Myeongjae Jeon's homepage

Associate professor @ UNIST CS

Research Team: OMNIA

Myeongjae Jeon


I am an associate professor in the Department of Computer Science and Engineering at Ulsan National Institute of Science and Technology (UNIST). Prior to joining UNIST in 2018 fall, I spent several years in industry with Systems Research Group at Microsoft Research (2015 - 2018) and with Systems Research Group at the ARM Research (2014 - 2015). My prior research work has been deployed in several production systems in Microsoft, including Bing search engine, Open Platform for AI (OpenPAI), and Azure telemetry monitoring system, bringing real-world impacts from systems research. Currently at UNIST, I attempt to realize such values in the context of AI systems, real-time big data analytics, and systems for new HW, with my team members at OMNIA Lab.

I finished my Ph.D. in computer science at Rice University in May 2014, under the supervision of Prof. Alan L. Cox and Prof. Scott Rixner. During my Ph.D. I actively collaborated with Dr. Yuxiong He and Dr. Sameh Elnikety through 4 internships at Microsoft Research. I received the M.S. degree in computer science from KAIST and the B.E. degree in computer engineering from Kwangwoon University.


Apr. 2022 Giving a talk for systems for continual learning and ML data augmentation at LG AI Research Lab

Feb. 2022 Giving a talk for streaming analytics with adaptive near-data processing at Computer System Society

Oct. 2021 Serving as a program committee at ICDCS'22 (ML on or for Distributed Systems track)

Oct. 2021 Serving as a vice session chair at SOSP'21 (Learning track)

Sep. 2021 Selected as one of 7 AI research labs by Kakao Brain (We are the only lab in AI systems: news)

Nov. 2020 Serving as a program committee at ICDCS'21 (ML on or for Distributed Systems track)

Jul. 2020 Selected as a Facebook Faculty Research Award finalist

Apr. 2020 Giving a talk for our ML systems research at Samsung Electronics (for Data & IT center)

Jan. 2020 Serving as a program committee at ICDCS'20 (Distributed & Federated Learning track)

Oct. 2019 Attending Rice CS 35th Anniversary as a panel speaker for "The Role of Programming Systems while Hardware Specialization is Exploding" with Kathryn, Mary, Dan, and Felix


Computer architecture 2021 fall

Operating systems 2021 spring, 2020 spring

Parallel computing 2019 spring

Data structure 2019 fall, 2018 fall

Big data systems (graduate) 2021 fall

AI systems (graduate) 2019 spring


  1. Predictive Retry on DNN Job Failures with Sibylla

      • Taeyoon Kim, Suyeon Jeong, Jongseop Lee, Soobee Lee, Myeongjae Jeon

      • USENIX ATC, July 2022 [PDF]

  2. Memory Harvesting in Multi-GPU Systems with Hierarchical Unified Virtual Memory

      • Sangjin Choi, Taeksoo Kim, Jinwoo Jeong, Rachata Ausavarungniurn, Myeongjae Jeon, Youngjin Kwon, Jeongsub Ahn

      • USENIX ATC, July 2022 [PDF]

  3. CarM: Hierarchical Episodic Memory for Continual Learning

      • Soobee Lee, Minindu Weerakoon, Jonghyun Choi, Minjia Zhang, Di Wang, Myeongjae Jeon

      • DAC, July 2022 [PDF][PDF(extended)]

  4. Jarvis: Large-scale Server Monitoring with Adaptive Near-data Processing

      • Atul Sandur, ChanHo Park, Stavros Volos, Gul Agha, Myeongjae Jeon

      • IEEE ICDE, May 2022 (Best Paper) [PDF]

  5. Streaming Analytics with Adaptive Near-data Processing

      • Atul Sandur, ChanHo Park, Stavros Volos, Gul Agha, Myeongjae Jeon

      • EMDC, Apr. 2022 [PDF] (Invited paper)

  6. Zico: Efficient GPU Memory Sharing for Concurrent DNN Training

      • Gangmuk Lim, Jeongseob Ahn, Wencong Xiao, Youngjin Kwon, Myeongjae Jeon

      • USENIX ATC, Jul. 2021 [PDF][Talk][Slides]

  7. Reliability of Large-scale GPU Clusters for Deep Learning Workloads

      • Junjie Qian, Taeyoon Kim, Myeongjae Jeon

      • EMDC, Apr. 2021 [PDF] (Invited paper)

  8. Approximate Quantiles for Datacenter Telemetry Monitoring

      • Gangmuk Lim, Mohamed Hassan, Ze Jin, Stavros Volos, Myeongjae Jeon

      • IEEE ICDE, Apr. 2020 [PDF] [PDF(extended)][Talk][Slides] (Short paper)

  9. Analysis of Large-Scale Multi-Tenant GPU Clusters for DNN Training Workloads

      • Myeongjae Jeon, Shivaram Venkataraman, Amar Phanishayee, Junjie Qian, Wencong Xiao, Fan Yang

      • USENIX ATC, Jul. 2019 [PDF][Slides][Talk][Trace]

  10. StreamBox-HBM: Stream Analytics on High Bandwidth Hybrid Memory

      • Hongyu Miao, Myeongjae Jeon, Gennady Pekhimenko, Kathryn S. McKinley, Felix Xiaozhu Lin

      • ASPLOS, Apr. 2019 [PDF][Talk][Slides]

  11. Tiresias: A GPU Cluster Manager for Distributed Deep Learning

      • Juncheng Gu, Mosharaf Chowdhury, Kang G. Shin, Yibo Zhu, Myeongjae Jeon, Junjie Qian, Hongqiang Liu, Chuanxiong Guo

      • NSDI, Feb. 2019 [PDF][Talk][Slides]

  12. Accelerated Training for CNN Distributed Deep Learning through Automatic Resource-Aware Layer Placement

      • Jay H. Park, Sunghwan Kim, Jinwon Lee, Myeongjae Jeon, Sam H. Noh

      • Preprint, Jan. 2019 [PDF]

  13. TerseCades: Efficient Data Compression in Stream Processing

      • Gennady Pekhimenko, Chuanxiong Guo, Myeongjae Jeon, Peng Huang, Lidong Zhou

      • USENIX ATC, Jul. 2018 [PDF][Slides]

  14. StreamBox: Modern Stream Processing on a Multicore Machine

      • Hongyu Miao, Heejin Park, Myeongjae Jeon, Gennady Pekhimenko, Kathryn S. McKinley, Felix Xiaozhu Lin

      • USENIX ATC, Jul. 2017 [PDF][Slides]

  15. SSD Failures in Datacenters: What, When and Why?

      • Iyswarya Narayanan, Di Wang, Myeongjae Jeon, Bikash Sharma, Laura Caulfield, Anand Sivasubramaniam, Ben Cutler, Jie Liu, Badriddine Khessib, Kushagra Vaid

      • ACM SIGMETRICS / IFIP Performance, Jun. 2016 [PDF] (Poster)

      • ACM SYSTOR, Jun. 2016 (Best Student Paper) [PDF]

  16. TPC: Target-Driven Parallelism Combining Prediction and Correction to Reduce Tail Latency in Interactive Services

      • Myeongjae Jeon, Yuxiong He, Hwanju Kim, Sameh Elnikety, Scott Rixner, Alan L. Cox

      • ASPLOS, Apr. 2016 [PDF][Slides]

  17. Predictive Parallelization: Taming Tail Latencies in Web Search

      • Myeongjae Jeon, Saehoon Kim, Seung-Won Hwang, Yuxiong He, Sameh Elnikety, Alan L. Cox, Scott Rixner

      • ACM SIGIR, Jul. 2014 [PDF][Slides(pptx)]

  18. Reducing DRAM Row Activations with Eager Read/Write Clustering

      • Myeongjae Jeon, Conglong Li, Alan L. Cox, Scott Rixner

      • ACM Transactions on Architecture and Code Optimization (TACO), Dec. 2013 [PDF]

  19. Adaptive Parallelism for Web Search

      • Myeongjae Jeon, Yuxiong He, Sameh Elnikety, Alan L. Cox, Scott Rixner

      • ACM EuroSys, Apr. 2013 [PDF][Slides(pptx)]

  20. Workload Characterization and Performance Implications of Large-Scale Blog Servers

      • Myeongjae Jeon, Youngjae Kim, Jaeho Hwang, Joonwon Lee, Euiseong Seo

      • ACM Transactions on the Web (TWEB), Nov. 2012 [PDF]

  21. Energy Reduction in Consolidated Servers Through Memory-Aware Virtual Machine Scheduling

      • Jae-Wan Jang, Myeongjae Jeon, Hyo-Sil Kim, Heeseung Jo, Jin-Soo Kim, Seungryoul Maeng

      • IEEE Transactions on Computers (TC), Apr. 2011 [PDF]

  22. Replicated Abstract Data Types: Building Blocks for Collaborative Applications

      • Hyun-Gul Roh, Myeongjae Jeon, Jinsoo Kim, Joonwon Lee

      • Journal of Parallel and Distributed Computing (JPDC), Mar. 2011 [PDF]

  23. Measurement, Modeling, and Analysis of a Large-scale Blog Server Workload

      • Myeongjae Jeon, Jaeho Hwang, Youngjae Kim, Jae-wan Jang, Joonwon Lee, Euiseong Seo

      • IEEE SocialCom SCA, Aug. 2010 [PDF]

  24. Log' version vector: Logging version vectors concisely in dynamic replication

      • Hyun-Gul Roh, Myeongjae Jeon, Euiseong Seo, Jinsoo Kim, Joonwon Lee

      • Elsevier Information Processing Letters (IPL), May. 2010 [PDF]

  25. Guest-Aware Priority-based Virtual Machine Scheduling for Highly Consolidated Server

      • Dongsung Kim, Hwanju Kim, Myeongjae Jeon, Euiseong Seo, Joonwon Lee

      • Euro-Par, Aug. 2008 [PDF]

  26. Domain Level Page Sharing in Xen Virtual Machine Systems

      • Myeongjae Jeon, Euiseong Seo, Junghyun Kim, Joonwon Lee

      • APPT, Nov. 2007 [PDF]