Possibly because CUDA is much easier to work with they say. OpenCL is said to be cumbersome and generally hasn't been well received by programmers, at least that's the sense I get when reading about CUDA vs. OpenCL from many different sources around the web. CUDA and the NVIDIA architecture were designed and built for each other therefore you can expect there to be fewer compromises. OpenCL was designed to work with a number of existing architectures (otherwise it would be senseless to make it open) so there are necessarily compromises. Compromises negatively affect user friendliness and therefore adoption rates. There is also a perception that CUDA is the platform that gives the greater performance to most massively parallel algorithms with the least effort.