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Nvidia Hopper GPU Architecture and H100 Accelerator

anandtech.com

61–70 of 183 posts

Re: Nvidia Hopper GPU Architecture and H100 Accelerator

#62
post #37

From the nvidia page, > 80 billion transistors > Hopper H100 .. generational leap > 9x at-scale training performance over A100 > 30x LLM inference throughput > Transformer Engine .. speed .. 6x without losing accuracy So another monster chip - same size of the Apple M1-max thingy .. I guess it comes down to pricing. The A100 is already ridiculously expensive at $10K. They can this one at $50K and it would sell out?

You can buy A100s in a server today, a number of integrators will happily sell it to you.

As someone who've tried for some weeks, it really seems like it's out-of-stock literally everywhere. The demand seems to be a lot higher than the supply at the moment, so much that I'm considering buying one myself instead of renting servers with it.

Re: Nvidia Hopper GPU Architecture and H100 Accelerator

#65
post #51

Earlier quoted context omitted.

The catch is it's only for TF32 computations (Nvidia proprietary 19 bit floating point number format)

I missed that, to me that makes the ‘32’ in the name misleading.

TF32 = FP32 range + FP16 precision

Re: Nvidia Hopper GPU Architecture and H100 Accelerator

#66

Earlier quoted context omitted.

Given that it's Nvidia, no Linux support. That's the catch.

All the AI software running on these data-centre chips is almost exclusively running on Linux. I wish people would stop talking rubbish about NVIDIA's Linux support.

That's because nvidias linux support for consumers is indeed trash, while their creators/business/creatives software (eg CUDA) is not trash, but you mostly hear consumers trashing nvidia.

Re: Nvidia Hopper GPU Architecture and H100 Accelerator

#70
post #63

This would be cool if they had decent drivers for Linux.

I can assure you systems that take advantage of this chip for scientific/ML workloads aren't running Windows.

they may have edited their comment but they were commenting on the lack of quality of their Linux drivers (which I agree with but only on a consumer level, never used nvidia in a server)
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