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Medicine Technology

The Science of Folding@home 88

mr_sifter writes "As previously discussed, computers running Folding@home now contribute over 1 petaflop of processing power to research into protein folding, making Folding@home the most successful example yet of a distributed computing app. It's also at the forefront of GPGPU computing, with both Nvidia and ATI keen to push how well their graphics chips perform when folding. So the technology is great, but what about the science? This feature looks at how the Folding project was developed, how it's helping researchers and the thorny question of how long it might be until the software running on your PC or PS3 actually produces real-world results."
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The Science of Folding@home

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  • by Futile Rhetoric ( 1105323 ) on Monday June 15, 2009 @09:01AM (#28334077)

    Let me Wikipedia [wikipedia.org] that for you.

  • Not a petaflop! (Score:3, Informative)

    by tomknight ( 190939 ) on Monday June 15, 2009 @09:01AM (#28334081) Homepage Journal
    It's petaflops, not petaflop. That s means something.
  • 5 petaflops, not 1 (Score:3, Informative)

    by Anonymous Coward on Monday June 15, 2009 @09:05AM (#28334109)

    "However, even Roadrunner looks decidedly weedy compared with the power of Stanfordâ(TM)s Folding@home project. Its computational power has now surpassed the five petaflops mark."

  • Re:Not a petaflop! (Score:5, Informative)

    by noundi ( 1044080 ) on Monday June 15, 2009 @09:16AM (#28334185)
    Actually it's petaFLOPS as it's an abbreviation.
  • Re:Not a petaflop! (Score:3, Informative)

    by Anonymous Coward on Monday June 15, 2009 @09:20AM (#28334233)

    Floating point operations per second; if anyone was wondering (honestly how long will you guys fight about that before actually saying the name?)

  • by Anonymous Coward on Monday June 15, 2009 @09:25AM (#28334289)

    If you leave the server on anyways, the power draw at 0% usage versus 100% usage is minimal.

    eg. I have an old Dual processor Dell server that uses 170 watts idle, and 180 watts running at 100%

    the largest difference I got was on my overclocked AMD FX-55 which had a difference of 30 watts. and a laptop that had a difference in 30 watts.

    I used the Kill-A-Watt device purchased from thinkgeek.com.

  • Re:Not a petaflop! (Score:3, Informative)

    by master5o1 ( 1068594 ) on Monday June 15, 2009 @09:29AM (#28334319) Homepage
    No, like 1*10^15 "Floating Point Operating Per Second"
  • Re:Not a petaflop! (Score:3, Informative)

    by master5o1 ( 1068594 ) on Monday June 15, 2009 @09:31AM (#28334343) Homepage
    FLoating point Operations Per Second
  • Re:Not a petaflop! (Score:0, Informative)

    by Anonymous Coward on Monday June 15, 2009 @09:31AM (#28334345)

    Like 1 kilometer/s.

  • Re:Not a petaflop! (Score:3, Informative)

    by Useful Wheat ( 1488675 ) on Monday June 15, 2009 @09:35AM (#28334375)

    Flops is short for FLoating point Operations Per Second. There is a point to the s.

  • by JustinOpinion ( 1246824 ) on Monday June 15, 2009 @09:42AM (#28334445)

    If everybody participating were able to total up the costs they incur by doing so, and just donate that to the project, you could probably get better results by buying hardware well matched to the task.

    Maybe or maybe not. One would have to include in the calculation the cost of building additional computers. One of the ways in which distributed computing is "green" is that it uses computers which have already been built, but would otherwise be idle. In this sense it is re-using resources that have already been committed, rather than requiring totally new equipment to be built, which consumes new resources.

    In other words, the newly-built computers would have to be sufficiently more efficient that they fully offset their own production costs, and then some.

    As long as we accept that doing the folding is a worthwhile use of resources ... the question is a matter of how to do it most efficiently

    Indeed. For many computational projects one has to take into the account the likely scaling of computer power and algorithmic power. For instance in principle for a given problem with a given deadline, it can sometimes be cheaper to wait until new computers are on the market, if they will be sufficiently faster (at a given cost) than the older ones. (That is, you may be able to "waste time" and still make your deadline.) Alternately, it may be a total waste of modern computer resources to inefficiently search a given parameter space if we have reason to believe that drastically better algorithms will become available in a few years.

    As it turns out, problems like protein folding are very difficult, and we have no reason to believe that dramatically better techniques are on the horizon. So if (as you say) we care about the problem at all, then it would seem that we can justify the energy spent doing those calculations right now on modern general-purpose machines.

  • by Amouth ( 879122 ) on Monday June 15, 2009 @11:01AM (#28335345)

    it would be intresting but remember that cray is now selling GPGPU powered mini super computers.

  • by Thaelon ( 250687 ) on Monday June 15, 2009 @11:03AM (#28335383)

    Folding@Home, and torrents are more like a micropayment system that actually works.

    Sure it costs you electricity and bandwidth, but in such small amounts (typically) and over time. Plus there are no additional transaction fees or middle men taking a cut. It's tax free, and there are no forms to fill out or any other bureaucracy.

    Torrents are just a distributed micropayment system.

  • by compro01 ( 777531 ) on Monday June 15, 2009 @11:27AM (#28335707)

    According to my UPS's monitoring software, by machine idles (screen off with torrents running) at 180W and hits 210W with folding@home (GPU edition on my 8800GTS) running, 30W extra. Assuming it does that 24 hours a day (it's always on anyway as it also runs as my FTP/web server and for remote access), that comes to 21.6KW-hr per month, which at local electrical rate (9.6 cents/KW-hr) comes to $2.07 per month.

Don't tell me how hard you work. Tell me how much you get done. -- James J. Ling