05. Launch Your Instance

Launch an Instance

Once AWS approves your GPU Limit Increase Request, you can start the process of launching your instance.

• Goto the EC2 Management Console

• Click on the “Launch Instance” button.
• Click "AWS Marketplace"
• Search for "Deep Learning AMI with Source Code (CUDA 8, Ubuntu)" AMI.
• Click the "Select" button for the "Deep Learning AMI CUDA 8 Ubuntu Version" AMI.

AMI (Amazon Machine Images) contains all the environment files and drivers for you to train on a GPU. It has cuDNN, and many other packages required for this course. Any additional packages required for specific projects will be detailed in the appropriate project instructions.

Instance Type

• Filter the instance list to only show “GPU instances”
• Select the p2.xlarge instance type
• Click on the “Review and Launch” button'

Security Groups

You'll be running a few Jupyter notebooks in this course, which default to port "8888". To access this port, you'll need to open this up on AWS by editing the security group.

• Click on "Edit security groups"

• Setup a security group
  • Select "Create a new security group"
  • Set the "Security group name" to "Jupyter"
  • Click "Add Rule"
  • Set a "Custom TCP Rule"
  • Set the "Port Range" to "8888"
  • Select "Anywhere" as the "Source"
• Click "Review and Launch"

Launch

• Click on the “Launch” button to launch your GPU instance.

  • AWS will ask if you’d like to specify an authentication key pair. You'll need to do so in order to access your instance, so you select “Create a new key pair” and click the "Download Key Pair" button. This will download a .pem file, which you'll need to be able to access your instance. Move the .pem file to a secure and easily remembered location on your computer; you'll need to access your instance through the location you select.

• After the .pem file has been downloaded, click the “Launch Instances” button.

• Click the “View Instances” button to go to the EC2 Management Console and watch your instance boot.

Be Careful!

From this point on, AWS will charge you for running this EC2 instance. You can find the details on the EC2 On-Demand Pricing page.

Most importantly, remember to “stop” (i.e. shutdown) your instances when you are not using them. Otherwise, your instances might run for a day, week, month, or longer without you remembering, and you’ll wind up with a large bill!

AWS charges primarily for running instances, so most of the charges will cease once you stop the instance. However, there are smaller storage charges that continue to accrue until you “terminate” (i.e. delete) the instance.