Visual analysis of large multi-dield AMR data on GPUs using interactive volume lines

buir.contributor.authorDemirci, Serkan
buir.contributor.authorGüdükbay, Uğur
buir.contributor.orcidDemirci, Serkan|0000-0001-8805-5310
buir.contributor.orcidGüdükbay, Uğur|0000-0003-2462-6959
dc.citation.epage60en_US
dc.citation.spage56
dc.contributor.authorZellmann, S.
dc.contributor.authorDemirci, Serkan
dc.contributor.authorGüdükbay, Uğur
dc.coverage.spatialMelbourne, Australia
dc.date.accessioned2024-03-07T10:06:59Z
dc.date.available2024-03-07T10:06:59Z
dc.date.issued2023-12-20
dc.departmentDepartment of Computer Engineering
dc.descriptionConference Name: 2023 IEEE Visualization and Visual Analytics (VIS)
dc.descriptionDate of Conference: 21-27 October 2023
dc.description.abstractTo visually compare ensembles of volumes, dynamic volume lines (DVLs) represent each ensemble member as a 1D polyline. To compute these, the volume cells are sorted on a space-filling curve and scaled by the ensemble’s local variation. The resulting 1D plot can augment or serve as an alternative to a 3D volume visualization free of visual clutter and occlusion. Interactively computing DVLs is challenging when the data is large, and the volume grid is not structured/regular, as is often the case with computational fluid dynamics simulations. We extend DVLs to support large-scale, multifield adaptive mesh refinement (AMR) data that can be explored interactively. Our GPU-based system updates the DVL representation whenever the data or the alpha transfer function changes. We demonstrate and evaluate our interactive prototype using large AMR volumes from astrophysics simulations.
dc.identifier.doi10.1109/VIS54172.2023.00020en_US
dc.identifier.eisbn979-8-3503-2557-7en_US
dc.identifier.eissn2771-9553en_US
dc.identifier.isbn979-8-3503-2558-4en_US
dc.identifier.issn2771-9537en_US
dc.identifier.urihttps://hdl.handle.net/11693/114383en_US
dc.language.isoEnglishen_US
dc.publisherIEEEen_US
dc.relation.isversionofhttps://dx.doi.org/10.1109/VIS54172.2023.00020
dc.source.title2023 IEEE Visualization and Visual Analytics (VIS)
dc.subjectHuman-centered computing
dc.subjectVisualization
dc.subjectVisualization application domain
dc.subjectVisual analytics
dc.titleVisual analysis of large multi-dield AMR data on GPUs using interactive volume lines
dc.typeConference Paper

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