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- 2021MS002717 type Paper assertion.
- 2021MS002717 type Resource assertion.
- 2021MS002717 type MediaObject assertion.
- 2021MS002717 description "Abstract Even to this date, most earth system models are coded in Fortran, especially those used at the largest compute scales. Our ocean model Veros takes a different approach: it is implemented using the high-level programming language Python. Besides numerous usability advantages, this allows us to leverage modern high-performance frameworks that emerged in tandem with the machine learning boom. By interfacing with the JAX library, Veros is able to run high-performance simulations on both central processing units (CPU) and graphical processing unit (GPU) through the same code base, with full support for distributed architectures. On CPU, Veros is able to match the performance of a Fortran reference, both on a single process and on hundreds of CPU cores. On GPU, we find that each device can replace dozens to hundreds of CPU cores, at a fraction of the energy consumption. We demonstrate the viability of using GPUs for earth system modeling by integrating a global 0.1° eddy-resolving setup in single precision, where we achieve 1.3 model years per day on a single compute instance with 16 GPUs, comparable to over 2,000 Fortran processes." assertion.
- 2021MS002717 dateCreated "2022-03-22 10:12:50.513184+00:00" assertion.
- 2021MS002717 name "Fast, Cheap, and Turbulent—Global Ocean Modeling With GPU Acceleration in Python" assertion.
- 2021MS002717 contentUrl "https://agupubs-onlinelibrary-wiley-com.ezproxy.uio.no/doi/10.1029/2021MS002717" assertion.
- 2021MS002717 creator mailto:jean.iaquinta@geo.uio.no assertion.
- 2021MS002717 dateModified "2022-03-22 16:42:57.788902+00:00" assertion.
- 2021MS002717 license no-permission assertion.
- 2021MS002717 sdDatePublished "2022-03-22 10:12:50.513184+00:00" assertion.
- 2021MS002717 doi "10.1029/2021MS002717" assertion.
- 2021MS002717 author mailto:jean.iaquinta@geo.uio.no assertion.