Dave Pugmire Contact PUGMIRE@ORNL.GOV All Publications Performance-Portable Particle Advection with VTK-m In Situ Visualization of Radiation Transport Geometry... Canopus: A Paradigm Shift Towards Elastic Extreme-Scale Data Analytics on HPC Canopus: Enabling Extreme-Scale Data Analytics on Big {HPC} Storage via Progressive Refactoring Exacution: Enhancing Scientific Data Management for Exascale Global adjoint tomography: first-generation model Global Adjoint Tomographt: First-Generation Model Preparing for In Situ Processing on Upcoming Leading-edge Supercomputers Visualization and Analysis Requirements for In Situ Processing for a Large-Scale Fusion Simulation Code Performance Modeling of In Situ Rendering Visualization and Analysis for Near-Real-Time Decision Making in Distributed Workflows Loosely Coupled In Situ Visualization: A Perspective on Why It's Here to Stay Visualizing the Radiation of the Kelvin-Helmholtz Instability A Data Centric View of Large-Scale Seismic Imaging Workflows... A Data Centric View of Large-Scale Seismic Imaging Workflows A Parallel EM Algorithm for Model-Based Clustering Applied to the Exploration of Large Spatio-Temporal Data ADIOS Visualization Schema: A First Step towards Improving Interdisciplinary Collaboration in High Performance Computing The Ultra-scale Visualization Climate Data Analysis Tools (UV-CDAT): Data Analysis and Visualization for Geoscience Data Exploring Collaborative HPC Visualization Workflows using VisIt and Python... GPU Acceleration of Particle Advection Workloads in a Parallel, Distributed Memory Setting The Ultra-scale Visualization Climate Data Analysis Tools (UV-CDAT): Data Analysis and Visualization for Geoscience Data... VisIt: An End-User Tool for Visualizing and Analyzing Very Large Data Visualization at Extreme-Scale Concurrency... Parallel Stream Surface Computation for Large Data Sets Mining Hidden Mixture Context with ADIOS-P to Improve Predictive Pre-fetcher Accuracy Pagination First page « First Previous page ‹‹ … Page 2 Current page 3 Page 4 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 Visualization Group
Research Highlight Accelerated Probabilistic Marching Cubes by Deep Learning for Time-Varying Scalar Ensembles
Research Highlight Fiber Uncertainty Visualization for Bivariate Data With Parametric and Nonparametric Noise Models
