linuxserver/foldingathome¶
Folding@home is a distributed computing project for simulating protein dynamics, including the process of protein folding and the movements of proteins implicated in a variety of diseases. It brings together citizen scientists who volunteer to run simulations of protein dynamics on their personal computers. Insights from this data are helping scientists to better understand biology, and providing new opportunities for developing therapeutics.
Supported Architectures¶
We utilise the docker manifest for multi-platform awareness. More information is available from docker here and our announcement here.
Simply pulling lscr.io/linuxserver/foldingathome:latest should retrieve the correct image for your arch, but you can also pull specific arch images via tags.
The architectures supported by this image are:
| Architecture | Available | Tag |
|---|---|---|
| x86-64 | ✅ | amd64-<version tag> |
| arm64 | ✅ | arm64v8-<version tag> |
| armhf | ❌ |
Application Setup¶
This image sets up the Folding@home client. The interface is available at http://your-ip:7396.
The built-in webserver provides very basic control (ie. GPUs are only active when set to Medium or higher). For more fine grained control of individual devices, you can use the FAHControl app on a different device and connect remotely via port 36330 (no password).
There are a couple of minor issues with the webgui: - If you get an "ERR_EMPTY_RESPONSE" error when trying to access via IP, it's most likely due to a clash of cookies/cache. Try opening in an incgnito window. - If you're getting a constant refresh of the window but no display of info, try a force refresh via shft-F5 or ctrl-F5.
GPU Hardware Acceleration¶
Nvidia¶
Hardware acceleration users for Nvidia will need to install the container runtime provided by Nvidia on their host, instructions can be found here: https://github.com/NVIDIA/nvidia-docker We automatically add the necessary environment variable that will utilise all the features available on a GPU on the host. Once nvidia-docker is installed on your host you will need to re/create the docker container with the nvidia container runtime --runtime=nvidia and add an environment variable -e NVIDIA_VISIBLE_DEVICES=all (can also be set to a specific gpu's UUID, this can be discovered by running nvidia-smi --query-gpu=gpu_name,gpu_uuid --format=csv ). NVIDIA automatically mounts the GPU and drivers from your host into the foldingathome docker container.
Usage¶
To help you get started creating a container from this image you can either use docker-compose or the docker cli.
docker-compose (recommended, click here for more info)¶
---
+ foldingathome - LinuxServer.io linuxserver/foldingathome¶
Folding@home is a distributed computing project for simulating protein dynamics, including the process of protein folding and the movements of proteins implicated in a variety of diseases. It brings together citizen scientists who volunteer to run simulations of protein dynamics on their personal computers. Insights from this data are helping scientists to better understand biology, and providing new opportunities for developing therapeutics.
Supported Architectures¶
We utilise the docker manifest for multi-platform awareness. More information is available from docker here and our announcement here.
Simply pulling lscr.io/linuxserver/foldingathome:latest should retrieve the correct image for your arch, but you can also pull specific arch images via tags.
The architectures supported by this image are:
Architecture Available Tag x86-64 ✅ amd64-<version tag> arm64 ✅ arm64v8-<version tag> armhf ❌
Application Setup¶
This image sets up the Folding@home client. The interface is available at http://your-ip:7396.
The built-in webserver provides very basic control (ie. GPUs are only active when set to Medium or higher). For more fine grained control of individual devices, you can use the FAHControl app on a different device and connect remotely via port 36330 (no password).
There are a couple of minor issues with the webgui: - If you get an "ERR_EMPTY_RESPONSE" error when trying to access via IP, it's most likely due to a clash of cookies/cache. Try opening in an incgnito window. - If you're getting a constant refresh of the window but no display of info, try a force refresh via shft-F5 or ctrl-F5.
GPU Hardware Acceleration¶
Nvidia¶
Hardware acceleration users for Nvidia will need to install the container runtime provided by Nvidia on their host, instructions can be found here: https://github.com/NVIDIA/nvidia-docker We automatically add the necessary environment variable that will utilise all the features available on a GPU on the host. Once nvidia-docker is installed on your host you will need to re/create the docker container with the nvidia container runtime --runtime=nvidia and add an environment variable -e NVIDIA_VISIBLE_DEVICES=all (can also be set to a specific gpu's UUID, this can be discovered by running nvidia-smi --query-gpu=gpu_name,gpu_uuid --format=csv ). NVIDIA automatically mounts the GPU and drivers from your host into the foldingathome docker container.
Usage¶
To help you get started creating a container from this image you can either use docker-compose or the docker cli.
docker-compose (recommended, click here for more info)¶
---
version: "2.1"
services:
foldingathome:
@@ -51,4 +51,4 @@
--pull \
-t lscr.io/linuxserver/foldingathome:latest .
The ARM variants can be built on x86_64 hardware using multiarch/qemu-user-static
Once registered you can define the dockerfile to use with -f Dockerfile.aarch64.
Versions¶
- 14.12.22: - Rebase to Ubuntu Jammy, migrate to s6v3.
- 15.01.22: - Rebase to Ubuntu Focal. Add arm64v8 builds (cpu only). Increase verbosity about gpu driver permission settings.
- 09.01.21: - Add nvidia.icd.
- 14.04.20: - Add Folding@home donation links.
- 20.03.20: - Initial release.
Last update: October 10, 2023
Created: February 5, 2019
\ No newline at end of file
+Once registered you can define the dockerfile to use with -f Dockerfile.aarch64.
Versions¶
- 14.12.22: - Rebase to Ubuntu Jammy, migrate to s6v3.
- 15.01.22: - Rebase to Ubuntu Focal. Add arm64v8 builds (cpu only). Increase verbosity about gpu driver permission settings.
- 09.01.21: - Add nvidia.icd.
- 14.04.20: - Add Folding@home donation links.
- 20.03.20: - Initial release.
Created: February 5, 2019