Articles | Volume 14, issue 7
https://doi.org/10.5194/gmd-14-4241-2021
https://doi.org/10.5194/gmd-14-4241-2021
Development and technical paper
 | 
06 Jul 2021
Development and technical paper |  | 06 Jul 2021

Parallel computing efficiency of SWAN 40.91

Christo Rautenbach, Julia C. Mullarney, and Karin R. Bryan

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Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Christo Rautenbach on behalf of the Authors (07 May 2021)  Author's response   Author's tracked changes   Manuscript 
ED: Referee Nomination & Report Request started (08 May 2021) by Julia Hargreaves
RR by Anonymous Referee #1 (11 May 2021)
RR by Anonymous Referee #2 (12 May 2021)
ED: Publish subject to minor revisions (review by editor) (17 May 2021) by Julia Hargreaves
AR by Christo Rautenbach on behalf of the Authors (18 May 2021)  Author's response   Author's tracked changes   Manuscript 
ED: Publish as is (10 Jun 2021) by Julia Hargreaves
AR by Christo Rautenbach on behalf of the Authors (10 Jun 2021)  Manuscript 
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Short summary
The simulation of ocean waves is important for various reasons, e.g. ship route safety and coastal vulnerability assessments. SWAN is a popular tool with which ocean waves may be predicted. Simulations using this tool can be computationally expensive. The present study thus aimed to understand which typical parallel-computing SWAN model set-up will be most effective. There thus do exist configurations where these simulations are most time-saving and effective.