Disclaimer: I’m not a GPGPU expert. Please be skeptical about what I’m about to say.
The issue seems to be that the major projects such as Google’s TensorFlow only support CUDA and (unfortunately) not OpenCL (yet). To my limited knowledge in this area, I believe the primary reason for this is because TensorFlow depends on Eigen, which currently only supports CUDA.
It would be awesome to have a vendor-agnostic platform layer of sorts, independent of OpenCL, CUDA and other future GPGPU interfaces X. Back when I was working in the games industry, I lead a rendering team which developed an analogous proprietary platform layer for OpenGL and DirectX. Building something like that is a massive and time-consuming undertaking.
It seems to me like Nvidia has an edge with CUDA, simply because that is what most established frameworks, libraries, tools and applications have chosen to target. Data scientists who make use of said products rarely have the know-how, time and interest to develop low-level GPU interfaces.
