Apple spends $100+ millions to design high performance microarchitecture to high-end process for their own products.
Google gives tiny amount of help to hobbyists so that they can make chips for legacy nodes. Nice thing to do, nothing to do with Apple SoC.
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Software people in HN constantly confuse two completely different things
(1) Optimized high performance microarchitecture for the latest prosesses and large volumes. This can cost $100s of millions and the work is repeated every few years for a new process. Every design is closely optimized for the latest fab technology.
(2) Generic ASIC design for process that is few generations old. Software costs few $k or $10ks and you can uses the same design long time.
I don't believe Google does anything because it's a "nice thing to do". There's some angle here. The angle could just be spurring general innovation in this area, which they'll benefit from indirectly down the line, but in one way or another this plays to their interests.
If only Google had this singular focus... From my external (and lay) observation - some Google departments will indulge senior engineers and let them work on their pet projects, even when the projects are only tangentially related to current focus areas.
Looking at Google org on Github (https://github.com/google); it might be a failure of imagination on my part, but I fail to see an "angle" on a good chunk of them.
And by old, I mean /old/. 130 nm was used on the GameCube, PPC G5, and Pentium 4.
Things don't have to be ultra modern to offer value.
You could probably close some of the single thread gap with architectural improvements, but your real problems are going to be power consumption and that you'd have to quadruple the die size if you wanted so much as a quad core.
The interesting uses might be to go the other way. Give yourself like a 10W power budget and make the fastest dual core you can within that envelope, and use it for things that don't need high performance, the sort of thing where you'd use a Raspberry Pi.
(Jim Keller explains in this interview how CPU designers are making use of the transistor budget: https://youtu.be/Nb2tebYAaOA)
They can outsource silicon development. Should not be a problem with their money.
In comparison to dotcom development teams, semi engineering teams are super cheap. In Taiwan, a good microelectronics PhD starting salary is USD $50k-60k...
Experienced teams who have designed high performance microarchitectures aren't common, because there just isn't that much of that work done.
And when you're eventually going to spend $$$$ on the entire process, even a 1% optimization on the front end (or more importantly, a reduction of failure risk from experience!) is invaluable.
At the scale that Google is at, it really wouldn't surprise me if they were working on their own silicon to solve the problems that exist at that scale.
"""Regularly upgrading network fabrics with the latest generation of commodity switch silicon allows us to deliver exponential growth in bandwidth capacity in a cost-effective manner."""
https://conferences.sigcomm.org/sigcomm/2015/pdf/papers/p183...
The next step in that set of goals for their data center would be custom silicon where merchant silicon doesn't provide the right combination.
My guess would be a cloud based chip design software is in the works. This would accelerate AI quite a bit I should think?
It's actually a big part of why some silicon companies distribute themselves around timezones - so someone in Texas can fire up the software immediately when someone in the UK finishes work.
It's not unusual to see an 'all engineering' email reminding to you close rather than minimize the software when you go to meetings.
But that all means nothing for companies who buy Virtuoso copies from from guys trading WaReZ in pedestrian underpasses in BJ.
A number of quite reputable SoC brands here in the PRD are known to be based on 100% pirated EDAs.
This is not a critique, but a call to think about that a bit.
In China, you can spin-up a microelectronics startup in under $1m, in USA, you will spend $1m to just buy a minimal EDA toolchain for the business.
Allwinner famously started with just $1m in capital, when disgruntled engineers from Actions decided to start their own business.
Or put another way, Apple and Google are both responding to Intel/the market’s failure to innovate enough in idiosyncratic manner:
- Apple treats lower layers as core, and brings everything in-house;
- Google treats lower layers as a threat and tries to open-source and commodify them to undermine competitors.
I don’t mean this free fabbing can compete chip-for-chip with Apple silicon of course, just that this could be a building block in a strategy similar to Android vs iOS: create a broad ecosystem of good-enough, cheap, open-source alternatives to a high-value competitor, in order to ensure that competitor does not gain a stranglehold on something that matters to Google’s money-making products.