Academic Journal
Veris: fast & efficient sea-ice modeling in Python with GPU acceleration.
| Title: | Veris: fast & efficient sea-ice modeling in Python with GPU acceleration. |
|---|---|
| Authors: | Gärtner, Jan P., Losch, Martin, Cheedela, Suvarchal K., Jochum, Markus, Nuterman, Roman |
| Source: | Geoscientific Model Development; 2026, Vol. 19 Issue 12, p5225-5236, 12p |
| Subject Terms: | Python programming language, FORTRAN, General circulation model, Software libraries (Computer programming), High performance computing, Atmospheric models |
| Abstract: | Climate models have traditionally been developed in Fortran, due to its long-standing use in scientific computing and its excellent computational performance. While Python offers substantial advantages in terms of code readability, maintainability, and the availability of libraries and tools, the performance gap between Python and Fortran has historically limited Python's use in large-scale climate modeling. This performance gap can be mitigated by using the JAX library, which significantly improves execution speed of Python code. We use JAX as a backend for Veris, a new sea ice model implemented in Python. Veris builds upon the Fortran-based sea ice component of the general circulation model MITgcm. Benchmark experiments show that Veris exhibits scaling behavior with increasing process counts comparable to the Fortran reference implementation. For small CPU process counts, Veris outperforms the MITgcm, showing the great potential that JAX has for climate modeling, particularly as further improvements in inter-process communication are anticipated. When executed on a high-end GPU, a single-process Veris simulation matches the performance of the parallelized Fortran reference running on hundreds of CPU cores, but at a fraction of the energy cost. These results demonstrate the potential of Veris for large-scale HPC-based simulations. [ABSTRACT FROM AUTHOR] |
| Copyright of Geoscientific Model Development is the property of Copernicus Gesellschaft mbH and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Complementary Index |
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| Items | – Name: Title Label: Title Group: Ti Data: Veris: fast & efficient sea-ice modeling in Python with GPU acceleration. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Gärtner%2C+Jan P%2E%22">Gärtner, Jan P.</searchLink><br /><searchLink fieldCode="AR" term="%22Losch%2C+Martin%22">Losch, Martin</searchLink><br /><searchLink fieldCode="AR" term="%22Cheedela%2C+Suvarchal K%2E%22">Cheedela, Suvarchal K.</searchLink><br /><searchLink fieldCode="AR" term="%22Jochum%2C+Markus%22">Jochum, Markus</searchLink><br /><searchLink fieldCode="AR" term="%22Nuterman%2C+Roman%22">Nuterman, Roman</searchLink> – Name: TitleSource Label: Source Group: Src Data: Geoscientific Model Development; 2026, Vol. 19 Issue 12, p5225-5236, 12p – Name: Subject Label: Subject Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Python+programming+language%22">Python programming language</searchLink><br /><searchLink fieldCode="DE" term="%22FORTRAN%22">FORTRAN</searchLink><br /><searchLink fieldCode="DE" term="%22General+circulation+model%22">General circulation model</searchLink><br /><searchLink fieldCode="DE" term="%22Software+libraries+%28Computer+programming%29%22">Software libraries (Computer programming)</searchLink><br /><searchLink fieldCode="DE" term="%22High+performance+computing%22">High performance computing</searchLink><br /><searchLink fieldCode="DE" term="%22Atmospheric+models%22">Atmospheric models</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Climate models have traditionally been developed in Fortran, due to its long-standing use in scientific computing and its excellent computational performance. While Python offers substantial advantages in terms of code readability, maintainability, and the availability of libraries and tools, the performance gap between Python and Fortran has historically limited Python's use in large-scale climate modeling. This performance gap can be mitigated by using the JAX library, which significantly improves execution speed of Python code. We use JAX as a backend for Veris, a new sea ice model implemented in Python. Veris builds upon the Fortran-based sea ice component of the general circulation model MITgcm. Benchmark experiments show that Veris exhibits scaling behavior with increasing process counts comparable to the Fortran reference implementation. For small CPU process counts, Veris outperforms the MITgcm, showing the great potential that JAX has for climate modeling, particularly as further improvements in inter-process communication are anticipated. When executed on a high-end GPU, a single-process Veris simulation matches the performance of the parallelized Fortran reference running on hundreds of CPU cores, but at a fraction of the energy cost. These results demonstrate the potential of Veris for large-scale HPC-based simulations. [ABSTRACT FROM AUTHOR] – Name: Abstract Label: Group: Ab Data: <i>Copyright of Geoscientific Model Development is the property of Copernicus Gesellschaft mbH and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.5194/gmd-19-5225-2026 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 12 StartPage: 5225 Subjects: – SubjectFull: Python programming language Type: general – SubjectFull: FORTRAN Type: general – SubjectFull: General circulation model Type: general – SubjectFull: Software libraries (Computer programming) Type: general – SubjectFull: High performance computing Type: general – SubjectFull: Atmospheric models Type: general Titles: – TitleFull: Veris: fast & efficient sea-ice modeling in Python with GPU acceleration. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Gärtner, Jan P. – PersonEntity: Name: NameFull: Losch, Martin – PersonEntity: Name: NameFull: Cheedela, Suvarchal K. – PersonEntity: Name: NameFull: Jochum, Markus – PersonEntity: Name: NameFull: Nuterman, Roman IsPartOfRelationships: – BibEntity: Dates: – D: 15 M: 06 Text: 2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 1991959X Numbering: – Type: volume Value: 19 – Type: issue Value: 12 Titles: – TitleFull: Geoscientific Model Development Type: main |
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