Features four CPU cores capable of executing four hardware threads each (totaling 16 threads). These cores handle upper-level system tasks, application scheduling, interface buses, and general driving policy tracking. Vision and Deep Learning Accelerators
: Multi-threaded execution modules optimized to perform specific pipeline steps more efficiently than standard CPUs, while maintaining greater flexibility than rigid ASICs.
An autonomous driving system relies heavily on seamless data ingestion and communication with the vehicle's electronic control units (ECUs). The EyeQ4 offers a robust I/O subsystem. Sensor & Camera Ingestion eyeq4 datasheet
Capable of processing up to 8 cameras simultaneously at 36 frames per second (fps). Architectural Overview
Understanding the EyeQ4: Technical Overview, Specifications, and Architecture Features four CPU cores capable of executing four
Detailed hardware integration data for the EyeQ4-Mid and EyeQ4-High includes: Flip-Chip FBGA with 784 pins . Dimensions: 22.5 mm x 22.5 mm x 1.7 mm.
A: 8 MP per channel, but total pixel throughput is 400 MP/s aggregate. An autonomous driving system relies heavily on seamless
The datasheet mandates strict sequencing: VDD_IO must rise before VDD_CORE. Minimum reset low pulse width: 50 µs.
Operates robust pedestrian, animal, and cyclist classification layers to power autonomous emergency braking (AEB) maneuvers at complex intersections. 5. Architectural Comparison: EyeQ3 vs. EyeQ4 vs. EyeQ5