Show simple item record

dc.contributor.authorSchneegans, S.
dc.contributor.authorNeary, L.
dc.contributor.authorFlatken, M.
dc.contributor.authorGerndt, A.
dc.date2017
dc.date.accessioned2018-01-23T09:34:07Z
dc.date.available2018-01-23T09:34:07Z
dc.identifier.urihttps://orfeo.belnet.be/handle/internal/6480
dc.descriptionTechnological advances in high performance computing and maturing physical models allow scientists to simulate weather and climate evolutions with an increasing accuracy. While this improved accuracy allows us to explore complex dynamical interactions within such physical systems, inconceivable a few years ago, it also results in grand challenges regarding the data visualization and analytics process. We present STRIELAD, a scalable weather analytics toolkit, which allows for interactive exploration and real-time visualization of such large scale datasets. It combines parallel and distributed feature extraction using high-performance computing resources with smart level-of-detail rendering methods to assure interactivity during the complete analysis process.
dc.languageeng
dc.titleSTRIELAD - A Scalable Toolkit for Real-time Interactive Exploration of Large Atmospheric Datasets
dc.typeConference
dc.subject.frascatiPhysical sciences
dc.audienceScientific
dc.subject.freeDistributed Systems
dc.subject.freeClient/Server
dc.subject.freeDistributed applications
dc.subject.freeGraphics Systems
dc.subject.freeDistributed/network graphics
dc.subject.freeRemote systems
dc.subject.freeSimulation Output Analysis
dc.subject.freePhysical sciences and engineering
dc.subject.freeEarth and atmospheric sciences
dc.source.titleIEEE Visualization, 1-6 October 2017, Phoenix, AZ, USA
Orfeo.peerreviewedNo


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record