You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
project_blurb: "[Folding@home]({{ project_url }}) 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."
- { device_path: "/dev/dri", device_host_path: "/dev/dri", desc: "Only needed if you want to use your Intel GPU (vaapi)." }
40
36
37
+
readonly_supported: true
38
+
41
39
# application setup block
42
40
app_setup_block_enabled: true
43
41
app_setup_block: |
@@ -56,11 +54,11 @@ app_setup_block: |
56
54
Unlike v7, v8 no longer bundles a local webgui. The web app is loaded from an online source and can only auto-detect instances that are running on the same machine (bare metal) as the browser. This is not possible in a docker container. Therefore, upgrading to v8 requires registering for an online account, retrieving the account token and setting it in the new env var `ACCOUNT_TOKEN`, along with a friendly name in `MACHINE_NAME`.
57
55
58
56
## GPU Hardware Acceleration
59
-
57
+
60
58
### Nvidia
61
-
59
+
62
60
Hardware acceleration users for Nvidia will need to install the container runtime provided by Nvidia on their host, instructions can be found here:
We automatically add the necessary environment variable that will utilise all the features available on a GPU on the host. Once nvidia container toolkit 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.
0 commit comments