Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 17, issue 6
Articles | Volume 17, issue 6
https://doi.org/10.5194/gmd-17-2427-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-17-2427-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 17, issue 6
Model description paper
 | 
28 Mar 2024
Model description paper |  | 28 Mar 2024

ParticleDA.jl v.1.0: a distributed particle-filtering data assimilation package

Daniel Giles, Matthew M. Graham, Mosè Giordano, Tuomas Koskela, Alexandros Beskos, and Serge Guillas

Viewed

Total article views: 2,060 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
1,489 501 70 2,060 87 57
  • HTML: 1,489
  • PDF: 501
  • XML: 70
  • Total: 2,060
  • BibTeX: 87
  • EndNote: 57
Views and downloads (calculated since 21 Mar 2023)
Cumulative views and downloads (calculated since 21 Mar 2023)

Viewed (geographical distribution)

Total article views: 2,060 (including HTML, PDF, and XML) Thereof 2,012 with geography defined and 48 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 27 Mar 2025
Download
Short summary
Digital twins of physical and human systems informed by real-time data are becoming ubiquitous across a wide range of settings. Progress for researchers is currently limited by a lack of tools to run these models effectively and efficiently. A key challenge is the optimal use of high-performance computing environments. The work presented here focuses on a developed open-source software platform which aims to improve this usage, with an emphasis placed on flexibility, efficiency, and scalability.
Read more
Share