Synopsys is building an open, secure, hardware accelerated agentic AI stack in collaboration with Nvidia to cater to use cases from silicon to systems.
Applied Materials is also collaborating with Synopsys to accelerate complex quantum chemistry simulations for large-scale dynamic materials modeling by up to 30 times using Synopsys QuantumATK optimized with Nvidia.
Synopsys at Nvidia GTC 2026 is showcasing the progress and impact of its strategic partnership with Nvidia to revolutionize design and engineering across industries. R&D teams, from the semiconductor industry to aerospace, automotive, industrial and beyond, face significant engineering challenges including increasing workflow complexity, escalating development costs, and time-to-market pressure.
At GTC, Synopsys is demonstrating how integrating the strengths of NVIDIA’s AI and
accelerated computing with Synopsys’ market-leading engineering solutions is enabling R&D teams to design, simulate, and verify intelligent products at lower cost with greater precision and speed.
“Traditional engineering methods can no longer keep pace with the complexity of today’s software-defined, intelligent systems,” said Sassine Ghazi, CEO of Synopsys, in a statement. “Together with ecosystem partners, Synopsys and NVIDIA are re-engineering how products are designed and developed. By enabling the co-design of electronics and multiphysics, accelerating compute-intensive workloads and applying the power of digital twin for virtual prototyping, we are helping customers engineer the future.”
“AI and accelerated computing are fundamentally reinventing engineering — from how products are designed to how they are built and operated,” said Jensen Huang, CEO of Nvidia. “Modern engineering happens inside simulations and digital twins. Together with Synopsys, we are combining Nvidia CUDA-X, Omniverse, and AI with Synopsys’ silicon-to-systems platforms to reimagine engineering for the age of AI and turn growing complexity into a powerful advantage.”
Synopsys has the industry’s broadest portfolio of engineering applications that enable AI and GPU-accelerated computing across engineering workloads — making engineering smarter, faster, and more intuitive. Customers are utilizing Nvidia GPU-accelerated applications from Synopsys to speed up compute-intensive workloads.
Today, Synopsys announced several examples:
Applied Materials is collaborating with Synopsys and Nvidia to advance AI and quantum chemistry R&D with accelerated materials modeling. Leveraging Synopsys QuantumATK’s new integration with Nvidia cuEST, early results from Applied Materials show a potential 30X speedup for complex quantum chemistry workloads compared to open-source models running on CPUs. Previously, Applied Materials achieved an 8X simulation speedup leveraging NVIDIA GPUs compared to multi-core CPUs for multi-nanometer amorphous systems featuring approximately 25,000 atoms.
“Applied Materials is working with Synopsys and Nvidia to accelerate materials engineering innovations that can deliver tremendous improvements in energy-efficient performance of advanced semiconductor devices,” said Gary Dickerson, CEO of Applied Materials, in a statement. “This collaboration allows us to significantly reduce the time it takes to run simulations of material behavior at the atomic level, thereby enabling the industry to bring chip design breakthroughs to market faster.”
Honda has also realized unsteady, large‐scale, high‐fidelity CFD that was previously impractical on CPUs through GPU acceleration on Ansys Fluent® fluid simulation software.
“We achieved 34x faster computation and 38x cost reduction using four GB200 GPUs compared to 1,920 cloud-based CPU cores,” said Yusuke Uda, Assistant Chief Engineer at Honda, in a statement. “Through close collaboration with Synopsys, Honda is accelerating the migration of its CFD simulations from CPUs to GPUs. This advancement enables us to continue delivering safer, higher‐quality products to our customers at appropriate cost, with consideration for the environment.”
As AI scaling drives the need for high-speed connectivity to move massive datasets with near-zero latency, advanced chips with ultra-high-speed SerDes interfaces require extensive circuit-level simulations.
Astera Labs achieved a 3.5X speedup running Synopsys PrimeSimTM using B200 GPU accelerated EC2 instances on AWS compared to CPU-only instances, dramatically shortening design validation cycles and enabling faster time-to-market for next-generation connectivity solutions.
The seamless access to GPU resources on AWS enables Astera Labs’ design teams to focus on innovation rather than infrastructure setup, further accelerating time-to-market while supporting superior design accuracy.
“The collaboration between Astera Labs, Synopsys, Nvidia, and AWS is transforming our ability to design advanced blocks for AI connectivity silicon,” said Jitendra Mohan, Chief Executive Officer of Astera Labs, in a statement. “By harnessing the power of Nvidia B200 GPU-accelerated computing on AWS, we have significantly reduced simulation times and enhanced design accuracy, allowing us to deliver innovative connectivity solutions to the
market faster than ever before.”
“Astera Labs’ work with AWS — achieving dramatically faster design cycles for the connectivity solutions that power AI — demonstrates how cloud technology is transforming innovation across entire industries,” said Ozgur Tohumcu, General Manager of Automotive and Manufacturing at AWS, in a statement. “We’re enabling companies to access the most advanced computing tools instantly, changing how breakthrough technologies get built without the burden of managing complex infrastructure.”