Google Cloud and AMD announced this weekend a curious technological association, in which AMD will perform electronic design automation (EDA) for your chip design workloads on Google Cloudfurther extending the local capabilities of AMD data centers.
AMD will also leverage Google Cloud’s global networking, storage, artificial intelligence and machine learning capabilities to further enhance its hybrid and multicloud strategy for these EDA workloads.
Scale, elasticity, and efficient use of resources play a critical role in chip design, especially as the demand for computing processing increases with each node advancement.
To remain flexible and scale easily, AMD will add the new C2D VM instance optimized for Google Cloud Computing, powered by AMD EPYC processors third generation, to its set of resources focused on EDA workloads. By leveraging Google Cloud, AMD plans to be able to run more designs in parallelgiving the team more flexibility to handle short-term IT demands, without reducing allocation on long-term projects.
“In today’s semiconductor environment, the speed, scale, and security of the cloud unlock much-needed flexibility,” said Sachin Gupta, general manager and vice president of infrastructure at Google Cloud. “We are excited to provide the infrastructure to support AMD’s computing performance needs and to equip the company with our AI solutions to continue designing innovative chips.”
“Using 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 us with a new way of high-performance resources that allow us to mix and match the right compute solution for our complex EDA workflows,” said Mydung Pham, vice president of Silicon Design Engineering, AMD. “We are excited to be working with Google Cloud to take advantage of its rich cloud features and 3rd Gen EPYC capabilities.”