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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).

It provides

  • GPU-accelerated computation based on PyTorch
  • Rapid Prototyping in 2D and 3D
  • Usage of neural networks and automatic differentiation within LBM

Resources

When using lettuce please cite:

@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}
}

Getting Started

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

import torch
from lettuce import BGKCollision, StandardStreaming, Lattice, D2Q9, TaylorGreenVortex2D, Simulation

device = "cuda:0"   # for running on cpu: device = "cpu"
dtype = torch.float32

lattice = Lattice(D2Q9, device, dtype)
flow = TaylorGreenVortex2D(resolution=256, reynolds_number=10, mach_number=0.05, lattice=lattice)
collision = BGKCollision(lattice, tau=flow.units.relaxation_parameter_lu)
streaming = StandardStreaming(lattice)
simulation = 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:

Installation

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

  • Create a new conda environment and install all dependencies:

    conda create -n lettuce -c pytorch -c conda-forge\
         "pytorch>=1.2" matplotlib pytest click cudatoolkit "pyevtk>=1.2"
    
  • Activate the conda environment:

    conda activate lettuce
    
  • 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
    

Credits

We use the following third-party packages:

This package was created with Cookiecutter and the audreyr/cookiecutter-pypackage project template.

License

  • Free software: MIT license, as found in the LICENSE file.
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