large Language Model Training Configurator for Real-World Clusters.
CoRR
Jinkyu Yim, Jaeyong Song, Yerim Choi, Jaebeen Lee, Jaewon Jung, Hongsun Jang, Jinho Lee
2024 A* conf
Smart-Infinity: Fast Large Language Model Training using Near-Storage Processing on a Real System.
HPCA
Hongsun Jang, Jaeyong Song, Jaewon Jung, Jaeyoung Park, Youngsok Kim, Jinho Lee
2024 J jnl
Smart-Infinity: Fast Large Language Model Training using Near-Storage Processing on a Real System.
CoRR
Hongsun Jang, Jaeyong Song, Jaewon Jung, Jaeyoung Park, Youngsok Kim, Jinho Lee
2023 A* conf
Fast Adversarial Training with Dynamic Batch-level Attack Control.
DAC
Jaewon Jung, Jaeyong Song, Hongsun Jang, Hyeyoon Lee, Kanghyun Choi, Noseong Park, Jinho Lee
2023 J jnl
GraNNDis: Efficient Unified Distributed Training Framework for Deep GNNs on Large Clusters.
CoRR
Jaeyong Song, Hongsun Jang, Jaewon Jung, Youngsok Kim, Jinho Lee
2023 — conf
Optimus-CC: Efficient Large NLP Model Training with 3D Parallelism Aware Communication Compression.
ASPLOS (2)
Jaeyong Song, Jinkyu Yim, Jaewon Jung, Hongsun Jang, Hyung-Jin Kim, Youngsok Kim, Jinho Lee
2023 J jnl
Optimus-CC: Efficient Large NLP Model Training with 3D Parallelism Aware Communication Compression.
CoRR
Jaeyong Song, Jinkyu Yim, Jaewon Jung, Hongsun Jang, Hyung-Jin Kim, Youngsok Kim, Jinho Lee
2023 A conf
Pipe-BD: Pipelined Parallel Blockwise Distillation.
DATE
Hongsun Jang, Jaewon Jung, Jaeyong Song, Joonsang Yu, Youngsok Kim, Jinho Lee
2023 J jnl
Pipe-BD: Pipelined Parallel Blockwise Distillation.
CoRR
Hongsun Jang, Jaewon Jung, Jaeyong Song, Joonsang Yu, Youngsok Kim, Jinho Lee
2023 A* conf
SGCN: Exploiting Compressed-Sparse Features in Deep Graph Convolutional Network Accelerators.
HPCA
Mingi Yoo, Jaeyong Song, Jounghoo Lee, Namhyung Kim, Youngsok Kim, Jinho Lee
2023 J jnl
SGCN: Exploiting Compressed-Sparse Features in Deep Graph Convolutional Network Accelerators.
CoRR
Mingi Yoo, Jaeyong Song, Jounghoo Lee, Namhyung Kim, Youngsok Kim, Jinho Lee
2023 J jnl
Slice-and-Forge: Making Better Use of Caches for Graph Convolutional Network Accelerators.
CoRR
Mingi Yoo, Jaeyong Song, Hyeyoon Lee, Jounghoo Lee, Namhyung Kim, Youngsok Kim, Jinho Lee
2022 B conf
Slice-and-Forge: Making Better Use of Caches for Graph Convolutional Network Accelerators.
PACT
Mingi Yoo, Jaeyong Song, Hyeyoon Lee, Jounghoo Lee, Namhyung Kim, Youngsok Kim, Jinho Lee
2021 J jnl
Making a Better Use of Caches for GCN Accelerators with Feature Slicing and Automatic Tile Morphing.
IEEE Comput. Archit. Lett.
Mingi Yoo, Jaeyong Song, Jounghoo Lee, Namhyung Kim, Youngsok Kim, Jinho Lee