I always feel like I'm not quite getting quantum stuff no matter how much I read and learn: what does this advancement have to do with quantum computers?
Don't worry about not grokking quantum computing stuff, neither do any of the people who invest in it as well as many people who work on it.
1. The OP has nothing to do with quantum computers.
2. Quantum computing deals in coherent quantum states: associated with N qubits there are 2^N complex amplitudes. You can measure by sampling the square-magnitude of the complex amplitude which turns it into a Probability Distribution. Quantum computing "gates" cause interference in the complex amplitude of entangled qubits cancelling out incorrect results, such that if you maintain coherence for long enough and sample the final state and measure the probability distribution, you get a computationally useful result. The key challenge in quantum computing is extending the coherence time of a larger and larger number of qubits, which is why you hear so much about quantum error correction. Recent results from Google showed a scaling law for "surface codes" using multiple qubits to create an error-corrected topological qubit with extended lifetime. There is no telling how far this scaling law will go, but as long as Gil Kalai is in the next room, it is unlikely there will be actual useful quantum computation for a while.
I’m sure they will license it. It’s better for them if everyone in the industry can innovate on everything around it. All the process tech companies will make it more cost effective, for instance, which helps IBM as well.
Broadly speaking yes, this is the business model. IBM has been at this for many years with technology transfers, licensing agreements, support and other arrangements. Rapidus, Samsung, GlobalFoundries, ST, SMIC, AMD, etc. have all used IBM R&D work at various times for various nodes and products.
The cutting edge of semiconductors is a writhing mass of copulating tapeworms, and IBM lives deep inside that ball. For IBM, what this means is that when you buy one of the ASML machines to make products with this process, you'll pay IBM for the knowledge and support to actually get it working, or give them a cut, or something else, TBD, as circumstances warrant.
Ah, thanks for that explanation. I was wondering how IBM could fund cutting edge research in semiconductors when they haven't been a semiconductor manufacturer for many years.
IBM regularly announces silicon breakthroughs like this but I'm not aware of those ever becoming products. Is IBM mainly in the business of licensing their technology to big silicon manufacturers with stuff like this? Is it just marketing for their consulting business?
IBM Z series mainframe Telum CPUs are designed by IBM but manufactured by Samsung. IBM no longer owns any fabs. I assume they have some kind of technology licensing deal.
It's a lab. It's where ASML brings up the prototype machine and gets it working, with IBM talent working out the problems and getting it ready for commercial operation. They won't make chips at scale there: the facility isn't designed for that part. The thing to understand here is that isn't a simple, clean, comprehensible business arrangement. The Albany facility is highly subsidized by the state. IBM has their hooks deep in the operation and occupation of the site. Such facilities are extraordinary with capabilities that talent that are unique and fabulously expensive. That's why ASML is there, and not just doing it in some village in the Netherlands. It's why when Obama, Biden, Trump or whomever tells ASML to whom they will and won't be selling hardware, ASML listens.
> It's why when Obama, Biden, Trump or whomever tells ASML to whom they will and won't be selling hardware, ASML listens.
My understanding is that ASML's acquisition of Cymer in California (the actual EUV light source technology) in 2014 was only permitted under a strict technology sharing and export agreement with the US government. And that the technology development and production had to remain within the US.
The USA CHIPS Act and NY State have provided $100 billion+ in funding with the expectation that ASML's core R&D and "prototyping" like this will be done in the US in partnership with US companies (like IBM).
A little bit of a nitpick, but wouldn't that be a picometer instead of angstrom node? Like, isn't a "pico-" the next magnitude smaller than "nano-", or am i wrong?
Otherwise, that chip tech sounds really awesome - at least for the future!
You had the right idea. Angstroms are not an SI unit. The SI units jump by three orders of magnitude at this scale: picometer, nanometer, micrometer, millimeter.
(In the same way that meter jumps three orders of magnitude to kilometer[1], or millions to billions to trillions, etc.)
[1] Technically there are intermediate SI units between meter and km but nobody uses them. There are not intermediate SI units between the tiny ones.
Decimeter is used occasionally for densities, because 1 g/cm^3 is the same as 1 kg/dm^3 but the latter is a little easier to imagine. The cube decimeter is also used under the name of... liter.
Likewise, there is also deca- and hecto-. Hectograms are used for shopping.
Decameter (dam, 10 m) is never used, but there is a non-SI unit of area based on it, called the are. Nobody uses the are, but its multiple the hectare (1 square hectometer) is common in some countries when talking about land plots. It's a little less than 2.5 acres, for people in the US.
Everyday necessity. The gap between mm and m is too large, there are many things in daily life that are better expressed in cm. SI units must strike a balance between three factors: not having so many denominations nobody can remember them; not having so few denominations that using them adds too much wordiness to daily life (150mm or 0.15m are wordier than 15cm); and a degree of familiarity with the everyday units people used before metric, to smooth the transition and encourage adoption.
Useless fact I just learned from Wikipedia: Ångström/Angstrom (in Sweden of course we still use the original spelling) has its own UNICODE symbol, Angstrom sign: Å (U+212B) not to confuse with the Swedish letter Å (U+00C5). Looks slightly different in my browser.
Looks like that's deprecated. From the next sentence:
However, version 5 of the standard already deprecates that code point and has it normalized into the code for the Swedish letter U+00C5 Å `latin capital letter a with ring above`
> logic technology can extend for the first time below the 1 nm node, advancing the era of angstrom-level scaling, where dimensions approach the size of individual atoms. While transistor nodes now refer to a generation of manufacturing technology versus an exact physical dimension, IBM’s 0.7 nm technology—also referred to as 7 angstroms—demonstrates how continued scaling remains possible.
Continuing the well established trend of making bold claims about physical dimensions that have nothing to do with any of the structures in the chip, and the name scales better than the tech.
What they actually deliver is a "nanostack architecture" built with ~5nm features that according to them is comparable to a hypothetical real sub-1nm chip.
It's an impressive achievement nonetheless but it looks like the industry has a few too many marketers.
My read on it was that they are trying to imply a transistor density (in a 2D plane sense) that is comparable to a 1nm process? But they achieve that through stacking (3D, not 2D) since the features aren't actually anywhere near 1nm?
Correction: it’s not stacking. They do things like FinFET (turning the gates in the third dimension) and gate-all-around which increases the density of transistors per unit area. But they don’t have layers of transistors. At least in the logic and analog processes.
I really can't see where the 0.7nm is coming from. The white line looks like it's just an edge of a feature that is "15 rows of silicon atoms", which by some quick arithmetic on Wolfram Alpha has to be AT LEAST ~1.6nm, and the way the rows of atoms appear to be packed in that image and by the provided scale, it seems to be significantly more. Using the white line as a meaningful measurement seems to me to be more misleading than any other interpretation here.
A 0.7 nm planar transistor made of silicon has no performance, because a device so small cannot function as a transistor.
The intended meaning of "0.7 nm" is that if you compare the transistor density per area of a "0.7 nm" manufacturing process with that of a "350 nm" process (like used for some Pentium II CPUs, at a time when "350 nm" was a real length), the ratio between the transistor densities is (350 nm / 0.7 nm)^2 = 500^2 = 250,000.
Comparing with the number of transistors of a Pentium II, a 0.7 nm CPU should be able to contain about 5000 billion transistors. This is consistent with the fact that the latest 3 nm NVIDIA Rubin GPU has 336 billion transistors and a 0.7 nm circuit must have a density around 16 times greater than a 3 nm circuit.
However, for many of the modern node names used by some companies even this computation is not really true, because marketing may have chosen an arbitrary name that is smaller than for the last process of the main competitor.
For now, IBM has not provided any kind of information that could prove their claim that their new CMOS process has the transistor density corresponding to "0.7 nm" (i.e. 16 times greater than the TSMC "3 nm" CMOS process).
> Continuing the well established trend of making bold claims about physical dimensions that have nothing to do with any of the structures in the chip, and the name scales better than the tech.
We care about PPA (power, performance, area) and not how large or not-large features actually are. Comparing gate lengths between a 1980s planar transistor and a 2010s 3D FinFET or GAA transistor is obviously nonsense, the relatively aligned node names of the industry actually do make sense as a shortcut here.
It's been decades since published node sizes had any connection to actual feature size. Sadly this is just how it works in the semiconductor industry now.
Smart money would be on the first person who realized that the expertise required to understand the technical details had grown beyond that possessed by 51%+ of stock investing (trading?) population as weighted by transaction volume.
>So essentially, since 1997, the node name has not been a representation of any actual dimension on the chip, and it has erred in both directions by almost a factor of 2.
We've already been through years of "7nm isn't actually 7nm" across different fabs - completely different measurement conventions, none corresponding to real feature sizes. Now sub-1nm? If it is real then at that scale we're probably in the several atom width territory.
As it can be seen from the photos, horizontally the features are much bigger than 5 nm.
For silicon, the gate length of a FET has a lower limit somewhere between 10 nm and 15 nm.
The current CMOS manufacturing processes have not reached the limit yet. For making smaller transistors, a transition to other semiconductor materials will be necessary.
The vertical thicknesses of various layers may be of only a few nanometers or even of a fraction of a nanometer, but that does not matter directly for the circuit density.
The supposed node size refers to horizontal dimensions, not to vertical dimensions.
Vertical dimensions of around 1 nanometer or less could be achieved already many decades ago, because they depend on growth speed and on time, not on lithography, like the horizontal dimensions.
The industry should have stopped decades ago to talk about the "size" but they should have characterized a CMOS process by its density, e.g. in logic gates per square mm.
However, an actual concrete number would be disliked by marketing, because they could no longer claim that their "1 nm" process is better than the "2 nm" process of another vendor, if their density is not really better.
The scale bar on the far right "photo" (micrograph?) doesn't make sense. It is only slightly less than half the scale bar on the middle photo (10 nm), but the image is clearly scaled up by much more than 2x. Individual silicon atoms are circled in the right photo, but the covalent radius of silicon is about 0.11 nm, so they should be much smaller if the scale bar is accurate.
The scale bar also got about 50% longer, which would imply a 3x zoom. That also seems about right based on the relative feature sizes. Same thing happened between the first and second image.
Better metrics are transistors/mm^2, performance/watt, and raw performance, since at this point "nm" is fluff and easily game-able.
Different companies measure it differently too. This was a while ago, but I remember reading that Intel 10nm was more or less close to TSMC 7nm. I'm sure this is still true to varying degrees.
Comparing nodes across foundries is a kind of a coin toss. At least, from the name. You actually need to go into the specifics of the pdk and process to understand what features there are. Can’t rely on the name for anything.
Unlike marketing terms, "nm density" is actually useful measure.
It describes density measure where you can compare it to planar transistors from the 28-nanometer (28 nm) node around 2010 to 2011 and before. A "0.7 nm" node has equivalent transistor density as if we could have shrunk standard flat transistor node down to 0.7 nanometers.
It's a physical quantity per some unit of spatial measurement so the units still don't match up b/c in one case the transistors are stacked per volume & in the other case per area.
> Historically, "node" sizes (like 28nm or 7nm) directly correlated to the physical length of a transistor's gate. Today, names like 3nm or 2nm reflect a marketing generation. The actual transistors are significantly larger than these nanometer labels, meaning density varies between companies
> Research organizations like IEEE have proposed new metrics, such as transistors per cubic millimeter (MTr/mm^3), to accurately map future 3D scaling. However, commercial chip foundries resist this change because it would make it harder to calculate commercial yields and thermal density limits using standard industry formulas.
> It's a physical quantity per some unit of spatial measurement so the units still don't match up b/c in one case the transistors are stacked per volume & in the other case per area.
However the active devices are still just one layer. This isn't like 3D NAND where you actually have transistors on top of each other. So the comparison only considers the area for both kinds of transistors.
The comparison is good. Humans are also stacked in volumes and we still measure population density over a surface because the third dimension is less significant in this context.
I got the answer from the AI I was looking for & it makes sense. You can try to map the volumetric density to areal density but the mapping is not canonical so it doesn't say anything about the physical reality of actual transistor density since the reality is that it is a volumetric measure that gets fudged for marketing purposes. 3D volume for chips is going to keep increasing so they will eventually transition to measuring density over volume instead of area.
3d population density would be an interesting measure, though. It would provide a better feel for how cramped a populated volume actually is.
It would have to be the displacement volume, to account for cities with only a few really tall buildings, and also somehow adjusted for buildings with high ceilings.
All "density" means is that it's a quotient; I use spectral densities daily and that's "count per Hertz" which weirdly enough works out in normal units to be seconds.
Density does directly scale with both of those in the form of more chips per die (=> lower cost) and smaller capacitance (=> less dynamic power dissipation).
If you want to reduce "effectiveness" of some process down to a single number, then density is far from the worst metric to pick.
Why is that all you care about? Stepping down a node gets you dramatically improved timing and design feasibility. The reduced density means you can pack the same design into less area. Your most challenging timing paths now have to traverse a shorter distance, and you can fit more of them relative to certain node-size invariant structures
> IBM and its partners conduct this work at a leading semiconductor research facility in Albany, New York, which will soon be home to a High Numerical Aperture Extreme Ultraviolet (High NA EUV) lithography tool, essential for the future of logic scaling. Developed by ASML, this technology enables ultra‑precise circuit printing, supporting the creation of smaller, more powerful chips.
I'm guessing that this is the technology that is developed by Cymer (ASML subsidiary) in California, correct? Is there competing technology? I know xLight is trying to make some inroads on their own version of this EUV tech. I have not heard about any progress though.
For anyone who needs it, a friendly reminder that CPU nm marketing is a complete fabrication and the physical size of transistors has zero relation to the marketing claims. These are not, in fact, physically sub 1 nm, despite the bombastic claims.
They don't describe the exact physical size (that would rather defeat the point of the marketing), but you can see the photographs at the bottom have a scale measured in tens of nm.
At some point in the transistor scaling, the electrons started leaking across the gate, we've switched from 2D design to 3D structures to prevent that, so the actual physical gate pitch for like the TSMC 3nm is around 45 nm in distance.
Currently thrown around numbers mean the "equivalent performance/density" or something like that.
I mean, you can't get smaller than an atom, there is some amount of plausibility of using individual atoms as at least the occasional computing element.
Beyond that, engineering a quark-gluon plasma as a processor? I'd watch that Star Trek episode. (we might fantasize about stuff like that but we're roughly monkeys smashing rocks together in a cave vs. building an iPhone sort of gap away from that kind of thing unless somebody has a really good idea)
You could, in principle, use photons and/or electrons. We got pretty damn close in the vacuum tube era, and photonic computing has been a popular research topic for a while.
You also have quantum computing, which I think can/does use subatomic particles? Not sure about that one
You can’t make smaller chips features with photonics. Visible light photons have a wavelength between 400 and 800 nm, much larger than current chip features. When you go to higher frequencies they get smaller, but they are really difficult to produce and control.
It depends on the type of quantum computer. In some a physical qubit is a single atom, but then to make it reliable they need to add error correction resulting in logical qubits consisting of at least 100 or so physical qubits.
Another type of quantum computer uses qubits consisting of "quantum circuits" which are actually huge macroscopic constructions (> 1mm).
> You could, in principle, use photons and/or electrons. We got pretty damn close in the vacuum tube era, and photonic computing has been a popular research topic for a while
Wait, what? How does this work in principle for storage? You can store electrons but you're saying you can store photons too?
We do use electrons. That's what flows through transistors to do computations. Or, vaguely, the distribution of the electric field....
>We got pretty damn close in the vacuum tube era
Uh, what?
There's only so many fundamental interactions in the Universe. Computing requires you to be able to distinguish two states and our current methodology is built around some sort of black box three input machine that can output either state, a switch.
That switch is the part that cannot be scaled down infinitely. The reality we are familiar with doesn't exist at atomic scales. "Things" don't even have properly defined boundaries at a certain level, and thermal noise is a huge issue.
IMO a much more direct limiter of our current computing capability is lack of manufacturing ability, and heat. We were lucky that transistors were so amenable to lithography as a concept, that they work so well in 2D and as a surface feature, as that is what drove our advances the past 100 years and enabled computing to be such a normal thing. The combination of a "Solid state" effect, the electric force having very convenient properties, and lithography being so amenable to scaling things in various directions is how we got here.
But lithography doesn't scale into 3D. We've been hacking around that by doing more layers but that scales awfully, has very strict limitations, and makes the heat problem infinitely worse, to the point of making it impossible to work around.
If we could assemble things atom by atom exactly how we want, we could vastly improve our theory and practice, and build really intricate processor chunks with effective cooling channels or something, and computing would scale so much more. Maybe. Maybe some other problem would suddenly start dominating in that world.
Biology literally is nanotechnology, but it takes massive tradeoffs in exchange. It might never be possible to manufacture, at scale, stuff atom by atom. The Universe doesn't promise us infinite progress in technology. Quite the opposite.
It doesn’t, no. The most successful platform actually uses superconducting devices as large as millimeters, you can literally see them with the naked eye.
The issue with “just” photons and electrons is that you need something else to force them to behave like you want. And photons are large and non-interacting, really the opposite of what you want for computing. Great for communications of course.
I always thought the true limit was the Planck length against which an atom is giant. There's a whole zoo of sub-atomic particles but I don't think we know how (or if) we can apply those for practical computing.
1. The OP has nothing to do with quantum computers.
2. Quantum computing deals in coherent quantum states: associated with N qubits there are 2^N complex amplitudes. You can measure by sampling the square-magnitude of the complex amplitude which turns it into a Probability Distribution. Quantum computing "gates" cause interference in the complex amplitude of entangled qubits cancelling out incorrect results, such that if you maintain coherence for long enough and sample the final state and measure the probability distribution, you get a computationally useful result. The key challenge in quantum computing is extending the coherence time of a larger and larger number of qubits, which is why you hear so much about quantum error correction. Recent results from Google showed a scaling law for "surface codes" using multiple qubits to create an error-corrected topological qubit with extended lifetime. There is no telling how far this scaling law will go, but as long as Gil Kalai is in the next room, it is unlikely there will be actual useful quantum computation for a while.
Broadly speaking yes, this is the business model. IBM has been at this for many years with technology transfers, licensing agreements, support and other arrangements. Rapidus, Samsung, GlobalFoundries, ST, SMIC, AMD, etc. have all used IBM R&D work at various times for various nodes and products.
The cutting edge of semiconductors is a writhing mass of copulating tapeworms, and IBM lives deep inside that ball. For IBM, what this means is that when you buy one of the ASML machines to make products with this process, you'll pay IBM for the knowledge and support to actually get it working, or give them a cut, or something else, TBD, as circumstances warrant.
What a metaphor! I will file that one away for some glorious future opportunity.
https://www.ibm.com/products/z/telum
Per IBM: "IBM Research at Albany [...] includes more than 100,000 square feet of semiconductor fabrication space"
I guess that is technically a R&D fab not a production one, but they definitely have in house fabrication capability
My understanding is that ASML's acquisition of Cymer in California (the actual EUV light source technology) in 2014 was only permitted under a strict technology sharing and export agreement with the US government. And that the technology development and production had to remain within the US.
The USA CHIPS Act and NY State have provided $100 billion+ in funding with the expectation that ASML's core R&D and "prototyping" like this will be done in the US in partnership with US companies (like IBM).
So many breakthroughs in hard drives, chips, transistor density, and other aspects of computing have come out of their labs.
Great to see them continuing to innovate.
But, yeah, usually they partner and license. Over the years, they've spun off more and more of their hardware businesses.
I wonder why isn't this more common.
Otherwise, that chip tech sounds really awesome - at least for the future!
(In the same way that meter jumps three orders of magnitude to kilometer[1], or millions to billions to trillions, etc.)
[1] Technically there are intermediate SI units between meter and km but nobody uses them. There are not intermediate SI units between the tiny ones.
We have centimeter (10 mm) then decimeter (100mm) then meter (1000mm). Then we jump to thousand again (kilometer).
Does anyone actually use those? I think I would throw up a little in my mouth if I saw either of those on a mechanical drawing.
Likewise, there is also deca- and hecto-. Hectograms are used for shopping.
Decameter (dam, 10 m) is never used, but there is a non-SI unit of area based on it, called the are. Nobody uses the are, but its multiple the hectare (1 square hectometer) is common in some countries when talking about land plots. It's a little less than 2.5 acres, for people in the US.
https://en.wikipedia.org/wiki/Angstrom
However, version 5 of the standard already deprecates that code point and has it normalized into the code for the Swedish letter U+00C5 Å `latin capital letter a with ring above`
1 angstrom = 0.1 nanometers, 100 picometers
1 nanometer = 10 angstroms, 1000 picometers
1 Å = 100 pm. 1 pm = 0.01 Å.
Continuing the well established trend of making bold claims about physical dimensions that have nothing to do with any of the structures in the chip, and the name scales better than the tech.
What they actually deliver is a "nanostack architecture" built with ~5nm features that according to them is comparable to a hypothetical real sub-1nm chip.
It's an impressive achievement nonetheless but it looks like the industry has a few too many marketers.
I know they won't go for an anything that makes as much sense as 5nm3, so I vote for "1nm hyper space"
We are used to stacking people vertically in cities.
The intended meaning of "0.7 nm" is that if you compare the transistor density per area of a "0.7 nm" manufacturing process with that of a "350 nm" process (like used for some Pentium II CPUs, at a time when "350 nm" was a real length), the ratio between the transistor densities is (350 nm / 0.7 nm)^2 = 500^2 = 250,000.
Comparing with the number of transistors of a Pentium II, a 0.7 nm CPU should be able to contain about 5000 billion transistors. This is consistent with the fact that the latest 3 nm NVIDIA Rubin GPU has 336 billion transistors and a 0.7 nm circuit must have a density around 16 times greater than a 3 nm circuit.
However, for many of the modern node names used by some companies even this computation is not really true, because marketing may have chosen an arbitrary name that is smaller than for the last process of the main competitor.
For now, IBM has not provided any kind of information that could prove their claim that their new CMOS process has the transistor density corresponding to "0.7 nm" (i.e. 16 times greater than the TSMC "3 nm" CMOS process).
We care about PPA (power, performance, area) and not how large or not-large features actually are. Comparing gate lengths between a 1980s planar transistor and a 2010s 3D FinFET or GAA transistor is obviously nonsense, the relatively aligned node names of the industry actually do make sense as a shortcut here.
Sometime around 2011 when Intel named their process node 22nm which the gate length was 26nm
>So essentially, since 1997, the node name has not been a representation of any actual dimension on the chip, and it has erred in both directions by almost a factor of 2.
For silicon, the gate length of a FET has a lower limit somewhere between 10 nm and 15 nm.
The current CMOS manufacturing processes have not reached the limit yet. For making smaller transistors, a transition to other semiconductor materials will be necessary.
The vertical thicknesses of various layers may be of only a few nanometers or even of a fraction of a nanometer, but that does not matter directly for the circuit density.
The supposed node size refers to horizontal dimensions, not to vertical dimensions.
Vertical dimensions of around 1 nanometer or less could be achieved already many decades ago, because they depend on growth speed and on time, not on lithography, like the horizontal dimensions.
The industry should have stopped decades ago to talk about the "size" but they should have characterized a CMOS process by its density, e.g. in logic gates per square mm.
However, an actual concrete number would be disliked by marketing, because they could no longer claim that their "1 nm" process is better than the "2 nm" process of another vendor, if their density is not really better.
We should flip the transistors sideways then!
"You can't go to the sun! You'll burn alive!"
"Duh! That's why we're going at night!"
How would you fix that? This is a global scam. Big Markets regulating them: that would have to be the USA and EU.
Different companies measure it differently too. This was a while ago, but I remember reading that Intel 10nm was more or less close to TSMC 7nm. I'm sure this is still true to varying degrees.
It describes density measure where you can compare it to planar transistors from the 28-nanometer (28 nm) node around 2010 to 2011 and before. A "0.7 nm" node has equivalent transistor density as if we could have shrunk standard flat transistor node down to 0.7 nanometers.
> Historically, "node" sizes (like 28nm or 7nm) directly correlated to the physical length of a transistor's gate. Today, names like 3nm or 2nm reflect a marketing generation. The actual transistors are significantly larger than these nanometer labels, meaning density varies between companies
> Research organizations like IEEE have proposed new metrics, such as transistors per cubic millimeter (MTr/mm^3), to accurately map future 3D scaling. However, commercial chip foundries resist this change because it would make it harder to calculate commercial yields and thermal density limits using standard industry formulas.
https://share.google/aimode/Z5BqUjlZWFNphm6Z6
"Planar" and "3D" in this context refers to the shape of the transistors themselves. In a planar transistor the functional structure is spread out in the area, like this: https://en.wikipedia.org/wiki/File:MOSFET_functioning_body.s... while 3D transistors spread into the volume: https://en.wikipedia.org/wiki/Multigate_device#/media/File:D...
However the active devices are still just one layer. This isn't like 3D NAND where you actually have transistors on top of each other. So the comparison only considers the area for both kinds of transistors.
You are suggesting it's measured over a cube volume?
It would have to be the displacement volume, to account for cities with only a few really tall buildings, and also somehow adjusted for buildings with high ceilings.
mass per volume is one example.
MTr/mm = 0.6×(NAND2 Tr Count)/(NAND2 Cell Area) + 0.4×(Scan Flip Flop Tr Count)/(Scan Flip Flop Cell Area)
If you want to reduce "effectiveness" of some process down to a single number, then density is far from the worst metric to pick.
I'm guessing that this is the technology that is developed by Cymer (ASML subsidiary) in California, correct? Is there competing technology? I know xLight is trying to make some inroads on their own version of this EUV tech. I have not heard about any progress though.
Why? What's their real size?
Not doubting you, just trying to understand and also trying to assess how exaggerated the marketing is.
Currently thrown around numbers mean the "equivalent performance/density" or something like that.
Is there a limit to how small things can go? A single atom?
Is there a physical/molecular limit to Moore's Law?
Beyond that, engineering a quark-gluon plasma as a processor? I'd watch that Star Trek episode. (we might fantasize about stuff like that but we're roughly monkeys smashing rocks together in a cave vs. building an iPhone sort of gap away from that kind of thing unless somebody has a really good idea)
You also have quantum computing, which I think can/does use subatomic particles? Not sure about that one
Another type of quantum computer uses qubits consisting of "quantum circuits" which are actually huge macroscopic constructions (> 1mm).
Wait, what? How does this work in principle for storage? You can store electrons but you're saying you can store photons too?
>We got pretty damn close in the vacuum tube era
Uh, what?
There's only so many fundamental interactions in the Universe. Computing requires you to be able to distinguish two states and our current methodology is built around some sort of black box three input machine that can output either state, a switch.
That switch is the part that cannot be scaled down infinitely. The reality we are familiar with doesn't exist at atomic scales. "Things" don't even have properly defined boundaries at a certain level, and thermal noise is a huge issue.
IMO a much more direct limiter of our current computing capability is lack of manufacturing ability, and heat. We were lucky that transistors were so amenable to lithography as a concept, that they work so well in 2D and as a surface feature, as that is what drove our advances the past 100 years and enabled computing to be such a normal thing. The combination of a "Solid state" effect, the electric force having very convenient properties, and lithography being so amenable to scaling things in various directions is how we got here.
But lithography doesn't scale into 3D. We've been hacking around that by doing more layers but that scales awfully, has very strict limitations, and makes the heat problem infinitely worse, to the point of making it impossible to work around.
If we could assemble things atom by atom exactly how we want, we could vastly improve our theory and practice, and build really intricate processor chunks with effective cooling channels or something, and computing would scale so much more. Maybe. Maybe some other problem would suddenly start dominating in that world.
Biology literally is nanotechnology, but it takes massive tradeoffs in exchange. It might never be possible to manufacture, at scale, stuff atom by atom. The Universe doesn't promise us infinite progress in technology. Quite the opposite.
The issue with “just” photons and electrons is that you need something else to force them to behave like you want. And photons are large and non-interacting, really the opposite of what you want for computing. Great for communications of course.
what matters is the size of the pumbing
https://en.wikipedia.org/wiki/Exotic_matter
I always thought the true limit was the Planck length against which an atom is giant. There's a whole zoo of sub-atomic particles but I don't think we know how (or if) we can apply those for practical computing.