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Is anybody aware of any GPU-enabled Lattice Boltzmann solvers (preferably on C++/OpenCL and open-source) that would be recommended?

I have found Advanced Simulation Library, but it seems to be very young. Did anybody try to work with it and verify their benchmarks?

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Sailfish is a great OS LBM solver that meets your needs. Sailfish is developer in the Python language in order to provide a rapid development environment; however, it compiles optimized OpenCL or CUDA via the pyopencl and pycuda libraries.

I have found it to be highly flexible with remarkable computational speeds. Inherently, no computation is performed with Python. The down-side to Sailfish is the very limited user community; however, if you're down the LBM path anyways, you're likely used to that.

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  • $\begingroup$ Thank you for this info. My problem with Sailfish is that it is on Python which I do not know. ASL seems also to use run-time code generation techniques, but it does it on C++ which is probably a bit faster, and is more consistent with OpenCL. $\endgroup$
    – user1876484
    Commented May 27, 2015 at 7:16
  • $\begingroup$ Sailfish only uses Python, essentially, as a means to generate CUDA/OpenCL code - it can be viewed as a wrapper. Python provides you many advantages in development time while all of the computational effort relies STRICTLY on CUDA/OpenCL, which as you said, is C++, so it will be the same or comparable. If you know C++, you will learn Python very quickly. $\endgroup$
    – Jesse Johns
    Commented May 28, 2015 at 2:11
  • $\begingroup$ Welcome to SciComp! Thank you for contributing an answer to this post! Could you please summarize why the software you link to would be a good fit for the original poster? This summary could be as simple as paraphrasing your comment. Stack Exchange tends to frown upon link-only answers without explanation because it diminishes the utility of the answer (e.g., sometimes the links die after a period of time; without context, it's hard to determine the utility of a link other than by clicking on it and investigating the material directly). $\endgroup$
    – Geoff Oxberry
    Commented May 28, 2015 at 3:03
  • $\begingroup$ When I said that ASL is probably faster I meant the generation of the OpenCL code, while the computation itself should be comparable. With regards to the Python's advantages in development time - I'm not sure... Now as I'm digging into ASL, I see that the authors have introduced several abstraction layers, that hide OpenCL completely and allow pretty fast extension/application of the code. And what's for sure - Python is one more dependency (need for the interpreter on the host computer). $\endgroup$
    – user1876484
    Commented May 28, 2015 at 7:11
  • $\begingroup$ "One more dependency" disadvantage is important if you want to distribute the code you write. $\endgroup$
    – user1876484
    Commented May 28, 2015 at 7:57
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After gaining more experience with ASL I'm convinced that it is the best accelerated open source LBM-solver as of end of 2015. It has following important advantages:

  1. simple C++ API (and only C++ - no need to know OpenCL or Python even for adding new numerical methods (which will automatically become hardware accelerated)!)
  2. remarkable performance
  3. multiphysics: many other physical/chemical phenomena besides CFD (Lattice Boltzmann method is used in ASL)
  4. hardware accelerated, can be deployed on CPU/GPU/FPGA/DSP/APU-clusters
  5. mesh-free, immersed boundary technology allows to move from CAD directly to simulation (important for automated design optimization).
  6. dynamic compilation approach enables an additional layer of optimization at run-time (i.e. for a specific parameters set the application was provided with)
  7. open source: AGPL + optional commercial license for closed-source projects.
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