EggXpert

We are also releasing another type of client, the Folding@home SMP client. SMP means "Symmetric Multi-processing" and it is a term that generally refers to the situation where a computer has more than one processor core. Dual core CPU's are pretty common and even 4-core boxes (currently implemented as dual socket dual core computers, such as Apple's Mac Pro) are becoming common. With advances from Intel and AMD, quad core processors are on the horizon, with 8-core and even 16-core boxes soon to become common.

The goals of the SMP client and the GPU client are similar: in order to tackle many of the problems of interest (especially related to protein misfolding and aggregation, such as in Alzheimer's Disease), we need to not just have lots of computers participating, but we need results returned more quickly so that we can simulate trajectories of sufficient length. Right now, we achieve this by running for many months to years (indeed, our first Alzheimer's Disease simulations ran for almost two years straight). That's where the SMP and GPU (and PS3) clients come in. They give us considerably longer trajectories in the same wall clock time, allowing us to turn what used to take years to simulate even on FAH, to a few weeks to months.

Moreover, the SMP and GPU clients are complementary. The GPU client can greatly (~30x) speed up a specific type of calculation (implicit solvent calculations), whereas the SMP client can lead to a 4x speed up over the complete range of calculations we need to run. Even a 4x speed up is significant here, since it affects virtually all types of FAH calculations, turning a year's worth of work into a few months. As multi-core CPUs become more common, we expect this trend to become more and more important, especially as 8-core boxes (with dual 4-core CPUs) have already been announced.

Our goal is to apply this new technology to dramatically advance the capabilities of Folding@home, applying our simulations to further study of protein folding and related diseases, including Alzheimer’s Disease, Huntington's Disease, and certain forms of cancer. With these computational advances, coupled with new simulation methodologies to harness the new techniques, we will be able to address questions previously considered impossible to tackle computationally, and make even greater impacts on our knowledge of folding and folding related diseases. "