The Kria K26 SOM is built on top of the Zynq® UltraScale+™ MPSoC architecture, which features a quad-core Arm® Cortex™ A53 processor, more than 250K logic cells, and a H.264/265 video codec. The SOM also features 4GB of DDR4 memory and 245 IOs that allow it to adapt to virtually any sensor or interface. This flexibility is one of the most compelling features of the Kria SOM.
Barber says the AI detection engine and other components running within an FPGA allows developers the option to adapt compute elements as needed. “If you have a very confined set of criteria, you can shrink that FPGA footprint down or grow it if you want more performance. Plus, it gives you the additional flexibility of tying it on to other peripherals like cameras.”
With 1.4 tera-ops of AI compute, the Kria K26 SOM enables developers to create vision AI applications offering more than 3X higher performance at lower latency and power compared to GPU-based SOMs, critical for smart vision applications including security cameras, city cameras, traffic cameras, retail analytics, machine vision, and vision guided robotics.
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