Norbert Podhorszki Distinguished Researcher Scientist Contact 865.574.7159 | PNB@ORNL.GOV All Publications Global Adjoint Tomographt: First-Generation Model Hello ADIOS: the challenges and lessons of developing leadership class I/O frameworks. ... Simulation of Fusion Plasmas: Current Status and Future Directions... Alternative mixed integer linear programming optimization for joint job scheduling and data allocation in grid computing Streaming Data in HPC Workflows Using ADIOS Optimising the Processing and Storage of Visibilities using lossy compression... HPC I/O innovations in the exascale era HPDR: High-Performance Portable Scientific Data Reduction Framework HPC Campaign Management: Remote data access with user-defined error bound using ADIOS and ZFP The Artificial Scientist: in-Transit Machine Learning of Plasma Simulations Understanding and Estimating Error Propagation in Neural Networks for Scientific Data Analysis... A Framework for Compressing Unstructured Scientific Data via Serialization To Derive or Not to Derive: I/O Libraries Take Charge of Derived Quantities Computation Error-controlled Progressive Retrieval of Scientific Data under Derivable Quantities of Interest AI Surrogate Model for Distributed Computing Workloads FunM2C: A Filter for Uncertainty Visualization of Multivariate Data on Multi-Core Devices Towards Resilient Near Real-Time Analysis Workflows in Fusion Energy Science GLAD-M35: a joint P and S global tomographic model with uncertainty quantification Optimizing Metadata Exchange: Leveraging DAOS for ADIOS Metadata I/O 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 Improving Progressive Retrieval for HPC Scientific Data using Deep Neural Network Hybrid Analysis of Fusion Data for Online Understanding of Complex Science on Extreme Scale Computers Understanding the Impact of Data Staging for Coupled Scientific Workflows... Organizing Large Data Sets for Efficient Analyses on HPC Systems Pagination Current page 1 Page 2 Page 3 … Next page ›› Last page Last » Key Links Google Scholar ORCID Organizations Computing and Computational Sciences Directorate Computer Science and Mathematics Division Data and AI Systems Section Workflow Systems Group
