My name is Gangmuk Lim. I am a 2nd year Ph.D. student at the Computer Science Department of the University of Illinois Urbana-Champaign, working with Professor Brighten Godfrey. Before starting my Ph.D., I earned my Bachelor and Master at the Computer Science at UNIST, South Korea, working with Professor Myeongjae Jeon.

My research primarily revolves around improving performance of microservice application in the cloud, reliability of cluster management system, and performance & resource utilization for machine learning applications. My most recent research project focuses on designing new service mesh system to minimize end-to-end latency and monetary costs associated with large scale microservice applications in the cloud. I am actively on the lookout to work on new projects around distributed systems for machine learning. If you are interested in working with me, please don't hesitate to reach out at gangmuk2 at illinois dot edu.

Previously, I was working on building a system for machine learning applications that improves GPU resource utilization and throughput by co-locating multiple training jobs.

You can find my full CV here.
Most likely, you can find me at Siebel building on 3rd floor at Urbana, IL.
LinkedIn, GitHub

News!

• Kivi accepted to USENIX ATC 24'
• Gave a talk at KubeCon 23' about SLATE . talk
• Gave a talk at IstioCon 23' about SLATE

Publication

• Kivi: Verification for Cluster Management
  Bingzhe Liu, Gangmuk Lim, Ryan Beckett, P. Brighten Godfrey.
  USENIX Annual Technical Conference (ATC'24), 2024
• Zico: Efficient GPU Memory Sharing for Concurrent DNN Training
  Gangmuk Lim, Jeongseob Ahn, Wencong Xiao, Youngjin Kwon, Myeongjae Jeon.
  USENIX Annual Technical Conference (ATC'21), 2021
• Approximate Quantiles for Data Center Telemetry Monitoring
  Gangmuk Lim, Myeongjae Jeon, Stavros Volos, Mohamed Hassan, Ze Jin.
  IEEE ICDE' 20 short