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The [email protected] project gains CUDA support, potentially speeding it up on NVIDIA GPUs by about 30%

Folding@home's software on a Covid-19 benchmark.
[email protected]'s software on a Covid-19 benchmark.
[email protected] has developed software that makes the complex process of protein structure analysis crowd-sourced. Accordingly, it benefits from the "spare" GPU power of its contributors' PCs. Furthermore, its software now has CUDA support, which may allow it and the Covid-19 research it feeds into to get much faster.

[email protected] (FAH) has produced software that allows huge numbers of users to dedicate some of their PC's power to the computational analysis of protein structure. As with many similar tasks, this is GPU-intensive. The project has been getting by on the OpenCL platform thus far. Now, however, it may be able to get more out of participating NVIDIA cards by harnessing their CUDA cores instead.

The project team estimates that this switch may improve the rate at which they generate data points per day by about 60% - although this upper limit generally applies to older cards such as the GTX 660. However, it may translate into gains of 15-30% for the average GPU.

FAH's work now also feeds into the analogous COVID Moonshot project, which is currently working on finding the candidate drug that best inhibits the SARS-CoV-2 main viral protease. NVIDIA GPUs can now crunch numbers that go towards this goal at rates of 50 to 100% faster compared to older versions of this software. The update that adopts CUDA support should take over seamlessly without input from contributors.


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> Notebook / Laptop Reviews and News > News > News Archive > Newsarchive 2020 09 > The [email protected] project gains CUDA support, potentially speeding it up on NVIDIA GPUs by about 30%
Deirdre O'Donnell, 2020-09-29 (Update: 2020-10- 2)