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WebTensor: Towards high-performance raster data analysis in the browser

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dc.contributor.authorNaumann, Lucas Fabian
dc.contributor.editorKönig-Ries, Birgitta
dc.contributor.editorScherzinger, Stefanie
dc.contributor.editorLehner, Wolfgang
dc.contributor.editorVossen, Gottfried
dc.date.accessioned2023-02-23T14:00:21Z
dc.date.available2023-02-23T14:00:21Z
dc.date.issued2023
dc.description.abstractWe present WebTensor, a chunked tensor implementation for WebAssembly (Wasm) compiled from C++ and designed to efficiently analyze raster data directly in the browser. WebTensor allows loading (chunked) data from various backends, manipulating it by aggregations and forwarding computed results in a zero-copy manner to JavaScript so that they can be further processed or visualized. We demonstrate the performance advantages of WebTensor by benchmarking data access and aggregation operations, and compare it against a JavaScript version of Webtensor compiled from the same C++ code.en
dc.identifier.doi10.18420/BTW2023-75
dc.identifier.isbn978-3-88579-725-8
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/40385
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofBTW 2023
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-331
dc.subjectWebAssembly
dc.subjectRaster Data
dc.subjectTensor Processing
dc.subjectVisual Analytics
dc.titleWebTensor: Towards high-performance raster data analysis in the browseren
dc.typeText/Conference Paper
gi.citation.endPage1089
gi.citation.publisherPlaceBonn
gi.citation.startPage1083
gi.conference.date06.-10. März 2023
gi.conference.locationDresden, Germany

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P331 - BTW2023- Datenbanksysteme für Business, Technologie und Web