The Folding@Home distributed computing program has long been able to run on GPUs, but the latest optimizations are for GPUs that support CUDA.  As CUDA is a relatively closed source architecture from NVIDIA, that leaves AMD GPU users in the cold; with long time users still using CAL/Direct3D to power their GPU Folding efforts.  According to a news story Hardware Canucks spotted, this is about to change as Stanford is working on optimizing F@H for OpenCL and the tests show almost a doubling of performance.  Do keep in mind that F@H results can change from day to day but this is definitely a good sign.

Folding@Home on AMD GPUs takes a leap forward - General Tech  1

If you have not yet encountered Folding@Home or are unclear as to why people give their spare processing cycles to the project you should drop by this thread in our own Folding@Home Forum which describes many of the reasons people choose to fold.  If you feel the cause is worthy enough for you to join up, it would be a great idea to join the Folding Frogs, our own PC Perspective Folding@Home team.  You can learn all about the Folding Frogs and how to join in this thread, if you already fold and would like to jump aboard then we are Team 734.

"A few weeks ago, Stanford introduced the new Core 16 Project 11293 work units which are specifically tailored towards OpenCL-supporting AMD graphics cards. But do they bring the hoped-for increase in Folding@Home performance or is this yet another step towards disappointment?"

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