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ORCIDJaeyong Song 0002
Person information
- affiliation: Seoul National University, Seoul, Korea
Other persons with the same name
- Jaeyong Song — disambiguation page
- Jaeyong Song 0001
![[0000-0003-0712-2425]](https://dblp.org/img/orcid-mark.12x12.png "0000-0003-0712-2425")
— ETH Zurich, Zurich, Switzerland
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2020 – today
- 2026
[c13]Hongsun Jang, Jaeyong Song, Changmin Shin, Si Ung Noh, Jaewon Jung, Jisung Park, Jinho Lee:
A Cost-Effective Near-Storage Processing Solution for Offline Inference of Long-Context LLMs. ASPLOS (2) 2026: 5-24- 2025
- [c12]Changmin Shin, Jaeyong Song, Hongsun Jang, Dogeun Kim, Jun Sung, Taehee Kwon, Jae Hyung Ju, Frank Liu, YeonKyu Choi, Jinho Lee:
Piccolo: Large-Scale Graph Processing with Fine-Grained in-Memory Scatter-Gather. HPCA 2025: 641-656 - [c11]Changmin Shin, Jaeyong Song, Seongmin Na, Jun Sung, Hongsun Jang, Jinho Lee:
FALA: Locality-Aware PIM-Host Cooperation for Graph Processing with Fine-Grained Column Access. MICRO 2025: 1520-1534 - [i12]Hongsun Jang, Si Ung Noh, Changmin Shin, Jaewon Jung, Jaeyong Song, Jinho Lee:
INF2: High-Throughput Generative Inference of Large Language Models using Near-Storage Processing. CoRR abs/2502.09921 (2025) - [i11]Changmin Shin, Jaeyong Song, Hongsun Jang, Dogeun Kim, Jun Sung, Taehee Kwon, Jae Hyung Ju, Frank Liu, YeonKyu Choi, Jinho Lee:
Piccolo: Large-Scale Graph Processing with Fine-Grained In-Memory Scatter-Gather. CoRR abs/2503.05116 (2025) - [i10]Seongyeon Park, Jaeyong Song, Changmin Shin, Sukjin Kim, Junguk Hong, Jinho Lee:
FlexiWalker: Extensible GPU Framework for Efficient Dynamic Random Walks with Runtime Adaptation. CoRR abs/2512.00705 (2025) - 2024
- [j2]Changmin Shin, Taehee Kwon, Jaeyong Song, Jae Hyung Ju, Frank Liu, YeonKyu Choi, Jinho Lee:
A Case for In-Memory Random Scatter-Gather for Fast Graph Processing. IEEE Comput. Archit. Lett. 23(1): 73-77 (2024) - [c10]Jaeyong Song, Hongsun Jang, Hunseong Lim, Jaewon Jung, Youngsok Kim, Jinho Lee:
GraNNDis: Fast Distributed Graph Neural Network Training Framework for Multi-Server Clusters. PACT 2024: 91-107 - [c9]Jaewon Jung, Hongsun Jang, Jaeyong Song, Jinho Lee:
PeerAiD: Improving Adversarial Distillation from a Specialized Peer Tutor. CVPR 2024: 24482-24491 - [c8]Jinkyu Yim, Jaeyong Song, Yerim Choi, Jaebeen Lee, Jaewon Jung, Hongsun Jang, Jinho Lee:
Pipette: Automatic Fine-Grained Large Language Model Training Configurator for Real-World Clusters. DATE 2024: 1-6 - [c7]Hongsun Jang, Jaeyong Song, Jaewon Jung, Jaeyoung Park, Youngsok Kim, Jinho Lee:
Smart-Infinity: Fast Large Language Model Training using Near-Storage Processing on a Real System. HPCA 2024: 345-360 - [c6]Seongyeon Park, Junguk Hong, Jaeyong Song, Hajin Kim, Youngsok Kim, Jinho Lee:
AGAThA: Fast and Efficient GPU Acceleration of Guided Sequence Alignment for Long Read Mapping. PPoPP 2024: 431-444 - [d1]Jaeyong Song, Hongsun Jang, Hunseong Lim, Jaewon Jung, Youngsok Kim, Jinho Lee:
AIS-SNU/GraNNDis_Artifact: Artifact Evaluation Submission. Zenodo, 2024
- [i9]Seongyeon Park, Junguk Hong, Jaeyong Song, Hajin Kim, Youngsok Kim, Jinho Lee:
AGAThA: Fast and Efficient GPU Acceleration of Guided Sequence Alignment for Long Read Mapping. CoRR abs/2403.06478 (2024) - [i8]Hongsun Jang, Jaeyong Song, Jaewon Jung, Jaeyoung Park, Youngsok Kim, Jinho Lee:
Smart-Infinity: Fast Large Language Model Training using Near-Storage Processing on a Real System. CoRR abs/2403.06664 (2024) - [i7]Jaewon Jung, Hongsun Jang, Jaeyong Song, Jinho Lee:
PeerAiD: Improving Adversarial Distillation from a Specialized Peer Tutor. CoRR abs/2403.06668 (2024) - [i6]Jinkyu Yim, Jaeyong Song, Yerim Choi, Jaebeen Lee, Jaewon Jung, Hongsun Jang, Jinho Lee:
Pipette: Automatic Fine-grained Large Language Model Training Configurator for Real-World Clusters. CoRR abs/2405.18093 (2024) - 2023
- [c5]Jaeyong Song, Jinkyu Yim, Jaewon Jung, Hongsun Jang, Hyung-Jin Kim, Youngsok Kim, Jinho Lee:
Optimus-CC: Efficient Large NLP Model Training with 3D Parallelism Aware Communication Compression. ASPLOS (2) 2023: 560-573 - [c4]Jaewon Jung, Jaeyong Song, Hongsun Jang, Hyeyoon Lee, Kanghyun Choi, Noseong Park, Jinho Lee:
Fast Adversarial Training with Dynamic Batch-level Attack Control. DAC 2023: 1-6 - [c3]Hongsun Jang, Jaewon Jung, Jaeyong Song, Joonsang Yu, Youngsok Kim, Jinho Lee:
Pipe-BD: Pipelined Parallel Blockwise Distillation. DATE 2023: 1-6 - [c2]Mingi Yoo, Jaeyong Song, Jounghoo Lee, Namhyung Kim, Youngsok Kim, Jinho Lee:
SGCN: Exploiting Compressed-Sparse Features in Deep Graph Convolutional Network Accelerators. HPCA 2023: 1-14 - [i5]Mingi Yoo, Jaeyong Song, Hyeyoon Lee, Jounghoo Lee, Namhyung Kim, Youngsok Kim, Jinho Lee:
Slice-and-Forge: Making Better Use of Caches for Graph Convolutional Network Accelerators. CoRR abs/2301.09813 (2023) - [i4]Jaeyong Song, Jinkyu Yim, Jaewon Jung, Hongsun Jang, Hyung-Jin Kim, Youngsok Kim, Jinho Lee:
Optimus-CC: Efficient Large NLP Model Training with 3D Parallelism Aware Communication Compression. CoRR abs/2301.09830 (2023) - [i3]Mingi Yoo, Jaeyong Song, Jounghoo Lee, Namhyung Kim, Youngsok Kim, Jinho Lee:
SGCN: Exploiting Compressed-Sparse Features in Deep Graph Convolutional Network Accelerators. CoRR abs/2301.10388 (2023) - [i2]Hongsun Jang, Jaewon Jung, Jaeyong Song, Joonsang Yu, Youngsok Kim, Jinho Lee:
Pipe-BD: Pipelined Parallel Blockwise Distillation. CoRR abs/2301.12443 (2023) - [i1]Jaeyong Song, Hongsun Jang, Jaewon Jung, Youngsok Kim, Jinho Lee:
GraNNDis: Efficient Unified Distributed Training Framework for Deep GNNs on Large Clusters. CoRR abs/2311.06837 (2023) - 2022
- [c1]Mingi Yoo, Jaeyong Song, Hyeyoon Lee, Jounghoo Lee, Namhyung Kim, Youngsok Kim, Jinho Lee:
Slice-and-Forge: Making Better Use of Caches for Graph Convolutional Network Accelerators. PACT 2022: 40-53 - 2021
- [j1]Mingi Yoo, Jaeyong Song, Jounghoo Lee, Namhyung Kim, Youngsok Kim, Jinho Lee:
Making a Better Use of Caches for GCN Accelerators with Feature Slicing and Automatic Tile Morphing. IEEE Comput. Archit. Lett. 20(2): 102-105 (2021)
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