Overview - Scale-Out Computing on AWS

Overview

Amazon Web Services (AWS) enables data scientists and engineers to manage their scale-out workloads such as high-performance computing (HPC) and deep learning training, without having extensive cloud experience.

The Scale-Out Computing on AWS solution helps customers more easily 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. This solution also deploys a user interface (UI) with cloud workstations, file management, and automation tools that enable you to create your own queues, scheduler resources, Amazon Machine Images (AMIs), and management functions for user and group permissions.

This solution is designed to be a production ready reference implementation you can use as a starting point for deploying an AWS environment to run scale-out workloads, enabling users to focus on running simulations designed to solve complex computational problems. For example, with the unlimited storage capacity provided by Amazon Elastic File System (Amazon EFS), users won’t run out of space for project input and output files. Additionally, you can integrate your existing LDAP directory with Amazon Cognito to enable users to seamlessly authenticate and run jobs on AWS.

Cost

You are responsible for the cost of the AWS services used while running this solution. The total cost to run this solution with default settings in the US East (N. Virginia) Region is approximately $370 per month. This cost estimate includes deploying an m5.large Amazon Elastic Compute Cloud (Amazon EC2) instance, an Application Load Balancer (ALB), a highly available Amazon Elasticsearch Service (Amazon ES) cluster, Amazon EFS, AWS Backup, and a NAT Gateway.

This pricing estimate does not include visualization and compute instances or data transfer costs. For full details, see the pricing webpage for each AWS service you will be using in this solution.