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Power curve and efficiency of Apple N3
- Thread starter leman
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It’s in the chart I posted at the start of this thread… for performance you can check out Geekbench
TSMC has said all along that N3 is either 10% better performing than N5P at the same power, or uses 25% less power at the same performance. This is exactly what the benchmarks are seeing. People expecting more are expecting too much.According to this site, it's only 10% faster and they used geekbench. GPU is 20% faster, but Apple added an extra GPU core. So it's not really one-to-one comparison.
Geekbench shows how much faster the iPhone 15 Pro's A17 chip is
The new iPhones are finally here, and when it comes to the iPhone 15 Pro and iPhone 15 Pro Max,...9to5mac.com
If only a 10% performance gain at the same power consumption is what you expected from the 3nm chip, then you are easy to please.
Reviewers of the iPhone 15 Pro expected also alot more from the 3nm chip, so I'm not the only one.
Did you expect more from a 4nm die shrink?
Intel Core 7 165H "Meteor Lake" CPU debuts on Geekbench with over 2.5K score - VideoCardz.com
Intel Core Ultra 7 165H appears on Geekbench The 165H is the same as the Intel Core Ultra 7 1002H. A fresh wave of leaks has surfaced showcasing Intel’s new generation of Core Ultra series processors, powered by the Meteor Lake architecture. In recent weeks, there has been an increase in leaks...
Because I fail to see why 2900 in a PHONE power envelope is somehow worse than 2500 in a LAPTOP power envelope...
It is, however, a fine methodology for rebutting the claims that "iPhone 15 Pro is a disaster"...
Which is what half the posts here (and more on the broader internet) are claiming.
To be honest I’m not sure how this relates to my point. The person I replied to stated their snapdragon 870 was more efficient than the A17 due to their method of running a benchmark while measuring the drop in battery percentage. I stated that isn’t the way to measure the A17’s efficiency.
EDIT: turns out I misread the original post. Apologies.
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How do you know the consumption of both SoC during the Geekbench testbench? What numbers did you use to get 25%?
Not sure it matters here, but that's not strictly true... It's certainly not true down to the 1Hz clock rate (which I realize was an exaggeration for effect).
The logic is leaking while it's running, so there's a constant power term in addition to the dynamic term and that constant tends to get larger as process geometry shrinks. So there's a point where running slower saves dynamic power but the benefit is lost to leakage.
This is further true at the system level, where finishing faster might mean turning off the display more quickly, but that's beyond what we can account for in this discussion...
My stress test measures power consumption running a demanding workload at a given frequency. Power consumption running Geekbench or anything else intensive at marching frequency will be the roughly same. I did verify this using powermetrics on my Mac, and I see no reason why other Apple hardware will behave any differently.
P.S. Apple Silicon does feature fine-grained power gating to save energy, but a demanding workload should tax just enough subsystems that this won’t change the results too much.
If you do, let me know how closely it hews to our f^2.15 estimate of yore near the operating point. 😉
"In theory, theory and practice agree. In practice, they don't."
I guess you have used 6.5W for M2 and 5W for A17, so you get around 25% (6.5-5)/6.5*100=23%.
So, assuming the A17 Pro consumes 5W at 3.8GHz and scores 2900 points and the A16 consumes 4W at 3.5GHz and scores 2500 points, the increase in consumption is greater than the increase in points on Geekbench.
Thanks for your response.
1) I didn't realize this. Time to do more reading.
2) Right, but not knowing that switching time was variable meant I thought it was all down to depth + wiring delay. Anyway, thanks for the link, that was a useful refresher on stuff I'd forgotten too many years ago.
Then they are as ill-informed as you.According to this site, it's only 10% faster and they used geekbench. GPU is 20% faster, but Apple added an extra GPU core. So it's not really one-to-one comparison.
Geekbench shows how much faster the iPhone 15 Pro's A17 chip is
The new iPhones are finally here, and when it comes to the iPhone 15 Pro and iPhone 15 Pro Max,...
If only a 10% performance gain at the same power consumption is what you expected from the 3nm chip, then you are easy to please.
Reviewers of the iPhone 15 Pro expected also alot more from the 3nm chip, so I'm not the only one.
Expectations for a pure die shrink would be +12-15% clock at equivalent power. [Edit: actually less, since the A16 is on N4, not N5- so perhaps Apple actually hit that number, whatever it is.] But Apple put in substantial design work and got a bit less than that. That leaves you with two choices about what to believe:
1) You believe that Apple is so stupid that they invested a ton in design work to get worse results.
2) You believe that Apple is clever and looks to the future and across its entire product line. That their lead in phone CPU is so substantial that they can afford to give up a little in pure efficiency in order to build a core that can scale to much higher clocks, given power and thermal headroom. In other words, in a Mac.
We won't know for sure which of those two things is true until the M3s ship in a desktop configuration (Studio and/or Pro), though the 14/16" Pro laptops will probably give us strong indications. But based on past performance, I'd bet real money on option #2.
Yes, all the data so far suggests that A17 is slightly less efficient that A16 at its peak and slightly more efficient than A16 when operating at reduced frequencies.
For discussion on this, I’d like to refer to you to the excellent post by @Confused-User just above this one.
I said otherwise, please, the only thing you do is telling people they are wrong, no argument, and you dont even know what is a burst load, there are more things than a graph in chip efficiency
For many, the A17's competition is the A16, not Qualcomm's latest SoC. So they may be disappointed if the A17 is less efficient than the A16.
How do you know that A17 is more efficient than A16 at reduced frequency? Are you comparing A17 at reduced frequency with A16 at maximum frequency or both at reduced frequency?
First off - thanks for this. This nicely illustrates your thoughts from this post (https://forums.macrumors.com/thread...d.2393667/page-31?post=32539219#post-32539219) about Apple designing for the desktop.
Curiosity question: Why are M1/M2 numbers 'scattered' on the graph? There seems to be more noise in those numbers. Is that because there's likely more going on in the background of MacOS compared to iOS?
Curiosity question: Why are M1/M2 numbers 'scattered' on the graph? There seems to be more noise in those numbers. Is that because there's likely more going on in the background of MacOS compared to iOS?
I read your post again and indeed you did say otherwise. I misread it initially and I am incorrect in stating that. Apologies.
this however is not a fair summation of my posts.
It was speculated earlier on in the thread, https://forums.macrumors.com/threads/power-curve-and-efficiency-of-apple-n3.2404894/post-32563082 ; "discrete frequencies"
really enjoying this thread, lots of smarts in here, thank ya'll
Only if you implement the logic in fast semiconductor transistors...
If you want low enough energy, you can use much less leaky (and slower) materials or, hell, ratchet-and-pawl style micro-mechanical movements that toggle "occasionally" based on environmental noise
This is of course a general principle. The same holds true for your car. It will be more gas efficient at low speeds (but no-one cares!) and if you want absolute efficiency, to hell with speed, you switch to considering very different sorts of designs from a car...
Look at the **** curves! Consider eg
At every frequency, the A17 curve draws less power (to do the same level of work) AND has slightly higher IPC (ie is in fact doing work at a slightly higher rate for the same frequency).
The complaint people appear to have (it's hard to tell when most of the people chiming in have no idea what they are trying to say beyond "Apple sux") is that at the end of the curve, the A17 curve pushes higher in frequency and power.
ie JUST LIKE the A16 curve did relative to A15. And JUST LIKE the A15 curve did relative to A14.
But if there's one constant in internet discussion, it's that people feel they have ZERO obligation to look at any sort of data or history before throwing out their opinions...
The A17 is in all respects superior (see below).
Because he gathered data points at various frequencies. The A17 is in all cases more efficient at a given clock. That is, for any frequency X, the A17 will use less energy than an A16.
IIRC, it will also do slightly more work as it has a very modest (small single-digit) IPC gain iso-clock.
Ok, so maybe I shouldn't have been so timid about leaving the scope of the data presented...Only if you implement the logic in fast semiconductor transistors...
If you want low enough energy, you can use much less leaky (and slower) materials or, hell, ratchet-and-pawl style micro-mechanical movements that toggle "occasionally" based on environmental noise
This is of course a general principle. The same holds true for your car. It will be more gas efficient at low speeds (but no-one cares!) and if you want absolute efficiency, to hell with speed, you switch to considering very different sorts of designs from a car...
In every one of those cases, there is energy being expended while you're waiting for your slow process to complete. If you're going to go into micro mechanics and internal combustion we may as well account for the metabolic energy consumed while you're waiting for your technology to respond. Your computer runs on a coin cell, but you've burned 3 pizzas waiting for your calculation to complete.
My point here is simply that dynamic power isn't the only power sink in a system. Optimal efficiency can sometimes be found by increasing processing speed. This is the whole reason for hurry-up-and-wait processing models.
Its more efficient, but It can consume more power, thats why 15 PM dont have more battery Life in some reviews, thats why some people are conplaining about heat and battery life