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OpenLB Release 1.7 available for download

The developer team is very happy to announce the release of the next version of OpenLB. The updated open-source Lattice Boltzmann (LB) code is now available for download.

Major changes include the adaptation of many existing models into the GPU-supporting operator style, a validated turbulent velocity inlet condition and a special focus on new multi phase and particle models. This is augmented by a collection of bugfixes and general usability improvements.

For the first time, the new release is also available in a new public Git repository together with all previous releases. We encourage everyone to submit contributions as merge requests and report issues there.

Core development continues within the existing private repository which is available to consortium members.

Release notes

New features and improvements

  • Many existing models converted to the operator-style (“GPU support”)
  • New multi phase models, interaction potentials and examples
  • New Unit Converter for multi phase simulations
  • New validated turbulent inlet condition Vortex Method
  • New particle decomposition scheme that improves parallel performance of fully resolved particulate flow simulations using HLBM
  • New boundary condition zero gradient
  • Tidy up, (performance) improvements of optimization code
  • Optional support for loading porosity data using OpenVDB voxel volumes

New examples

  • multiComponent/airBubbleCoalescence3d
  • multiComponent/waterAirflatInterface2d
  • advectionDiffusionReaction/longitudinalMixing3d
  • advectionDiffusionReaction/convectedPlate3d
  • porousMedia/city3d
  • porousMedia/resolvedRock3d

Examples with full GPU support

  • turbulence/tgv3d
  • turbulence/nozzle3d
  • turbulence/venturi3d
  • turbulence/aorta3d
  • laminar/poiseuille(2,3)d
  • laminar/poiseuille(2,3)dEoc
  • laminar/cylinder(2,3)d
  • laminar/bstep(2,3)d
  • laminar/cavity(2,3)d
  • laminar/cavity3dBenchmark
  • laminar/testFlow3dSolver
  • laminar/powerLaw2d
  • laminar/cavity2dSolver
  • multiComponent/fourRollMill2d
  • multiComponent/rayleighTaylor3d
  • multiComponent/youngLaplace3d
  • multiComponent/binaryShearFlow2d
  • multiComponent/microFluidics2d
  • multiComponent/contactAngle(2,3)d
  • multiComponent/phaseSeparation(2,3)d
  • multiComponent/rayleighTaylor2d
  • multiComponent/airBubbleCoalescence3d
  • multiComponent/waterAirflatInterface2d
  • multiComponent/youngLaplace2d
  • advectionDiffusionReaction/advectionDiffusion(1,2,3)d
  • advectionDiffusionReaction/convectedPlate3d
  • thermal/squareCavity2d
  • thermal/porousPlate(2,3)d
  • thermal/squareCavity3d
  • thermal/rayleighBenard(2,3)d
  • porousMedia/city3d
  • porousMedia/resolvedRock3d
  • freeSurface/fallingDrop(2,3)d
  • freeSurface/breakingDam(2,3)d
  • freeSurface/rayleighInstability3d
  • freeSurface/deepFallingDrop2d


If you want to cite OpenLB 1.7 you can use:

A. Kummerländer, T. Bingert, F. Bukreev, L. Czelusniak, D. Dapelo, N. Hafen, M. Heinzelmann, S. Ito, J. Jeßberger, H. Kusumaatmaja, J.E. Marquardt, M. Rennick, T. Pertzel, F. Prinz, M. Sadric, M. Schecher, S. Simonis, P. Sitter, D. Teutscher, M. Zhong, and M.J. Krause.

OpenLB Release 1.7: Open Source Lattice Boltzmann Code.

Version 1.7. Feb. 2024.

DOI: 10.5281/zenodo.10684609

General metadata is also available as a CITATION.cff file following the standard Citation File Format (CFF).

Supported Systems

OpenLB is able to utilize vectorization (AVX2/AVX-512) on x86 CPUs [1] and NVIDIA GPUs for block-local processing. CPU targets may additionally utilize OpenMP for shared memory parallelization while any communication between individual processes is performed using MPI.

It has been successfully employed for simulations on computers ranging from low-end smartphones over multi-GPU workstations up to supercomputers and even runs in your browser.

The present release has been explicitly tested in the following environments:

  • Red Hat Enterprise Linux 8.x (HoreKa, BwUniCluster2)
  • NixOS 22.11, 23.11 and unstable (Nix Flake provided)
  • Ubuntu 20.04 and newer
  • Windows 10, 11 via WSL
  • Mac OS Ventura 13.6.3

[1]: Other CPU targets are also supported, e.g. common Smartphone ARM CPUs and Apple M1/M2.

New Android App “paint2sim” Released

Introducing the app “paint2sim” – A Digital Twin for 2D Fluid Flow Simulations

Paint2sim is a mobile application using a Lattice Boltzmann Method realized by the open-source simulation framework OpenLB. This innovative app allows users to scan hand-drawn domains and visualize 2D fluid flow simulations just-in-time on their mobile devices. Whether you’re a student, researcher, or engineer, explore fluid dynamics with an intuitive interface with your fingertips. The app is freely available for download.

For in-depth technical insights, refer to our latest paper, “Just-in-Time Fluid Flow Simulation on Mobile Devices Using OpenVisFlow and OpenLB

Dennis Teutscher and his team developed the app paint2sim as part of the “teaching4future” project, with funding from the Lattice Boltzmann Research Group at KIT and the Ministry of Science, Research, and Arts of Baden-Württemberg, Germany.

Use Case: Scanning a hand-drawn domain and simulating it on a mobile device

OpenLB Community YouTube Channel Update

We have just released a new video on our OpenLB YouTube Channel:

Heterogeneous Load Balancing in OpenLB: Cooperatively Utilizing CPUs and GPUs for a Turbulent Mixing Simulation

Following up on the turbulent micromixer simulation showcased here, the present video illustrates OpenLB’s heterogeneous computation capabilities.

The performance of the simulation case is improved by up to 87% when using heterogeneous CPU-GPU based compared to GPU-only execution. This is achived by distributing the two computationally expensive turbulent inlet regions onto CPUs while the comparatively cheaper bulk regions are processed on GPUs. The underlying inhomogeneous spatial domain decomposition was obtained using a novel genetic algorithm for cost-aware optimization.

A single accelerated CPU-GPU node of the HoreKa supercomputer (2x Intel Xeon Platinum 8368, 4x NVIDIA A100) was used for the showcased simulation consisting of 355 million lattice cells.
OpenLB enabled the cooperative usage of MPI, OpenMP, AVX-512 vectorization and CUDA, reaching a throughput of ~19.25 billion (NSE-only) resp. ~4.79 billion cell updates per second for the fully coupled case.

Simulation setup: Fedor Bukreev
Heterogeneous Load Balancing, Performance engineering, Visualization: Adrian Kummerländer

For further information please vist the associated show case: Heterogeneous Load Balancing

7th Spring School in Heidelberg (Germany) 2024  – Register Now

Registration is now open for the Seventh Spring School on Lattice Boltzmann Methods with OpenLB Software Lab that will be held in Heidelberg/Germany from 4th to 8th of March 2024. The spring school introduces scientists and applicants to the theory of Lattice Boltzmann Methods (LBM) and trains them on practical problems.

Option B: The first half of the week is dedicated to theoretical fundamentals up to ongoing research on selected topics in kinetic theory, scientific computing, LBM, and Partial Differential Equations. Followed by mentored training on case studies using OpenLB in the second half of the week. Emphasis is placed on the modelling and simulation of particulate, multi-component, and turbulent fluid flows.

Option A: Advanced OpenLB users and developers are enabled to solve their own application problems and implement their own solution approaches. All participants benefit from knowledge exchange during the poster session, coffee breaks, and the excursion. We look forward to your participation.

Keep in mind that the number of participants is limited and that the registration follows a first come first serve principle.

On behalf of the spring school executive committee, Kerstin Dick, Shota Ito, Mathias J. Krause, Stephan Simonis

OpenLB paper is ranked 5th on the list of top cited articles in Computers & Mathematics with Applications

We are proud to share that our paper “OpenLB—Open source lattice Boltzmann code” ( is ranked 5th on the list of “Top cited articles published in the past 3 years” in the journal Computers & Mathematics with Applications (IF 2.9, SJR Q1 in “Modeling and Simulation” and in “Computational Theory and Mathematics”).

By the way, out of the first five articles in this list, two are on LBM-based software!

In addition, within the list of “The most downloaded articles in the last 90 days” our paper is ranking 6th. Three out of the first six papers in this list use #LBM.

Thank you to the community for citing us, to the team, the co-authors, the co-developers, and especially to Mathias J. Krause for leading the development of #OpenLB in the past years. 



LBM Spring School in Greenwich successfully finished

The executive committee is happy to announce the closing of the 6th LBM Spring School with OpenLB Software Lab. We hosted 50 participants from 15 countries this year. Congratulations to Martijn Gobes from the Netherlands for winning our poster award.

We are already busy planing next years spring school. The 7th spring school is planned to take place in Heidelberg/Karlsruhe in Germany from March 4th to 8th 2024. 

Thank you all for attending the 6th spring school in Greenwich!

On behalf of the spring school executive committee.

OpenLB Community YouTube Channel Update

We have just released a new video on our OpenLB YouTube Channel about Multi-GPU Simulation of Turbulent Mixing Using an LES Lattice Boltzmann Model and OpenLB.

Accurate simulations of species transport and mixing with reactions in fluids are a grand challenge in CFD because they require resolving relevant turbulent structure down to the Bachelor scales. We present here our first results for our approach on simulating turbulent confined impinging jets (CIJ) micromixer [Johnson & Prud’homme 2003]. With the help of OpenLB ( it is now possible to perform an LES-Lattice Boltzmann Method of that case with a newly developed stabilized species transport. The two turbulent inlets are set up with the vortex method and the wall is mapped with a Bouzidi ansatz for a higher precision. The simulation is meshed in parallel in OpenLB with 248 millions cells which are load-balanced and distributed to 24 A100 GPUs of the HoreKA cluster at KIT. The simulation has taken 40 hours to complete 5.4 ms of real time (17.4 residence times). Two species are simulated but only one is visualized.

Simulation & Visualization: Fedor Bukreev, Adrian Kummerländer