Cadence Expands AI and Robotics Efforts with Nvidia and Google Cloud
At its recent CadenceLIVE event, Cadence Design Systems unveiled two significant AI-focused partnerships, enhancing its collaboration with Nvidia and introducing new integrations with Google Cloud. These efforts aim to advance AI applications in robotic systems, semiconductor design, and large-scale AI infrastructure.
Combining AI with Physics-Based Simulation for Robotics
The partnership with Nvidia centers on integrating AI with physics-based simulation and accelerated computing to improve robotic systems and system-level design. This approach targets the modeling and deployment of semiconductors and extensive AI infrastructures, including what Nvidia terms “physical AI”—robotic systems trained and tested in simulated physical environments.
Cadence is incorporating its multi-physics simulation and system design tools with Nvidia’s CUDA-X libraries, AI models, and Omniverse simulation environment. This combined platform enables engineers to simulate thermal, mechanical, networking, and power system interactions, allowing for thorough system behavior assessment before physical deployment.
The collaboration also advances robotics development by linking Cadence’s physics engines, which simulate real-world material interactions, with Nvidia’s AI models that train robotic systems in virtual settings. This method reduces reliance on real-world data collection, generating training datasets through precise physics-based simulations.
“The more accurate generated training data is, the better the model will be,” said Cadence CEO Anirudh Devgan. Nvidia CEO Jensen Huang emphasized their active work on robotic systems during the event.
Industrial robotics firms such as ABB Robotics, FANUC, YASKAWA, and KUKA are already leveraging Nvidia’s Isaac simulation frameworks and Omniverse-based digital twins to test and commission robotic production lines virtually before physical implementation.
Advancing Chip Design Automation via Google Cloud
Separately, Cadence introduced a new AI agent aimed at automating physical layout stages of chip design, which translate circuit designs into silicon implementations. This complements a previously launched AI agent focused on front-end circuit design.
Available through Google Cloud, the integration combines Cadence’s electronic design automation tools with Google’s Gemini AI models to automate design and verification workflows. Cloud deployment enables teams to execute these demanding workloads without on-premise infrastructure.
Cadence’s ChipStack AI Super Agent platform employs model-based reasoning to coordinate multiple design stages, interpreting design requirements and automating corresponding tasks. Early deployments have demonstrated productivity improvements of up to 10 times in design and verification tasks.
“We help build AI systems, and then those AI systems can help improve the design process,” Devgan remarked.
Digital Twins and Simulation Validate Complex Systems
Both partnerships emphasize the use of digital twin models and simulations to validate system designs before physical rollout. This software-based testing facilitates performance evaluation, trade-off analysis, and optimization, particularly critical given the high costs and complexities associated with large-scale data center and semiconductor infrastructures.
Nvidia Introduces Quantum AI Models
In a related announcement, Nvidia revealed a new set of open-source quantum AI models called NVIDIA Ising, named after the Ising model from physics. Designed to support quantum processor calibration and error correction, these models promise up to 2.5 times faster performance and threefold accuracy improvements in decoding error correction processes.
“AI is essential to making quantum computing practical,” explained Jensen Huang. “With Ising, AI becomes the control plane – the operating system of quantum machines – transforming fragile qubits into scalable and reliable quantum-GPU systems.”
This suite of advancements underscores the critical role AI continues to play in revolutionizing fields from robotics to semiconductor design and quantum computing, highlighting the strategic importance of collaborations like those between Cadence, Nvidia, and Google Cloud.
Fonte: ver artigo original
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