Key Takeaways:
Synopsys and Nvidia have built autonomous AI agents that can run chip verification and thermal simulation workflows from start to finish, compressing weeks of engineering labor into hours.
At the 2026 DAC Chips to Systems Conference in San Francisco, Synopsys Inc. (Nasdaq: SNPS) demonstrated fully autonomous, long-running agentic workflows spanning electronic design automation (EDA) and computer-aided engineering (CAE), developed in collaboration with Nvidia. The centerpiece is a design verification agent that orchestrates the entire chip verification cycle — from test plan generation to coverage closure and advanced debug — delivering up to 50 times faster time-to-validated RTL while achieving a 20 percent improvement in coverage, according to the company.
"The future of engineering is agentic, where AI agents reason, plan, execute complex workflows and verify their own work across the entire product development lifecycle," said Tim Costa, vice president and general manager for computational engineering at Nvidia. "Synopsys is using Nvidia AI tools and accelerated computing to build simulation and AI physics agents that help teams close verification, automate thermal analysis and compress development cycles from weeks to hours."
The autonomous verification agent, built on Synopsys' AgentEngineer technology and Nvidia's agentic AI infrastructure — including the Nemotron 3 Ultra open model, Agent Toolkit and OpenShell runtime — deconstructs verification goals from specification, design, test repository and user inputs, then orchestrates specialized agents and tools in a closed-loop workflow. The system traces root failure causes throughout development, a capability that moves chip design teams from tool-assisted incremental progress to goal-driven autonomous execution. Synopsys also demonstrated its first fully autonomous CAE workflow for electronics thermal analysis, using Ansys Icepak software (now part of the Synopsys portfolio) to autonomously execute simulation setup, pre-processing and post-processing for complex GPU cooling design optimization in a fraction of the time required for manual approaches.
The competitive landscape shifts as EDA incumbents race to embed agentic AI
Synopsys is not alone in pursuing autonomous engineering agents. Cadence Design Systems is using Nvidia Nemotron and CUDA-X libraries with its recently launched AuraStack AI Super Agent to drive advanced packaging and PCB design from exploration through signoff, claiming up to 20 times faster multiphysics performance. Siemens is using Nvidia NeMo Gym and Nemotron models with its Fuse EDA AI Agent to orchestrate multi-tool workflows across semiconductor, 3D-IC, PCB and system design, delivering more than 10 times faster library characterization in its Solido Characterization Suite. Samsung is applying Nvidia PhysicsNeMo to perform chip-scale thermal-stress analysis across domains containing up to 10 billion cells.
The competitive dynamic mirrors the broader AI infrastructure arms race: whoever delivers the most reliable autonomous agents for chip design could capture a disproportionate share of the $8 billion-plus EDA market, where design complexity is outpacing engineering headcount growth. Synopsys' approach — combining its AgentEngineer orchestration layer with Nvidia's Nemotron models and accelerated computing — positions it to defend its roughly 30 percent share of the EDA market against Cadence and Siemens, both of which are building competing agent stacks on the same Nvidia foundation.
GPU acceleration extends across 20-plus Synopsys products
Beyond agentic workflows, Synopsys expanded its portfolio of GPU-accelerated EDA and multiphysics products to more than 20 tools. PrimeSim SPICE circuit simulations now run up to 18 times faster on Nvidia GPUs compared to CPU-only workloads. Synopsys QuantumATK accelerates semiconductor material innovation by up to 50 times for quantum chemistry simulations using cuEST and up to 200 times for machine-learned force field simulations on Nvidia Blackwell GPU infrastructure. Ansys Lumerical FDTD 3D electromagnetic simulation software achieved a 10 times speedup on Nvidia GPUs when used within Synopsys' Multiphysics Fusion solution for analog and photonic design.
The GPU acceleration push matters because chip design teams face exponentially growing simulation workloads — a single modern system-on-chip can require billions of simulation cycles before tape-out. Every order-of-magnitude speedup in simulation time directly reduces design cycle risk and allows teams to explore more architectural trade-offs before committing to fabrication.
What this means for investors
Synopsys shares have gained roughly 25 percent over the past 12 months, trading at about 35 times forward earnings, according to data compiled by Bloomberg. The autonomous agentic workflows, if adopted broadly, could expand Synopsys' addressable market by enabling EDA tools to capture value previously tied to engineering labor hours — potentially lifting revenue per design win. Customers are currently evaluating the agentic EDA and CAE capabilities, with general availability planned for the second half of 2026. Nvidia, meanwhile, benefits from deepening its software moat: every EDA vendor building agents on Nemotron and Agent Toolkit reinforces Nvidia's position as the compute platform of choice for chip design AI, extending beyond its traditional GPU hardware dominance.
This article is for informational purposes only and does not constitute investment advice.
