The International Conference for High Performance Computing, Networking, Storage, and Analysis
The International Conference for High Performance Computing, Networking, Storage, and Analysis
Workshop:DRBSD-7: The 7th International Workshop on Data Analysis and Reduction for Big Scientific Data
Authors: Chris Johnson (University of Utah)
Abstract: Time-varying computational field simulations are often prohibitively large and pose challenges for accurate interactive analysis and exploration. In this talk, I will present visual analysis research for large-scale time-varying simulations, including a new deep neural network-based particle tracing method to explore time-varying vector fields represented by Lagrangian flow maps. In situ processing is first utilized to extract Lagrangian flow maps and deep neural networks then use the extracted data to learn flow field behavior. Using a trained model to predict new particle trajectories offers a small, fixed memory footprint that significantly reduces the burden of I/O when reading data for visualization.