AWS for Industries
Author: Eran Brown
Eran Brown is a senior semiconductor Specialist Solution Architect. He spent 7 years working with semiconductor companies designing HPC storage infrastructure, and after all these years is still amazed at what a square inch of silicon can do.
Cut time to results without changing your EDA flows
Using advanced node technology to successfully manufacture a chip is getting harder as chip geometries continue to shrink. Electronic Design Automation (EDA) consumes more compute, storage, and time. Giving your engineers more time to iterate and find bugs in the design and verification phases will result in saving millions in re-spins and lost revenue. Further […]
Faster post–silicon analysis with an AWS data lake
Manufacturing semiconductor devices using advanced nodes have many challenges, but perhaps none is more directly linked to the company’s profitability and competitive position than yield. Yield improvements directly reduce the cost of manufacturing a single die while also helping the company amortize the development costs across more dies. There are great commercial products helping customers […]
Increasing fab productivity through data classification
Introduction Semiconductor manufacturing has become incredibly complex and the effort it takes to get electronics in front of the end customer at a reasonable price point is very challenging. This coupled with the chip shortage, and the cost and time to build fabs to increase capacity, has led to companies focusing on improving productivity. A […]
Predict the cost of Electronic Design Automation on AWS using simulation
Introduction Designing semiconductor requires High Performance Computing (HPC) to run Electronic Design Automation (EDA) tools. These workloads vary over time in both the amount and type of compute resources required. This makes it an ideal workload for the elasticity of the cloud. Customers choose optimal instance types to optimize each tools runtime. This reduces time-to-results […]
Simplifying microelectronics education labs with Ruby Cherry EDA on AWS
University faculty members and non-profit organizations looking to improve the training experience for the next generation of microelectronics engineers face multiple challenges with the computing environment required, both technical and organizational. In this blog we will review these challenges, and how to solve them using ready-made solutions on AWS and how these solutions can scale […]
Building Elastic HPC Clusters for EDA with Altair on AWS
Introduction Chip design is not only compute and memory intensive, it also requires varying amounts of resource in different Integrated Circuit (IC) design phases: some frontend tools are single threaded and CPU bound, while backend tools rely on high performance storage and large memory. Fixed-size compute farms on-premises result in jobs waiting in queue for […]