Roche, AntoineDubois, JérômeByška, Jan and Jänicke, Stefan2020-05-242020-05-242020978-3-03868-105-2https://doi.org/10.2312/eurp.20201115https://diglib.eg.org:443/handle/10.2312/eurp20201115Adaptive Mesh Refinement (AMR) methods are common in scientific workloads, and very useful during analyses and visualization. In this work, we aim to reduce memory and storage footprint of AMR data. We adapt tree compression (SVDAG) and GPU Ray Cast rendering, created for Computer Graphics surface scenes, for volume data from Scientific Visualization workloads. In particular, experiments have been conducted with the native Tree-Based AMR (TB-AMR) data structure in the Visualization ToolKit (VTK): vtkHyperTreeGrid (HTG). A HTG to SVDAG online converter has been implemented as well as a multi-SVDAG extension. Results showed several orders of magnitude memory footprint reduction thanks to the compression and efficient Ray Cast rendering. Furthermore, serialization to SVDAG enabled almost instant loading and display of simulation data instead of minutes. Overall our experiments show great benefits, and this shows great promises to further improve TB-AMR analyses.Attribution 4.0 International LicenseGeneral and referenceDesignPerformanceEvaluationHuman centered computingVisualizationSoftware and its engineeringDesigning softwareInformation systemsData compression10.2312/eurp.202011155-7