It's nice to see NVidia's behavior here is more widely known now. To this day, I do not understand the justification for asserting that one cannot install GeForce GPUs wherever one wants to install them. I really wish that Nvidia felt more secure that killer Tesla features like NVLINK and the Tensor Cores were sufficient product differentiation to make purchasing Tesla GPUs worth the price.

And that's because to the best of my knowledge, most of the CUDA ecosystem out there was developed on GeForce GPUs.

There is currently no GeForce equivalent of Volta at a time when the underlying programming model has undergone some traumatic changes that really alter the way to write efficient code going forward. If the only way to access Volta GPUs turns out to be AWS instances at $25/hour or $150,000 DGX-1V servers plus hosting costs, I suspect a lot of existing CUDA code will bitrot.

Imagine a near future where AMD Vega GPUs are faster than GTX 1080 TI at FP16 training and inference for deep learning. Without some sort of successor to that GPU, I really think that could happen because Nvidia went out of its way to cripple FP16 performance on GeForce.