Nvidia invested $2bn in Synopsys common stock at US$414.79 per share as part of a multi-year AI collaboration
Nvidia and Synopsys have announced an expanded strategic partnership to integrate AI and accelerated computing with engineering solutions for research and development teams across semiconductor, aerospace, automotive and industrial sectors. Nvidia invested US$2bn in Synopsys common stock at US$414.79 per share as part of the multi-year collaboration focused on CUDA accelerated computing, agentic and physical AI, and Omniverse digital twins to deliver simulation capabilities at speed and scale beyond traditional CPU computing.
The partnership includes joint development initiatives to accelerate Synopsys applications using Nvidia CUDA-X libraries and AI-Physics technologies across chip design, verification, molecular simulations and electromagnetic analysis. The companies will integrate Synopsys AgentEngineer technology with Nvidia’s agentic AI technology stack including NIM microservices and NeMo Agent Toolkit software for autonomous design capabilities in electronic design automation and simulation workflows.
Nvidia and Synopsys will collaborate on digital twins using Omniverse and Cosmos technologies for industries including semiconductor, robotics, aerospace and automotive. The companies plan to enable cloud access for GPU-accelerated engineering solutions and develop joint go-to-market initiatives utilizing Synopsys’ global network of sellers and channel partners.
“CUDA GPU-accelerated computing is revolutionizing design – enabling simulation at unprecedented speed and scale, from atoms to transistors, from chips to complete systems, creating fully functional digital twins inside the computer,” Jensen Huang, Founder and Chief Executive Officer of Nvidia, said. “Our partnership with Synopsys harnesses the power of Nvidia accelerated computing and AI to reimagine engineering and design.”
Sassine Ghazi, President and Chief Executive Officer of Synopsys, added: “The complexity and cost of developing next-generation intelligent systems demands engineering solutions with a deeper integration of electronics and physics, accelerated by AI capabilities and compute.”
Source: Synopsys
