The industry heavy-weights continue to progress through new collaborations aimed at embedding AI across semiconductor design and engineering workflows
The Nvidia GTC event has always been known to be more than just an industry gala. In fact, for years, it has served industry pundits, trends spotters, and the audiences with glimpses of the next big innovations in tech. So, at the GTC-DC event last week, predictably, the highlights were AI, quantum, and 6G — the trio dominating headlines in 2025.
Synopsys, an industry bellwether in electronic design automation (EDA) and silicon IP, attended the event to showcase its engineering solutions, powered by Nvidia — and announced yet another collaboration with the chip giant. According to the announcement, Synopsys is using the Nvidia NeMo Agent Toolkit and Nemotron open models for AgentEngineer, Synopsys’ agentic AI technology (released in May) for streamlining and improving engineering workflows.
“From our perspective, AI is really the right solution at the right time because we are seeing a tremendous increase in chip design complexity generation-over-generation, and for Nvidia to build these amazing chips on a yearly cycle, the only way to really have that kind of schedule and deliver that kind of complexity is to have AI all over the design flow,” said Shakar Krishnamoorthy, chief product development officer at Synopsys, during a panel discussion at the event.
Now in it’s third generation of AI solutions, Synopsys has been decisively injecting reinforcement learning into validation, test, and analog space designs for years. The goal, as CEO Sassine Ghazi has emphasized in the recent past, is to incorporate AI — especially AI agents — into chip design and simulation, so that human engineers can offload the laborious steps of design and validation and achieve higher efficiency and productivity.
The recent collaboration builds on this same effort and deepens integration of AI tools into Synopsys’ chip design flows for enhanced engineering productivity, design quality, and time-to-market.
In an interview with the Reuters, Shankar Krishnamoorthy said, “AI plays a huge role, because your R&D capacity is not growing… You’ve got a certain team, you’re not going to just double it, triple it, quadruple it. So you have to increase this R&D capacity.”
The integration of Nvidia AI toolkit into Synopsys’ technology has resulted in breakthrough accelerations, according to both companies. “Simulation software providers like Ansys, part of Synopsys, are using NVIDIA PhysicsNeMo to achieve up to 500x speedups in computational engineering,” writes Timothy Costa, senior director of CAE, quantum and CUDA-X at Nvidia, in a blog.
By leveraging Nvidia for Fluent, Ansys’ fluid simulation software, the software is able to manage workloads much faster. Running on eight Nvidia Blackwell GPUs, Fluent demonstrated 50x speed gains compared to 258 CPU cores.
The GPU acceleration is now further compounded with the incorporation of Nvidia PhysicsNeMo AI physics framework and Nvidia DoMINO NIM that are being used to initialize simulations, delivering 10x more GPU time gains — and 500x faster speeds compared to traditional methods.
“These are not incremental optimizations—they’re architectural shifts that redefine engineering velocity and fidelity,” Prith Banerjee, senior VP of Simulation & Analysis Incubation Group at Synopsys, wrote in a LinkedIn post.
Simulation tools are vital for catching bugs in chip designs early on. The new framework marks the beginning of advanced fluid simulations where costly computational tasks in the early phases are eliminated with a highly accurate initial state. The combined effect of GPU performance enhances and accuracy of AI physics leads to simulations being completed in 40 mins — compared to what took 2 weeks before, say Synopsys and Nvidia.
The collaboration is however not limited to AI. Synopsys is also leveraging Nvidia to accelerate computational materials simulation. Its QuantumATK atomistic simulation software now uses the Blackwell architecture and Nvidia CUDA-X libraries, achieving “15x improvement in time to results” for quantum-mechanical methods, resulting in faster development of AI-driven solutions.
For those who do not know, Synopsys and Nvidia’s partnership is not new. It goes back to when Nvidia’s corporate office used to be a one-room office. The alliance started to create buzz when Ghazi and Jensen Huang, CEO of Nvidia, together took to the stage at a 2024 GTC event. Huang revealed that Nvidia has been relying on Synopsys’ simulation and design tools to catch errors in chip design and tape-outs for years.
As computational power becomes a strong currency in the AI economy, the alliance of these two juggernauts will be a force-multiplier in the AI chip design, validation and automation space, as they lean on each other to capitalize this huge market opportunity opening up for AI.
As Hiếu Trần Trung, senior manager, SoC Engineering at Synopsys, wrote in a recent LinkedIn post, “The Synopsys–NVIDIA relationship positions both companies as central players in the shift toward AI-powered engineering. Their joint efforts are laying the foundation for a future where digital twins, real-time simulation, and AI physics models become standard tools across industries.”