ASML EUV lithography machine could keep Moore’s Law on track
spectrum.ieee.org
spectrum.ieee.org
This is incredible and feels like the most sci-fi sentence I've read in a long time.
It's unbelievable to think that this works, not just in a lab, but in commercial systems that will produce hundreds of chip wafers an hour (>100 anyway, they didn't clarify further).
>Hynix reported at the 2009 EUV Symposium that the wall plug efficiency was ~0.02% for EUV, i.e., to get 200-watts at intermediate focus for 100 wafers-per-hour, one would require 1-megawatt of input power
https://en.wikipedia.org/wiki/Extreme_ultraviolet_lithograph...
It's an damn good question of how much further this can scale. EUV photons are a lot more like x-rays than they are visible light. They're energetic enough now they're inflicting ionization effects on photoresist material, blurring the exposed area with secondary electron scatter. The fundamental limit of electronic transistors, ones made out of single molecules, are going to be tough to make with lithography.
Many semiconductor manufacturers have folded, dropped out, or merged over the years due to costs putting development of the next node out of their reach. If the remaining 3 drop out of the race, they will be following the same pattern as many before.
Maybe it will make sense for mobile SoCs or some other energy constrained applications which benefit from lower power draw of smaller process node chips. But power efficiency can outweigh lower absolute performance only to some degree.
I'm not talking about the marginal cost to make the device, I'm talking about the R&D and capital expenditure to develop and build the machines for the next node.
You can be reductive and say it always boils down to competition, but then you would also say that ultimately shrinking will end when it can no longer compete with mature nodes. Competition in both cases. So I'm not sure what exactly that's getting at.
> If it soon goes up significantly, it will stop to make economic sense to increase transistor density any further. Why pay the same amount of money for a less powerful chip?
That's not strictly true, performance of a transistor still has value. Companies like Apple pay premiums to get in early on leading edge nodes, more per device than the mature nodes they move from.
> That's not strictly true, performance of a transistor still has value. Companies like Apple pay premiums to get in early on leading edge nodes, more per device than the mature nodes they move from.
Apple can't increase the price of their product arbitrarily. So if the price per performance increases, the new iPhone would be slower than the old one. Maybe people will still buy it if it has better power efficiency, but that is a trade-off which has its limits.
Not arbitrarily, but IIRC Apple's profit margin on iPhones is over 100% - the iPhone 14 Pro max is supposed to have a BoM cost of ~470 $ and retails for well over 1000$. That means Apple can both afford the high upfront premium/R&D cost of going to a smaller node and to eat up higher SoC costs and yet still have a profit per unit that would lead most other companies' CFOs to drool.
On top of that, even if the economics should not work out for mobile... a fully spec'd out M2 Ultra Mac Pro runs at ~14.000$, Intel ones IIRC could reach 50.000$. The crowd that pays such absurd prices has zero problems paying a grand or two more for higher performance.
No, why? Lots of foundries out there that don't compete on leading edge nodes.
> Apple can't increase the price of their product arbitrarily. So if the price per performance increases, the new iPhone would be slower than the old one. Maybe people will still buy it if it has better power efficiency, but that is a trade-off which has its limits.
That doesn't address what I said -- that price per transistor is not the single limiting factor. I never said any performance increase is worth infinite value.
The discussion was about Moore's law ("scaling down"), which is only about the leading edge.
No, the point was that the leading edge will stop advancing when it can no longer compete economically with companies that sell mature nodes. Which is obvious, but I was just being similarly reductive.
> The point is that they will stop scaling chips before technical limits are reached.
Sure, like most commercial ventures, cost becomes prohibitive at some point and overtakes benefits. As it always has been.
The "mature node" here will just be the one before the first node that doesn't make economic sense anymore. And this will be from a leading edge company, most likely TSMC. Say, if 2nm is too expensive compared to 3nm, then TSMC will stick with 3nm.
https://www.sec.gov/Archives/edgar/data/937966/0000937966220...
But when it comes to cost, evidently replacing many passes and other complicated processes with DUV machines with fewer EUV passes is a net win. And the energy required to create these chips must be a small fraction of the energy they will use in their lifetimes, so improved efficiency of the smaller nodes enabled by EUV would surely be a win, all else being equal.
Aren't those tuneable to any wavelength down to X-rays?
> Wavelength 0.05 to 4.7 nanometres
- https://www.xfel.eu/facility/overview/facts_amp_figures/inde...
which is sufficient and possibly excessive.
Not that I know anything about any of the other considerations in such things. Is 3.4 km "too big"? Is €1.22 bn "too expensive"?
https://iopscience.iop.org/article/10.35848/1347-4065/acc18c
> This form of maskless lithography has high resolution but low throughput, limiting its usage to photomask fabrication, low-volume production of semiconductor devices, and research and development. [1]
The beam has to scan across the entire wafer instead of exposing it all at once, so it's extremely slow and uneconomical for mass production.
You could conceive of making the speed up in parallel production.
F... yeah!
Kind of like (iirc) the tip of a scanning tunneling microscope might be used to pick up & manipulate individual atoms.
Self-organizing materials like DNA might make that process easier, not scale it down further.
(Typed on a device made by this process, which I still don’t quite believe.)
Once "gently" to deform it briefly into a concave shape, and the second, harder pulse to actually activate the droplet to emit extreme ultraviolet light
Asianometry on EUV. Skip to 10m50s. https://youtu.be/5Ge2RcvDlgw
Modern chip manufacturing is basically black magic.
This, if you ever want to feel wonder at things the human race can accomplish, lithography has to be in the top 3 reasons imo.
https://www.asml.com/en/technology/lithography-principles/li....
Just absolutely insane engineering going on there.
A short video showing the laser in action:
And that is sad part of so called "Tech" today. Zero appreciation of it outside of the minorities.
They are doing is on a massive scale, extreme precision, high cost of electricity, insane difficulty in both designing chips and production.
And yet HN thinks all the hardware chips today are over priced and absurdly expensive.
i.e. there absolutely cannot be any obligation to subscribe to the ideology of either team eddison or team westinghouse in order to make use of a light switch.
This has always been true of technology.
Do you think most people cared about how a steam engine worked, or simply that it allowed them to go faster than a horse? Or the telegraph, radio, television, the internal combustion engine, etc.
“Physics of laser-driven tin plasma sources of EUV radiation for nanolithography” (2019) https://iopscience.iop.org/article/10.1088/1361-6595/ab3302
That's why ASML doesn't have any competition: everyone else gave up.
Alternatives were tried. Synchrotron EUV sources. (works, but huge). Linear accelerators (The SLAC beamline was used as a light source as a test). X-ray lasers (don't work yet). Electron beam lithography (works, but too slow.)
There's got to be a better way to do this.
EUV masks are made that way, slowly.
Think 'boxes in boxes' to get maximum insulation. I also have a friend who works in this industry and he once joked that they have an almanac built in to deal with moon tides and while it is a funny joke you have to wonder if there isn't going to be a time when even that sort of effect will have to be accounted for. Amazing stuff.
ASML is one of a short list of Dutch companies that I'm super proud of, they keep on innovating no matter how extreme the challenges are. The moat they have is incredibly deep.
[1]: https://arstechnica.com/science/2020/07/ligo-is-so-sensitive...
(3.47mm per month)/(30 * 24 * 60 * 60 seconds) = 1.33nm/second
The Pratt and Whitney Jig Borer was hitting 50 microns... in 1928. See https://img.photobucket.com/albums/v337/johnoder/8PiecesofIr...
Knowing that a silicon atom is larger than 0.1 nm, how can we possibly keep Moore's Law on track? It feels like we're close to hitting fundamental limits.
Any insights would be much appreciated. Thanks!
If there’s hope for the future, it’s that there are many other computing technologies besides traditional silicon that show potential, so maybe the torch will be passed to quantum, or superconductors or dna or something else.
[1] https://en.wikipedia.org/wiki/Limits_of_computation
[2] The ~12 watts computer inside each living human adult skull (and perhaps each eukaryote cell [6]) is still the state-of-the-art, for quite some time.
[3] 2021, Jim Keller: The Secret to Moore's Law, https://www.youtube.com/watch?v=x17jIKQf9hE
[4] 2019, Jim Keller: Moore’s Law is Not Dead, https://www.youtube.com/watch?v=oIG9ztQw2Gc
[5] 2023, Change w/ Jim Keller, https://www.youtube.com/watch?v=gzgyksS5pX8
[6] Our computers aren't yet able of polycomputation, where the computation topology, data, and functions depend on the observer, instead of computation in a passive implementation, once done forever set in s̶t̶o̶n̶e̶ silicon, 2023, Michael Levin, Agency, Attractors, & Observer-Dependent Computation in Biology & Beyond, https://www.youtube.com/watch?v=whZRH7IGAq0
[1] https://geohot.github.io/blog/jekyll/update/2023/04/26/a-per...
[2] https://en.wikipedia.org/wiki/We_choose_to_go_to_the_Moon
It's precisely this penny pusher rhetoric which in the end will make China win, deservedly so.
[1] https://www.simonandschuster.com/books/The-Man-Who-Broke-Cap...
For the rest I often wonder if would not be better for the environment to re-purpose older, already made tech.
Plenty of embedded systems grinding on for a long time.
And user facing applications lack one thing: public stats of peak system usage. When confronted with a new purchase we should be handed over a sheet of our own and peers statistics. Producers and service providers have them anyway.
In an ideal world, the cost of everything we buy would include the real costs of pollution (including greenhouse gases), depletion of common resources such as water, and recycling or otherwise accounting for the environmental impact after use.
As you say, suddenly those 5 year old phones and computers would be economically attractive again. With a knock-on effect that websites and software would cater more for older devices.
But we don't live in an ideal world. We live in a literal Tragedy Of The Commons (https://en.wikipedia.org/wiki/Tragedy_of_the_commons).
Note that I'm not at all saying that we shouldn't have companies like ASML researching processes like this - more efficient chips are good for the environment and the economy.
Something containing ~100k transistors, ~10KB RAM & flash, running at a few MHz in a power envelope measured in milliWatts, has production cost (and environmental footprint) of practically 0 these days. But still enough brains to control your washing machine, monitor solar panel or open garage door w/ remote.
A few steps up & you have epaper equipped tablet that allows you to read books, simple games or check weather forecast, doing so for days or weeks on battery power.
On the other end of the scale you have datacenters, supercomputers & their energy + manufacturing footprint. With desktop PC's, laptops & game consoles somewhere in between.
When choosing between:
a) Apply budget, see how much CPU, GPU, RAM etc. that buys you, and deal with physical size + power draw / thermals, these days I go for
b) Pick physical size + power budget, see what kind of CPU / GPU / RAM etc you can shoehorn in there @ what cost, and just deal with the limitations of such device (if perceived as limiting, that is).
It's amazing what a Raspberry Pi sized computer (or further down, a modern uC) can do these days. Lean software does exist. No clunky desktop needed if you just want to play PacMan. :-)
It is. https://www.lowtechmagazine.com/2020/12/how-and-why-i-stoppe...
I think I've listen to asianometry (YT channel) talk about this too, but I am unable to find any clip now where he explicitly talks about interference lithography...
The one thing I can answer is that multi-patterning does not shine light through two masks simultaneously. Instead, it consists of multiple separate steps.
I think for the rest, the point is that light arriving on the waver is not a binary thing, but due to refraction and self-interference light arrives in variable intensities. So within difficult constraints, this allows you to control the area in which the intensity is below our above certain thresholds. I assume that if you then manage to control the chemistry just right, you can then produce features that are smaller than the wavelength of the light -- under severe constraints of what shapes you can produce. You definitely do not get to produce an arbitrary bitmap of sub-wavelength pixel size.
then again, it's called the wave-lenght, not the wave-width
If you drag a baseball bat through sand, the edge of the cut "channel" is much sharper and narrower than the baseball bat.
Now offset the baseball bat a bit and draw another line which is partially overlapped over the first one. You will get the intersection of the two baseball bat wide channels, but it will be much narrower.
The standard computer configuration has been stuck at 8 GB of RAM and 256 GB of SSD storage forever.
Maybe it was different where you live. That's OK.
I am talking about the memory and storage configuration of the "typical" computer that an average consumer will buy from a big box store or a website. This has been 8GB/256GB SSD for a long time now. That is my source of complaint. Growing up in the 80s and 90s there would be absolute leaps in memory and storage every time you would upgrade your computer. That is no longer the case. We are just now starting to see some 16GB/512GB configurations appear on consumer default configurations after what, almost a decade?
Your story gets even weirder! Sourcing components from the local brick and mortar store when building your own desktop usually negates most of the benefits of building your own desktop computer. It's not entirely surprising that they had an excess of outdated SSDs on display.
> Plenty of people had laptops, sure, but most daily-driver work machines were still desktops.
Are we suddenly confining the discussion to corporate-owned office PCs, or do you genuinely not understand that laptops have been outselling desktops for a very long time?
For locally playing with AI, those are a joke. A beefy desktop gpu, preferably with 24GB vram, a nice desktop high threaded cpu. 64GB of ram and as many TB of fast M.2 storage you can afford is the starting point.
Those OSS LLM models will eat your typical enthusiast gaming PC for breakfast.
I don't know, I've been working with LLMs a lot recently and for the first time in a while I am wishing I had access to much more compute than I do. Imagine having the power of a H100 locally without having to pay thousands of dollars a month.
I hope that AI hype lead us to more memory and more memory bandwidth, because they are really lagging behind computer power increase from like 15 years already.
One approach would be to snip RAM in as many pieces as you have cores, and attach each piece locally to a CPU core. Say eg. 1k cores each with 1/1000th of total RAM, accessible at L1 cache like speeds. Giving you crazy-high (combined) memory bandwidth. I know, there exist some IC's that actually do this.
Problem is such a setup is not suitable for all types of computation. For data structures that require individual cores to access other cores' local RAM, you still need some communication protocol (+ latency, bringing you back to square 1).
And we haven't quite figured out how to program such a beast in software developer-friendly way.
Hence the usual approach of "all RAM in one pile, connected via a fat pipe to a heap of CPU cores".
I think you can get a 2TB ssd for like a 100 bucks nowadays. They are dirt cheap.
Unless you're paying Apple for it :^). Hope you like 12x markup to go with your 1TB SSD :^)
I’m talking about the typical computer you’re going to find in a big box store or the default configuration on a website.
Yes you can add an SSD yourself for that price but the markup for configuring it at purchase is considerably more than $100. I’m not talking just Apple when it comes to this, Dell, Lenovo, HP, Microsoft, and just about everyone else do it too. RAM is even worse now that many (most?) laptops have it soldered in, so there is no DIY upgrade after you buy.
And the point about gaming setups is very relevant because you can get consumer hardware (aka cheap), instead of being forced into "workstation/server" which carries a huge markup.
You can get 128GB RAM and stupid amounts of ssd storage for cheap with consumer hardware.
The hardware hasn't stagnated at all. I think you're problem is simply with pre-built markups?
Also if you want a laptop, the markups for upgrading said memory and storage are actually pretty significant and may not be worthwhile. Upgrading laptops is quickly becoming difficult to impossible. Yes I know about Framework, but they are not ever going to be mainstream for a number of reasons.
From the cursory look to an e-shop, it seems to me that majority of notebooks have soldered-in memory, but also one SIDIMM slot for expansion. Just the very low-end ones (and Apple) have no SODIMM slot.
And 16 GB is definitely the most populous category of notebooks.
8GB - ~350
16GB - ~1060
32GB - ~550
I don't know about desktop PCs, but in laptops 8GB is not mainstream any more.
thou, 8gigs are overly common (and overrepresented in regard to your market analysis) as most consumers (and enterprises) tend to buy the low-end config unless it's absolutely necessary to spend more.
FPGAs do that, but the "smart" routing fabric in them makes compiling code to them take hours or days.
If you eliminate the switching fabric on an FPGA, you are left with a grid of Look Up Tables (LUTS) each connected to their neighbors. The result is a Turing Complete computer that works exclusively in parallel.
ASML: $287B
AMD: $182B
Intel: $154B
[0] https://www.reuters.com/technology/intel-orders-asml-machine...
No exclusivity, as it’s ASML business model to work fairly with all semiconductor manufacturers.
>Intel has announced that manufacturing of 18A-node chips will commence in H2 2024, six months ahead of schedule. According to a roadmap released last year, this node will be Intel’s first to employ high-NA lithography. It’s not clear whether this means that the next-gen EUV technology makes its debut in production a little earlier than expected. Last January, ASML CEO Peter Wennink told investors that he expected high-volume high-NA manufacturing to start in 2025 or 2026.
ASML high NA Credit: ASML ASML’s first high-NA system, the Twinscan EXE:5000, is fully production-capable, but chip manufacturers will initially use it for process development. The first unit will ship in H1 2023, with Intel on the receiving end. The US processor maker also placed the first order for the EXE:5000’s successor, the EXE:5200. The swift adoption of high-NA is an important element in Intel’s strategy to regain “unquestioned leadership” in the semiconductor industry by 2025.
[1]https://bits-chips.nl/artikel/intel-moves-high-na-node-up-6-... [2]https://www.tomshardware.com/news/intel-completes-developmen...
ASML is never going to tie themselves to a single customer like that, let alone one which isn't even the market leader. High-NA is a massive technological change, and all the major players have already ordered their machines. Intel was simply the first to complete their order in a desperate attempt to avoid a repeat of their EUV debacle, but they'll receive their new toy at most a month or two earlier than their competition.
I assume these will be made available to Intel Fab customers as well at internally to Intel, since they are opening up 3rd party fabrication at a service offering.
Even considering all of that the economics seem to have already stagnated in cost for performance.[1]
[1] http://databasearchitects.blogspot.com/2023/04/the-great-cpu...
[1]https://en.wikipedia.org/wiki/2_nm_process
But yeah, the fact that latest process nodes actually increase in cost is why people say "Moore's law is dead". Performance improves, but to keep the trendline roughly exponential, many things have had to give since the late 2000s. Such as: cost per wafer, power usage for max performance etc.
A somewhat simple 2x2 cm Si photonics Chip in my line of work takes about 24h exposure for two layers - a full scale wafer is hundreds of times larger, more complex, and has dozens of layers. The math, physics, and geometry just don't really work out (yet)
The limits of physics can be surpassed with parallelization.
Moore's law is a reflection of the private and business market's desire/need for ever greater efficiency.
There is no limit.
It does highlight some potential pitfalls. Chiefly the rapid decay of muons and dealing decay particles. Also you need a source of high energy protons.
Proton lithograhy anyone?
When the choice was made to go for EUV, E-Beam was actually the most mature technology available for next-gen lithography - but it just wasn't economically viable. The technology has remained in development over the years, but not a lot has changed yet.
If you want to know more about the topic, I can strongly recommend this video from Asianometry: https://www.youtube.com/watch?v=RmgkV83OhHA