Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
https://github.com/richstokes/k8s-folding-at-home
⛑ Run folding@home on your Kubernetes cluster
https://github.com/richstokes/k8s-folding-at-home
coronavirus covid folding folding-at-home kubernetes kubernetes-deployment research
Last synced: 11 days ago
JSON representation
⛑ Run folding@home on your Kubernetes cluster
- Host: GitHub
- URL: https://github.com/richstokes/k8s-folding-at-home
- Owner: richstokes
- License: bsd-3-clause
- Created: 2020-03-04T20:54:57.000Z (almost 5 years ago)
- Default Branch: master
- Last Pushed: 2022-10-29T15:17:03.000Z (about 2 years ago)
- Last Synced: 2024-12-11T17:09:31.787Z (11 days ago)
- Topics: coronavirus, covid, folding, folding-at-home, kubernetes, kubernetes-deployment, research
- Language: Dockerfile
- Homepage:
- Size: 41 KB
- Stars: 104
- Watchers: 9
- Forks: 27
- Open Issues: 2
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# k8s-fah
**Run folding@home on Kubernetes**.
The folding@home project [added support](https://foldingathome.org/2020/02/27/foldinghome-takes-up-the-fight-against-covid-19-2019-ncov/) for the Corona virus (2019-nCoV).
This deployment lets you run folding@home on Kubernetes, should you have any spare cluster-power you'd like to donate.
_Note: COVID-19 work units are currently being prioritized, however the folding@home client is liable to select jobs for other diseases too._
_If/when they add an option to work only on COVID-19, I will update the deployment here to do so (until the pandemic is over)._
# Overview
There are options to run this on CPU, GPU or a combination of both.
To use these deployment sets that uses GPU's to fold with, I assume that you have a working k8s cluster that have nodes with either 1 or more NVIDIA GPUs in them. (AMD have not been tested).
We are using the same prerequisites as the [k8s-device-plugin](https://github.com/NVIDIA/k8s-device-plugin)
* NVIDIA drivers ~= 384.81
* nvidia-docker version > 2.0 (see how to [install](https://github.com/NVIDIA/nvidia-docker) and it's [prerequisites](https://github.com/nvidia/nvidia-docker/wiki/Installation-\(version-2.0\)#prerequisites))
* docker configured with nvidia as the [default runtime](https://github.com/NVIDIA/nvidia-docker/wiki/Advanced-topics#default-runtime).
* Kubernetes version >= 1.10
## Installation modes
### Only CPU
> *The default install deploys 2 replicas, limited to using 1 CPU core each.*
>
```bash
kubectl apply -f https://raw.githubusercontent.com/richstokes/k8s-fah/master/folding-cpu.yaml
```
### Only GPU (Nvidia)
> *The default install deploys 2 replicas, limited to using 1 GPU in each pod.*
>
```bash
kubectl apply -f https://raw.githubusercontent.com/richstokes/k8s-fah/master/folding-gpu.yaml
```
### Both CPU & GPU (Nvidia)
```bash
kubectl apply -f https://raw.githubusercontent.com/richstokes/k8s-fah/master/folding-gpu-cpu.yaml
```
### Minikube (CPU only mode)
> Runs 6x replicas, 1 CPU core each.
>
```bash
kubectl apply -f https://raw.githubusercontent.com/richstokes/k8s-fah/master/folding-minikube.yaml
```
I like to give my minikube cluster extra resources with:
```bash
minikube config set cpus 6
minikube config set memory 8192
minikube delete && minikube start
```
### Tested GPU's:
* NVIDIA
* NVIDIA GeForce GTX 1080
* GeForce RTX 2080
* Tesla K40m
* Tesla K80
* V100
* AMD
* ... If you have tested this on AMD GPU's, please make a PR accordingly and update the list!
## Rancher
If you have Rancher, you can easily install by searching for "folding" in your Rancher app catalog.
## DaemonSet
You can also run this as a DaemonSet (runs one replica per node) with:
```kubectl apply -f https://raw.githubusercontent.com/richstokes/k8s-fah/master/folding-daemonset.yaml```
There is a `tolerations` section in this .yaml you can uncomment in order to also run FAHClient on master nodes if you wish.
To enable GPU with the daemon set, uncomment the `nvidia.com/gpu: "1"` lines from `folding-daemonset.yaml` before applying.
# Customizing
Set the replica count and resource limit as appropriate depending on how much CPU you wish to donate. In my testing, memory load has been reasonably low (<512Mi).
I've also added the framework for a `PriorityClass`, so that K8s may preemptively evict folding@home pods if a higher-priority pod needs resources.
## config.xml
The most compatible way to edit the config.xml is by modifying it's values and creating your own Docker image.
You *can* override/mount as a configMap in Kubernetes (you can see the scaffolding for this inside the manifests), however FAHClient seems to what to copy/move this file around, which doesn't work if the file is mounted.
You'll get a bunch of errors from the FAHClient if you do this - there may be a better way to manage the config file - PRs welcome!
# Credits
Special thanks to [Bendik](https://github.com/skandix) for his work on supporting GPUs and general tweaks to the configs.