There is still an ane. No mention of performance improvements in it afaik. What were you thinking the gpu cores uplift would be?
Would Geekbench scores provide evidence of this or is there another test which would be better?It all depends on which precision they mean when advertising 4x improvement. FP32? Amazing! FP16? Meh… INT8? Lackluster…
I was hoping for 4-way FP16 dot product with 32-wide SIMD, which would match the performance of the 4070 RTX on the 40-core Max variant. But they mention 4x, which sounds more like 2-way dot product. My math could be off completely of course, it’s late and I’m tired from spending my day at the beach![]()
Really, is that what they said? No more separate ANE? That is quite surprising.
edit: I am looking at the images and the ANE cores are still visibly present in the A19 Pro SoC depiction. So I’m inclined to interpret this in the most conservative way that the matmul performance of the new GPU cores is 4x of the old GPU cores. Which is a bit disappointing to be honest (and in line with my speculation thst the new mixed pipeline is used to support dot product computation).
Would Geekbench scores provide evidence of this or is there another test which would be better?
Yeah, I just noticed that the ANE is still present as a separate unit. That said, why is 4x matmul disappointing to you? It’s pretty much what I was hoping for.
Well, the RTX 4070 offers 60 TFLOPs of FP16 matmul with FP32 accumulate and 120 TFLOPs with FP16 accumulate - and that is without scarcity. Would be great if the new Max Studio offered competitive performance.
I certainly would be interested to see it.IIRC the actual utilization for nvidia GPUs is quite low due to power or thermals or something and they only get close to their specs with trivial matrices (e.g. all 0s or all 1s). I can try to find the article again if you’d like.
I certainly would be interested to see it.
Would Geekbench scores provide evidence of this or is there another test which would be better?
One would imagine that GB AI GPU should?I don’t know if GB uses matmul APIs in their GPU tests. The difference could show up, if they do.
To test the new units, the simplest thing would be to write some very simple compute shaders using the new Metal tensor APIs.
Well, the RTX 4070 offers 60 TFLOPs of FP16 matmul with FP32 accumulate and 120 TFLOPs with FP16 accumulate - and that is without scarcity. Would be great if the new Max Studio offered competitive performance.
So flops per watt still important for GPUs even on the high end ... that could be interesting ...Found it (though I haven’t had a chance to reread it to check that I’m not misremembering): https://www.thonking.ai/p/strangely-matrix-multiplications
Edit: I should also mention that Horace He (the author of that blog) isn’t some internet rando. He’s been a gem in ML and worked on PyTorch for years, and is now a founding engineer at Thinking Machines which has gathered an extraordinarily talented crew. He posted about it here: https://www.thonking.ai/p/why-pytorch-is-an-amazing-place-to
Edit2: The penalty for real data is not nearly as bad as I’d remembered (my apologies). Still a very interesting read, though.
I’m really torn between the Pro Max and Air... No macro, but do you know what the minimum in-focus distance would be for the Air? I’m a bit weak with camera/optics stuff.I'm a little bummed the 17 Air doesn't have camera macro capability. Which now that I think about it, makes sense. I really wanted a much thinner phone, but I'll likely pass on this one.
I’m really torn between the Pro Max and Air... No macro, but do you know what the minimum in-focus distance would be for the Air?
If those are representative, that’s a substantial GPU improvement and an okay CPU upgrade over the A18 Pro.Some of the first Geekbench scores:
CPU https://browser.geekbench.com/v6/cpu/13736665
View attachment 36489
GPU https://browser.geekbench.com/v6/compute/4765303
View attachment 36488
If those are representative, that’s a substantial GPU improvement and an okay CPU upgrade over the A18 Pro.
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