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The benefit is that we can all put this into a single repo, and the code will be automatically loaded when a user, e.g., imports CUDA.
That way, they don't need to import several separate packages, and the registration procedure should be simplified for us.
The text was updated successfully, but these errors were encountered:
This is a good idea indeed --- I didn't know about this capability so thanks! I would still keep AbstractFastHartleyTransform.jl separate from this particular one, but it is indeed a good idea to have CUDA (and perhaps AMDGPU one using rocFFT) inside this package in this way.
I added FastHartleyTransformCUDAExt in ext using weakdep, and then removed FastHartleyTransformCUDAExt.jl. I can add the rocFFT version by replacing CuArray/CUFFT to rocArray/rocFFT but I can't test because I don't have a AMD GPU now....
Anyway, it works ok with my local nvidia's GPU. I will move forward to registering this package.
I will close this issue as I have officially released the first version (which is now being registered to the Julia package repo). Feel free to open the issue again if needed.
I noticed that we are making a bunch of packages. Would it be easier to just use Julia package extensions for this?
This is described here https://pkgdocs.julialang.org/v1/creating-packages/#Conditional-loading-of-code-in-packages-(Extensions)
The benefit is that we can all put this into a single repo, and the code will be automatically loaded when a user, e.g., imports CUDA.
That way, they don't need to import several separate packages, and the registration procedure should be simplified for us.
The text was updated successfully, but these errors were encountered: