The holy grail would be a direct replacement backend that could be fed into TF, like CUDA.
The holy grail would be a direct replacement backend that could be fed into TF, like CUDA.
ROCm has a direct replacement backend that can even take CUDA code (it's designed to be incredibly similar). It's called HIP. It's just that no one wants to support it. That is actually how TensorFlow on AMD works (mostly), and you can compile the latest stable release that way.
I can boot into Linux, and swap into Windows in 2 seconds with this setup. I have a dirty 20 line Bash script that deals with detaching the console, and passing the right things to the right place, but it all works.
ROCm on consumer cards does not work well. The tooling sucks. Massively. I don't understand why AMD doesn't have an extra team of 20 devs working just on the tooling.
Using DirectML with Windows Subsystem for Linux gives you better ML GPGPU support then AMDs native tooling.
That's a matter of opinion I suppose, but I don't personally find that passable.
>Using DirectML with Windows Subsystem for Linux gives you better ML GPGPU support then AMDs native tooling.
DirectML sucks even more than ROCm, IMO. Also, WSL sucks more than a normal VM.
What is a setup that would be passable then? I think a setup like the one that I have described [I believe] would be impossible with Hyper-V or ESXi (though, not that I have even attempted it with either).