HyLiPoD: Parallel Particle Advection Via a Hybrid of Lifeline Scheduling and Parallelization-Over-Data

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dc.contributor.authorBinyahib, Robaen_US
dc.contributor.authorPugmire, Daviden_US
dc.contributor.authorChilds, Hanken_US
dc.contributor.editorLarsen, Matthew and Sadlo, Filipen_US
dc.date.accessioned2021-06-12T11:26:06Z
dc.date.available2021-06-12T11:26:06Z
dc.date.issued2021
dc.description.abstractPerformance characteristics of parallel particle advection algorithms can vary greatly based on workload.With this short paper, we build a new algorithm based on results from a previous bake-off study which evaluated the performance of four algorithms on a variety of workloads. Our algorithm, called HyLiPoD, is a ''meta-algorithm,'' i.e., it considers the desired workload to choose from existing algorithms to maximize performance. To demonstrate HyliPoD's benefit, we analyze results from 162 tests including concurrencies of up to 8192 cores, meshes as large as 34 billion cells, and particle counts as large as 300 million. Our findings demonstrate that HyLiPoD's adaptive approach allows it to match the best performance of existing algorithms across diverse workloads.en_US
dc.description.sectionheadersFlow
dc.description.seriesinformationEurographics Symposium on Parallel Graphics and Visualization
dc.identifier.doi10.2312/pgv.20211038
dc.identifier.isbn978-3-03868-138-0
dc.identifier.issn1727-348X
dc.identifier.pages1-5
dc.identifier.urihttps://doi.org/10.2312/pgv.20211038
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/pgv20211038
dc.publisherThe Eurographics Associationen_US
dc.subjectHuman centered computing
dc.subjectScientific visualization
dc.subjectVisualization techniques
dc.titleHyLiPoD: Parallel Particle Advection Via a Hybrid of Lifeline Scheduling and Parallelization-Over-Dataen_US
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EGPGV21: Eurographics Symposium on Parallel Graphics and Visualization