Cloud providers such as AWS recommend disabling hyperthreading for HPC applications.
As someone who is only vaguely familiar with what that means, I am left wondering: Would disabling hyperthreading on my machine have any potential to improve the performance of polars (and, for that matter, other parallelized python libraries for data scientists)?
Why not just go and try it? It’s pretty easy to revert the change in the BIOS.
The logic is that hyper threading lets you do more work on a physical core when it’s not saturated with computational work. Since a high performance numerical library should be saturated the cores, there shouldn’t be an advantage to hyper threading. But you’d have to test to be sure.