Driving the Future of Mobility with Cadence

Back in November 2024 Cadence kicked-off a CadenceTECHTALK webinar series called “The Road Ahead: Navigating Trends and Tools in Automotive Design with Cadence”. In 10 webinars, Cadence experts discuss the rapidly evolving automotive landscape covering trends such as autonomous driving, software-defined vehicles, zonal architectures, high-performance computing chiplets, power module design, functional safety, and more.

Robert Schweiger, Group Director Automotive Solutions delivered the first webinar, “Exploring Emerging Trends and Innovative System Design with Cadence.” If you missed one of these webinars, you can watch the recording later on-demand by following this link.

So, what are the trends, disruptions, and challenges that the automotive industry is currently facing?

The automotive industry is undergoing a remarkable transformation as car manufacturers leverage the power of software and digital technologies. Trends such as autonomous vehicles, electric vehicles (EV), and software-defined vehicles (SDV) are reshaping the landscape with advancements in technologies such as 3D integrated circuits (3D-IC), silicon carbide (SiC), and 800-volt BEV architectures. The transition of vehicles from traditional mechanical machines to dynamic, software-defined entities is driving significant growth in the semiconductor industry. The automotive semiconductor market is projected to grow at an impressive CAGR of 11% to nearly $100 billion by 2029—and the SiC market alone expects a 24% increase.

These trends bring unique application-specific and automotive-specific challenges that manufacturers must address to stay competitive. Cadence, a leader in computational software, plays a pivotal role in this evolution by providing innovative tools, IP, and comprehensive solutions that accelerate design for OEMs, Tier 1 suppliers, and semiconductor companies. This blog explores the innovations shaping the automotive landscape, their challenges, and how Cadence’s comprehensive portfolio enables these innovations.

SDVs

Imagine a future where your vehicle evolves with you. You can keep your car for years, and when you desire that shiny new feature, there’s no need to buy a new one. Instead, you can get the latest features through a software update!

 Software-defined vehicles (SDVs) are making this a reality with personalized digital experiences, cloud connectivity, over-the-air updates (OTA), electrification, and autonomous capabilities. Unlike traditional vehicles reliant on hardware-based systems, SDVs leverage centralized computing and scalable architectures to enhance functionality. The centralized zonal architecture simplifies vehicle hardware by optimizing the number of ECUs from hundreds to just a few, leading to cost and space optimization. The primary appeal for OEMs adopting this architecture is the significant cost reduction achieved through extensive ECU and network consolidation. However, this transformation has many challenges, including the architecture overhaul, as it may trigger a chain reaction of significant updates in a car. Various requirements/challenges for SDV adoption are as follows:

• Update in-vehicle networking to get higher bandwidth (up to 10Gbit/s or more)
• Multiple sensors (camera, radar, lidar, etc.) and high-performance computing (for AI-related tasks)
• Advanced chiplet based Fusion system-on-chip (SoC) designs for integration of ADAS and infotainment SoCs
• Scalability and cost considerations
• Power, EMI, and thermal challenges
• Reliability, safety, and security requirements
• Creation of virtual platforms to enable early software development

EVs

The rise of electric vehicles (EVs) is driving demand for efficient power electronics, particularly silicon carbide (SiC) and gallium nitride (GaN) technologies. These power devices are critical for enabling 800V battery architectures, which improve efficiency and reduce charging times. However, the transition to EVs introduces many challenges, including:

• High-efficiency requirements
• Thermal management
• Stability and safety in lithium batteries
• Electromagnetic interference (EMI) from electric drivetrains
• Charging infrastructure
• Cost efficiency

ADAS and AI

Autonomous driving is one of the most transformative trends in the automotive industry. It requires massive computational power, advanced sensor integration, and AI-driven decision-making capabilities. Integrating advanced driver-assistance systems (ADAS), infotainment, and AI-driven functionalities demands highly complex SoCs, often built on different leading-edge process nodes. Other challenges include:

• Efficient compute and AI performance
• High-speed interfaces
• Heterogeneous integration
• Scalability
• Safety verification
• Thermal optimization and power management

Functional Safety and Security

As vehicles become more software-driven, ensuring functional safety and cybersecurity is paramount. Standards like ISO 26262 require rigorous verification and validation processes, including FMEDA in combination with fault injection, to ensure fail-safe or even fail-operational ADAS systems.

Cadence’s Solutions for the Evolving Automotive Landscape

Cadence is uniquely positioned for modern automotive design with comprehensive tools, IP, and solutions. To enable the development of SDVs, Cadence provides numerous tools and systems that address critical needs, such as zonal architectures and complex SoC designs. Cadence offers scalable computing solutions powered by AI engines and DSPs for ADAS and autonomous vehicles that cater to high-performance computing, sensors, and advanced SoC design. Cadence's scalable multicore AI platform with its Neo NPU represents the pinnacle of efficiency, specifically designed for high-performance computational tasks.

The scalable multicore DSP and AI platform leverages Cadence Tensilica Vision 4DR accelerator DSPs for ADAS (L1-L2++) applications and Cadence Janus Network on Chip (NoC) system IP for autonomous cars that can be scaled up to 100 TOPS for high-performance systems. It also features NeuroWeave SDK to support popular neural network frameworks such as  TensorFlow, Caffe, PYTORCH, etc. In addition, Cadence also provides a unified DSP platform with Tensilica 4DR accelerators for typical compute-intensive applications such as image analysis, blur detection video stream, etc. It avoids using different core types for different data types and offers area and power benefits.

Further, to keep up with the increasing modular chiplet design demands, the Cadence Integrity 3D-IC Platform unifies the design processes and the Allegro X Design Platform. Cadence UCIe IP and verification solutions ensure robust die-to-die communication. Cadence provides a broad interface IP portfolio to address the needs of next-generation SoC interconnects.

Cadence empowers developers with early software development platforms like Cadence Helium Virtual and Hybrid Studio, accelerating a design’s time to market. To enable system verification, Cadence provides an AI-driven verification platform, Verisium Manager. In addition, Cadence has a broad portfolio of VIP for protocols such as Ethernet TSN, MIPI, PCIe, and CAN that enable seamless verification of automotive interfaces.

As the automotive industry moves towards electrification, power electronics is crucial in developing energy-efficient vehicles and enhancing battery management, propulsion, and charging. Cadence, with a new power module flow that combines PCB layout, circuit simulation, packaging, and system analysis, including thermal, structural, and power integrity, is crucial in advancing vehicle technology and sustainability.

Ultimately, Cadence provides tools that allow package design for digital design RFIC design for SoCs that are monolithic or chiplet-based. Cadence offers a comprehensive system analysis tool suite with dedicated thermal, RF/EM solvers, signal integrity, power integrity, and computational fluid dynamics (CFD). Cadence's Optimality Intelligent System Explorer utilizes the results from these engines to optimize system-level designs. It helps address the design from the component to the board level and perform the 3D thermal analysis from chip to board to ECU.

The integrated FMEDA-driven safety solution allows the digital verification of the design safety system and helps derive chip hardware metrics. It also allows the USF-driven implementation of the chip and provides a link on the analog/mixed signals side to detect fault simulation.

In summary, Cadence provides solutions for software-defined vehicles, autonomous vehicles, electric vehicles, and functional safety.

Many customers have benefitted from adopting Tensilica DSPs; a few are below:

This blog is an excerpt from a webinar by Robert Schweiger from Cadence: View the webinar.

Learn More:

• ZuKIMo Project: Dream Chip and Cadence Demo Automotive SoC Featuring Tensilica AI IP at Embedded World 2024
• Revolution on the Road: How Cadence Is Driving the Future of Automotive Design!
• Cadence Sets the Gold Standard for UCIe Connectivity 
• Cadence Automotive Solutions
• Functional Safety