• • • SUPPLEMENT • • •
HOW CADENCE IS ENGINEERING THE FUTURE OF THE AI ERA
essential to advancing the next generation of intelligent systems.
Designing the BY ROD METCALFE,
SENIOR PRODUCT MANAGEMENT GROUP DIRECTOR,
CADENCE DESIGN SYSTEMS
$2 trillion by 2030. At the centre of this expansion is artificial
T
intelligence (AI), which is driving demand for more powerful chips, advanced memory, intelligent systems, and hyperscale data centres. Yet the industry’s biggest challenge is no longer
just performance. It is complex. Every new generation of AI hardware requires greater levels of integration, optimisation and engineering effort. As designs become more sophisticated, engineering teams cannot simply scale alongside them. The industry must find new ways to deliver dramatically higher productivity. Cadence is addressing this challenge through a
dual strategy: Design for AI and AI for Design. Together, these approaches create a powerful engineering cycle. As AI drives demand for increasingly advanced computing infrastructure, AI itself is being used to accelerate the design of that infrastructure. The result is a continuous loop of innovation where better technology enables better AI, and better AI helps create better technology. Cadence CEO Dr. Anirudh Devgan describes this
ecosystem as a three-layer cake. The foundation is accelerated computing hardware, including GPUs, CPUs and specialised silicon. Above it sits the layer of physics-based simulation, algorithms and mathematical solvers that provide engineering accuracy and scientific grounding. At the top are AI and agentic systems that increasingly automate complex tasks. Progress across all three layers is
he semiconductor industry is entering a period of unprecedented growth, with projections placing the market near
infrastructure for AI The AI boom has changed what semiconductor design means. Performance is no longer determined by a chip alone. Today’s AI systems depend on optimisation across chiplets, advanced packaging, networking, cooling, power delivery and entire data centre architectures. This shift has increased demand for
technologies such as 3D-IC design, photonics, multiphysics simulation and system-level analysis. Cadence supports these requirements through solutions including Integrity 3D-IC, Allegro X and Clarity 3D Solver, helping customers manage the growing complexity of heterogeneous system design. At the same time, energy efficiency has become
a critical engineering priority. As AI workloads expand, power consumption and thermal management increasingly determine system performance and operating costs. Digital twin technology and advanced simulation are, therefore, becoming essential tools for AI infrastructure design. Using platforms such as the Cadence Reality
Digital Twin Platform and Celsius Studio, engineers can model airflow, cooling behaviour, thermal performance and power distribution before deployment. This enables better-informed design decisions, reduced risk and more efficient operations. In one deployment, optimisation using Cadence’s digital twin technology improved tokens-per-watt performance by 17 per cent, highlighting the value of modelling and simulation in modern AI infrastructure.
Using AI to reinvent engineering While Cadence helps customers build AI systems, it is also transforming how those systems are designed.
40 ELECTRICAL ENGINEERING • JULY/AUGUST 2026 Traditional electronic design automation relies
heavily on deterministic algorithms and extensive manual iteration. However, systems containing billions, and increasingly trillions, of transistors are pushing conventional methodologies to their limits. Cadence is embedding AI directly into
engineering workflows through technologies such as Cerebrus AI Studio. Rather than relying solely on general-purpose AI models, these solutions use specialised machine learning techniques integrated within design tools to automate optimisation and accelerate design convergence. The result is faster development cycles and measurable improvements in power, performance and area (PPA). The next stage of this evolution is the
emergence of AI super agents. Moving beyond simple assistants, these systems combine natural language interaction, engineering expertise, deterministic workflows and deep tool integration to help deliver production-ready outcomes. Cadence is advancing this vision through
solutions such as ChipStack AI Super Agent, ViraStack AI Super Agent, InnoStack AI Super Agent and AuraStack AI Super Agent, all coordinated through the AgentStack platform. These technologies automate tasks across the design flow, from RTL generation and verification to analog design, implementation and signoff. Early deployments have demonstrated productivity gains of between three and ten times in analog workflows. As AI expands beyond digital applications into
physical and scientific domains, the connection between intelligent systems and intelligent engineering will only deepen. The future of semiconductors will not be defined solely by faster chips, but by how effectively computing, simulation and AI work together to create more autonomous and innovative technologies.
www.cadence.com
electricalengineeringmagazine.co.uk
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