Creating a recipe for CUDA-enabled pytorch

[odgaard]

Hi! Thank you for your incredible work with this layer.
After successfully building the python3-pytorch recipe today I discovered that it seems like a CPU-only install.
Have you made any attempts at getting a GPU-accelerated pytorch recipe working? Do you think it would be feasible to implement this based on your existing recipe?

[zboszor]

I assume you are building Yocto for x86-64 as I do.

Intel's MKL and oneDNN (MKLDNN) is already enabled in pytorch if meta-intel is added to the set of layers. This may make the GPU used implicitly, which is not the same as a fully accelerated build.

I haven't found a complete Yocto layer which provides CUDA with selectable version to provide support for obsolete hardware and is up to date with styhead and walnascar support.

Eventually I would want to go with chipStar (see #8 ) to fake CUDA which can work with any sufficiently mature OpenCL implementation. At least all its samples work with the Intel Compute Runtime's OpenCL driver. But chipStar is not there yet to build pytorch completely and you need Intel's icpx SYCL compiler from meta-intel to build chipStar's optional HIP libraries that may be needed to compile pytorch with chipStar's nvcc replacement. Unfortunately, icpx is not exposed as a native compiler executable by the Intel packages.

The XPU method of GPU acceleration in pytorch also needs icpx, so it's not enabled either.

So we're stuck with CPU-only at the moment. But at least the AVX2 and AVX512 stuff works.

FWIW, OpenVINO can be built using PACKAGECONFIG += "opencl" and it does provide GPU acceleration with a proper OpenCL driver.

[zboszor]

I have just seen the new AdaptiveCpp 25.02.0 release with "portable CUDA" which may be what we need for a "CUDA enabled" pytorch build using SYCL/OpenCL behind the scenes.

[cmcquinn]

I am interested in using this layer with meta-tegra. I might fork this layer, create some way to enable CUDA via a bbappend and then open a PR with my changes. Has anyone ever tried using this layer with meta-tegra before?

[zboszor]

I am interested in using this layer with meta-tegra. I might fork this layer, create some way to enable CUDA via a bbappend and then open a PR with my changes. Has anyone ever tried using this layer with meta-tegra before?

I have not used meta-tegra before but please, go ahead and try it.

See the python3-pytorch_%.bbappend for how it was done to support MKL when building for Intel.

You can add USE_CUDA=1 etc. in a meta-tegra-specific python3-pytorch_%.bbappend here under dynamic-layers/tegra and don't forget to change BBFILES_DYNAMIC in layer.conf.