With news of the rapid spread of Coronavirus dominating news cycles, shutting down entire regions and cities, causing mass panic and – tragically – many untimely deaths, it’s hard not to feel a little bit helpless in the face of all that’s going on.
How Your Computer’s GPU Can Help Fight Coronavirus
Anyone who owned a PlayStation 3 will probably remember Folding@home. When the PS3 was released back in 2006 (or 2007 in Europe) its Cell processor was as much as 20x faster than PCs of the time for performing certain types of calculations. Folding@home took advantage of that power from March 2007 until November 2012, allowing users to form part of a network of distributed computing power, so that whilst the PS3 was unused its immense power could be used not for gaming and HD graphics but to simulate protein folding, computational drug design and other types of molecular dynamics.
Think of it like this: instead of (or as well as) building a single, huge supercomputer in one location, this is instead lots of smaller mini-supercomputers (the PS3s) distributed around the world and connected together via the Internet.
The individual “nodes” of the distributed supercomputer all perform their tasks and then send the results back to the main Pande Laboratory at Stanford University, where they are combined into larger datasets which can then be worked upon by researchers and other scientists.
It’s not just PS3s which can help; modern-day graphics cards are immensely powerful, and NVIDIA themselves have fully endorsed gamers and others with powerful GPUs getting behind this effort:
PC Gamers, let’s put those GPUs to work.
— NVIDIA GeForce (@NVIDIAGeForce) March 13, 2020
Join us and our friends at @OfficialPCMR in supporting folding@home and donating unused GPU computing power to fight against COVID-19!
Learn more → https://t.co/EQE4u7xTZT pic.twitter.com/uO0ZCq8PEv
The team at Folding@home have worked tirelessly in recent weeks to get a bunch of projects up and running, and at the time of writing there are 8 ongoing projects which anyone running the software can contribute spare computing power to (see the original Reddit post here).
How Can I Install Folding@Home to use my GPU to Fight Coronavirus?
All you need to do is download and install the Folding@home software. Once installed and setup, it’ll open a Web Control page in your web browser where you can choose whether it should run all the time (probably not) or just when your computer is Idle (ie. when you’re not using your computer). You can also choose how much of your system’s power you want it to use, because bear in mind running this at full power for extended periods WILL put up your electricity bill somewhat. But then, that’s your donation to a worthwhile cause for humanity.
I set mine to Full Power and opened up the Windows task manager to see how much it would make use of my NVIDIA GeForce GTX 1080 and as you can see, it was only using around 44% of the GPU and around a quarter of my (overclocked) Intel Core i7-3770K CPU:
Disk/storage usage as well as RAM usage appears to be negligible, so if you’re the type of person who leaves your computer on most of the time, then you can put it to good use and help with vital work when you’re not working or gaming – and there are plenty of other projects that Folding@home works towards as well, besides the COVID-19 research effort.
This won’t be suitable for everyone, though, so don’t be disappointed if your computer isn’t really powerful enough to contribute as it’s a pretty intensive workload. You can contribute by directing others whose computers can help out to this article!
Have you already installed Folding@home to help in the fight against Coronavirus? Are you going to after reading this article? Let us know in the comments below and please share this article with anyone who has a powerful GPU which can join in the effort!
By the way…
If you want to see just how powerful a GPU can be compared to the computer’s CPU for certain tasks, here’s a video we made about the NVIDIA GTX 1080 graphics card in a direct head-to-head comparison against the Intel Core i7 for video editing work: