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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  • Cliff34 - Thursday, March 26, 2020 - link

    Forget about amd vs Nvidia. Is Anand ran beating Tom's hardware? Reply
  • Cliff34 - Thursday, March 26, 2020 - link

    I mean to say Anandtech team. Reply
  • Holliday75 - Thursday, March 26, 2020 - link

    Looks like it. Anandtech is 17th and Toms is 19th.

    https://stats.foldingathome.org/teams
    Reply
  • Ryan Smith - Thursday, March 26, 2020 - link

    Yep. We're still showing Tom's who the boss is! Reply
  • Cliff34 - Friday, March 27, 2020 - link

    Yay! Reply
  • npz - Thursday, March 26, 2020 - link

    Part of the increase may also be due to cryptocurrency incentives. Some crypto are using FAH as their proof of work:
    https://foldingcoin.net/ - the original FAH coin, which has long been in service
    and newer coins:
    https://curecoin.net/
    https://bananominer.com/
    Reply
  • SaberKOG91 - Thursday, March 26, 2020 - link

    A very small part if any. People are scared and want this to be over. Participating in something like this is reward enough. Reply
  • Klimax - Friday, March 27, 2020 - link

    One of largest teams on BOINC side is GRCPool and it supports both Rosetta@Home and GPUGrid. Reply
  • tuxRoller - Friday, March 27, 2020 - link

    Damn. It's sad that Linux uses are biased further towards Nvidia than are Windows users.
    Despite AMD's extensive efforts, it really indicates what matters, statistically.
    Reply
  • Spunjji - Tuesday, March 31, 2020 - link

    It's an interesting trend, as it shouldn't follow the same "buy from whoever has the fastest gaming card" logic that Windows purchasers tend to go with (even when they're not buying the fastest card). Reply

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