Facebook has hinted that they employ smart C++ people because some core optimizations can save on the order of several hundred thousand dollars per year (possibly in the millions). Most of that is off because they don't have to buy as much power to cool the server rooms, some of it is buying less servers as what they have can do more. Facebook doesn't actually say what they save, but they have said they measure it, and we know how much it costs to employ an engineer full time working only on optimization, and we know who some of those engineers are.

You have to be very large to notice it, but the likes of Facebook, amazon, and Google have massive warehouses almost entirely filled with computers. It doesn't take much to see how their power bill can add up.

Years ago Alexandrescu said that Facebook estimated a .1% speedup to HHVM would save them $100k/year. It's presumably only gone up since then, but he's stopped giving an actual number in talks.

I would argue that he is bragging, and that the amount of code optimization is minimal. Large companies love to brag about how many servers they have, and optimizing compilation is just a buzz word. Go ahead, buy another servers. $100k is nothing. Its less than 1 engineer year vs 24,000 engineer years.

The Distribution collectors, they brag about speed, and optimization is very important to them. They want to be able to test changes very quickly.

The parent works at Facebook/Meta leading their Rust team, focusing on compiler and ecosystem improvements. So that in and of itself is a sort of hint into what that info could be like, even if it's not actual details of the order of magnitude or anything.

The Google Search optimization team measures changes in terms of millions of CPUs. So if upgrading your compiler saves even 0.1%, well, that's a lot of servers you don't have to buy next year.

Apple went out and bought a CRAY.

"Jun 30, 1987 — The Cray is part of a $20m installation used by Apple's Advanced Technology group and consists of four CPUs operating at 9.5nS per cycle,"

Now we have distcc, that can both massively parallelize compilation, and optimization.

Googles team probably shows some slight improvement, just to justify their work, but in the long run, its just as sloppy as industry wide coding is.

Microsoft is the absolute worst, along with Apple.

One avenue is to think about it in terms of datacenter compute. If modern compiler optimizations improve performance by 10%, aggregate the perf improvements across the entire world's compute and you get a huge saving.