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Launching a GPU Instance

We run our GPUs on virtual machines using customized Docker images. Launching a container is straightforward and can be done in several ways.

Through the Console

  1. Log in to the Snowcell Console: Access the Snowcell Console through your web browser and log in with your credentials.

  2. Navigate to the Instances Page: Go to the 'Instances' section in the console menu.

  3. Create a New Instance:

    • Click on the 'Create Instance' button.
    • Select the desired GPU type from the available options.
    • Configure the instance settings, such as memory, storage, and network configurations.
    • Choose a customized AMI or provide your own Docker image. We have AMIs preinstalled with the most recent ML-libraries.
  4. Launch the Instance: Review your settings and click 'Launch'. Your GPU instance will be up and running within minutes.

Through the CLI

  1. Install Snowcell CLI:

    • Ensure you have the Snowcell CLI installed on your local machine. If not, download and install it through either:
    • pip (PyPI):
      pip install snc
    • Homebrew (macOS):
      brew install snc
    • Binary Release: Download the latest release from the Snowcell GitHub repository and follow the installation instructions provided.
    • Linux (Apt-based systems):
      wget -qO - https://your-snowcell-cli-repo-url/snowcell-cli.gpg.key | sudo apt-key add -
      echo "deb [arch=amd64] https://your-snowcell-cli-repo-url/ stable main" | sudo tee /etc/apt/sources.list.d/snowcell-cli.list
      sudo apt-get update
      sudo apt-get install snowcell-cli
  2. Authenticate the CLI:

    • Use the following command to authenticate the CLI with your Snowcell account:
      snc login
    • Enter your credentials when prompted.
  3. List Available GPU Types:

    • To see the available GPU types, use the following command:
      snc describe-instances
  4. Create a New Instance:

    • Use the following command to create a new GPU instance:
      snc create-instance --type <GPU_TYPE> --memory <MEMORY_SIZE> --storage <STORAGE_SIZE> --network <NETWORK_CONFIG> --image <DOCKER_IMAGE>
    • Replace <GPU_TYPE>, <MEMORY_SIZE>, <STORAGE_SIZE>, <NETWORK_CONFIG>, and <DOCKER_IMAGE> with your desired configurations.

    Example:

    snc create-instance --type nvidia-v100 --memory 16GB --storage 500GB --network default --image my-custom-image:latest
  5. Launch the Instance:

    • Once configured, it will launch automatically. If for some reason the instance is not running, start it manually:
      snc restart-instance --id <INSTANCE_ID>
    • Replace <INSTANCE_ID> with the ID of the instance you created.

Next Steps

After launching your GPU instance, you can connect to it using SSH, deploy your workloads, and start utilizing the computational power for your tasks.