Oceananigans.jl

Fast and friendly fluid dynamics on CPUs and GPUs.
https://github.com/clima/oceananigans.jl

Category: Hydrosphere
Sub Category: Ocean Models

Keywords

climate climate-change data-assimilation fluid-dynamics gpu julia machine-learning ocean

Keywords from Contributors

ocean-modelling ode oceanography sciml differential-equations numerical partial-differential-equations pde neural-ode ocean-sciences

Last synced: about 11 hours ago
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Repository metadata

🌊 Julia software for fast, friendly, flexible, ocean-flavored fluid dynamics on CPUs and GPUs

Host: GitHub
URL: https://github.com/clima/oceananigans.jl
Owner: CliMA
License: mit
Created: 2018-10-13T14:15:44.000Z (over 6 years ago)
Default Branch: main
Last Pushed: 2025-04-21T18:51:16.000Z (5 days ago)
Last Synced: 2025-04-21T19:46:43.362Z (5 days ago)
Topics: climate, climate-change, data-assimilation, fluid-dynamics, gpu, julia, machine-learning, ocean
Language: Julia
Homepage: https://clima.github.io/OceananigansDocumentation/stable
Size: 47.3 MB
Stars: 1,110
Watchers: 31
Forks: 230
Open Issues: 321
Releases: 318
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Citation: CITATION.cff

Oceananigans is a fast, friendly, flexible software package for finite volume simulations of the nonhydrostatic
and hydrostatic Boussinesq equations on CPUs and GPUs.
It runs on GPUs (wow, fast!), though we believe Oceananigans makes the biggest waves
with its ultra-flexible user interface that makes simple simulations easy, and complex, creative simulations possible.

Oceananigans.jl is developed by the Climate Modeling Alliance and heroic external collaborators.

Contents
Installation instructions
Running your first model
The Oceananigans knowledge base
Citing and otherwise spreading the word
Contributing
Movies
Performance benchmarks

Installation instructions

Oceananigans is a registered Julia package. So to install it,

Download Julia (version 1.9 or later).
Launch Julia and type

julia> using Pkg

julia> Pkg.add("Oceananigans")

This installs the latest version that's compatible with your current environment.
Don't forget to be careful 🏄 and check which Oceananigans you installed:

julia> Pkg.status("Oceananigans")

Running your first model

Let's run a two-dimensional, horizontally-periodic simulation of turbulence using 128² finite volume cells for 4 non-dimensional time units:

using Oceananigans
grid = RectilinearGrid(CPU(), size=(128, 128), x=(0, 2π), y=(0, 2π), topology=(Periodic, Periodic, Flat))
model = NonhydrostaticModel(; grid, advection=WENO())
ϵ(x, y) = 2rand() - 1
set!(model, u=ϵ, v=ϵ)
simulation = Simulation(model; Δt=0.01, stop_time=4)
run!(simulation)

But there's more: changing CPU() to GPU() makes this code run on a CUDA-enabled Nvidia GPU.

Dive into the documentation for more code examples and tutorials.
Below, you'll find movies from GPU simulations along with CPU and GPU performance benchmarks.

The Oceananigans knowledge base

It's deep and includes:

Documentation that provides
- example Oceananigans scripts,
- tutorials that describe key Oceananigans objects and functions,
- explanations of Oceananigans finite-volume-based numerical methods,
- details of the dynamical equations solved by Oceananigans models, and
- a library documenting all user-facing Oceananigans objects and functions.
Discussions on the Oceananigans github, covering topics like
- "Computational science", or how to science and set up numerical simulations in Oceananigans, and
- "Experimental features", which covers new and sparsely-documented features for those who like to live dangerously.
If you've got a question or something, anything! to talk about, don't hesitate to start a new discussion.
The Oceananigans wiki contains practical tips for getting started with Julia, accessing and using GPUs, and productive workflows when using Oceananigans.
The #oceananigans channel on the Julia Slack, which accesses "institutional knowledge" stored in the minds of the amazing Oceananigans community.
Issues and pull requests also contain lots of information about problems we've found, solutions we're trying to implement, and dreams we're dreaming to make tomorrow better 🌈.

Citing and otherwise spreading the word

If you use Oceananigans for your research, teaching, or fun 🤩, everyone in our community will be grateful
if you credit Oceananigans by name.

The community has published a number of articles describing the development of Oceananigans,
including a recent preprint submitted to the Journal of Advances in Modeling Earth Systems that presents an overview of all the things that make Oceananigans unique:

"High-level, high-resolution ocean modeling at all scales with Oceananigans"

by Gregory L. Wagner, Simone Silvestri, Navid C. Constantinou, Ali Ramadhan, Jean-Michel Campin,
Chris Hill, Tomas Chor, Jago Strong-Wright, Xin Kai Lee, Francis Poulin, Andre Souza, Keaton J. Burns,
John Marshall, Raffaele Ferrari

submitted to the Journal of Advances in Modeling Earth Systems, arXiv 2502.14148

Please cite this 👆 overview paper if you use Oceananigans in published work.

We've also published/submitted several model development papers. Please cite these below 👇 if you use
the features they describe! Also, if you have developed a new feature in Oceananigans and describe it in a paper, make sure to open a pull request to add it to this list:

Silvestri et al., "A New WENO-Based Momentum Advection Scheme for Simulations of Ocean Mesoscale Turbulence".

This paper describes the development of WENOVectorInvariant() advection scheme, which can be used as the
momentum_advection scheme for HydrostaticFreeSurfaceModel.
Silvestri et al., "A GPU-based ocean dynamic core for routine mesoscale-resolving climate simulations".

This paper describes the optimization of the HydrostaticFreeSurfaceModel algorithm, including the implementation
of a new SplitExplicitFreeSurface algorithm for Distributed architectures for multiple GPUs. As a result of this work,
global simulations with O(10 km) grid spacing can be run on 16-20 nodes, achieving 10 simulated years per day (SYPD).
Wagner et al., "Formulation and calibration of CATKE, a one-equation parameterization for microscale ocean mixing".

This paper describes the development of CATKEVerticalDiffusivity(), including how it was calibrated automatically to
a suite of 35 large eddy simulations (also run with Oceananigans). It additionally features solutions from TKEDissipationVerticalDiffusivity (also known as "k-epsilon").
Ramadhan et al., "Oceananigans.jl: Fast and friendly geophysical fluid dynamics on GPUs".

This article in the Journal of Open Source Software describes an early version of Oceananigans' NonhydrostaticModel.

We also maintain a list of publications using Oceananigans.jl.
If you have work using Oceananigans that you would like to have listed there, please open a pull request to add it or let us know!

Contributing

If you're interested in contributing to the development of Oceananigans we want your help no matter how big or small a contribution you make!
Cause we're all in this together.

If you'd like to work on a new feature, or if you're new to open source and want to crowd-source neat projects that fit your interests, you should start a discussion right away.

For more information check out our contributor's guide.

Movies

Deep convection

Free convection

Winds blowing over the ocean

Free convection with wind stress

Performance benchmarks

We perform some performance benchmarks (see the performance benchmarks section of the documentation) by initializing models of various sizes and measuring the wall clock time taken per model iteration (or time step).

To make full use of or fully saturate the computing power of a GPU such as an Nvidia Tesla V100 or
a Titan V, the model should have around ~10 million grid points or more.

Sometimes counter-intuitively running with Float32 is slower than Float64. This is likely due
to type mismatches causing slowdowns as floats have to be converted between 32-bit and 64-bit, an
issue that needs to be addressed meticulously. Due to other bottlenecks such as memory accesses and
GPU register pressure, Float32 models may not provide much of a speedup so the main benefit becomes
lower memory costs (by around a factor of 2).

Performance benchmark plots

Citation (CITATION.cff)

cff-version: 1.2.0
preferred-citation:
  type: article
  authors:
  - family-names: "Ramadhan"
    given-names: "Ali"
    orcid: "https://orcid.org/0000-0003-1102-1520"
  - family-names: "Wagner"
    given-names: "Gregory LeClaire"
    orcid: "https://orcid.org/0000-0001-5317-2445"
  - family-names: "Hill"
    given-names: "Chris"
  - family-names: "Jean-Michel"
    given-names: "Campin"
  - family-names: "Churavy"
    given-names: "Valentin"
    orcid: "https://orcid.org/0000-0002-9033-165X"
  - family-names: "Souza"
    given-names: "Andre"
  - family-names: "Edelman"
    given-names: "Adam"
    orcid: "https://orcid.org/0000-0002-9033-165X"
  - family-names: "Ferrari"
    given-names: "Raffaele"
    orcid: "https://orcid.org/0000-0003-1895-4294"
  - family-names: "Marshall"
    given-names: "John"
  title: "Oceananigans.jl: Fast and friendly geophysical fluid dynamics on GPUs"
  journal: "Journal of Open Source Software"
  doi: "10.21105/joss.02018"
  volume: 5
  issue: 53
  start: 2018
  year: 2020

Owner metadata

Name: Climate Modeling Alliance
Login: CliMA
Email: [email protected]
Kind: organization
Description: An alliance of scientists, engineers and applied mathematicians, dedicated to pioneering a new, data-informed approach to climate modeling
Website: https://clima.caltech.edu
Location:
Twitter:
Company:
Icon url: https://avatars.githubusercontent.com/u/43161188?v=4
Repositories: 67
Last ynced at: 2023-03-03T21:04:27.588Z
Profile URL: https://github.com/CliMA

GitHub Events

Total

Fork event: 42
Create event: 468
Commit comment event: 146
Release event: 55
Issues event: 193
Watch event: 169
Delete event: 588
Member event: 7
Issue comment event: 2290
Push event: 3767
Pull request review event: 1377
Pull request review comment event: 1086
Pull request event: 750

Last Year

Fork event: 42
Create event: 468
Commit comment event: 146
Release event: 55
Issues event: 193
Watch event: 169
Delete event: 588
Member event: 7
Issue comment event: 2290
Push event: 3767
Pull request review event: 1377
Pull request review comment event: 1086
Pull request event: 750

Committers metadata

Last synced: 3 days ago

Total Commits: 10,950
Total Committers: 76
Avg Commits per committer: 144.079
Development Distribution Score (DDS): 0.682

Commits in past year: 454
Committers in past year: 25
Avg Commits per committer in past year: 18.16
Development Distribution Score (DDS) in past year: 0.551

Name	Email	Commits
ali-ramadhan	a**n@g**m	3487
Gregory Wagner	w**g@g**m	2500
Simone Silvestri	s**0@g**m	1830
Navid C. Constantinou	n****y	1715
tomchor	t**r@g**m	606
francispoulin	f**n@u**a	267
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sandreza	a**a@g**m	73
suyashbire1	s**9@g**m	45
hennyg888	h**2@h**m	38
Victoria Whitley	w**v@a**t	37
Jago Strong-Wright	j**w@p**m	33
christophernhill	c**h@m**u	29
github-actions[bot]	4****]	25
William Moses	gh@w****m	18
Valentin Churavy	v**y@g**m	13
Jean-Michel Campin	j**c@m**u	13
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Simone Silvestri	s**i@d**u	9
Alex Cavaliere	a**e@s**m	5
Avik Pal	a**l@m**u	5
Gabriele Bozzola	g**a@c**u	5
iury simoes-sousa	i**t@p**e	5
Kamontat Chantrachirathumrong	g**b@k**t	4
Alexis Montoison	3****n	4
Keaton J. Burns	k**s@g**m	4
Sid	s**u@g**m	4
Tim Besard	t**d@g**m	4
Xin Kai Lee	5****i	4
and 46 more...

Committer domains:

Issue and Pull Request metadata

Last synced: 1 day ago

Total issues: 1,684
Total pull requests: 2,667
Average time to close issues: 6 months
Average time to close pull requests: 24 days
Total issue authors: 114
Total pull request authors: 73
Average comments per issue: 5.21
Average comments per pull request: 4.28
Merged pull request: 2,094
Bot issues: 0
Bot pull requests: 99

Past year issues: 283
Past year pull requests: 711
Past year average time to close issues: 20 days
Past year average time to close pull requests: 11 days
Past year issue authors: 43
Past year pull request authors: 29
Past year average comments per issue: 5.7
Past year average comments per pull request: 3.4
Past year merged pull request: 486
Past year bot issues: 0
Past year bot pull requests: 21

More stats: https://issues.ecosyste.ms/repositories/lookup?url=https://github.com/clima/oceananigans.jl

Top Issue Authors

glwagner (455)
ali-ramadhan (447)
navidcy (224)
tomchor (145)
francispoulin (72)
simone-silvestri (63)
jagoosw (23)
iuryt (13)
xkykai (10)
Sumanshekhar17 (8)
liuchihl (8)
suyashbire1 (8)
mukund-gupta (8)
sandreza (7)
NoraLoose (7)

Top Pull Request Authors

glwagner (841)
navidcy (470)
ali-ramadhan (429)
simone-silvestri (321)
tomchor (157)
github-actions[bot] (92)
francispoulin (51)
jagoosw (45)
wsmoses (21)
siddharthabishnu (19)
christophernhill (16)
xkykai (11)
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output 💾 (66)
science 🌊 (60)
package 📦 (53)
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good first issue 🐤 (41)
help wanted 🦮 (39)
distributed 🕸️ (26)
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🚨 high priority 🚨 (18)
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science 🌊 (51)
grids 🗺️ (45)
output 💾 (42)
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extensions 🧬 (38)
distributed 🕸️ (30)
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Package metadata

Total packages: 1
Total downloads:
- julia: 2,022 total
Total dependent packages: 9
Total dependent repositories: 0
Total versions: 313

juliahub.com: Oceananigans

🌊 Julia software for fast, friendly, flexible, ocean-flavored fluid dynamics on CPUs and GPUs

Homepage: https://clima.github.io/OceananigansDocumentation/stable
Documentation: https://docs.juliahub.com/General/Oceananigans/stable/
Licenses: MIT
Latest release: 0.96.21 (published 26 days ago)
Last Synced: 2025-04-25T14:39:17.905Z (1 day ago)
Versions: 313
Dependent Packages: 9
Dependent Repositories: 0
Downloads: 2,022 Total
Rankings:
- Stargazers count: 0.386%
- Forks count: 0.421%
- Average: 5.957%
- Dependent repos count: 6.056%
- Dependent packages count: 16.965%

Dependencies

.github/workflows/CompatHelper.yml actions

julia-actions/setup-julia v1 composite

.github/workflows/TagBot.yml actions

JuliaRegistries/TagBot v1 composite

Dockerfile docker

julia 1.9.3 build

Score: 19.213145681423168

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