Creating GPU-Enabled Notebook Servers

Describes how to create and deploy the GPU-enabled notebook servers.

Prerequisites

Sign in to HPE Ezmeral Unified Analytics Software.

About this task

Create GPU-enabled notebook servers in HPE Ezmeral Unified Analytics Software.

Procedure

  1. Click Notebooks icon on the left navigation bar of HPE Ezmeral Unified Analytics Software screen.
  2. Click New Notebook Server. You will be navigated to the Kubeflow Notebooks UI. You can choose JupyterLab as your notebook server within Kubeflow Notebooks.
  3. Configure the notebook server with the following options:
    • Select one of the following docker images:
      • (Tensorflow CUDA image) gcr.io/mapr-252711/kubeflow/notebooks/jupyter-tensorflow-cuda-full:<image-tag>
      • (PyTorch CUDA image) gcr.io/mapr-252711/kubeflow/notebooks/jupyter-pytorch-cuda-full:<image-tag>
    • Set Requested memory in Gi to at least two to three Gi.
    • Set GPUs as follows:
      • Number of GPUs: 1
        NOTE
        With MIG configuration, only one GPU can be assigned per application. To learn more on what happens when you assign more than one GPU to the notebook server, see GPU. For details regarding GPU, see GPU Support.
      • GPU Vendor: Nvidia
  4. Click Launch.

Results

The new GPU-enabled notebook server is created.