2 ms·
Oh shiny! As a data scientist who currently is in Pandas day-to-day, under the hood it uses BLAS (and I think LAPACK) which should give some nice acceleration
by proverbialbunny 6y ago
Oh shiny! As a data scientist who currently is in Pandas day-to-day, under the hood it uses BLAS (and I think LAPACK) which should give some nice acceleration benefits when working with larger dataframes on Apple's M series chips.
- jhayward 6y agoNumpy recently removed Apple's Accelerate framework as a supported BLAS implementation, due to alleged bugs in Accelerate. The Accelerate framework is the only thing that has the Matrix co-processor support. https://github.com/numpy/numpy/pull/15759 https://github.com/numpy/numpy/pull/15759
- JacobiX 6y agoTo benefit from the acceleration, one should use the Apple implementation of BLAS/LAPACK: the Accelerate framework, for the moment I think numerical python libs link against OpenBLAS ? But I'm not 100% sure.