First 3D Nanotube and RRAM ICs Come Out of Foundry
spectrum.ieee.org
spectrum.ieee.org
I say it seems likely because Landauer's limit works out to about 0.003 attojoules per bit erasure at room temperature, while current top-efficiency processors use on the order of 100–200 picojoules per instruction — say, about 1 picojoule per bit erasure. So we're about 10 orders of magnitude from Landauer's limit, even before we switch to reversible computation, or drop Landauer's limit by a factor of 75 by operating our computers at the temperature of the cosmic background radiation. Other fundamental limits on computation (Lloyd's "ultimate laptop": https://arxiv.org/abs/quant-ph/9908043) are even further off.
In 2D, though, we're actually sort of close, in the sense that the transistors TSMC and Samsung are mass-producing are only about five orders of magnitude larger than the somewhat fundamental limit of single-atom transistors; https://news.ycombinator.com/item?id=20273007 says silicon atoms in an unstrained lattice are 0.235 nm apart, so a 10-nm-wide gate is 40 atoms across. Single-atom transistors have been working for decades in the lab (IBM Almaden, maybe?) so we know there aren't any fundamental limits to computation in between here and there.
transistor density is still improving logarithmic.
Moore's law is about the number of transistors on a chip, not about performance.
People talking about Moore's law talk about the "more transistors means more performance" aspect. That part hasn't held for a while now. No one cares if you have ten times as many transistors if it doesn't improve performance.
Even if performance didn't improve, that wouldn't make moore's law dead.
You might say that Dennard scaling is dead. But Dennard scaling isn't Moore's law even thought is gets conflated a lot.
Edit:
Compare a GTX 285 to a RTX 2080 ti, the performance has increases more than 9 times over the last decade.
Correct, though number of cores is far harder to use in software than the higher Mhz/Ghz we enjoyed before. Same for GPUs. If you can use them you still enjoy a noticable increase in performance, but not all programs (or rather algorithms) can be changed to benefit from more cores and even less commercial ones.
> You might say that Dennard scaling is dead. But Dennard scaling isn't Moore's law even thought is gets conflated a lot.
Fair enough. I looked this up and the combination of Dennard scaling and Moore's law seems to be called Koomey's law - I've never heard that term before, but it fits the definition of what people usually attribute to Moore's law:
> Jonathan Koomey articulated the trend as follows: "at a fixed computing load, the amount of battery you need will fall by a factor of two every year and a half."
"It may prove economical to build large systems out of smaller functions, which are separately packaged and interconnected."