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Xilinx announces adaptive devices for autonomous driving

Xilinx has expanded its automotive-qualified 16 nanometer (nm) family with two new devices – the Xilinx Automotive (XA) Zynq UltraScale+ MPSoC 7EV and 11EG.

These two new parts deliver the high capacity, performance and I/O capabilities needed for high-speed, data aggregation, pre-processing, and distribution (DAPD). They also provide compute acceleration for L2+ to L4 advanced driver-assistance systems (ADAS) and autonomous driving (AD) applications.

With these new additions, Xilinx can help meet the safety, quality and reliability requirements for automotive, with a comprehensive line of products scaling from small devices powering edge sensors to new high-performance devices for centralised domain controllers.

“Through customer-driven requests, we’ve broadened our XA product family to meet the complex levels of today’s ADAS and autonomous driving systems,” commented Emre Onder, senior vice president, marketing, Xilinx. “With these additions to the Zynq UltraScale+ product line, Xilinx delivers unmatched processing flexibility and scalability vital for today’s rapidly changing requirements. Whether customers are developing for L1 or for L4 systems, we have a solution that meets their needs.”

The new XA Zynq UltraScale+ MPSoC 7EV and 11EG devices offer over 650,000 programmable logic cells – and nearly 3,000 DSP slices. In addition, the XA 7EV contains a video codec unit for h.264/h.265 encode and decode, while the XA 11EG includes 32 12.5Gb/s transceivers and provides four PCIe Gen3x16 blocks.

The addition of these high-performance devices to the XA portfolio enables carmakers, robotaxi developers, and Tier-1 suppliers to perform the DAPD and compute acceleration in a power envelope that allows for scalable production deployments for AD vehicles.

The company also today announced its new Vitis unified software platform and open source libraries are available for immediate download. The free resources aim to allow a broad range of developers – from software engineers to AI scientists – to work with Xilinx’s adaptable hardware.

Author
Charlotte Hathway

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