Xilinx AI Edge SoC platform offers highest AI performance-per-Watt

June 10, 2021 // By Jean-Pierre Joosting
Xilinx AI Edge platform offers highest AI performance-per-Watt
Versal AI Edge ACAP series delivers AI-enabled intelligence for automotive, robotics, healthcare, and aerospace applications.

Xilinx has introduced the Versal™ AI Edge series, designed to enable AI innovation from the edge to the endpoint. With 4X the AI performance-per-watt versus GPUs [1] and 10X greater compute density versus previous-generation adaptive SoCs, the Versal AI Edge series claims to be the most scalable and adaptable portfolio for next-generation distributed intelligent systems.

Versal AI Edge adaptive compute acceleration platforms (ACAPs) deliver intelligence to a wide 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.

AI-enabled automated systems require high compute density that can accelerate whole applications from sensor to AI to real-time control. Versal AI Edge devices achieve this by delivering 10X compute density versus Zynq® UltraScale+™ MPSoCs, enabling more intelligent autonomous systems. Additionally, Versal AI Edge devices support multiple safety standards across industrial (IEC 61508), avionics (DO-254/178), and automotive (ISO 26262) markets, where vendors can meet ASIL C random hardware integrity and ASIL D systematic integrity levels.


Vous êtes certain ?

Si vous désactivez les cookies, vous ne pouvez plus naviguer sur le site.

Vous allez être rediriger vers Google.