Folding@Home

Creator: Stanford University

Folding@home is possibly the most successful GPGPU application at the moment, with ATI pioneering GPU-based folding years ago with its Radeon X1000 range of GPUs. Since then, folding has spread to the point where Nvidia has supported folding on all GPUs since its GeForce 8-series.

Folding is a client-based distributed computing application that simulates protein folding to aid our understanding of complex diseases such as Alzheimer's, Mad Cow Disease (BSE), CJD, ALS, Huntington's, Parkinson's disease, and many Cancers and cancer-related syndromes. To add some interest to the furthering of scientific and medical research doesn't hold any interest for you, Stanford also has team- and user-based leaderboards, so folding is also a competition.

To fold on your GPU, visit the High Performance Client page and download the latest version. The client downloads work units (aka 'projects') from Stanford, and each work unit is worth a certain amount of points.

You can monitor your folding progress via the FahMon tool, which will calculate how quickly your card can get through the current work unit and extrapolates a points per day (ppd) figure. You can join Custom PC's folding team (currently ranked fifth in the world) by using the team number 35947. Your contribution is valued.

Folding@home performance

Given the identical design and clock speeds of the Sapphire Vapor-X, it should fold at the same rate as any other stock-speed HD 4870. The difference you can see above is due to the different work units that were assigned to the cards - unfortunately it's random as to which project a card is dealt and we couldn't download a 384pt project no matter how many times we re-installed the folding client to get some consistency.

The Vapor-X cooler of the Sapphire card means that it remained much quieter than a reference HD 4870 when folding.

Folding@home power consumption

We tested the power consumption with a Watts Up? Pro power meter, using the device to record the total system power consumption at the wall socket, while we set the card folding. Using the data recorded by the meter we could determine the peak output.

As both ATI and Nvidia test benches are now identical Core i7 systems, we can accurately determine the apples to apples difference of what power both PCs take to run.


With the 1GB of extra memory to power, it's no surprise to see that the Sapphire Vapor-X is a touch more power hungry than the reference 1GB HD 4870. That the difference is relatively low is likely due to folding not requiring much in the way of memory actions, though the fact that the fan doesn't need to blow as hard as that of the reference cooler could also help here. It could also be that Sapphire's claims that its bespoke VRMs are more power efficient than those of the reference design are true.