Semiconductor and Electronics Resources
Find whitepapers, videos, blogs, and technical tools for semiconductor and electronics.
Optimizing electronic design automation on AWS
This whitepaper presents an overview of the EDA workflow, recommendations for moving EDA tools to AWS, and the specific AWS architectural components to optimize EDA workloads on AWS.
Best practices for deploying ClioSoft SOS7 on AWS
This paper outlines the advantages of and best practices for deploying the ClioSoft SOS design data management software on the AWS Cloud platform.
Using Ellexus Breeze for EDA workload migration to AWS
This whitepaper outlines the best practices for migrating Electronic Design Automation (EDA) workloads to AWS using the I/O profiling and dependency analysis tool suite Breeze from Ellexus. Profiling the EDA tool on premises and in the cloud ensures that the AWS configuration is right sized for the application and that costs are optimized.
Blogs & articles
AWS and Arm help semiconductor companies innovate faster with increased flexibility
David Pellerin and Caroline Lawrence
Aug 15, 2020
Introduction to semiconductor design workflows on AWS
Mark Duffield and David Pellerin
Feb 25, 2020
Semiconductor and Electronics on AWS: Enabling collaboration and innovation from customer specification to silicon
Architectural deep dive into AWS services, data movement, analytics, and collaboration across the design process.
Semiconductor and Electronics on AWS: AWS services and data movement for semiconductor design
An architectural overview of AWS services and data movement options for semiconductor design workflows.
Scale-out computing on AWS, services used
Launch a turnkey scale-out computing environment in minutes.
Remote desktop for EDA
Launch Xilinx Vivado design suite using NICE DCV remote desktop on AWS.
EDA on AWS with IBM Spectrum LSF
Running EDA workloads on AWS with LSF Resource Connector.
Decoupled serverless scheduler, part 1 of 2
Deploy a decoupled serverless scheduler to run any HPC application at scale.
Videos & webinars
How do you innovate and enable new products in an increasingly fast paced industry? Henk Coenen from NXP dives into NXP's transformation and how innovation can be enabled by embracing failure and taking the right approach to organization change.
In this session, learn how AWS helps achieve the maximum possible performance and throughput for design and verification workloads and enhances electronic product manufacturing through advanced analytics and machine learning. See optimization techniques and architectures for accelerating batch and interactive workloads. Learn to extend and migrate on-premises EDA workloads with AWS and to use a combination of instances to minimize costs.
In this session, we discuss deployment tools and methods, and use cases, for running the entire EDA workflow on AWS. Using customer examples, we show how AWS can improve performance, meet tape-out windows, and effortlessly scale out to meet unforeseen demand.
Technical tools & training
Scale-out computing on AWS
An overview of the AWS Solution (Architecture Diagram, Features, and Deployment Resources) Scale-Out Computing on AWS is a solution that helps customers more easily deploy and operate a multiuser environment for computationally intensive workflows.
EDA workshop with IBM Spectrum LSF
The CloudFormation templates in this workshop deploy a fully functional IBM Spectrum LSF compute cluster with all resources and tools required to run an EDA verification workload on a sample design in the AWS Cloud.
AWS decoupled serverless scheduler
This guide goes over the deployment process, which leverages AWS CloudFormation. This allows you to use infrastructure as code to automatically build out your environment.
AWS remote desktop for EDA
In this workshop we will demonstrate the high performance capabilities of NICE DCV leveraging the Xilinx Vivado Tool Suite, a popular EDA (Electronic Design Automation) tool suite.
Wafer data analysis of WM811K on AWS
This workshop goes the process of first launching an EC2 instance, then downloading and analyzing semiconductor wafer data ([MIR_LAB]) for the purposes of understanding how a foundry can better predict and prevent failures more quickly.