4 ms·

Like I said, I'm just curious. Google has so much capacity that I'm not sure it would be important for their bottom line to move it between Google and customer

Like I said, I'm just curious. Google has so much capacity that I'm not sure it would be important for their bottom line to move it between Google and customer workloads in quanta smaller than one physical machine. Your theory also requires Google to have a substantial standby workload that is currently not scheduled, doesn't it?

jfoutz 10y ago
In my very limited experience, trying to answer research questions can soak up all the computation you can throw at it. Consider something like the traveling salesman problem. The only answer is to check every path. There are heuristics to get good answers, but you never know if they're optimal. 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.
- hueving 10y ago
  There are some questions though where the saved energy from not running the batch jobs is worth more than the answer (e.g. searching for the next prime).
  - dekhn 10y ago
    We (google) ran numerous theory problems on Google's computing platform via the Exacycle program. Peter Norvig convinced me this was a bad idea, but mainly to say that time was better spent on disproving the conjecture using pure math, not search. http://norvig.com/beal.html http://norvig.com/beal.html "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."

jfoutz 10y ago

In my very limited experience, trying to answer research questions can soak up all the computation you can throw at it. Consider something like the traveling salesman problem. The only answer is to check every path. There are heuristics to get good answers, but you never know if they're optimal. 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.

hueving 10y ago
There are some questions though where the saved energy from not running the batch jobs is worth more than the answer (e.g. searching for the next prime).
- dekhn 10y ago
  We (google) ran numerous theory problems on Google's computing platform via the Exacycle program. Peter Norvig convinced me this was a bad idea, but mainly to say that time was better spent on disproving the conjecture using pure math, not search. http://norvig.com/beal.html http://norvig.com/beal.html "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."