Today, we have a guest blog post by  Vickie Curtis, a research student in the UK’s Centre for Research in Education and Educational Technology.  She’s working with the Folding@home team…
Read moreWe have been aggressively working on OpenMM (the key code used in the FAH GPU cores), creating new algorithms to increase performance on NVIDIA and AMD GPUs. The results have…
Read moreGuest post from Dr. Greg Bowman, UC Berkeley Prof. Vince Voelz’s lab has published an exciting paper on their recent successes with predicting the structures of protein-like molecules called peptoids…
Read moreThe Quick Return Bonus (QRB) gives more points when WUs are completed quickly. This helps keep the points in line with the science. Now with the GPU core maturing, our…
Read moreWe often have to make difficult decisions on what hardware to support in the future, including adding new platforms or removing existing ones. Removing existing platforms always leads to a…
Read moreGuest post from Dr. Gregory Bowman, University of California, Berkeley One objective of the Folding@home project is to provide insight into general protein folding mechanisms that hold across a variety…
Read moreToday, we have a guest post by Team MaximumPC. Two new work unit servers have been funded by the Folding@home (FAH) community in memory of Gordon T. Smitheman and his…
Read moreApril 2016 update: The latest FAHBench information is available at fahbench.github.io As previously blogged, FAHBench is the official Folding@Home GPU benchmark. It measures the compute performance of GPUs for Folding@Home. In addition,…
Read moreAs also announced on OpenMM/Folding@home programmer Yutong "proteneer" Zhao's web site, we are happy to announce that Folding@Home Core 17 has entered Beta. Externally, you probably won’t notice too much…
Read moreOpenMM is a key part of Folding@home, powering its GPU cores. You can learn more about OpenMM at its youtube page, which includes technical videos on how you can incorporate…
Read more