Does this accelerate on an M1? I know this says it is for cuda and that obviously means Nvidia GPU, but lots of ML projects have a port to Apple silicon. I would love to try this on my Mac and see what kind of acceleration my pandas tools get for free.
I wish we could commit to not conflating NVIDIA with GPU. It wouldn't hurt a soul to call it "cuDF - NVIDIA DataFrame Library." To answer your question, it will probably run on the CPU.
Jax-metal on Apple M-series GPUs is barely useable in my opinion. It's not possible to invert a matrix, for example, because Apple has not implemented the necessary triangular solve operator. It's also not possible to sample points from a normal distribution, because the Cholesky decomposition operator is not yet implemented. Apple hasn't responsed to both of these issues for the past year. It's difficult to take a numerical computing framework seriously if one cannot invert a matrix.
I should have been more precise to say that I wondered if there was anyone trying to port it to the M1. It seems like every other ML project has some pull request trying that. Or, perhaps there is another project that is attempting to do the same thing for pandas on the M1. It's a noble goal.
