I am curious about characteristics of transistors in modern chips (propagation time, resistances and capacitances, drive current). Can someone spill the details?
I tried to make some estimations: modern CPUs can work at 4 GHz, which is 250 ps/cycle. Modern CPUs allegedly can do 64-bit addition in that one clock cycle. Carry-lookahead adder requires a fat 63-input AND followed by fat 63-input OR for computing the carry for MSB, which can be implemented as 2×8 layers of 2-input gates or 2×3 layers of 4-input gates, or 2×2 layers of 8-input gates. Then you add the carry to the sum which requires a XOR which is probably like 2 layers of standard gates. Then you need to respect set-up time for the flip-flop, and account for a propagation inside it. A flip-flop (2 latches) is at least 2 layers of gates. So if we consider 4-input gates, the path would be 6 + 2 + 2 = 10 layers, and the propagation time for one gate should be 250÷10 ~ 25 ps.
Is that correct or not? Or the clock of CPU is limited by thermal limits and not by propagation time? Or there are some tricks that allow using slower transistors?
20% growth then 20% again still seems pretty good to me though. I guess compounded that is a 44% increase N3 to A14 which also starts to look much better if you zoom out a bit. I mean 44% more density since a few years ago seems, if not massive, not insignificant, like you will definitely notice it.
Yes but considering N10 was fabricated with DUV lithography right before the shift to EUV I'm not sure how fair that comparison is. That being said the density scaling of N10 nodes compared to predecessors using the same lithography technique was much higher than we have seen since with the EUV nodes. Density scaling is the most meaningful comparison metric, but it doesn't take into account additional technology developments.
If we exclude short-term shortages then no. The cost to make a wafer hasn't really changed. Larger wafers improved costs but that's about it AFAIK.
Feature sizes have been shrinking unevenly for two decades now combined with the overall slowdown in improvements. Transistors themselves are FinFET geometry and something like 15-30 atoms thick and maybe 80-100 across. There ain't much juice left to squeeze in terms of size but perhaps we'll figure out how to reduce leakage (heat).
Physics hates the very large and the very small. The large get the tyranny of volume scaling + general relativity. The small have their entire concept of reality smashed by quantum mechanics.
It's hard to tell because AI has pushed up costs. IE. Chip fab margins are increasing.
But generally, I think it's even or increasing $/transistor for each node. I'd guess that A14 would have been 20% more expensive than N2 regardless or AI or not.
It probably is still worth it because you're also getting 20-30% better power efficiency - which is a big deal for data center chips.
A lot of that is the lack of SRAM scaling. There’s still quite a bit of improvements in the back end (metal traces). That aside, if foundries adopted say a 1T-1C SRAM we’d see a pretty rapid density doubling
Is 1T1C SRAM a technological thing or does it mean "persuade designers to use DRAM in the many cases where the retention contract could be timeboxed with a bit of extra thought and cross-team haggling"?
MRAM is 1T, non-volatile and supposedly has nanosecond-scale write times so it naively seems like it'd be an ideal SRAM replacement. But I guess shrinking MTJ is more difficult than other components or there are some other limitations.
Aka eDRAM? It was a thing back on 14nm node, but AFAIR not so much anymore. The 1C part is hard to get right in a way that is compatible with a logic process.
I did find it funny recently when Huawei when talking about its folded logic say the Vertical Bonding Pitch's are every 15,000 angstroms. It is a very fancy way of saying an interconnect every 1.5 microns.
IEDM is more or less the most prestigious conference on semiconductor devices. Hard to get a more reliable source than a TSCM-affiliated paper from IEDM.
In simpler terms, the SRAM density improved by 2.9% (according to ChatGPT). Which is better than it sounds, because SRAM had reached a wall, in terms of density gains, and, chips can be dominated by SRAM in terms of surface area, so this can mean a lot more room for logic, even though that is also getting considerably denser.
Or AMD’s putting sram on a separate chip. I’m surprised they didn’t go there yet except for extra L3 instead of all of it. At some point the costs will shift the decisions.
I was laughing at the expected expectation of universally working UTF-8 just because it's 2026 when I read that. Soooo many things just do not work with UTF-8 as expected. I'm looking at MS Excel with heavy side eye
I tried to make some estimations: modern CPUs can work at 4 GHz, which is 250 ps/cycle. Modern CPUs allegedly can do 64-bit addition in that one clock cycle. Carry-lookahead adder requires a fat 63-input AND followed by fat 63-input OR for computing the carry for MSB, which can be implemented as 2×8 layers of 2-input gates or 2×3 layers of 4-input gates, or 2×2 layers of 8-input gates. Then you add the carry to the sum which requires a XOR which is probably like 2 layers of standard gates. Then you need to respect set-up time for the flip-flop, and account for a propagation inside it. A flip-flop (2 latches) is at least 2 layers of gates. So if we consider 4-input gates, the path would be 6 + 2 + 2 = 10 layers, and the propagation time for one gate should be 250÷10 ~ 25 ps.
Is that correct or not? Or the clock of CPU is limited by thermal limits and not by propagation time? Or there are some tricks that allow using slower transistors?
Please help me solve this puzzle.
Feature sizes have been shrinking unevenly for two decades now combined with the overall slowdown in improvements. Transistors themselves are FinFET geometry and something like 15-30 atoms thick and maybe 80-100 across. There ain't much juice left to squeeze in terms of size but perhaps we'll figure out how to reduce leakage (heat).
Physics hates the very large and the very small. The large get the tyranny of volume scaling + general relativity. The small have their entire concept of reality smashed by quantum mechanics.
But generally, I think it's even or increasing $/transistor for each node. I'd guess that A14 would have been 20% more expensive than N2 regardless or AI or not.
It probably is still worth it because you're also getting 20-30% better power efficiency - which is a big deal for data center chips.
Aka eDRAM? It was a thing back on 14nm node, but AFAIR not so much anymore. The 1C part is hard to get right in a way that is compatible with a logic process.
eDRAM isn't the same as 1T-SRAM, which isn't quite the same as 1T-1C SRAM...
But overall they run into the same problems that you mention; it's just too hard to get a capacitor in play.
There is Zeno Semi's Bi-SRAM, buuuut it hasn't seemed to catch on for one reason or another.
Not sure what this source is, but it looks sketchy.
> provides up-to 50% area reduction and reduced power consumption by a factor ten