Changho Hwang

Researcher @ Systems & Networking Research Group,

Microsoft Research Asia


South Korea

Profile

Researcher at Microsoft, studying scalable AI and large-scale GPU systems. Received Ph.D. in Electrical Engineering from KAIST in February 2022, advised by Prof. KyoungSoo Park.

Research Interest

Systems support for deep learning, scalable networked systems, GPU systems, system performance optimization

Education

Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea

Ph.D. (Integrated M.S.-Ph.D. Program), Electrical Engineering

Advisor: KyoungSoo Park
Feb 2017 — Feb 2022

M.S. student, Electrical Engineering

Advisor: KyoungSoo Park
Feb 2016 — Jan 2017

B.S., Electrical Engineering (major) and Computer Science (minor)

Feb 2012 — Jan 2016

Professional Experience

Microsoft Research Asia, Beijing, China

Researcher, Networking Research Group

Mar 2022 — Present

Microsoft Research Asia, Beijing, China

Research Intern, Networking Research Group

Jul 2019 — Sep 2019

Dec 2018 — Feb 2019

Publications

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, and Yongqiang Xiong

arXiv:2206.03382, June 2022


Elastic Resource Sharing for Distributed Deep Learning

Changho Hwang, Taehyun Kim, Sunghyun Kim, Jinwoo Shin, and KyoungSoo Park

In Proceedings of the 18th USENIX Symposium on Networked Systems Design and Implementation (NSDI)

Virtual Event, April 2021


Confident Multiple Choice Learning

Kimin Lee, Changho Hwang, KyoungSoo Park, and Jinwoo Shin

In Proceedings of the 34th International Conference on Machine Learning (ICML)

Sydney, Austrailia, August 2017


APUNet: Revitalizing GPU as Packet Processing Accelerator

Younghwan Go, Muhammad Jamshed, YoungGyoun Moon, Changho Hwang, and KyoungSoo Park

In Proceedings of the 14th USENIX Symposium on Networked Systems Design and Implementation (NSDI)

Boston, MA, March 2017


Workshops & Posters

Towards GPU-driven Code Execution for Distributed Deep Learning (Awarded Best Paper)

Changho Hwang, KyoungSoo Park, Ran Shu, Xinyuan Qu, Peng Cheng, and Yongqiang Xiong

In the 3rd Machine Learning for Computer Architecture and Systems (MLArchSys@ISCA)

New York, United States, June 2022


Accelerating GNN Training with Locality-Aware Partial Execution (Awarded Best Paper)

Taehyun Kim, Changho Hwang, KyoungSoo Park, Zhiqi Lin, Peng Cheng, Youshan Miao, Lingxiao Ma, and Yongqiang Xiong

In the 12th ACM SIGOPS Asia-Pacific Workshop on Systems (APSys)

Virtual Event, August 2021


A Case for Two-stage Inference with Knowledge Caching

Geonha Park, Changho Hwang, and KyoungSoo Park

In the 3rd International Workshop on Embedded and Mobile Deep Learning (EMDL@MobiSys)

Seoul, Republic of Korea, June 2019


Efficient Resource Sharing for Distributed Deep Learning

Changho Hwang, Taehyun Kim, Kyuho Son, Jinwoo Shin, and KyoungSoo Park

In the 13th USENIX Symposium on Operating Systems Design and Implementation (OSDI) — poster

Carlsbad, CA, October 2018


Awards

The 28th Humantech Paper Award, Gold Prize, Computer Science & Engineering

Changho Hwang and KyoungSoo Park

February 2022

Changho Hwang — changhohwang@microsoft.com