Transforming EDA to accelerate chip development: Leveraging AWS Cloud Computing for speed-of-light chip execution and best time-to-market

The semiconductor industry is confronted with significant challenges, including rapidly increasing design complexity and accelerated time-to-market demands. Conventional on-premises compute infrastructures often fail to accommodate the intensive requirements of modern EDA workloads while maintaining cost-effectiveness and achieving fastest possible schedule. More than that, on-premises compute infrastructure increased developers friction and employees dissatisfaction. This keynote discusses how cloud-native solutions, utilizing the EDA-optimized servers, including AWS Graviton processors, and strategic alliances, are fundamentally redefining the economics of EDA.

We will analyze how elastic design capacity signifies a critical departure from traditional constraints, enabling organizations to gain a strategic competitive advantage. Drawing on performance data from Siemens EDA implementations, we will illustrate how AWS Graviton compute empowers IC design teams to expedite verification cycles through optimized workload management, mitigate business risks via diversified compute resources, and establish predictable cost models that facilitate broader verification coverage—ultimately providing measurable improvements in time-to-market.

Key topics to be addressed include:

• Strategic benefits of cloud architectures for managing EDA dynamic need and computational surge
• Advanced security and compliance frameworks surpassing conventional on-premises standards
• Techniques for optimizing compute expenditure based on workload profiles
• Graviton (arm) and their specific relevance to EDA applications
• Outcomes from collaborative efforts among AWS, Siemens, and TSMC demonstrating enterprise-scale feasibility

This evolution encompasses more than cost reduction; it opens new avenues for semiconductor innovation through sophisticated compute strategies capable of scaling with increasing design complexity while alleviating infrastructure constraints.