[fermienrico]

I understand the difficultly with legacy code, but your opinion about "Silicon Valley" types, etc. is very off putting.

World needs to evolve. Those who do not, disappear.

If there is a way without sacrificing accuracy, then GPU computation would be absolutely amazing. Imagine the productivity boost, time savings, power and infrastructure savings you'd gain by using a GPU (if it is possible that is). Imagine being able to simulate engineering problems in near real time without having to wait for hours for a solver to converge.

I don't have experience in the solvers, but if there is a way to enable GPU computation then why the hell not!? Silicon valley types or not. People who are engaged in CFD (I used to work at Lockheed's flutter dynamics team) are certainly not "old fashioned" as you describe. GPU to them wouldn't just be a "kid's video game toy" - I can assure you having worked with these folks.

[bauta-steen]

Perhaps the main issue is that even if a PDE solver supports distributed CPU parallelism, the distributed block solvers do not typically allow for decoupling to thousands of independent threads that GPUs are good at. Therefore as the PDE problems and solvers are tightly coupled they do not easily parallelize to GPUs and don't allow for simple recompilation with GPU targets. Most often an existing code would require a complete rewrite/redesign (man years of work for big code bases), at least if there are to be any gains to be had. There are new codes coming, particularly in academia, utilizing GPUs. From what I've seen one can expect around 10x improvement switching to GPUs, so it's good, but not magnitudes better considering the work involved.