Tuesday, September 29th 2020
Folding @ Home Bakes in NVIDIA CUDA Support for Increased Performance
GPU Folders make up a huge fraction of the number-crunching power of Folding@home, enabling us to help projects like the COVID Moonshot open science drug discovery project evaluate thousands of molecules per week in their quest to produce a new low-cost patent-free therapy for COVID-19. The COVID Moonshot (@covid_moonshot) is using the number-crunching power of Folding@home to evaluate thousands of molecules per week, synthesizing hundreds of these molecules in their quest to develop a patent-free drug for COVID-19 that could be taken as a simple 2x/day pill.
As of today, your folding GPUs just got a big powerup! Thanks to NVIDIA engineers, our Folding@home GPU cores—based on the open source OpenMM toolkit—are now CUDA-enabled, allowing you to run GPU projects significantly faster. Typical GPUs will see 15-30% speedups on most Folding@home projects, drastically increasing both science throughput and points per day (PPD) these GPUs will generate.Editor's Note:TechPowerUp features a strong community surrounding the Folding @ Home project. Remember to fold aggregated to the TPU team, if you so wish: we're currently 44# in the world, but have plans for complete world domination. You just have to input 50711 as your team ID. This is a way to donate efforts to cure various diseases affecting humanity that's at the reach of a few computer clicks - and the associated power cost with these computations.
GPU speedups for CUDA-enabled Folding@home core22 on typical Folding@home projects range from 15-30% for most GPUs with some GPUs seeing even larger benefits.
Even more exciting is that the COVID Moonshot Sprints—which use special OpenMM features to estimate how tightly potential therapeutics will inhibit the SARS-CoV-2 main viral protease—can see speedups up to 50-100% on many GPUs, helping us enormously accelerate our progress toward a cure. You can follow Moonshot's progress on Twitter.GPU speedups for CUDA-enabled Folding@home core22 on COVID Moonshot projects—which use special features of OpenMM to help identify promising therapeutics—range from 50-400%!
To see these speed boosts, you won't have to do anything—the new 0.0.13 release of core22 will automatically roll out over the next few days on many projects, automatically downloading the CUDA-enabled version of the core and CUDA runtime compiler libraries needed to accelerate our code. If you have an NVIDIA GPU, your client logs will show that the 0.0.13 core will attempt to launch the faster CUDA version.To get the most performance out of the new CUDA-enabled core, be sure to update your NVIDIA drivers! There's no need to install the CUDA Toolkit.
While core22 0.0.13 should automatically enable CUDA support for Kepler and later NVIDIA GPU architectures, if you encounter any issues, please see the Folding Forum for help in troubleshooting. Both Folding@home team members and community volunteers can provide help debug any issues.
Besides CUDA support, core22 0.0.13 includes a number of bugfixes and new science features, as well as more useful information displayed in the logs.
We're incredibly grateful to all those that contributed to development of the latest version of the Folding@home GPU core, especially:
Source:
Folding @ Home
As of today, your folding GPUs just got a big powerup! Thanks to NVIDIA engineers, our Folding@home GPU cores—based on the open source OpenMM toolkit—are now CUDA-enabled, allowing you to run GPU projects significantly faster. Typical GPUs will see 15-30% speedups on most Folding@home projects, drastically increasing both science throughput and points per day (PPD) these GPUs will generate.Editor's Note:TechPowerUp features a strong community surrounding the Folding @ Home project. Remember to fold aggregated to the TPU team, if you so wish: we're currently 44# in the world, but have plans for complete world domination. You just have to input 50711 as your team ID. This is a way to donate efforts to cure various diseases affecting humanity that's at the reach of a few computer clicks - and the associated power cost with these computations.
GPU speedups for CUDA-enabled Folding@home core22 on typical Folding@home projects range from 15-30% for most GPUs with some GPUs seeing even larger benefits.
Even more exciting is that the COVID Moonshot Sprints—which use special OpenMM features to estimate how tightly potential therapeutics will inhibit the SARS-CoV-2 main viral protease—can see speedups up to 50-100% on many GPUs, helping us enormously accelerate our progress toward a cure. You can follow Moonshot's progress on Twitter.GPU speedups for CUDA-enabled Folding@home core22 on COVID Moonshot projects—which use special features of OpenMM to help identify promising therapeutics—range from 50-400%!
To see these speed boosts, you won't have to do anything—the new 0.0.13 release of core22 will automatically roll out over the next few days on many projects, automatically downloading the CUDA-enabled version of the core and CUDA runtime compiler libraries needed to accelerate our code. If you have an NVIDIA GPU, your client logs will show that the 0.0.13 core will attempt to launch the faster CUDA version.To get the most performance out of the new CUDA-enabled core, be sure to update your NVIDIA drivers! There's no need to install the CUDA Toolkit.
While core22 0.0.13 should automatically enable CUDA support for Kepler and later NVIDIA GPU architectures, if you encounter any issues, please see the Folding Forum for help in troubleshooting. Both Folding@home team members and community volunteers can provide help debug any issues.
Besides CUDA support, core22 0.0.13 includes a number of bugfixes and new science features, as well as more useful information displayed in the logs.
We're incredibly grateful to all those that contributed to development of the latest version of the Folding@home GPU core, especially:
- Peter Eastman, lead OpenMM developer (Stanford)
- Joseph Coffland, lead Folding@home developer (Cauldron Development)
- Adam Beberg, Principal Architect, Distributed Systems (NVIDIA) and original co-creator of Folding@home nearly 21 years ago!
5 Comments on Folding @ Home Bakes in NVIDIA CUDA Support for Increased Performance
I hope soon to be back contributing to this project.
my "old" rx590 would help too and is a good room heater :p