The products are good, but NVidia also cleverly bootstrapped a whole ecosystem around them. One of the other posts mentions 2014 as a turning point. At that ti

The products are good, but NVidia also cleverly bootstrapped a whole ecosystem around them. One of the other posts mentions 2014 as a turning point. At that time, GPGPU stuff was entering the (scientific) mainstream and NVidia was all over academia, convincing people to try it out in their research. They handed out demo accounts on boxes with beefy GPUs, and ran an extremely generous hardware grant proposal. There was tons of (free) training available: online CUDA MOOCs and in-person training sessions. The first-party tools were pretty decent. As a result, people built a lot of stuff using CUDA. Others, wanting to use those programs, basically had to buy NVidia. Lather, rinse, repeat. This is in stark contrast to the other “accelerator” vendors. Around the same time, I looked into using Intel Xenon Phi and they were way less aggressive: “here are some benchmarks, here’s how it works, your institution has one or two somewhere if you want to contact them and try it out.” As for OpenCL…crickets. I don’t even remember any AMD events, and the very broad standard made it hard to figure out what would work/work well and you might end up needing to port it too!