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Changho Hwang
Changho Hwang
Microsoft Research
Verified email at microsoft.com - Homepage
Title
Cited by
Cited by
Year
APUNet: Revitalizing GPU as Packet Processing Accelerator
Y Go, MA Jamshed, YG Moon, C Hwang, KS Park
The 14th USENIX Symposium on Networked Systems Design and Implementation, 83-96, 2017
1192017
Elastic Resource Sharing for Distributed Deep Learning
C Hwang, T Kim, S Kim, J Shin, KS Park
The 18th USENIX Symposium on Networked Systems Design and Implementation …, 2021
542021
Confident Multiple Choice Learning
K Lee, C Hwang, KS Park, J Shin
The 34th International Conference on Machine Learning, 2014-2023, 2017
532017
Tutel: Adaptive mixture-of-experts at scale
C Hwang, W Cui, Y Xiong, Z Yang, Z Liu, H Hu, Z Wang, R Salas, J Jose, ...
Proceedings of Machine Learning and Systems 5, 2023
35*2023
Accelerating GNN training with locality-aware partial execution
T Kim, C Hwang, KS Park, Z Lin, P Cheng, Y Miao, L Ma, Y Xiong
The 12th ACM SIGOPS Asia-Pacific Workshop on Systems, 2021
82021
Pre-gated MoE: An Algorithm-System Co-Design for Fast and Scalable Mixture-of-Expert Inference
R Hwang, J Wei, S Cao, C Hwang, X Tang, T Cao, M Yang, M Rhu
arXiv preprint arXiv:2308.12066, 2023
22023
A case for two-stage inference with knowledge caching
G Park, C Hwang, KS Park
The 3rd International Workshop on Deep Learning for Mobile Systems and …, 2019
22019
ARK: GPU-driven Code Execution for Distributed Deep Learning
C Hwang, KS Park, R Shu, X Qu, P Cheng, Y Xiong
The 20th USENIX Symposium on Networked Systems Design and Implementation, 0
1*
ForestColl: Efficient Collective Communications on Heterogeneous Network Fabrics
L Zhao, S Maleki, Z Yang, H Pourreza, A Shah, C Hwang, ...
arXiv preprint arXiv:2402.06787, 2024
2024
Towards GPU-driven Code Execution for Distributed Deep Learning
C Hwang, KS Park, R Shu, X Qu, P Cheng, Y Xiong
The 3rd Machine Learning for Computer Architecture and Systems, 2022
2022
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Articles 1–10