Changho Hwang

Ph.D. Candidate @ School of Electrical Engineering, KAIST


Room 820, N1 ITC-Building

291 Daehak-ro, Yuseong-gu, Daejeon 34141, Republic of Korea

Profile

Graduate student at KAIST, studying high-performance networked systems and deep learning. Working in Networked & Distributed Computing Systems Lab (NDSL) with my advisor, Prof. KyoungSoo Park, since Dec 2015.

Research Interest

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

Education

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

Ph.D. student, Electrical Engineering

Advisor: KyoungSoo Park
Feb 2017 —

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

Research Intern, Network Research Group

Dec 2018 — Feb 2019

Research Projects

CoDDL Project

May 2017 —

Cloud coordinator for distributed deep learning.

Confident Multiple Choice Learning

Aug 2016 — Mar 2017

Efficient ensemble method for DNN classifiers that leverages multiple specializer models.
Open Source

APUNet Project

Jan 2015 — Dec 2015

High-performance packet processor accelerated by an integrated GPU.

Publications

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

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'19)

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


Skills

  • C/C++
  • Unix/GNU Linux
  • Python
  • PyTorch
  • CUDA
  • OpenCL
  • TensorFlow
  • LaTeX

Changho Hwang — chhwang@kaist.ac.kr