Cadence Accelerates the Sustainability of AI Factories with NVIDIA Omniverse

AI is transforming industries at an unprecedented pace, and the demand for efficient and sustainable data centers, often called "AI factories," has never been greater. With growing concerns about AI's energy consumption, pursuing every available energy-saving technology to accelerate sustainable computing is essential. By bringing digital twins to the design and operation of data centers, Cadence can deliver AI's benefits to society while reducing the power consumption and environmental impact of data centers.

The semiconductor industry has leveraged digital twins to achieve first-time success in delivering exponential growth in complexity and capability. Using digital twins, built on NVIDIA Omniverse technologies, data center operators can improve their efficiency and utilization by up to 40%, lowering AI's energy footprint and even preventing the need for new data centers to be built in some cases. AI factories can achieve better performance optimization and more efficient resource utilization and energy management by integrating these digital twin technologies.

Cadence is deepening its collaboration with NVIDIA to accelerate digital twin development for AI factory buildout. By integrating core technologies for OpenUSD (Universal Scene Description) and NVIDIA RTX from the NVIDIA Omniverse platform into Cadence's Reality Digital Twin Platform, Cadence will enable the development of more efficient data center designs, aligning with our commitment to reducing carbon footprints and promoting sustainability.

Enhancing the Design, Deployment, and Operation of AI Factories

The Cadence Reality Digital Twin Platform, powered by NVIDIA Omniverse Cloud APIs and OpenUSD, enhances the design, deployment, and operation of AI factories. Cadence’s continued collaboration with NVIDIA enables the ecosystem to leverage advanced computer graphics, generative AI, and simulation capabilities to create and deploy physically accurate, high-fidelity data center digital twins that can be used to accelerate facility design and simulate operational scenarios. The integration of these technologies enables better planning and resource management and provides unique insights that facilitate optimized performance, energy efficiency, and predictive maintenance.

Digital Twin Models for NVIDIA A100 and H100 GPUs and NVIDIA GB200 Systems

To effectively harness digital twins of AI factories, it is essential to develop robust digital twin models for NVIDIA's accelerating computing technologies, including the NVIDIA A100 Tensor Core GPU, NVIDIA H100 Tensor Core GPU, and NVIDIA GB200 NVL72 systems. These digital twin models enable precise simulations of these powerful GPU systems' performance, resource utilization, and thermal dynamics within data center environments. The development of these digital twin models is made possible by OpenUSD, which offers a standardized framework that promotes interoperability and scalability across data ecosystems. By developing on OpenUSD, developers can ensure that their digital twin models are compatible with a wide range of platforms and applications.

To truly capture the benefits of digital twins, Cadence will need a robust library of high-quality models across the ecosystem—including ODMs and critical infrastructure components like cooling.

The Sustainable AI Factory

An AI factory is a modern data center specifically designed to support the deployment and operation of artificial intelligence applications. These factories are characterized by their high-performance computing (HPC) capabilities, which are crucial for processing vast datasets and executing complex algorithms. In an AI factory, advanced hardware, such as NVIDIA GPUs, is integrated with sophisticated software ecosystems to streamline operations and enhance efficiency.

As AI factories grow in prominence, the need for sustainable computing practices becomes even more critical. Integrating advanced technologies such as HPC, machine learning (ML), and real-time analytics can significantly enhance energy efficiency within data centers. Implementing AI-driven solutions allows for more innovative resource management, enabling systems to dynamically adjust to operational demands while minimizing waste. Cadence's collaborative efforts with NVIDIA aim not only to improve the operational effectiveness of AI factories but also to help ensure their environmental impact is mitigated through strategic energy usage and improved regulatory compliance.

Furthermore, by utilizing digital twins, stakeholders can simulate various operational scenarios, thereby predicting potential issues and optimizing resource allocation in a manner that aligns with sustainability goals. This proactive approach enables data center operators to make informed decisions about energy consumption and resource management, helping pave the way for a more sustainable future in technology. As the industry evolves, it is essential to keep sustainable computing at the core of AI factory development as both a responsibility and a competitive advantage.

Building the AI Factories of the Future

Cadence's collaboration with NVIDIA marks a significant step forward in accelerating sustainability and efficiency in AI factories. By leveraging digital twins, businesses can optimize their operations, reduce environmental impact, and drive innovation in the data center industry. The future is promising, and with collective effort and engagement from the broader ecosystem, the full potential of digital twins can be realized, helping benefit society as a whole.

Learn more about the NVIDIA and Cadence partnership to accelerate AI and scientific computing.