The Unsustainability of Moore's Law
bzolang.blog
bzolang.blog
This seems improbable.
50-year-old technology works because 50 years ago, transistors were micron-scale.
Nanometer-scale nodes wear out much more quickly. Modern GPUs have a rated lifespan in the 3-7 year range, depending on usage.
One of my concerns is we're reaching a point where the loss of a fab due to a crisis -- war, natural disaster, etc. -- may cause systemic collapse. You can plot lifespan of chips versus time to bring a new fab online. Those lines are just around the crossing point; modern electronics would start to fail before we could produce more.
I recently bought a new MacBook, my previous one having lasted me for over 10 years. The big thing that pushed me to finally upgrade wasn’t hardware (which as far as I could tell had no major issues), it was the fact that it couldn’t run latest macOS, and software support for the old version it could run was increasingly going away.
The battery and keyboard had been replaced, but (AFAIK) the logic board was still the original
which is very annoying, as none of the newer OS versions has anything that warrants dumping hardware to buy brand new to run them with! With the exception of security upgrades, which i find dubious for a company to stop creating (as they would need to do so for their newer OS versions just as well, so the cost of maintaining security patches ought to not be much, if at all), it is definitely more likely to be a dark-pattern to force hardware upgrades.
https://lore.kernel.org/lkml/20250425084216.3913608-1-mingo@...
https://lore.kernel.org/lkml/CAHk-=wicfBCyMj_x5BiL32o55jqXfn...
https://lore.kernel.org/lkml/CAHk-=wjCiEk-kc-vOug2GKJdhHKce3...
As long as there are enough users of some hardware, free software will support it, because the users of that hardware want it to.
Also he said that software from third parties also don’t support the older OS so even if Apple did provide security updates, he would still be in the same place.
The screen on the MacBookPro10,2 is 2560x1600 which is still higher than a lot of brand new laptops. The latest version it will run is 10.15 from 2019. I know Apple switched to ARM but most people don't need a new faster computer. I stopped buying Apple computers because I want my computer supported more than 6 years.
I do have 3 newer computers but these old Macbooks are kept at various relative's houses for when I visit and wnat my own Linux machine. They have no problems running a web browser and watching videos so why replace them?
That statement absolutely needs a source. Is "usage" 100% load 24/7? What is the failure rate after 7 years? Are the failures unrepairable, i.e. not just a broken fan?
I think it was about 15 years back they stopped saying that. Once we passed the 28nm mark it started to become apparent that they couldnt really state that.
It makes sense, as parts get smaller they will get more fragile from general usage.
With your GPUs yeah they are probably still fine but they could already be half way through their life time, you wouldnt know it until failure point. Add in the silicon lotto and it gets more complicated.
I design chips in modern tech nodes (currently using 2nm). What we get feom the fab is a statistical model of device failure modes. Aging is one of them. When transistors gradually age they get slower sue to increased threshold voltage. This eventually causes failure at a point where timing is tight. When will it happen varies greatly sue to initial conditions, exact conditions the chip was in(temp, vdd, number of on-off cycles, even the workload). After an agong failure the chip will still work if the clock freq is reduced. There are aging monitors on-chip sometimes which try to catch it early and scale down the clock.
There are catastrophic failures too, like gate insulator breakdown, electromigration or mechanical failures of IO interconnect. The last one is orders of magnitude more likely than anything else these days.
For graphics, the same defect could be severe enough to completely render the GPU useless.
By 'Modern' they must mean latest generation, so we'll have to wait and see. I was imagining not using an RTX 5090 for 7 years and find it doesn't work, or one used 24x7 for 3 years then failing.
Though, it can be solved with redundancy at the cost of performance.
The silicon gates in GPUs just don’t wear out like that, not at that timescale. The only thing that sort of does is SSDs (and that’s a write limit, which has existed for decades, not a new thing).
since electromigration is basically a matter of long, high-current interconnect, I guess I have been assuming it's merely designed around. By, for instance, having hundreds of power and ground pins, implying quite a robust on-chip distribution mesh, rather than a few high-current runs.
But it someone is running an LLM 24 hours a day, might not go for as long.
We are flying blind, both on those claiming short life span and those who are not.
https://duckduckgo.com/?t=ffab&q=gpu+lifespan&ia=web
You'll need to scroll past the ones talking about obsolescence versus failure. Toss in 'data center' if you like.
You'll see a range of numbers -- including some lower than I cited -- but it's all in that ballpark.
I seriously doubt this is true. The venerable GTX 1060 came out 9 years ago, and still sees fairly widespread use based on the Steam hardware survey. According to you, many (most?) of those cards should have given out years ago.
what is the age-related failure mode you're referring to?
or are you merely referring to warranty period? (which has more to do with support costs, like firmware - not expected failures.)
This is absolutely ridiculous. Even if Taiwan sank today we really don't need those fabs for anything critical. i strongly suspect we could operate the entire supply chain actually necessary for human life with just z80s or some equivalent.
Dual ported TCAM memory isn't getting faster and we've got to 1,000,000 prefixes in the internet and ipv6 are 4 times bigger. Memory speed is a real issue.
Dont mistake technical viability for economic viability.
We're on 8 as a mixture of fast and slow, hot and cool, on almost all personal devices now. I routinely buy Intel instruction racks with 16 per CPU construct, and a TB of memory. At one remove, chips seem to be fulfilling my mission but I am not in GPU/TPU land. Although I note, FPGA/GPU/TPU seems like where a lot of the mental energy goes these days.
VLSI is a black art. Quantum effects are close enough to magic I feel confident saying few people today understand VLSI. I know I don't, I barely understand virtual memory. I ache for the days when a zero pointer was a valid address on a pdp11
As interesting as this breakdown of the current state of things is, it doesn’t tell us much we didn’t know or predict much about the future, and that’s the thing I most wanted to hear from an expert article on the subject, even if we can take it with a large pinch of salt.
>software is getting slower more rapidly than hardware is becoming faster.
>Wirth attributed the saying to Martin Reiser, who in the preface to his book on the Oberon System wrote: "The hope is that the progress in hardware will cure all software ills. However, a critical observer may observe that software manages to outgrow hardware in size and sluggishness."
I wish that there would be more instances of developments like to Mac OS X 10.6, where rather than new features, the software was simply optimized for a given CPU architecture, and the focus was on improving performance.
No it's not :)
Phones do not shut down. Powering off and back on still takes forever.
As for desktops, Windows at least keeps starting stuff in the background long after your UI gets displayed.
My windows machine can go from completely powered off to a big application like a web browser fully open and operational on maybe 10-15 seconds, and yes, fully powered off. No way I’m making coffee in that time. Sure, windows might run stuff in the background, but it’s so fast that stuff doesn’t get in the way of me using the thing at all.
As for phones, “forever” is a silly thing to say but even if I granted you that one off boot time, you have somewhat moved the goalposts as you talked about the act of using software in day to day usage. On my laptop I can genuinely open 10 apps, close 10 apps, and open 10 apps again all within 10 seconds, probably faster if I wasn’t constrained by literal click actions. My computers growing up would grind to a halt if you tried to run like 3 things at once!
There are always instances of inefficient software, but there was back in the day too, I remember generating a new map on civilisation 1 on my 286 and it taking 10 hours. There is no way you can possibly say that on average software is slower today than it used to be, that statement in general is just completely false.
And oh yeah, 100% I agree SSD’s are a huge factor as to why software runs faster now than it used to on average for day to day activities. Thanks for mentioning one of the things that helps demonstrate my point.
But it is not the only thing, that’s for sure. I can think of a few other critical things that made usage of computing faster over the years, and I bet you can too.
Partially unrelated but I once downloaded anime on dialup, used to take 30 hours per episode at low quality…
Humm. If my glasses are rose tinted, yours are black tinted. I've played quite a lot of civ 1, even on an xt with 8088, and i'm pretty sure map generation did not take 10 hours.
Perhaps if you hacked yours to use larger maps...
I'm also pretty sure civ 1 got to the menu on my 8088 faster than Death Stranding 2 on my ps5. Although that might be my rose tinted glasses indeed. Civ 1 also didn't have a 29 Gb day one patch :)
Which… by default… means I’m you’re going to have a lot of trouble asserting your “everything is slower now” point, if you see my point ;). I may also have to accept I can’t assert necessarily that everything is faster now. Fortunately I don’t really need to, as I am happy to restrict my point to simple activities, such as web browsing and such, but that’s by the by.
And to answer your question I don’t remember why it took quite so long to generate civ 1 maps, but I have a vague memory of trying to do weird things with the maps with my dad, so perhaps they were larger or there was some generation mod but I honestly couldn’t tell you my memory is too fuzzy. I do remember the copy protection that required looking up words in the manual though…
But there is something to be said about prior optimizations in limited resources. A few months back a friend was restoring a G4 iMac and I was astounded at how snappy the whole thing felt once the OS had finally loaded.
We forget how snappy iTunes was while using only 30MB of RAM.
If you can combine the best of boths worlds, there could be something special there.
Modern OS and software are very bloated but it is astounding how fast the hardware crunches through all that. But it could be better.
We haven't been bound by moore's law because we just waste computing power because programmers are expensive. No one is trying to optimize nowadays except in very niche places. And when push comes to shove we just start wasting slightly less. Like adding a JIT to a script language 15 years too late.
Like seriously that they have just gone all in on higher end hardware for Doom Dark ages was kind of disappointing.
Doom 2016 runs at almost 60fps on a Pentium 4!
The one title that did impress me was ’Humanity’but that uses a heavily modifed Unreal 4 engine, but it all runs very smoothly on limited hardware because of some smart design choices.
Given the power and ubiquity of smart phones, most people don't need any other computer in their personal life. What can be done locally on a smart phone seems like it will be more constrained by battery life and physical size than anything else, and there will continue to be a mix of things that can run on-device and other more compute-hungry functions run in the cloud. I don't see smartphones being replaced or augmented by other devices like smart glasses - people want one device that does it all, and not one they wear on their face.
The same is somewhat true for business use too, especially if compute-heavy AI use becomes more widespread - some functions local and the heavy work done in AI-ready datacenters. I'm mildly surprised that there hasn't already been a greater shift away from local compute to things like Chromebooks (ubiquitous in schools) since it has so many benefits (cost, ease of management, reduced need to upgrade), but maybe it will still come if the need to rely on datacenter compute increases.
Even if we imagine futuristic power-sipping neuromorphic chips, I don't see that changing things very much other that increasing the scope of what can be done locally on a power budget.
Maybe, but they need other form factors, too. Like a big screen and a keyboard.
And once you have those, you might as well through some compute in there: getting smartphone-like performance out of desktop-like components (or even laptop components) is pretty cheap, so might as well throw them in.
Chromebooks are fairly capable 'thin' clients. Their specs aren't that much worse than other laptops.
However all that being said, I mostly agree that at least with current style AI we will likely see a lot more data centre compute in the future. At least as long as hardware costs are a significant fraction of total costs: the 'cloud' can multiplex multiple users over expensive hardware, your local computer is mostly idle and waiting for your input. (And it has to be, if you want low latency.)
However, if costs shift so that electricity and not hardware is the main cost, we might see a return to local compute. Maybe.
It seems generational habits are changing. TV is dead, and younger generation seems ok watching things on small screens, even smartphone. Can always sync phone to parent's/hotel big screen TV if available.
For users, a few hundred dollar extra ( on top of the original purchase ) is a such a small number compared to the productivity gain over the usage span of the computer.
AI alone not only increased the server hardware requirement but also user client requirement. It is basically the question everyone has been asking, what is after Smartphone? And to a degree it is AI. ( or LLM )
This will easily push the whole Semi-Conductor Industry forward all the way to 2032 ~ 2035. We will be at 8A or 6A by then.
PCIe 7? possibly PCIe 8? WiFi 9 which is a fixed version of WiFi 8. There are so many great Hardware improvement coming out all because of the demand of greater computing usage.
Software side has been rather boring TBH. I really like the phase Allan Kay uses to describe modern days software are "reinventing the flat tire".
We must live in very different worlds. Most people I know absolutely hate it and are immediately put off by anything that tries to force it in.
I am not AI but it needs to be used purposefully rather than just another check box to the feature set.
Productivity gains for some, needless slop for others.
For something more substantial than an anecdote, 92% of UK students use AI: https://studenttimes.org/news/uk-students-turn-to-ai-in-reco...
Re garage invention: lithography is probably too big an issue for that. It's important to keep in mind that we're currently producing a lot of transistors with today's tech. Any alternative would have to match that (eg stamping technologies).
(I work on lithography optics)
that... isn't the moore law, it is about count / complexity, not density. and larger chips are a valid way to fullfill it.
https://hasler.ece.gatech.edu/Published_papers/Technology_ov...
https://www.eng.auburn.edu/~agrawvd/COURSE/E7770_Spr07/READ/...
> the density of transistors that can be fit onto a silicon chip doubles
the whole article takes off from a flawed and fantasious misinterpretation and argue against that self created windmill
Wikipedia, referencing his original paper:
"The observation is named after Gordon Moore, the co-founder of Fairchild Semiconductor and Intel and former CEO of the latter, who in 1965 noted that the number of components per integrated circuit had been doubling every year,[a] and projected this rate of growth would continue for at least another decade. In 1975, looking forward to the next decade, he revised the forecast to doubling every two years, a compound annual growth rate (CAGR) of 41%. Moore's empirical evidence did not directly imply that the historical trend would continue, nevertheless, his prediction has held since 1975 and has since become known as a law.
I literally linked the paper. The paper doesn't mention density.
"First three website you found on Google"'s opinion don't matter for a lot when we have the original formulation, right there, archived
And Wikipedia passage you quoted doesn't mention density either, only count.
I really, truly don't understand where your comment is coming from and going to.
Clearly what is driving advances in compute nowadays is not single-chip transistor density but instead multi-chiplet datacenter processors and much higher level multi-chip connectivity such as TPU pods and AI datacenter designs.
1) exponentially decreasing cost per transistor and
2) exponentially decreasing power consumption per transistor.
However, in recent years 1) has generally weakened. At some point, the price per transistor will no longer decrease for smaller process nodes, and even start to increase. Then making smaller transistors could only be justified for power constrained chips that benefit from 2). But even this has only limited value.
So at some point, producing chips with smaller transistors will no longer make economic sense, even if transistor size could technically still be decreased at a similar rate as in the past.
As the article points out, Moore's Law was principally about the number of features. Today, the "Intel ISA" portion of one of their CPU cores is dwarfed by caches and vector & machine learning processing facilities devoted to that same core. Off-chip memory access and other I/O is still a huge factor for why we don't have 10 GHz processors yet. These days we are devoting silicon resources to slowing things down - due to previous performance designs that turned out to have flaws (SPECTRE, Meltdown, etc).
The features per nm just keep on a-coming.
The most persuasive argument is the one that he puts in the beginning; at the current rate, we are fast approaching the point where there are no companies left who can afford a new fab.
You're on air cooled silicon. You were never going past 4GHz in this configuration. This was an understood limit well before we hit it.
> How small or fast or efficient a transistor can be made in a lab is of absolutely no relevance if they can’t be mass-manufactured at a price anyone is willing to pay.
Here’s how:
S-Well = Symmetric Inversion CMOS n/p wells are asymmetrical by default—different V<sub>th</sub>, different μ. That imbalance kills any attempt at clean energy recovery. HeartMOS fixes this with a balanced doping profile (p+ base, tilted retrograde n/p implants) to hit matched threshold voltages and drive currents. That’s symmetric inversion—engineered for resonance.
Fast, Not Fragile Instead of RC step waves (CMOS square pulses), HeartMOS runs trapezoidal φ/¬φ waveforms at 6GHz, 8-phase pipelined. Think smooth clock rails, not bang-bang toggling. Less dV/dt = less heat = no thermal throttling. It’s not just efficient—it’s sustainable at scale.
Bottom line: Adiabatic ≠ slow. Asymmetric inversion = slow. Symmetric = harmonic = fast.
Patent Pending – “HeartMOS™ — Symmetric Semiconductor Device with Co-Optimized Doping for Reversible Computing” https://sites.tufts.edu/tcal/publications/hotgauge/
That's... not how this works at all. Eventually the depletion region where the positive or negative charge carriers (for p or n doped silicon) deplete far enough and then at the threshold voltage inversion happens when the opposite sort of charge carrier start to accumulate along the oxide and allow conduction. By surrounding the channel there's less space for a depletion region and so inversion happens at lower voltages, leading to higher performance. Same as people used to do with silicon on oxide.
The Wikipedia article has nice diagrams:
That means that the channels are inherently intrinsic. You can't really have doping when there's statistically less than an atom. There's a nice review from 2023.
https://semiengineering.com/what-designers-need-to-know-abou...
https://www.semiconductor-digest.com/the-shape-of-tomorrows-...
This is more recent with pretty pictures.
The key is that all increases in transistor count are now based on either stacking layers in the silicon (like flash scaling), stacking die with chiplets (we're already at 12-16 die for HBM) or scaling beyond the reticle limit (there's a lot of investment in larger substrates right now). None of these help cost scaling and all have huge yield challenges.
Moore's law really ends when the investors and CFOs decide it does. The generative AI boom has extended that for a while.
that is, ML is about periodic shrinks producing squared improvements to device density at iso-area, and thus costs. if you have to change equipment, ML (in this narrow sense) is out the window. if you have to spend linear resources to stack die or chiplets, that's also not ML-compatible (because linear, not 1/(shrink^2))
vertical flash is interesting because it appears to scale surprisingly well - that is, extra layers don't seem to exponentially degrade yield. I'm not sure any of that applies to logic, though.
https://www.chipstrat.com/p/what-happens-if-tsmc-controls-it
My feeling is that algorithmic improvements to LLMs may continue for another order of magnitude or two though. That could continue the scaling for a while.
Of course fixed development costs are now over $1B at 2nm, so if you're not making a large number of die (>1M at $1k/ea), it makes no sense to scale.
Here’s how:
S-Well = Symmetric Inversion CMOS n/p wells are asymmetrical by default—different V<sub>th</sub>, different μ. That imbalance kills any attempt at clean energy recovery. HeartMOS fixes this with a balanced doping profile (p+ base, tilted retrograde n/p implants) to hit matched threshold voltages and drive currents. That’s symmetric inversion—engineered for resonance.
Fast, Not Fragile Instead of RC step waves (CMOS square pulses), HeartMOS runs trapezoidal φ/¬φ waveforms at 6GHz, 8-phase pipelined. Think smooth clock rails, not bang-bang toggling. Less dV/dt = less heat = no thermal throttling. It’s not just efficient—it’s sustainable at scale.
Bottom line: Adiabatic ≠ slow. Asymmetric inversion = slow. Symmetric = harmonic = fast.
So we may have Apple and NVidia as the only ones that can afford to build a fab. Edit, correction, Microsoft is the current number 2 company by market cap.
Even one step lower in the chain, ASML sells prototypes of their new photolitho chip makers to the big chip houses years before they develop them. The chip houses understand that the first releases will require ASML engineers to babysit the new tech, patching design issues as they become visible through use.
That is a de facto joint venture.
https://www.livescience.com/technology/electronics/what-is-m...
since then, there have been some adjustments, but it still holds as a prediction of a general trend since as noted in that article:
>One reason for the success of Moore’s prediction is that it became a guide — almost a target — for chip designers.
but as noted:
>The days when we could double the number of transistors on a chip every two years are far behind us. However, Moore’s Law has acted as a pacesetter in a decades-long race to create chips that perform more complicated tasks quicker, especially as our expectations for continual progress continue.
I'm waiting somewhat impatiently for AtomicSemi to make some announcements.
> We’re entering the post-Moore era, I’m busy designing chips (and maybe a fab) for this new world. I’d be happy to talk to investors.
We were told in uni in the early 2000s that post-Moore era was just few years from then.
Which did roughly end in the mid 2000s. That's why we've spent so much time parallelizing in the past 20 years rather than just expecting increases in single threaded perf
They just have to deal with less efficiency and higher maintenance costs. You have not discovered a free lunch, sorry.
Ultimately, there's a cap. For as far as I know, the universe is finite.
I don't think we know that. We don't even know how big the universe really is - we can only see so far. All we have is a best guess.
There may also be a multiverse out there (or right beside us).
And, creating universes might be a thing.
... I don't expect Moore's law to hold for ever either, but I don't believe in creating unnecessary caps.
As I understand it Moore's Law doesn't address any sort of fundamental physical limitations other than perhaps an absolutely limit in terms of some fundamental limit on the smallness of an object, it's just an observation of the doubling of transistor density over a consistent period of time.
It seems more like an economical or social observation than a physical one to me.
We don't know what we don't know - there's always the potential of radical technology coming from an upending of things which were 'established' for decades or centuries previously; that's just the nature of science.
"In the usual models" - that's the whole point. For the entire 60 year history of Moore's Law, the "usual models" have stated that it would come to an end in about ten years.
https://en.wikipedia.org/wiki/Moore%27s_second_law
> Rock's law or Moore's second law, named for Arthur Rock or Gordon Moore, says that the cost of a semiconductor chip fabrication plant doubles every four years.[1]
Roughly every two years, the density of transistors that can be fit onto a silicon chip doubles.
The complexity for minimum component costs has increased at a rate of roughly a factor of two per year.
Effectively, it was always more of a "marketing law" than an engineering one. Semiconductor chips only had 18-36 months to reap big profits, so Intel tried to stay ahead of that curve.
Yes, but the engineering still has to be feasible. If Henry Ford had coined a similar law about eg the power of car engines, that might have been interesting marketing, but it doesn't mean Ford and the car industry could have sustained that for as long as Moore's law held.
https://hopefullyintersting.blogspot.com/2019/03/what-is-moo...
especially after describing all the other desperate scaling techniques in the past - and that history argues for the need (almost manifest destiny in the ML sense) to do these things.
https://en.m.wikipedia.org/wiki/Moore%27s_law
It tells us more about market and ppl's hunger for apps/cabilities than fabrication and physics, although fabrication quality is indirectly related through cost.