| --- |
| frameworks: |
| - "" |
| language: |
| - en |
| license: apache-2.0 |
| tags: |
| - OneScience |
| - fluid dynamics |
| - external flow prediction |
| - unstructured-mesh simulation |
|
|
| --- |
| <p align="center"> |
| <strong> |
| <span style="font-size: 30px;">MeshGraphNet</span> |
| </strong> |
| </p> |
| |
| # Model Overview |
|
|
| MeshGraphNets is a graph neural network developed by DeepMind for mesh-based physical simulation. It rapidly predicts the dynamics of complex physical systems, including fluids, structures, and cloth. |
|
|
| Paper: Learning Mesh-Based Simulation with Graph Networks |
| https://arxiv.org/abs/2010.03409 |
|
|
| # Model Description |
| MeshGraphNets uses an encoder–processor–decoder graph-network architecture trained on trajectories from fluid, structural, and cloth simulations to perform long-horizon dynamical simulation of complex physical systems. |
|
|
| ## Use Cases |
|
|
| | Use Case | Description | |
| |---|---| |
| | External flow prediction | Predict velocity, pressure, and other flow variables at mesh nodes | |
| | Structural deformation simulation | Predict the displacement, stress, and deformation of loaded structures | |
| | Cloth dynamics | Simulate the motion of deformable objects such as flexible membranes and cloth | |
| | ModelScope/OneCode execution | Download the standalone model package, install its dependencies, and run the provided scripts | |
|
|
|
|
| # Usage |
|
|
| ## 1. OneCode |
|
|
| Use the online OneCode environment for an intelligent, one-click AI for Science (AI4S) programming experience: |
|
|
| [Launch OneCode for one-click AI4S programming](https://web-2069360198568017922-iaaj.ksai.scnet.cn:58043/home) |
|
|
| ## 2. Manual Setup |
|
|
| **Hardware Requirements** |
|
|
| - A GPU or DCU is recommended. |
| - DCU users must install DTK in advance. DTK 25.04.2 or later, or the OneScience-recommended version for the target cluster, is recommended. |
|
|
|
|
| ### Download the Model Package |
|
|
| ```bash |
| modelscope download --model OneScience/MeshGraphNet --local_dir ./MeshGraphNet |
| cd MeshGraphNet |
| ``` |
|
|
| ### Set Up the Runtime Environment |
|
|
|
|
| **DCU Environment** |
|
|
| ```bash |
| # Activate DTK and Conda first |
| conda create -n onescience311 python=3.11 -y |
| conda activate onescience311 |
| # Installation with uv is also supported |
| pip install onescience[cfd-dcu] -i http://mirrors.onescience.ai:3141/pypi/simple/ --trusted-host mirrors.onescience.ai |
| ``` |
|
|
| **GPU Environment** |
| ```bash |
| # Activate Conda first |
| conda create -n onescience311 python=3.11 -y libstdcxx-ng=12 libgcc-ng=12 gcc_linux-64=12 gxx_linux-64=12 |
| conda activate onescience311 |
| # Installation with uv is also supported |
| pip install onescience[cfd-gpu] -i http://mirrors.onescience.ai:3141/pypi/simple/ --trusted-host mirrors.onescience.ai |
| ``` |
|
|
| ### Training Data |
|
|
| The OneScience community provides the `cylinder_flow` dataset for training. Download it with the command below and verify that the data path in `config/config.yaml` is configured correctly: |
|
|
| ```bash |
| modelscope download --dataset OneScience/cylinder_flow --local_dir ./data |
| ``` |
|
|
| ### Training |
|
|
| Single GPU: |
|
|
| ```bash |
| python scripts/train.py |
| ``` |
|
|
| Multiple GPUs: |
|
|
| ```bash |
| torchrun --nproc_per_node=8 --nnodes=1 --rdzv_id=1000 --rdzv_backend=c10d --max_restarts=0 --master_addr="localhost" --master_port=29500 scripts/train.py |
| ``` |
|
|
| Training saves `.pth` files under `weight/checkpoints`. |
|
|
| ### Model Weights |
| This repository will provide weights trained on the `cylinder_flow` dataset in the `weights/` directory. The weights will be uploaded soon. |
|
|
| ### Inference |
|
|
| ```bash |
| python scripts/inference.py |
| ``` |
|
|
| Inference results are saved to `result/output/`. |
|
|
| ### Evaluation and Visualization |
|
|
| ```bash |
| python scripts/result.py |
| ``` |
|
|
|
|
| # Official OneScience Resources |
|
|
| | Platform | OneScience Repository | Skills Repository | |
| | --- | --- | --- | |
| | Gitee | https://gitee.com/onescience-ai/onescience | https://gitee.com/onescience-ai/oneskills | |
| | GitHub | https://github.com/onescience-ai/OneScience | https://github.com/onescience-ai/oneskills | |
|
|
| # Citations and License |
| - Original MeshGraphNet paper: [Learning Mesh-Based Simulation with Graph Networks](https://arxiv.org/abs/2010.03409). |
| - This repository retains source attribution and has been adapted for automated execution through OneScience and ModelScope. |
|
|
