What numbers did you use for this calculation?It’s a smartphone CPU that’s faster than M2 Ultra while using 25% less power…
What numbers did you use for this calculation?It’s a smartphone CPU that’s faster than M2 Ultra while using 25% less power…
What numbers did you use for this calculation?
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?Nice cherrypicking. Not are you only cherrypicking an outdated Intel chip, the comparison doesn’t even make sense.
To judge the 3nm performance, you need to compare it to the 5nm chip of the previous Apple Silicon version. And it doesn’t look impressive.
I expected alot more from the 3nm die shrink.
It is, however, a fine methodology for rebutting the claims that "iPhone 15 Pro is a disaster"...We are discussing the efficiency/performance of the A17 on N3. This person is running 3dmark and measuring a battery percentage drop over that time. That’s fine as a rough measurement of phone efficiency, but doesn’t yield much information about the efficiency of the A17 unless we know what’s happening to the other components.
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.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.
How do you know the consumption of both SoC during the Geekbench testbench? What numbers did you use to get 25%?It’s in the chart I posted at the start of this thread… for performance you can check out Geekbench
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).doing something slower always uses less energy, but no-one is interested in 1Hz CPUs.
How do you know the consumption of both SoC during the Geekbench testbench? What numbers did you use to get 25%?
Nice work! Did you choose a degree-four polynomial by doing a log-log plot and finding you got a good fit to a straight line with a slope of four? Would you be willing to share this data? I'd like to play with some curve fitting myself.
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%.My stress test measures power consumption running a demanding workload at a given frequency. Power consumption running Geekbench or anything else intensive has the same power consumption. I did verify this using powermetrics on my Mac, and I see no reason why other Apple hardware will behave any differently.
Thanks for your response.1) Zen uses larger transistors, as does any design that is striving for higher frequency. Apple gets its IPC wins from using lots of transistors, which means density and smaller transistors.
2) What do you think critical path IS? Why can't I run critical path faster? Because critical path cycle time is determined by the sum of the switching times of the sequence of transistors that make up the critical path!
You can see some discussion of these elements here: https://www.realworldtech.com/fo4-metric/
although I think *everyone* would agree that 6 to 8 FO4 is insanely low, you do much better overall by using a slightly longer cycle length that allows for at least some degree of superscalar/OoO/speculation smarts, and taking the IPC win over the frequency loss.
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,...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.
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.
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 efficiencyTo 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.
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.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.
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?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.
I read your post again and indeed you did say otherwise. I misread it initially and I am incorrect in stating that. Apologies.I said otherwise,
this however is not a fair summation of my posts.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
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"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?
Only if you implement the logic in fast semiconductor transistors...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...
Look at the **** curves! Consider egFor 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?
The A17 is in all respects superior (see below).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.
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.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?
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...
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 lifeThe 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.
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