It also seems like a pretty important question to answer because it has big implications for the advancement of AI technology which has everyone so freaked out.
So what's the consensus around here? Is Moore's Law actually over yet, or not?
This graph to me show that while yes technically Moore's law of doubling transistor per "thing Intel or AMD sells you" is still holding, it has ended for single threaded workloads. Moore's law is only holding due to core count increase.
For everyday use of users running multiple simple programs/apps, that's fine. But for truly compute heavy workloads (think a CAD software or any other heavy processing), developers turned to GPUs to get the compute power improvements.
Writing amazing programs taking full advantage of the core count increase is simply impossible (see Amdahl's law). So even if one wanted to rearchitect programs to take full advantage of the overall transistor count from ~2005 to now, they won't be able to.
Compare with pre-2005, where one just had to sit & wait too see their CPU-heavy workloads improve... It's definitely a different era of compute improvements
Intel, by contrast, says that Moore's Law is still alive. But Intel is technologically behind, and it is easier to improve when there is someone to learn from, so maybe there is a wall that they haven't yet hit.
Regardless, it is a very different law than when I was young, when code just magically got faster each year. Now we can run more and more things at once, but the timing for an individual single-threaded computation hasn't really improved in the last 15 years.
Moore posited in 1965 that the the amount of transistor per chip will roughly double every year - something he himself called "a wild extrapolation" in a later interview.
Actual development speed proved slower than that, so in 1975 he revised his prediction to transistors doubling every two years - so, the original "Moore's Law" was already dead by then. The second revision of his prediction proved more long-lived, in part because manufacturers were actively planning their development and releases around fulfilling that expectation - making it sorta a self-fulfilling prophecy.
There was another slow down in 2010 though - with actual development falling behind "schedule" since then.
But neither the "doubling" - nor the "year" or "two years" were ever anywhere near precise to begin with, so the question "is it dead" depends highly on how much leeway you are willing to give.
If you demand strict doubling every year - that's been dead since before 1975.
If you demand roughly doubling every two years - that's probably mostly dead since 2010.
If you allow for basically exponential growth but with a tiny bit of slow down over time - then it's still alive and well.
There can be no precise answer to the question - since the whole prediction was so imprecise to begin with. I don't think there's any benefit to getting hung up on drawing a supposedly precise line in the sand...
- Transistor count doubles every ~24 months (Moore's law) - still going strong
- Total power stays ~constant (Dennard Scaling) - no longer holds
- Total cost stays ~constant - don't know if there is a name for this, but it no longer holds either
The real magic was when you had all three trends working together, you would get more transistors for the same power and same total cost. As the last two trends have fallen off, the benefit of Moore's law by itself is reduced.
There is still some effect of the last two trends, power per transistor and cost per transistor are still dropping, just at a slower rate than density is increasing. So power budgets and costs continue to grow. Hence 450W GPUs and 400W CPUs.
Today's 3nm processes use 3 dimensional gates that have film thicknesses on the order of 5 to 8 atoms thick and the features size is smaller than the wavelength of light used to measure expose wafers' different mask reticles that rely on using light slit interference to make features smaller than the EUV wavelength of around 10nm.
To get much smaller than 1nm using these techniques is going to run into fundamental physical limits in a decade and probably that limit will be around .5nm feature size.
The next frontier in silicon will be building three dimensional chips and IBM is a pioneer in 3D stacking of CMOS gates.
https://www.tomshardware.com/news/no-sram-scaling-implies-on...
https://www.youtube.com/live/oIG9ztQw2Gc?feature=share
This isn’t the best recording on YouTube but it’s late and I couldn’t quickly find the other one.
https://ourworldindata.org/grapher/transistors-per-microproc...
(the stagnation of 2019-2020 has nothing to do with technology; it's COVID)
https://www.tsmc.com/english/news-events/blog-article-201908...
We'll probably have a couple more innovations and might get to making a transistor out of a single atom (silicon atom is 0.262nm; carbon atom is 0.3).
5nm / (2*2*2*2) =~ 0.3
So I don't think we're done making faster hardware just yet, but we're certainly getting to the boundaries of what appears to be physically possible.
"AI's Rule: Just as Moore's Law unfolds, the language models might expand, doubling the size and inference capability every [insert timeframe], revolutionizing communication and comprehension in unprecedented ways." (generated by ChatGPT)
[1] "a cliché and phrasal template that can be used and recognized in multiple variants", https://en.wikipedia.org/wiki/Snowclone
Edit: I have no idea why anyone would downvote a link to this article. It directly answers the question with a decent level of technical detail. We are nowhere near single atom sized features yet, despite what node names might lead you to believe. There's still quite a ways to go.
What is definitely over is Dennard scaling. As transistors got smaller it used to be possible to reduce the current used to drive them. That in turn made it possible to increase the clock frequency without frying the chip. Heat dissipation is proportional to the frequency and drive current. It's not possible anymore because you have leakage current and other parasitics (electrical noise essentially) that does not scale with transistor size. In the past you could take a 486 dx, overclock it from 25 to 50MHz and it would "magically" get about twice as fast. That is not possible anymore and chips are unlikely to ever run much faster than 5GHz.
However, Moore's law still provides performance because you can fit more cores, larger caches, specialized circuits, SIMD units, etc, on the same chip.
People have been predicting its end for a long time.
Note also that it's about transistor cost, not about cpu performance - people sometimes think it is because performance used to be more correlated with transistor count.
I remember reading in a magazine when I was a kid that Pentium 4 Extreme failed to reach 4.0 GHz in 2003 or 2004.
Since then, it took Intel quite some years to hit 4.0 GHz. Instead, the industry shifted to multi-core CPU, starting with the Core 2 series.
Does multi-core CPU count? I would say it's a bit of a stretch. It's more about horizontal scaling, where multi-CPU or even cluster also work in similar ways - there's no hard limit on how many CPUs you can add as long as you can cool them down. You can also make it much larger and sparse then put it in a large box to deal with the heating problem.
P.S. From the perspective of programming paradigm, people would then find "share nothing" and "message passing" is the way to harness concurrent and multi-core programming, after getting burned again and again with shared memory. These disciplines of not sharing RAM would further make multi-core more like programming on multi-CPU or clusters.
Let's measure transistor in a chip without caring about die size, so you can just use a larger die size measurement to keep the Moore's Law narrative alive. Well at some point that wont work because your maximum die size is still ~840mm2 due to reticle limit.
Then what? There is Chiplet, or what about you package all the die together using CoWos or EMIB? Yep. More transistor per "Chip" because the definition of Chip just changed for Die to multi die.
Or finally another media narrative, or Intel, AMD' PR or even how Jim Keller uses it. Any continuous improvement in transistor density per mm2 is consider as following Moore's law.
>So what's the consensus around here?
Generally speaking HN is very poor source of information on anything Hardware. I would use any consensus on HN as final say on the subject.
But even during the Dennard era there were a bunch of big random innovations needed to keep things going. CMP allowing the number of metal routing layers to balloon, keeping distances under control. Damascene metals allowing much finer metals carrying heavier currents. Strained channels for higher frequency and better balance between P and N. Work-function-biased fully depleted transistors to avoid the stochastic problems with doping small channels. Etc.
So what really happened is not that Moore ended. We still have a wealth of random improvements (where "wealth" is the driving force) which contribute to an emergent Moore improvement. But the large change is Dennard ended, which gave us scaling at constant power. Although some of the random improvements do improve energy efficiency per unit of computation, they are not overall holding the line on power per cm2. At the end of the classic Dennard we were around 25W /cm2 but now we commonly have 50W in server chips, and there are schemes in the works to use liquid cooling up to hundreds of W / cm2.
Well, ok. But does that kill Moore? Not if it keeps getting cheaper per unit function. And by that I do not mean per transistor. But as long at that SOC in your phone keeps running faster radio, drawing better graphics, understanding your voice, generating 3D audio, etc., and is affordable by hundreds of millions of consumers, Moore remains undead.
People are starting to move to getting performance improvements by increasing chip sizes and power budgets - part of the reason why GPUs are more expensive than they used to be.
"The complexity for minimum component costs has in creased at a rate of roughly a factor of two per year (see graph on next page). Certainly over the short term this rate can be expected to continue, if not to increase."
1. https://www.intel.com/content/www/us/en/newsroom/resources/moores-law.html
2. https://download.intel.com/newsroom/2023/manufacturing/moores-law-electronics.pdf
I’m excited about photon-based processors, but until that’s a reality we still have a ton of headway for application-specific scaling.
If you rip specific loops out of a general purpose CPU, there are still plenty of gains to be made!
https://firstmonday.org/ojs/index.php/fm/article/view/1000/9...
So don't fall for software vendors that want to convince you that you need a faster CPU every x year. You don't.