Pushing onwards from our recent addition of AMD accelerator support in OpenLB Release 1.9, the developer team is happy to share that we now have preliminary support for Intel GPUs. This means OpenLB now supports hardware acceleration across all of the big three platforms: NVIDIA, AMD, and Intel!
Using a new SYCL-based backend for our platform-transparent model implementations, we scaled up to a problem size of 4000 billion single-precision D3Q19 cells. Utilizing 1,000 nodes (~10%) of the Aurora supercomputer at the Argonne Leadership Computing Facility (TOP500 #3), this yielded a peak performance of 21,120 billion cell updates per second (GLUPs).
This work was done in the context of our ALCF Directorโs discretionary allocation project ๐๐ฑ๐ฆ๐ฏ๐๐ ๐ฐ๐ฏ ๐๐น๐ข๐ด๐ค๐ข๐ญ๐ฆ: ๐๐น๐ต๐ฆ๐ฏ๐ฅ๐ช๐ฏ๐จ ๐ฑ๐ญ๐ข๐ต๐ง๐ฐ๐ณ๐ฎ-๐ต๐ณ๐ข๐ฏ๐ด๐ฑ๐ข๐ณ๐ฆ๐ฏ๐ค๐บ ๐ต๐ฐ ๐๐ฏ๐ต๐ฆ๐ญ ๐๐ฆ-๐๐๐ (OLEX).
Interested in this or any other aspect of OpenLB and Lattice Boltzmann Methods? Join our upcoming Spring School this March in Liverpool, UK! (Early bird registration ends today)
Our Spring School brings together researchers and industry professionals to explore the lattice Boltzmann method (LBM), from fundamental theory to real-world applications.
๐น ๐๐ถ๐ฟ๐๐ ๐ต๐ฎ๐น๐ณ of the week: Learn the ๐๐ต๐ฒ๐ผ๐ฟ๐ฒ๐๐ถ๐ฐ๐ฎ๐น ๐ณ๐ผ๐๐ป๐ฑ๐ฎ๐๐ถ๐ผ๐ป๐ ๐ผ๐ณ ๐๐๐ , including insights into current research and advanced topics. ๐น ๐ฆ๐ฒ๐ฐ๐ผ๐ป๐ฑ ๐ต๐ฎ๐น๐ณ of the week: Hands-on, mentored ๐ฐ๐ฎ๐๐ฒ ๐๐๐๐ฑ๐ถ๐ฒ๐ ๐๐๐ถ๐ป๐ด ๐ข๐ฝ๐ฒ๐ป๐๐, offering deep practical experience with state-of-the-art LBM simulations.
For experienced participants, the advanced option of the Spring School provides the opportunity to work on your own application challenges or develop custom LBM implementations, supported by expert tutors. Thursday and Friday are dedicated to independent work, with continuous feedback and in-depth discussions encouraged.
What makes this Spring School special? โจ A unique, highly interactive learning concept within the LBM community โจ Close mentoring by experts โจ Valuable networking during poster sessions, coffee breaks, and the excursion
We look forward to welcoming you to an inspiring week of learning, collaboration, and exchange!
The 9th Spring School 2026 on Lattice Boltzmann Methods with OpenLB Software Lab will be held in Liverpool/UK from March 23rd to 27th 2026.
The developer team is very happy to announce the release of the next major version of OpenLB. The updated open-source Lattice Boltzmann (LB) code is now available for download.
For this release, we refactored almost all of our 138 examples into a new unified and more user friendly case style. This allows for easy adjustment of parameters and convenient re-use of example for e.g. parameter studies, adjoint optimization and uncertainty quantification. It is also essential preparation for the introduction of transparent local grid refinement. Beyond that we added various new models and example cases in addition to introducing SI-unit-based setters for moments. Last but not least, OpenLB 1.9 also provides preliminary support for AMD GPUs using HIP/ROCm.
The new release is also available in our public Git repository together with all previous releases. Recently, we also started pushing lots of incremental updates and fixes there, so keep a look out! We also encourage everyone to submit contributions as merge requests and report issues there.
Highlights
New unified style for simulation cases
Consistent CLI interface for changing parameters without re-compilation
SI setters for moments
Initial support for AMD GPUs (tested on AMD Instinct MI300A and AMD RX 7800 XT)
Startup message including a fancy ASCII art logo and environment information
Models
New electrochemical models and validated applications to electroosmotic flows in porous media
Physically parameterized and well-balanced multi phase
New characteristics-based boundary condition and damping function for acoustics
Support for cell-centered grid refinement
Citation
If you want to cite OpenLB 1.9 you can use:
A. Kummerlรคnder, T. Bingert, S. Bock, F. Bukreev, D. Castroviejo, L.E. Czelusniak, D. Dapelo, C. Gaul, M. Dorn, L. Dorneles, J. Grafen, M. Grinschewski, S. Ito, J. Jeรberger, F. Kaiser, D. Khazaeipoul, T. Krรผger, A. Kumbhat, H. Kusumaatmaja, A. Nettekoven, A. Raeli, T. Riazantsev, M. Rennick, G. Prakash, F. Prinz, L. Sauterleute, M. Schecher, A. Schneider, Y. Shimojima, S. Simonis, P. Spelten, A. Tacques, and M.J. Krause.
OpenLB Release 1.9: Open Source Lattice Boltzmann Code.
Version 1.9.0. Dec. 2025.
DOI: 10.5281/zenodo.17899765
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 as well as both NVIDIA and AMD 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:
NixOS 24.11 and later (Nix Flake provided)
Fedora 39
Red Hat Enterprise Linux 9.4
Rocky Linux 8.9
Windows 10, 11 via WSL
Mac OS Tahoe
OpenLB was also tested on all partitions (blue, green, teal, ruby) of HoreKa (NHR@KIT) as well as Karolina (IT4I), Leonardo (CINECA) and ALPS (CSCS).
For the second time, more than twenty OpenLB developers retreated to the mountains for their annual Hackathon. There, they spent one week fully focused on improving the framework, exchanging knowledge and enjoying nature. This time, the focus was on refactoring all 133 example cases into a new consistent and user-friendly case style as well as general maintenance. The result is already visible in the public repository and will be incorporated into a new release this December.
Preparations for next year’s iteration are already ongoing, any interested external contributors should feel free to contact us and join!
Registration is now open for the 9th Spring School on Lattice Boltzmann Methods with OpenLB Software Lab that will be held in Liverpool, United Kingdomfrom March 23rd to 27th 2026.
The spring school introduces scientists and users from industry to the theory of LBM and trains them on practical problems. The first half of the week is dedicated to the theoretical fundamentals of LBM up to ongoing research on selected topics. Followed by mentored training on case studies using OpenLB in the second half, where the participants gain deep insights into LBM and its applications. This educational concept is unique in the LBM community and offers a comprehensive and personal guided approach to LBM. Participants also benefit from the knowledge exchange during poster session, coffee breaks and an excursion. We look forward to your participation.
The OpenLB team enjoyed a fantastic week at the CIRM in Marseille for the 8th and largest Spring School to date with 105 participants from 18 countries. Together with our friends from AMU, ProLB and the Falcon project we were happy to both introduce many new people to the theory and practice of LBM as well as to continue collaborating on many interesting research questions in the advanced section.
We also want to congratulate Sai Ravi Gupta Polasanapalli for winning this year’s poster award.
Already, we are busy organizing the next spring school which will take place in Liverpool, UK from March 23-27 2026. Stay tuned for more details soon!
The developer team is very happy to announce the release of the next major version of OpenLB. The updated open-source Lattice Boltzmann (LB) code is now available for download.
This release contains a plethora of new models, features and usability improvements, not to forget 40+ new example cases. The addition of a wall model for fixed and moving walls usable together with a new platform-transparent fluid structure interaction module, physically parameterized multi-phase models and examples and a completely revamped code generation pipeline deserve special mention. Last but not least, it also provides preliminary support for grid refinement operators.
The new release is also available in our 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
Highlights
Revised and new turbulence wall model for static and moving walls
Physically parameterize multi-phase models
New conservative Allen-Cahn model with access to high density and viscosity ratios as well as high surface tension and wetting
Improved well balanced Cahn-Hilliard model, now with no spurious currents and access to higher density and viscosity contrasts and wetting
Improved and consistent pseudo-potential model
Lots of new multi-phase examples, now in physical units
First release of general purpose fluid structure interaction module
Platform-transparent and performance optimized
Validation benchmark examples
Completely revamped automatic code generation for dynamics and non-local post processors
Automatic CSE optimization of any non-branching dynamics and post processor
Easily triggered without complex dependencies by introspection output
110+ dynamics optimized
Initial operators for efficient, GPU-enabled grid refinement
Initial examples using the scheme by Lagrava et al.
New backwards automatic differentiation approach for automatic generation of CSE-optimized adjoint dynamics
Initial immersed boundary model for resolved deformable blood cells New Uncertainty quantification (UQ) module
Non-intrusive UQ methods integrated with full support for Monte Carlo, Quasi Monte Carlo, Latin Hypercube Sampling, and stochastic collocation generalized polynomial chaos
A. Kummerlรคnder, T. Bingert, F. Bukreev, L. Czelusniak, D. Dapelo, C. Gaul. N. Hafen, S. Ito, J. Jeรberger, D. Khazaeipoul, T. Krรผger, H. Kusumaatmaja, J.E. Marquardt, A. Raeli, M. Rennick, F. Prinz, M. Schecher, A. Schneider, Y. Shimojima, S. Simonis, P. Sitter, P. Spelten, A. Tacques, D. Teutscher, M. Zhong, and M.J. Krause.
OpenLB Release 1.8: Open Source Lattice Boltzmann Code.
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 24.11 and unstable (Nix Flake provided)
Ubuntu 22.04 and newer
Windows 10, 11 via WSL
Mac OS Ventura 13.6.3
However, it generally will run without issue on any system offering one of the supported compilers. Don’t hesitate to contact us via the forum should you face any difficulties.
[1]: Other CPU targets are also supported, e.g. common Smartphone ARM CPUs and Apple M1/M2.
Registration is now open for the 8th Spring School 2025 on Lattice Boltzmann Methods with OpenLB and ProLB Software Lab that will be held in Marseille/France form 19.05.2025 โ 23.05.2025.
The spring school introduces scientists and applicants from industry to the theory of LBM and trains them on practical problems. The first half of the week is dedicated to the theoretical fundamentals of LBM up to ongoing research on selected topics. Followed by mentored training on case studies using OpenLB or ProLB in the second half, where the participants gain deep insights into LBM and its applications. This educational concept is probably unique in the LBM community and offers a comprehensive and personal guided approach to LBM. Participants also benefit from the knowledge exchange during poster session, coffee breaks and the excursion. We look forward to your participation.
From October 6-11, 2024, the LBRG successfully organized the first OpenLB Hackathon in Feldberg, Germany. For one week, 14 group members focused on core development to further improve OpenLB in terms of boundary condition modeling, GPU support and user friendliness.
We have just released a new video on our OpenLB YouTube Channel:
Particle Swarm Settling Behavior Spheres and Cubes Using Lattice Boltzmann Methods and OpenLB
This video presents a detailed comparison of the swarm settling (or hindered settling) behavior of volume-equivalent spheres and cubes. The simulation is fully resolved and four-way coupled, showing the dynamic behavior of 1934 particles within a triple periodic domain measuring 15D x 15D x 15D, where D = 3 mm is the diameter of the spheres. The particle volume fraction is approximately 30% and the Archimedes number is set to 2000.
Observations from the video
Shape matters: Particle shape has a significant effect on the suspension dynamics.
Average settling velocity: Cubes settle on average approximately 24% slower than the volume-equivalent spheres.
Clustering: Spheres have a higher tendency to form clusters than cubes.
The simulations were performed with OpenLB using 152 cores (Intel Xeon Platinum 8368 CPU) and both simulations together took less than 13 hours to complete.
Further details and in-depth analysis can be found in the corresponding publications [1, 2].
[1]: J. E. Marquardt, N. Hafen, and M. J. Krause, โA novel model for direct numerical simulation of suspension dynamics with arbitrarily shaped convex particles,โ Computer Physics Communications, vol. 304, p. 109321, 2024, doi: 10.1016/j.cpc.2024.109321.
[2]: J. E. Marquardt, N. Hafen, and M. J. Krause, โA novel particle decomposition scheme to improve parallel performance of fully resolved particulate flow simulations,โ Journal of Computational Science, vol. 78, p. 102263, 2024, doi: https://doi.org/10.1016/j.jocs.2024.1….
We use cookies to ensure that we give you the best experience on our website. If you continue to use this site we will assume that you are happy with it.
