Folding@home is a distributed computing project, run by Stanford University, that utilizes the combined processing power of thousands of computers around the world to run complex simulations in an effort to help solve some of the medical mysteries surrounding the worlds most deadly diseases, namely Alzheimers, Huntington's, Parkinson's and Cancer.
Folding@home uses your computer to run protein folding simulations. Many diseases are believed to be caused by protein mis-folding, and running these simulations helps scientists and medical professionals get closer to understanding what causes these afflictions. Folding@home downloads a "work unit," or a "WU" to your computer. The program then runs the necessary simulations, and sends the completed WU back to a Stanford Folding@home WU collection server. The data from the various WU's being folded on multiple machines can be compiled by the project maintainers and used to help eventually discover the root cause of many of these diseases.
Folding@home now allows you to leverage your CPU as well as any compatible graphics cards you have towards the project. Most relatively new (within the last 5 to 6 years) Nvidia and AMD graphics cards are compatible, Nvidia cards must be CUDA compatible however. Almost all x86 CPU's are compatible with the project as well, although older CPU's will complete work unit's very slowly.
The Folding@home client can be controlled in a few different ways, either by command-line, an online client control or a downloadable FAH Client Control application (which is compatible with Linux, Windows and Mac operating systems). You can set Folding@home to use spare CPU and GPU power to fold quietly in the background while you use your computer regularly, or set the client to fold at full power, using close to maximum CPU and GPU power. Dedicating your machine to folding at maximum power obviously increases the speed at which WU's are folded.
Many people choose to fold anonymously, or under a user name. Others decide to join folding teams. Teams climb up in rank based upon the number of WU's folded. WU's are assigned point values, some greater than others, determined by the complexity and length of time required to fold a particular work unit. An infinite number of users can join a particular team. This page has a Folding@home team, called Folding@PC Tech & Headphone Hub (formerly called Folding@Audiophiles). If you decide to participate in the Folding@home project, and wish to participate in a team, our team number is 218845. Team statistics can be pulled up at the Folding@home website (which I have linked at the end of this article.)
Running Folding@home at maximum, especially on a high-end desktop can put a significant strain on your power bill. I tend to fold off an on with my gaming rig (which has two graphics cards and draws a large amount of power) instead of constantly (or even nightly) to avoid significantly increasing the power bill. Setting your client to light folding however, will reduce the power draw of your machine while still contributing to the project in a big way.
If you are interested in the Folding@home project, but haven't heard about it before, I would recommend reading up on the project. I find the biological, scientific, and technical/ computational aspects of the project extremely interesting, and if you do decide to begin folding, consider joining the Folding@PC Tech & Headphone Hub team!
Folding@PC Tech & Headphone Hub Team