Use GPU in Render Animation Worker Job

[philippotto]

Detailed Description

As a follow-up to #7348, speed might be improvable by using the GPU in the worker job.

Context

• Specific to long-running jobs (set jobsEnabled=true in application.conf)
• Specific to webknossos.org (set isDemoInstance=true in application.conf)

[hotzenklotz]

Time measurements for a single frame based on job 655b4d0e01000026094d9893__render_animation__1700482319547

• Cycles @ Blender 3.3 CPU NYT-Docker on Humerus : 01:13.68
• Eevee @ Blender 3.6.5 CPU on ???: 03:50.79
• Cycles @ native Blender 3.6.5 CPU Humerus: 01:05.13
• Eevee @ native Blender 3.6.5 GPU Euphorix: 00:01.12

[philippotto]

• Eevee @ native Blender 3.6.5 GPU Euphorix: 00:01.12

Awesome! So, very good news, right?

[hotzenklotz]

Awesome! So, very good news, right?

Well... we already knew that GPU support is quick. But the WK worker is no running a on a GPU server. Nor was this in Docker....

[philippotto]

Ok, I see..

[hotzenklotz]

With the nvidia-container-toolkit installed you can just run the regular wk-worker Docker container to benefit from GPU support, e.g.

docker run \
    -v $(pwd):$(pwd) \
    -w $(pwd) \
    -u $(id -u ${USER}):$(id -g ${USER}) \
    --rm \
    --gpus all  \
    --runtime=nvidia \
    --privileged \
    -e NVIDIA_VISIBLE_DEVICES=all \
    -e NVIDIA_DRIVER_CAPABILITIES=display,compute \
    -v /run/nvidia-persistenced/socket:/run/nvidia-persistenced/socket \
    -v /var/run/nvidia-fabricmanager/socket:/var/run/nvidia-fabricmanager/socket \
    -v /tmp/nvidia-mps:/tmp/nvidia-mps \
    scalableminds/webknossos-worker:23.11.1.post15.dev0--e32a27ebe \
    blender --background --python create_blender_animation.py

Ca. 0.13s per frame on Euphorix with Geforce GTX 1080

[hotzenklotz]

Blender had a peak usage of slightly more then 900MB of VRAM for my test dataset (2 large meshes).