Domain Level Page Sharing in Xen Virtual Machine Systems. - Myeongjae Jeon; Euiseong Seo; Junghyun Kim; Joonwon Lee (APPT, 2007)

Guest-Aware Priority-Based Virtual Machine Scheduling for Highly Consolidated Server. - Dongsung Kim; Hwanju Kim; Myeongjae Jeon; Euiseong Seo; Joonwon Lee (Euro-Par, 2008)

Measurement, Modeling, and Analysis of a Large-scale Blog Sever Workload. - Myeongjae Jeon; Jeaho Hwang; Youngjae Kim 001; Jae-Wan Jang; Joonwon Lee; Euiseong Seo (SocialCom/PASSAT, 2010)

Log' version vector: Logging version vectors concisely in dynamic replication. - Hyun-Gul Roh; Myeongjae Jeon; Euiseong Seo; Jinsoo Kim 001; Joonwon Lee (Inf. Process. Lett., 2010)

Replicated abstract data types: Building blocks for collaborative applications. - Hyun-Gul Roh; Myeongjae Jeon; Jinsoo Kim 001; Joonwon Lee (J. Parallel Distributed Comput., 2011)

Energy Reduction in Consolidated Servers through Memory-Aware Virtual Machine Scheduling. - Jae-Wan Jang; Myeongjae Jeon; Hyo-Sil Kim; Heeseung Jo; Jin-Soo Kim 001; Seungryoul Maeng (IEEE Trans. Computers, 2011)

Workload Characterization and Performance Implications of Large-Scale Blog Servers. - Myeongjae Jeon; Youngjae Kim 001; Jeaho Hwang; Joonwon Lee; Euiseong Seo (ACM Trans. Web, 2012)

Adaptive parallelism for web search. - Myeongjae Jeon; Yuxiong He; Sameh Elnikety; Alan L. Cox; Scott Rixner (EuroSys, 2013)

Reducing DRAM row activations with eager read/write clustering. - Myeongjae Jeon; Conglong Li; Alan L. Cox; Scott Rixner (ACM Trans. Archit. Code Optim., 2013)

Predictive parallelization: taming tail latencies in web search. - Myeongjae Jeon; Saehoon Kim; Seung-won Hwang; Yuxiong He; Sameh Elnikety; Alan L. Cox; Scott Rixner (SIGIR, 2014)

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, 2016)

SSD Failures in Datacenters: What? When? and Why? - Iyswarya Narayanan; Di Wang 003; Myeongjae Jeon; Bikash Sharma; Laura Caulfield; Anand Sivasubramaniam; Ben Cutler; Jie Liu 001; Badriddine M. Khessib; Kushagra Vaid (SYSTOR, 2016)

StreamBox: Modern Stream Processing on a Multicore Machine. - Hongyu Miao 002; Heejin Park; Myeongjae Jeon; Gennady Pekhimenko; Kathryn S. McKinley; Felix Xiaozhu Lin (USENIX ATC, 2017)

TerseCades: Efficient Data Compression in Stream Processing. - Gennady Pekhimenko; Chuanxiong Guo; Myeongjae Jeon; Peng Huang 005; Lidong Zhou (USENIX ATC, 2018)

StreamBox-HBM: Stream Analytics on High Bandwidth Hybrid Memory. - Hongyu Miao 002; Myeongjae Jeon; Gennady Pekhimenko; Kathryn S. McKinley; Felix Xiaozhu Lin (ASPLOS, 2019)

Tiresias: A GPU Cluster Manager for Distributed Deep Learning. - Juncheng Gu; Mosharaf Chowdhury; Kang G. Shin; Yibo Zhu; Myeongjae Jeon; Junjie Qian; Hongqiang Harry Liu; Chuanxiong Guo (NSDI, 2019)

Analysis of Large-Scale Multi-Tenant GPU Clusters for DNN Training Workloads. - Myeongjae Jeon; Shivaram Venkataraman; Amar Phanishayee; Junjie Qian; Wencong Xiao; Fan Yang 024 (USENIX ATC, 2019)

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 (CoRR, 2019)

Approximate Quantiles for Datacenter Telemetry Monitoring. - Gangmuk Lim; Mohamed S. Hassan 002; Ze Jin; Stavros Volos; Myeongjae Jeon (ICDE, 2020)

Zico: Efficient GPU Memory Sharing for Concurrent DNN Training. - Gangmuk Lim; Jeongseob Ahn; Wencong Xiao; Youngjin Kwon; Myeongjae Jeon (USENIX ATC, 2021)

Reliability of Large Scale GPU Clusters for Deep Learning Workloads. - Junjie Qian; Taeyoon Kim; Myeongjae Jeon (WWW (Companion Volume), 2021)

Carousel Memory: Rethinking the Design of Episodic Memory for Continual Learning. - Soobee Lee; Minindu Weerakoon; Jonghyun Choi; Minjia Zhang; Di Wang 003; Myeongjae Jeon (CoRR, 2021)

SWAN: WAN-aware stream processing on geographically-distributed clusters. - Won Wook Song; Myeongjae Jeon; Byung-Gon Chun (APSys, 2022)

CarM: hierarchical episodic memory for continual learning. - Soobee Lee; Minindu Weerakoon; Jonghyun Choi; Minjia Zhang; Di Wang 003; Myeongjae Jeon (DAC, 2022)

Jarvis: Large-scale Server Monitoring with Adaptive Near-data Processing. - Atul Sandur; Chanho Park; Stavros Volos; Gul Agha; Myeongjae Jeon (ICDE, 2022)

Memory Harvesting in Multi-GPU Systems with Hierarchical Unified Virtual Memory. - Sangjin Choi; Taeksoo Kim; Jinwoo Jeong; Rachata Ausavarungnirun; Myeongjae Jeon; Youngjin Kwon; Jeongseob Ahn (USENIX ATC, 2022)

Sibylla: To Retry or Not To Retry on Deep Learning Job Failure. - Taeyoon Kim; Suyeon Jeong; Jongseop Lee; Soobee Lee; Myeongjae Jeon (USENIX ATC, 2022)

Streaming Analytics with Adaptive Near-data Processing. - Atul Sandur; Chanho Park; Stavros Volos; Gul Agha; Myeongjae Jeon (WWW (Companion Volume), 2022)

Cost-effective On-device Continual Learning over Memory Hierarchy with Miro. - Xinyue Ma; Suyeon Jeong; Minjia Zhang; Di Wang 003; Jonghyun Choi; Myeongjae Jeon (MobiCom, 2023)

EnvPipe: Performance-preserving DNN Training Framework for Saving Energy. - Sangjin Choi; Inhoe Koo; Jeongseob Ahn; Myeongjae Jeon; Youngjin Kwon (USENIX ATC, 2023)

Sponge: Fast Reactive Scaling for Stream Processing with Serverless Frameworks. - Won Wook Song; Taegeon Um; Sameh Elnikety; Myeongjae Jeon; Byung-Gon Chun (USENIX ATC, 2023)

FusionFlow: Accelerating Data Preparation for Machine Learning with Hybrid CPU-GPU Processing. - Taeyoon Kim; Chanho Park; Mansur Mukimbekov; Heelim Hong; Minseok Kim; Ze Jin; Changdae Kim; Ji-Yong Shin; Myeongjae Jeon (Proc. VLDB Endow., 2023)

Blaze: Holistic Caching for Iterative Data Processing. - Won Wook Song; Jeongyoon Eo; Taegeon Um; Myeongjae Jeon; Byung-Gon Chun (EuroSys, 2024)

Metis: Fast Automatic Distributed Training on Heterogeneous GPUs. - Taegeon Um; Byungsoo Oh; Minyoung Kang; Woo-Yeon Lee; Goeun Kim; Dongseob Kim; Youngtaek Kim; Mohd Muzzammil; Myeongjae Jeon (USENIX ATC, 2024)

REP: Resource-Efficient Prompting for On-device Continual Learning. - Sungho Jeon 005; Xinyue Ma; Kwang In Kim; Myeongjae Jeon (CoRR, 2024)

HiP Attention: Sparse Sub-Quadratic Attention with Hierarchical Attention Pruning. - Heejun Lee; Geon Park; Youngwan Lee; Jina Kim; Wonyoung Jeong; Myeongjae Jeon; Sung Ju Hwang (CoRR, 2024)

Training-Free Exponential Extension of Sliding Window Context with Cascading KV Cache. - Jeffrey Willette; Heejun Lee; Youngwan Lee; Myeongjae Jeon; Sung Ju Hwang (CoRR, 2024)

A Training-Free Sub-quadratic Cost Transformer Model Serving Framework with Hierarchically Pruned Attention. - Heejun Lee; Geon Park; Youngwan Lee; Jaduk Suh; Jina Kim; Wonyong Jeong; Bumsik Kim; Hyemin Lee; Myeongjae Jeon; Sung Ju Hwang (ICLR, 2025)

Training Free Exponential Context Extension via Cascading KV Cache. - Jeffrey Willette; Heejun Lee; Youngwan Lee; Myeongjae Jeon; Sung Ju Hwang (ICLR, 2025)