"Fullstack chip designers" exist in the mixed-signal world. Where the analogue component is the majority of the chip, and the digital is fairly simple, it's sometimes done by single person to save money. At least it was definitely a thing in the late 00's and early 2010's in small fabless design centers. Not sure about nowadays.
There was a ton of energy & hype & visibility for the first couple years after launch (2018). But it's been pretty quiet, a lot less PR since. I wish there was more visibility into the evolution of this & related effort. https://github.com/The-OpenROAD-Project/OpenROAD?tab=readme-...
Also take a look at the Open Source EDA BOF from the DAC conference - https://open-source-eda-birds-of-a-feather.github.io/
In the GPU world, you have games, which are built on game engines, which are built against an API, which is implemented in a driver (which contains a compiler!), which communicates through OS abstractions with hardware, which is written in a HDL (this is where you write RTL!), which is then laid out in silicon. Now each of these parts of the stack have ridiculous complexity in them, and there are definitely things in the upper layers of the stack that impact how you want to write your RTL (and vice versa). So if your stack knowledge stops at RTL(which, honestly there is absolutely nothing wrong with!), there is still lots of fun complexity left in the stack.
I've worked on some of the current highest profile chip projects doing "frontend" RTL design, and at every major chip company I've worked at, and from talking with coworkers about their past experiences at other companies, the handoff-wall between RTL and PD is leaving a substantial amount of perf per power/area on the table. (like 30% I'm general)
RTL designers generally have no visibility into how their designs are getting laid out, and generally don't want to have to care. PD engineers have no visibility into the uArch and low level code details, and maybe they want to care but everything is too obfuscated in general.
So when your pins are misplaced during an early iteration, RTL will blindly add retiming to resolve timing issues and make PD happy but never check if it's actually needed. PD will slave away trying to make busted RTL work with placement and recipe adjustments rather than asking RTL for a trivial fix, etc etc.
There are a ton of small things where visibility into either side of the process would result in measurably better hardware, but the current team structures and responsibility boundaries encourage people not to care.
(Source: I've been a CPU Architect going on my fourth decade.)
GianFabien•7mo ago
FirmwareBurner•7mo ago
There is local data on each major manufacturer/designer that they can use to train their LLMs. I'm sure Synopsys/Mentor/Siemens are also working towards providing solutions to their customers can use to train their own LLMs.
pedro_caetano•7mo ago
The companies with the biggest treasure trove of non-public training data will likely have a technical advantage. _If_ they can purposefully use that data to create better models for their niche problem domain.
webdevver•7mo ago
im quietly holding out hope for atomicsemi.com or someone like that
mithro•7mo ago
There are a huge number of designs from Tiny Tapeout which are all public - see https://tinytapeout.com/runs/
The designs are still more in the MCU size, but you have to start somewhere!
The Google open MPW program also had 10 runs with 40 projects published at http://foss-eda-tools.googlesource.com/third_party/shuttle/ -- All the submissions had to be open source and there were 1000+ of those. I did try pitching to multiple Google Research groups that continuing the open MPW funding would grow the available designs which have been manufactured and that was useful for AI training but didn't get any bites.
The now defunct Efabless also ran a number of challenges in this space which got pretty good results, see https://efabless.com/challenges