AMD to run EDA for chip-design workloads on Google Cloud

AMD announced its technology partnership with Google Cloud to run electronic design automation (EDA) for its chip-design workloads on Google Cloud.
AMD EPYC processor for Google Cloud
AMD will also leverage Google Cloud’s networking, storage, artificial intelligence, and machine learning capabilities to further improve upon its hybrid and multi-cloud strategy for these EDA workloads.

AMD will add Google Cloud’s compute-optimized C2D VM instance, powered by AMD EPYC processors, to its suite of resources focused on EDA workloads. AMD aims to run more designs in parallel, giving the team more flexibility to manage short-term compute demands, without reducing allocation on long-term projects.

“Leveraging the Google Cloud C2D instances powered by 3rd Gen EPYC processors for our complex EDA workloads has helped our engineering and IT teams tremendously. C2D has allowed us to be more flexible,” said Mydung Pham, corporate vice president, Silicon Design Engineering, at AMD.

Google Cloud and AMD will continue to explore new capabilities and innovations, while AMD will enjoy benefits such as:

Increased flexibility and choice to run applications in the most efficient manner possible

Improved design and operations from applied Google Cloud artificial intelligence and machine learning tools and frameworks

More transparency with costs and resource consumption

Greater agility and less vendor lock-in

“In today’s semiconductor environment, the speed, scale, and security of the cloud unlock much needed flexibility,” said Sachin Gupta, GM and VP, Infrastructure, at Google Cloud.

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