blp

Yes, except the important parts. In Moore’s law scaling, you reduce the cost per transistor, and because of that there is money for capex and the consumer benefits.

In Huangs law, si is commoditized, so the benefit accrues to the designer and software makers, and really only in narrow domains.

Dennards law held until the approximately linear relations that made it work ended. Delay stopped being entirely gage, and more importantly, voltage couldn’t drop forever, due to material limits and intrinsic silicon limits.

Yet happiness, productivity, and lifespan are all higher in Europe. Regulation is different, and in some areas less.

Who are you optimizing for?

It is great and the math is easy. There are a couple clever tricks ( like how to calculate pi), but nothing beyond high school math.

Well said. I will add that each different industry is different, and often every company aligns the role somewhat differently.

If you are building enterprise software, vs hardware, vs consumer products...the process can be very different, with different balances on risk and very different timelines

If you then centralize the composters, for efficiency, the you really have something.

This is just....not true. IBM doesn’t make 5nm chips. This is a research demo of a transistor design for that node. They don’t make it, and never will.

It is an equivalent scale. Density is fine pitchm2 pitchtrack height. You scal node by an equivalent reduction.

It would be better to use logic density, but it is easier to use numbers we are used to.

I can split any small pitch exposure into separate, larger pitch exposures. For instance, if I need 40nm pitch, and my system is limited to 80nm, I can do 4 exposures. The next shrink requires 8.

To figure this out, draw a square, and each node is an exposure.

This process works forever in theory, but is limited in practice by the mutual registration of the exposures.