If they get TensorFlow/Torch/MXNet running with no changes in the code, 32GB HBM2 for training models would be awesome! These days hitting memory limitations is biting more than general slowness of GPUs during Deep Learning training.
https://sod.pixlab.io/samples.html for some code samples.
The commenter asked how the performance compares to an NVidia 1080Ti GPU.
A precise benchmark may not be necessary but in general, it will take for example how many Skylake cores at 3.5 Ghz to approximate the GPU example?
Not with mainline kernel (which supports up to Polaris), but it it already got merged into 4.18 that is going to be released in a couple of weeks. Until then it requires a bit extra effort https://github.com/RadeonOpenCompute/ROCm#dkms-driver-instal...
> Keras?
over opencl with https://github.com/plaidml/plaidml
And even ignoring that, you still can’t use PyTorch.