Jong Choi

Orcid: 0000-0002-6459-6152

Affiliations:
  • Oak Ridge National Laboratory, Oak Ridge, TN, USA


According to our database1, Jong Choi authored at least 88 papers between 2005 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Scalable Training of Graph Foundation Models for Atomistic Materials Modeling: A Case Study with HydraGNN.
CoRR, 2024

MDLoader: A Hybrid Model-driven Data Loader for Distributed Deep Neural Networks Training.
Proceedings of the IEEE International Parallel and Distributed Processing Symposium, 2024

2023
Data Distillation for Neural Network Potentials toward Foundational Dataset.
CoRR, 2023

Unraveling Diffusion in Fusion Plasma: A Case Study of In Situ Processing and Particle Sorting.
CoRR, 2023

DDStore: Distributed Data Store for Scalable Training of Graph Neural Networks on Large Atomistic Modeling Datasets.
Proceedings of the SC '23 Workshops of The International Conference on High Performance Computing, 2023

Analyzing File Access Patterns on Large-Scale HPC Systems: Opportunities for File Prefetching.
Proceedings of the 31st International Symposium on Modeling, 2023

Predicting Power Outage During Extreme Weather Events with EAGLE-I and NWS Datasets.
Proceedings of the 24th IEEE International Conference on Information Reuse and Integration for Data Science, 2023

Fast Algorithms for Scientific Data Compression.
Proceedings of the 30th IEEE International Conference on High Performance Computing, 2023

Online and Scalable Data Compression Pipeline with Guarantees on Quantities of Interest.
Proceedings of the 19th IEEE International Conference on e-Science, 2023

2022
Multi-task graph neural networks for simultaneous prediction of global and atomic properties in ferromagnetic systems <sup>*</sup>.
Mach. Learn. Sci. Technol., 2022

Scalable training of graph convolutional neural networks for fast and accurate predictions of HOMO-LUMO gap in molecules.
J. Cheminformatics, 2022

The Exascale Framework for High Fidelity coupled Simulations (EFFIS): Enabling whole device modeling in fusion science.
Int. J. High Perform. Comput. Appl., 2022

Scalable Hybrid Learning Techniques for Scientific Data Compression.
CoRR, 2022

Multi-task graph neural networks for simultaneous prediction of global and atomic properties in ferromagnetic systems.
CoRR, 2022

A codesign framework for online data analysis and reduction.
Concurr. Comput. Pract. Exp., 2022

Machine Learning Assisted HPC Workload Trace Generation for Leadership Scale Storage Systems.
Proceedings of the HPDC '22: The 31st International Symposium on High-Performance Parallel and Distributed Computing, Minneapolis, MN, USA, 27 June 2022, 2022

An Algorithmic and Software Pipeline for Very Large Scale Scientific Data Compression with Error Guarantees.
Proceedings of the 29th IEEE International Conference on High Performance Computing, 2022

Hybrid Analysis of Fusion Data for Online Understanding of Complex Science on Extreme Scale Computers.
Proceedings of the IEEE International Conference on Cluster Computing, 2022

2021
Online data analysis and reduction: An important Co-design motif for extreme-scale computers.
Int. J. High Perform. Comput. Appl., 2021

Co-design Center for Exascale Machine Learning Technologies (ExaLearn).
Int. J. High Perform. Comput. Appl., 2021

Scalable Multigrid-based Hierarchical Scientific Data Refactoring on GPUs.
CoRR, 2021

Maintaining Trust in Reduction: Preserving the Accuracy of Quantities of Interest for Lossy Compression.
Proceedings of the Driving Scientific and Engineering Discoveries Through the Integration of Experiment, Big Data, and Modeling and Simulation, 2021

Accelerating Multigrid-based Hierarchical Scientific Data Refactoring on GPUs.
Proceedings of the 35th IEEE International Parallel and Distributed Processing Symposium, 2021

DYFLOW: A flexible framework for orchestrating scientific workflows on supercomputers.
Proceedings of the ICPP Workshops 2021: 50th International Conference on Parallel Processing, 2021

2020
Characterizing Output Bottlenecks of a Production Supercomputer: Analysis and Implications.
ACM Trans. Storage, 2020

ADIOS 2: The Adaptable Input Output System. A framework for high-performance data management.
SoftwareX, 2020

Extending the Publish/Subscribe Abstraction for High-Performance I/O and Data Management at Extreme Scale.
IEEE Data Eng. Bull., 2020

Chimbuko: A Workflow-Level Scalable Performance Trace Analysis Tool.
CoRR, 2020

Opportunities for Cost Savings with In-Transit Visualization.
Proceedings of the High Performance Computing - 35th International Conference, 2020

Visualization as a Service for Scientific Data.
Proceedings of the Driving Scientific and Engineering Discoveries Through the Convergence of HPC, Big Data and AI, 2020

Machine Learning for the Complex, Multi-scale Datasets in Fusion Energy.
Proceedings of the Driving Scientific and Engineering Discoveries Through the Convergence of HPC, Big Data and AI, 2020

Data Federation Challenges in Remote Near-Real-Time Fusion Experiment Data Processing.
Proceedings of the Driving Scientific and Engineering Discoveries Through the Convergence of HPC, Big Data and AI, 2020

Leading magnetic fusion energy science into the big-and-fast data lane.
Proceedings of the 19th Python in Science Conference 2020 (SciPy 2020), Virtual Conference, July 6, 2020

Near real-time analysis of big fusion data on HPC systems.
Proceedings of the IEEE/ACM HPC for Urgent Decision Making, UrgentHPC@SC 2020, Atlanta, GA, 2020

Comparing Time-to-Solution for In Situ Visualization Paradigms at Scale.
Proceedings of the 10th IEEE Symposium on Large Data Analysis and Visualization, 2020

2019
Harnessing Data Movement in Virtual Clusters for In-Situ Execution.
IEEE Trans. Parallel Distributed Syst., 2019

Can I/O Variability Be Reduced on QoS-Less HPC Storage Systems?
IEEE Trans. Computers, 2019

Comparing the Efficiency of In Situ Visualization Paradigms at Scale.
Proceedings of the High Performance Computing - 34th International Conference, 2019

A Codesign Framework for Online Data Analysis and Reduction.
Proceedings of the 2019 IEEE/ACM Workflows in Support of Large-Scale Science, 2019

Scalable Performance Awareness for In Situ Scientific Applications.
Proceedings of the 15th International Conference on eScience, 2019

2018
Binning Based Data Reduction for Vector Field Data of a Particle-In-Cell Fusion Simulation.
Proceedings of the High Performance Computing, 2018

In Situ Analysis and Visualization of Fusion Simulations: Lessons Learned.
Proceedings of the High Performance Computing, 2018

Understanding and Modeling Lossy Compression Schemes on HPC Scientific Data.
Proceedings of the 2018 IEEE International Parallel and Distributed Processing Symposium, 2018

A View from ORNL: Scientific Data Research Opportunities in the Big Data Age.
Proceedings of the 38th IEEE International Conference on Distributed Computing Systems, 2018


2017
Personalized Search Inspired Fast Interactive Estimation of Distribution Algorithm and Its Application.
IEEE Trans. Evol. Comput., 2017

On the Scalability of Data Reduction Techniques in Current and Upcoming HPC Systems from an Application Perspective.
Proceedings of the High Performance Computing, 2017

Comprehensive Measurement and Analysis of the User-Perceived I/O Performance in a Production Leadership-Class Storage System.
Proceedings of the 37th IEEE International Conference on Distributed Computing Systems, 2017

Exacution: Enhancing Scientific Data Management for Exascale.
Proceedings of the 37th IEEE International Conference on Distributed Computing Systems, 2017

StoreRush: An Application-Level Approach to Harvesting Idle Storage in a Best Effort Environment.
Proceedings of the International Conference on Computational Science, 2017

Predicting Output Performance of a Petascale Supercomputer.
Proceedings of the 26th International Symposium on High-Performance Parallel and Distributed Computing, 2017

Analysis and Modeling of the End-to-End I/O Performance on OLCF's Titan Supercomputer.
Proceedings of the 19th IEEE International Conference on High Performance Computing and Communications; 15th IEEE International Conference on Smart City; 3rd IEEE International Conference on Data Science and Systems, 2017

Canopus: Enabling Extreme-Scale Data Analytics on Big HPC Storage via Progressive Refactoring.
Proceedings of the 9th USENIX Workshop on Hot Topics in Storage and File Systems, 2017

Computing Just What You Need: Online Data Analysis and Reduction at Extreme Scales.
Proceedings of the Euro-Par 2017: Parallel Processing - 23rd International Conference on Parallel and Distributed Computing, Santiago de Compostela, Spain, August 28, 2017

Canopus: A Paradigm Shift Towards Elastic Extreme-Scale Data Analytics on HPC Storage.
Proceedings of the 2017 IEEE International Conference on Cluster Computing, 2017

Extending Skel to Support the Development and Optimization of Next Generation I/O Systems.
Proceedings of the 2017 IEEE International Conference on Cluster Computing, 2017

TGE: Machine Learning Based Task Graph Embedding for Large-Scale Topology Mapping.
Proceedings of the 2017 IEEE International Conference on Cluster Computing, 2017

2016
Towards Real-Time Detection and Tracking of Spatio-Temporal Features: Blob-Filaments in Fusion Plasma.
IEEE Trans. Big Data, 2016

Visualization and Analysis for Near-Real-Time Decision Making in Distributed Workflows.
Proceedings of the 2016 IEEE International Parallel and Distributed Processing Symposium Workshops, 2016

Persistent Data Staging Services for Data Intensive In-situ Scientific Workflows.
Proceedings of the ACM International Workshop on Data-Intensive Distributed Computing, 2016

A synthesized ranking-assisted NSGA-II for interval multi-objective optimization.
Proceedings of the IEEE Congress on Evolutionary Computation, 2016

2015
Towards Real-Time Detection and Tracking of Blob-Filaments in Fusion Plasma Big Data.
CoRR, 2015

Combining Phase Identification and Statistic Modeling for Automated Parallel Benchmark Generation.
Proceedings of the 2015 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems, 2015

Loosely Coupled In Situ Visualization: A Perspective on Why It's Here to Stay.
Proceedings of the First Workshop on In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization, 2015

2014
Hello ADIOS: the challenges and lessons of developing leadership class I/O frameworks.
Concurr. Comput. Pract. Exp., 2014

Active workflow system for near real-time extreme-scale science.
Proceedings of the first workshop on Parallel programming for analytics applications, 2014

2013
ADIOS Visualization Schema: A First Step Towards Improving Interdisciplinary Collaboration in High Performance Computing.
Proceedings of the 9th IEEE International Conference on eScience, 2013

2012
Mining hidden mixture context with ADIOS-P to improve predictive pre-fetcher accuracy.
Proceedings of the 8th IEEE International Conference on E-Science, 2012

2011
Cloud computing paradigms for pleasingly parallel biomedical applications.
Concurr. Comput. Pract. Exp., 2011

Browsing large-scale cheminformatics data with dimension reduction.
Concurr. Comput. Pract. Exp., 2011

2010
Generative topographic mapping by deterministic annealing.
Proceedings of the International Conference on Computational Science, 2010

Hybrid cloud and cluster computing paradigms for life science applications.
BMC Bioinform., 2010

Browsing large scale cheminformatics data with dimension reduction.
Proceedings of the 19th ACM International Symposium on High Performance Distributed Computing, 2010

Dimension reduction and visualization of large high-dimensional data via interpolation.
Proceedings of the 19th ACM International Symposium on High Performance Distributed Computing, 2010

High Performance Dimension Reduction and Visualization for Large High-Dimensional Data Analysis.
Proceedings of the 10th IEEE/ACM International Conference on Cluster, 2010

2009
Using Web 2.0 for scientific applications and scientific communities.
Concurr. Comput. Pract. Exp., 2009

Biomedical Case Studies in Data Intensive Computing.
Proceedings of the Cloud Computing, First International Conference, CloudCom 2009, Beijing, 2009

2008
Fast and Black-box Exploit Detection and Signature Generation for Commodity Software.
ACM Trans. Inf. Syst. Secur., 2008

PRECIP: Towards Practical and Retrofittable Confidential Information Protection.
Proceedings of the Network and Distributed System Security Symposium, 2008

BioVLAB-Microarray: Microarray Data Analysis in Virtual Environment.
Proceedings of the Fourth International Conference on e-Science, 2008

SALSA Project: Parallel Data Mining of GIS, Web, Medical, Physics, Chemical, and Biology Data.
Proceedings of the Fourth International Conference on e-Science, 2008

Social networking for scientists using tagging and shared bookmarks: a Web 2.0 application.
Proceedings of the 2008 International Symposium on Collaborative Technologies and Systems, 2008

2007
SpyShield: Preserving Privacy from Spy Add-Ons.
Proceedings of the Recent Advances in Intrusion Detection, 10th International Symposium, 2007

2006
Auditable Privacy: On Tamper-Evident Mix Networks.
Proceedings of the Financial Cryptography and Data Security, 2006

Tamper-Evident Digital Signature Protecting Certification Authorities Against Malware.
Proceedings of the Second International Symposium on Dependable Autonomic and Secure Computing (DASC 2006), 29 September, 2006

Packet vaccine: black-box exploit detection and signature generation.
Proceedings of the 13th ACM Conference on Computer and Communications Security, 2006

2005
Tamper-Evident Digital Signatures: Protecting Certification Authorities Against Malware.
IACR Cryptol. ePrint Arch., 2005

Balancing auditability and privacy in vehicular networks.
Proceedings of the Q2SWinet'05, 2005


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