Edge applications such as advanced driver-assistance systems (ADAS) and autonomous driving (AD) in next-generation cars are fueling the need for large amounts of sensor data from image, radar, and Lidar sensors to be captured and processed to make intelligent decisions in real time. AD platforms are still in their infancy with evolving architectures. These platforms are expected to have many different configurations (number of sensors, resolutions, and types of sensors) needing very flexible yet optimal architectures for edge use cases. Xilinx’s Versal® AI Core ACAP with extensible I/O flexibility supports many sensor interfaces and varied configurations, with a programmable network on chip (NoC) and scalable memory subsystems that enable efficient data movement around key functional blocks. AI Engines and Adaptable Engines accelerate convolutional neural network (CNN) processing overlays, and image sensor processing functions provide a flexible yet optimal solution for next-generation automotive needs.

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