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Scale-Out Computing on AWS helps customers deploy and operate a multiuser environment for computationally intensive workflows, such as computer-aided engineering (CAE). This AWS Solution features a large selection of compute resources, a fast network backbone, unlimited storage, and budget and cost management directly integrated within AWS.
Benefits
User interface
Deploy and set up an example user interface (UI) with a common set of APIs that allow the administrator and users to interact with their Amazon Elastic Compute Cloud (Amazon EC2) cluster.
Pre- and post-processing in the cloud
Help users easily access the EC2 cluster to perform any pre- and post-processing visualization actions through Desktop Cloud Visualization (DCV) graphical sessions.
Near real-time analytics
Ingest schedulers and application logs in near real-time, and then store them in the data lake for further processing.
Custom code and automation
Customize and extend a collection of scripts deployed with the solution to help users collect data and run common cluster tasks.
Step 6 AWS Lambda functions verify the required prerequisites and create a default signed certificate for an Application Load Balancer (ALB) to manage access to DCV workstation sessions.
Step 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 a web interface which allows users and administrators to interact with the environment.
Step 4 Launch a 2D or 3D Workstation that uses Amazon DCV, which can be used to submit batch jobs and run GUI tools.
Step 6 AWS Lambda functions verify the required prerequisites and create a default signed certificate for an Application Load Balancer (ALB) to manage access to DCV workstation sessions.
Step 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 a web interface which allows users and administrators to interact with the environment.
Step 4 Launch a 2D or 3D Workstation that uses Amazon DCV, which can be used to submit batch jobs and run GUI tools.
Step 6 AWS Lambda functions verify the required prerequisites and create a default signed certificate for an Application Load Balancer (ALB) to manage access to DCV workstation sessions.
Step 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 a web interface which allows users and administrators to interact with the environment.
Step 4 Launch a 2D or 3D Workstation that uses Amazon DCV, which can be used to submit batch jobs and run GUI tools.
Step 6 AWS Lambda functions verify the required prerequisites and create a default signed certificate for an Application Load Balancer (ALB) to manage access to DCV workstation sessions.
Step 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 a web interface which allows users and administrators to interact with the environment.
Step 4 Launch a 2D or 3D Workstation that uses Amazon DCV, which can be used to submit batch jobs and run GUI tools.
AWS re:Invent 2020: Rivian pushes the pace of automotive innovation with AWS
This video shows a re:Invent 2020 presentation detailing how how Rivian overcame obstacles and improved the engineering experience while encouraging self-service with cloud-based services and automation.
This video demonstrates how to implement Scale-Out Computing on AWS to deploy and operate a multiuser environment for computationally intensive workflows.
In 2020, Rivian found that its on-premises research and development information technology infrastructure could not keep up with its performance needs.
Resource bottlenecks affected product lifecycle management, computer-aided design, and computer-aided engineering, so Rivian began using AWS to architect an agile engineering environment.
Scaling EDA Workloads using Scale-Out Computing on AWS
Semiconductor and electronics companies using electronic design automation (EDA) applications can significantly accelerate their product development lifecycle and time to market by taking advantage of the near infinite compute, storage, and other resources available on AWS.
This blog post provides architectural and system-level guidance to build out an environment capable of scaling EDA applications to 30,000 cores or more.
Deploying multi-physics simulations for biopharma process development on AWS
Amgen built and integrated a HPC platform based on the open-source Scale-Out Computing on AWS solution as an extension of their current AWS cloud infrastructure.
With this solution, Amgen was able to build a convenient and easy-to-use platform to run computation fluid dynamics simulations, expediting medical device development and biopharmaceutical process development.
