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Apple M1 Ultra

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Re: Apple M1 Ultra

#491

Post by TuringNYC »

polyrand wrote: post #258

I think the GPU claims are interesting. According to the graph's footer, the M1 Ultra was compared to an RTX 3090. If the performance/wattage claims are correct, I'm wondering if the Mac Studio could become an "affordable" personal machine learning workstation (which also won't make the electricity bill skyrocket). If Pytorch becomes stable and easy to use on Apple Silicon [0][1], it could be an appealing choice. [0]…

It shocks me how much payroll and cap-ex is spent on the M1 and how little is invested in getting TensorFlow/Pytorch to work on it. I could 10x my M1 purchases for our business if we could reliably run TensorFlow on it. Seems pretty shortsighted.

The GPU claims wouldnt even need to be on parity with NVIDIA, it would just need to offer a vertically integrated alternative to having to use EC2.

Re: Apple M1 Ultra

#492

Post by oneplane »

mehmetoguzderin wrote: post #488
apohn wrote: post #396

Earlier quoted context omitted.

The 3090 also can do fp16 and the M1 series only supports fp32, so the M1 series of chips basically needs more RAM for the same batch sizes. So it isn't an Oranges to Oranges comparison. Back when that M1 MAX vs 3090 blog post was released, I ran those same tests on the M1 Pro (16GB), Google Colab Pro, and free GPUs (RTX4000, RTX5000) on the Paperspace Pro plan. To make a long story short, I don't think buying any M1…

> The 3090 also can do fp16 and the M1 series only supports fp32 Apple Silicon (including base M1) actually has great FP16 support at the hardware level, including conversions. So it is wrong to say it only supports FP32.

I'm not sure if he was talking about the ML engine, the ARM cores, the microcode, the library or the OS. But it does indeed have FP16 in the Arm cores.

Re: Apple M1 Ultra

#493

Post by wil421 »

zdw wrote: post #450
joshspankit wrote: post #419

Earlier quoted context omitted.

Watching the keynote I was almost thinking that Nvidia missed the boat when they chose not to sign whatever they had to to make OSX drivers. Thank you for recalibrating me to actual reality and not Apple Reality (tm)

nVidia missed the boat in releasing a bunch of "replace the whole laptop logic board" chips that died in the 2008-2012 timeframe and annoyed a whole host of OEMs: https://www.techpowerup.com/64683/nvidia-admits-to-selling-f... Apple specifically: https://support.apple.com/en-us/HT203254

My 2011 MPB 15” suffered from the Nvidia GPU issue. It was so bad my computer wouldn’t boot properly and the Apple Geniuses kept denying the claim because it couldn’t finish a test.

Anyway, it was still my longest lived Laptop. My Sony VAIOs were great but I liked that Mac better.

Re: Apple M1 Ultra

#494

Post by rpmisms »

Normal_gaussian wrote: post #468
gtvwill wrote: post #440

Earlier quoted context omitted.

1000 bucks for 45 mins work? Maybe 1.5hrs tops? I didn't realise their wage was >500 an hour?

To be fair here, there is more to it than just assembly. You have to spec out the parts, ensuring compatibility. Manage multiple orders and deliveries. Assemble it. Install drivers/configuration specific packages. All of these things are easier today than ten or twenty years ago - but assigning it to a random mid-level engineer and I'd set my project management gamble on half a day for the busiest, most focused engin…

PC part picker will do the heavy lifting for you. There are also management tools that will let you install software bundles easily, no real extra time investment.

Re: Apple M1 Ultra

#495

Post by apohn »

mehmetoguzderin wrote: post #488
apohn wrote: post #396

Earlier quoted context omitted.

The 3090 also can do fp16 and the M1 series only supports fp32, so the M1 series of chips basically needs more RAM for the same batch sizes. So it isn't an Oranges to Oranges comparison. Back when that M1 MAX vs 3090 blog post was released, I ran those same tests on the M1 Pro (16GB), Google Colab Pro, and free GPUs (RTX4000, RTX5000) on the Paperspace Pro plan. To make a long story short, I don't think buying any M1…

> The 3090 also can do fp16 and the M1 series only supports fp32 Apple Silicon (including base M1) actually has great FP16 support at the hardware level, including conversions. So it is wrong to say it only supports FP32.

Thanks. At least when I ran the benchmarks with Tensorflow, using mixed precision resulted in the CPU being used for training instead of the GPU on the M1 Pro. So if the hardware is there for fp16 and they will implement the software support for DL frameworks, that will be great.

Re: Apple M1 Ultra

#496

Post by batiudrami »

mwint wrote: post #463
eyegor wrote: post #447

Earlier quoted context omitted.

Ehh, I wouldn't put too much stock in graphs of "relative performance" on a 0-200 scale like these. Marketing can cook up whatever they like when they want to make a product look good. Wait for actual benchmarks before trying to judge the product. Their base claim is >2x the m1 max, which is still nowhere close to the performance of a 3090. Apple's footnotes don't even pretend to explain what these charts are. > Perf…

Remember last time Apple put out these weird relative performance charts, and we all thought they were hiding something? The M1 announcement. They turned out to be pretty accurate. So I’ll wait and see real benchmarks, but it wouldn’t surprise me if this does have incredible performance.

Their GPU claims weren’t accurate though. The M1 max doesn’t have real world performance anything like the 3070 as claimed.

Re: Apple M1 Ultra

#497

Post by apohn »

oneplane wrote: post #492
mehmetoguzderin wrote: post #488

Earlier quoted context omitted.

> The 3090 also can do fp16 and the M1 series only supports fp32 Apple Silicon (including base M1) actually has great FP16 support at the hardware level, including conversions. So it is wrong to say it only supports FP32.

I'm not sure if he was talking about the ML engine, the ARM cores, the microcode, the library or the OS. But it does indeed have FP16 in the Arm cores.

I should have been more clear. I didn't mean the hardware, but the speedup you get from using mixed precision in something like Tensorflow with an NVIDIA GPU.

Re: Apple M1 Ultra

#498

Post by enedil »

mhh__ wrote: post #215
marcan_42 wrote: post #150

Earlier quoted context omitted.

My 1st gen 16 core Threadripper is barely faster than an M1 Pro/Max at kernel builds, so a 64 core TR3 should handily double the M1 Ultra performance. But you know, I'm still happy to double my current build perf in a small box I can stick in my closet. Ordered one :-)

How many threads are actually getting utilized in those kernel builds? I don't work on the kernel enough to have intuition in mind but people make wildly optimistic assumptions about how compilation stresses processors. Also 1st gen threadrippers are getting on a bit now, surely. It's a ~6 year old microarchitecture.

Kernel has thousands of compilation units. Each of them is compiled by a separate compiler process. Only the linking at the end doesn't parallelise, however it should take a much smaller part of the time. The proportions change of course, if you develop kernel and do incremental builds lots of times. Then the linking stage might become a bottleneck.

The above statement should also relate to most other C/C++ projects.

Re: Apple M1 Ultra

#499

Post by [deleted] »

Geee wrote: post #307

This is insane. They claim that its GPU performance tops the RTX 3090, while using 200W less power. I happen to have this GPU on my PC and not only it costs over $3000, but its also very power-hungry and loud. Currently, you need this kind of GPU performance for high resolution VR gaming at 90 fps, but its just barely enough. This means that the GPU will run very loudly and heat up the room, and running games like HL…

[deleted]

Re: Apple M1 Ultra

#500

Post by EvgeniyZh »

paulmd wrote: post #459
Macha wrote: post #432

Earlier quoted context omitted.

We've already seen x86 draw even with Intel 12th gen: https://www.youtube.com/watch?v=X0bsjUMz3EM

So in that one, you've got a 20-thread Intel part (6+8C/20T) at probably 3.5 GHz going against a 10-thread Apple part (8+2C/10T), at probably 3 GHz, and the Apple part still comes out on top by ~5% in Cinebench R23 MT. And that's with Intel having 50% more high-performance threads available. Work out the IPC there - the Intel has a 2x thread count advantage, a 17% clock advantage, and Apple comes out 5% ahead. So the…

How much little cores and HT contribute at this workload tho? If I say turn them off, could I claim the opposite, losing even 20% but using 40% less threads?
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