[q3k]

Please keep in mind that even the slightest error in a silicon mask is likely to cause hundreds of millions of dollars of losses and months of delay in time to market for a modern chip.

With that in mind, does it make more sense to come up with new, experimental, untested algorithms... or just use wider numbers and slowly iterate on well known algorithms? Especially with LVS/DRC you really want the dumbest, easiest to reason about thing that is most likely to catch design issues no matter what. Even if it's excruciatingly slow, it's your last line of defense against writing off a set of masks as a hundreds of millions of dollars loss.

EDA / silicon CAD is a totally different world of design requirements compared to video games or even MCAD software.

EDIT: and just for context, here's a DRC set for the (very much not modern) SKY130 process: https://github.com/RTimothyEdwards/open_pdks/blob/master/sky...

[jiggawatts]

The exact same arguments were made by CAD people insisting on 64-bit maths for OpenGL. They were wrong. They too were working on projects worth billions of dollars, over decades, where mistakes were very costly.

Your link to a "DRC set" doesn't mean much to me out of context. I see some basic looking code with small-ish numeric constants in it. So what? This is not that different to the input to a simple physics simulation or a computer game.

[hardolaf]

So let's get this straight. You know nothing about this area and you assume the experts in it are wrong? Do you know what happens if you accidentally couple lines during one of the manufacturing steps? The wafer can, in the absolute worst case scenario, explode from super heating destroying not just the wafer but potentially the entire chamber it is in (any defect beyond what was designated as allowable by the design engineers means the chamber and everything in it is now scrap).

For somewhat obvious reasons, we have a vested interest in this never occurring. So we default to safety over speed. Meanwhile in the CAD world with 64-bit math not making it into OpenGL, they just wrote a library to do 64-bit math anyways on-top of or in parallel to OpenGL. They didn't switch away from 64-bit math, they just reduced its use where it isn't needed and kept it where it is needed. The semiconductor industry is full of absolutely brilliant engineers who know far too much about all of the problems and if they could use 64-bit instead of 128-bits for a data structure, they'd switch in a heartbeat to save massive amounts of compute time (and thus money).

[jiggawatts]

> Do you know what happens if you accidentally couple lines during one of the manufacturing steps?

I understand the consequences. I also understand both both physics and computer science. A 32-bit integer is sufficient to subdivide something the size of a wafer mask to well under the wavelength of the light used for photolithography. There is literally no way for additional precision to matter for things like "coupling lines". It is impossible.

See for yourself: https://www.wolframalpha.com/input?i=3+cm++*+2%5E-32

Iterated algorithms are a different beast entirely, but there are fixed-point or integer algorithms that sidestep these issues.

You cannot imagine the volume of computer science research that has been written on shape-shape intersections in both 2D and 3D! Literal textbooks worth. Hundreds if not thousands of PhD-level papers. The sheer intellectual effort that has gone into optimisations in this space is staggering.

Hence my incredulity. I've worked with 128-bit numbers and even arbitrary-precision numbers, but only in the context of computational mathematics. There are no "physics constraints" in mathematics to limit the benefit of additional range or precision.

Also, the financial argument doesn't hold water either. Modern chips have tens of billions of features. The data volume can exceed the size of main memory of even the largest computers. Data representation efficiency and simulation speed absolutely would have tangible business benefits: faster iteration cycles, lower simulation cost, better optimisation solutions, etc...

This is literally the point of the article -- being able to do things in GPUs using their native 32-bit maths capabilities is a huge benefit to the chip design workflow. This requires clever algorithms and data structure design. You can't be wasteful because "it feels safer" if you have a budget of 24 GB (or whatever) to squeeze the mask data into.

> assume the experts in it are wrong?

Yes! Something I've noticed is that there is surprisingly little "cross pollination" between fields. You can have very smart people in one industry blithely unaware that another industry has solved their "very hard problem". I've seen this with biology, physics, medicine, etc...

How many chip design automation experts have also done low-level game engine programming? Maybe half a dozen in the whole world? Less?