Automotive electronics revolution requires faster, smarter interfaces
By Raj Kumar Nagpal (Synopsys) and Edo Cohen (Valens)
In the automotive industry, features such as advanced driver-assistance systems (ADAS), connected in-vehicle infotainment (IVI) and emerging autonomous driving systems (ADS) are more important than ever, making vehicles safer and improving the driving experience. Yet they also are creating new requirements that are increasing complexity and making product development more expensive and time-consuming.
Automakers are facing pressure to include the latest capabilities while containing costs, minimizing power consumption and ensuring electronic systems are reliable, safe and secure for the life of the vehicle. Meeting these expectations requires new approaches to in-car connectivity, especially the physical-layer interfaces that link sensors and displays to their associated electronic control units (ECUs).
Let’s take a look at these trends, the demands they create and ways to meet those requirements.
To read the full article, click here
Related Semiconductor IP
- MIPI D-PHY and FPD-Link (LVDS) Combinational Transmitter for TSMC 22nm ULP
- MIPI SoundWire I3S Peripheral IP
- MIPI SoundWire I3S Manager IP
- MIPI SWI3S Manager Core IP
- MIPI I3C Target Device
Related Articles
- Deliver "Smarter" Faster: Design Methodology for AI/ML Processor Design
- FD-SOI: A Cyber-Resilient Substrate Against Laser Fault Injection—The Future Platform for Secure Automotive Electronics
- Revolutionizing Consumer Electronics with the power of AI Integration
- Soc Design -> Emulation verifies multiple network interfaces
Latest Articles
- PDF: PUF-based DNN Fingerprinting for Knowledge Distillation Traceability
- TeraPool: A Physical Design Aware, 1024 RISC-V Cores Shared-L1-Memory Scaled-up Cluster Design with High Bandwidth Main Memory Link
- AutoGNN: End-to-End Hardware-Driven Graph Preprocessing for Enhanced GNN Performance
- LUTstructions: Self-loading FPGA-based Reconfigurable Instructions
- CQ-CiM: Hardware-Aware Embedding Shaping for Robust CiM-Based Retrieval