What does this AWS Solutions Implementation do?

The Scale-Out Computing on AWS solution helps customers deploy and operate a multiuser environment for computationally intensive workflows, such as computer-aided engineering (CAE). The solution features a large selection of compute resources, a fast network backbone, unlimited storage, and budget and cost management directly integrated within AWS. 

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Benefits

User interface

Scale-Out Computing on AWS deploys and sets up an example UI with a common set of APIs that the administrator and users can use to interact with their Amazon EC2 cluster.

Pre- and post-processing in the cloud

The solution leverages Desktop Cloud Visualization (DCV) graphical sessions to enable users to easily access the cluster to perform any pre- and post-processing visualization actions.

Real-time analytics

Schedulers and application logs are ingested in real-time and stored in the data lake for further processing.

Custom code and automation

The solution is deployed with a collection of scripts that are customizable and can be extended to help users collect data and run common cluster tasks.

AWS Solutions Implementation overview

The diagram below presents the architecture you can automatically deploy using the solution's implementation guide and accompanying AWS CloudFormation template.

Scale-Out Computing on AWS | Architecture Diagram
 Click to enlarge

Scale-Out Computing on AWS architecture

The CloudFormation template deploys the following architecture consisting of eight components:

1. Amazon EC2 Auto Scaling to automatically provision the resources necessary to run cluster user tasks such as scale-out compute jobs.

2. This solution also deploys Amazon Elastic File System (Amazon EFS) for persistent storage, Amazon Simple Storage Service (Amazon S3) for persistent logs, and optional parallel file system Amazon FSx for Lustre.

3. At its core, the Amazon Elastic Compute Cloud (Amazon EC2) instance implements a scheduler, which dynamically provisions AWS resources required for jobs submitted by users. The scheduler instance also hosts web interface which allows users and administrators to interact with the environment.

4. Launch a 2D or 3D Workstation that uses NICE Desktop Cloud Visualization (DCV), that can be used to submit batch jobs and run GUI tools.

5. Security services and resources that are used include AWS Secrets Manager, AWS Certificate Manager, Security Groups , and AWS Identity and Access Management (IAM). 

6. AWS Lambda functions to verify the required prerequisites and create a default signed certificate for an Application Load Balancer (ALB) to manage access to DCV workstation sessions.

7. An Amazon OpenSearch Service (successor to Amazon Elasticsearch service) cluster to store job and host information.

8. Elastic Load Balancing is used to ensure accessibility across Availability Zones, and Cost Allocation Tags are used with AWS Cost Explorer.

Scale-Out Computing on AWS

Version 2.7.0
Release date: 11/2021
Author: AWS

Estimated deployment time: 35 min

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