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Nvidia And Stanford Finalizing Folding@Home Client For GeForce GPUs

 

Santa Clara (CA) - During Nvidia Editor’s Day, we learned that Nvidia and the Folding@Home research group led by Vijay Pande are making final preparation to launch the first version of the Folding@Home client for Nvidia graphics processors.

The unveiling of the client is set for the next week as part of the launch of Nvidia’s GT200 GPU series. Owning such a card will have its benefits in Folding@Home and will outrun Radeon 3870 cards. The new GeForce cards are expected to hit more than 650 nanoseconds of protein simulation in a single day, while the Radeon HD 3870 is stuck at about 170 ns. The Playstation 3 is able to produce "only" 100 ns of simulation, while a quad-core CPU creates an output of just four nanoseconds. For those who are keeping count: The GeForce GPU will be about 163 times faster than a quad-core processor in this specific application.

Nvidia founded Team "Whoopass", which consists only of several computers that are running the Folding@Home GPU client. Even with just 4-5 test machines, the team quickly moved into the top 5% of all contributors by sheer processing power. Dr. Vijay told us that if only 1% of all CUDA-capable users would start using Folding@Home in their spare time, the Folding@Home machine would quickly be considered the fastest performing HPC computer in the whole world - hitting about 60-80 Peta FLOPS of processing power.

Folding@Home for Nvidia CUDA-capable graphics cards (GeForce 8 and above) should become available next week. The codename for this client is GPU2/NVIDIA. The GPU1 client was retired, while GPU2 client will continue to be updated for both Nvidia and ATI cards.

ATI was first with a client for the Folding@Home project, which was released back in September of 2006 for the X1900 series of cards. Back then, the cards topped out at 375 GFlops. The next GPU generation should provide more than double the horsepower.

  • ilovebarny
    man those cards sound awesome!!!
    Reply
  • Lozil
    Amazing.....163 times faster than Quadcore....?? Astonishing... :D

    http://free-and-useful.blogspot.com
    Reply
  • A_Dying_Wren
    Hmm... next gen ATI are much better in terms of GFLOPS so this should be interesting...
    Reply
  • When's SETI@HOME coming out with this?
    Reply
  • heffeque
    I've got a 8600 GT on my MacBookPro. Will it work on MacOS X or only on Windows?
    Reply
  • Wheat_Thins
    I am assuming the speed boost comes from the built in physics processing that is shipping with the new cards courtesy of the Ageia buyout?
    Reply
  • Fadamor
    I posted a reference to this article on Stanford's Folding Forum, and Vijay Pande replied that they are HOPING the client can be released "soon", but that it is still in QA at this time. He also specifically addressed this article as follows:

    "PS Note that Tom's H numbers are a bit misleading. We're not getting 650ns/day (yet) on the gtx280 (more like 550) and we're now getting 250ns/day on 3870's in the lab (perhaps 300ns/day in time), and the 3870's are the previous gen ATI cards. The gtx280 is going to be really great at folding though."
    Reply
  • Fadamor
    Heffeque, Based on the article, as long as the card can understand nVidia's CUDA programming language, it should work. Whether PandeGroup provides a Mac installer to go with a Win installer is up to them.

    Everyone, please note that the performance specs they're quoting in the article (and in Vijay Pande's response above) are based on the new GPU nVidia is releasing next week. Those of us with the older GPUs will not have the same performance boost but it still should be much better than the SMP or single core clients.
    Reply
  • whats folding@home do?
    Reply
  • Fadamor
    Stanford University has a Distributed Computing project ongoing to predict the causes of protein mis-folding... the suspected causes of fatal diseases such as Amalydosis, Alzheimer's, and Mad Cow.

    You can find all sorts of information on their website: http://folding.stanford.edu

    Basically, they use your computer when it's "twiddling its thumbs" to crunch a minute portion of a protein's normal (or abnormal) folding process. The result is sent back to Stanford, where they add it into the results returned by other participants. There are over one million participants from all parts of the world, so Stanford is able to get faster results than if they used a supercomputer!
    Reply