Hongsun Jang

According to our database, Hongsun Jang authored at least 15 papers between 2023 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

NAVIS: Concurrent Search and Update with Low Position-Seeking Overhead in On-SSD Graph-Based Vector Search.

Jaeyong Song, Hongsun Jang, Changmin Shin, Seongyeon Park, Yong Jae Ryoo, Seo Jin Park, Jinho Lee

CoRR, May, 2026

GriNNder: Breaking the Memory Capacity Wall in Full-Graph GNN Training with Storage Offloading.

Jaeyong Song, Seongyeon Park, Hongsun Jang, Jaewon Jung, Hunseong Lim, Junguk Hong, Jinho Lee

CoRR, May, 2026

A Cost-Effective Near-Storage Processing Solution for Offline Inference of Long-Context LLMs.

Hongsun Jang, Jaeyong Song, Changmin Shin, Si Ung Noh, Jaewon Jung, Jisung Park, Jinho Lee

Proceedings of the 31st ACM International Conference on Architectural Support for Programming Languages and Operating Systems, 2026

2025

INF²: High-Throughput Generative Inference of Large Language Models using Near-Storage Processing.

Hongsun Jang, Si Ung Noh, Changmin Shin, Jaewon Jung, Jaeyong Song, Jinho Lee

CoRR, February, 2025

FALA: Locality-Aware PIM-Host Cooperation for Graph Processing with Fine-Grained Column Access.

Changmin Shin, Jaeyong Song, Seongmin Na, Jun Sung, Hongsun Jang, Jinho Lee

Proceedings of the 58th IEEE/ACM International Symposium on Microarchitecture, 2025

Piccolo: Large-Scale Graph Processing with Fine-Grained in-Memory Scatter-Gather.

Changmin Shin, Jaeyong Song, Hongsun Jang, Dogeun Kim, Jun Sung, Taehee Kwon, Jae Hyung Ju, Frank Liu, YeonKyu Choi, Jinho Lee

Proceedings of the IEEE International Symposium on High Performance Computer Architecture, 2025

2024

AIS-SNU/GraNNDis_Artifact: Artifact Evaluation Submission.

Jaeyong Song, Hongsun Jang, Hunseong Lim, Jaewon Jung, Youngsok Kim, Jinho Lee

Dataset, July, 2024

Smart-Infinity: Fast Large Language Model Training using Near-Storage Processing on a Real System.

Hongsun Jang, Jaeyong Song, Jaewon Jung, Jaeyoung Park, Youngsok Kim, Jinho Lee

Proceedings of the IEEE International Symposium on High-Performance Computer Architecture, 2024

Pipette: Automatic Fine-Grained Large Language Model Training Configurator for Real-World Clusters.

Jinkyu Yim, Jaeyong Song, Yerim Choi, Jaebeen Lee, Jaewon Jung, Hongsun Jang, Jinho Lee

Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2024

PeerAiD: Improving Adversarial Distillation from a Specialized Peer Tutor.

Jaewon Jung, Hongsun Jang, Jaeyong Song, Jinho Lee

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

GraNNDis: Fast Distributed Graph Neural Network Training Framework for Multi-Server Clusters.

Jaeyong Song, Hongsun Jang, Hunseong Lim, Jaewon Jung, Youngsok Kim, Jinho Lee

Proceedings of the 2024 International Conference on Parallel Architectures and Compilation Techniques, 2024

2023

GraNNDis: Efficient Unified Distributed Training Framework for Deep GNNs on Large Clusters.

Jaeyong Song, Hongsun Jang, Jaewon Jung, Youngsok Kim, Jinho Lee

CoRR, 2023

Pipe-BD: Pipelined Parallel Blockwise Distillation.

Hongsun Jang, Jaewon Jung, Jaeyong Song, Joonsang Yu, Youngsok Kim, Jinho Lee

Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2023

Fast Adversarial Training with Dynamic Batch-level Attack Control.

Jaewon Jung, Jaeyong Song, Hongsun Jang, Hyeyoon Lee, Kanghyun Choi, Noseong Park, Jinho Lee

Proceedings of the 60th ACM/IEEE Design Automation Conference, 2023

Optimus-CC: Efficient Large NLP Model Training with 3D Parallelism Aware Communication Compression.

Jaeyong Song, Jinkyu Yim, Jaewon Jung, Hongsun Jang, Hyung-Jin Kim, Youngsok Kim, Jinho Lee

Proceedings of the 28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, 2023