Today, computer-aided engineering (CAE) is standard in any industry that uses design software to develop new products or to create new features for existing products. CAE allows
engineers to perform simulations of a product’s physical properties quickly by eliminating the need to build a physical prototype. Virtually all industries are using CAE in product development processes, including: automotive, aerospace,plant engineering, electronics, energy, and consumer goods.
Simulating with CAE takes only a few hours at most, compared to the days or weeks it would
require to build a physical prototype. Products that can be test simulated range from extremely small components inside electronic devices or machine parts, to very big and complex structures such as race cars, bridges, skyscrapers, or even power plants.
Engineers need simulation models to quickly and accurately ensure the effective functioning
of a product in all environments and at different periods of time in a product’s lifecycle. However, realistically simulating a product’s complex geometries and testing those in all conditions requires an immense amount of computing power.
CAE simulations require storing and processing large amounts of data, and this is only possible
with “clusters” or groups of really powerful high performance and reliable computers connected through high speed communication channels. Modern simulation tools, software as a service (SaaS) solvers, and cloud computing, have removed barriers to streamlining the difficult endeavor of CAE. Engineers can now leverage the power and speed of high performance computing (HPC) in the cloud to speed up the standard CAE workflow and significantly reduce the cost and time required for each design iteration cycle.
A better alternative—leverage the latest technologies on AWS
By using the AWS Cloud, engineers across all disciplines can access nearly infinite HPC compute infrastructure capacity and resources to run complex simulations, for a fraction of the time and cost it would take to run locally. AWS delivers an integrated suite of services that provides everything needed to quickly and easily build and manage HPC clusters in the cloud to run the most compute-intensive CAE workloads to support your organization or project.
AWS removes the long wait times and lost productivity often associated with on-premises HPC clusters. Flexible configuration and virtually unlimited scalability allow you to grow and
shrink your infrastructure as your workloads dictate, not the other way around. All the while, you only pay for the resources you consume.
Your organization may be at the start of the journey with some initial CAE projects in the pipeline, or you may be an engineer working independently without a great deal of administrative support.
Either way, AWS is here to help you integrate the value of CAE more deeply into your engineering process. If you aren’t already exploring CAE now, you may need to play catch-up.
The speed of innovation required to engineer new products and solutions is continuously challenging the processes that administrators need to develop internally to stay competitive.
There is tremendous value for your organization and for your career as an engineer, developing skills in cloud-based CAE.
AWS provides the most elastic and scalable cloud infrastructure to run your HPC applications. With virtually unlimited capacity, engineers, researchers, and HPC system owners can innovate beyond the limitations of on-premises HPC infrastructure. AWS delivers an integrated suite of services that provides everything needed to quickly and easily build and manage HPC clusters in the cloud to run the most compute intensive workloads across various industry verticals. These workloads span the traditional HPC applications, like genomics, computational chemistry, financial risk modeling, computer aided engineering, weather prediction, and seismic imaging, as well as emerging applications, like machine learning, deep learning, and autonomous driving.
HPC on AWS removes the long wait times and lost productivity often associated with on-premises HPC clusters. Flexible configuration and virtually unlimited scalability allow you to grow and shrink your infrastructure as your workloads dictate, not the other way around. Additionally, with access to a broad portfolio of cloud-based services like Data Analytics, Artificial Intelligence (AI), and Machine Learning (ML), you can redefine traditional HPC workflows to innovate faster.
Today, more cloud-based HPC applications run on AWS than on any other cloud. Customers like Bristol-Myers Squibb, FINRA, BP and Autodesk trust AWS to run their most critical HPC workloads.