Visual analysis of large multi-dield AMR data on GPUs using interactive volume lines
buir.contributor.author | Demirci, Serkan | |
buir.contributor.author | Güdükbay, Uğur | |
buir.contributor.orcid | Demirci, Serkan|0000-0001-8805-5310 | |
buir.contributor.orcid | Güdükbay, Uğur|0000-0003-2462-6959 | |
dc.citation.epage | 60 | en_US |
dc.citation.spage | 56 | |
dc.contributor.author | Zellmann, S. | |
dc.contributor.author | Demirci, Serkan | |
dc.contributor.author | Güdükbay, Uğur | |
dc.coverage.spatial | Melbourne, Australia | |
dc.date.accessioned | 2024-03-07T10:06:59Z | |
dc.date.available | 2024-03-07T10:06:59Z | |
dc.date.issued | 2023-12-20 | |
dc.department | Department of Computer Engineering | |
dc.description | Conference Name: 2023 IEEE Visualization and Visual Analytics (VIS) | |
dc.description | Date of Conference: 21-27 October 2023 | |
dc.description.abstract | To 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.provenance | Made 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: 2023-12-20 | en |
dc.identifier.doi | 10.1109/VIS54172.2023.00020 | en_US |
dc.identifier.eisbn | 979-8-3503-2557-7 | en_US |
dc.identifier.eissn | 2771-9553 | en_US |
dc.identifier.isbn | 979-8-3503-2558-4 | en_US |
dc.identifier.issn | 2771-9537 | en_US |
dc.identifier.uri | https://hdl.handle.net/11693/114383 | en_US |
dc.language.iso | English | en_US |
dc.publisher | IEEE | en_US |
dc.relation.isversionof | https://dx.doi.org/10.1109/VIS54172.2023.00020 | |
dc.source.title | 2023 IEEE Visualization and Visual Analytics (VIS) | |
dc.subject | Human-centered computing | |
dc.subject | Visualization | |
dc.subject | Visualization application domain | |
dc.subject | Visual analytics | |
dc.title | Visual analysis of large multi-dield AMR data on GPUs using interactive volume lines | |
dc.type | Conference Paper |
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