Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 16, issue 19
Articles | Volume 16, issue 19
https://doi.org/10.5194/gmd-16-5539-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-16-5539-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 16, issue 19
Development and technical paper
 | 
05 Oct 2023
Development and technical paper |  | 05 Oct 2023

Comparing the Performance of Julia on CPUs versus GPUs and Julia-MPI versus Fortran-MPI: a case study with MPAS-Ocean (Version 7.1)

Siddhartha Bishnu, Robert R. Strauss, and Mark R. Petersen

Viewed

Total article views: 8,125 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
6,842 1,209 74 8,125 95 122
  • HTML: 6,842
  • PDF: 1,209
  • XML: 74
  • Total: 8,125
  • BibTeX: 95
  • EndNote: 122
Views and downloads (calculated since 15 Feb 2023)
Cumulative views and downloads (calculated since 15 Feb 2023)

Viewed (geographical distribution)

Total article views: 8,125 (including HTML, PDF, and XML) Thereof 8,125 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 29 Oct 2025
Download
Short summary
Here we test Julia, a relatively new programming language, which is designed to be simple to write, but also fast on advanced computer architectures. We found that Julia is both convenient and fast, but there is no free lunch. Our first attempt to develop an ocean model in Julia was relatively easy, but the code was slow. After several months of further development, we created a Julia code that is as fast on supercomputers as a Fortran ocean model.
Read more
Share