| Registro completo |
| Provedor de dados: |
ArchiMer
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| País: |
France
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| Título: |
The Pangeo Big Data Ecosystem and its use at CNES
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| Autores: |
Eynard-bontemps, Guillaume
Abernathey, Ryan
Hamman, Joseph
Ponte, Aurelien
Rath, Willi
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| Data: |
2019
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| Ano: |
2019
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| Palavras-chave: |
Pangeo
Dask
Jupyter
HPC
Cloud
Big Data
Analysis
Open Source
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| Resumo: |
Pangeo[1] is a community-driven effort for open-source big data initially focused on the Earth System Sciences. One of its primary goals is to enable scientists in analyzing petascale datasets both on classical high-performance computing (HPC) and on public cloud infrastructure. In only a few years, Pangeo has grown into a very productive community collaborating on the development of open-source analysis tools for science. It provides a set of example deployments based on open-source Scientific Python packages like Jupyter[2], Dask[3], and Xarray[4] that bring together scientists and developer with their actual use-cases. In this paper, we first describe Pangeo ecosystem and community. We then present its impact on the work of scientists from CNES on the HPC deployment there. We conclude with a future outlook for Pangeo in this agency and beyond.
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| Tipo: |
Text
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| Idioma: |
Inglês
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| Identificador: |
https://archimer.ifremer.fr/doc/00503/61441/65160.pdf
https://archimer.ifremer.fr/doc/00503/61441/
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| Editor: |
P. Soille, S. Loekken, and S. Albani (Eds.) Proc. of the 2019 conference on Big Data from Space (BiDS’2019), EUR 29660 EN, Publications Office of the European Union, Luxembourg, 2019, ISBN 978-92-76-00034-1 , doi:10.2760/848593, 2019. Part. Interactive Processing and Visualisation, pp.49-52
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| Formato: |
application/pdf
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| Direitos: |
info:eu-repo/semantics/openAccess
restricted use
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