Are you perhaps using GLM? I have a discussion where I found excessive usage in julia recently (I don’t know when it started, but it wasn’t there when I originally developed the script) and it looked like GLM was using too many threads for regression. I guess it uses LinearAlgebra under the covers. I fixed it by reducing the BLAS thread count.
You can see the discussion here: Huge CPU load when using GLM
I found the solution.
I know we don’t use julia the right way. We run every script in the global environment 
(but we wanna change it soon)
BUT - the solution was:
I put
import Pkg
Pkg.activate()
at the very beginning of each script.
Thanks for all the help
Edit:
Not sure if the obove was the solution.
I just found out that JULIA_NUM_THREADS=4 was also needed.
I find this solution quite disturbing as it seems to imply that packages may interact in unknown ways to slow down the run.
Probably just different versions of packages being used.
And would that justify a “much slower than”?
I guess those versions are slower than the other ones. Shouldn’t be too hard to verify, run the code with the same Project + Manifest on different julia versions and see if there is a perf difference.
But I’m very much interested why the change in my last edit works. I run 6 scripts in parallel and wanna give them as much CPU as possible. Why do I need to restricht it to less than the system can offer?