GPUs: mistakes and lessons ideas and experiences

[ariacosmi]

I wanted to start a broader mistakes and lessons thread around GPUs.

A useful angle is advanced workflows, but it also connects with data quality. Different tools and workflows can produce very different results even when the goal is similar.

It would be interesting to compare practical examples, experiments, setups, or lessons that show where GPUs is genuinely useful and where it still needs improvement.



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[josh9099]

For GPUs: mistakes and lessons ideas and experiences, I would separate the problem into setup, output quality and repeatability. gpus and lessons fits into that because it can change the result quite a lot depending on the workflow. The original point — "I wanted to start a broader mistakes and lessons thread around GPUs. A useful angle is advanced workflows, but it also connects with data quality. Different tools and workflows ca…" — gives a useful starting point for that comparison.