Scott A Klasky Group Leader for Workflow Systems Group Contact 865.241.9980 | klasky@ornl.gov All Publications Towards Resilient Near Real-Time Analysis Workflows in Fusion Energy Science A Personalized AI Assistant for Intuition-Driven Visual Explorations Optimizing Metadata Exchange: Leveraging DAOS for ADIOS Metadata I/O Hades: A Context-Aware Active Storage Framework for Accelerating Large-Scale Data Analysis Performance Improvements of Poincaré Analysis for Exascale Fusion Simulations Scaling Ensembles of Data-Intensive Quantum Chemical Calculations for Millions of Molecules Role of turbulent separatrix tangle in the improvement of the integrated pedestal and heat exhaust issue for stationary-operation tokamak fusion reactors Hybrid Approaches for Data Reduction of Spatiotemporal Scientific Applications Fast Algorithms for Scientific Data Compression MGARD: A multigrid framework for high-performance, error-controlled data compression and refactoring Spatiotemporally Adaptive Compression for Scientific Dataset with Feature Preservation – A Case Study on Simulation Data with Extreme Climate Events Analysis Online and Scalable Data Compression Pipeline with Guarantees on Quantities of Interest Driving Next-Generation Workflows from the Data Plane... RAPIDS: Reconciling Availability, Accuracy, and Performance in Managing Geo-Distributed Scientific Data 2022 Review of Data-Driven Plasma Science Improving Progressive Retrieval for HPC Scientific Data using Deep Neural Network An Algorithmic and Software Pipeline for Very Large Scale Scientific Data Compression with Error Guarantees Running Ensemble Workflows at Extreme Scale: Lessons Learned and Path Forward Hybrid Analysis of Fusion Data for Online Understanding of Complex Science on Extreme Scale Computers Region-adaptive, Error-controlled Scientific Data Compression using Multilevel Decomposition Error-Bounded Learned Scientific Data Compression with Preservation of Derived Quantities Understanding the Impact of Data Staging for Coupled Scientific Workflows... A codesign framework for online data analysis and reduction Organizing Large Data Sets for Efficient Analyses on HPC Systems Maintaining Trust in Reduction: Preserving the Accuracy of Quantities of Interest for Lossy Compression Pagination Current page 1 Page 2 Page 3 … Next page ›› Last page Last » Key Links ORCID Google Scholar Publications
