Folding@home has announced that cumulative compute performance of systems participating in the project has exceeded 1.5 ExaFLOPS, or 1,500,000,000,000,000,000 floating point operations per second. The level of performance currently available from Folding@home participants is by an order of magnitude higher than that of the world’s most powerful supercomputer.

Right now, cumulative performance of active CPUs and GPUs (which have returned Work Units within the last 50 days) participating in the Folding@home project exceeds 1,5 ExaFLOPS, which is 10 times faster than performance of IBM’s Summit supercomputer benchmarked for 148.6 PetaFLOPS. To get there, Folding@Home had to employ 4.63 million CPU cores as well as nearly 430 thousand GPUs. Considering the nature of distributed computing, not all CPU cores and GPUs are online at all times, so performance available for Folding@home projects varies depending on availability of hardware.

Folding@home Active CPUs & GPUs
Reported on Wed, 25 Mar 2020 23:04:31 GMT
  AMD GPUs NVIDIA GPUs CPUs CPU Cores TFLOPS x86 TFLOPS
Windows 75,823 314,952 474,277 3,588,315 680,371 1,384,998
Linux 3,675 41,113 78,124 811,997 85,028 167,152
macOS - - 41,582 230,198 2,578 2,578
Total 79,498 356,065 593,983 4,630,510 767,977 1,554,728
Note: CPUs and GPUs which have returned Work Units within the last 50 days are considered Active.

The outbreak of COVID-19 has been taxing for a number of computational biology and chemistry projects. IBM recently formed its COVID-19 High Performance Computing Consortium that pools together major supercomputers run by various research institutions and technology companies in the USA to run research simulations in epidemiology, bioinformatics, and molecular modeling. Cumulative performance of supercomputers participating in IBM’s COVID-19 HPC Consortium is 330 PetaFLOPS.

Folding@home distributed computing project uses compute capabilities to run simulations of protein dynamics in a bid to better understand them and find cures for various diseases. Recently F@H started to run projects simulating theoretically druggable protein targets from SARS-CoV-2, which attracted a lot of attention as SARS-CoV-2 and COVID-19 are clearly the hottest topics these days.

We at AnandTech also have our Folding@Home team, which are currently in a race against our sister site Tom's Hardware. If you have a GPU spare that's not too old, think about joining us in our battle. We are Team 198.

Related Reading:

Source: Folding@Home Twitter

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  • quadrivial - Thursday, March 26, 2020 - link

    For comparison, then ENTIRE top 500 supercomputer list Rmax only adds up to 1.646 exaFLOPS

    https://www.top500.org/lists/2019/11/download/TOP5...
    Reply
  • voicequal - Thursday, March 26, 2020 - link

    Bitcoin network is 100,000,000 Terahash/s
    1000 ops per hash (rough order of magnitude)
    = 100 zettaOPS

    SHA256 on Bitcoin doesn't use floating point, so can't technically call them FLOPS.
    Reply
  • Kuto8879 - Thursday, March 26, 2020 - link

    i3 6100 / GTX 1050 Ti. Not much, but all of what I have! GO EVERYONE! Reply
  • vladx - Friday, March 27, 2020 - link

    There's no point until they expand their storage capacity to accommodate the total workload. Reply
  • darkos - Thursday, March 26, 2020 - link

    How about sticking with reports of whether any of this compute capability is actually making any difference at all. How do the results of the compute capability feed into the workflow they have? Is it actually helping, or is it just a huge flight of fantasy to think that this can make a dent in the problem? Reply
  • azfacea - Thursday, March 26, 2020 - link

    why cant we have some fun? what r u doing ruining the fun.

    and yes for protein folding actually its compute that matters not so much network, memory or other things its a bit like searching for encryption key.
    Reply
  • voicequal - Thursday, March 26, 2020 - link

    The F@H site lists 223 academic papers that apparently derived research benefit from F@H computations. Haven't heard of any major scientific breakthroughs, probably because this kind of research and its application are still in their infancy. Reply
  • zodiacfml - Thursday, March 26, 2020 - link

    Wouldn't mind contributing GPUs I have here but power is so expensive, costs similar to some places in Hawaii. Reply
  • voicequal - Thursday, March 26, 2020 - link

    Best to run in cold climates where you can at least use the heat. Reply
  • Soulkeeper - Thursday, March 26, 2020 - link

    If AMD bothered to still support my older vid cards, or my newer raven ridge laptop, in linux they'd be folding too. Reply

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