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Ah, but part of the reason for CUDA's success is that the open source developer who wants to run unit tests or profile their kernel can pick up a $200 card. Tha

Ah, but part of the reason for CUDA's success is that the open source developer who wants to run unit tests or profile their kernel can pick up a $200 card. That PhD student with a $2000 budget can pick up a card. Academic lab with $20,000 for a beefy server, or tiny cluster? nvidia will take their money. And that's all fixed capital expenditure - there's no risk a code bug or typo by an inexperienced student will lead to a huge bill. Also, if you're looking for an alternative to CUDA because you dislike vendor lock-in, switching to something only available in GCP would be an absurd choice.

_ea1k 3y ago
I'm really shocked at how dependent companies have become on the cloud offerings. Want a GPU? Those are expensive, lets just rent on Amazon and then complain about operational costs! I've noticed this at companies. Yeah, the cloud is expensive, but you have a data center, and a few servers with RTX 3090s aren't expensive. A lot of research workloads can run on simple, cheap hardware. Even older Nvidia P40s are still useful.