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yeah, you could also say the performance is only 57% in this particular test for the M1 vs A100. Still not bad for a laptop though with a first gen chip.

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The M1 is (supposedly) specialized for ML calculations and on a decidedly denser node, though. I guess it's a testament to either CUDA's power or machine learning GPGPU optimization.

> The M1 is (supposedly) specialized for ML calculations

It is, but they’re not using any of that. Only the M1 GPU at this time.

Yeah the ANE and AMX on cpu are wrapped behind Accelerate Framework and CoreML. So you will have to use CoreML (which wasn't able to compile the latest TF BERT). ANE is also inference only. So if you want training you will have to use the GPU with Apple's Tensorflow-Metal.

//part of nod.ai / SHARK team.

I like this blog to understand NVidia perf stats (search for "Normalized GPU deep learning performance"):

https://timdettmers.com/2020/09/07/which-gpu-for-deep-learni...

It seems that their consumer GPUs also have a gap

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