[existencebox]

Probably? (jadedly) It's a cheap one off that earns them a lot of free publicity.

Folding and SETI have been at it for decades, and will be for decades more. That'd be a lot of power/hardware costs for little net gain modulo time spent.

(Note: 30 cpu years really isn't a lot of time when you start getting truly massive parallelism, and google is certainly at that scale. I'm honestly surprised to see this is pthreads based, I would have expected it to lean heavily on CUDA (or maybe I'm just showing my naivete to the field of parallel programming))

[birken]

Just to put some numbers behind this:

35 CPU years = 35 * 365 = 12,775 CPU days

Let's assume that your standard Google machine has 2 8-core processors, that is 16 cores per machine

12,775 / 16 = 798 machines

800 machines is a lot for your average person, but for a company like Google it is a very small drop in the bucket. And that is assuming you need to do all of the calculations in one day. If you are willing to do the calculations over a month, you only need 26 machines.

Even if "CPU year" applies to one 8-core processor, that still means it is just 26 * 8 = 416 machines, which is a very small number for Google.

And remember, the machines are still doing other things, this is just using idle CPU (generally a plentiful resource for your standard internet giant workload).

[largote]

It would seem to me that this kind of program would be heavily reliant on branching for which Vector processing (which is what GPUs excel at) is not the best choice.

[nathancahill]

CUDA is for GPUs (specifically NVIDIA GPUs). This is CPU processing. Pthreads is the way to go.