Cadence: Leveraging Sustainability for a Competitive Edge

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Mark Fenton, Product Engineering Director for Cadence
Mark Fenton, Product Engineering Director at Cadence explores how Cadence is leveraging AI and data to make sustainability a competitive edge

Mark Fenton, Product Engineering Director at Cadence explores how the software company is using AI and data-driven solutions to ensure that sustainability is a competitive advantage.

Please introduce yourself and your role.

I’m Mark Fenton, Product Engineering Director for Cadence Reality DC software, physics-based digital twin platform that simulates cooling and power distribution behavior through data centers. I have over 20 years of experience in computational fluid dynamics (CFD) and a master’s in mechanical engineering, which I use to help data center professionals optimise design and operations.

My job at Cadence involves incorporating global data center market trends, engineering technologies, and customer and sales requirements into the development, marketing, and sales strategies for our software products. The digital twin software I work on leads to significant improvements in cooling and power efficiencies within data centers, including the prevention of overheating in equipment. This can often impact the performance of critical applications. Furthermore, using digital twins helps facilities reduce overprovisioning, which refers to operators deliberately allocating more resources than necessary to meet peak demands. As this powerful technology improves resource allocation, it drastically reduces the overprovisioning of energy, leading to more sustainable practices and reduced carbon use in the data center.

Please give an overview of the division you are in at Cadence.

Cadence is a global leader in electronic design, driving innovation across many industries, such as data centers, automotive, mobile, consumer, industrial, and life sciences. One key aspect of the business is its cutting-edge digital twin technology, which essentially creates virtual replicas of physical data centers. This allows data center personnel, such as engineers, to simulate and design entire systems before investing time and money into implementing them, highlighting performance issues and providing recommendations for improvements.

Data centres are often incredibly energy intensive

For example, a simulation could be used to test how the data center would react to different cooling strategies and evaluate energy consumption. By replicating these real-world conditions, data centers can develop more energy-efficient and sustainable strategies without impacting current operations.

How is your division at Cadence leveraging sustainability to gain a competitive edge?

Cadence is on a mission to solve technology’s toughest challenges and make a lasting, positive impact on the world. This mission has become even more critical as the rapid implementation of AI drives massive energy consumption, putting significant strain on data centers worldwide. For example, the Electric Power Research Institute (EPRI) report estimates that while a traditional Google search consumes about 0.3 watt-hours of electricity, a single ChatGPT request uses approximately 2.9 watt-hours — nearly 10 times more energy. This increasing demand places immense pressure on national power grids and, in some cases, has even conflicted with other infrastructure projects, such as housing developments, that are competing for resources like energy and water.

As public awareness of AI's environmental footprint grows, businesses face increasing pressure to adapt and implement the technology. Cadence’s solutions allow data centers to embrace the power of AI within their operations with digital twins. Not only this, but Cadence also helps facilities manage the pressures created by housing AI, which provides us with a competitive advantage. The main reason is that digital twins capture real-time data on energy consumption, equipment performance, and cooling efficiency, which allows data centers to track key metrics, identify inefficiencies, and improve reporting. As a result, this helps data centers perform better operationally while meeting growing regulatory demands for transparency on energy use. Meanwhile, internally, Cadence’s dedication to driving meaningful change and supporting sustainability makes working here all the more rewarding for team members.

What role do AI and data-driven solutions play in your division's efforts to enhance efficiency and achieve environmental goals?

Data centers face increasing pressure to meet sustainability goals while maintaining operational efficiency. This challenge is highlighted by the EU’s 2025 Energy Efficiency Directive, which will introduce new requirements for energy and water usage reporting by May 2025. By enabling comparisons of industry performance, the directive will drive the creation of new targets and potentially even further regulations that promote greater energy efficiency.

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Digital twin solutions play a pivotal role in meeting environmental goals. Acting as a central hub, digital twins unify disparate data sources within a data center into a comprehensive, actionable model. This structure enables operators to make faster, data-informed decisions. AI takes this further, as it can conduct predictive tasks. AI surrogates, digital replicas that act as substitutes or representations of real-world entities, such as humans, can understand performance in a fraction of the time. They can allow operations to make more effective capacity decisions that optimise their available resources.

How does your division at Cadence invest in the evolution of skills and talent?

The data center industry continues to undergo a generational shift whereby experienced professionals retire, and a new wave of younger, tech-savvy talent brings in AI, automation, and sustainability expertise. To accelerate this transition, Cadence is actively supporting the future workforce in becoming fluent in simulation technologies, such as digital twins, which play a critical role in fostering a culture of innovation and sustainability. What’s more, Cadence offers diverse opportunities for students and recent graduates across all aspects of the business to ensure the company attracts individuals passionate about making a meaningful impact in the tech industry.

We invest in talent that shares our sense of purpose to do good for communities. This not only ensures that employees are technically prepared to tackle future sustainability challenges but are also passionate about doing so. Ultimately, by integrating leadership training with technical skill-building, Cadence future-proofs its workforce to make meaningful contributions, both within the company and across society.

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What's next for your specific team at Cadence?

The coming year holds exciting developments for the data center industry, particularly with the rapid experimentation of AI agents within data centers. Software providers like Cadence are at the forefront of this innovation, exploring large language models (LLMs), a type of AI designed to understand and generate human language. This includes how they can be implemented within digital twin technology.

Through Cadence’s own testing of advanced LLMs, it’s become clear that even relatively modest setups require substantial infrastructure for training and operations, with each model functioning as a “personal assistant” for operators. Then, for an AI assistant to be well informed, they need significant training to understand the questions asked and provide the correct answers. As such, for assistants to be quick in providing those answers, businesses will need low latency and high-speed compute running the show, something that can require vast amounts of energy.

Organisations will need to weigh the ROI of AI agents carefully. For example, at Cadence, integrating LLMs could enable data center digital twins to become personal assistants that provide on-the-spot insights for automating cooling and optimising energy efficiency, supercharging data centers to find sustainability improvements constantly. As such, this synergy between AI and digital twins has the potential to redefine data center operations, creating cost and energy efficiencies at a time of heightened environmental scrutiny. Ultimately, implementing LLMs across any platform will require strategic planning to ensure that their financial and environmental benefits outweigh the energy costs required to support them.


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