How to get a maximally performant NumPy installation from Pip?
conda does a great job of installing a maximally performant NumPy,
pip leaves me with a 6x performance reduction by comparison.
How can I get
pip to install NumPy, such that it yields the same performance as when installed via
Solution – 1
You should install intel-numpy package via pip, in order to get the same performance.
Read more about why this happens here.
In short, conda version was built with MKL.
And the PyPi numpy package was build using BLAS and LAPACK.
p.s. Also that’s the reason why Numpy sucks so much with the famous Ryzen Threadripper by default.
But I must say there was a workaround to make MKL work on AMD processors, but intel fixed and removed this possibility.