Daegun Yoon

According to our database, Daegun Yoon authored at least 13 papers between 2020 and 2024.

Collaborative distances:

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

2024

Preserving Near-Optimal Gradient Sparsification Cost for Scalable Distributed Deep Learning.

Daegun Yoon, Sangyoon Oh

CoRR, 2024

2023

SAGE: toward on-the-fly gradient compression ratio scaling.

Daegun Yoon, Minjoong Jeong, Sangyoon Oh

J. Supercomput., July, 2023

WAVE: designing a heuristics-based three-way breadth-first search on GPUs.

Daegun Yoon, Minjoong Jeong, Sangyoon Oh

J. Supercomput., April, 2023

Can hierarchical client clustering mitigate the data heterogeneity effect in federated learning?

Seungjun Lee, Miri Yu, Daegun Yoon, Sangyoon Oh

Proceedings of the IEEE International Parallel and Distributed Processing Symposium, 2023

DEFT: Exploiting Gradient Norm Difference between Model Layers for Scalable Gradient Sparsification.

Daegun Yoon, Sangyoon Oh

Proceedings of the 52nd International Conference on Parallel Processing, 2023

MiCRO: Near-Zero Cost Gradient Sparsification for Scaling and Accelerating Distributed DNN Training.

Daegun Yoon, Sangyoon Oh

Proceedings of the 30th IEEE International Conference on High Performance Computing, 2023

2022

SURF: Direction-Optimizing Breadth-First Search Using Workload State on GPUs.

Daegun Yoon, Sangyoon Oh

Sensors, 2022

AMBLE: Adjusting mini-batch and local epoch for federated learning with heterogeneous devices.

Juwon Park, Daegun Yoon, Sangho Yeo, Sangyoon Oh

J. Parallel Distributed Comput., 2022

Empirical Analysis on Top-k Gradient Sparsification for Distributed Deep Learning in a Supercomputing Environment.

Daegun Yoon, Sangyoon Oh

CoRR, 2022

2021

Balanced content space partitioning for pub/sub: a study on impact of varying partitioning granularity.

Daegun Yoon, Zhetao Li, Sangyoon Oh

J. Supercomput., 2021

Mitigating Cold Start Problem in Serverless Computing with Function Fusion.

Seungjun Lee, Daegun Yoon, Sangho Yeo, Sangyoon Oh

Sensors, 2021

Exploring a system architecture of content-based publish/subscribe system for efficient on-the-fly data dissemination.

Daegun Yoon, Gyudong Park, Sangyoon Oh

Concurr. Comput. Pract. Exp., 2021

2020

CPartition: a Correlation-Based Space Partitioning for Content-Based Publish/Subscribe Systems with Skewed Workload.

Daegun Yoon, Gyudong Park, Sangyoon Oh

Proceedings of the 2020 IEEE International Conference on Big Data and Smart Computing, 2020