Eyeq4 Datasheet

The Mobileye EyeQ4 is a high-performance vision system-on-chip (SoC) designed for Advanced Driver Assistance Systems (ADAS) and semi-autonomous driving. It provides approximately 2.5 teraflops of processing power while maintaining a low-power automotive-grade envelope of roughly 3W. Technical Specifications Summary

The EyeQ4 architecture is based on a heterogeneous computing model that assigns specific tasks to specialized cores for maximum efficiency. Feature Specification Details Processor Cores

4x multi-threaded 64-bit RISC MIPS CPUs (4 hardware threads each) Vision Accelerators

6x Vector Microcode Processors (VMP), 2x Multithreaded Processing Clusters (MPC), 2x Programmable Macro Arrays (PMA) Compute Power >2.5 Teraflops (or 2.5 TOPS depending on variant) Power Consumption ~3 Watts (up to 5W in some high-load configurations) Process Node

28nm Fully Depleted Silicon On Insulator (FD-SOI) by STMicroelectronics Camera Support Up to 8 cameras simultaneously at 36 FPS Safety Standard ISO 26262 compliant with ASIL-B(D) safety level Packaging Flip-Chip FBGA 784-pin; 22.5 x 22.5 x 1.7 mm EyeQ4 Variant Differences

Mobileye developed multiple versions of the chip to support different vehicle capabilities: EyeQ4-High (EyeQ4H)

: The most capable version, supporting trifocal front-sensing, surround-view systems (4 cameras), and sensor fusion with radar and laser scanners. EyeQ4-Medium (EyeQ4M)

: A cost-optimized variant with a subset of cores, typically used for monocular or trifocal camera configurations in standard ADAS applications. Key Interfaces and Connectivity eyeq4 datasheet

According to the EyeQ4 Product Brief, the chip includes the following I/O: Memory: Dual 32-bit LPDDR4 SDRAM interfaces at 1.6GHz. Network: 1Gb Ethernet port.

Video Input: 4x MIPI CSI-2 Rx serial video ports and 1x parallel video port.

Automotive Buses: 3x CAN ports (>1Mbps), 3x UART, 3x I2C, and 4x SPI interfaces. Documentation and Resources Mobileye EyeQ4 Vision Processor Family - Yole Group

Inside the EyeQ4: The "Supercomputer" Driving Your Next Car Mobileye EyeQ4

isn't just another chip; it's the silicon brain that moved Advanced Driver Assistance Systems (ADAS) from simple warnings to near-autonomous "safety cocoons". Launched in 2018, this System-on-Chip (SoC) provides a staggering 10x more processing power

than its predecessor, the EyeQ3, while keeping power consumption remarkably low.

Here is a deep dive into the technical specifications and capabilities that make the a landmark in automotive technology. Technical Specifications: The Power of Efficiency is manufactured using 28nm Fully Depleted Silicon On Insulator (FD-SOI) technology by STMicroelectronics Key Features

. This specialized manufacturing process is what allows it to deliver "super-computer" performance within a tiny power envelope. Computational Performance: 2.5 Teraflops (trillions of operations per second). Power Consumption: Approximately , which is less than many standard mobile phone processors. Architecture: A heterogeneous mix of cores designed for specific tasks: Four multi-threaded MIPS cores. VMP (Vector Microcode Processors):

Six cores for image processing and integral types used in computer vision. MPC (Multi-threaded Processing Cluster):

Two cores more versatile than GPUs and more efficient than CPUs. PMA (Programmable Macro Array):

Two cores providing high compute density for dense computer vision algorithms. Supports dual 1.6GHz, 32-bit LPDDR4 SDRAM interfaces. Connectivity:

Includes a 1Gb Ethernet port, multiple CAN ports (>1Mbps), UART, and I2C interfaces. Safety Rating: Designed according to ISO-26262 to provide safety levels. Advanced ADAS Capabilities What does all that silicon power actually do? The is designed to process information from up to eight cameras simultaneously

at 36 frames per second. This allows it to support sophisticated features that were previously impossible for a single chip: ZF and Mobileye Safety Technology Chosen by Toyota

Key Features

Performance: Offers high processing capabilities for handling the complex computations required for tasks like object detection, depth estimation, and motion forecasting. such as detection
Power Efficiency: Designed to be power-efficient, which is crucial for automotive applications where energy consumption and heat dissipation are critical considerations.
Vision Processing: Optimized for computer vision tasks, with support for a wide range of algorithms used in ADAS and autonomous driving, such as detection, tracking, and scene understanding.
Memory and Interface: Supports various interfaces for connecting to sensors (cameras, radar, lidar), and other components of the vehicle's system. It also includes support for high-bandwidth memory to handle the data-intensive tasks.

Design Considerations for Engineers

If you are downloading the EYEQ4 datasheet for a new project, keep these practical engineering factors in mind:

Technical Specifications Summary

For engineers reading an eyeq4 datasheet, the following electrical and physical parameters are critical: