Keep your GPUs warm with Quarantine@Home: https://quarantine.infino.me/
For first time nvidia-docker users these 2 commands do nothing, skip to install. Make sure all nvidia-dockers are removed first:

sudo docker volume ls -q -f driver=nvidia-docker | xargs -r -I{} -n1 docker ps -q -a -f volume={} | xargs -r docker rm -f
sudo apt-get purge nvidia-docker

Install nvidia-docker 2.0. First install the repository for your distribution:

curl -s -L https://nvidia.github.io/nvidia-docker/gpgkey | sudo apt-key add -
curl -s -L https://nvidia.github.io/nvidia-docker/ubuntu18.04/nvidia-docker.list | sudo tee /etc/apt/sources.list.d/nvidia-docker.list
sudo apt-get update
sudo apt-get install nvidia-docker2 -y
sudo pkill -SIGHUP dockerd
sudo docker run --runtime=nvidia --rm nvidia/cuda nvidia-smi
git clone https://github.com/cjmielke/quarantineAtHome && cd quarantineAtHome

Run Quarantine@Home:

sudo docker build -t quarantinegpu -f Dockerfile.gpu . && sudo nvidia-docker run -it -e ME=Aurum quarantinegpu

Thanks for the guide Aurum. It worked perfectly for me on Linux mint 19.3.

Thanks! Gold man!

Thanks for guide and interesting gpu project to run autodock in a docker. Sadly i could add docker2 on 20.04LTS.

ME=Aurum

default is userid

ME=anonymous

Is there a blacklist/whitelist of GPUs usable for quarantine@home, as there is for F@H? Are there tasks that can only run on a CPU, or would it be more efficient to use only the GPU for quarantine@home while reserving the CPU for something else?

I have quarantine@home running on a virtual instance of Debian Buster right now, CPU only, just to try it out. When I get back home, I'll put together a machine with a GPU; we'll see how it works out.

Are you aware of WCG's Open Pandemic project, and the Ibercivis project? Both seem to be doing similar work. The three seem to compliment one another, as well as Rosetta, F@H, and GPUGrid.

Are there tasks that can only run on a CPU, or would it be more efficient to use only the GPU for quarantine@home while reserving the CPU for something else?

It seems that the same tasks run on either a CPU or GPU.

As for the time, let's put it this way: the average Windows or Linux CPU is in the range of 200 to 400 seconds. My GTX 1070 under Ubuntu 18.04.4 is averaging 8.5620 seconds. (It helps to reserve two CPU cores though.)

EDIT: But it randomly stops running and I have to restart it every few hours or even minutes. I leave my machines on 24/7, so I think they are dropping the connection.

Thanks. I've been getting about 160s/task. I have 2 instances of Q@H running, both in that same VM, to which I assigned 2 cores. (The host laptop has 4.)

So, from your experience on both GPUs and CPUs, it looks like the project is parallel-able. Or "Embarassingly parallel?" (Please excuse my ignorance of the correct terminology; still new to this.) So it'll run better on a GPU. It works on CPU, but that should be reserved for projects that are not parallel-able, or that simply don't have a GPU option, such as Rosetta, WCG, etc.

Sound about right? I'll try it out on some GPUs when I get home.

I'm also doing some due diligence. It's common sense to check out a new project to make sure it's not really a bitcoin mining scam, or that the code isn't malware. So far it looks good.

I will be contributing when they get a Windows client built. Hopefully there is one in the works but I am unsure wishful thinking on my part