Creating a Deep Learning VM Instance From the Google Cloud Platform Marketplace

GCP Marketplace lets you quickly deploy functional software packages that run on Compute Engine. A Deep Learning VM can be created quickly from the GCP Marketplace within the GCP Console without having to use the command line.

Before you begin

Before following the steps below, choose the specific Deep Learning VM image to use. Your choice depends on your preferred framework and processor type.

Creating an instance without GPUs

  1. Go to the Deep Learning VM GCP Marketplace page in the Google Cloud Platform Console.

    Go to the Deep Learning VM GCP Marketplace page

  2. Click Launch on Compute Engine.
  3. Enter a Deployment name which will be the root of your VM name. Compute Engine appends -vm to this name when naming your instance.
  4. Choose your Framework and Zone.
  5. In the GPU section, set the number of GPUs to Zero and enter n/a in the Quota confirmation field.
  6. In the CPU section, select your Machine type. Learn more about machine types.
  7. Select your boot disk type and size.
  8. Click Deploy.

Creating an instance with one or more GPUs

Compute Engine offers the option of adding GPUs to your virtual machine instances. GPUs offer faster processing for many complex data and machine learning tasks. Learn more about GPUs.

To provision a Deep Learning VM instance with one or more GPUs:

  1. Go to the Deep Learning VM GCP Marketplace page in the Google Cloud Platform Console.

    Go to the Deep Learning VM GCP Marketplace page

  2. Click Launch on Compute Engine.
  3. Enter a Deployment name which will be the root of your VM name. Compute Engine appends -vm to this name when naming your instance.
  4. Choose your Framework and Zone.
  5. Choose your GPU type. Not all GPU types are available in all zones; confirm that your combination is supported.
  6. Choose the number of GPUs to deploy. Each GPU supports different numbers; confirm that your combination is supported.
  7. An NVIDIA driver is required when using GPUs. You can install the driver yourself, or select the checkbox to have the latest stable driver installed automatically.
  8. Follow the instructions on the page to check your GPU quota, and enter the required phrase to confirm.
  9. In the CPU section, adjust your machine type as needed. For certain workflows, you may want to increase the number of cores (e.g. for CPU-heavy preprocessing) or the amount of memory (e.g. using CPU as a parameter store for distributed training).
  10. Click Deploy.

If you've elected to install NVIDIA drivers, allow 3-5 minutes for installation to complete.

Once the VM has been deployed, the page will update with instructions for accessing the instance.

What's next

For instructions on connecting to your new Deep Learning VM instance through the GCP Console or command line, read Connecting to Instances. Your instance name is the Deployment name you specified with -vm appended.

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