Design and Evaluation of a GPU Streaming Framework for Visualizing Time-Varying AMR Data

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dc.contributor.authorZellmann, Stefanen_US
dc.contributor.authorWald, Ingoen_US
dc.contributor.authorSahistan, Alperen_US
dc.contributor.authorHellmann, Matthiasen_US
dc.contributor.authorUsher, Willen_US
dc.contributor.editorBujack, Roxanaen_US
dc.contributor.editorTierny, Julienen_US
dc.contributor.editorSadlo, Filipen_US
dc.date.accessioned2022-06-02T14:36:53Z
dc.date.available2022-06-02T14:36:53Z
dc.date.issued2022
dc.description.abstractWe describe a systematic approach for rendering time-varying simulation data produced by exa-scale simulations, using GPU workstations. The data sets we focus on use adaptive mesh refinement (AMR) to overcome memory bandwidth limitations by representing interesting regions in space with high detail. Particularly, our focus is on data sets where the AMR hierarchy is fixed and does not change over time. Our study is motivated by the NASA Exajet, a large computational fluid dynamics simulation of a civilian cargo aircraft that consists of 423 simulation time steps, each storing 2.5 GB of data per scalar field, amounting to a total of 4 TB. We present strategies for rendering this time series data set with smooth animation and at interactive rates using current generation GPUs. We start with an unoptimized baseline and step by step extend that to support fast streaming updates. Our approach demonstrates how to push current visualization workstations and modern visualization APIs to their limits to achieve interactive visualization of exa-scale time series data sets.en_US
dc.description.sectionheadersGPU Based Visualization
dc.description.seriesinformationEurographics Symposium on Parallel Graphics and Visualization
dc.identifier.doi10.2312/pgv.20221066
dc.identifier.isbn978-3-03868-175-5
dc.identifier.issn1727-348X
dc.identifier.pages61-71
dc.identifier.pages11 pages
dc.identifier.urihttps://doi.org/10.2312/pgv.20221066
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/pgv20221066
dc.publisherThe Eurographics Associationen_US
dc.rightsAttribution 4.0 International License
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.titleDesign and Evaluation of a GPU Streaming Framework for Visualizing Time-Varying AMR Dataen_US
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EGPGV22: Eurographics Symposium on Parallel Graphics and Visualization