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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 woul

by xrd 2y ago

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.

zamalek 2y ago
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.
- xs83 2y ago
  It requires NVIDIA
killingtime74 2y ago
From the readme, no. Says NVIDIA drivers required
- xrd 2y ago
  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.
kiratp 2y ago
Jax is the closest thing at the moment. https://developer.apple.com/metal/jax/ https://developer.apple.com/metal/jax/ And MLX https://github.com/ml-explore/mlx https://github.com/ml-explore/mlx
- mvanaltvorst 2y ago
  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. [1]: https://github.com/google/jax/issues/16321 https://github.com/google/jax/issues/16321 [2]: https://github.com/google/jax/issues/17490 https://github.com/google/jax/issues/17490