Comments (3)
This is happening because we moved the backend CUDA library from CUDArt to CUDAdrv. That will be a lot more robust but there may be a couple of small changes needed.
In your case you should just use CUDAdrv.CuArray
in place of CUDArt.CudaArray
, and things should just work.
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I see. Thanks for taking care of JuliaGPU, these packages are in dire need of some love.
I've seen that you're deprecating CUDArt too. I'm wondering, would there be interest in making a guide as that in the README of CUDArt for CUDAdrv? (ie, a quick "this is how you can call your cuda functions with this package" such as this one: https://github.com/JuliaGPU/CUDArt.jl/blob/master/README.md#usage)
I spent today figuring that out and I think it could save others some time, but I understand this wouldn't be super useful if API changes are coming to CUDAdrv soon.
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Yeah, lots of old and forgotten code around here, but also some useful stuff that we can make good use of going forward.
I don't think CUDAdrv is about to undergo huge API changes (cc @maleadt just in case), so any doc improvements would be really welcome.
I don't know your use case, but you might also be interested in CuArrays, which provides more general array functionality. Not all of BLAS is wrapped yet but I'll happily add stuff if needed.
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