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ORCIDJong Choi 0001
Jong Youl Choi
Person information
- affiliation: Oak Ridge National Laboratory, Oak Ridge, TN, USA
Other persons with the same name
- Jong Choi 0002 — Sangmyung Women's University, Seoul, South Korea
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2020 – today
- 2024
[c61]Jonghyun Bae, Jong Youl Choi, Massimiliano Lupo Pasini, Kshitij Mehta, Khaled Z. Ibrahim:
MDLoader: A Hybrid Model-driven Data Loader for Distributed Deep Neural Networks Training. IPDPS (Workshops) 2024: 1193-1195- [i11]Massimiliano Lupo Pasini, Jong Youl Choi, Kshitij Mehta, Pei Zhang, David M. Rogers, Jonghyun Bae, Khaled Z. Ibrahim, Ashwin M. Aji, Karl W. Schulz, Jorda Polo, Prasanna Balaprakash:
Scalable Training of Graph Foundation Models for Atomistic Materials Modeling: A Case Study with HydraGNN. CoRR abs/2406.12909 (2024) - 2023
- [c60]Tania Banerjee, Jaemoon Lee, Jong Choi, Qian Gong
, Jieyang Chen, Choong-Seock Chang, Scott Klasky, Anand Rangarajan, Sanjay Ranka:
Online and Scalable Data Compression Pipeline with Guarantees on Quantities of Interest. e-Science 2023: 1-10 - [c59]Tania Banerjee, Jaemoon Lee, Jong Choi, Qian Gong, Jieyang Chen, Scott Klasky, Anand Rangarajan, Sanjay Ranka:
Fast Algorithms for Scientific Data Compression. HiPC 2023: 143-152 - [c58]Sangkeun Lee, Jong Choi, Gs Jung, Anika Tabassum, Nils M. Stenvig, Supriya Chinthavali:
Predicting Power Outage During Extreme Weather Events with EAGLE-I and NWS Datasets. IRI 2023: 211-212 - [c57]Ahmad Maroof Karimi, Arnab K. Paul, Jong Youl Choi, Lipeng Wan, Feiyi Wang:
Analyzing File Access Patterns on Large-Scale HPC Systems: Opportunities for File Prefetching. MASCOTS 2023: 1-4 - [c56]Jong Youl Choi, Massimiliano Lupo Pasini, Pei Zhang, Kshitij Mehta, Frank Liu, Jonghyun Bae, Khaled Ibrahim:
DDStore: Distributed Data Store for Scalable Training of Graph Neural Networks on Large Atomistic Modeling Datasets. SC Workshops 2023: 941-950 - [i10]Junmin Gu, Paul Lin, Kesheng Wu, Seung-Hoe Ku, Choong-Seock Chang, Randy Michael Churchill, Jong Choi, Norbert Podhorszki, Scott Klasky:
Unraveling Diffusion in Fusion Plasma: A Case Study of In Situ Processing and Particle Sorting. CoRR abs/2311.01288 (2023) - [i9]Gang Seob Jung, Sangkeun Lee, Jong Youl Choi:
Data Distillation for Neural Network Potentials toward Foundational Dataset. CoRR abs/2311.05407 (2023) - 2022
- [j19]Kshitij Mehta, Bryce Allen, Matthew Wolf, Jeremy Logan, Eric Suchyta, Swati Singhal, Jong Youl Choi, Keichi Takahashi, Kevin A. Huck, Igor Yakushin, Alan Sussman, Todd S. Munson, Ian T. Foster, Scott Klasky:
A codesign framework for online data analysis and reduction. Concurr. Comput. Pract. Exp. 34(14) (2022) - [j18]Eric Suchyta, Scott Klasky, Norbert Podhorszki, Matthew Wolf, Abolaji D. Adesoji, Choong-Seock Chang, Jong Choi, Philip E. Davis, Julien Dominski, Stéphane Ethier, Ian T. Foster, Kai Germaschewski, Berk Geveci, Chris Harris, Kevin A. Huck, Qing Liu, Jeremy Logan, Kshitij Mehta, Gabriele Merlo, Shirley V. Moore, Todd S. Munson, Manish Parashar, David Pugmire, Mark S. Shephard, Cameron W. Smith, Pradeep Subedi, Lipeng Wan, Ruonan Wang, Shuangxi Zhang:
The Exascale Framework for High Fidelity coupled Simulations (EFFIS): Enabling whole device modeling in fusion science. Int. J. High Perform. Comput. Appl. 36(1): 106-128 (2022) - [j17]Jong Youl Choi, Pei Zhang, Kshitij Mehta, Andrew E. Blanchard, Massimiliano Lupo Pasini:
Scalable training of graph convolutional neural networks for fast and accurate predictions of HOMO-LUMO gap in molecules. J. Cheminformatics 14(1): 70 (2022) - [j16]Massimiliano Lupo Pasini, Pei Zhang, Samuel Temple Reeve, Jong Youl Choi:
Multi-task graph neural networks for simultaneous prediction of global and atomic properties in ferromagnetic systems *. Mach. Learn. Sci. Technol. 3(2): 25007 (2022) - [c55]Eric Suchyta, Jong Youl Choi, Seung-Hoe Ku, David Pugmire, Ana Gainaru, Kevin A. Huck, Ralph Kube, Aaron Scheinberg, Frédéric Suter, Choong-Seock Chang, Todd S. Munson, Norbert Podhorszki, Scott Klasky:
Hybrid Analysis of Fusion Data for Online Understanding of Complex Science on Extreme Scale Computers. CLUSTER 2022: 218-229 - [c54]Tania Banerjee, Jong Choi, Jaemoon Lee, Qian Gong, Ruonan Wang, Scott Klasky, Anand Rangarajan, Sanjay Ranka:
An Algorithmic and Software Pipeline for Very Large Scale Scientific Data Compression with Error Guarantees. HIPC 2022: 226-235 - [c53]Arnab K. Paul, Jong Youl Choi, Ahmad Maroof Karimi, Feiyi Wang:
Machine Learning Assisted HPC Workload Trace Generation for Leadership Scale Storage Systems. HPDC 2022: 199-212 - [i8]Massimiliano Lupo Pasini, Pei Zhang, Samuel Temple Reeve, Jong Youl Choi:
Multi-task graph neural networks for simultaneous prediction of global and atomic properties in ferromagnetic systems. CoRR abs/2202.01954 (2022) - [i7]Jong Youl Choi, Pei Zhang, Kshitij Mehta, Andrew E. Blanchard, Massimiliano Lupo Pasini:
Scalable training of graph convolutional neural networks for fast and accurate predictions of HOMO-LUMO gap in molecules. CoRR abs/2207.11333 (2022) - [i6]Tania Banerjee, Jong Choi, Jaemoon Lee, Qian Gong, Jieyang Chen, Scott Klasky, Anand Rangarajan, Sanjay Ranka:
Scalable Hybrid Learning Techniques for Scientific Data Compression. CoRR abs/2212.10733 (2022) - 2021
- [j15]Francis J. Alexander, James A. Ang, Jenna A. Bilbrey, Jan Balewski, Tiernan Casey, Ryan Chard, Jong Choi, Sutanay Choudhury, Bert J. Debusschere, Anthony M. DeGennaro, Nikoli Dryden, J. Austin Ellis, Ian T. Foster, Cristina Garcia-Cardona, Sayan Ghosh, Peter Harrington, Yunzhi Huang, Shantenu Jha, Travis Johnston, Ai Kagawa, Ramakrishnan Kannan, Neeraj Kumar, Zhengchun Liu, Naoya Maruyama, Satoshi Matsuoka, Erin McCarthy, Jamaludin Mohd-Yusof, Peter Nugent, Yosuke Oyama, Thomas Proffen, David Pugmire, Sivasankaran Rajamanickam, Vinay Ramakrishnaiah, Malachi Schram, Sudip K. Seal, Ganesh Sivaraman, Christine Sweeney, Li Tan, Rajeev Thakur, Brian Van Essen, Logan T. Ward, Paul M. Welch, Michael Wolf, Sotiris S. Xantheas, Kevin G. Yager, Shinjae Yoo, Byung-Jun Yoon:
Co-design Center for Exascale Machine Learning Technologies (ExaLearn). Int. J. High Perform. Comput. Appl. 35(6): 598-616 (2021) - [j14]Ian T. Foster, Mark Ainsworth, Julie Bessac, Franck Cappello, Jong Choi, Sheng Di, Zichao Wendy Di, Ali Murat Gok, Hanqi Guo, Kevin A. Huck, Christopher Kelly, Scott Klasky, Kerstin Kleese van Dam, Xin Liang, Kshitij Mehta, Manish Parashar, Tom Peterka, Line Pouchard, Tong Shu, Ozan Tugluk, Hubertus Van Dam, Lipeng Wan, Matthew Wolf, Justin M. Wozniak, Wei Xu, Igor Yakushin, Shinjae Yoo, Todd S. Munson:
Online data analysis and reduction: An important Co-design motif for extreme-scale computers. Int. J. High Perform. Comput. Appl. 35(6): 617-635 (2021) - [c52]Swati Singhal, Alan Sussman, Matthew Wolf, Kshitij Mehta, Jong Youl Choi:
DYFLOW: A flexible framework for orchestrating scientific workflows on supercomputers. ICPP Workshops 2021: 31:1-31:11 - [c51]Jieyang Chen, Lipeng Wan, Xin Liang, Ben Whitney, Qing Liu, David Pugmire, Nicholas Thompson, Jong Youl Choi, Matthew Wolf, Todd S. Munson, Ian T. Foster, Scott Klasky:
Accelerating Multigrid-based Hierarchical Scientific Data Refactoring on GPUs. IPDPS 2021: 859-868 - [c50]Qian Gong, Xin Liang, Ben Whitney, Jong Youl Choi, Jieyang Chen, Lipeng Wan, Stéphane Ethier, Seung-Hoe Ku, Randy Michael Churchill, Choong-Seock Chang, Mark Ainsworth, Ozan Tugluk, Todd S. Munson, David Pugmire, Richard Archibald, Scott Klasky:
Maintaining Trust in Reduction: Preserving the Accuracy of Quantities of Interest for Lossy Compression. SMC 2021: 22-39 - [i5]Jieyang Chen, Lipeng Wan, Xin Liang, Ben Whitney, Qing Liu, Qian Gong, David Pugmire, Nicholas Thompson, Jong Youl Choi, Matthew Wolf, Todd S. Munson, Ian T. Foster, Scott Klasky:
Scalable Multigrid-based Hierarchical Scientific Data Refactoring on GPUs. CoRR abs/2105.12764 (2021) - 2020
- [j13]Jeremy Logan, Mark Ainsworth, Chuck Atkins, Jieyang Chen, Jong Choi, Junmin Gu, James Kress, Greg Eisenhauer, Berk Geveci, William F. Godoy, Mark Kim, Tahsin M. Kurç, Qing Liu, Kshitij Mehta, George Ostrouchov, Norbert Podhorszki, David Pugmire, Eric Suchyta, Nicholas Thompson, Ozan Tugluk, Lipeng Wan, Ruonan Wang, Ben Whitney, Matthew Wolf, Kesheng Wu, Scott Klasky:
Extending the Publish/Subscribe Abstraction for High-Performance I/O and Data Management at Extreme Scale. IEEE Data Eng. Bull. 43(1): 35-46 (2020) - [j12]William F. Godoy, Norbert Podhorszki, Ruonan Wang, Chuck Atkins, Greg Eisenhauer, Junmin Gu, Philip E. Davis, Jong Choi, Kai Germaschewski, Kevin A. Huck, Axel Huebl, Mark Kim, James Kress, Tahsin M. Kurç, Qing Liu, Jeremy Logan, Kshitij Mehta, George Ostrouchov, Manish Parashar, Franz Poeschel, David Pugmire, Eric Suchyta, Keichi Takahashi, Nick Thompson, Seiji Tsutsumi, Lipeng Wan, Matthew Wolf, Kesheng Wu, Scott Klasky:
ADIOS 2: The Adaptable Input Output System. A framework for high-performance data management. SoftwareX 12: 100561 (2020) - [j11]Bing Xie, Sarp Oral, Christopher Zimmer, Jong Youl Choi, David Dillow, Scott Klasky, Jay F. Lofstead, Norbert Podhorszki, Jeffrey S. Chase:
Characterizing Output Bottlenecks of a Production Supercomputer: Analysis and Implications. ACM Trans. Storage 15(4): 26:1-26:39 (2020) - [c49]James Kress, Matthew Larsen, Jong Choi, Mark Kim, Matthew Wolf, Norbert Podhorszki, Scott Klasky, Hank Childs, David Pugmire:
Comparing Time-to-Solution for In Situ Visualization Paradigms at Scale. LDAV 2020: 22-26 - [c48]Ralph Kube, Randy Michael Churchill, Jong Choi, Ruonan Wang, Minjun Choi, Scott Klasky, Choong-Seock Chang:
Near real-time analysis of big fusion data on HPC systems. UrgentHPC@SC 2020: 55-63 - [c47]Ralph Kube, Randy Michael Churchill, Jong Youl Choi, Ruonan Wang, Scott Klasky, CS Chang, Minjun J. Choi, Jinseop Park:
Leading magnetic fusion energy science into the big-and-fast data lane. SciPy 2020: 140-147 - [c46]David Pugmire, James Kress, Jieyang Chen, Hank Childs, Jong Choi, Dmitry Ganyushin, Berk Geveci, Mark Kim, Scott Klasky, Xin Liang, Jeremy Logan, Nicole Marsaglia, Kshitij Mehta, Norbert Podhorszki, Caitlin Ross, Eric Suchyta, Nick Thompson, Steven Walton, Lipeng Wan, Matthew Wolf:
Visualization as a Service for Scientific Data. SMC 2020: 157-174 - [c45]Randy Michael Churchill, Jong Choi, Ralph Kube, Choong-Seock Chang, Scott Klasky:
Machine Learning for the Complex, Multi-scale Datasets in Fusion Energy. SMC 2020: 269-284 - [c44]Jong Choi, Ruonan Wang, Randy Michael Churchill, Ralph Kube, Minjun Choi, Jinseop Park, Jeremy Logan, Kshitij Mehta, Greg Eisenhauer, Norbert Podhorszki, Matthew Wolf, Choong-Seock Chang, Scott Klasky:
Data Federation Challenges in Remote Near-Real-Time Fusion Experiment Data Processing. SMC 2020: 285-299 - [c43]James Kress, Matthew Larsen, Jong Choi, Mark Kim, Matthew Wolf, Norbert Podhorszki, Scott Klasky, Hank Childs, David Pugmire:
Opportunities for Cost Savings with In-Transit Visualization. ISC 2020: 146-165 - [i4]Sungsoo Ha, Wonyong Jeong, Gyorgy Matyasfalvi, Cong Xie, Kevin A. Huck, Jong Youl Choi, Abid Malik, Li Tang, Hubertus Van Dam, Line Pouchard, Wei Xu, Shinjae Yoo, Nicholas D'Imperio, Kerstin Kleese van Dam:
Chimbuko: A Workflow-Level Scalable Performance Trace Analysis Tool. CoRR abs/2008.13742 (2020)
2010 – 2019
- 2019
- [j10]Dan Huang, Qing Liu, Jong Choi, Norbert Podhorszki, Scott Klasky, Jeremy Logan, George Ostrouchov, Xubin He, Matthew Wolf:
Can I/O Variability Be Reduced on QoS-Less HPC Storage Systems? IEEE Trans. Computers 68(5): 631-645 (2019) - [j9]Dan Huang, Qing Liu, Scott Klasky, Jun Wang, Jong Youl Choi, Jeremy Logan, Norbert Podhorszki:
Harnessing Data Movement in Virtual Clusters for In-Situ Execution. IEEE Trans. Parallel Distributed Syst. 30(3): 615-629 (2019) - [c42]Matthew Wolf, Julien Dominski, Gabriele Merlo, Jong Choi, Greg Eisenhauer, Stéphane Ethier, Kevin A. Huck, Scott Klasky, Jeremy Logan, Allen D. Malony, Chad Wood:
Scalable Performance Awareness for In Situ Scientific Applications. eScience 2019: 266-276 - [c41]Kshitij Mehta, Ian T. Foster, Scott Klasky, Bryce Allen, Matthew Wolf, Jeremy Logan, Eric Suchyta, Jong Choi, Keichi Takahashi, Igor Yakushin, Todd S. Munson:
A Codesign Framework for Online Data Analysis and Reduction. WORKS@SC 2019: 11-20 - [c40]James Kress, Matthew Larsen, Jong Choi, Mark Kim, Matthew Wolf, Norbert Podhorszki, Scott Klasky, Hank Childs, David Pugmire:
Comparing the Efficiency of In Situ Visualization Paradigms at Scale. ISC 2019: 99-117 - 2018
- [c39]Jong Youl Choi, Choong-Seock Chang, Julien Dominski, Scott Klasky, Gabriele Merlo, Eric Suchyta, Mark Ainsworth, Bryce Allen, Franck Cappello, Michael Churchill, Philip E. Davis, Sheng Di, Greg Eisenhauer, Stéphane Ethier, Ian T. Foster, Berk Geveci, Hanqi Guo, Kevin A. Huck, Frank Jenko, Mark Kim, James Kress, Seung-Hoe Ku, Qing Liu, Jeremy Logan, Allen D. Malony, Kshitij Mehta, Kenneth Moreland, Todd S. Munson, Manish Parashar, Tom Peterka, Norbert Podhorszki, Dave Pugmire, Ozan Tugluk, Ruonan Wang, Ben Whitney, Matthew Wolf, Chad Wood:
Coupling Exascale Multiphysics Applications: Methods and Lessons Learned. eScience 2018: 442-452 - [c38]Scott Klasky, Matthew Wolf, Mark Ainsworth, Chuck Atkins, Jong Choi, Greg Eisenhauer, Berk Geveci, William F. Godoy, Mark Kim, James Kress, Tahsin M. Kurç, Qing Liu, Jeremy Logan, Arthur B. Maccabe, Kshitij Mehta, George Ostrouchov, Manish Parashar, Norbert Podhorszki, David Pugmire, Eric Suchyta, Lipeng Wan, Ruonan Wang:
A View from ORNL: Scientific Data Research Opportunities in the Big Data Age. ICDCS 2018: 1357-1368 - [c37]Tao Lu, Qing Liu, Xubin He, Huizhang Luo, Eric Suchyta, Jong Choi, Norbert Podhorszki, Scott Klasky, Matthew Wolf, Tong Liu, Zhenbo Qiao:
Understanding and Modeling Lossy Compression Schemes on HPC Scientific Data. IPDPS 2018: 348-357 - [c36]James Kress, Jong Choi, Scott Klasky, Michael Churchill, Hank Childs, David Pugmire:
Binning Based Data Reduction for Vector Field Data of a Particle-In-Cell Fusion Simulation. ISC Workshops 2018: 215-229 - [c35]Mark Kim, James Kress, Jong Choi, Norbert Podhorszki, Scott Klasky, Matthew Wolf, Kshitij Mehta, Kevin A. Huck, Berk Geveci, Sujin Phillip, Robert Maynard, Hanqi Guo, Tom Peterka, Kenneth Moreland, Choong-Seock Chang, Julien Dominski, Michael Churchill, David Pugmire:
In Situ Analysis and Visualization of Fusion Simulations: Lessons Learned. ISC Workshops 2018: 230-242 - 2017
- [j8]Yang Chen, Xiaoyan Sun, Dunwei Gong, Yong Zhang, Jong Choi, Scott Klasky:
Personalized Search Inspired Fast Interactive Estimation of Distribution Algorithm and Its Application. IEEE Trans. Evol. Comput. 21(4): 588-600 (2017) - [c34]Tao Lu, Eric Suchyta, David Pugmire, Jong Choi, Scott Klasky, Qing Liu, Norbert Podhorszki, Mark Ainsworth, Matthew Wolf:
Canopus: A Paradigm Shift Towards Elastic Extreme-Scale Data Analytics on HPC Storage. CLUSTER 2017: 58-69 - [c33]Jeremy Logan, Jong Youl Choi, Matthew Wolf, George Ostrouchov, Lipeng Wan, Norbert Podhorszki, William F. Godoy, Scott Klasky, Erich Lohrmann, Greg Eisenhauer, Chad Wood, Kevin A. Huck:
Extending Skel to Support the Development and Optimization of Next Generation I/O Systems. CLUSTER 2017: 563-571 - [c32]Jong Youl Choi, Jeremy Logan, Matthew Wolf, George Ostrouchov, Tahsin M. Kurç, Qing Liu, Norbert Podhorszki, Scott Klasky, Melissa Romanus, Qian Sun, Manish Parashar, Randy Michael Churchill, Choong-Seock Chang:
TGE: Machine Learning Based Task Graph Embedding for Large-Scale Topology Mapping. CLUSTER 2017: 587-591 - [c31]Ian T. Foster, Mark Ainsworth, Bryce Allen, Julie Bessac, Franck Cappello, Jong Youl Choi, Emil M. Constantinescu, Philip E. Davis, Sheng Di, Zichao Wendy Di, Hanqi Guo, Scott Klasky, Kerstin Kleese van Dam, Tahsin M. Kurç, Qing Liu, Abid Malik, Kshitij Mehta, Klaus Mueller, Todd S. Munson, George Ostrouchov, Manish Parashar, Tom Peterka, Line Pouchard, Dingwen Tao, Ozan Tugluk, Stefan M. Wild, Matthew Wolf, Justin M. Wozniak, Wei Xu, Shinjae Yoo:
Computing Just What You Need: Online Data Analysis and Reduction at Extreme Scales. Euro-Par 2017: 3-19 - [c30]Tao Lu, Eric Suchyta, Jong Youl Choi, Norbert Podhorszki, Scott Klasky, Qing Liu, David Pugmire, Matthew Wolf, Mark Ainsworth:
Canopus: Enabling Extreme-Scale Data Analytics on Big HPC Storage via Progressive Refactoring. HotStorage 2017 - [c29]Lipeng Wan, Matthew Wolf, Feiyi Wang, Jong Youl Choi, George Ostrouchov, Scott Klasky:
Analysis and Modeling of the End-to-End I/O Performance on OLCF's Titan Supercomputer. HPCC/SmartCity/DSS 2017: 1-9 - [c28]Bing Xie, Yezhou Huang, Jeffrey S. Chase, Jong Youl Choi, Scott Klasky, Jay F. Lofstead, Sarp Oral:
Predicting Output Performance of a Petascale Supercomputer. HPDC 2017: 181-192 - [c27]Qing Liu, Norbert Podhorszki, Jong Youl Choi, Jeremy Logan, Matthew Wolf, Scott Klasky, Tahsin M. Kurç, Xubin He:
StoreRush: An Application-Level Approach to Harvesting Idle Storage in a Best Effort Environment. ICCS 2017: 475-484 - [c26]Lipeng Wan, Matthew Wolf, Feiyi Wang, Jong Youl Choi, George Ostrouchov, Scott Klasky:
Comprehensive Measurement and Analysis of the User-Perceived I/O Performance in a Production Leadership-Class Storage System. ICDCS 2017: 1022-1031 - [c25]Scott Klasky, Eric Suchyta, Mark Ainsworth, Qing Liu, Ben Whitney, Matthew Wolf, Jong Youl Choi, Ian T. Foster, Mark Kim, Jeremy Logan, Kshitij Mehta, Todd S. Munson, George Ostrouchov, Manish Parashar, Norbert Podhorszki, David Pugmire, Lipeng Wan:
Exacution: Enhancing Scientific Data Management for Exascale. ICDCS 2017: 1927-1937 - [c24]Axel Huebl, René Widera, Felix Schmitt, Alexander Matthes, Norbert Podhorszki, Jong Youl Choi, Scott Klasky, Michael Bussmann:
On the Scalability of Data Reduction Techniques in Current and Upcoming HPC Systems from an Application Perspective. ISC Workshops 2017: 15-29 - [i3]Axel Huebl, René Widera, Felix Schmitt, Alexander Matthes, Norbert Podhorszki, Jong Youl Choi, Scott Klasky, Michael Bussmann:
On the Scalability of Data Reduction Techniques in Current and Upcoming HPC Systems from an Application Perspective. CoRR abs/1706.00522 (2017) - 2016
- [j7]Lingfei Wu, K. John Wu, Alex Sim, Michael Churchill, Jong Youl Choi, Andreas Stathopoulos, Choong-Seock Chang, Scott Klasky:
Towards Real-Time Detection and Tracking of Spatio-Temporal Features: Blob-Filaments in Fusion Plasma. IEEE Trans. Big Data 2(3): 262-275 (2016) - [c23]Pengfei Zhang, Ruidong Xu, Xiaoyan Sun, Dunwei Gong, Yong Zhang, Jong Choi:
A synthesized ranking-assisted NSGA-II for interval multi-objective optimization. CEC 2016: 861-868 - [c22]Melissa Romanus, Fan Zhang, Tong Jin, Qian Sun, Hoang Bui, Manish Parashar, Jong Youl Choi, Saloman Janhunen, Robert Hager, Scott Klasky, Choong-Seock Chang, Ivan Rodero:
Persistent Data Staging Services for Data Intensive In-situ Scientific Workflows. DIDC@HPDC 2016: 37-44 - [c21]David Pugmire, James Kress, Jong Youl Choi, Scott Klasky, Tahsin M. Kurç, Michael Churchill, Matthew Wolf, Greg Eisenhauer, Hank Childs, Kesheng Wu, Alexander Sim, Junmin Gu, Jonathan Low:
Visualization and Analysis for Near-Real-Time Decision Making in Distributed Workflows. IPDPS Workshops 2016: 1007-1013 - 2015
- [c20]Ye Jin, Mingliang Liu, Xiaosong Ma, Qing Liu, Jeremy Logan, Norbert Podhorszki, Jong Youl Choi, Scott Klasky:
Combining phase identification and statistic modeling for automated parallel benchmark generation. PPoPP 2015: 269-270 - [c19]James Kress, Scott Klasky, Norbert Podhorszki, Jong Youl Choi, Hank Childs, David Pugmire:
Loosely Coupled In Situ Visualization: A Perspective on Why It's Here to Stay. ISAV@SC 2015: 1-6 - [c18]Ye Jin, Xiaosong Ma, Mingliang Liu, Qing Liu, Jeremy Logan, Norbert Podhorszki, Jong Youl Choi, Scott Klasky:
Combining Phase Identification and Statistic Modeling for Automated Parallel Benchmark Generation. SIGMETRICS 2015: 309-320 - [i2]Lingfei Wu, Kesheng Wu, Alex Sim, Michael Churchill, Jong Youl Choi, Andreas Stathopoulos, Choong-Seock Chang, Scott Klasky:
Towards Real-Time Detection and Tracking of Blob-Filaments in Fusion Plasma Big Data. CoRR abs/1505.03532 (2015) - 2014
- [j6]Qing Liu, Jeremy Logan, Yuan Tian, Hasan Abbasi, Norbert Podhorszki, Jong Youl Choi, Scott Klasky, Roselyne Tchoua, Jay F. Lofstead, Ron A. Oldfield, Manish Parashar, Nagiza F. Samatova, Karsten Schwan, Arie Shoshani, Matthew Wolf, Kesheng Wu, Weikuan Yu:
Hello ADIOS: the challenges and lessons of developing leadership class I/O frameworks. Concurr. Comput. Pract. Exp. 26(7): 1453-1473 (2014) - [c17]Yanwei Zhang, Qing Liu, Scott Klasky, Matthew Wolf, Karsten Schwan, Greg Eisenhauer, Jong Youl Choi, Norbert Podhorszki:
Active workflow system for near real-time extreme-scale science. PPAA@PPoPP 2014: 53-62 - 2013
- [c16]Roselyne Tchoua, Jong Youl Choi, Scott Klasky, Qing Liu, Jeremy Logan, Kenneth Moreland, Jingqing Mu, Manish Parashar, Norbert Podhorszki, David Pugmire, Matthew Wolf:
ADIOS Visualization Schema: A First Step Towards Improving Interdisciplinary Collaboration in High Performance Computing. e-Science 2013: 27-34 - 2012
- [c15]Jong Youl Choi, Hasan Abbasi, David Pugmire, Norbert Podhorszki, Scott Klasky, Cristian Capdevila, Manish Parashar, Matthew Wolf, Judy Qiu, Geoffrey C. Fox:
Mining hidden mixture context with ADIOS-P to improve predictive pre-fetcher accuracy. eScience 2012: 1-8 - 2011
- [j5]Jong Youl Choi, Seung-Hee Bae, Judy Qiu, Bin Chen, David J. Wild:
Browsing large-scale cheminformatics data with dimension reduction. Concurr. Comput. Pract. Exp. 23(17): 2315-2325 (2011) - [j4]Thilina Gunarathne, Tak-Lon Wu, Jong Youl Choi, Seung-Hee Bae, Judy Qiu:
Cloud computing paradigms for pleasingly parallel biomedical applications. Concurr. Comput. Pract. Exp. 23(17): 2338-2354 (2011) - 2010
- [j3]Judy Qiu, Jaliya Ekanayake, Thilina Gunarathne, Jong Youl Choi, Seung-Hee Bae, Hui Li, Bingjing Zhang, Tak-Lon Wu, Yang Ruan, Saliya Ekanayake, Adam Hughes, Geoffrey C. Fox:
Hybrid cloud and cluster computing paradigms for life science applications. BMC Bioinform. 11(S-12): S3 (2010) - [c14]Jong Youl Choi, Seung-Hee Bae, Xiaohong Qiu, Geoffrey C. Fox:
High Performance Dimension Reduction and Visualization for Large High-Dimensional Data Analysis. CCGRID 2010: 331-340 - [c13]Seung-Hee Bae, Jong Youl Choi, Judy Qiu, Geoffrey C. Fox:
Dimension reduction and visualization of large high-dimensional data via interpolation. HPDC 2010: 203-214 - [c12]Jong Youl Choi, Seung-Hee Bae, Judy Qiu, Geoffrey C. Fox, Bin Chen, David J. Wild:
Browsing large scale cheminformatics data with dimension reduction. HPDC 2010: 503-506 - [c11]Jong Youl Choi, Judy Qiu, Marlon E. Pierce, Geoffrey C. Fox:
Generative topographic mapping by deterministic annealing. ICCS 2010: 47-56
2000 – 2009
- 2009
- [j2]Marlon E. Pierce, Geoffrey C. Fox, Jong Youl Choi, Zhenhua Guo, Xiaoming Gao, Yu Ma:
Using Web 2.0 for scientific applications and scientific communities. Concurr. Comput. Pract. Exp. 21(5): 583-603 (2009) - [c10]Geoffrey C. Fox, Xiaohong Qiu, Scott Beason, Jong Youl Choi, Jaliya Ekanayake, Thilina Gunarathne, Mina Rho, Haixu Tang, Neil Devadasan, Gilbert Liu:
Biomedical Case Studies in Data Intensive Computing. CloudCom 2009: 2-18 - 2008
- [j1]XiaoFeng Wang, Zhuowei Li, Jong Youl Choi, Jun Xu, Michael K. Reiter, Chongkyung Kil:
Fast and Black-box Exploit Detection and Signature Generation for Commodity Software. ACM Trans. Inf. Syst. Secur. 12(2): 11:1-11:35 (2008) - [c9]Marlon E. Pierce, Geoffrey C. Fox, Joshua J. Rosen, Siddharth Maini, Jong Youl Choi:
Social networking for scientists using tagging and shared bookmarks: a Web 2.0 application. CTS 2008: 257-266 - [c8]Youngik Yang, Jong Youl Choi, Kwangmin Choi, Marlon E. Pierce, Dennis Gannon, Sun Kim:
BioVLAB-Microarray: Microarray Data Analysis in Virtual Environment. eScience 2008: 159-165 - [c7]Xiaohong Qiu, Geoffrey C. Fox, Seung-Hee Bae, Jong Youl Choi, Jaliya Ekanayake, Yang Ruan:
SALSA Project: Parallel Data Mining of GIS, Web, Medical, Physics, Chemical, and Biology Data. eScience 2008: 335-336 - [c6]XiaoFeng Wang, Zhuowei Li, Ninghui Li, Jong Youl Choi:
PRECIP: Towards Practical and Retrofittable Confidential Information Protection. NDSS 2008 - 2007
- [c5]Zhuowei Li, XiaoFeng Wang, Jong Youl Choi:
SpyShield: Preserving Privacy from Spy Add-Ons. RAID 2007: 296-316 - 2006
- [c4]XiaoFeng Wang, Zhuowei Li, Jun Xu, Michael K. Reiter, Chongkyung Kil, Jong Youl Choi:
Packet vaccine: black-box exploit detection and signature generation. CCS 2006: 37-46 - [c3]Jong Youl Choi, Philippe Golle, Markus Jakobsson:
Tamper-Evident Digital Signature Protecting Certification Authorities Against Malware. DASC 2006: 37-44 - [c2]Jong Youl Choi, Philippe Golle, Markus Jakobsson:
Auditable Privacy: On Tamper-Evident Mix Networks. Financial Cryptography 2006: 126-141 - 2005
- [c1]Jong Youl Choi, Markus Jakobsson, Susanne Wetzel:
Balancing auditability and privacy in vehicular networks. Q2SWinet 2005: 79-87 - [i1]Jong Youl Choi, Philippe Golle, Markus Jakobsson:
Tamper-Evident Digital Signatures: Protecting Certification Authorities Against Malware. IACR Cryptol. ePrint Arch. 2005: 147 (2005)
Coauthor Index
Michael Churchill
aka: Randy Michael Churchill
aka: Randy Michael Churchill
[c60] [c59] [i10] [j19] [j18] [c55] [c54] [i6] [j14] [c51] [c50] [i5] [j13] [j12] [j11] [c49] [c48] [c47] [c46] [c45] [c44] [c43] [j10] [j9] [c42] [c41] [c40] [c39] [c38] [c37] [c36] [c35] [j8] [c34] [c33] [c32] [c31] [c30] [c29] [c28] [c27] [c26] [c25] [c24] [i3] [j7] [c22] [c21] [c20] [c19] [c18] [i2] [j6] [c17] [c16] [c15]
David Pugmire
aka: Dave Pugmire
aka: Dave Pugmire
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