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[BOINC](https://boinc.berkeley.edu/) is a platform for high-throughput computing on a large scale (thousands or millions of computers). It can be used for volunteer computing (using consumer devices) or grid computing (using organizational resources). It supports virtualized, parallel, and GPU-based applications.
## Supported Architectures
Our images support multiple architectures such as `x86-64`, `arm64` and `armhf`. We utilise the docker manifest for multi-platform awareness. More information is available from docker [here](https://github.com/docker/distribution/blob/master/docs/spec/manifest-v2-2.md#manifest-list) and our announcement [here](https://blog.linuxserver.io/2019/02/21/the-lsio-pipeline-project/).
Simply pulling `linuxserver/boinc` should retrieve the correct image for your arch, but you can also pull specific arch images via tags.
Docker images are configured using parameters passed at runtime (such as those above). These parameters are separated by a colon and indicate `<external>:<internal>` respectively. For example, `-p 8080:80` would expose port `80` from inside the container to be accessible from the host's IP on port `8080` outside the container.
### Ports (`-p`)
| Parameter | Function |
| :----: | --- |
| `8080` | Boinc desktop gui. |
### Environment Variables (`-e`)
| Env | Function |
| :----: | --- |
| `PUID=1000` | for UserID - see below for explanation |
| `PGID=1000` | for GroupID - see below for explanation |
| `TZ=Europe/London` | Specify a timezone to use EG Europe/London. |
| `GUAC_USER=abc` | Username for the BOINC desktop gui. |
| `GUAC_PASS=900150983cd24fb0d6963f7d28e17f72` | Password's md5 hash for the BOINC desktop gui. |
### Volume Mappings (`-v`)
| Volume | Function |
| :----: | --- |
| `/config` | Where BOINC should store its database and config. |
#### Device Mappings (`--device`)
| Parameter | Function |
| :-----: | --- |
| `/dev/dri` | Only needed if you want to use your Intel GPU (vaapi). |
When using volumes (`-v` flags), permissions issues can arise between the host OS and the container, we avoid this issue by allowing you to specify the user `PUID` and group `PGID`.
Ensure any volume directories on the host are owned by the same user you specify and any permissions issues will vanish like magic.
In this instance `PUID=1000` and `PGID=1000`, to find yours use `id user` as below:
This image sets up the BOINC client and manager and makes its interface available via Guacamole server in the browser. The interface is available at `http://your-ip:8080`.
By default, there is no username or password set. Custom usernames and passwords can be set via optional docker environment variables. Keep in mind that the `GUACPASS` variable accepts the `md5 hash` of the desired password (the sample above is the hash for `abc`). The md5 hash can be generated by either of the following commands:
```
echo -n password | openssl md5
```
```
printf '%s' password | md5sum
```
You can access advanced features of the Guacamole remote desktop using `ctrl`+`alt`+`shift` enabling you to use remote copy/paste and different languages.
It is recommended to switch to `Advanced View` in the top menu, because the `Computing Preferences` don't seem to be displayed in `Simple View`.
Sometimes, the pop-up windows may open in a tiny box in the upper left corner of the screen. When that happens, you can find the corner and resize them.
Hardware acceleration users for Intel Quicksync will need to mount their /dev/dri video device inside of the container by passing the following command when running or creating the container:
```--device=/dev/dri:/dev/dri```
We will automatically ensure the abc user inside of the container has the proper permissions to access this device.
### 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 BOINC docker container.
[](https://mods.linuxserver.io/?mod=boinc "view available mods for this container.")
We publish various [Docker Mods](https://github.com/linuxserver/docker-mods) to enable additional functionality within the containers. The list of Mods available for this image (if any) can be accessed via the dynamic badge above.
