Open igorkf opened 4 years ago
I would reimplement the Cython part of the library using Numba or Jax to optimize for GPU and CPU at the same time.
Jax already has experimental sparse matrix support: https://jax.readthedocs.io/en/latest/jax.experimental.sparse.html
First of all, thank you very much for that awesome package!
I think
lightFM
could useCuPy
to enable GPU computation.I have a lot of data and making predictions take long time.
I'm already using
cupy
arrays to store the top-k recommended items, and I could decrease sorting the predictions usingcp.argsort
by the half of time! That's a huge improvement.Now I'm thinking that the sparse matrices calculations could be massive calculations too.
How about support lightFM to use
cupy
sparse matrices?https://docs.cupy.dev/en/stable/reference/sparse.html?highlight=sparse