├── LICENSE
└── README.md


/LICENSE:
--------------------------------------------------------------------------------
 1 | MIT License
 2 | 
 3 | Copyright (c) 2021 VulcanClimateModeling
 4 | 
 5 | Permission is hereby granted, free of charge, to any person obtaining a copy
 6 | of this software and associated documentation files (the "Software"), to deal
 7 | in the Software without restriction, including without limitation the rights
 8 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
 9 | copies of the Software, and to permit persons to whom the Software is
10 | furnished to do so, subject to the following conditions:
11 | 
12 | The above copyright notice and this permission notice shall be included in all
13 | copies or substantial portions of the Software.
14 | 
15 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
16 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
17 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
18 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
19 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
20 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
21 | SOFTWARE.
22 | 


--------------------------------------------------------------------------------
/README.md:
--------------------------------------------------------------------------------
 1 | # Ai2 Climate Modeling Repostories
 2 | 
 3 | Our work is spread across a few key open-source, open-development repositories. These are roughly divided in to Applications and Libraries.
 4 | 
 5 | ## Applications
 6 | 
 7 | The domain specific language (DSL) and machine learning (ML) teams are each producing two top-level applications. DSL is creating a *faster* climate model, and ML is creating a *better* one:
 8 | 
 9 | - (better) https://github.com/ai2cm/fv3net. A machine-learning capable climate model, machine learning training schemes, and diagnostics. This repository uses a monorepo style to suit the ML team's highly coordinated development approach.
10 | - (faster) https://github.com/ai2cm/pace. Pace is the Python version of the FV3GFS dynamical core and physical parameterizations based on the GT4Py domain-specific language (see Libraries below) which can run on x86 CPUs and NVIDIA GPUs.
11 | 
12 | We also maintain a fork of the *baseline* FV3GFS model with improved diagnostic capability and continuous integration.
13 | 
14 | - (baseline) https://github.com/ai2cm/fv3gfs-fortran. A containerized Vulcan fork of the FV3GFS model.
15 | 
16 | ## Libraries
17 | 
18 | The applications above depend on a series of libraries:
19 | - https://github.com/a2icm/fv3gfs-wrapper. A python wrapper of FV3, used to apply python-based ML predictions in fv3net.
20 | - https://github.com/ai2cm/fv3config. A tool for configuring and preparing input data for FV3GFS. Used to provision test data for several repos, and to configure scientific experiments declaratively or programatically with python.
21 | - https://github.com/ai2cm/pace/tree/main/fv3gfs-util. A toolkit of Python objects and routines for writing weather and climate models. Contains features like halo-exchange and parallel I/O. Used by fv3gfs-wrapper and fv3core.
22 | 
23 | We also maintain a fork of the baseline GT4Py library for our own rapid development before contributing new features upstream.
24 | 
25 | - https://github.com/ai2cm/gt4py. GT4Py Python library for generating high-performance implementation of stencil kernels from a high-level defintion using regular Python functions.
26 | 
27 | 


--------------------------------------------------------------------------------