Universities, government labs, and sometimes IT vendors donate their excess supercomputing capacity through grants to academics to help advance various sciences. Now Google is letting boffins loose on its systems.
In a blog post, Alfred Spector, vice president of research and special initiatives at the Chocolate Factory, said that Google had created an academic research grant program called the Google Exacycle for Visiting Faculty, which will donate one billion core-hours to science.
Google says that this level of computing is orders of magnitude more computing than most academics can get their hands on, no matter how big the endowment is at the university or how much research they do for government.
Google is not just giving away compute cycle on its massive server clusters to get a tax write-off on unused capacity, but to blind us with science. "Google Exacycle for Visiting Faculty is not a conventional grant program," the company claims. "We aim to stimulate advances in science and engineering research by supporting the computational needs of projects that push boundaries and reach for remarkable breakthroughs."
Google is not giving all of the billion core-hours to one lucky researcher. The plan is to solicit distinguished researchers and postdoctoral scholars from all over the globe and award them grants for jobs that can chew through at least 100 million core-hours.
Those who win the grants will do their work from Google offices and sign an employee agreement with Google for the term of the simulation. You have to pay your own travel, lodging, and living expenses while the simulations run.
The company says that large-scale genomics and protein folding simulations are the kinds of jobs it expects to most benefit from such a large number of cores to frolic upon; embarrassingly parallel jobs will do best, and "pleasantly parallel" jobs (yes that is a technical term) will work.
"The higher the CPU to I/O rate, the better the match with the system," Google says, and jobs that have minimal communication between nodes will do best. (Sounds like Gigabit Ethernet to me.) Your program has to be coded in C/C++ and compiled via Google's Native Client SDK, its tweak of the open source GNU C++ toolbox. Sorry, no Fortran or Java apps need apply. Researchers have until May 31 to apply for the capacity.
Looking ahead, Spector says that Google is thinking of extending CPU capacity grants to businesses in various industries, including biotech, financial services, manufacturing, and energy. Spector did not say that these grants would be free – he didn't say Google would charge for them, but it makes sense that it would – and is soliciting ideas from industry now on what jobs companies might want to run.
So just how much is a billion core-hours in terms of HPC capacity?
The largest cluster of Xeon machines in the world not using a proprietary interconnect of some kind is the Pleiades supercomputer at NASA's Ames Research Center. It uses Intel's old quad-core Xeon 5400 processors from two generations ago in two-socket machines; the cluster has 81,920 cores running at 2.93 GHz and links the servers together with an InfiniBand network.
Those chips can issue four floating point instructions per clock cycle per core, which works out to over 960 teraflops of aggregate peak number-crunching power. (On the Linpack floating point test, the Pleiades machine delivers 772.7 teraflops of actual performance.) If you ran the Pleiades machine flat out for a full year, you are talking about 718 million core-hours.
A grant of 100 million core-hours is around 11,408 Xeon cores running for a full year, and with modern six-core Xeon 5600 processors, you are talking about Google giving 950 server nodes. (Obviously, if you want to run that job in three months instead of 12, you have to quadruple the server node count.)
Google has millions of servers, so this is a tiny fraction of what the search giant has running in its 36 data centers. Depending on how fast you want to burn those cores, the virtual HPC cluster that Google will grant you could be rated from one to several hundred teraflops.
So the Google grants may be a tiny piece of Mountain View's capacity, but the capacity Google is putting up for grabs is a lot more than most researchers can get their hands on