Digital Twins

What Is a Digital Twin?

A digital twin is a virtual representation of a real-world entity or a system; in other words, a counterpart of a physical object or a process powered by technologies like machine learning (ML), the internet of things (IoT), and analytics. When developing expensive hardware or software, such as a data center, automobile, or airplane, a virtual model enables collaboration, simulation, and data acquisition for better iterative design. It helps you understand the system’s performance and behavior in a real-world scenario. The virtual replication gives you the answers to the “what if” methods without breaking the prototype.

One of the main advantages of a digital twin is that the physical system and its digital twin can co-exist, communicate, and use real-life data from the physical system to improve the simulation. Digital twins are used across industries in several ways. For example, healthcare utilizes this capability for clinical diagnoses, learning, and training. The automotive sector uses it to optimize the manufacturing value chain, supply chain, product innovation, and enhancements. And data center operators employ digital twins to enhance cooling and improve energy efficiency, reduce risk and cost, and optimize resource allocation and capacity.

Why Are Digital Twins Important?

Hardware-software partitioning in a parallel design cycle development environment accelerates design schedules. An integrated emulation and prototyping solution can maintain the design integrity that enables iterative and simultaneous verification, which can handle tasks of varied sizes and execution lengths, from smaller IP blocks to subsystems up to the SoC and system level. It is also essential to extend this verification effort across the enterprise to other designs being developed concurrently. When managing multiple SoC design projects, it is critical to have a platform that bridges the verification productivity gap to accelerate the verification of SoCs, subsystems, IP blocks, and system-level validation. And it is essential to take a holistic view of the parameters when evaluating emulation throughput.

Using a digital twin allows you to verify a chip as well as the software on that chip. The combined use of the Cadence Dynamic Duo of emulation and prototyping platforms enables you to transition quickly and effortlessly from debugging a chip on the emulation platform to debugging the software running on that chip with the prototyping platform. Digital twins play a crucial role in redefining the emulation architecture with microprocessor-based technology.

In the bustling world of data centers, efficiency, uptime, and cost-effectiveness are paramount. Digital twins offer unique benefits that revolutionize how these facilities are managed. Real-time monitoring is one of the most significant advantages. By creating a digital replica of a data center, operators can continuously track every component's status, from servers to cooling systems, ensuring optimal performance. Predictive maintenance is another critical benefit; machine learning algorithms analyze data trends to predict when equipment might fail, allowing for proactive repairs that minimize disruptions. Additionally, digital twins enable the optimization of resources. By simulating different configurations and operating conditions, data centers can find the most efficient ways to utilize energy, cooling, and space, thus reducing operational costs and environmental impact.

Digital twins represent a crucial tool for modern data center management, offering significant advantages in downtime prevention, predictive maintenance, and asset utilization. By simulating real-world conditions, digital twins empower operators to make informed decisions that enhance efficiency, sustainability, and performance.

Digital Twins for IC Design

On their own, Cadence’s Dynamic Duo of the Palladium and Protium platforms provide best-in-class emulation and FPGA prototyping; together, they unleash the true potential needed to develop products with digital twinning and differentiation. The Palladium platform has its core strength in SoC verification from custom IC and simulation bring-up to debug activity. The Protium platform has superior performance in fast pre-silicon software bring-up, software, and fast regression. Seamless transitions between the two engines are provided using Cadence flows and peripherals, including SpeedBridge adapters, accelerator verification IP (AVIP), and the memory model portfolio (MMP). With 2X capacity, rack improvements, and 1.5X performance, the Cadence Dynamic Duo 2.0 is the next generation of Palladium Z2 emulation and Protium X2 prototyping platforms to accelerate chip debug and pre-silicon software validation.

Digital Twins for System Design

Cadence Millennium Enterprise Multiphysics Platform is the industry’s first hardware/software accelerated digital twin solution for multiphysics system design and analysis. Designing mechanical systems for new levels of performance and efficiency has become a key priority in the automotive, aerospace and defense (A&D), energy, and turbomachinery industries. The first-generation Millennium M1 Supercomputer provides the required performance, accuracy, capacity, and accelerated computing that are essential to enabling digital twin simulations, providing confidence that the designs will function as intended before undertaking prototype development and testing.

Digital Twins for Data Center Design and Optimization

The Cadence Reality DC digital twin software uses AI, high-performance computing, and physics-based simulation to help data center operators visualize the entire data center, improving capacity, energy efficiency, and compliance. Using AI for model generation and simulation, it accurately predicts the external physical forces that impact data center operation, such as airflow, wind speeds, building obstructions on air intake, and complications from internal and external temperature changes.