73 lines
2.5 KiB
Markdown
73 lines
2.5 KiB
Markdown
# Folding@Home Docker Image Builds for Nvidia GPUs [](https://jenkins.home.keganmyers.com/job/folding-at-home-docker-gpu/)
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This is a fork of [this](https://github.com/wandhydrant/folding-at-home-docker-gpu)
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repo with minor modifications to make pre-built images.
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## Usage
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### Run it:
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GPU access by containers went through several stages:
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first direct export of /dev/dri and other devices; then
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solutions with Docker "runtimes" (nvidia-docker v1
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and v2); the current variant is the Nvidia Container
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Toolkit. The latter is the only one I tested this with.
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As for the BOINC Nvidia container, please:
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1. Install Docker (19.03 or later);
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2. Install the Nvidia drivers (so that "nvidia-smi" gives you output on the host);
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3. Install the [Nvidia Container Toolkit](https://github.com/NVIDIA/nvidia-docker) (see "Usage" on the linked page to test nvidia-smi in a container).
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Finally you can run this container:
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```
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docker run -d \
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--name folding-at-home \
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--gpus all \
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-h node \
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-e USER=Anonymous \
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-e TEAM=0 \
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-e ENABLE_GPU=true \
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-e ENABLE_SMP=true \
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--restart unless-stopped \
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terribleplan/folding-at-home-docker-gpu:latest \
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--allow 0/0 --web-allow 0/0
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```
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``-h node`` sets an anonymous hostname instead of copying yours.
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The last line means that Folding@home's web access will let everybody in,
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but as the port is not exported, you can use it only from the Docker host,
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pointing your browser at the container:
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```
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echo http://$(docker inspect --format "{{range .NetworkSettings.Networks}}{{.IPAddress}}{{end}}" folding-at-home):7396
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```
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### (optional) Build the image yourself
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If you do not wish to use pre-built images you can build it yourself:
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```
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cd <git-checkout>
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docker build -t my-fah-nvidia-image .
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```
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## Parameters
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- USER - Folding@home username (default: Anonymous)
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- TEAM - Foldinghome team number (default: 0)
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- PASSKEY - [optional] Folding@home [passkey](https://apps.foldingathome.org/getpasskey)
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- ENABLE_GPU - Enable GPU compute (default: true)
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- ENABLE_SMP - Enable auto-configuration of SMP slots (default: true)
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- POWER - by default "full"; but you might want to switch to "medium" and see how hot your hardware gets (especially laptops). "light" did not use the GPU at all for me. You can always switch this in the web interface.
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Additional configuration parameters can be passed as command line arguments. To get the full list of parameters run:
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```
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docker run terribleplan/folding-at-home-docker-gpu --help
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```
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