Is it possible to utilize all cores when performing matrix calculations?

[u3Izx9ql7vW4]

Hi,

I'm using lu.solve() for doing least squares and I noticed CPU utilization is mostly confined to one core, whereas Numpy's linalg.lstsq has all cores running at 100%. For the size of the matrix I'm working with, lu.solve() took on average 27 seconds (build) whereas Numpy took on average 19 seconds, both on the same machine. I'm wondering if there's some way to get nalgebra to run on all available cores like Numpy to possibly get a performance boost.

For the benchmark, nalgebra's lu.solve was ported to Python for comparison using Maturin, and the above results was done in release mode.