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Because GPUs calculations are the same type of calculations. If you have a problem where you need to add plus 1 in all of the elements of a matrix, then GPUs are great. Games are a great example because you can take one pixel and calculate its values over time without much worry of what happens around it. Similar story for neural nets.

For CFD it is a different problem. In each time-step you essentially solving a linear system Ax=b, so even if you are looking at element x(100,100,timeperiod2) you need to also know the value of the element x(1,1,timeperiod1).

There are some algorithms that decouple the problem by introducing residuals for each element and then trying to iteratively reduce them, but as you can see, it is not a linear increase in speed as someone would had expected by looking at the GPU specs.

TLDR: Yes you can do CFD with GPUs, but dont expect miracles.




using GPUs for CFD is pretty standard these days and has been for a few years. GPUs are fantastic for solving linear systems.

Nobody uses GPUs for "linear speedups by looking at GPU specs". That's not how accelerators are measured.


"using GPUs for CFD is pretty standard these days and has been for a few years. "

It is not standard in OpenFoam (only though rapidCFD) or Ansys (only this year they made an announcement for full acceleration).

"GPUs are fantastic for solving linear systems."

*Some* linear systems. They are horrible for sparse algebra.




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