Computer Engineering Commons^™

Feature Extraction And Parallel Visualization For Large-Scale Scientific Data, Lina Yu

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

Advanced computing and sensing technologies enable scientists to study natural and physical phenomena with unprecedented precision, resulting in an explosive growth of data. The unprecedented amounts of data generated from large scientific simulations impose a grand challenge in data analytics and visualization due to the fact that data are too massive for transferring, storing, and processing.

This dissertation makes the first contribution to the design of novel transfer functions and application-aware data replacement policy to facilitate feature classification on highly parallel distributed systems. We design novel transfer functions that advance the classification of continuously changed volume data by combining the …