Tuesday, 25 August 2009


I've recently joined the folding@home project under the name srkiNZ84. Folding@Home is a hugely distributed computing project with the purpose of doing protein folding (anyone remember seti@home?). I've joined TeamUbuntu and started crunching my way through those work units.

At first what got me intrigued with this project was just trying to benchmark my computer(s), but now what really keeps me interested in it is the competition. You see, with this project you get to keep statistics on how many work units you've completed, in what kind of time frame etc... and every member of the project is ranked. This gives rise to cool personal and team statistics screens like this one from extremeoverclocking or this one from xtreme cpu. Personally I think the competition is one of the main reasons that the project has so many followers.

Right now I'm ranked 455th in my team and 171,330th overall. This isn't too bad considering I've only started. However, the only real way I'm going to get into the top 10% or so of the rankings is by making use of a high performance GPU client. These are versions of the folding@home software that run on your graphics card and make use of it's parallel processing capabilities to complete work units in a much shorter space of time. ATI were the first to produce a client for their line of graphics cards, but were soon followed by nvidia, which blew them away with their much better CUDA performance. I'm not even sure that there is a GPU client for Linux (at least not on the official folding@home website), but I haven't been through the whole recruitment post on ubuntu forums, so I'm hoping there's some clues on there.