• Physical AI System Architecture
• Right-Sized AI Inference
• Trusted Execution and Lifecycle Security
• Monolithic and Chiplet-Based Design
• A Complete Path From Spec to Silicon to System

eBook Overview

Physical AI demands more than traditional edge silicon. Devices must perceive, reason, and act in real time while protecting data and scaling across product lines. This eBook shows how Cadence supports the path from concept to production while reducing the complexity and risk of silicon development.

What You Will Learn:

The eBook focuses on four key areas of Physical AI system design:

• • Right-Sized Inference for Physical AI. Scale from always-on, ultra-low-power inference to complex multimodal workloads with the Neo NPU, Neo MX subsystem, and NeuroWeave SDK.
  • Trusted Execution Across the Lifecycle. Protect data, models, firmware, and devices with hardware-anchored security spanning provisioning, deployment, updates, and end-of-life management.
  • Scale Through Standards-Based Modularity. Evaluate monolithic and chiplet-based architectures while using reusable, interoperable building blocks aligned with standards such as OCP FCSA and UCIe.
  • One Partner, From Spec to Silicon to System. Bring together Cadence IP, EDA, advanced packaging, software enablement, and silicon realization services to reduce integration risk and accelerate development.

Plus, apply a practical decision framework for right-sizing AI inference and determining when monolithic or chiplet-based architectures best fit your performance, power, cost, and scalability requirements.

Download the eBook to learn more!