Changho Hwang

Senior Researcher

출판물

자료 보기:

- Learning to Generate Unit Test via Adversarial Reinforcement Learning
  
  Dongjun Lee, Changho Hwang, Kimin Lee
  
  ICLR 2026 | April 2026
  
  Preprint
- MSCCL++: Rethinking GPU Communication Abstractions for AI Inference
  
  Changho Hwang, Peng Cheng, Roshan Dathathri, Abhinav Jangda, Saeed Maleki, Madan Musuvathi, Olli Saarikivi, Aashaka Shah, Ziyue Yang, Binyang Li, Caio Rocha, Qinghua Zhou, Mahdieh Ghazimirsaeed, Sreevatsa Anantharamu, Jithin Jose
  
  ACM International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS) | March 2026
  
  Preprint
- Pre-gated MoE: An Algorithm-System Co-Design for Fast and Scalable Mixture-of-Expert Inference
  
  Ranggi Hwang, Jianyu Wei, Shijie Cao, Changho Hwang, Xiaohu Tang, Ting Cao, Mao Yang
  
  ISCA 2024 | July 2024
  
  Microsoft Research Focus https://www.microsoft.com/en-us/research/blog/research-focus-week-of-july-15-2024/
  
  Publication
- ARK: GPU-driven Code Execution for Distributed Deep Learning
  
  Changho Hwang, Ran Shu, Peng Cheng, Yongqiang Xiong, KyoungSoo Park
  
  NSDI | April 2023
  
  Publication
- Tutel: Adaptive Mixture-of-Experts at Scale
  
  Changho Hwang, Wei Cui, Yifan Xiong, Ziyue Yang, Ze Liu, Han Hu, Zilong Wang, Rafael Salas, Jithin Jose, Prabhat Ram, Joe Chau, Peng Cheng, Fan Yang, Mao Yang, Yongqiang Xiong
  
  July 2022
  
  Publication
- Accelerating GNN training with locality-aware partial execution
  
  Taehyun Kim, Changho Hwang, KyoungSoo Park, Zhiqi Lin, Peng Cheng, Youshan Miao, Lingxiao Ma, Yongqiang Xiong
  
  August 2021
  
  Publication

- Learning to Generate Unit Test via Adversarial Reinforcement Learning
  
  Dongjun Lee, Changho Hwang, Kimin Lee
  
  ICLR 2026 | April 2026
  
  Preprint
- MSCCL++: Rethinking GPU Communication Abstractions for AI Inference
  
  Changho Hwang, Peng Cheng, Roshan Dathathri, Abhinav Jangda, Saeed Maleki, Madan Musuvathi, Olli Saarikivi, Aashaka Shah, Ziyue Yang, Binyang Li, Caio Rocha, Qinghua Zhou, Mahdieh Ghazimirsaeed, Sreevatsa Anantharamu, Jithin Jose
  
  ACM International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS) | March 2026
  
  Preprint
- MSCCL++: Rethinking GPU Communication Abstractions for AI Inference
  
  Changho Hwang, Peng Cheng, Roshan Dathathri, Abhinav Jangda, Saeed Maleki, Madan Musuvathi, Olli Saarikivi, Aashaka Shah, Ziyue Yang, Binyang Li, Caio Rocha, Qinghua Zhou, Mahdieh Ghazimirsaeed, Sreevatsa Anantharamu, Jithin Jose
  
  ACM International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS) | March 2026
  
  Preprint
- Pre-gated MoE: An Algorithm-System Co-Design for Fast and Scalable Mixture-of-Expert Inference
  
  Ranggi Hwang, Jianyu Wei, Shijie Cao, Changho Hwang, Xiaohu Tang, Ting Cao, Mao Yang
  
  ISCA 2024 | July 2024
  
  Microsoft Research Focus https://www.microsoft.com/en-us/research/blog/research-focus-week-of-july-15-2024/
  
  Publication
- ARK: GPU-driven Code Execution for Distributed Deep Learning
  
  Changho Hwang, Ran Shu, Peng Cheng, Yongqiang Xiong, KyoungSoo Park
  
  NSDI | April 2023
  
  Publication
- Tutel: Adaptive Mixture-of-Experts at Scale
  
  Changho Hwang, Wei Cui, Yifan Xiong, Ziyue Yang, Ze Liu, Han Hu, Zilong Wang, Rafael Salas, Jithin Jose, Prabhat Ram, Joe Chau, Peng Cheng, Fan Yang, Mao Yang, Yongqiang Xiong
  
  July 2022
  
  Publication
- Accelerating GNN training with locality-aware partial execution
  
  Taehyun Kim, Changho Hwang, KyoungSoo Park, Zhiqi Lin, Peng Cheng, Youshan Miao, Lingxiao Ma, Yongqiang Xiong
  
  August 2021
  
  Publication
- Learning to Generate Unit Test via Adversarial Reinforcement Learning
  
  Dongjun Lee, Changho Hwang, Kimin Lee
  
  ICLR 2026 | April 2026
  
  Preprint
- ARK: GPU-driven Code Execution for Distributed Deep Learning
  
  Changho Hwang, Ran Shu, Peng Cheng, Yongqiang Xiong, KyoungSoo Park
  
  NSDI | April 2023
  
  Publication

- Learning to Generate Unit Test via Adversarial Reinforcement Learning
  
  Dongjun Lee, Changho Hwang, Kimin Lee
  
  ICLR 2026 | April 2026
  
  Preprint
- MSCCL++: Rethinking GPU Communication Abstractions for AI Inference
  
  Changho Hwang, Peng Cheng, Roshan Dathathri, Abhinav Jangda, Saeed Maleki, Madan Musuvathi, Olli Saarikivi, Aashaka Shah, Ziyue Yang, Binyang Li, Caio Rocha, Qinghua Zhou, Mahdieh Ghazimirsaeed, Sreevatsa Anantharamu, Jithin Jose
  
  ACM International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS) | March 2026
  
  Preprint
- Pre-gated MoE: An Algorithm-System Co-Design for Fast and Scalable Mixture-of-Expert Inference
  
  Ranggi Hwang, Jianyu Wei, Shijie Cao, Changho Hwang, Xiaohu Tang, Ting Cao, Mao Yang
  
  ISCA 2024 | July 2024
  
  Microsoft Research Focus https://www.microsoft.com/en-us/research/blog/research-focus-week-of-july-15-2024/
  
  Publication
- ARK: GPU-driven Code Execution for Distributed Deep Learning
  
  Changho Hwang, Ran Shu, Peng Cheng, Yongqiang Xiong, KyoungSoo Park
  
  NSDI | April 2023
  
  Publication
- Tutel: Adaptive Mixture-of-Experts at Scale
  
  Changho Hwang, Wei Cui, Yifan Xiong, Ziyue Yang, Ze Liu, Han Hu, Zilong Wang, Rafael Salas, Jithin Jose, Prabhat Ram, Joe Chau, Peng Cheng, Fan Yang, Mao Yang, Yongqiang Xiong
  
  July 2022
  
  Publication
- Accelerating GNN training with locality-aware partial execution
  
  Taehyun Kim, Changho Hwang, KyoungSoo Park, Zhiqi Lin, Peng Cheng, Youshan Miao, Lingxiao Ma, Yongqiang Xiong
  
  August 2021
  
  Publication

Changho Hwang

출판물

Learning to Generate Unit Test via Adversarial Reinforcement Learning

MSCCL++: Rethinking GPU Communication Abstractions for AI Inference

Pre-gated MoE: An Algorithm-System Co-Design for Fast and Scalable Mixture-of-Expert Inference

ARK: GPU-driven Code Execution for Distributed Deep Learning

Tutel: Adaptive Mixture-of-Experts at Scale

Accelerating GNN training with locality-aware partial execution

Learning to Generate Unit Test via Adversarial Reinforcement Learning

MSCCL++: Rethinking GPU Communication Abstractions for AI Inference

MSCCL++: Rethinking GPU Communication Abstractions for AI Inference

Pre-gated MoE: An Algorithm-System Co-Design for Fast and Scalable Mixture-of-Expert Inference

ARK: GPU-driven Code Execution for Distributed Deep Learning

Tutel: Adaptive Mixture-of-Experts at Scale

Accelerating GNN training with locality-aware partial execution

Learning to Generate Unit Test via Adversarial Reinforcement Learning

ARK: GPU-driven Code Execution for Distributed Deep Learning

Learning to Generate Unit Test via Adversarial Reinforcement Learning

MSCCL++: Rethinking GPU Communication Abstractions for AI Inference

Pre-gated MoE: An Algorithm-System Co-Design for Fast and Scalable Mixture-of-Expert Inference

ARK: GPU-driven Code Execution for Distributed Deep Learning

Tutel: Adaptive Mixture-of-Experts at Scale

Accelerating GNN training with locality-aware partial execution

연락처 Changho Hwang

Microsoft Research Lab – Asia