Rendering images can be accelerated with GPU compute. In the Rendered.ai cloud platform, we use GPU compute on deployed channels to improve channel runtimes. Linux developers who have a NVIDIA GPU on their local machine can use the GPU when developing their channels by installing the NVIDIA Container toolkit and configuring a devcontainer.json file in the codebase. Windows users will only need to configure the devcontainer.json file in the codebase.
The NVIDIA Container Toolkit allows users to build and run GPU accelerated Docker containers. More information about the library can be found at NVIDIA/nvidia-docker.
After installing the NVIDIA Container Toolkit we should be able to test whether Docker has access to your GPU with the following command. This will download an officially supported NVIDIA Docker image and run the 'nvidia-smi' command to query the device.
Next we will configure our VSCode Dev Container startup instructions to use the GPU.
VSCode Development Container
VSCode Development Containers use a devcontainer.json configuration file to instruct VSCode how to startup and run the Docker container. In the devcontainer.json file, we need to modify the runArgs list to include the “--gpus all“ part of our command above. Take a look at the example below:
After we have the change, we can start or restart the Developer Container. In VSCode, press F1 to bring up the command palette then select Remote-Containers: Rebuild and Reopen in Container. We can then test that our Developer Container has access to the GPU by running the nvidia-smi command from a terminal within the container.
