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Lab 1: Deploy Environment

We want you to have hands-on experience deploying your own cluster, and in this module we will have you walk through the process of launching a cluster in your temporary AWS account. This cluster will be provisioned in the background. For the subsequent modules you'll access a pre-built cluster where EDA tools and licenses have been provisioned.

Step 1: Launch stack

This automated AWS CloudFormation template deploys a scale-out computing environment in the AWS Cloud.

  1. Sign in to the AWS Management Console and click the Launch Stack link in the instructions below to launch the scale-out-computing-on-aws AWS CloudFormation template.

    Launch Stack <--- CLICK HERE

  2. Verify the launch region is Oregon

    Important

    The template must be launched in Oregon for this workshop.

  3. On the Create stack page, you should see the template URL in the Amazon S3 URL text box and choose Next.

  4. On the Specify stack details page, assign a name to your solution stack. We recommend naming it "tutorial".

    Warning

    The stack name must be less than 20 characters and must be lower-case only.

  5. Under Parameters, modify the the last four parameters, which are marked with REQUIRED. Leave all other fields with their default values. These are variables passed the CloudFormation automation that deploys the environment.

    Parameter Default Description
    Install Location
    Installer S3 Bucket solutions-reference The default AWS bucket name. Do not change this parameter.
    Installer Folder scale-out-computing-on-aws/v2.6.1 The default AWS folder name. Do not change this parameter.
    Linux Distribution
    Linux Distribution AmazonLinux2 The preferred Linux distribution for the scheduler and compute instances. Do not change this parameter.
    Custom AMI If using a customized Amazon Machine Image, enter the ID. Leave this field blank.
    Network and Security
    EC2 Instance Type for Scheduler node m5.xlarge The instance type for the scheduler. Do not change this parameter.
    VPC Cluster CIDR 10.0.0.0/16 Choose the CIDR (/16) block for the VPC. Do not change this parameter.
    IP Address See description REQUIRED The public-facing IP address that is permitted to log into the environment. We recommend you change it to your public-facing IP address. You can find your public-facing IP address at http://checkip.amazonaws.com then add the /32 suffix to the IP number.
    Key Pair Name ee-default-keypair REQUIRED Select the ee-default-keypair provided by the workshop.
    Default LDAP User
    User Name REQUIRED Set a username for the default cluster user.
    Password REQUIRED Set a password for the default cluster user. (5 characters minimum, uppercase/lowercase/digit only)

  6. Choose Next.

  7. On the Configure Stack Options page, choose Next.

  8. On the Review page, review the settings and check the two boxes acknowledging that the template will create AWS Identity and Access Management (IAM) resources and might require the CAPABILITY_AUTO_EXPAND capability.

  9. Choose Create stack to deploy the stack.

You can view the status of the stack in the AWS CloudFormation console in the Status column. You should see a status of CREATE_COMPLETE in approximately 35 minutes.

By now you've learned how to deploy Scale-Out Computing on AWS to create a compute cluster for EDA Workloads in an AWS account. For the remaining portion of the this tutorial, you'll login to a different pre-built cluster that has the following items:

  • Synopsys VCS and Verdi software pre-installed,

  • A license server with valid licenses, and

  • Test case to use for VCS and Verdi

You can now move on to the next lab. Click Next.