>What I'm after is something simple as for exemple what ArrayFire.jl
If ArrayFire is the kind of simplicity you want and if you don't need more
than that, ArrayFire is your best bet right now!
It should be relatively stable. Make sure that you installed the
dependencies correctly and if it still doesn't pass please open a Github
Another option is CUDAnative.jl <https://github.com/JuliaGPU/CUDAnative.jl>
lets you run a subset of Julia code on an NVIDIA gpu.
Sadly, it's not that simple to use yet. You need to build a special Julia
version, set things up correctly and you will still frequently hit bugs
with opaque errors.
I'm currently working on a GPUArray prototype, which makes using
CUDAnative.jl <https://github.com/JuliaGPU/CUDAnative.jl> easier and has a
fallback if you're not on NVIDIA hardware/ not building your own Julia
But that's still in the early prototype phase.
Am Samstag, 17. September 2016 11:21:12 UTC+2 schrieb Ferran Mazzanti:
> Hi folks,
> I know this is a very naive question as such but I can't make me a
> complete picture of this world. I would like to be able to program Julia
> code for the nVidia GPU's supporting CUDA: What is the best/easiest way to
> do that? Is it possible to write all the code (including the GPU part) in
> Julia, or does one need to resort to C to write kernels? What I'm after is
> something simple as for exemple what ArrayFire.jl seems to provide, but
> unfortunately this one does not seem to pass the tests in Julia. Does
> anybody know of a good (and simple) CUDA tutorial for that?
> Thanks in advance and sorry for being so naive,