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There's a winner-take-all dynamic at play, though. The better CUDA is, the more things get built on top of it. The more things get built on top of CUDA, the b
by ketzo 4y ago
There's a winner-take-all dynamic at play, though.
The better CUDA is, the more things get built on top of it.
The more things get built on top of CUDA, the better the CUDA ecosystem of tooling, frameworks, etc. gets.
The better the CUDA ecosystem is, the better CUDA is. GOTO 1.
But you're right -- lots and lots of folks will be motivated to compete.
- CuriouslyC 4y agoExcept that CUDA is low level, so it's not hard to shim above it and write interoperable code. There are too many players who don't want to play the Nvidia tax, this will play out like OpenGL vs Direct3d in reverse.
- ethbr0 4y ago> this will play out like OpenGL vs Direct3d in reverse Is that also like OpenCL vs CUDA in reverse?
- WanderPanda 4y agoI feel like abstractions don't work if we want to get the maximum performance. Afaik Tensor cores are not usable from opencl and on the other hand even in the CUDA universe cuBLAS (hand optimized) seems to outperform cutlass (using abstractions)
- roenxi 4y agoI dunno; CUDA is a library. How many closed source libraries win winner-takes-all games? Nvidia is a lonely proprietary ship in a hostile sea of open source packages. It might take 20 years if Intel and AMD fail to do anything useful, but sooner or later they'll either open source CUDA defensively or get ground down by an open library. There are a finite list of features to implement before "Runs on Nvidia" vs "Runs on any graphics card" becomes the only important box left on the bureaucrat's checklist. The math here is literally 1st & 2nd year university subjects. That is a good short term moat, but not a defensible one long term.