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dc.contributor.authorPugmire, Daviden_US
dc.contributor.authorYenpure, Abhisheken_US
dc.contributor.authorKim, Marken_US
dc.contributor.authorKress, Jamesen_US
dc.contributor.authorMaynard, Roberten_US
dc.contributor.authorChilds, Hanken_US
dc.contributor.authorHentschel, Bernden_US
dc.contributor.editorHank Childs and Fernando Cucchiettien_US
dc.date.accessioned2018-06-02T18:02:40Z
dc.date.available2018-06-02T18:02:40Z
dc.date.issued2018
dc.identifier.isbn978-3-03868-054-3
dc.identifier.issn1727-348X
dc.identifier.urihttp://dx.doi.org/10.2312/pgv.20181094
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/pgv20181094
dc.description.abstractParticle advection is the fundamental kernel behind most vector field visualization methods. Yet, the efficient parallel computation of large amounts of particle traces remains challenging. This is exacerbated by the variety of hardware trends in today's HPC arena, including increasing core counts in classical CPUs, many-core designs such as the Intel Xeon Phi, and massively parallel GPUs. The dedicated optimization of a particle advection kernel for each individual target architecture is both time-consuming and error prone. In this paper, we propose a performance-portable algorithm for particle advection. Our algorithm is based on the recently introduced VTK-m system and chiefly relies on its device adapter abstraction. We demonstrate the general portability of our implementation across a wide variety of hardware. Finally, our evaluation shows that our hardware-agnostic algorithm has comparable performance to hardware-specific algorithms.en_US
dc.publisherThe Eurographics Associationen_US
dc.titlePerformance-Portable Particle Advection with VTK-men_US
dc.description.seriesinformationEurographics Symposium on Parallel Graphics and Visualization
dc.description.sectionheadersSession 3
dc.identifier.doi10.2312/pgv.20181094
dc.identifier.pages45-55


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