A Study of Ray Tracing Large-scale Scientific Data in Two Widely Used Parallel Visualization Applications

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dc.contributor.authorBrownlee, Carsonen_US
dc.contributor.authorPatchett, Johnen_US
dc.contributor.authorLo, Li-Taen_US
dc.contributor.authorDeMarle, Daviden_US
dc.contributor.authorMitchell, Christopheren_US
dc.contributor.authorAhrens, Jamesen_US
dc.contributor.authorHansen, Charles D.en_US
dc.contributor.editorHank Childs and Torsten Kuhlen and Fabio Martonen_US
dc.date.accessioned2013-11-08T10:25:56Z
dc.date.available2013-11-08T10:25:56Z
dc.date.issued2012en_US
dc.description.abstractLarge-scale analysis and visualization is becoming increasingly important as supercomputers and their simulations produce larger and larger data. These large data sizes are pushing the limits of traditional rendering algorithms and tools thus motivating a study exploring these limits and their possible resolutions through alternative rendering algorithms . In order to better understand real-world performance with large data, this paper presents a detailed timing study on a large cluster with the widely used visualization tools ParaView and VisIt. The software ray tracer Manta was integrated into these programs in order to show that improved performance could be attained with software ray tracing on a distributed memory, GPU enabled, parallel visualization resource. Using the Texas Advanced Computing Center's Longhorn cluster which has multi-core CPUs and GPUs with large-scale polygonal data, we find multi-core CPU ray tracing to be significantly faster than both software rasterization and hardware-accelerated rasterization in existing scientific visualization tools with large data.en_US
dc.description.seriesinformationEurographics Symposium on Parallel Graphics and Visualizationen_US
dc.identifier.isbn978-3-905674-35-4en_US
dc.identifier.issn1727-348Xen_US
dc.identifier.urihttps://doi.org/10.2312/EGPGV/EGPGV12/051-060en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectCategories and Subject Descriptors (according to ACM CCS): I.3.1 [Computer Graphics]: Graphics Systems- Distributed/network graphicsen_US
dc.titleA Study of Ray Tracing Large-scale Scientific Data in Two Widely Used Parallel Visualization Applicationsen_US
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EGPGV12: Eurographics Symposium on Parallel Graphics and Visualization