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dc.contributor.advisor
dc.contributor.authorMeca, Ondřej
dc.contributor.authorŘíha, Lubomír
dc.contributor.authorJansík, Branislav
dc.contributor.authorBrzobohatý, Tomáš
dc.date.accessioned2022-04-05T11:57:02Z
dc.date.available2022-04-05T11:57:02Z
dc.date.issued2022
dc.identifier.citationAdvances in Engineering Software. 2022, vol. 166, art. no. 103100.cs
dc.identifier.issn0965-9978
dc.identifier.issn1873-5339
dc.identifier.urihttp://hdl.handle.net/10084/145996
dc.description.abstractThis paper presents an algorithm for highly-parallel loading and processing of unstructured mesh databases in a dis tributed memory environment of large HPC clusters without collecting data into a single process. The algorithm is proved effective, having linear speedup in the large dataset limit. Demonstrated on Ansys CDB, EnSight, VTK Legacy, and XDMF databases, we show that it is possible to efficiently reconstruct meshes with 800 million nodes and 500 million elements in several seconds on thousands of processors, even from databases that were not designed to be read in parallel. The algorithm is implemented in our MESIO library that can be used as (i) an efficient parallel loader (e.g. for numerical physical solvers) or as (ii) a high performing parallel converter between mesh databases.cs
dc.language.isoencs
dc.publisherElseviercs
dc.relation.ispartofseriesAdvances in Engineering Softwarecs
dc.relation.urihttps://doi.org/10.1016/j.advengsoft.2022.103100cs
dc.rights© 2022 Elsevier Ltd. All rights reserved.cs
dc.subjectunstructured meshcs
dc.subjectparallel loadercs
dc.subjectformat convertercs
dc.subjectdomain decompositioncs
dc.titleToward highly parallel loading of unstructured meshescs
dc.typearticlecs
dc.identifier.doi10.1016/j.advengsoft.2022.103100
dc.type.statusPeer-reviewedcs
dc.description.sourceWeb of Sciencecs
dc.description.volume166cs
dc.description.firstpageart. no. 103100cs
dc.identifier.wos000774225000004


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