Interactive Selection on Calculated Attributes of Large-Scale Particle Data

dc.contributor.authorWollet, Benjaminen_US
dc.contributor.authorReinhardt, Stefanen_US
dc.contributor.authorWeiskopf, Danielen_US
dc.contributor.authorEberhardt, Bernharden_US
dc.contributor.editorLarsen, Matthew and Sadlo, Filipen_US
dc.date.accessioned2021-06-12T11:26:11Z
dc.date.available2021-06-12T11:26:11Z
dc.date.issued2021
dc.description.abstractWe present a GPU-based technique for efficient selection in interactive visualizations of large particle datasets. In particular, we address multiple attributes attached to particles, such as pressure, density, or surface tension. Unfortunately, such intermediate attributes are often available only during the simulation run. They are either not accessible during visualization or have to be saved as additional information along with the usual simulation data. The latter increases the size of the dataset significantly, and the required variables may not be known in advance. Therefore, we choose to compute intermediate attributes on the fly. In this way, we are even able to obtain attributes that were not calculated by the simulation but may be relevant for data analysis or debugging. We present an interactive selection technique designed for such attributes. It leverages spatial regions of the selection to efficiently compute attributes only where needed. This lazy evaluation also works for intelligent and data-driven selection, extending the region to include neighboring particles. Our technique is evaluated by measurements of performance scalability and case studies for typical usage examples.en_US
dc.description.sectionheadersParticles
dc.description.seriesinformationEurographics Symposium on Parallel Graphics and Visualization
dc.identifier.doi10.2312/pgv.20211045
dc.identifier.isbn978-3-03868-138-0
dc.identifier.issn1727-348X
dc.identifier.pages63-73
dc.identifier.urihttps://doi.org/10.2312/pgv.20211045
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/pgv20211045
dc.publisherThe Eurographics Associationen_US
dc.subjectComputing methodologies
dc.subjectVisual analytics
dc.subjectHuman centered computing
dc.subjectVisualization design and evaluation methods
dc.subjectVisual analytics
dc.titleInteractive Selection on Calculated Attributes of Large-Scale Particle Dataen_US
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