Intel Habana, Graphcore, Google TPU, and Nvidia A100 Compared In AI Training
On a slightly unrelated note: NVIDIA recently published a blog post about using AI to design parts of the H100(https://twitter.com/rjrshr/status/1545446397759016962). They're suggesting that AI can beat out EDA tools in many cases. Do you think that's plausible? Do you see EDA firms starting to integrate AI capabilities into their software or is there space for disruption here?
Thanks for the comparison.
Curious about some points that occurred to me after reading the article:
(a) Is it the case that Google's TPUs are useful only for a select class of AI models? Is that why Google still buys thousands of Nvidia GPUs?
(b) From the perspective of a GCP customer, Google recently claimed on their blog that TPUs would reduce their costs by 35-40% (they compared TPUs on GCP to A-100s on Azure). So is Nvidia's good software stack the only reason that customers at GCP are not adopting TPUs en masse?
(c) Surprised that except Google, no one thinks it is worth the effort to create their own silicon for training & inference? Keep hearing about AWS's Graviton but nothing more & it seems to be a CPU chip, not a GPU.
(d) How is Nvidia so confident that GPUs will be the dominant hardware form-factor going ahead? I understand models are changing very fast at the cutting edge, but wouldn't some kind of ASIC/FPGA kind of hardware give lower TCO?
Sorry for so many queries but I am just so surprised at how dominant Nvidia has stayed over the last 5-6 years, and how no one seems to be posing any effective threat.
Curious where Apple stands in all this. While they don't sell AI components or even AI itself, they clearly invest in it. Do you see the possibility that 3rd parties will use Apple's M-series systems for AI applications such as research or even sell AI application software packages on m-series systems?
Enjoyed the read, with up-to-date numbers and something people interested in the Genomics / Bioinformatics field should keep an eye on.
I expected to see the market much open this time. But Nvidia still keeping up with a 2 years old piece of silicon is very impressive. Next submission with H100 will be a blood bath for the competition...
I don't know Betteridge's law of headlines. But, yes, I clicked and read article because of fancy headline.^^
Apologies for Betteridge's law of headlines to the title of this post, but it got you to click and read it didn’t it!
Were any results submitted for AMD?
Would've been interesting to understand where they stand in this space (SW wise).