Young-Kyoon Suh
Cited by
Cited by
EDISON: a web-based HPC simulation execution framework for large-scale scientific computing software
YK Suh, H Ryu, H Kim, KW Cho
2016 16th IEEE/ACM International Symposium on Cluster, Cloud and Grid …, 2016
A survey of simulation provenance systems: modeling, capturing, querying, visualization, and advanced utilization
YK Suh, KY Lee
Human-centric Computing and Information Sciences 8 (1), 1-29, 2018
DBMS metrology: measuring query time
S Currim, RT Snodgrass, YK Suh, R Zhang
ACM Transactions on Database Systems (TODS) 42 (1), 1-42, 2016
Construction and Service of a web-based Cyber-learning Platform for the Computational Science and Engineering Community in Korea
Y Suh, KW Cho
Journal of Internet Computing and Services 17 (4), 115-125, 2016
Extent mapping scheme for flash memory devices
YK Suh, B Moon, A Efrat, JS Kim, SW Lee
2012 IEEE 20th International Symposium on Modeling, Analysis and Simulation …, 2012
Empirical evaluation across multiple GPU-accelerated DBMSes
H Chu, S Kim, JY Lee, YK Suh
Proceedings of the 16th International Workshop on Data Management on New …, 2020
EMP: execution time measurement protocol for compute‐bound programs
YK Suh, RT Snodgrass, JD Kececioglu, PJ Downey, RS Maier, C Yi
Software: Practice and Experience 47 (4), 559-597, 2017
AZDBLab: a laboratory information system for large-scale empirical DBMS studies
YK Suh, RT Snodgrass, R Zhang
Proceedings of the VLDB Endowment 7 (13), 1641-1644, 2014
A survey of industrial internet of things platforms for establishing centralized Data-Acquisition middleware: categorization, experiment, and challenges
JS Ok, SD Kwon, CE Heo, YK Suh
Scientific Programming 2021, 1-11, 2021
A new tool for multi-level partitioning in teradata
YK Suh, A Ghazal, A Crolotte, P Kostamaa
Proceedings of the 21st ACM international conference on Information and …, 2012
CLUTCH: a clustering-driven runtime estimation scheme for scientific simulations
YK Suh, S Kim, J Kim
IEEE Access 8, 220710-220722, 2020
EXTES: An Execution-Time Estimation Scheme for Efficient Computational Science and Engineering Simulation via Machine Learning
S Kim, YK Suh, J Kim
IEEE Access 7, 98993-99002, 2019
SuperMan: a novel system for storing and retrieving scientific-simulation provenance for efficient job executions on computing clusters
YK Suh, J Ma
2017 IEEE 2nd International Workshops on Foundations and Applications of …, 2017
Design and implementation of a data-driven simulation service system
KY Lee, YJ Shin, YJ Choe, SJ Kim, YK Suh, JH Sa, KW Cho
Proceedings of the Sixth International Conference on Emerging Databases …, 2016
Development of a simulation result management and prediction system using machine learning techniques
KY Lee, YK Suh, KW Cho
International Journal of Data Mining and Bioinformatics 19 (1), 75-96, 2017
A comprehensive analysis of COVID-19 vaccine discourse by vaccine brand on Twitter in Korea: topic and sentiment analysis
S Park, YK Suh
Journal of Medical Internet Research 25, e42623, 2023
A pattern-based outlier region detection method for two-dimensional arrays
KY Lee, YK Suh
The Journal of Supercomputing 75, 170-188, 2019
Application parameter description scheme for multiple job generation in problem solving environment
B Kim, D Nam, YK Suh, JH Lee, K Cho, S Hwang
Third IEEE International Conference on e-Science and Grid Computing (e …, 2007
Have query optimizers hit the wall?
RT Snodgrass, S Currim, YK Suh
The VLDB Journal, 1-20, 2022
A simulation provenance data management system for efficient job execution on an online computational science engineering platform
J Ma, S Lee, KW Cho, YK Suh
Cluster Computing 22, 147-159, 2019
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