I'm curious to know what workloads you think Google is running on the same hardware that cloud customers are using.
I've never worked at google. Do they just let each team go with their own crazy hardware setup? Or maybe two separate systems, one internal and one external? That seems a little wasteful (they have the money, so whatever).
But wouldn't programming against a big unified api be a bit more, well, sane? I can see really sensitive stuff locked away on its own hardware, but the search front end? why not serve some JS or provide chrome downloads from a giant pool of common hardware?
Things grow organically, and they might be technically locked into a specific layout right now, that's totally understandable. But, unused capacity is just capital depreciating steadily away with no gain. Soaking up every spare cycle doing something useful should probably be somewhere in the company goals.
You can get an answer on your laptop in an hour. You'll probably get a better answer throwing 1000 hours at your algorithm though, and a better answer throwing 10000 hours.
You can do a lot of neat things if p=np. Since no one knows if that's true, we're stuck with bad big O. More computer time is the only way out right now.
The point is, I'd be disappointed in google researchers if they didn't have a huge amount of unscheduled workload.
"But Witold Jarnicki and David Konerding already did that: they wrote a C++ program that built a table of Cz(modp)Cz(modp) up to 5000500050005000 , and, in parallel across thousands of machines, searched for A,BA,B up to 200,000 and x,yx,y up to 5,000, but found no counterexamples. On a smaller scale, Edwin P. Berlin Jr. searched all CzCz up to 10171017 and also found nothing. So I don't think it is worthwhile to continue on that path."