Synopsys and Microsoft have developed Synopsys.ai Copilot which designs ICs for the Azure Open AI Service.

 

Synopsys.ai is an AI-driven EDA suite. Azure OpenAI Service gives access to OpenAI’s large language models (LLMs) with the enterprise-ready capabilities of Microsoft Azure.

Together, the companies collaborated to support Synopsys’ development of Synopsys.ai Copilot, bringing together Azure OpenAI Service generative AI capabilities with Synopsys’ industry-leading chip design tools and IP to help engineering teams accelerate time to market and address systemic complexity through the power of conversational intelligence.

“The semiconductor industry is racing to develop faster, more efficient, and optimized computing, which is also driving complexity. At the same time, we’re facing a projected 15% to 30% workforce gap for chip design engineers by 2030,” said Shankar Krishnamoorthy, general manager of the Synopsys EDA Group. “AI-driven design can help address these challenges. Synopsys pioneered AI-driven design with our Synopsys.ai EDA suite. Now, working collaboratively with Microsoft, we’re taking AI-driven design to the next level with generative capability such as conversational intelligence delivered in this first Synopsys.ai Copilot.

In 2022, Synopsys introduced the industry’s first SaaS EDA solution powered by Microsoft Azure.

This collaboration is designed to deliver:

New AI-powered experiences: Synopsys.ai Copilot works alongside designers in the Synopsys tools they use every day, enabling conversational intelligence, in natural language, across the design team. Synopsys.ai Copilot, the first in a planned line of generative AI capability from Synopsys, is designed to learn new skills and grow with teams’ needs, making it easier for chipmakers to boost productivity and achieve design targets across all stages of chip design, from system architecture exploration to design and manufacturing.
AI infrastructure at scale: Deployable in any on-prem or on-cloud environment, Synopsys.ai Copilot integrates Microsoft Azure on-demand high-performance computing infrastructure with the availability, affordability, and capacity to handle AI workloads for advanced chip design and verification applications.
Safe and responsible design: Underpinning the collaboration is a mutual focus on building responsible AI systems that are safe and trustworthy. The intention of this framework is to promote the safe deployment of AI technologies in the creation of new silicon-based applications.