Journal metrics

Journal metrics

  • IF value: 4.252 IF 4.252
  • IF 5-year value: 4.890 IF 5-year 4.890
  • CiteScore value: 4.49 CiteScore 4.49
  • SNIP value: 1.539 SNIP 1.539
  • SJR value: 2.404 SJR 2.404
  • IPP value: 4.28 IPP 4.28
  • h5-index value: 40 h5-index 40
  • Scimago H index value: 51 Scimago H index 51
Discussion papers | Copyright
https://doi.org/10.5194/gmd-2017-270
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.

Model evaluation paper 15 Dec 2017

Model evaluation paper | 15 Dec 2017

Review status
This discussion paper is a preprint. It has been under review for the journal Geoscientific Model Development (GMD). The revised manuscript was not accepted.

Performance evaluation of ROMS v3.6 on a commercial cloud system

Kwangwoog Jung1, Yang-Ki Cho2, and Yong-Jin Tak2 Kwangwoog Jung et al.
  • 1School of Earth and Environmental Science, Seoul National University, Seoul, Korea
  • 2School of Earth and Environmental Science/Research Institute of Oceanography, Seoul National University, Seoul, Korea

Abstract. Many commercial cloud computing companies provide technologies such as high-performance instances, enhanced networking and remote direct memory access to aid in High Performance Computing (HPC). These new features enable us to explore the feasibility of ocean modelling in commercial cloud computing. Many scientists and engineers expect that cloud computing will become mainstream in the near future. Thus, evaluation of the exact performance and features of commercial cloud services for numerical modelling is appropriate. In this study, the performance of the Regional Ocean Modelling System (ROMS) and the High Performance Linpack (HPL) benchmarking software package was evaluated on Amazon Web Services (AWS) for various configurations. Through comparison of actual performance data and configuration settings obtained from AWS and laboratory HPC, we conclude that cloud computing is a powerful Information Technology (IT) infrastructure for running and operating numerical ocean modelling with minimal effort. Thus, cloud computing can be a useful tool for ocean scientists that have no available computing resource.

Download & links
Kwangwoog Jung et al.
Interactive discussion
Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement
Interactive discussion
Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement
Kwangwoog Jung et al.
Kwangwoog Jung et al.
Viewed
Total article views: 599 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
419 154 26 599 7 25
  • HTML: 419
  • PDF: 154
  • XML: 26
  • Total: 599
  • BibTeX: 7
  • EndNote: 25
Views and downloads (calculated since 15 Dec 2017)
Cumulative views and downloads (calculated since 15 Dec 2017)
Viewed (geographical distribution)
Total article views: 616 (including HTML, PDF, and XML) Thereof 615 with geography defined and 1 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Cited
Saved
No saved metrics found.
Discussed
No discussed metrics found.
Latest update: 20 Sep 2018
Publications Copernicus
Download
Short summary
The performance of the ROMS was evaluated on Amazon Web Services for various configurations. Our study shows how numerical ocean models can be constructed and parallelised in a commercial cloud computing environment and outlines how performance similar to local high-performance computing can be achieved in commercial cloud computing environments by optimising the modelling environment. Cloud computing can be a useful tool for those who have no available computing resource.
The performance of the ROMS was evaluated on Amazon Web Services for various configurations. Our...
Citation
Share