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

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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.description.provenanceMade available in DSpace on 2024-03-07T10:06:59Z (GMT). No. of bitstreams: 1 Visual_analysis_of_large_multi-dield_AMR_data_on_GPUs_using_interactive_volume_lines.pdf: 420292 bytes, checksum: 5c1b13bdce7086ad21f92fc5a927aa8f (MD5) Previous issue date: 2023-12-20en
dc.identifier.doi10.1109/VIS54172.2023.00020
dc.identifier.eisbn979-8-3503-2557-7
dc.identifier.eissn2771-9553
dc.identifier.isbn979-8-3503-2558-4
dc.identifier.issn2771-9537
dc.identifier.urihttps://hdl.handle.net/11693/114383
dc.language.isoen_US
dc.publisherIEEE
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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