Arm, says AWS, will leverage AWS for its cloud use, including the vast majority of its EDA workloads by leveraging AWS Graviton2 -based instances (powered by Arm Neoverse cores) - leading the way for transformation of the semiconductor industry, which has traditionally used on-premises data centers for the computationally intensive work of verifying semiconductor designs. To carry out verification more efficiently, Arm uses the cloud to run simulations of real-world compute scenarios, taking advantage of AWS's virtually unlimited storage and high-performance computing infrastructure to scale the number of simulations it can run in parallel.
"AWS provides truly elastic high performance computing, unmatched network performance, and scalable storage that is required for the next generation of EDA workloads," says Peter DeSantis, Senior Vice President of Global Infrastructure and Customer Support, AWS, "and this is why we are so excited to collaborate with Arm to power their demanding EDA workloads running our high-performance Arm-based Graviton2 processors. Graviton2 processors can provide up to 40% price performance advantage over current-generation x86-based instances."
Arm says that since beginning its AWS cloud migration it has realized a 6x improvement in performance time for EDA workflows on AWS. In addition, by running telemetry - the collection and integration of data from remote sources - and analysis on AWS, Arm says it is generating more powerful engineering, business, and operational insights that help increase workflow efficiency and optimize costs and resources across the company. The company ultimately plans to reduce its global datacenter footprint by at least 45% and its on-premises compute by 80% as it completes its migration to AWS.
Highly specialized semiconductors - such as those that power everything from smartphones, to data center infrastructure, to medical equipment, to self-driving vehicles - can each contain billions of transistors engineered down to the single-digit nanometer level (roughly 100,000x smaller than the width of a human hair) to drive maximum performance in minimal space. EDA is one of