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Accelerated PyTorch Training on M1 Mac

pytorch.org

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Re: Accelerated PyTorch Training on M1 Mac

#11

Post by my123 »

Scene_Cast2 wrote: post #8

I'm curious about the performance compared to something like, say, the RTX 3070.

Low. Apple doesn't have matrix math accelerators in their current GPUs.

The neural engine is small and inference only. It's also only exposed by a far higher level interface, CoreML.

Where it could still make sense is if you have a small VRAM pool on the dGPU and a big one on the M1, but with the price of a Mac, not sure that makes a lot of sense either in most scenarios compared to paying for a big dGPU.

Re: Accelerated PyTorch Training on M1 Mac

#15

Post by amelius »

> Accelerated GPU training is enabled using Apple’s Metal Performance Shaders (MPS) as a backend for PyTorch.

What do shaders have to do with it? Deep learning is a mature field now, it shouldn't need to borrow compute architecture from the gaming/entertainment field. Anyone else find this disconcerting?

Re: Accelerated PyTorch Training on M1 Mac

#16

Post by my123 »

amelius wrote: post #15

> Accelerated GPU training is enabled using Apple’s Metal Performance Shaders (MPS) as a backend for PyTorch. What do shaders have to do with it? Deep learning is a mature field now, it shouldn't need to borrow compute architecture from the gaming/entertainment field. Anyone else find this disconcerting?

Apple doesn't have a separate API tailored towards compute only, but a single unified API that makes concessions to both.

Concessions towards compute: a C++ programming language for device code (totally unlike what's done for most graphics APIs!)

Concessions towards graphics: no single-source programming model at all for example...

Re: Accelerated PyTorch Training on M1 Mac

#17

Post by dagmx »

amelius wrote: post #15

> Accelerated GPU training is enabled using Apple’s Metal Performance Shaders (MPS) as a backend for PyTorch. What do shaders have to do with it? Deep learning is a mature field now, it shouldn't need to borrow compute architecture from the gaming/entertainment field. Anyone else find this disconcerting?

Shaders are just the way compute is defined on the GPU.

Why is that concerning to you?

Re: Accelerated PyTorch Training on M1 Mac

#18

Post by geertj »

amelius wrote: post #15

> Accelerated GPU training is enabled using Apple’s Metal Performance Shaders (MPS) as a backend for PyTorch. What do shaders have to do with it? Deep learning is a mature field now, it shouldn't need to borrow compute architecture from the gaming/entertainment field. Anyone else find this disconcerting?

Not sure if it’s concerning but it caught my eye as well.

Re: Accelerated PyTorch Training on M1 Mac

#19

Post by my123 »

dagmx wrote: post #17
amelius wrote: post #15

> Accelerated GPU training is enabled using Apple’s Metal Performance Shaders (MPS) as a backend for PyTorch. What do shaders have to do with it? Deep learning is a mature field now, it shouldn't need to borrow compute architecture from the gaming/entertainment field. Anyone else find this disconcerting?

Shaders are just the way compute is defined on the GPU. Why is that concerning to you?

That terminology isn't used at all in GPGPU compute APIs specifically tailored for that purpose, which use quite different programming models where you can mix host and device code in the same program.

And there are "GPUs" today that can't do graphics at all (AMD MI100/MI200 generations) or in a restricted way (Hopper GH100) which has the fixed function pipeline only on two TPCs, for compatibility, but running very slowly due to that.

Re: Accelerated PyTorch Training on M1 Mac

#20

Post by apohn »

Scene_Cast2 wrote: post #8

I'm curious about the performance compared to something like, say, the RTX 3070.

I wrote a comment about an Tensorflow on M1 comparison to some cloud providers. I imagine PyTorch on M1 would give similar results. I think the gist would be that the 3070 is going to be a better investment.

https://news.ycombinator.com/item?id=30608125

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