MI300X vs. H100 vs. H200 Benchmark Part 1: Training – CUDA Moat Still Alive

Re:MI300X vs. H100 vs. H200 Benchmark Part 1: Training – CUD... by mike_hearn on Tuesday December 24, 2024 @06:42AM (#42501293)

AI labs don't want to train models using a stack build some guy hacked up on his desktop last night that's been through no proper QA process. The cost of a training run that fails or results in a garbage model due to numerical errors are huge.

Which is why, as they say clearly, nobody is training models on AMD. Only inference, at most. I'm not sure why you keep claiming they are training using private drivers. They clearly aren't.

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Re:MI300X vs. H100 vs. H200 Benchmark Part 1: Training – CUD... by sangnoir on Tuesday December 24, 2024 @05:54PM (#42505536)

Now I i see how where talking past each other. I 100% agree that none of if the hyperscalers are currently (publicly) training on AMD silicon. I disagree with forward-looking statements like it "can't" happen, because I can guarantee you several of them are actively working on making it possible to train on AMD chips - that's just too juicy a target for a bonus packets all the way up to directors: "Our team saved the org $x0 million in TCO vy enabling training on MI300/MI400X in our new clusters"

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Re:MI300X vs. H100 vs. H200 Benchmark Part 1: Training – CUD... by mike_hearn on Thursday December 26, 2024 @06:11AM (#42514521)

Oh, I see. "Can't" means in the present tense in my previous sentence, it wasn't meant to be a definitive statement about the entire future.

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