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Please use this identifier to cite or link to this item: https://hdl.handle.net/11681/40887
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dc.contributor.authorDuque, Earl P. N.en_US
dc.contributor.authorLegensky, Steve M.en_US
dc.contributor.authorWhitlock, Brad J.en_US
dc.contributor.authorRogers, David H.en_US
dc.contributor.authorBauer, Andrew C.en_US
dc.contributor.authorImlay, Scott T.en_US
dc.contributor.authorThompson, Daviden_US
dc.contributor.authorTsutsumi, Seijien_US
dc.creatorInformation Technology Laboratory (U.S.)en_US
dc.creatorIntelligent Light LLCen_US
dc.creatorTecploten_US
dc.creatorKitware, Inc.en_US
dc.creatorLos Alamos National Laboratoryen_US
dc.creatorUchū Kōkū Kenkyū Kaihatsu Kikōen_US
dc.date.accessioned2021-06-08T17:44:05Zen_US
dc.date.available2021-06-08T17:44:05Zen_US
dc.date.issued2021-06en_US
dc.identifier.govdocERDC/ITL MP-21-10en_US
dc.identifier.urihttps://hdl.handle.net/11681/40887en_US
dc.identifier.urihttp://dx.doi.org/10.21079/11681/40887en_US
dc.descriptionMiscellaneous Paperen_US
dc.description.abstractAt the AIAA SciTech 2020 conference, the Meshing, Visualization and Computational Environments Technical Committee hosted a special technical panel on In Situ/In Transit Computational Environments for Visualization and Data Analytics. The panel brought together leading experts from industry, software vendors, Department of Energy, Department of Defense and the Japan Aerospace Exploration Agency (JAXA). In situ and in transit methodologies enable Computational Fluid Dynamic (CFD) simulations to avoid the excessive overhead associated with data I/O at large scales especially as simulations scale to millions of processors. These methods either share the data analysis/visualization pipelines with the memory space of the solver or efficiently off load the workload to alternate processors. Using these methods, simulations can scale and have the promise of enabling the community to satisfy the Knowledge Extraction milestones as envisioned by the CFD Vision 2030 study for "on demand analysis/visualization of a 100 Billion point unsteady CFD simulation". This paper summarizes the presentations providing a discussion point of how the community can achieve the goals set forth in the CFD Vision 2030.en_US
dc.description.sponsorshipUnited States. Army. Corps of Engineersen_US
dc.format.extent39 pages / 13.06 MBen_US
dc.format.mediumPDF/Aen_US
dc.language.isoen_USen_US
dc.publisherEngineer Research and Development Center (U.S.)en_US
dc.relation.ispartofseriesMiscellaneous Paper (Engineer Research and Development Center (U.S.)) ; ERDC/ITL MP-21-10en_US
dc.relation.isversionofDuque, Earl P., Steve M. Legensky, Brad J. Whitlock, David H. Rogers, Andrew C. Bauer, Seiji Tsutsumi, Scott T. Imlay, and David Thompson. "Summary of the SciTech 2020 Technical Panel on In Situ/In Transit Computational Environments for Visualization and Data Analytics." In AIAA Scitech 2021 Forum, p. 1596. 2021. https://doi.org/10.2514/6.2021-1596en_US
dc.rightsApproved for Public Release; Distribution is Unlimiteden_US
dc.sourceThis Digital Resource was created in Microsoft Word and Adobe Acrobaten_US
dc.subjectHigh performance computingen_US
dc.subjectComputer simulationen_US
dc.subjectInformation visualizationen_US
dc.subjectData processingen_US
dc.subjectFluid dynamicsen_US
dc.titleSummary of the SciTech 2020 Technical Panel on In Situ/In Transit Computational Environments for Visualization and Data Analysisen_US
dc.typeReporten_US
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