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AMD chooses Google Cloud to provide scale for chip design workloads

Duncan is an award-winning editor with more than 20 years experience in journalism. Having launched his tech journalism career as editor of Arabian Computer News in Dubai, he has since edited an array of tech and digital marketing publications, including Computer Business Review, TechWeekEurope, Figaro Digital, Digit and Marketing Gazette.


Google Cloud and AMD have formed a technology partnership in which AMD will run electronic design automation (EDA) for its chip-design workloads on Google Cloud, further extending the on-premises capabilities of AMD data centese.

AMD will also leverage Google Cloud’s global networking, storage, artificial intelligence, and machine learning capabilities to further improve upon its hybrid and multicloud strategy for these EDA workloads.

Scale, elasticity, and efficient utilization of resources play critical roles in chip design, particularly given that the demand for compute processing grows with each node advancement. To remain flexible and scale easily, AMD will add Google Cloud’s newest compute-optimized C2D VM instance, powered by 3rd Gen AMD EPYC™ processors, to its suite of resources focused on EDA workloads. By leveraging Google Cloud, AMD anticipates being able to run more designs in parallel, giving the team more flexibility to manage short-term compute demands, without reducing allocation on long-term projects.

Sachin Gupta, GM and VP, Infrastructure, at Google Cloud, said: “In today’s semiconductor environment, the speed, scale, and security of the cloud unlock much needed flexibility. We are pleased to provide the infrastructure required to meet AMD’s compute performance needs and equip the company with our AI solutions to continue designing innovative chips.”

Mydung Pham, corporate VP of silicon design engineering at AMD, said: “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 and provided a new avenue of high-performance resources that allows us to mix and match the right compute solution for our complex EDA workflows.

“We’re happy to work with Google Cloud to take advantage of their wealth of cloud features and the capabilities of 3rd Gen EPYC.”

Through this multi-year technology partnership, 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

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