Using GPUs in sessions and deployments¶
Anaconda Enterprise enables you to leverage the compute power of graphics processing units (GPUs) from within your editor sessions. To do so, you can select a resource profile that features a GPU when you first create the project, or use the project’s Settings tab to select a resource profile after the project is created.
To enable access to a GPU while running a deployed application, select the appropriate resource profile when you deploy the associated project.
In either case, if the resource profile you need isn’t listed, ask your Administrator to configure one for you to use.
Watch this short video to see how to access GPU resources to train a TensorFlow model in a JupyterLab session with Anaconda Enterprise 5.2: