• Enterprises require AI platforms that are designed to run on on-premises equipment and are also cloud-enabled.
  • By offloading the naturally compute-intensive AI algorithms to advanced high-performance servers in the cloud, companies can free up their on premium capacity for more traditional EDA workloads.
  • AI and ML workloads in EDA and systems will be powering the next explosion of cloud compute.
  • Leveraging the cloud for EDA tasks is growing exponentially as the industry moves towards advanced nodes and pursues ever-greater power, performance, and area (PPA), higher bandwidth and lower latency.
  • As we head towards 3nm and below, compute infrastructure requirements increase by multiple orders of magnitude, which, in-turn, necessitates the need for more advanced chips.
  • It is a virtuous cycle that is driving the overall need, and it is easy to see why EDA in the cloud is rapidly becoming a necessity— even for companies with near-unlimited on-premium capacity.
  • With the adoption of cloud, companies are discovering that the performance of their current EDA tools increases by an order of magnitude, too—everything just works that much faster.
  • With the next generation of processors available instantly only in the cloud, they are able to increase engineering productivity and slash costs and project timelines.
  • In summary, AI and cloud together will bring unprecedented functionality, scale, and access, which are enabling the next wave of innovation in semiconductor and electronics design.


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