Wednesday, June 9, 2021

Xilinx debuts Versal AI Edge series processors

Xilinx introduced the Versal AI Edge series processors, boasting 4X the AI performance-per-watt versus GPUs and 10X greater compute density versus previous-generation adaptive SoCs.

Xilinx is positioning the new Versal AI Edge adaptive compute acceleration platforms (ACAPs) for a range of applications including: automated driving with the highest levels of functional safety, collaborative robotics, predictive factory and healthcare systems, and multi-mission payloads for the aerospace and defense markets. The portfolio features AI Engine-ML to deliver 4X machine learning compute compared to the previous AI Engine architecture and integrates new accelerator RAM with an enhanced memory hierarchy for evolving AI algorithms. These architectural innovations deliver up to 4X AI performance-per-watt versus GPUs and lower latency resulting in far more capable devices at the edge.

"Edge computing applications require an architecture that can evolve to address new requirements and scenarios with a blend of flexible compute processing within tight thermal and latency constraints,” said Sumit Shah, senior director, Product Management and Marketing at Xilinx. “The Versal AI Edge series delivers these key attributes for a wide range of applications requiring greater intelligence, making it a critical addition to the Versal portfolio with devices that scale from intelligent edge sensors to CPU accelerators.”

The Versal AI Edge series takes the production-proven 7nm Versal architecture and miniaturizes it for AI compute at low latency, all with power efficiency as low as six watts and safety and security measures required in edge applications. As a heterogeneous platform with diverse processors, the Versal AI Edge series matches the engine to the algorithm, with Scalar Engines for embedded compute, Adaptable Engines for sensor fusion and hardware adaptability, and Intelligent Engines for AI inference that scales up to 479 (INT4) TOPS2—unmatched by ASSPs and GPUs targeting edge applications—and for advanced signal processing workloads for vision, radar, LiDAR, and software defined radio.

Sampling is available to early access customers, with shipments expected during the first half of 2022.