WebTensor: Towards high-performance raster data analysis in the browser
Autor(en):
Zusammenfassung
We 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.
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- BibTeX
Naumann, L. F.,
(2023).
WebTensor: Towards high-performance raster data analysis in the browser.
In:
König-Ries, B., Scherzinger, S., Lehner, W. & Vossen, G.
(Hrsg.),
BTW 2023.
Gesellschaft für Informatik e.V..
DOI: 10.18420/BTW2023-75
@inproceedings{mci/Naumann2023,
author = {Naumann, Lucas Fabian},
title = {WebTensor: Towards high-performance raster data analysis in the browser},
booktitle = {BTW 2023},
year = {2023},
editor = {König-Ries, Birgitta AND Scherzinger, Stefanie AND Lehner, Wolfgang AND Vossen, Gottfried} ,
doi = { 10.18420/BTW2023-75 },
publisher = {Gesellschaft für Informatik e.V.},
address = {}
}
author = {Naumann, Lucas Fabian},
title = {WebTensor: Towards high-performance raster data analysis in the browser},
booktitle = {BTW 2023},
year = {2023},
editor = {König-Ries, Birgitta AND Scherzinger, Stefanie AND Lehner, Wolfgang AND Vossen, Gottfried} ,
doi = { 10.18420/BTW2023-75 },
publisher = {Gesellschaft für Informatik e.V.},
address = {}
}
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Mehr Information
DOI: 10.18420/BTW2023-75
ISBN: 978-3-88579-725-8
Datum: 2023
Sprache:
(en)
(en)
Typ: Text/Conference Paper

