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.
The following Python code will run a two-dimensional Taylor-Green vortex on a GPU:
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.
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 # or pip 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
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}
}
We use the following third-party packages:
This package was created with Cookiecutter and the audreyr/cookiecutter-pypackage project template.
- Free software: MIT license, as found in the LICENSE file.