Beyond ExaBricks: GPU Volume Path Tracing of AMR Data

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dc.contributor.authorZellmann, Stefanen_US
dc.contributor.authorWu, Qien_US
dc.contributor.authorSahistan, Alperen_US
dc.contributor.authorMa, Kwan-Liuen_US
dc.contributor.authorWald, Ingoen_US
dc.contributor.editorAigner, Wolfgangen_US
dc.contributor.editorArchambault, Danielen_US
dc.contributor.editorBujack, Roxanaen_US
dc.date.accessioned2024-05-21T08:18:46Z
dc.date.available2024-05-21T08:18:46Z
dc.date.issued2024
dc.description.abstractAdaptive Mesh Refinement (AMR) is becoming a prevalent data representation for HPC, and thus also for scientific visualization. AMR data is usually cell centric (which imposes numerous challenges), complex, and generally hard to render. Recent work on GPU-accelerated AMR rendering has made much progress towards real-time volume and isosurface rendering of such data, but so far this work has focused exclusively on ray marching, with simple lighting models and without scattering events or global illumination. True high-quality rendering requires a modified approach that is able to trace arbitrary incoherent paths; but this may not be a perfect fit for the types of data structures recently developed for ray marching. In this paper, we describe a novel approach to high-quality path tracing of complex AMR data, with a specific focus on analyzing and comparing different data structures and algorithms to achieve this goal.en_US
dc.description.number3
dc.description.sectionheadersVolume Rendering and Large Data
dc.description.seriesinformationComputer Graphics Forum
dc.description.volume43
dc.identifier.doi10.1111/cgf.15095
dc.identifier.issn1467-8659
dc.identifier.pages12 pages
dc.identifier.urihttps://doi.org/10.1111/cgf.15095
dc.identifier.urihttps://diglib.eg.org/handle/10.1111/cgf15095
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.titleBeyond ExaBricks: GPU Volume Path Tracing of AMR Dataen_US
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