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Has been a decade+. If you build company on their GPUs you will fail. Just adding implementation complexity for no reason. Unfixable software.

But all I'm doing is warning. The consensus viewpoint is not this so you can listen to HN consensus or you can listen to me.




> The consensus viewpoint is not this so you can listen to HN consensus or you can listen to me.

Can you corroborate your points? None of it really aligns with my experience. Nvidia hardware seems quite popular and effective for raster solutions, accelerated RT, dedicated AI and even low-power handheld gaming. I'm typing this out on a Linux box with an Nvidia GPU right now :P

It's worth noting that Nvidia isn't a saint, sure. They play for keeps, and CUDA is limited to paying customers only. CUDA doesn't have open source alternatives, though. Some things do part of what CUDA does really well (or better), but nobody is making a full-stack replacement. Apple is investing in the Accelerate framework which has almost no industry/datacenter application; AMD is doubling down on OpenBLAS and community support. Intel is half-assing some proprietary frameworks and pushing it into demos for a good look.

It would be great if these incumbent companies would pool their vast resource advantage to write, deliver, test and maintain a cross-platform GPGPU library. But that's a lot to ask, and it's easier to just disrupt the entire market with a single integrated package.


> Intel is half-assing some proprietary frameworks and pushing it into demos for a good look.

My understanding is the likes of oneAPI is supposed to be enable non nvidia gpus to work on CUDA workloads? Is oneAPI one of your these proprietary frameworks?


I should have said "The HN consensus viewpoint is apparently not this based on this thread"




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