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Digital twin technology is soaring in its use cases at the moment. Cadence Design Systems, a long-standing heavyweight in computational software, is expanding its digital twin technology beyond semiconductors.
While Cadence has long been known for its work in EDA (electronic design automation), the company is now using its computational horsepower to simulate systems that range from drug molecules to urban traffic patterns.
In an interview with AIM, Jayashankar Narayanankutty, the group director at Cadence, discussed the company’s expanding digital twin strategy and its implications across sectors.
“At Cadence, we didn’t set out to do this—but over time, our ability to simulate billions of nodes simultaneously evolved into something far more powerful,” Narayanankutty said. “That’s what led us into digital twins, and the results have been nothing short of groundbreaking.”
Simulations to City-Scale Solutions
The company is now powering breakthroughs in drug discovery, reshaping data centre infrastructure, and helping India develop indigenous GPU capabilities.
“Digital twins can model anything, from a single human to a system of multiple machines,” he explained. “You can test ‘what-if’ scenarios in a simulated space instead of experimenting in the real world.”
Digital twins are no longer confined to just engineering simulations. As Narayanankutty explains, “You foresee faults, optimise design, and iterate quickly.”
He added that this capability isn’t just academic. The implications are profound, whether managing a city’s traffic grid, a factory’s assembly line, or the cooling of next-generation AI data centres.
When brought into perspective through the cityscape of Bengaluru, Narayanankutty responded with advancements that could be transformational.
“If Bangalore’s traffic system were modelled as a digital twin, the improvements in flow, congestion management, and real-time routing would be game-changing,” he noted.
In his keynote at GTC 2025, Jensen Huang underscored Cadence’s capability, saying, “NVIDIA uses Cadence Reality digital twins accelerated by CUDA and Omniverse libraries to simulate air and liquid cooling systems… real-time simulation lets us run large-scale what-if scenarios in seconds versus hours.”
The NVIDIA Chapter
Huang clarified, “The future of design will rely on digital ASC designers from Cadence’s AI framework, integrated seamlessly with NVIDIA’s models.”
The partnership between Cadence and NVIDIA lies at the heart of the upcoming shift. With Blackwell, Cadence’s AI-driven simulations have been accelerated up to 50 times, enabling real-time computation and analysis, transforming industries from healthcare to high-performance computing.
Huang called this one of the biggest developments of the last year. “Working with Cadence, Synopsys, Ansys, and all the systems companies, we’ve now made it possible for just about every important EDA and CAE library to be accelerated,” he said.
The Cadence Reality platform, accelerated by NVIDIA, simulates entire systems, from data centres to aircraft takeoffs, allowing for rapid design iterations and improved energy efficiency.
Reimagining Drug Discovery
Perhaps Cadence’s most unexpected application of digital twins is biological simulation. Using its AI-powered Orion platform, the company can now simulate how drugs are delivered to biological cells, a challenge traditionally tackled through expensive and time-consuming field trials.
“We have always been about computational software,” Narayanankutty explains. “We know how to do the maths. We simulate billions of nodes and now are using that to model the best medium for delivering drugs to biological cells.”
He elaborated that this kind of simulation traditionally takes a long time. However, by integrating AI with computational capability, the company “can simulate scenarios that are humanly impossible to replicate through field tests”.
Field tests are usually limited by time, cost, and the number of participants, but AI allows overcoming these limitations. He also notes the company’s shift from being a code-based computational software company to operating in a web-based AI environment.
The company believes it has caught the attention of stakeholders across the industry, who are interested in its achievements.
Digital Twins Inside Data Centres
“Today, nearly 20% of the world’s energy is consumed by data centres,” Narayanankutty noted. One of Cadence’s digital twins’ most tangible use cases is AI-driven data centre design.
The company’s Reality DC platform simulates data centre operations to dynamically optimise cooling and energy usage, two of the most critical cost factors in modern computing.
“We help design data centres specific to the model,” Narayanankutty said. “Then we simulate them in real time so energy consumption decreases.”
Traditional data centres apply uniform cooling, which leads to inefficiencies like higher heat in certain racks, reducing performance, while overcooling in less active areas wastes energy.
“With Reality DC, we dynamically redirect resources to where they’re needed, cutting energy use by up to 30%.”
NVIDIA itself uses Cadence Reality to optimise its AI factories. Huang noted, “Omniverse Blueprint connects with Cadence’s Reality Digital Twin Platform to design and operate AI factories.”
This partnership is already paying dividends, with companies like Schneider Electric deploying these simulations to increase power block efficiency and reliability in real time.
Building an Indigenous Ecosystem
India is in the middle of a semiconductor revival, and Cadence plays a foundational role in shaping its trajectory. With growing demand for domestic chipmaking and the government’s $10 billion push under the India Semiconductor Mission, the timing couldn’t be better.
Its contributions to India’s indigenous GPU initiatives underscore the importance of digital twin technology in scaling local hardware development. “There’s no tribal knowledge yet in 3D IC design that levels the playing field,” Narayanankutty said.
“India has a real chance to leap ahead in these next-gen technologies.”
He highlights India’s readiness to move from a service-based model to a product-centric approach. Digital twins are key to this transition, helping simulate chiplets, optimise supply chains, and streamline manufacturing.
Cadence’s recent acquisitions and divestitures are further shaping its strategy. The acquisition of Secure-IC strengthens its focus on embedded security, which is critical in the era of AI and IoT.
Its tools are already made available to startups under the Design Linked Incentive (DLI) scheme, while the company collaborates with over 350 universities across India. “We’re not just helping companies, we’re helping shape talent and capability,” he noted.
The geopolitical landscape, including US-China trade tensions and US tariff implications, has made supply chain resilience a priority. Cadence’s ability to simulate and optimise supply chains via digital twin technology offers clients a competitive edge in uncertain times.
