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https://github.com/lettucecfd/lettuce

Computational Fluid Dynamics based on PyTorch and the Lattice Boltzmann Method
https://github.com/lettucecfd/lettuce

cfd lattice-boltzmann machine-learning physics-simulation pytorch torch

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Computational Fluid Dynamics based on PyTorch and the Lattice Boltzmann Method

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README 

        
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GPU-accelerated Lattice Boltzmann Simulations in Python

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



Lettuce is a Computational Fluid Dynamics framework based on the lattice Boltzmann method (LBM).



- **GPU-Accelerated Computation**: Utilizes PyTorch for high performance and efficient GPU utilization.

- **Rapid Prototyping**: Supports both 2D and 3D simulations for quick and reliable analysis.

- **Advanced Techniques**: Integrates neural networks and automatic differentiation to enhance LBM.

- **Optimized Performance**: Includes custom PyTorch extensions for native CUDA kernels.



Resources

---------



- `Documentation`_

- Presentation at CFDML2021 - `Paper`_ | `Preprint`_ | `Slides`_ | `Video`_ | `Code`_



.. _Paper: https://www.springerprofessional.de/en/lettuce-pytorch-based-lattice-boltzmann-framework/19862378

.. _Documentation: https://lettuceboltzmann.readthedocs.io

.. _Preprint: https://arxiv.org/pdf/2106.12929.pdf

.. _Slides: https://drive.google.com/file/d/1jyJFKgmRBTXhPvTfrwFs292S4MC3Fqh8/view

.. _Video: https://www.youtube.com/watch?v=7nVCuuZDCYA

.. _Code: https://github.com/lettucecfd/lettuce-paper



Resources

---------



- `Documentation`_

- Presentation at CFDML2021 - `Preprint`_ | `Slides`_ | `Video`_ | `Code`_



.. _Documentation: https://lettuceboltzmann.readthedocs.io

.. _Preprint: https://arxiv.org/pdf/2106.12929.pdf

.. _Slides: https://drive.google.com/file/d/1jyJFKgmRBTXhPvTfrwFs292S4MC3Fqh8/view

.. _Video: https://www.youtube.com/watch?v=7nVCuuZDCYA

.. _Code: https://github.com/lettucecfd/lettuce-paper



Getting Started

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



The following Python code will run a two-dimensional Taylor-Green vortex on a GPU:



.. code:: python



    import torch

    import lettuce as lt



    lattice = lt.Lattice(lt.D2Q9, device='cuda', dtype=torch.float64, use_native=False)  # for running on cpu: device='cpu'

    flow = lt.TaylorGreenVortex2D(resolution=128, reynolds_number=100, mach_number=0.05, lattice=lattice)

    collision = lt.BGKCollision(lattice, tau=flow.units.relaxation_parameter_lu)

    streaming = lt.StandardStreaming(lattice)

    simulation = lt.Simulation(flow=flow, lattice=lattice, collision=collision, streaming=streaming)

    mlups = simulation.step(num_steps=1000)

    print("Performance in MLUPS:", mlups)



More advanced examples_ are available as jupyter notebooks.



Please ensure you have Jupyter installed to run these notebooks.



.. _examples: https://github.com/lettucecfd/lettuce/tree/master/examples



Installation

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



* Install the anaconda package manager from www.anaconda.org

* Create a new conda environment and install PyTorch::



    conda create -n lettuce -c pytorch -c nvidia pytorch pytorch-cuda=12.1



* Activate the conda environment::



    conda activate lettuce



* Install all requirements::



    conda install -c conda-forge -c anaconda matplotlib pytest click pyevtk h5py mmh3



* Clone this repository from github

* Change into the cloned directory

* Run the install script::



    python setup.py install



* Run the test cases::



    python setup.py test



* Check out the convergence order, running on CPU::



    lettuce --no-cuda convergence



* For running a CUDA-driven LBM simulation on one GPU omit the `--no-cuda`. If CUDA is not found,

  make sure that cuda drivers are installed and compatible with the installed cudatoolkit

  (see conda install command above).



* Check out the performance, running on GPU::



    lettuce benchmark



Citation

--------

If you use Lettuce in your research, please cite the following paper::



    @inproceedings{bedrunka2021lettuce,

      title={Lettuce: PyTorch-Based Lattice Boltzmann Framework},

      author={Bedrunka, Mario Christopher and Wilde, Dominik and Kliemank, Martin and Reith, Dirk and Foysi, Holger and Kr{\"a}mer, Andreas},

      booktitle={High Performance Computing: ISC High Performance Digital 2021 International Workshops, Frankfurt am Main, Germany, June 24--July 2, 2021, Revised Selected Papers},

      pages={40},

      organization={Springer Nature}

    }



Credits

-------

We use the following third-party packages:



* pytorch_

* numpy_

* pytest_

* click_

* matplotlib_

* versioneer_

* pyevtk_

* h5py_

* mmh3_



This package was created with Cookiecutter_ and the `audreyr/cookiecutter-pypackage`_ project template.



.. _Cookiecutter: https://github.com/audreyr/cookiecutter

.. _`audreyr/cookiecutter-pypackage`: https://github.com/audreyr/cookiecutter-pypackage



.. _pytorch: https://github.com/pytorch/pytorch

.. _numpy: https://github.com/numpy/numpy

.. _pytest: https://github.com/pytest-dev/pytest

.. _click: https://github.com/pallets/click

.. _matplotlib: https://github.com/matplotlib/matplotlib

.. _versioneer: https://github.com/python-versioneer/python-versioneer

.. _pyevtk: https://github.com/pyscience-projects/pyevtk

.. _h5py: https://github.com/h5py/h5py

.. _mmh3: https://github.com/hajimes/mmh3



License

-----------

* Free software: MIT license, as found in the LICENSE_ file.



.. _LICENSE: https://github.com/lettucecfd/lettuce/blob/master/LICENSE