Data-Intensive Computing &
Systems Laboratory

The paper titled 'Coordinating Compaction between LSM-tree based Key-Value Stores for Edge Federation' authored by Jeeseob Kim, Honghyeon Yoo, Seungjae Lee, Hongsu Byun and Sungyong Park, has been accepted in the IEEE International Conference on Cloud Computing
(IEEE CLOUD'24).

Soon (PhD student) completed an internship at Oak Ridge National Lab during the last winter vacation, and as a result, contributed to the publication of an I/O acceleration poster for distributed deep learning at SOS26.

The paper titled 'Ensuring Compaction and Zone Cleaning Efficiency through Same-Zone Compaction in ZNS Key-Value Store,' authored by Sungjin Byeon, Joseph Ro, and Youngjae Kim, has been accepted for presentation at the 38th International Conference on Massive Storage Systems and Technology (MSST).

Hyungwoo Lee has joined us as a new MS student. Welcome aboard!

The paper titled 'DeepVM: Integrating Spot and On-Demand VMs for Cost-Efficient Deep Learning Clusters in the Cloud,' authored by Yoochan Kim, Kihyun Kim, Jinwoo Kim, Youngjae Kim, has been accepted for presentation at the 24th IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing (CCGrid).

Kyuri Park, Sungyong Park's paper titled "Performance Improvement Using Multi Checkpointing Technique in Micro-batch Streaming System" has been selected as the best paper presentation award in the field of the high performance computing at Korea Software Congress (KSC'23).

The paper titled 'OctoFAS: A Two-Level Fair Scheduler for Enhancing Fairness in Network-based Key-Value Storage,' authored by Yeohyeon Park, Junhyeok Park, Junghwan Park, Awais Khan, Youngjae Kim, has been accepted in the MDPI Electronics (Electronics).

Soyang Baek, Dongjae Lee, Honghyeon Yoo, Sungjin Byeon and Junhyeok Park have joined us as new MS students. Welcome on board!

The paper titled 'An Analytical Model-based Capacity Planning Approach for Building CSD-based Storage Systems,' authored by Hongsu Byun, Safdar Jamil, Sungyong Park, Youngjae Kim, has been accepted in the Transactions on Embedded Computing Systems (TECS).

The paper titled 'OctoKV: An Agile Network-based Key-Value Storage System with Robust Load Orchestration,' authored byYeohyeon Park, Junhyeok Park, Junghwan Park, Chang-Gyu Lee, and Youngjae Kim, has been accepted for presentation at the 31st International Symposium on the Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS).

Soon Hwang has joined us as a new PhD student. Welcome aboard!

Kyuri Park, Sungyong Park's paper titled "Performance Evaluation and Analysis for LSM based Persistent Key-Value Store in Streaming Application" has been selected as the best paper presentation award in the field of the high performance computing at Korea Computer Congress (KCC'23).

Jinwoo Kim(MS/PhD), SeJeong Oh(MS) and Junghyun Ryu(MS) have joined us. Welcome on board!

Prof. Youngjae Kim's co-authored Paper on "TomDB: A Hardware-Accelerated Key-Value Store for Data-Intensive Applications" has been accepted in the IEEE conference on Cluster Computing (Cluster'23).

Sungjin Byeon, Joseph Ro, Safdar Jamil, Jeong-Uk Kang, Youngjae Kim's Paper on "A Free-Space Adaptive Runtime Zone-Reset Algorithm for Enhanced ZNS Efficiency" has been accepted in the 15th ACM Workshop on Hot Topics in Storage and File Systems (HotStorage'23).

Seungjin Lee, Chang-Gyu, Donghyun Min, and Youngjae Kim's Paper on "Iterator Interface Extended LSM-tree-based KVSSD for Range Queries" has been accepted in the 16th ACM International Systems and Storage Conference (SYSTOR) 2023.

Donghyun Min, Kihyun Kim, Seungjin Lee, Youngjae Kim's Paper on "A Multi-Tenant Key-Value SSD with Secondary Index for Search Query Processing and Analysis" has been accepted in the Transactions on Embedded Computing Systems (TECS).

Sanha Maeng, Gordon Euhyun Moon, Sungyong Park's paper titled "Chronica: A Data-Imbalance-Aware Scheduler for Distributed Deep Learning" has been accepted in the 23rd IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing (CCGrid).