Yeah. That's been my general problem with adopting NVidia for anything. They make good hardware, but there's a lot of lock-in, and not a lot of transparency. That introduces business risk.

I'm not in a position where I need GPGPU, but if there wasn't that risk, and generally there were mature, open standards, I'd definitely use it. The major breakpoint would be when libraries like Numpy do it natively, and better yet, when Python can fork out list comprehensions to a GPU. I think at that point, the flood gates will open up, and NVidia's marketshare will explode from specialized applications to everywhere.

Intel stumbled into it by accident, but got it right with x86. Define an open(ish) standard, and produce superior chips to that standard. Without AMD, Cyrix, Via, and the other knock-offs, there would be no Intel at this point.

Intel keeps getting it right with numerical libraries. They're open. They work well. They work on AMD. But because Intel is building them, Intel has that slight bit of advantage. If Intel's open libraries are even 5% better on Intel, that's a huge market edge.