Dense Texture Flow Visualization using Data-Parallel Primitives

dc.contributor.authorKim, Marken_US
dc.contributor.authorKlasky, Scotten_US
dc.contributor.authorPugmire, Daviden_US
dc.contributor.editorHank Childs and Fernando Cucchiettien_US
dc.date.accessioned2018-06-02T18:02:41Z
dc.date.available2018-06-02T18:02:41Z
dc.date.issued2018
dc.description.abstractRecent trends in supercomputing towards massively threaded on-node processors to increase performance has also introduced fragmented software support. In response to this changing landscape, new scientific visualization packages have been developed to provide a portable framework to exploit this on-node parallelism with data parallel primitives, while also providing a single interface to multiple hardware backends. This necessitates adapting algorithms to the data parallel primitives paradigm. In numerous cases the algorithm is serial, but other times the technique is tied to hardware and needs to be generalized to broadly disseminate. In this work, we present unsteady flow line integral convolution (UFLIC) using only data parallel primitives. Line integral convolution (LIC) is a fundamental flow visualization technique in scientific visualization. LIC and its texture-based variants, are used in fields such as meteorology and computational fluid dynamics to aid practitioners because of its efficient memory usage, strong, visual flow characteristics, and efficient performance. However, in practice performant implementations are GPU shader-based approaches, which limits deployment and adoption. By utilizing VTK-m, our approach is a performant, memory efficient implementation, with the added benefit of portability, with a single implementation across many architectures.en_US
dc.description.sectionheadersSession 3
dc.description.seriesinformationEurographics Symposium on Parallel Graphics and Visualization
dc.identifier.doi10.2312/pgv.20181095
dc.identifier.isbn978-3-03868-054-3
dc.identifier.issn1727-348X
dc.identifier.pages57-61
dc.identifier.urihttps://doi.org/10.2312/pgv.20181095
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/pgv20181095
dc.publisherThe Eurographics Associationen_US
dc.subjectI.3.3 [Computer Graphics]
dc.subjectPicture/Image Generation
dc.subjectLine and curve generation
dc.titleDense Texture Flow Visualization using Data-Parallel Primitivesen_US
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