I love to learn and share the amazing hardware and services being built to enable Artificial Intelligence, the next big thing in technology.
Every six months, NVIDIA, Intel and Google show how much their AI training hardware and software have improved while their competitors hide in the bushes. NVIDIA is starting to see some competitive threats but remains the leader, especially in the scale of its supercomputers and benchmark breadth.
The semiannual benchmarking marathon for AI training has just published the latest results in MLPerf 3.1. Not surprisingly, most competitors shy away from transparency. Still, Intel once again demonstrated it is the only viable alternative to NVIDIA for AI, at least until AMD releases its MI300 GPU next month. Here are some observations.NVIDIA is justifiably proud of their new EOS supercomputer, which they claim is the fastest AI facility in the universe; I mean the world.
These results should help pave the way for Gaudi3, due in 2024. But of course, at that time, Intel will have to compete with NVIDIA’s next-generation GPU, the B100, aka Blackwell. We know nothing about H100 except that it will be produced on TSMC’s 3nm process. It is rumored to be a relatively minor upgrade than the astounding H100 represented over its A100 predecessor, but we shall see.
We should also mention that Intel submitted results for the Xeon 4th generation CPU, which has considerable die area dedicated to performing matrix operations needed to run AI. A large NVIDIA Korean customer, Naver Corporation, the creator of South Korea's top search portal, has switched from Nvidia GPUs to Intel CPUs, citing AI GPU shortages and price hikes.Conclusions
It looks to us like the combination of Gaudi and the upcoming AMD MI300 will, for the very first time, provide competitive alternatives to NVIDIA, at least from the hardware standpoint. While not as fast as an H100, Gaudi 2 is more affordable and available and can get the job done, especially in enterprise use cases. And Hugging Face has hundreds of models ready for deployment on Gaudi2.
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