Jaeyong Song
Orcid: 0000-0001-9976-7487Affiliations:
- Seoul National University, Seoul, Korea
According to our database1,
Jaeyong Song authored at least 21 papers
between 2021 and 2026.
Collaborative distances:
Collaborative distances:
Timeline
Legend:
Book In proceedings Article PhD thesis Dataset OtherLinks
Online presence:
-
on orcid.org
On csauthors.net:
Bibliography
2026
NAVIS: Concurrent Search and Update with Low Position-Seeking Overhead in On-SSD Graph-Based Vector Search.
CoRR, May, 2026
GriNNder: Breaking the Memory Capacity Wall in Full-Graph GNN Training with Storage Offloading.
CoRR, May, 2026
FlexiWalker: Extensible GPU Framework for Efficient Dynamic Random Walks with Runtime Adaptation.
Proceedings of the 21st European Conference on Computer Systems, 2026
A Cost-Effective Near-Storage Processing Solution for Offline Inference of Long-Context LLMs.
Proceedings of the 31st ACM International Conference on Architectural Support for Programming Languages and Operating Systems, 2026
2025
INF<sup>2</sup>: High-Throughput Generative Inference of Large Language Models using Near-Storage Processing.
CoRR, February, 2025
FALA: Locality-Aware PIM-Host Cooperation for Graph Processing with Fine-Grained Column Access.
Proceedings of the 58th IEEE/ACM International Symposium on Microarchitecture, 2025
Proceedings of the IEEE International Symposium on High Performance Computer Architecture, 2025
2024
IEEE Comput. Archit. Lett., 2024
AGAThA: Fast and Efficient GPU Acceleration of Guided Sequence Alignment for Long Read Mapping.
Proceedings of the 29th ACM SIGPLAN Annual Symposium on Principles and Practice of Parallel Programming, 2024
Smart-Infinity: Fast Large Language Model Training using Near-Storage Processing on a Real System.
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.
Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2024
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.
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.
CoRR, 2023
SGCN: Exploiting Compressed-Sparse Features in Deep Graph Convolutional Network Accelerators.
Proceedings of the IEEE International Symposium on High-Performance Computer Architecture, 2023
Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2023
Proceedings of the 60th ACM/IEEE Design Automation Conference, 2023
Optimus-CC: Efficient Large NLP Model Training with 3D Parallelism Aware Communication Compression.
Proceedings of the 28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, 2023
2022
Slice-and-Forge: Making Better Use of Caches for Graph Convolutional Network Accelerators.
Proceedings of the International Conference on Parallel Architectures and Compilation Techniques, 2022
2021
Making a Better Use of Caches for GCN Accelerators with Feature Slicing and Automatic Tile Morphing.
IEEE Comput. Archit. Lett., 2021